Category: Knowledge

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Keris Malela Tulang Belud: Karya Seni Pusaka Warisan Melayu

Oleh Shahabuddin Amerudin

Keris, senjata tradisional yang sangat istimewa dalam kebudayaan Melayu, telah menjadi bahagian tak terpisahkan dari sejarah dan budaya Melayu selama berabad-abad. Salah satu jenis keris yang amat dihargai dan penuh dengan keunikan adalah Keris Malela Tulang Belud. Keris ini mempunyai ciri-ciri yang memukau dan kecantikan yang menjadikannya sebagai salah satu karya seni yang amat dihargai dalam warisan budaya Melayu. Artikel ini akan mengulas dengan terperinci tentang Keris Malela Tulang Belud, dengan memberi tumpuan kepada beberapa elemen penting yang menjadikannya begitu istimewa.

1. Bilah Malela Tulang Belud Luk 5

Bilah keris Malela Tulang Belud ini mempunyai kepanjangan sekitar 10 inci, menjadikannya sebagai ukuran yang sesuai untuk pelbagai kegunaan. Panjang yang sederhana ini membolehkan keris ini berfungsi dengan baik sebagai senjata tajam dan juga sebagai objek seni yang cantik. Keris luk 5 adalah istilah yang merujuk pada jumlah lengkung atau goresan pada bagian bilah keris. Luk-luk ini mengacu pada bentuk dan jumlah alur-alur yang terukir pada bilah keris. Dalam hal ini, setiap luk pada keris mewakili salah satu dari lima rukun Islam.

2. Ukiran Sampir Kusriwa yang Anggun

Salah satu ciri yang membezakan Keris Malela Tulang Belud adalah sampir kusriwa yang diukir dengan indah. Sampir adalah hiasan pelindung yang terletak di bahagian atas sarung keris. Ukiran yang rumit dan halus pada sampir ini mencerminkan tahap kepandaian yang tinggi dari pembuat keris. Motif-motif ukiran pada sampir seringkali menggambarkan unsur-unsur alam, mitologi, atau bentuk seni yang berbeza, menambah nilai estetika pada senjata ini.

3. Hulu Pekaka yang Menarik

Hulu pekaka adalah bahagian pegangan keris yang terdapat pada hujung sarung. Keris Malela Tulang Belud mempunyai hulu pekaka yang direka dengan penuh perhatian terhadap butiran. Hulu ini sering kali diperbuat daripada bahan-bahan berharga dan dihiasi dengan hiasan atau ukiran yang menawan. Selain berfungsi sebagai pegangan, hulu pekaka juga merupakan elemen dekoratif yang memperkukuh keindahan keris ini.

4. Pemanis Tanduk Kerbau

Tanduk kerbau adalah bahan yang sering digunakan untuk membuat bahagian pegangan keris. Keunikan Keris Malela Tulang Belud terletak pada pemilihan tanduk kerbau berkualiti tinggi. Tanduk ini diolah dengan teliti sehingga memberikan penampilan yang indah dan tahan lama. Pemanis tanduk kerbau ini boleh berbentuk hiasan atau ukiran, menambah unsur estetika pada keris ini.

Keris Malela Tulang Belud adalah bukti nyata akan seni dan kemahiran tinggi para pandai keris Melayu. Setiap unsur dalam pembuatan keris ini menunjukkan perhatian terhadap butiran dan usaha untuk mencipta karya seni yang luar biasa. Selain sebagai senjata tradisional, keris ini juga menjadi simbol budaya dan identiti Melayu.

Keris Malela Tulang Belud adalah satu contoh gemilang dari warisan budaya Melayu yang patut dijaga dan diwarisi. Kemahiran para pandai keris yang mewarisi tradisi ini perlu dihargai, dan peranan keris dalam budaya Melayu perlu diteruskan agar kekal hidup dan berkembang. Keris bukan sekadar senjata, tetapi juga merupakan warisan budaya yang berharga yang mencerminkan keindahan dan kekayaan sejarah Melayu.

Suggestion for Citation:
Amerudin, S. (2023). Keris Malela Tulang Belud: Karya Seni Pusaka Warisan Melayu. [Online] Available at: https://people.utm.my/shahabuddin/?p=7253 (Accessed: 10 October 2023).
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Hakikat Mati Sebelum Mati

Kesufian adalah sebuah aliran kerohanian yang mendalam, penuh dengan makna-makna tersembunyi dan pemahaman mendalam tentang hubungan manusia dengan Tuhan. Dalam aliran ini, ada satu konsep yang sangat penting yang dikenal sebagai “mati sebelum mati.” Istilah ini merujuk pada perubahan batiniah yang sangat dalam yang dialami oleh seorang Sufi dalam perjalanan kerohanian mereka.

Mati sebelum mati bukanlah kematian jasad, tetapi lebih merupakan proses perubahan dalam pemikiran dan perasaan. Ini adalah pemahaman bahawa hidup kita di dunia ini hanyalah sementara, dan yang sejati adalah keberadaan roh kita yang abadi. Dalam konteks ini, mati sebelum mati adalah proses mengalahkan ego, mengendalikan hawa nafsu, dan mengalami pemahaman yang mendalam tentang Tuhan yakni Allah.

Dalam perjalanan ini, kesadaran akan keberadaan diri yang lebih tinggi adalah kunci. Ini melibatkan mengatasi ego, mengendalikan nafsu amarah, dan mengabaikan kepentingan diri sendiri demi kepentingan Ilahi. Ini bukanlah tugas yang mudah, dan seringkali berkomitmen untuk menjalani latihan rohani yang ketat, termasuk bersembahyang, berpuasa, dan berzikir secara terus-menerus.

Salah satu aspek penting dari hakikat mati sebelum mati adalah pemahaman bahawa Allah adalah satu-satunya yang benar-benar ada. Ini adalah pengalaman yang mendalam di mana seseorang merasakan keberadaan diri mereka sendiri hampir menghilang, digantikan oleh kesedaran akan Allah yang Maha Esa. Dalam kata lain, individu tersebut berusaha untuk menjadi seperti cermin bagi Allah, mencerminkan kebesaran-Nya.

Seseorang yang mencapai tingkat pemahaman ini sering disebut sebagai “Wali Allah.” Mereka adalah orang-orang yang telah mencapai makrifat, yaitu pengenalan yang mendalam akan Tuhan. Mereka adalah hamba Allah yang sejati, yang hidup dalam kesedaran akan Allah dalam setiap aspek kehidupan mereka.

Seseorang yang telah mencapai tingkat ini memiliki doa yang sangat kuat yang dikabulkan oleh Tuhan. Mereka adalah khalifah Allah di dunia ini, menjalankan tugas-tugas Ilahi di bumi. Mereka adalah manifestasi ayat-ayat Allah yang hidup di antara manusia.

Namun, penting untuk diingatkan bahwa untuk mencapai tingkat kesedaran ini bukanlah tugas yang mudah. Ini memerlukan komitmen yang mendalam, latihan rohani yang terus-menerus, dan bimbingan dari seorang Guru yang berpengalaman. Proses mati sebelum mati adalah perjalanan panjang dan penuh cabaran yang memerlukan ketekunan dan kesabaran.

Dalam hakikat ini, mati sebelum mati adalah pintu menuju pemahaman yang mendalam tentang Allah dan pengalaman kerohanian yang luar biasa. Ini adalah proses yang melibatkan perubahan batiniah yang mendalam, yang akhirnya membawa individu lebih dekat kepada Allah. Sebagai manusia, kita dapat belajar banyak dari ajaran dan pengalaman ini, dan mungkin saja menemukan jalan menuju pemahaman kerohanian yang lebih dalam dalam hidup kita.

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Peta Bangunan | Building Map | FABU UTM

Oleh Shahabuddin Amerudin

Pada 1 Julai 2018, Universiti Teknologi Malaysia (UTM) melihat pencapaian sejarah baru dengan penggabungan dua fakulti yang berprestij, iaitu Fakulti Alam Bina (FAB) dan Fakulti Geoinformasi dan Harta Tanah (FGHT) dalam rangkaian SINERGY UTM. Gabungan ini membentuk Fakulti Alam Bina dan Ukur (FABU), yang bertujuan untuk meningkatkan sinergi dalam bidang utama seperti senibina, perancangan, geomatik, geoinformatik dan harta tanah.

Bangunan Fakulti Alam Bina dan Ukur (FABU) menjadi landasan penting bagi pembangunan ilmu, penyelidikan, dan pembelajaran di universiti ini. FABU mengintegrasikan aset-aset utama dari kedua fakulti yang digabungkan, dan bangunan-bangunan yang menjadi sebahagian daripada fakulti ini memainkan peranan penting dalam memberikan peluang pendidikan dan penyelidikan berkualiti kepada pelajar dan staf akademik UTM.

Fakulti Geoinformasi dan Harta Tanah (FGHT) sebelumnya memiliki sejumlah bangunan utama, antaranya adalah Blok C02, C03, C04, C05, C06, dan B08. Bangunan ini telah berperanan sebagai tempat pembelajaran, penyelidikan, dan pentadbiran bagi fakulti ini. Blok C02 dan seangkatan dengannya menjadi pusat aktiviti akademik, dengan dewan kuliah, bilik makmal, dan ruang-ruang pengajaran yang moden.

Di samping itu, Fakulti Alam Bina (FAB) juga memberikan sumbangan yang signifikan terhadap landskap bangunan FABU. Blok-blok seperti B02, B03, B04, B05, B06, B07, B08, B09, B11, dan B12, semuanya menjadi tempat penyelidikan perancangan dan senibina yang super canggih. Bangunan-bangunan ini adalah lokasi di mana para pelajar menjalani kuliah, melaksanakan eksperimen makmal, dan melibatkan diri dalam aktiviti senibina kreatif dan fantastik.

Sebagai pusat pendidikan tinggi yang berprestij, FABU juga memastikan bahawa bangunan-bangunannya mempunyai pelbagai kemudahan dan utiliti yang berkualiti. Di antara ruang-ruang yang terdapat dalam bangunan ini termasuklah dewan kuliah moden, bilik makmal dengan peralatan termoden dan terkini, bengkel-bengkel yang dilengkapi dengan peralatan senibina, studio senibina yang hidup 24 jam sehari, bilik seminar untuk perbincangan akademik, bilik pelbagai guna yang mandiri, pejabat pentadbiran yang mesra-pelanggan, perpustakaan yang dipenuhi dengan sumber ilmu, serta dewan konvensyen yang sesuai untuk program-program besar dan acara-acara kampus.

FABU dengan pelbagai bangunannya yang berinovasi memainkan peranan penting dalam mendukung misi universiti dalam penyampaian pendidikan, penyelidikan, dan khidmat kepada masyarakat. Dengan gabungan FAB dan FGHT di bawah satu payung FABU, universiti ini terus menjadi pusat keunggulan dalam bidang senibina, perancangan, geomatik, geoinformatik dan harta tanah, dan bangunan-bangunan ini menjadi tempat yang mencerminkan semangat pencapaian dan penyelidikan berkualiti di dalam SINERGY UTM.

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Applying Bloom’s Taxonomy to Geoinformatics Education

By Shahabuddin Amerudin

Abstract

This article explores the practical application of Bloom’s Taxonomy within the field of Geoinformatics, offering detailed examples at various proficiency levels within each of its three domains: Cognitive, Affective, and Psychomotor. Bloom’s Taxonomy, initially developed in the 1950s by Benjamin Bloom and colleagues, classifies educational objectives into these domains, providing a structured approach to designing curricula, assessing student progress, and cultivating comprehensive learning experiences. In Geoinformatics, where spatial data is of paramount importance, integrating Bloom’s Taxonomy into education equips educators with a powerful tool to tailor their teaching methods and shape well-rounded geospatial professionals. This article highlights the significance of Bloom’s Taxonomy as a blueprint for holistic and effective learning, emphasizing its role in fostering ethical awareness and practical expertise within this ever-evolving field.

Introduction

In the ever-evolving realm of Geoinformatics, where spatial data’s significance is indisputable, the demand for effective educational strategies is paramount. One such strategy, Bloom’s Taxonomy, a hierarchical framework initially devised by Benjamin Bloom and his colleagues in the 1950s, has emerged as a cornerstone in the evolution of contemporary educational practices. This taxonomy meticulously classifies educational objectives into three distinct domains: Cognitive, Affective, and Psychomotor, each with its array of learning proficiency levels. Acquiring a profound comprehension of Bloom’s Taxonomy equips educators with a formidable instrument for curriculum design, student assessment, and the cultivation of comprehensive learning experiences.

The Three Domains of Bloom’s Taxonomy

1. Cognitive Domain: “Think”

The Cognitive domain pertains to intellectual capabilities and encompasses a wide range of thinking skills. It provides a structured approach to developing students’ thinking abilities, from basic knowledge recall to advanced critical thinking. The levels within this domain include:

C1: Recall Data

At the foundational level, students are expected to remember factual information, such as dates, names, and definitions.

Example: Recall the latitude and longitude coordinates of major world capitals.

Significance: Foundational knowledge is essential in Geoinformatics, where location data serves as the backbone of spatial analysis.

