All Projects & Portfolio

A complete collection of GIS, remote sensing, cartography, and spatial analysis projects developed during academic and research work.

CSA Zone Map - Maha Season

Climate-Smart Agricultural Zone Delineation

Anuradhapura District, Sri Lanka

Geospatial delineation of climate-smart agricultural zones using multi-temporal remote sensing indices and GIS-based multi-criteria analysis.

Data

Landsat 8/9, Sentinel-2 LULC, CHIRPS & Sri Lanka Meteorology Rainfall, Soil Type Map, SRTM DEM, Irrigation Network, Anuradhapura Boundary

Methods

NDVI, EVI, SAVI, NDWI, NDDI, SMI, LST, Rainfall & Slope Analysis, Soil & Land Use, Irrigation Access, AHP-based MCDA, Weighted Overlay

Software

ArcGIS Pro, Google Earth Engine, MS Excel

Outcome

Seasonal CSA zone maps supporting drought resilience planning

What I Learned: Integrated remote sensing indices with GIS-based decision models to support climate-smart agricultural planning.
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Pre- and Post-Flood Analysis Using SAR Imagery - Matara

Pre- & Post-Flood Analysis Using SAR Imagery

Matara District, Sri Lanka

Comparative flood extent and impact assessment of the October 8, 2023 flood event using pre- and post-flood Sentinel-1 SAR imagery and GIS-based spatial analysis.

Data

Sentinel-1 SAR (Pre-flood: 26 Sept 2023, Post-flood: 08 Oct 2023), Land Use/Land Cover data, DEM, Esri infrastructure datasets

Methods

SAR preprocessing (radiometric & terrain correction, speckle filtering), threshold-based water classification, change detection, flood extent mapping, land use & infrastructure impact analysis

Software

ArcGIS Pro, ENVI (SAR Processing)

Outcome

Flood extent maps and impact assessment identifying affected land use and critical infrastructure for disaster management planning

What I Learned: Applied SAR-based change detection and GIS spatial analysis to accurately map flood inundation and assess impacts under adverse weather conditions.
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Spatial Correlation Analysis of Vegetation, Chlorophyll, and Water Availability

Spatial Correlation Analysis of Vegetation Health, Chlorophyll Content, and Water Availability

Galenbindunuwewa DS Division, Anuradhapura District, Sri Lanka

Assessment of vegetation health, chlorophyll concentration, and water availability using Sentinel-2 remote sensing indices and spatial correlation analysis to understand ecological interactions and environmental stress patterns.

Data

Sentinel-2 Multispectral Imagery (Band 3, Band 4, Band 8, Band 11), Galenbindunuwewa DS Boundary

Methods

NDVI, Green Chlorophyll Index (GCI), Land Surface Water Index (LSWI), Thematic Mapping, Random Sampling (100 Points), Pearson Correlation Analysis, Scatter Plots & Trendlines

Software

ArcGIS Pro, Microsoft Excel

Outcome

Identified strong NDVI–GCI correlation (R² = 0.94) and moderate NDVI–LSWI relationship (R² = 0.227), highlighting spatial patterns of vegetation health, chlorophyll content, and water stress.

What I Learned: Applied spatial statistics and remote sensing indices to interpret ecological relationships, enhancing skills in vegetation analysis, correlation mapping, and environmental assessment.
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Hotspot Analysis of Chronic Kidney Disease in Anuradhapura and Polonnaruwa Districts

Hotspot Analysis of Chronic Kidney Disease (CKD)

Anuradhapura & Polonnaruwa Districts, Sri Lanka

This project presents a spatial hotspot analysis of Chronic Kidney Disease (CKD) distribution across the Anuradhapura and Polonnaruwa districts for two time periods (2014–2016 and 2017–2020). The analysis identifies statistically significant hot and cold spots using confidence levels of 90%, 95%, and 99%, revealing temporal shifts in CKD concentration patterns and high-risk zones. The outputs support public health planning, disease surveillance, and targeted intervention strategies.

