Thesis, Dissertation and Project

Terminologies like thesis, dissertation and project are common in academic and research practice. Although, these terms are used synonymously by students and some faculty they have different implications. 

The word ‘dissertation’ is derived from the Latin word “dissertare” which means ‘to discuss’. Oxford Dictionary defines dissertation as ‘a long essay on a particular subject or topic especially written for a university degree or diploma’. In Merriam Webster dictionary, it is defined as “an extended usually written treatment of a subject; specifically: one submitted for a doctorate”. The Cambridge dictionary defines dissertation as “a long piece of writing on a particular subject, especially one that is done to receive a degree at college or university”. It is clear from these definitions that the emphasis in a dissertation is on a review and write up on a subject rather than the novelty of the research.

The origin of the word “thesis” comes from the Greek word “tithenai” which means “to place or to put forth”. The early Greek word “tithenai” metamorphosed into ‘thesis’ which in Greek refers “to put forth something” like a proposal. The Oxford English dictionary defines a thesis as “a long essay or dissertation involving personal research, written by a candidate for a university degree”. In Merriam Webster dictionary it is defined as a “dissertation embodying results of original research and especially substantiating a specific view”. The Cambridge dictionary defines a thesis as “a long piece of writing on a subject, especially one based on original research and done for a higher college or university degree”. In some countries, a dissertation is also referred to as a thesis. However, in contrast to dissertation thesis is an in-depth study of a topic that contributes novel information in the field of research.

The word project is derived from the Latin word “projectum” from the Latin verb “proicere” (before an action), which in turn comes from “pro” (precedence), and “iacere”(to do). Thus, the original meaning of the word “project” is to plan of something and not to the act of carrying out the plan. The Oxford English dictionary defines project as “a piece of research work undertaken by a school or college student”. In Merriam Webster dictionary, it is defined as a planned undertaking: such as a formulated piece of research. The Cambridge dictionary defines a project as “a study of a particular subject done over a period, especially by students”.

The word project is often used in the engineering field and various government plans. A research project can be a short-term (less than a year) or long-term project. A short-term research project is usually undertaken by the undergraduate students and a long-term project is usually undertaken by faculty working in research institutes. A short-term research project is an abbreviated form of the dissertation where the focus is on research methodology and not the outcome of the research. In the long-term research project, the focus is on the novelty of research in addition to the methodology like a thesis.

Source: Subhash Chandra Parija and Vikram Kate (2018). Thesis, Dissertation and Project in Thesis Writing for Master’s and Ph.D. Program. Springer Nature Singaporer Pte Ltd.

10 Python Libraries for GIS and Mapping

Python Libraries for GIS and Mapping

Python libraries are the ultimate extension in GIS because it allows you to boost its core functionality.

By using Python libraries, you can break out of the mould that is GIS and dive into some serious data science.

There are 200+ standard libraries in Python. But there are thousands of third-party libraries too. So, it’s endless how far you can take it.

Today, it’s all about Python libraries in GIS. Specifically, what are the most popular Python packages that GIS professionals use today? Let’s get started.

First, why even use Python libraries for GIS?

Have you ever noticed how GIS is missing that one capability you need it to do? Because no GIS software can do it all, Python libraries can add that extra functionality you need.

Put simply, a Python library is code someone else has written to make life easier for the rest of us. Developers have written open libraries for machine learning, reporting, graphing and almost everything in Python.

If you want this extra functionality, you can leverage those libraries by importing them in your Python script. From here, you can call functions that aren’t natively part of your core GIS software.

PRO TIP: Use pip to install and manage your packages in Python

Python Libraries for GIS

If you’re going to build an all-star team for GIS Python libraries, this would be it. They all help you go beyond the typical managing, analyzing and visualizing of spatial data. That is the true definition of a geographic information system.

1 Arcpy

If you use Esri ArcGIS, then you’re probably familiar with the ArcPy library. ArcPy is meant for geoprocessing operations. But it’s not only for spatial analysis, but it’s also for data conversion, management and map production with Esri ArcGIS.

2 Geopandas

Geopandas is like pandas meet GIS. But instead of straight-forward tabular analysis, the geopandas library adds a geographic component. For overlay operations, geopandas uses Fiona and Shapely, which are Python libraries of their own.


The GDAL/OGR library is used for translating between GIS formats and extensions. QGIS, ArcGIS, ERDAS, ENVI and GRASS GIS and almost all GIS software use it for translation in some way. At this time, GDAL/OGR supports 97 vector and 162 raster drivers.

GIS Formats Conversions


The RSGISLib library is a set of remote sensing tools for raster processing and analysis. To name a few, it classifies, filters and performs statistics on imagery. My personal favourite is the module for object-based segmentation and classification (GEOBIA).

5 PyProj

The main purpose of the PyProj library is how it works with spatial referencing systems. It can project and transform coordinates with a range of geographic reference systems. PyProj can also perform geodetic calculations and distances for any given datum.

Python Libraries for Data Science

Data science extracts insights from data. It takes data and tries to make sense of it, such as by plotting it graphically or using machine learning. This list of Python libraries can do exactly this for you.