C2: Understand

Moving beyond rote memorization, this level requires students to comprehend concepts, principles, and ideas. They should be able to explain and interpret the information.

Example: Explain the concept of spatial data and how it differs from non-spatial data.

Significance: Understanding the fundamental principles is crucial for effective data handling and interpretation.

C3: Apply

At this stage, learners are encouraged to put their knowledge into practice by using it in various situations. They demonstrate their ability to apply learned concepts to real-world problems.

Example: Use GIS software to overlay population data with land use data to identify areas with potential urban expansion.

Significance: Applying knowledge to real-world scenarios fosters practical skills for geospatial analysis.

C4: Analyze

Analytical thinking comes into play here as students break down information into its component parts. They identify patterns, relationships, and structures within the material.

Example: Analyze a topographic map to identify watersheds and determine the flow direction of rivers.

Significance: Analytical thinking is vital for interpreting complex spatial relationships.

C5: Synthesize

Synthesis involves creating something new by combining elements from different sources. Learners at this level integrate knowledge to form new concepts or solutions.

Example: Create a custom web mapping application that integrates data from multiple sources, allowing users to explore environmental factors affecting a specific area.

Significance: Synthesizing data facilitates the creation of advanced tools for spatial decision-making.

C6: Evaluate

The highest level in the Cognitive domain calls for critical evaluation and judgment. Students assess information, make informed decisions, and compare ideas based on set criteria.

Example: Evaluate the suitability of different projection systems for a specific cartographic project, considering factors like distortion and scale.

Significance: Evaluation skills ensure accurate and meaningful representation of spatial data.

2. Affective Domain: “Feel”

The Affective domain addresses emotions, feelings, attitudes, and behaviors. It recognizes that learning is not solely an intellectual endeavor but also a matter of the heart. The levels within this domain include:

A1: Receive (Awareness)

At the initial level, learners become aware of information or stimuli and show openness to receiving it.

Example: Become aware of the ethical considerations and potential privacy issues associated with the collection and use of geospatial data.

Significance: Awareness of ethical dilemmas promotes responsible data handling.

A2: Respond (React)

Responding involves reacting to stimuli with a chosen emotion, attitude, or behavior. It signifies a more active engagement with the information.

Example: Express enthusiasm for the potential of Geoinformatics in disaster management and the ability to save lives through accurate spatial data analysis.

Significance: Positive responses encourage engagement and innovation in the field.

A3: Value (Understand and Act)

At this level, students not only understand but also attach value to the information. They begin to prioritize certain attitudes and behaviors over others.

Example: Recognize the importance of open data policies in Geoinformatics and actively support initiatives that promote data transparency.

Significance: Valuing ethical principles drives advocacy and participation in ethical practices.

A4: Organize Personal Value System

Learners start organizing their values and beliefs into a coherent system, aligning their actions with their chosen values.

Example: Integrate the principles of sustainability and environmental stewardship into personal and professional practices within the Geoinformatics field.

Significance: Organizing values aligns individual behavior with broader societal and environmental goals.

A5: Internalize Value System (Adopt Behavior)

The highest level in the Affective domain represents a deep and lasting change in behavior. Students internalize their values, and these values guide their actions and decisions.

Example: Demonstrate consistent ethical behavior by refusing to participate in projects that misuse or misrepresent geospatial data.

Significance: Internalized values guide ethical decision-making in complex situations.

3. Psychomotor Domain: “Do”

The Psychomotor domain focuses on physical and manual skills. It recognizes that learning involves not only thinking and feeling but also doing. The levels within this domain include:

P1: Imitation (Copy)

At the basic level, learners imitate and replicate actions demonstrated to them.

Example: Copy the process of digitizing a paper map into a digital format using a GIS software package.

Significance: Imitation lays the groundwork for mastering practical skills in geospatial data handling.

P2: Manipulation (Follow Instructions)

This level involves following specific instructions to perform tasks or skills accurately.

Example: Follow instructions to create a map overlay that displays weather data on a GIS map in real-time.

Significance: Manipulation skills allow for the accurate execution of specific geospatial tasks.

P3: Develop Precision

As learners progress, they refine their skills to achieve a higher level of precision and accuracy.

Example: Develop precision in using GPS equipment to collect high-accuracy location data for geospatial research.

Significance: Precision ensures the reliability of geospatial data in research and decision-making.

P4: Articulation (Combine, Integrate Related Skills)

Articulation requires the integration of various related skills to accomplish complex tasks effectively.

Example: Combine skills in remote sensing, GIS, and statistical analysis to perform land cover change detection over time.

Significance: Articulation leads to the development of advanced capabilities for complex geospatial analyses.

P5: Naturalization (Automate, Become Expert)

The pinnacle of the Psychomotor domain signifies the mastery of a skill, where it becomes almost second nature, allowing for expert-level performance.

Example: Automate geoprocessing tasks using Python scripting to streamline data analysis workflows.

Significance: Naturalization signifies expertise, where geospatial tasks become almost second nature.

Conclusion

In conclusion, Bloom’s Taxonomy offers educators in the field of Geoinformatics a powerful and versatile framework for designing curricula and assessing student progress. By incorporating the Cognitive, Affective, and Psychomotor domains, educators can nurture individuals who possess a multifaceted skill set. This approach empowers students to think critically, articulate their values, and master practical skills essential for spatial analysis. The enduring relevance of Bloom’s Taxonomy in education underscores its significance as a blueprint for holistic and effective learning, equipping Geoinformatics professionals to excel in a complex and ever-evolving field while ensuring a strong foundation in ethics and practical expertise.

Suggestion for Citation:
Amerudin, S. (2023). Applying Bloom's Taxonomy to Geoinformatics Education. [Online] Available at: https://people.utm.my/shahabuddin/?p=7212 (Accessed: 27 September 2023).
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Revolutionizing Geospatial Data Analysis Through Generative AI

Introduction

In recent years, Generative Artificial Intelligence (AI) has emerged as a revolutionary force in various industries, transforming the way data is analyzed, interpreted, and leveraged for actionable insights. Nowhere is this transformation more evident than in the realm of geospatial data analysis. The integration of Generative AI into the analysis of sensor and machine datasets has ushered in a new era of efficiency, accuracy, and innovation. This article explores the groundbreaking role of Generative AI in geospatial analytics and its ability to simplify complex tasks while exponentially increasing productivity.

Generative AI Unleashes the Power of Geospatial Data

Geospatial data analysis has always presented a unique set of challenges due to the inherent complexity of spatial relationships and the vastness of the datasets involved. Traditionally, analysts have relied on specialized software and manual coding to process and interpret these datasets, a process that is often time-consuming and error-prone. Generative AI, however, is changing the game by providing advanced capabilities that simplify the authoring of sophisticated geospatial algorithms against massive datasets.

One of the most remarkable advancements in this field is the ability of Large Language Models (LLMs) to understand and execute complex geo-joins, ST_Geometry functions, and geo-graph solvers by simply expressing the question in plain English. This means that analysts no longer need to be experts in geospatial software or programming languages to perform intricate geospatial analyses. They can now communicate their requirements in natural language, and Generative AI takes care of the rest, executing the tasks within seconds.

The Efficiency and Productivity Revolution

The integration of Generative AI into geospatial data analysis has had a profound impact on efficiency and productivity. Here’s how:

  1. Rapid Analysis: Generative AI can process vast amounts of geospatial data at lightning speed. This enables analysts to conduct analyses that would have previously taken weeks or months in a matter of hours or even minutes. As a result, decision-makers can access critical information more quickly, allowing for faster responses to evolving situations.
  2. Error Reduction: Human errors are a common pitfall in geospatial analysis, especially when dealing with complex coding and software. Generative AI significantly reduces the risk of errors by automating the analysis process and ensuring consistency in results. This leads to more accurate and reliable insights.
  3. Accessibility: The democratization of geospatial analysis is another significant advantage of Generative AI. Analysts with varying levels of technical expertise can now harness the power of geospatial data without extensive training. This accessibility expands the pool of potential users and promotes innovation across diverse fields.
  4. Scalability: Generative AI systems can easily scale to handle larger datasets and more complex analyses. This scalability is essential for organizations dealing with ever-expanding data volumes, ensuring that geospatial analysis remains effective even as data grows.

Unlocking Profound Insights

Generative AI doesn’t just simplify geospatial analysis; it also unlocks profound insights that were previously hidden within the data. By automating the analysis process, Generative AI can uncover intricate patterns, correlations, and trends that might be missed by human analysts working with limited resources and time constraints.

Furthermore, the ability to express analysis requirements in natural language allows analysts to explore “what-if” scenarios easily. They can experiment with different questions and hypotheses, gaining a deeper understanding of geospatial data and its implications.

Applications Across Industries

The impact of Generative AI in geospatial analysis extends across various industries:

  1. Environmental Monitoring: Generative AI helps monitor environmental changes, track deforestation, analyze climate patterns, and assess the impact of pollution. This is invaluable for conservation efforts and sustainable resource management.
  2. Urban Planning: City planners can use Generative AI to optimize transportation routes, plan infrastructure projects, and make data-driven decisions for urban development and expansion.
  3. Disaster Response: Rapid analysis of geospatial data is crucial during natural disasters. Generative AI can assist in predicting disaster impacts, coordinating relief efforts, and assessing damage quickly.
  4. Agriculture: Farmers can benefit from geospatial analysis for precision agriculture. Generative AI can provide insights into crop health, soil conditions, and optimal planting times.

Conclusion

Generative AI is revolutionizing geospatial data analysis by simplifying complex tasks, increasing efficiency, and unlocking profound insights. The ability to express analysis requirements in natural language and have them executed within seconds is a game-changer for analysts across industries. As Generative AI continues to evolve, its role in geospatial analytics will become even more critical, reshaping how we harness the power of spatial data to address pressing global challenges and drive innovation. Analysts who embrace this technology are poised to be 10 times more productive and make significant strides in their respective fields, while those who do not may find themselves falling behind in this rapidly advancing landscape.

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Evolution and Sustainability of Free and Open Source Software (FOSS) Development in Geospatial Applications

By Shahabuddin Amerudin

Abstract

This article explores the evolution and sustainability of Free and Open Source Software (FOSS) development in the realm of geospatial applications. Drawing from the seminal work of Arnulf Christl published in 2008 in “Open Source Approaches in Spatial Data Handling,” this paper provides an updated perspective on the state of FOSS development in the geospatial domain. It delves into the changing nature of FOSS development, the challenges of funding, the role of transparency, and the benefits of collaborative, open-source approaches. Throughout, it references and builds upon the insights offered by Christl while providing contemporary examples and case studies to illustrate the ongoing developments in this field.

Introduction

Arnulf Christl’s work in 2008 provided a foundational understanding of Free and Open Source Software (FOSS) development in the geospatial domain. Since then, the field has undergone significant transformations, which this article explores. In doing so, we delve into the changing nature of FOSS development, the persistent challenge of funding, the importance of transparency, and the enduring benefits of collaborative, open-source approaches.

The Changing Nature of FOSS Development

Christl’s characterization of FOSS development as a grassroots movement remains accurate to some extent. However, the landscape has evolved significantly. FOSS projects today encompass a vast spectrum of development methodologies, programming languages, and solution types (Smith et al., 2020). This expansion reflects the dynamic and adaptive nature of the FOSS ecosystem, accommodating a diverse range of geospatial needs.

Monetizing FOSS: A Complex Endeavor

One of the perennial challenges in FOSS development is the quest for sustainable funding. Despite the growing significance of geospatial applications, monetizing FOSS remains intricate. Geospatial software often caters to niche markets, and formidable competition from large corporations can pose significant hurdles to sustainability (Ghosh, 2017). Nevertheless, FOSS development perseveres, driven by its intrinsic value and commitment to openness.

The Rise of Spatial Commodities

The rapid adoption of scalable spatial applications by large internet companies has had a dual effect on the geospatial FOSS landscape. On one hand, it has limited opportunities for new software development. On the other, it has fostered a thriving secondary market of innovative application mashups (Jones et al., 2021). This phenomenon underscores the adaptability and resilience of FOSS in responding to evolving market demands, further cementing its relevance.

Evolution of Development Methodologies

As FOSS projects gain acceptance in professional contexts, they undergo a process of maturation that leads to the professionalization of development methodologies. The evolution of software is driven by the need for sustainability and continuous innovation (Li and Murray-Rust, 2019). This shift reflects the community’s commitment to delivering robust and reliable solutions.

Sustainable FOSS Development

Sustainability remains a pressing concern for FOSS projects, particularly those with complex architectures and numerous dependencies. Ensuring funding for these projects necessitates robust organization and efficient coordination (Johnson et al., 2022). FOSS projects often depend on the dedication of volunteers, making effective resource management a critical factor in their long-term viability.

Funding Generic Code

Developing generic code that serves diverse purposes remains a funding challenge. Often, cross-financing from less visible features is the lifeblood of these initiatives (Wang et al., 2020). Transparency and clear communication with stakeholders are essential to secure the necessary funding. This highlights the importance of articulating the long-term benefits of generic software solutions.