Data

CKD patient records aggregated by Divisional Secretariat, administrative boundaries, and base map layers (National Renal Disease Prevention and Research Unit)

Methods

Spatial data preprocessing, aggregation by DS division, Getis-Ord Gi* hotspot analysis, and temporal comparison

Software

QGIS for spatial analysis, hotspot modeling, and professional map layout design

Output

Bi-temporal hotspot maps with confidence levels, legend, scale bar, north arrow, and location inset map

What I Learned: Applied spatial statistics for public health analysis, interpreted hotspot confidence levels, and improved skills in temporal GIS visualization and cartographic communication.
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Comprehensive Spatial and Statistical Analysis of Dengue Distribution in Colombo City

Comprehensive Spatial and Statistical Analysis of Dengue Distribution

Colombo City, Sri Lanka

This project presents a comprehensive GIS-based analysis of dengue distribution in Colombo City by integrating spatial statistics and density-based analytical methods. The study examines spatial patterns, clustering behavior, and directional trends of dengue cases using multiple geospatial techniques. Central tendency and dispersion were analyzed using Mean Center, Median Center, Standard Distance, and Standard Deviational Ellipse, while disease concentration and hotspot patterns were explored through Kernel Density, Point Density, Nearest Neighbor Analysis, and K-function analysis. The outputs support evidence-based public health planning and targeted dengue control strategies in urban environments.

Data

Secondary dengue patient data, mosquito breeding site data, Colombo city administrative boundaries, and land use datasets

Methods

Mean center, median center, standard distance, standard deviational ellipse, kernel density, point density, nearest neighbor analysis, and multi-distance K-function analysis

Software

ArcGIS 10.8 – Spatial Statistics Tools and Spatial Analyst Extension

Output

Dengue distribution maps, density maps, clustering analysis maps, directional ellipses, statistical graphs, and land use overlays

What I Learned: Integrated multiple spatial analysis techniques to assess disease distribution, interpreted clustering and dispersion statistics, and strengthened GIS-based public health decision-making and cartographic visualization skills.
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3D Map Using LiDAR Data

3D Map Generation Using LiDAR Data

Oregon State University, Corvallis, OR, USA

Creation of high-resolution 3D maps using airborne LiDAR point cloud data to accurately represent terrain, buildings, and vegetation with real-world height and volume characteristics.

Data

Airborne LiDAR (.LAS) data from Oregon Department of Geology and Mineral Industries (DOGAMI) LiDAR Program, OpenTopography

Methods

LAS dataset creation, point cloud visualization, LAS statistics analysis, surface model generation (TIN), 3D object profiling, volume calculation

Software

ArcGIS Desktop 10.8 (ArcMap), ArcGIS ArcScene

Outcome

Realistic 3D maps highlighting accurate building structures, tree canopy cover, and terrain volume derived from LiDAR data

What I Learned: Processing LiDAR point cloud data and creating precise 3D surface models significantly improves spatial accuracy and visualization compared to conventional 3D mapping techniques.
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New Dams and Reservoirs in Sri Lanka Map

New Dams and Reservoirs Mapping

Sri Lanka (Nationwide)

Comprehensive GIS-based mapping of existing, under-construction, and proposed dams and reservoirs in Sri Lanka, integrating river basins, institutional responsibility, and development status to support national water resource planning.

Data

National dam & reservoir inventory, river basin boundaries, Sri Lanka administrative boundary, institutional records (ID, MASL, CEB, NWSDB, NPC), capacity and construction-year data

Methods

Data compilation & validation, attribute standardisation, spatial classification by status and organisation, river basin-wise analysis, cartographic visualisation

Software

ArcGIS Pro, MS Excel

Outcome

A national-level thematic map showing completed, under-construction, and proposed dams and reservoirs by managing organisation and river basin

What I Learned: Practical experience in national-scale water resources mapping, data harmonisation across multiple institutions, and professional cartographic presentation during my internship at the Irrigation Department.
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Landuse of Yatinuwara DS Division

Land Use Mapping of Yatinuwara DS Division

Yatinuwara Divisional Secretariat Division, Kandy District, Sri Lanka

This project presents a detailed land use map of the Yatinuwara Divisional Secretariat Division, illustrating the spatial distribution of major land use categories such as paddy, forest, tea, rubber, homesteads, scrub land, rock outcrops, streams, and tanks. The map supports regional planning, environmental assessment, and land management decision-making.

