model

Carta Benner Cycle

Memahami Kitaran Ekonomi dengan Benner Cycle

By • • Knowledge, Other, Personal, Public • , , , • 3 minutes of reading

Benner Cycle mungkin kelihatan seperti istilah yang berkaitan dengan Profesor Bruce Banner, tetapi sebenarnya ia dicipta oleh seorang petani dan pelabur bernama Samuel T. Benner pada tahun 1875. Model ini muncul selepas Benner mengalami kerugian besar akibat Kemelesetan Besar tahun 1873. Untuk memahami lebih mendalam tentang dinamika ekonomi, Benner meneliti data sejarah dan mendapati corak berulang dalam ekonomi, yang membentuk carta yang dikenali sebagai Benner Cycle. Carta Benner Cycle terbahagi kepada tiga bahagian utama, masing-masing mewakili fasa yang berbeza dalam kitaran ekonomi. Bahagian pertama, Bahagian A, merujuk kepada tahun-tahun di mana panik ekonomi berlaku dan dijangka akan berulang. Contoh tahun-tahun dalam […]

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sinkhole

From AHP to GWR in Sinkhole Susceptibility Modeling with Advanced GIS Methods

By • • Jurnal, Knowledge, Project, Research • , , , , • 5 minutes of reading

Introduction Rosdi et al. (2017) made significant strides in understanding sinkhole susceptibility in Kuala Lumpur and Ampang Jaya by combining Geographic Information Systems (GIS) with the Analytical Hierarchical Process (AHP). Their work laid a solid foundation for assessing sinkhole risk, but there remains an opportunity to refine and enhance these models using more advanced spatial analysis techniques. One promising approach is Geographically Weighted Regression (GWR), which has the potential to improve both the accuracy and granularity of sinkhole susceptibility assessments. This article examines how incorporating GWR, along with other advanced GIS methodologies, could lead to more precise and insightful analyses

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Sinkhole Risk Mapping with GIS and AHP: Kuala Lumpur and Ampang Jaya Case Study

Understanding Sinkhole Susceptibility in Kuala Lumpur and Ampang Jaya: A GIS and AHP-Based Approach

By • • Jurnal, Knowledge, Public, Research • , , , , , , • 4 minutes of reading

Introduction Sinkholes are a significant geohazard, particularly in urban areas like Kuala Lumpur and Ampang Jaya, where the increasing number of incidents has raised concerns over public safety and urban infrastructure. Since 1968, the Klang Valley region has witnessed a growing frequency of sinkholes, posing serious threats to human lives, assets, and structures, particularly in Malaysia’s bustling capital. To address this issue, Rosdi et al. (2017) conducted a study that employed Geographic Information Systems (GIS) integrated with the Analytical Hierarchical Process (AHP) to develop a Sinkhole Hazard Model (SHM). This article discusses the findings of this study, the methods used,

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GeoAI and planning

Advancing Urban Planning with GeoAI through Global Street Network Analysis

By • • Jurnal, Knowledge, Project, Research, Teaching • , , , , • 7 minutes of reading

By Shahabuddin Amerudin Introduction Geographic Artificial Intelligence (GeoAI) integrates Geographic Information Systems (GIS) with artificial intelligence (AI), offering advanced capabilities for urban planning and development. This convergence allows for a more nuanced understanding of spatial dynamics and provides tools to address complex urban challenges. By harnessing GeoAI, urban planners can optimize infrastructure, manage resources more efficiently, and create sustainable urban environments. This article delves into how GeoAI can be applied to enhance city planning by analyzing street network configurations across different global cities. Understanding GeoAI GeoAI represents the intersection of spatial data analysis and AI technologies, including machine learning and

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Assessment of Landslide Vulnerability

By • • Knowledge, Project, Public, Research • , , , • 9 minutes of reading

Introduction Assessment of landslide vulnerability involves determining the likelihood that a landslide will occur in a certain area, as well as the potential impact of such an event. This process typically includes the following steps: Identifying the potential landslide hazards in the area, such as steep slopes, areas with a history of landslides, and areas prone to heavy rainfall or erosion. Analyzing the susceptibility of the area to landslides, taking into account factors such as soil type, groundwater conditions, and land use practices. Evaluating the potential impact of a landslide on human and natural resources, such as buildings, infrastructure, and

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