Transparency and Long-term Benefits

Transparent communication regarding the necessity and long-term advantages of generic software development plays a pivotal role in securing funding. Effective project-level organization and the presence of independent contact points have emerged as critical factors in this process (Brown and Smith, 2018). Transparency builds trust and demonstrates the commitment of FOSS projects to their stakeholders.

The Role of Independent Contact Points

Independent contact points, whether individuals or professionals offering support contracts, play a vital role in facilitating funding for FOSS development. Their engagement, whether within or outside the core development group, contributes significantly to project sustainability (Gupta and Sharma, 2019). These individuals act as bridges between the development community and those willing to invest in FOSS projects, ensuring the continuity of essential geospatial tools.

FOSS Accessibility

One of the hallmarks of FOSS is its accessibility and inclusivity, which empower a diverse range of contributors. This open collaboration fosters a wealth of perspectives and rigorous peer review, ultimately enhancing the quality, resilience, and robustness of geospatial software (Chen and Liu, 2021). The strength of FOSS lies in its community-driven development, which benefits users and developers alike.

Licensing and Collaboration

FOSS licenses and development contracts often require implementers to share enhancements with the broader community. This collaborative ethos benefits not only developers but also end-users, who enjoy a continuously improving product (Dutta and Choudhury, 2020). The ethos of sharing and collaboration ensures that geospatial FOSS projects remain relevant and adaptive to evolving needs.

The Pitfall of Short-Term Solutions


In summary, although the allure of short-term, cost-effective solutions may be strong, the lasting benefits provided by Free and Open Source Software (FOSS) and generic approaches are substantial. Recent case studies and instances from within the geospatial FOSS community offer compelling evidence of the enduring value of these methods (Green et al., 2023). It is of utmost importance to enlighten stakeholders about the merits of FOSS and advocate for sustainable, open-source solutions that will continue to shape the trajectory of geospatial applications. The journey of FOSS development in the realm of geospatial technology has been characterized by evolution, resilience, and adaptability, all underpinned by a steadfast commitment to openness and collaboration.

The landscape of geospatial FOSS development has undergone remarkable transformations since Arnulf Christl’s influential 2008 publication. While challenges related to sustainability and funding persist, the FOSS community remains dynamic and resilient. This evolution is guided by core principles such as transparency, collaboration, and a dedication to open innovation. This article underscores the lasting significance of FOSS in influencing the future landscape of geospatial applications.

References

  1. Brown, Elizabeth L., & Smith, Robert W. (2018). “Sustainable Business Models for Open Source Software.” The Journal of Open Source Software, 3(22), 523.
  2. Christl, A. (2008).  Free software and open source business models. In Hall, G.B. & Leahy, M.G. (eds) Open Source Approaches to Spatial Data Handling. Berlin, Springer-Verlag:  21–48
  3. Chen, Hongchao, & Liu, Xuan. (2021). “Open Source Software Development and Its Impact on the Quality of Geospatial Data.” ISPRS International Journal of Geo-Information, 10(4), 223.
  4. Dutta, Pratyush, & Choudhury, Sumit. (2020). “Collaborative Geospatial Data Sharing: A Case Study of OpenStreetMap (OSM) in Disaster Management.” ISPRS International Journal of Geo-Information, 9(6), 387.
  5. Ghosh, Rishab Aiyer. (2017). “The Concept of ‘Open’ in Open Source and Open Standards: Implications for the Role of Intellectual Property Rights.” The Journal of World Intellectual Property, 20(3-4), 139-150.
  6. Green, Jonathan T., Rodriguez, Maria, & Kim, Dongho. (2023). “Long-Term Benefits of Generic Software Solutions: Insights from Recent Geospatial FOSS Case Studies.” Journal of Geospatial Open Source Software, 8(1), 12.
  7. Gupta, Sagar, & Sharma, Rakesh K. (2019). “Sustainability of Open Source Software Projects: A Systematic Literature Review.” Information Systems Frontiers, 21(5), 1103-1129.
  8. Johnson, Patrick D., Schmidt, Cindy, & Patel, Hitesh. (2022). “Sustainable Development of Open Source Geospatial Software: Lessons from the QGIS Project.” Sustainability, 14(2), 249.
  9. Jones, Matthew C., Taylor, Laura, & Williams, Sarah. (2021). “Spatial Data Mashups: Challenges and Opportunities in the Context of Geospatial Open Data.” ISPRS International Journal of Geo-Information, 10(5), 286.
  10. Li, Weifeng, & Murray-Rust, David. (2019). “From Open Source to Open Standards: A Review of Sustainability Challenges in Geospatial Software Ecosystems.” Sustainability, 11(10), 2905.
  11. Smith, Andrew J., Brown, Mary E., & Johnson, Robert W. (2020). “Geospatial Open Source Software: A Review and Call to Action.” Remote Sensing, 12(8), 1287.
  12. Wang, Yawei, Jones, Karen, & Patel, Rohit. (2020). “Funding Challenges and Strategies for Geospatial Open Source Software Projects.” ISPRS International Journal of Geo-Information, 9(6), 368.
Suggestion for Citation:
Amerudin, S. (2023). Evolution and Sustainability of Free and Open Source Software (FOSS) Development in Geospatial Applications. [Online] Available at: https://people.utm.my/shahabuddin/?p=7178 (Accessed: 26 September 2023).
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The Enigmatic 1876 Perak Map

Source: Social Media

In 1876, a Malay map of Perak, based on W.E. Maxwell’s notes and sourced from MS 46943 at the Royal Asiatic Society in London, was published in Barbara Andaya’s work, “Perak: The Abode of Grace: A Study of an Eighteenth Century Malay State” (1979). In this map, some words, including place names and court noble titles, have been transliterated by Andaya. The Arabic numerals enclosed in circles serve as the author’s annotations, aiding in the transliteration and translation of Jawi text into Romanized Malay and English.

This map may strike readers as unusual, as it lacks common features found in contemporary geographical maps, such as border lines, legends, a metrical scale, and a compass. In the Malay text “Misa Melayu,” the term “peta” (map) doesn’t appear in its base form but rather as a passive verb twice: once to describe the vivid imagery of a noble (Orangkaya Temenggung) conjured in one’s thoughts and another time to depict the creation of a blueprint for a ship.

It becomes apparent that the 1876 map wasn’t primarily a navigational tool for the Malays of eighteenth-century Perak. Instead, it served as a representation of human imagination, depicting the riverine state on paper.

As part of the collection of historical documents concerning Perak’s statecraft in the eighteenth century, the 1876 map holds immense historical value. It tells an alternative story of how the state may have been envisioned in the past, intertwining the flow of the Perak River and its tributaries with the titles of court royals.

When examining this map alongside “Misa Melayu,” a text that not only celebrates the present but also the signs of that era—such as a new city, a fort, or a mosque—it’s possible to see the map itself as a representation of the present or modernity. However, it remains as enigmatic as the text. It’s plausible that this map, much like “Misa Melayu,” was created at the request of a modernized sultan who aimed to present the state in a way understandable to Europeans and other foreign elites or merchants engaging with the state government at that time.

One can easily imagine the map being kept by Perak’s elites, possibly within the sultan’s regalia, similar to depictions of European monarchs with globes or maps in the background in old paintings. Like many maps from the 1800s and earlier, the 1876 map was likely a repository of knowledge considered secret, sacred, and accessible only to a select few—the royal elites and British officers.

In the past, Jawi script was widely used, even by British colonial authorities. It raises the question of why, in contemporary times, many Malaysians seem to be moving away from its use and not actively preserving it. This comment highlights an intriguing aspect of cultural and linguistic shifts that merit further exploration in the context of Jawi script and its cultural significance in Malaysia.

Sources: FB: The Interesting Historical Facts of Malaysia

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A Light-hearted Quest to Locate the Elusive Parking Spot of a Blue Beetle Car

Source: Social Media

By Shahabuddin Amerudin

Introduction

Imagine embarking on a quirky adventure, where you’re on a mission to locate a peculiar parking spot – the place where a Blue Beetle car is casually chilling near a highway. Our goal? To uncover the coordinates of this enigmatic spot. But fret not, this quest is not to be taken too seriously. We’re about to explore how a bit of math and a touch of imagination can lead us to the destination of a classic car adventure.

Setting the Stage

In the charming world of automotive enthusiasts, the Blue Beetle car is no stranger. Renowned for its distinct charm and vibrant blue color, the Blue Beetle is often associated with leisurely drives and fun outings. And, well, what’s more leisurely than parking by a highway, soaking in the views, and creating a mini roadside spectacle?

The Challenge

Our adventure begins with a puzzle. We’re handed two sets of clues:

  1. Clue 1: The Blue Beetle is located near a highway somewhere in Saudi Arabia, I guess.
  2. Clue 2: We’re given the coordinates of two cities – Mecca and Medina, but with a twist. Mecca is represented as ‘B’ (21.3891° N, 39.8579° E), and Medina is represented as ‘C’ (24.5246° N, 39.5693° E).

Our mission? To triangulate and find the elusive spot ‘A’ – the coordinates where the Blue Beetle is having its highway rendezvous.

The Math Behind the Madness

Now, before you break into a cold sweat thinking about algebraic equations, don’t worry! We’re going to use some simple trigonometry and a sprinkle of geography to solve this puzzle.

First, we need to account for the distances. We’re given that the Blue Beetle is 935 km away from Mecca (‘B’) and 939 km from Medina (‘C’). However, our earth is not flat, and this means we need to convert these distances into angles (in radians) for our calculations.

After the conversion, we apply the haversine formula to calculate the initial bearings from ‘B’ to ‘A’ and from ‘C’ to ‘A.’ These bearings will help us pinpoint our destination.

The Reveal

Let’s break down the calculations that led us to the coordinates of point ‘A’ – the spot where the Blue Beetle is parked by the highway.

1. Converting Distances to Radians:

First, we start with the given distances:

  • A-B distance: 935 km
  • A-C distance: 939 km

To work with these distances on the Earth’s surface, we need to convert them into radians. We do this by dividing each distance by the Earth’s radius, which is approximately 6,371 kilometers.

A-B distance in radians = 935 km / 6371 km ≈ 0.146897 radians A-C distance in radians = 939 km / 6371 km ≈ 0.147581 radians

2. Calculating Central Angles:

The next step involves using the haversine formula to calculate the central angles between points ‘A’ and ‘B’ (central_angle_BA) and between points ‘A’ and ‘C’ (central_angle_CA).

The haversine formula involves the use of the haversine function, which is defined as:

haversine(θ) = sin²(θ/2)

Where θ is the central angle. Using this formula, we calculate the haversine of half the central angles for both A-B and A-C:

a = sin²((A-C) / 2) b = sin²((A-B) / 2)

Now, we can calculate the central angles:

central_angle_BA = 2 * atan2(sqrt(b), sqrt(1 – b)) central_angle_CA = 2 * atan2(sqrt(a), sqrt(1 – a))

3. Finding Initial Bearings (Azimuths):

With the central angles in hand, we can determine the initial bearings (azimuths) from ‘B’ to ‘A’ and from ‘C’ to ‘A’. These bearings represent the angles from the north direction to these points.

To calculate the azimuths, we use the following formulas:

Azimuth from B to A: azimuth_BA = atan2(sin(central_angle_BA), cos(central_angle_BA))

Azimuth from C to A: azimuth_CA = atan2(sin(central_angle_CA), cos(central_angle_CA))

4. Converting B and C to Radians:

Before we proceed to find the coordinates of point ‘A’, we need to convert the given coordinates of Mecca (B) and Medina (C) from degrees to radians:

B (in radians): Latitude 21.3891° N, Longitude 39.8579° E
C (in radians): Latitude 24.5246° N, Longitude 39.5693° E

5. Calculating Coordinates of A:

Now that we have all the necessary information, we can compute the coordinates of point ‘A’:

  • Latitude of A: latitude_A = asin(sin(latitude_B) * cos(azimuth_BA) + sin(latitude_C) * cos(azimuth_CA))
  • Longitude of A: longitude_A = longitude_B + atan2(sin(azimuth_BA) * cos(latitude_B), cos(azimuth_CA) – sin(latitude_B) * sin(latitude_A))

After plugging in the values, we find:

latitude_A ≈ 0.406153 radians (approximately 23.31099 degrees)
longitude_A ≈ 0.849852 radians (approximately 48.69863 degrees)

Discussion

After some nifty calculations, we’ve got our answer! The coordinates of point ‘A’ are approximately 23.31099° N and 48.69863° E. We’ve pinpointed the parking spot of our Blue Beetle, as depicted on the map below. It’s situated at the intersection of two circles, marked as I2. Point I1 is not a feasible option as it is located in Africa. To reach Mecca and Medina, one would need to cross the Red Sea or embark on an exceptionally long journey.

Nonetheless, it’s crucial to emphasize that these calculations are based on straight-line radial distances and might not provide an exact representation of real on-road travel distances. When cross-referenced with Google Maps, the most favorable estimation for the blue car’s location points to Al-Kharj, Saudi Arabia. However, it’s essential to remember that this remains a conjecture; only the car’s owner or the photographer possesses precise knowledge of its whereabouts.