Data

1:50,000 land use data, road network, railways, hydrology and administrative boundaries (Survey Department of Sri Lanka)

Methods

Data preprocessing, feature classification, cartographic symbolization, and map composition

Software

ArcGIS Desktop for spatial editing and map layout design

Output

A thematic land use map with legend, scale bar, north arrow, and settlement labeling

What I Learned: Improved thematic mapping skills, land use classification understanding, and professional cartographic layout design following national mapping standards.
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3D Urban Model created using CityEngine

3D Urban Planning with CityEngine

Academic Urban Area (Demonstration Model)

A procedural 3D city modeling project developed using Esri CityEngine to explore urban form, building patterns, and street networks in the context of GIS-based urban planning and design.

Data

Base maps, road network data, land parcel boundaries, and procedural CGA rules

Methods

Spatial data preparation, procedural rule definition, 3D building generation, and visual evaluation of urban form

Software

Esri CityEngine

Outcome

A simplified 3D urban model demonstrating the application of procedural GIS techniques for urban planning visualization

Key Learning Outcomes: Application of procedural modeling concepts in 3D GIS, visualization of urban design scenarios, and understanding the role of CityEngine in planning workflows.
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Satellite Image Classification - Galenbindunuwewa DS Division

Satellite Image Classification (LULC Mapping)

Galenbindunuwewa DS Division, Anuradhapura District, Sri Lanka

Supervised satellite image classification to map land use and land cover patterns using Landsat imagery, supporting regional land management and environmental monitoring.

Data

Landsat Satellite Imagery, DS Division Boundary, Reference Samples for Accuracy Assessment

Methods

Supervised Image Classification, Training Sample Collection, Land Cover Classification, Accuracy Assessment, Producer’s & User’s Accuracy, Kappa Statistics

Software

ArcGIS Pro

Outcome

Land use / land cover map identifying water, forest, shrubland, developed areas, wetlands, and planted/cultivated land with ~76% overall accuracy

What I Learned: Gained hands-on experience in supervised classification techniques, land cover interpretation, and accuracy assessment for reliable spatial decision-making.
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Allai Irrigation Scheme - Digitized Historical Contours

Historical Survey Sheet Digitization – Allai Scheme

Mutur Area, Trincomalee District, Sri Lanka

Digitization of historical engineering survey sheets to reconstruct high-density contour data for the Allai Irrigation Scheme using georeferenced analogue maps prepared between 1943 and 1955.

Data

71 historical engineering survey sheets (1943–1955), scanned analogue maps, reference basemaps

Methods

Georeferencing of historical maps, sheet-wise alignment, manual high-density contour digitization, topology-aware editing

Software

ArcGIS Pro

Outcome

GIS-ready contour dataset forming a terrain base layer for irrigation and engineering analysis

What I Learned: Handling legacy analogue survey data, performing precise manual digitization, and building foundational GIS datasets for large-scale irrigation schemes.
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Physical and Human Geography Maps - North Central Province

Physical & Human Geography Mapping – North Central Province

North Central Province, Sri Lanka

A comprehensive series of thematic maps illustrating the physical and human geographical characteristics of Sri Lanka’s North Central Province using GIS-based spatial analysis and cartographic techniques.

Data

Rainfall & temperature data, contour and elevation data, stream and waterbody layers, land cover data, soil and mineral resource maps, population statistics, urban centre data, ethnic composition data, administrative boundaries

Methods

Thematic map design, spatial data classification, vector and raster data processing, symbolization, layering, and map layout creation following cartographic principles

Software

ArcGIS Pro

Outcome

A structured map series representing climate, topography, natural resources, land cover, population distribution, urban centres, and ethnic patterns of the North Central Province

What I Learned: Improved thematic cartography skills, integration of physical and human geography datasets, and effective spatial storytelling through GIS-based map series design.
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Monthly Average Rainfall of Sri Lanka (January to December)

Monthly Average Rainfall Distribution (Jan–Dec)

Sri Lanka

Animated GIS visualisation of monthly average rainfall distribution across Sri Lanka from January to December, highlighting seasonal and spatial rainfall variability.

Data

Monthly average rainfall data (January–December) from the Meteorological Department of Sri Lanka, national administrative boundary data

Methods

Raster classification using a consistent legend, monthly map layout standardisation, temporal sequencing and animation creation

Software

ArcGIS Pro, image processing and GIF export tools

Outcome

A 12-month animated rainfall map supporting climate, hydrological and seasonal pattern analysis

What I Learned: Visualising spatio-temporal climate data through animated GIS maps improves interpretation of seasonal rainfall dynamics.
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Cartographic Representation of US Population Distribution

Cartographic Representation of US Population Distribution

United States of America

This project demonstrates multiple cartographic techniques used to visualize population distribution in the United States. The maps include Graduated Symbol, Proportional Symbol, Dot Density, and Choropleth (Graduated Color) methods. Each technique highlights population characteristics differently, enabling comparison of visual effectiveness, data interpretation, and spatial pattern recognition. The project emphasizes cartographic principles and appropriate symbolization for quantitative geographic data.