6 NumPy

Numerical Python (NumPy library) takes your attribute table and puts it in a structured array. Once it’s in a structured array, it’s much faster for any scientific computing. One of the best things about it is how you can work with other Python libraries like SciPy for heavy statistical operations.

7 Pandas

The Pandas library is immensely popular for data wrangling. It’s not only for statisticians. But it’s incredibly useful in GIS too. Computational performance is key for pandas. The success of Pandas lies in its data frame. Data frames are optimized to work with big data. They’re optimized to such a point that it’s something that Microsoft Excel wouldn’t even be able to handle.

8 Matplotlib

When you’re working with thousands of data points, sometimes the best thing to do is plot it all out. Enter matplotlib. Statisticians use the matplotlib library for visual display. Matplotlib does it all. It plots graphs, charts and maps. Even with big data, it’s decent at crunching numbers.


9 Scikit

Lately, machine learning has been all the buzz. And with good reason. Scikit is a Python library that enables machine learning. It’s built in NumPy, SciPy and matplotlib. So, if you want to do any data mining, classification or ML prediction, the Scikit library is a decent choice.

10 Re (regular expressions)

Regular expressions (Re) are the ultimate filtering tool. When there’s a specific string you want to hunt down in a table, this is your go-to library. But you can take it a bit further like detecting, extracting and replacing with pattern matching.

11 ReportLab

ReportLab is one of the most satisfying libraries in this list. I say this because GIS often lacks sufficient reporting capabilities. Especially, if you want to create a report template, this is a fabulous option. I don’t know why the ReportLab library falls a bit off the radar because it shouldn’t.

PRO TIP: If you need a quick and dirty list of functions for Python libraries, check out DataCamp’s Cheat Sheets.


Alternative measures of terrain distance

This figure provides a simple cross-sectional illustration of the kind of issues that arise. We wish to determine the distance separating points A and B. If A and B are not too far apart (e.g. less than 10 km) we could use a high precision laser rangefinder to establish the slope distance between A and B, assuming there is no atmospheric distortion. In practice, there will be some distortion and the laser wave path will need to be adjusted in order to provide an estimated slope path distance. This, in turn, will require further adjustment if it is to be referenced to a common datum or a level terrain surface. In each case, the distance recorded between A and B will be different.

From the figure, it is clear that none of these distances corresponds to the actual distance across the terrain surface along a fixed transect, nor to a distance adjusted or computed to reflect the particular model of the Earth or region of the globe we are using. In some cases, these differences will be small, whilst in other, they may be highly significant.

Source: Smith, Goodchild and Longley (2020). Geospatial Analysis. The Winchelsea Press.


Kunjungan dari bekas pelajar – Sdri. Azne Hazira bt. Sukor

Hari ini seorang bekas pelajar PSM saya, Sdri. Azne Hazira bt Sukor telah datang ke UTM Johor Bahru di atas urusan pengesahan dokumen dan mengambil kesempatan untuk menziarahi saya. Beliau sekarang bekerja di Perunding Ukur DC di Subang dan sebelum itu berkhidmat di Geoinfo Services, Taman Melawati, Kuala Lumpur selepas sahaja tamat pengajian di dalam program Sarjana Muda Sains (Geoinformatik).

Pada sesi pengajian 2018/2019 beliau telah berjaya menyiapkan sebuah thesis Projek Sarjana Muda bertajuk “Determination of Potential Water Pipeline Bursting using Stochastic Approach in Geographical Information System”. Di dalam projek PSM tersebut beliau telah mendapat kerjasama daripada Pejabat Harta Bina (PHB) bagi membekalkan data awalan dan Sekolah Kejuruteraan Awam, Fakulti Kejuruteraan bagi khidmat nasihat tentang proses pengagihan bekalan paip air di kawasan UTM.

Selamat maju jaya diucapkan kepada beliau.


Merujuk kepada perkembangan semasa dan maklumat daripada pihak Kementerian Kesihatan Malaysia (KKM), Universiti Teknologi Malaysia (UTM) turut mengambil langkah-langkah pengawasan wabak COVID-19 sejak ianya dikesan bagi memastikan UTM bebas daripada wabak tersebut.

Sehubungan itu, pihak Pengurusan Universiti telah mengeluarkan Pekeliling Pentadbiran Bil 10/2020 bertarikh 29 Februari 2020 menasihatkan staf dan pelajar (termasuk UTM Mobility (outbound)) untuk menangguhkan perjalanan ke China dan negara-negara yang tersenarai oleh pihak KKM iaitu Korea Selatan, Jepun, Iran dan Itali. Bagi pelajar kanan, permohonan penangguhan pengajian yang disebabkan oleh COVID-19 diputuskan juga sebagai tidak termasuk dalam kiraan semester pengajian.  Keputusan ini terpakai sehingga keadaan kembali normal berdasarkan pengesahan pihak KKM.

Pihak Universiti juga sedia maklum terdapat pelajar antarabangsa baharu yang telah menerima tawaran mengikuti pengajian dari negara-negara yang tersenarai. Bakal pelajar (termasuk UTM Mobility (inbound)) yang belum tiba di Malaysia adalah dinasihatkan supaya menangguhkan pendaftaran masing-masing.

Semua pihak yang terlibat adalah diminta mengambil maklum dan tindakan mengenainya.

Sekian, terima kasih

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