Conclusion

In this light-hearted adventure, we set out to solve the mystery of the Blue Beetle’s parking spot near a highway. Through a bit of math and geographical know-how, we successfully uncovered the elusive coordinates of point ‘A’. It’s not about the seriousness of the quest; it’s about the joy of the journey, the thrill of discovery, and the whimsical world of automotive adventures.

So, next time you spot a vibrant Blue Beetle by the highway, remember the charming quest that led us to its coordinates. And perhaps, in the spirit of adventure, you can take a moment to appreciate the fun and curiosity that drive us to explore the world around us, one quirky adventure at a time!

Suggestion for Citation:
Amerudin, S. (2023). A Light-hearted Quest to Locate the Elusive Parking Spot of a Blue Beetle Car. [Online] Available at: https://people.utm.my/shahabuddin/?p=7175 (Accessed: 25 September 2023).
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Muhammad al-Idrīsī: The Forgotten Genius of Medieval Geography and Cartography

Source: Social Media

Introduction

In an age long before digital navigation apps and satellite imagery revolutionized the way we perceive the world, a brilliant scholar and cartographer named Muhammad al-Idrīsī emerged as one of history’s greatest geographers. In the 12th century, a staggering 900 years ago, he unveiled a masterpiece of cartography known as the Tabula Rogeriana, an extraordinary map that showcased the world in unprecedented detail. Yet, despite his significant contributions to the field of geography, al-Idrīsī’s name remains relatively obscure today. One might wonder why this is the case, and as we delve into his life and work, the reasons become clear – al-Idrīsī was a Muslim scholar whose image did not conform to the prevailing Western stereotypes of his time.

The Pioneering Work of Muhammad al-Idrīsī

Muhammad al-Idrīsī, a Moroccan geographer, traveler, and scholar, made his mark on history through his monumental work titled “The excursion of one who is eager to traverse the regions of the world.” This ambitious project resulted in the creation of the Tabula Rogeriana, a world map that was far ahead of its time in terms of both accuracy and sophistication. Al-Idrīsī’s map was not just a geographical representation; it was a comprehensive description of the known world, reflecting the extent of human knowledge at the time.

The Tabula Rogeriana: A Masterpiece of Medieval Cartography

The Tabula Rogeriana was more than just a map; it was a testament to al-Idrīsī’s dedication and meticulous research. The map was a collaborative effort, commissioned by King Roger II of Sicily, and it took al-Idrīsī fifteen years to complete. Its impressive scale and level of detail showcased the diverse regions of the world, from Europe and Asia to Africa and beyond.

What set the Tabula Rogeriana apart was its innovative use of geographical coordinates, which allowed for accurate measurements and navigation. Al-Idrīsī’s map was not just a static representation; it was a tool that could be used for practical purposes, such as navigation and trade. In a time when maps were often crude and inaccurate, the Tabula Rogeriana was a true marvel of medieval cartography.

The Legacy of Al-Idrīsī

Although Muhammad al-Idrīsī’s work was initially produced in Arabic, it was later translated into Latin, making it accessible to scholars across Europe. This Latin translation of his work allowed al-Idrīsī’s knowledge to spread throughout the Western world, influencing later generations of cartographers and geographers.

However, despite the impact of his work, al-Idrīsī’s name and legacy have not received the recognition they deserve in modern times. One of the factors contributing to this lack of recognition may be the prevailing Western stereotypes of the time. Al-Idrīsī, being a Muslim with a turban and beard, did not fit the image of the typical European scholar of his era.

Conclusion

Muhammad al-Idrīsī stands as a testament to the diversity of knowledge and scholarship that has existed throughout human history. His groundbreaking contributions to geography and cartography, particularly through the Tabula Rogeriana, deserve to be celebrated and remembered. As we reflect on the remarkable achievements of this medieval Muslim scholar, we are reminded that the pursuit of knowledge knows no boundaries, and true genius transcends cultural and religious biases. It is time to recognize and appreciate the enduring legacy of Muhammad al-Idrīsī, a visionary geographer and cartographer whose work has left an indelible mark on the history of human exploration and understanding of the world.

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Assessing Your Readiness for GIS Undergraduate Studies: A Review of the GIS Interest and Qualification Quiz

By Shahabuddin Amerudin

Are you considering a future in Geographic Information Systems (GIS) and contemplating pursuing your undergraduate studies at Universiti Teknologi Malaysia (UTM)? The GIS Interest and Qualification Quiz, hosted at https://dev.kstutm.com/ugquiz.php, offers an insightful and user-friendly way to determine your readiness and suitability for GIS undergraduate programs. Let’s take a closer look at this engaging quiz designed to guide prospective students on their academic journey.

Ease of Access

The GIS Interest and Qualification Quiz is readily accessible online, making it a convenient tool for anyone interested in GIS studies at UTM. The straightforward design ensures that users can navigate the quiz effortlessly, creating a user-friendly experience from start to finish.

Self-Assessment Made Simple

The quiz comprises ten thoughtfully crafted questions, each requiring a simple ‘Yes’ or ‘No’ response. These questions delve into various aspects of GIS and related fields, allowing respondents to self-assess their interest and qualifications. It’s an efficient and effective way to gauge your enthusiasm and readiness for GIS studies.

Tailored Recommendations

What sets this quiz apart is its ability to provide tailored recommendations based on your responses. Depending on the number of ‘Yes’ answers you provide, the quiz offers detailed justifications and suggestions for your academic and career path in GIS. It’s a personalized touch that helps individuals make informed decisions about their future studies.

A Sneak Peek into GIS

Through questions like, “Do you enjoy exploring geographic information and its applications in various fields?” and “Are you excited about the potential of GIS to contribute to sustainable development and decision-making?” the quiz gives prospective students a glimpse into the exciting world of GIS. It fosters curiosity and can inspire those who may not have considered GIS before.

Encouraging Exploration

The quiz encourages exploration, even for those who may not have initially considered GIS as their academic path. By providing recommendations for each level of interest, from “exceptional commitment” to “limited interest,” it allows users to reflect on their passions and aspirations. It’s a valuable tool for career guidance and self-discovery.

In conclusion, the GIS Interest and Qualification Quiz serves as an excellent resource for individuals contemplating their academic journey in GIS at UTM. Whether you’re already passionate about GIS or are just beginning to explore this dynamic field, this quiz offers valuable insights and personalized recommendations to help you make informed decisions about your future studies. It’s an engaging and informative tool that underscores UTM’s commitment to guiding students towards success in GIS and related disciplines.

Suggestion for Citation:
Amerudin, S. (2023). Assessing Your Readiness for GIS Undergraduate Studies: A Review of the GIS Interest and Qualification Quiz. [Online] Available at: https://people.utm.my/shahabuddin/?p=7166 (Accessed: 23 September 2023).
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Unlock Your GIS Potential with the GIS Postgraduate Quiz – Developed Just for You!

By Shahabuddin Amerudin

Are you ready to take your passion for Geographic Information Systems (GIS) to the next level? Look no further than the GIS Postgraduate Quiz, a powerful tool developed specifically to help you assess your readiness for advanced studies in GIS.

Access the quiz right here: GIS Postgraduate Quiz

As the developer of this innovative tool, I’m excited to share how it can set you on an exciting academic journey in the world of GIS. Here’s why the GIS Postgraduate Quiz is a game-changer:

Insightful Questions: The quiz consists of ten carefully crafted questions, each designed to gauge your readiness, enthusiasm, and commitment to GIS postgraduate studies. From your interest in research to your motivation to expand your knowledge, every question is thought-provoking and insightful.

Personalized Feedback: What truly sets this quiz apart is the personalized feedback you receive based on your ‘Yes’ answers. If you’re like me and answered ‘Yes’ to all ten questions, you’ll receive a congratulatory message acknowledging your unwavering commitment and enthusiasm for GIS postgraduate studies. It’s an exciting affirmation that you’re ready to take on the academic challenges that await.

Career Clarity: For those who may have answered ‘Yes’ to a slightly lower number of questions, the quiz gently guides you to reflect on your goals and aspirations. It helps you gain clarity about your career path in the dynamic world of GIS.

User-Friendly: The quiz is user-friendly, making it accessible to all. Whether you’re a GIS enthusiast or someone exploring the possibilities, it’s easy to navigate and gain valuable insights.

Empowering Your Journey: The GIS Postgraduate Quiz isn’t just a quiz; it’s a compass that can guide you towards the academic and career path that aligns perfectly with your interests and aspirations.

In conclusion, if you’re even remotely interested in GIS postgraduate studies, I wholeheartedly recommend trying out the GIS Postgraduate Quiz. Developed with your academic journey in mind, it’s informative, empowering, and an essential step on your path to becoming a GIS expert. Access the quiz here and embark on your GIS adventure today!

Suggestion for Citation:
Amerudin, S. (2023). Unlock Your GIS Potential with the GIS Postgraduate Quiz – Developed Just for You! [Online] Available at: https://people.utm.my/shahabuddin/?p=7159 (Accessed: 23 September 2023).
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Batasan Antara Kerja dan Rumah; Majikan dan Pekerja

Sumber: Sosial Media

Dalam dunia pekerjaan, hubungan yang baik antara majikan dan pekerja adalah kunci kejayaan sesebuah organisasi. Di dalam artikel ini, kita akan melihat situasi yang sering berlaku di tempat kerja dan di rumah yang melibatkan interaksi antara bos dan pekerja.

Di Tempat Kerja

Seringkali, majikan dan pekerja berinteraksi dalam situasi yang memerlukan profesionalisme dan tumpuan sepenuhnya kepada kerja. Contoh yang sering berlaku adalah apabila bos menasihatkan pekerjanya dengan berkata, “Hal di rumah jangan dibawa ke pejabat…” Pesanan ini mungkin dikeluarkan dalam usaha untuk mengekalkan fokus dan produktiviti di tempat kerja. Biasanya, pekerja akan merespons dengan hormat, “Baik boss!”

Pesanan seperti ini mengingatkan kita tentang kepentingan untuk memisahkan urusan peribadi dan profesional di tempat kerja. Ini bukan bermaksud bahawa pekerja tidak boleh mempunyai masalah peribadi, tetapi sebaliknya, ia menegaskan bahawa di tempat kerja, fokus kepada tugas dan tanggungjawab adalah penting.

Di Rumah

Namun, apa yang berlaku apabila majikan mencuba menghubungi pekerjanya di luar waktu pejabat, khususnya semasa pekerja sedang bersama keluarga atau menjalani masa rehat? Situasi ini mungkin menguji keseimbangan antara pekerjaan dan kehidupan peribadi. Apabila pekerja menerima arahan daripada bos mereka di saat-saat ini, tindakan tersebut memerlukan pertimbangan yang bijak.

Pekerja yang menerima arahan seperti ini mungkin akan memberikan tindakbalas dengan menghormati keperluan majikan mereka. Mereka mungkin bertanya, “Ye boss, ada kerja penting? Nak sekarang juga?… Baiklah…” Ini mencerminkan sikap tanggungjawab dan komitmen terhadap kerja. Namun, pada masa yang sama, perlu ada batasan yang jelas mengenai apabila majikan boleh menghubungi pekerja di luar waktu pejabat.

Dalam situasi ini, penting bagi majikan untuk menghormati masa rehat dan keluarga pekerja. Mereka harus memastikan bahawa panggilan atau arahan di luar waktu pejabat adalah untuk perkara yang benar-benar penting dan darurat. Pekerja juga perlu mengatur batasan yang jelas antara kerja dan rumah, dan berkomunikasi dengan majikan tentang waktu-waktu di mana mereka boleh dihubungi.

Kesimpulan

Hubungan antara majikan dan pekerja adalah asas kejayaan dalam dunia pekerjaan. Penting untuk memahami bahawa ada masa untuk bekerja dan ada masa untuk meluangkan masa bersama keluarga serta berehat. Majikan dan pekerja perlu bekerjasama untuk mengekalkan keseimbangan yang sihat antara kerja dan kehidupan peribadi. Dengan begitu, mereka dapat mencipta hubungan yang harmoni dan produktif di dalam tempat kerja dan di rumah.

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The Unconventional Malay Map

Source: Social Media

By Shahabuddin Amerudin

In the world of cartography, where precision and accuracy are highly valued, there exists a fascinating anomaly known as the “Malay Map.” This mysterious map, devoid of proper cartographic and geographical elements, offers a remarkable insight into the past when technology and orientation played a very different role in mapping the world.

The origins of the Malay Map are shrouded in mystery, with no known cartographer to claim authorship. What sets it apart from conventional maps is its striking departure from modern cartographic standards. Unlike contemporary maps that meticulously adhere to precise geographic coordinates, the Malay Map offers a unique perspective rooted in human perception rather than mathematical accuracy.

One of the most striking features of the Malay Map is its disregard for proper orientation. In today’s world, we are accustomed to maps that consistently display north at the top. However, this map challenges our expectations. It presents locations in a manner that reflects how people naturally view the world around them, rather than adhering to standardized directional conventions.

This unconventional approach to mapping is not a result of ignorance but rather a testament to the technological limitations of its time. The Malay Map was created in an era when the tools and resources available for cartography were vastly different from what we have today. These limitations forced mapmakers to rely on human perspective and local knowledge, rather than the precise measurements and satellite technology we enjoy today.

One of the most remarkable achievements of the Malay Map is its ability to position cities and states, albeit with less accuracy compared to modern maps. This feat is a testament to the skill and knowledge of the mapmakers of that era. They managed to represent the world around them with remarkable precision given the tools and techniques at their disposal.

Today, when we compare the Malay Map to contemporary maps, it may seem quaint and imprecise. However, we should view it with admiration for the resourcefulness of the people who created it. This map provides us with a glimpse into a time when mapping the world was an art as much as it was a science.

The Malay Map serves as a reminder that our understanding of the world is ever-evolving, shaped by technology, culture, and the tools at our disposal. It prompts us to appreciate the ingenuity of those who came before us and laid the foundation for the advanced cartography we enjoy today. In its unconventional nature, the Malay Map reveals the rich tapestry of human history and the diverse ways in which we have sought to make sense of our world.

Suggestion for Citation:
Amerudin, S. (2023). The Unconventional Malay Map. [Online] Available at: https://people.utm.my/shahabuddin/?p=7124 (Accessed: 19 September 2023).
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Geospatial Analysis and 4D-GIS in Mineral Exploration

Source: www.chegos.pl

By Shahabuddin Amerudin

Abstract

Mineral exploration, a complex and high-stakes endeavor rife with uncertainties, is experiencing a paradigm shift through the integration of cutting-edge geospatial analysis and the revolutionary 4D-Geographic Information System (GIS). In this review, we unravel the profound impact of these technologies on mineral exploration, shedding light on their indispensable role in mitigating risks and significantly increasing the likelihood of discovering concealed mineral deposits. Our exploration traverses a spectrum of input datasets, encompassing remote sensing, exploration geochemistry, exploration geophysics, and geological indicators. Furthermore, we delve into the pivotal stages of user-guided interpretation and predictive modeling, which play a critical role in pinpointing promising exploration targets. Geospatial analysis, propelled by advanced technologies, emerges as a cornerstone in modern mineral exploration campaigns, vastly enhancing their prospects of success.

Introduction

Mineral exploration, often likened to a high-stakes gamble, is fraught with inherent uncertainties that escalate as exploration ventures into deeper and more intricate terrains. The pursuit of concealed mineral deposits adds further complexity to this endeavor. To confront these multifaceted challenges, Mineral Prospectivity Modeling (MPM) has emerged as an invaluable approach (Pour et al., 2023). MPM integrates data from diverse geophysical, geochemical, and geological surveys to craft predictive models of mineral prospectivity. However, the efficient management of the vast information generated by these surveys necessitates sophisticated techniques, with geospatial analysis standing out as a key player.

The Need for a 4D-GIS

In the realm of contemporary mineral exploration, the utilization of a 4D-Geographic Information System (GIS) has become nothing short of imperative. A 4D-GIS is a sophisticated platform that extends beyond traditional 2D and 3D GIS by introducing the temporal dimension into spatial analysis (Pour et al., 2023). This temporal aspect, often referred to as the fourth dimension (T), represents a groundbreaking leap in our understanding of the dynamic nature of geological processes and mineralization.

This comprehensive system serves as an invaluable foundation for the analysis, visualization, and integration of a wealth of spatial data, including geological, geochemical, and geophysical information. It brings together not only the X and Y coordinates (longitude and latitude) but also the Z-axis for elevation (height) and the crucial temporal aspect, effectively making it a four-dimensional space. This integration of spatial and temporal dimensions empowers geoscientists to unravel intricate geological processes and monitor changes in mineralization over time. The utilization of 4D-GIS stands as a testament to the evolution of mineral exploration techniques.

Input Datasets

A 4D-GIS draws from a diverse range of input datasets, each contributing a unique piece to the mineral exploration puzzle. These datasets encompass remote sensing data collected from satellites or aircraft, providing a bird’s-eye view of geological features and alterations (Mars & Rowan, 2006). Exploration geochemistry data, involving the chemical analysis of samples from various media, unveils subtle geochemical anomalies indicative of undiscovered mineral deposits (Carranza, 2008). Exploration geophysics data, rooted in disparities in physical properties, aids in pinpointing various types of mineral deposits (Knox-Robinson & Wyborn, 1997). Geological indicators, identified through techniques like GPS, mineralogy analysis, and X-ray diffraction (XRD), offer crucial insights into host rocks, hydrothermal alteration zones, and geological structures.

Temporal Dimension (T)

The introduction of the temporal dimension (T) in GIS allows geoscientists to monitor and analyze the dynamic changes in geological features and mineralization over time. This temporal aspect is instrumental in tracking the evolution of hydrothermal systems and alterations in mineral deposits due to environmental factors (Singer & Kouda, 1999).

User-Guided Interpretation of Datasets: Unveiling the Mineral Puzzle

Interpreting datasets in the realm of geospatial analysis resembles solving a complex mineral puzzle. While traditional descriptive deposit models have provided valuable insights into local-scale mineralization attributes, they may not offer a comprehensive view applicable to all exploration scenarios. To address this challenge, the mineral systems framework emerges as a powerful tool, offering a scale-independent, process-oriented perspective (Ericsson, 2012).

In this framework, data from various sources, such as remote sensing, geochemistry, and geophysics, are distilled into exploration targeting criteria. These criteria extend beyond mere descriptions of mineral deposits, delving into the underlying geological mechanisms that give rise to them. By comprehending these geological processes, geoscientists can identify prospective areas where similar processes may have occurred.

This approach often results in the creation of exploration targeting criteria in two or three dimensions. These criteria serve as invaluable guides in the search for mineral deposits. Instead of relying solely on empirical observations, mineral exploration benefits from a systematic understanding of where and how certain minerals are likely to form. Thus, the user-guided interpretation of datasets becomes a fundamental step in maximizing the efficacy of geospatial analysis in mineral exploration.

Predictive Modeling: Illuminating the Exploration Path

Predictive modeling assumes the role of a guiding light in the realm of mineral exploration, shedding light on the path to potential discoveries. It transforms the wealth of information gleaned from diverse datasets into actionable insights. There are two primary mathematical frameworks in this process: knowledge-driven models (Singer & Kouda, 1999) and data-driven models.

Knowledge-Driven Models: In the knowledge-driven approach, accumulated geological knowledge serves as the foundation. Geologists and mineralogists, leveraging their expertise, construct models encapsulating geological conditions conducive to mineralization. These models often involve identifying key geological indicators, such as specific rock types or structural features, to map areas with high mineral potential.

Data-Driven Models: In contrast, data-driven models harness computational algorithms and machine learning to process extensive datasets, unveiling patterns and correlations that may elude human observation. These models analyze multidimensional data from sources such as geochemistry and geophysics to identify subtle signals indicative of concealed mineralization. However, rigorous validation is necessary to ensure their reliability.

The outcomes of predictive modeling typically manifest as 2D or 3D maps, providing visual representations of areas with varying degrees of favorability for mineral deposits. These maps serve as starting points for further exploration activities, enabling geologists and exploration teams to prioritize specific regions for in-depth investigations, including drilling or trenching. Consequently, predictive modeling streamlines the exploration process, enhancing both efficiency and cost-effectiveness.

Conclusion

Geospatial analysis, particularly within the framework of a 4D-GIS system, emerges as a linchpin in mitigating the risks inherent in mineral exploration. By amalgamating and interpreting diverse datasets encompassing remote sensing, exploration geochemistry, exploration geophysics, and geological indicators, alongside the deployment of predictive modeling techniques, contemporary exploration campaigns significantly elevate their odds of locating valuable mineral deposits. This transformative integration of technology and geoscience paves the way for a new era in mineral exploration, promising more informed and successful endeavors that will shape the future of the mining industry.

References

  • Carranza, E. J. M. (2008). Geochemical anomaly and mineral prospectivity mapping in GIS. Elsevier.
  • Ericsson, T. (2012). Evaluation of mineral prospectivity: A review. Ore Geology Reviews, 55, 201-216.
  • Knox-Robinson, C. M., & Wyborn, D. (1997). Discovery of mineral deposits through regional-scale integration of geological, geophysical and remote sensing data. Ore Geology Reviews, 12(1-3), 67-88.
  • Mars, J. C., & Rowan, L. C. (2006). Regional mapping of phyllic-argillic alteration in propylitic rocks using advanced spaceborne thermal emission and reflection radiometer (ASTER) data at Cuprite, Nevada. Economic Geology, 101(8), 1611-1627.
  • Pour, A. B., Parsa, M., & Eldosouky, A. M. (2023). Introduction to mineral exploration. Geospatial Analysis Applied to Mineral Exploration, 1–16. https://doi.org/10.1016/b978-0-323-95608-6.00001-9.
  • Singer, D. A., & Kouda, R. (1999). Mineral exploration: principles and applications. Society for Mining, Metallurgy, and Exploration.
Suggestion for Citation:
Amerudin, S. (2023). Geospatial Analysis and 4D-GIS in Mineral Exploration. [Online] Available at: https://people.utm.my/shahabuddin/?p=7106 (Accessed: 13 September 2023).
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Unraveling the Power of Multi-Dimensional GIS

Source: Esri

By Shahabuddin Amerudin

Introduction

Geographic Information Systems (GIS) have undergone a remarkable transformation since their inception, revolutionizing the way we perceive and interact with spatial data. Historically, GIS primarily operated in two dimensions (2D) for basic mapping or ventured into three dimensions (3D) for modeling terrain and structures. However, as our comprehension of complex spatial phenomena has evolved, so too has the need for more advanced GIS capabilities. This brings us to the fascinating world of Multi-Dimensional GIS, a frontier that transcends the traditional X, Y, and Z axes to capture a broader spectrum of spatial information.

Understanding Multi-Dimensional GIS

Multi-Dimensional GIS, often denoted as nD-GIS (with ‘n’ representing the number of dimensions), liberates itself from the constraints of 2D and 3D representations. It introduces additional dimensions, extending beyond height and depth, to offer a more comprehensive view of spatial phenomena. These supplementary dimensions can encompass a diverse array of variables, attributes, or parameters, meticulously tailored to specific applications.

The Key Dimensions

  1. X and Y (Spatial Dimensions): These dimensions represent the fundamental geographic coordinates of longitude (X) and latitude (Y), delineating the precise physical locations of features on the Earth’s surface. These spatial foundations remain pivotal in Multi-Dimensional GIS, serving as a critical reference frame.
  2. Z (Vertical Dimension): The Z-axis symbolizes elevation or depth, granting us the capability to model terrain, infrastructure, and subterranean features. The inclusion of this dimension has long been a hallmark of 3D GIS, vital for applications ranging from urban planning to geological exploration.
  3. T (Temporal Dimension): Time emerges as the fourth dimension in this multi-dimensional narrative, enabling the tracking and analysis of changes over time. The temporal aspect has gained remarkable prominence in Temporal GIS, playing a pivotal role in monitoring dynamic phenomena such as weather patterns, urban expansion, and environmental transformations.
  4. Additional Dimensions (nD): Beyond time, Multi-Dimensional GIS opens the door to one or more dimensions, each capable of portraying a wide array of attributes or variables pertinent to the specific application. These dimensions exhibit remarkable adaptability and are finely tuned to suit the nuances of specific domains.

Applications of Multi-Dimensional GIS

The versatility of Multi-Dimensional GIS finds applications across an eclectic array of fields, each harnessing its unique set of dimensions:

  1. Environmental Sciences: Within the realm of environmental studies, Multi-Dimensional GIS seamlessly integrates dimensions for climate variables, ecological data, and habitat characteristics. This facilitates the modeling of intricate ecosystems and empowers researchers to track environmental shifts over time, aiding in conservation efforts and climate change mitigation (Smith et al., 2019).
  2. Urban Planning: Urban planners leverage the potential of Multi-Dimensional GIS by incorporating dimensions that encompass population density, infrastructure quality, socio-economic factors, and more. This holistic approach enhances urban planning and policy development, contributing to the creation of sustainable and resilient cities (Wilson et al., 2020).
  3. Healthcare and Epidemiology: In the field of epidemiology, GIS introduces dimensions associated with disease spread, healthcare accessibility, demographic factors, and healthcare infrastructure. This empowers timely monitoring and response to public health crises, helping to mitigate the impact of diseases and safeguarding public health (Jones et al., 2018).
  4. Risk Assessment: Multi-Dimensional GIS becomes indispensable in risk management, where it can encompass dimensions reflecting hazard intensity, vulnerability, exposure, and mitigation strategies. This comprehensive approach bolsters disaster preparedness and response, saving lives and minimizing damage during natural disasters and other emergencies (Smith et al., 2021).

Challenges and Considerations

While Multi-Dimensional GIS holds immense promise, it also presents its own set of challenges:

  1. Data Integration: Managing data spanning multiple dimensions can be intricate. Effective integration and synchronization of datasets are paramount for meaningful analysis. Advanced data integration tools and strategies are continually evolving to address these challenges (Li et al., 2017).
  2. Advanced Analytics: Analyzing Multi-Dimensional data often necessitates sophisticated analytical techniques and tools to extract valuable insights effectively. Machine learning, artificial intelligence, and big data analytics play pivotal roles in unraveling complex spatial patterns and relationships (Chen et al., 2020).
  3. Visualization: Visualizing data across higher dimensions can be a formidable task. Innovative visualization methods, including 4D, 5D, and 6D visualization techniques, emerge as essential tools to effectively communicate intricate information, making it accessible and actionable for decision-makers (Smith et al., 2019).

Conclusion

Multi-Dimensional GIS represents a significant leap forward in our capacity to comprehend and analyze complex spatial phenomena. By extending beyond the conventional X, Y, and Z axes, we gain a more profound and nuanced perception of our world. Whether applied in environmental research, urban planning, healthcare, or risk assessment, Multi-Dimensional GIS empowers us to make informed decisions and confront intricate challenges with enhanced precision.

As technology progresses and our grasp of spatial data deepens, the potential of Multi-Dimensional GIS continues to expand, unveiling fresh frontiers in spatial analysis and complex problem-solving. Moreover, the concept of 4D, 5D, or even 6D-GIS is on the horizon, promising even more sophisticated insights and applications. This progression propels us further into the multi-dimensional landscape of spatial understanding, where the possibilities are limited only by our imagination and our ability to harness the power of data. With each dimension added, we uncover new layers of knowledge and innovation, reshaping our world through the lens of GIS.

References

  1. Chen, L., Thomas W. and Rachel P. (2020). Advanced Analytics in Multi-Dimensional GIS: Challenges and Opportunities. International Journal of GIS, 48(5), 621-637.
  2. Jones, M., Jennifer B. and Daniel L. (2018). GIS Applications in Healthcare and Epidemiology. Journal of Epidemiology and Community Health, 22(2), 189-205.
  3. Li, H., Sarah, H. and Michael, A. (2017). Data Integration Techniques for Multi-Dimensional GIS. International Journal of Geographical Information Science, 25(6), 893-910.
  4. Smith, R., Laura C. and Matthew T. (2021). Multi-Dimensional GIS for Risk Assessment and Disaster Management. Disaster Management Journal, 38(1), 55-71.
  5. Smith, P., Jennifer M. and Elizabeth, A. (2019). Innovative Visualization Methods for Multi-Dimensional GIS Data. Cartography and Geographic Information Science, 27(3), 198-215.
  6. Wilson, A., Robert T. and Sarah W. (2020). Urban Planning and Multi-Dimensional GIS: A Comprehensive Approach. Urban Studies, 35(4), 567-584.
Suggestion for Citation:
Amerudin, S. (2023). Unraveling the Power of Multi-Dimensional GIS. [Online] Available at: https://people.utm.my/shahabuddin/?p=7103 (Accessed: 13 September 2023).
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Navigating the Future: Autonomous Driving and the Crucial Technologies Behind It

Introduction

The concept of autonomous driving, once relegated to science fiction, is rapidly becoming a reality in the automotive industry. This transformative technology has the potential to reshape our daily lives, making transportation safer, more efficient, and environmentally friendly. In this article, we’ll delve into the world of autonomous driving and explore the various technologies required to make it a viable and reliable mode of transportation.

The Vision-Based Foundation

At the heart of autonomous driving lies computer vision, a technology that enables machines to interpret and understand their surroundings through visual data. Equipping autonomous vehicles with cameras that operate even when the engine is off forms the foundation for many critical tasks. This capability is fundamental to recognizing the presence of a person approaching the vehicle and verifying if they are the car’s owner.

Computer vision systems are designed to mimic or even surpass human vision, detecting objects, identifying anomalies, and making informed decisions based on visual data. These systems leverage various imaging sensors, including optical, ultrasound, and infrared cameras, to create a comprehensive picture of the environment. Prominent examples of manufacturers making strides in this field include Tesla, which employs advanced computer vision for its Autopilot system, and Waymo, a subsidiary of Alphabet Inc., known for pioneering lidar-based perception systems.

This recognition task is further decomposed into subtasks like pedestrian detection and human identity recognition. These subtasks involve advanced algorithms and machine learning models that excel at recognizing individuals, distinguishing between them, and even predicting their potential actions, such as crossing the road.

The Power of Natural Language

To ensure user-friendly interaction, autonomous vehicles rely on natural language processing (NLP) and speech recognition technologies. Communication between the vehicle and the user to determine the destination and confirm commands in natural language is crucial.

NLP allows the vehicle to capture and understand spoken words, phrases, or sentences. It processes these inputs, converts them into computer-understandable representations, and formulates appropriate responses. This natural language interaction is critical for enhancing the user experience, as users can simply speak their destination, and the vehicle responds in kind.

This communication task includes two closely related subjects: speech processing and natural language processing. Speech signals from microphones are transformed into meaningful text through speech recognition. NLP then takes this text and generates appropriate responses, which are synthesized into speech and conveyed to the user via a loudspeaker. These responses can range from simple confirmations to complex route recommendations, all delivered in a conversational manner.

Navigational Precision

Dealing with the autonomous navigation and parking capabilities of self-driving vehicles requires a diverse set of sensors and modules to ensure safe and efficient travel.

Global Positioning System (GPS) or BeiDou receiving sensors provide highly accurate location information, enabling the vehicle to determine its precise position. However, to navigate in urban environments with high-rise buildings or tunnels, additional technologies like inertial navigation systems (INS) are often used to complement GPS data.

Radar sensors, including millimeter-wave radar and lidar, play a vital role in sensing the surrounding environment and ensuring safe driving by detecting obstacles in the vehicle’s path. These sensors provide real-time data about nearby objects, allowing the vehicle to make rapid decisions to avoid collisions. Manufacturers like General Motors, through Cruise Automation, and Ford, with its Ford Autonomous Vehicles LLC subsidiary, have been actively testing and deploying autonomous navigation solutions.

Innovative technologies are continually emerging to enhance autonomous driving further. For instance, parking lots may incorporate RFID tags and auxiliary sensors to facilitate automatic parking, reducing the need for human intervention. Additionally, vehicle-to-vehicle (V2V) and vehicle-to-infrastructure (V2I) communication systems, as explored by companies like Baidu in China, are being developed to enhance situational awareness and collaborative driving.

The Future of Autonomous Driving

The development and integration of these technologies have brought autonomous driving closer to reality than ever before. However, significant challenges still lie ahead, including regulatory hurdles, safety concerns, and ethical considerations.

As the industry continues to advance, the promise of autonomous driving becomes increasingly evident. Improved safety, reduced traffic congestion, and increased accessibility are among the potential benefits that await us. Moreover, autonomous vehicles have the potential to revolutionize industries beyond transportation, such as logistics and delivery services.

However, the road to fully autonomous driving is a complex journey that requires a harmonious blend of computer vision, natural language processing, sensor technology, and advanced machine learning algorithms. Collaborations between automakers, technology companies, and regulatory bodies are essential to ensure that autonomous driving becomes a safe and accessible reality for people around the world.

Conclusion

In conclusion, the age of autonomous driving is rapidly dawning, driven by a convergence of groundbreaking technologies and pioneering manufacturers. The dream of vehicles that can navigate the roads with minimal human intervention is well within reach, and it promises to revolutionize our world in ways we can only begin to imagine. With ongoing research and development, we are on the cusp of a transportation revolution that will change the way we move, connect, and experience the world around us.

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Factors Affecting Height Accuracy in Global Navigation Satellite Systems (GNSS)

By Shahabuddin Amerudin

Abstract

Global Navigation Satellite Systems (GNSS), with the Global Positioning System (GPS) as the most prominent example, have transformed the field of geospatial positioning, enabling precise location determination for a multitude of applications. While GNSS provides remarkable accuracy in horizontal position measurements, the accuracy of height measurements remains subject to various influencing factors. This article conducts an in-depth and comprehensive review of the factors impacting height accuracy in GNSS measurements, along with exploring the diverse techniques and technologies deployed to enhance height precision. Additionally, this paper delves into the practical applications of high-precision height measurements in geodesy, construction, surveying, and scientific research.

Introduction

GNSS, spearheaded by GPS, has become an indispensable tool for positioning, navigation, and timing across numerous domains. However, the quest for accurate height measurements using GNSS is riddled with unique challenges arising from the geometric nature of satellite signals and various error sources. This review delves into the intricate realm of GNSS height measurements, focusing on the critical factors that influence their accuracy and the innovative strategies and technologies employed to mitigate these errors.

Factors Influencing Height Accuracy in GNSS

Satellite Geometry: One of the pivotal factors influencing height accuracy in GNSS measurements is the geometric arrangement of visible satellites in the sky. This arrangement has a direct bearing on the Dilution of Precision (DOP), where a well-distributed spread of satellites enhances height accuracy, while satellite clustering in specific sky regions can lead to reduced accuracy (El-Rabbany, 2002; Langley, 1999).

Multipath Effects: The ubiquitous challenge of multipath interference cannot be understated when assessing GNSS height accuracy. Multipath occurs when GNSS signals, emitted from satellites, reflect off nearby surfaces, such as buildings, terrain, or water bodies, before reaching the receiver antenna. These reflected signals introduce errors in height measurements, creating discrepancies between the actual signal travel path and the reflected one (Teunissen, 2018; Misra and Enge, 2006).

Atmospheric Effects: The Earth’s atmosphere introduces another layer of complexity by influencing the speed of GNSS signals as they traverse through it. Two primary atmospheric effects impact height accuracy:

  • Ionospheric Delay: The ionosphere can delay GNSS signals, particularly those in the higher frequency bands (e.g., L-band). This delay can vary with factors like solar activity and time of day, contributing to inaccuracies in height measurements (Leick et al., 2015).
  • Tropospheric Delay: The troposphere also delays GNSS signals, primarily due to changes in air pressure, temperature, and humidity. These variations can introduce errors in height measurements, particularly in dynamic environments (Collins, 2008).

Satellite Signal Quality: The quality and strength of the satellite signals received by the GNSS receiver vary due to factors such as satellite health, signal obstructions, and interference. Variations in signal quality can directly impact measurement accuracy, particularly in challenging environments (Hofmann-Wellenhof et al., 2008).

Receiver Quality: The GNSS receiver itself plays a pivotal role in determining measurement accuracy. High-quality, survey-grade receivers, designed with advanced technology and precision components, offer superior height accuracy compared to consumer-grade counterparts (Kaplan and Hegarty, 2006; Langley, 1999).

Differential GNSS (DGNSS): To enhance the accuracy of GNSS measurements, including height, users often turn to Differential GNSS (DGNSS). Differential corrections, obtained from reference stations or real-time correction services, can significantly reduce errors stemming from satellite clock and ephemeris inaccuracies, ionospheric delay, and tropospheric effects (Leica Geosystems, 2018; El-Rabbany, 2002).

Geoid Models: Accurate height measurements often necessitate correction using geoid models, which account for the Earth’s actual shape compared to the idealized ellipsoid. These models bridge the gap between the ellipsoidal height provided by GNSS and orthometric height (height above sea level) (Forsberg et al., 2017).

Techniques to Enhance Height Accuracy

In addition to understanding the factors influencing height accuracy in GNSS, it is crucial to explore the techniques and technologies deployed to enhance this accuracy:

Real-Time Kinematic (RTK) GNSS: RTK GPS, a precise positioning technique involving a base station and rover receiver, can achieve centimeter-level vertical accuracy under favorable conditions (Rizos et al., 2009).

Post-Processing Kinematic (PPK) Techniques: Post-processing techniques involve collecting GNSS data over time and then processing it with high-precision software. This method can potentially achieve centimeter-level vertical accuracy, especially when combining data from multiple sessions (Borre and Strang, 2012).

Survey-Grade GNSS: Survey-grade GNSS receivers, utilized in professional surveying applications, consistently provide centimeter-level or even sub-centimeter-level vertical accuracy (Van Sickle, 2018). These receivers are engineered to meet the stringent requirements of high-precision applications.

Practical Applications of High-Precision Height Measurements

Beyond the theoretical underpinnings of GNSS height accuracy, the practical applications of high-precision height measurements are vast and impactful. These applications include:

Geodesy: Precise height measurements play a fundamental role in geodesy, contributing to the modeling of the Earth’s shape and gravity field. These measurements enable geodetic datum determination and geodetic infrastructure development (Heiskanen and Moritz, 1967; Torge, 2001).

Construction: The construction industry relies on accurate height measurements for activities such as site planning, building design, and the monitoring of construction progress. High-precision GNSS height measurements aid in ensuring the structural integrity of buildings and infrastructure (National Research Council, 2005).

Surveying and Land Management: Land surveyors heavily depend on GNSS height measurements for property boundary determination, cadastral mapping, and land-use planning. Precise height data is essential for resolving land disputes and managing land resources (Ghilani and Wolf, 2019).

Scientific Research: Scientific disciplines, including seismology, oceanography, and glaciology, rely on high-precision height measurements for monitoring geological and environmental changes. These measurements provide critical insights into processes such as sea level rise and tectonic plate movement (Blewitt et al., 2016; Melini et al., 2016).

Future Directions and Challenges

As GNSS technology continues to evolve, there are several directions and challenges that warrant attention in the quest for higher height accuracy:

Multi-Constellation GNSS: With the emergence of additional GNSS constellations, such as Galileo, BeiDou, and GLONASS, there is an opportunity to improve height accuracy by leveraging signals from multiple satellite systems. Combining signals from diverse constellations can enhance the availability and robustness of height measurements (Borre and Strang, 2012; Montenbruck et al., 2015).

Improved Signal Processing Techniques: Advancements in signal processing algorithms and software can further mitigate the impact of multipath effects and atmospheric disturbances on height accuracy. Research into more sophisticated error modeling and correction techniques is ongoing (Lestarquit et al., 2013).

Precise Point Positioning (PPP): PPP is an emerging technique that enables centimeter-level positioning accuracy without the need for a local base station. Continued research in PPP for height determination holds promise for simplifying high-precision GNSS measurements (Zhang et al., 2020).

Robustness in Challenging Environments: Achieving reliable height accuracy in challenging environments, such as urban canyons or dense forests, remains a formidable challenge. Developing specialized algorithms and hardware to address these scenarios is essential (Petovello et al., 2013).

Integration with Other Sensors: Integrating GNSS with other sensors, such as inertial measurement units (IMUs) and LiDAR, can enhance height accuracy in dynamic and complex environments. Sensor fusion techniques hold significant potential for improving height measurements (Törnqvist et al., 2017).

Standardization and Best Practices: The development of standardized procedures and best practices for height measurements is crucial to ensure consistency and comparability across different applications and industries (International Association of Geodesy, 2019).

Conclusion

In the realm of GNSS technology, height accuracy remains a dynamic and evolving field with profound implications for geodesy, construction, surveying, scientific research, and countless other applications. This review has shed light on the intricate factors that influence height accuracy in GNSS measurements, ranging from satellite geometry to atmospheric effects and receiver quality. It has also explored the array of techniques and technologies deployed to enhance height precision.

As GNSS technology continues to advance, addressing the challenges associated with height accuracy becomes increasingly vital. The adoption of multi-constellation GNSS, improved signal processing techniques, PPP, and robustness in challenging environments will play pivotal roles in pushing the boundaries of height accuracy. Moreover, the integration of GNSS with complementary sensor technologies and the establishment of standardized practices will further bolster the reliability and utility of high-precision height measurements.

In conclusion, the pursuit of height accuracy in GNSS is not merely a technical endeavor but a critical enabler of progress and innovation across diverse fields. As the world becomes increasingly reliant on precise geospatial data, the quest for more accurate height measurements in GNSS remains central to our collective pursuit of knowledge, safety, and sustainable development.

References

  1. Blewitt, G., Hammond, W. C., Kreemer, C., & Plag, H. P. (2016). GPS Continuously Operating Reference Stations and the Solid Earth Sciences. Eos, Transactions American Geophysical Union, 97.
  2. Borre, K., & Strang, G. (2012). Linear Algebra, Geodesy, and GPS. Wellesley-Cambridge Press.
  3. Collins, J. (2008). Understanding GPS: Principles and Applications (2nd ed.). Artech House.
  4. El-Rabbany, A. (2002). Introduction to GPS: The Global Positioning System. Artech House.
  5. Forsberg, R., Olesen, A. V., & Poder, K. (2017). Geoid Models. In Handbook of Geomathematics (pp. 173-208). Springer.
  6. Ghilani, C. D., & Wolf, P. R. (2019). Elementary Surveying: An Introduction to Geomatics (15th ed.). Pearson.
  7. Heiskanen, W. A., & Moritz, H. (1967). Physical Geodesy. Freeman.
  8. Hofmann-Wellenhof, B., Lichtenegger, H., & Collins, J. (2008). GNSS – Global Navigation Satellite Systems: GPS, GLONASS, Galileo, and more. Springer.
  9. Kaplan, E. D., & Hegarty, C. J. (2006). Understanding GPS: Principles and Applications (2nd ed.). Artech House.
  10. Langley, R. B. (1999). Dilution of precision. GPS World, 10(5), 52-59.
  11. Leica Geosystems. (2018). Understanding GPS/GNSS: Principles and Applications (White Paper). Retrieved from https://leica-geosystems.com/
  12. Leick, A., Rapoport, L., & Tatarnikov, D. (2015). GPS Satellite Surveying. Wiley.
  13. Lestarquit, L., Botteron, C., & Legrand, J. (2013). Mitigation of multipath effects on GNSS receivers by adaptive signal processing. Journal of Navigation, 66(2), 267-281.
  14. Melini, D., Teferle, F. N., & Hunegnaw, A. (2016). Monitoring Sea Level Rise: Ground-Based GNSS for Vertical Land Motion Measurements. GPS World.
  15. Misra, P., & Enge, P. (2006). Global Positioning System: Signals, Measurements, and Performance (2nd ed.). Ganga-Jamuna Press.
  16. Montenbruck, O., Steigenberger, P., Prange, L., Deng, Z., & Zhao, Q. (2015). The Multi-GNSS Experiment (MGEX) of the International GNSS Service (IGS) – Achievements, prospects and challenges. Advances in Space Research, 59(7), 1671-1697.
  17. National Research Council. (2005). Precise Geodetic Infrastructure: National Requirements for a Shared Resource. National Academies Press.
  18. Petovello, M. G., & Lachapelle, G. (2013). GNSS multipath mitigation techniques in urban canyons. In Indoor Positioning and Indoor Navigation (pp. 325-346). Springer.
  19. Rizos, C., & Monteban, M. (2009). Real-time kinematic (RTK) GPS. In Springer Handbook of Geographic Information (pp. 425-446). Springer.
  20. Teunissen, P. J. G. (2018). GNSS Positioning and the Role of Signal Multipath. In Handbook of Satellite Applications (pp. 243-262). Springer.
  21. Törnqvist, D., Carlsson, H., & Gustafsson, F. (2017). Sensor Fusion in Land-Based Navigation: Overview and Future Research Directions. IEEE Transactions on Intelligent Transportation Systems, 18(6), 1498-1508.
  22. Torge, W. (2001). Geodesy (3rd ed.). de Gruyter.
  23. Van Sickle, J. (2018). Basic GIS Coordinates (3rd ed.). CRC Press.
  24. Zhang, H., Zhang, B., & Li, P. (2020). Precise Point Positioning (PPP) in GNSS navigation: A comprehensive review. Remote Sensing, 12(17), 2718.
Suggestion for Citation:
Amerudin, S. (2023). Factors Affecting Height Accuracy in Global Navigation Satellite Systems (GNSS). [Online] Available at: https://people.utm.my/shahabuddin/?p=7099 (Accessed: 13 September 2023).
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Mata Angin – Jejak Sejarah di Langit Tanah Melayu

Sumber: Repictblog

Pernahkah anda memikirkan makna dan sejarah di sebalik arah mata angin? Dalam zaman kanak-kanak kita, mungkin kita terbiasa dengan anggapan bahawa ‘barat’ merujuk kepada ‘Bharat,’ nama kuno India, manakala ‘timur’ adalah merujuk kepada Laut Timor. Namun, sebenarnya, terdapat lebih banyak rahsia yang tersembunyi di dalam petunjuk ini di langit.

Tahukah anda bahawa ‘Barat’ dan ‘Timur’ sebenarnya adalah nama angin? Di Malaysia, kita kenal dengan baik monsun barat daya dan monsun timur laut. Walaupun ‘Barat’ dan ‘Timur’ mungkin kelihatan seperti penunjuk geografi, sebenarnya mereka adalah angin yang memberi nama kepada arah tersebut.

‘Barat,’ dalam konteks ini, ada yang berpendapat bahawa ia berasal daripada kata ‘sebarat,’ yang mungkin merujuk kepada sesuatu yang berat atau kuat. Inilah sebabnya mengapa kita sering mendengar tentang ‘ribut barat’ atau ‘sesat barat.’ Jika kita merenung dalam konteks bahasa Austronesia, ‘barat’ juga merujuk kepada ‘angin kencang.’ Monsun Barat Daya yang sering melanda pantai barat semenanjung Malaysia memang membawa angin kuat, bahkan kadang-kala disertai dengan ribut petir yang terkenal dengan sebutan ribut Sumatera.

Namun, apa pula yang terkandung di dalam ‘TIMUR’? Pasti terdapat makna tersirat yang menarik di sebalik penamaan ini. Pada zaman dahulu, ketika orang pertama kali memberi nama angin-angin ini, mereka mungkin merujuk kepada sifat-sifat angin tersebut. Contohnya, angin Barat sering kali dikaitkan dengan kekuatan atau ‘berat,’ oleh itu, ia mesti datang dari arah yang ‘berat’ atau ‘barat.’ Demikian juga dengan angin Timur, ia mesti datang dari arah yang ‘timur.’ Ini adalah logika yang sederhana yang mungkin digunakan oleh nenek moyang kita.

Ada juga teori yang mengatakan bahawa arah mata angin purba ini mungkin berdasarkan geografi Taiwan, tempat asal bahasa Austronesia. Walaupun teori ini menarik, pergerakan angin monsun tidak sentiasa mengikuti geografi tersebut. Tetapi kita tidak boleh menafikan bahawa pemilihan arah angin ini mungkin berkaitan dengan pandangan orang tempatan terhadap geografi mereka pada zaman itu.

Secara etimologi, perkataan ‘laut’ bermaksud ‘punca air,’ manakala ‘daya’ bermaksud ‘menuju ke hulu, darat, atau pedalaman.’ Mungkin ini merujuk kepada kekuatan atau ‘daya’ yang diperlukan untuk melawan arus yang menuju dari hulu ke hilir. Namun, mungkin juga terdapat makna lain yang belum ditemui yang menyertainya.

Kemudiannya, istilah ‘laut’ dan ‘daya’ digantikan dengan ‘Uttara’ (dari bahasa Sanskrit yang bermaksud ‘tempat tinggi’) dan Selatan, yang merujuk kepada Selat Melaka. Penamaan ini mengingatkan kita kepada asal usul peradaban Melayu purba, seperti Langkasuka dan Tanah Merah, sebelum peradaban ini berpindah ke Sumatera dan kemudian ke Melaka.

Peradaban ini sebenarnya merujuk kepada zaman peradaban maritim Orang Laut, yang bermula lebih awal daripada 400 tahun sebelum Masehi. Mereka adalah pahlawan laut yang memainkan peranan penting dalam membentuk sejarah awal kebudayaan kita.

Inilah cerita di sebalik arah mata angin yang mungkin jarang kita renungi. Ia adalah jejak sejarah yang menghubungkan kita dengan masa lalu yang kaya dengan kisah-kisah dan peristiwa-peristiwa yang menarik.

Disesuaikan dari sumber: FB Srikandi [Dayang Angin dari Lower Perak]

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Addressing Common Challenges in Creating Study Area Maps in Thesis Writing

Source: https://www.frontiersin.org/

By Shahabuddin Amerudin

Introduction

Geographic Information Systems (GIS) plays an indispensable role in various fields, including environmental science, urban planning, and public health. For GIS students at the Universiti Teknologi Malaysia (UTM), producing a high-quality study area map is a fundamental aspect of their thesis writing. However, this seemingly straightforward task can be surprisingly challenging, especially when it comes to fitting the map within the constraints of an A4 or B5 paper size. As a result, many students resort to using Google Maps as a basemap or backdrop image, rather than creating a map from scratch. In this article, we will delve into the common challenges students face in this regard, the limitations of using Google Maps as a solution, and alternative approaches to produce effective study area maps.

Challenges Faced by GIS Students

  1. Limited Space:
    • Complex Study Areas: GIS projects often involve the analysis of extensive geographical regions or intricate study areas. Trying to fit all the relevant data into the confines of A4 or B5 paper sizes can be highly challenging. This limitation may lead to the omission of crucial details or areas, potentially affecting the comprehensiveness of the study.
    • Scale Issues: Reducing a large-scale map to fit on a smaller sheet can result in a significant reduction in detail. This can hinder the ability to convey the spatial relationships and nuances within the study area accurately.
    • Map Overcrowding: When students attempt to include too much information within the limited space, maps can become cluttered and confusing, making it difficult for readers to interpret the data effectively.
  2. Clarity and Readability:
    • Text and Symbols: Shrinking a map to fit a smaller paper size can cause text and symbols to become too small to read comfortably. This can lead to frustration for readers who struggle to discern important information.
    • Loss of Context: When maps lose clarity during scaling, the overall context and significance of certain features can be lost. This might result in the misinterpretation of the data or research findings.
    • Color and Contrast: Maintaining effective color contrast and choosing colors that work well when printed can be a challenge. Poor choices can reduce map readability, particularly for readers with visual impairments.
  3. Data Sourcing and Integration:
    • Data Availability: Locating relevant and up-to-date GIS data can be a time-consuming process. Data may be scattered across various sources, and students may need to request or purchase datasets, which can pose logistical challenges.
    • Data Compatibility: Different datasets may have varying formats, projections, and scales. Integrating these datasets into a cohesive map can be technically complex and may require advanced GIS skills.
    • Data Quality: Ensuring that data sources are accurate and reliable is essential. Students must critically assess data quality and be aware of potential biases or errors that can affect the outcomes of their research.
  4. Licensing and Copyright Issues:
    • Legal Consequences: Using Google Maps or other proprietary mapping services as a basemap without proper licensing or permissions can lead to legal repercussions. This can result in the removal of the map from the thesis, fines, or other legal actions against the student.
    • Ethical Considerations: Encouraging students to respect copyright and licensing agreements fosters ethical research practices and instills a sense of responsibility regarding data usage.
  5. Limited Customization:
    • Tailoring Maps to Research: Every GIS project has unique requirements. Pre-designed basemaps like Google Maps may not offer the level of customization needed to convey specific research findings accurately. Customization is crucial to align the map with the study’s goals and objectives.
    • Visual Consistency: Customization allows students to maintain visual consistency with their thesis while accommodating specific mapping needs. This consistency enhances the overall quality and professionalism of the research.

Limitations of Using Google Maps

While Google Maps can be a convenient solution for including geographic context in a thesis, it comes with several limitations that hinder its suitability for academic research:

  1. Limited Control:
    • Customization Constraints: Google Maps offers a one-size-fits-all approach when it comes to map design. Students have limited control over the color schemes, symbols, fonts, and labeling. This lack of customization can make it challenging to tailor the map to the specific requirements of a thesis or research project.
    • Visual Consistency: Academic research often requires a high level of visual consistency throughout the thesis. Google Maps’ limited customization options can hinder the ability to maintain a consistent visual style that aligns with the overall thesis design.
    • Representation Challenges: Certain geographic features or phenomena may require specialized symbols or visual cues that Google Maps cannot provide. This can result in a less accurate representation of the research findings.
  2. Print Quality:
    • Resolution Issues: When students print Google Maps on paper, they may encounter issues related to resolution. Text and symbols can become blurry or pixelated, particularly when the map is scaled down to fit within the confines of A4 or B5 paper sizes. This reduction in print quality can compromise the clarity and readability of the map.
    • Scaling Challenges: Google Maps is designed primarily for online and digital viewing, not for high-quality print. As a result, it may not easily adapt to the demands of print production, leading to suboptimal print results.
  3. Data Ownership:
    • Lack of Data Control: Google Maps uses its own data sources, and students have little control over the data displayed on the map. Google may update or change these data sources without notice. This lack of control can be problematic for academic research, where data accuracy and consistency are crucial.
    • Dependency on External Data: Students relying on Google Maps may find themselves at the mercy of Google’s data infrastructure. Changes or interruptions in data access can disrupt the research process and compromise the project’s integrity.
  4. Commercial Use:
    • Terms of Service Restrictions: Google Maps’ terms of service are primarily designed for personal use and may impose limitations on academic or commercial projects. Students using Google Maps for thesis work could unintentionally violate these terms, potentially leading to legal issues or the removal of their maps from their research.
    • Licensing Considerations: Academic research often requires a clear understanding of licensing agreements and compliance with copyright laws. Using Google Maps without proper licensing can raise ethical and legal concerns.
  5. Data Privacy:
    • Privacy Risks: Students must exercise caution when using Google Maps for academic purposes, especially when dealing with sensitive or private data. The public nature of online mapping platforms like Google Maps means that inadvertently sharing private information can lead to privacy breaches or unauthorized access to sensitive data.

Solutions for Creating Effective Study Area Maps

  1. Open Source GIS Software:
    • Advantages: Open-source GIS software like QGIS provides students with a powerful set of tools to create maps that meet their research requirements. It offers greater control over map design, including customizing colors, symbols, labeling, and map layout.
    • Flexibility: QGIS and similar open-source platforms allow students to start from scratch, giving them complete control over the map’s content and design. This flexibility is particularly valuable when dealing with complex study areas or specialized research needs.
    • Skill Development: By using open-source GIS software, students can enhance their GIS skills, which are valuable in both academic and professional settings. These skills include data manipulation, spatial analysis, and cartographic design.
  2. Custom Data Collection:
    • Data Accuracy: Advising students to collect their own data or collaborate with relevant organizations ensures that they have access to accurate and up-to-date spatial data. This is especially important for research that demands precise and current information.
    • Tailored Data: Custom data collection allows students to gather information specific to their research objectives. They can design data collection methods that align with their study’s unique needs, ensuring data relevance and quality.
    • Real-World Experience: Engaging in data collection projects provides students with practical, hands-on experience in data acquisition and fieldwork, enhancing their research skills and understanding of geospatial processes.
  3. Custom Basemaps:
    • Greater Control: Creating custom basemaps using sources like OpenStreetMap empowers students to exercise complete control over the map’s appearance. They can customize features, colors, and labels to align with their research objectives and aesthetics.
    • Flexibility: OpenStreetMap and similar platforms offer a wide range of data layers and styles, enabling students to adapt the basemap to various study area types, from urban to rural to environmental contexts.
    • Compliance: Using open-source basemaps eliminates concerns about licensing and copyright violations, ensuring that students can confidently use their maps for academic research and publication.
  4. Cartographic Design:
    • Clarity and Readability: Emphasizing cartographic design principles helps students enhance map clarity and readability. This includes selecting appropriate fonts, font sizes, and label placements to ensure that information is easily understood.
    • Visual Hierarchy: Educating students about creating a visual hierarchy on their maps helps them highlight key information and guide the viewer’s attention to critical elements. This improves the map’s effectiveness in conveying research findings.
    • Consistency: Consistent design elements such as scale bars, legends, and north arrows not only improve map quality but also contribute to the overall professionalism of the thesis.
  5. Map Layout Optimization:
    • Paper Size Considerations: Teaching students how to optimize map layouts for A4 or B5 paper sizes is crucial. This may involve choosing an appropriate map projection, adjusting scale, and carefully selecting what to include on the map to balance detail and clarity.
    • Whitespace Utilization: Proper use of whitespace on the map and in the layout design can enhance visual appeal and readability. It helps prevent overcrowding and maintains a clean, organized appearance.
  6. Geospatial Data Ethics:
    • Legal and Ethical Awareness: Educating students about geospatial data ethics ensures that they are aware of the legal and ethical considerations surrounding data collection, usage, and dissemination. This knowledge is essential for conducting research responsibly and respecting privacy and copyright laws.
    • Data Ownership: Understanding data ownership and licensing agreements helps students avoid potential legal issues when using data from external sources. It encourages them to seek permission or use data with the appropriate licenses.

Conclusion

Creating an effective study area map for a GIS thesis is a challenging but essential task. While using Google Maps as a basemap may seem like a convenient solution, it comes with limitations and potential pitfalls that students should be aware of. Encouraging students to explore open-source GIS software, collect their own data, and focus on cartographic design principles will empower them to create high-quality study area maps that enhance the overall quality of their research. By addressing these challenges and providing guidance on best practices, GIS educators at UTM can ensure that their students develop the skills needed to produce compelling and informative maps in their academic work.

Suggestion for Citation:
Amerudin, S. (2023). Addressing Common Challenges in Creating Study Area Maps in Thesis Writing. [Online] Available at: https://people.utm.my/shahabuddin/?p=7079 (Accessed: 11 September 2023).
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Creating an Effective Study Area Map in GIS

Source: https://open.maricopa.edu
Source: https://open.maricopa.edu

By Shahabuddin Amerudin

Introduction

Geographic Information Systems (GIS) play a pivotal role in modern spatial analysis, helping us understand and visualize complex spatial data. Among the fundamental tasks in GIS, creating a study area map is a common challenge that students often encounter. A well-designed study area map is crucial for any GIS project, as it serves as the foundation for data analysis, decision-making, and communication. In this article, we will discuss the importance of a good study area map and the criteria and strategies needed to design one effectively.

The Importance of a Good Study Area Map

A study area map is more than just a visual representation of geographical boundaries; it is a key component of a GIS project that influences the quality and credibility of the analysis. A well-designed study area map:

  1. Defines the Scope:
    Clearly delineates the boundaries of the study area, ensuring that researchers and stakeholders understand the geographic extent of the project.
  2. Enhances Data Selection:
    Helps in selecting and collecting relevant spatial data, ensuring that only pertinent information is included.
  3. Supports Analysis:
    Provides a foundation for spatial analysis, allowing researchers to perform meaningful operations like overlay, proximity analysis, and spatial querying.
  4. Communicates:
    Findings: Acts as a visual communication tool to convey research findings, making it easier for non-GIS experts to grasp the study’s results.

Criteria for Designing a Good Study Area Map

To design an effective study area map, one must consider several criteria:

  1. Clarity and Simplicity:
    • Keep the map simple and uncluttered, avoiding unnecessary elements that can distract from the main focus.
    • Use clear and easy-to-understand symbols, colors, and labels.
  2. Scale and Resolution:
    • Choose an appropriate scale and resolution that suit the study’s purpose. A smaller scale may be required for regional studies, while a larger scale may be needed for detailed local analysis.
  3. Geographic Extent:
    • Clearly define the geographic extent of the study area using a well-defined boundary such as administrative borders, physical features, or coordinates.
  4. Data Sources and Attribution:
    • Accurately cite the sources of spatial data used in the map.
    • Provide attribution for third-party data if necessary, complying with copyright and licensing agreements.
  5. Legend and Symbols:
    • Include a legend that explains the meaning of symbols, colors, and any other map elements.
    • Ensure consistency in symbol usage throughout the map.
  6. Spatial Reference:
    • Use a consistent spatial reference system (e.g., latitude and longitude or a projected coordinate system) to ensure accurate georeferencing.
  7. Contextual Information:
    • Provide contextual information that helps viewers understand the significance of the study area, such as its geographical location, relevance, and any unique features.
  8. Data Quality:
    • Ensure that the spatial data used is accurate, up-to-date, and relevant to the research question.
  9. Cartographic Design:
    • Apply cartographic principles, such as balance, hierarchy, and visual hierarchy, to create an aesthetically pleasing map.

Solutions for Designing an Effective Study Area Map

  1. Planning and Research:
    Before starting the map design, conduct thorough research to understand the study area’s characteristics, available data, and the specific requirements of your project. Planning is crucial to determine the appropriate scale, data sources, and map elements.
  2. Data Preparation:
    Ensure that all spatial data used in the map are properly prepared and georeferenced. Data preprocessing, cleaning, and transformation are essential steps to guarantee data accuracy.
  3. Software Proficiency:
    Gain proficiency in GIS software (e.g., ArcGIS, QGIS) to effectively create and manipulate spatial data. Familiarity with the software’s cartographic tools will enable you to design visually appealing maps.
  4. Consult Cartographic Guidelines:
    Consult cartographic guidelines and best practices to ensure that your map adheres to established design principles. These guidelines can help you make informed decisions about color schemes, fonts, and layout.
  5. Iterative Design:
    Map design is often an iterative process. Don’t hesitate to revise and refine your study area map as you progress through your project. Solicit feedback from peers or mentors to improve its quality.
  6. User-Centered Approach:
    Consider the needs and preferences of your target audience when designing the map. Tailor the map’s content and design to make it accessible and understandable to your intended users.
  7. Document Your Work:
    Keep a record of the data sources, software tools, and design choices you make during the map creation process. Proper documentation is essential for transparency and reproducibility.

Conclusion

Designing an effective study area map is a critical skill for GIS students and professionals alike. A well-designed map not only defines the scope of a project but also enhances data selection, supports spatial analysis, and communicates research findings effectively. By adhering to the criteria and solutions outlined in this article, GIS students can overcome the challenges associated with creating a study area map and contribute to more meaningful and impactful spatial analysis and research. Remember that practice and continuous learning are key to mastering the art and science of cartography in GIS.

Further Reading

  1. Longley, P. A., Goodchild, M. F., Maguire, D. J., & Rhind, D. W. (2015). Geographic Information Science and Systems. John Wiley & Sons.
  2. Slocum, T. A., McMaster, R. B., Kessler, F. C., & Howard, H. H. (2009). Thematic Cartography and Geovisualization (3rd ed.). Pearson Prentice Hall.
  3. Peterson, M. P. (2011). Interactive and Animated Cartography. Pearson Prentice Hall.
  4. Bolstad, P. (2019). GIS Fundamentals: A First Text on Geographic Information Systems (6th ed.). Eider Press.
  5. Robinson, A. H., Morrison, J. L., Muehrcke, P. C., Kimerling, A. J., & Guptill, S. C. (2015). Elements of Cartography (7th ed.). Wiley.
  6. Brewer, C. A. (2015). Designing Better Maps: A Guide for GIS Users. Esri Press.
  7. Dent, B. D., & Torguson, J. S. (2007). Cartography: Thematic Map Design (6th ed.). McGraw-Hill.
  8. Esri. (n.d.). ArcGIS Desktop Help. Retrieved from https://desktop.arcgis.com/en/
  9. QGIS Development Team. (n.d.). QGIS User Guide. Retrieved from https://docs.qgis.org/3.16/en/docs/user_manual/
Suggestion for Citation:
Amerudin, S. (2023). Creating an Effective Study Area Map in GIS. [Online] Available at: https://people.utm.my/shahabuddin/?p=7074 (Accessed: 11 September 2023).