Data

United States population data aggregated by state-level administrative boundaries and national base map layers

Methods

Graduated symbol mapping, proportional symbol mapping, dot density mapping, and choropleth (graduated color) classification techniques

Software

ArcGIS Pro for data visualization, symbolization, and cartographically sound map layout design

Output

A series of population maps using different cartographic representation techniques, including legends, scale bars, north arrows, and clear visual hierarchy

What I Learned: Improved understanding of cartographic visualization methods, selection of appropriate mapping techniques for quantitative data, and effective communication of spatial patterns through map design.
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Population Distribution and Density of Tunis - 2024

Population Distribution & Density Analysis

Tunis Metropolitan Area, Tunisia

Spatial analysis of population distribution and population density at municipal level in Tunis for the year 2024, highlighting urban concentration patterns and demographic variation across municipalities.

Data

Municipal boundary data, population statistics (2024), administrative divisions, OpenStreetMap basemap

Methods

Choropleth mapping, population classification, density calculation (population per sq km), municipal-level spatial analysis

Software

ArcGIS Pro, GIS-based spatial analysis tools

Outcome

Population distribution map and population density map supporting urban planning and demographic assessment

What I Learned: Improved skills in demographic mapping, municipal-scale spatial analysis, and visual interpretation of population concentration patterns using GIS.
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District Population of Sri Lanka - 2012

District Population Distribution Map

Sri Lanka (District Level)

Choropleth map representing the spatial distribution of district-level population in Sri Lanka based on Census data for the year 2012, highlighting regional population concentration patterns.

Data

District Boundary Shapefile, Population Census Data (2012), Department of Census and Statistics, Sri Lanka

Methods

Attribute Table Join, Data Classification, Graduated Colour Symbology, Map Layout Design and Cartographic Elements

Software

ArcGIS Desktop (ArcMap)

Outcome

A clear visualisation of population density variations across districts to support planning and demographic analysis

What I Learned: Creating thematic population maps using census data, applying appropriate classification methods, and improving cartographic presentation for demographic analysis.
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Mean Income of Sri Lanka Map

Mean Income Distribution Analysis

Sri Lanka (District Level)

Spatial and statistical analysis of mean household income across Sri Lanka using district-level census data, visualised through thematic mapping and exploratory data analysis techniques.

Data

Mean household income data (district-wise), Administrative boundary shapefile of Sri Lanka from the Population and Census Department

Methods

Choropleth mapping, data classification, histogram analysis, scatter plot analysis, box plot visualisation, exploratory data analysis (EDA)

Software

ArcGIS Desktop, MS Excel

Outcome

Identification of spatial income disparities and regional economic patterns across Sri Lanka

What I Learned: Applied thematic mapping and statistical visualisation techniques to interpret socio-economic patterns and income inequality.
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Mean Expenditure of Sri Lanka Map

Mean Expenditure Distribution Analysis

Sri Lanka (District Level)

Spatial and statistical analysis of mean household expenditure across Sri Lanka using district-level census data. The study integrates thematic mapping with exploratory statistical visualisations to identify regional expenditure patterns and disparities.

Data

Mean household expenditure data (district-wise) and administrative boundary shapefiles of Sri Lanka obtained from the Department of Census and Statistics

Methods

Choropleth mapping, data classification, histogram analysis, scatter plot analysis, box plot visualisation, and exploratory data analysis (EDA)

Software

ArcGIS Desktop, MS Excel

Outcome

Identification of spatial variations in household expenditure, highlighting high- and low-expenditure districts and overall distribution trends across Sri Lanka

What I Learned: Strengthened skills in thematic mapping and statistical data interpretation, and improved understanding of spatial socio-economic disparities using integrated map and chart-based analysis.
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Pharmacy Site Selection Map - Kekirawa DS Division

Site Selection for a Pharmacy

Kekirawa DS Division, Sri Lanka

GIS-based site suitability analysis for identifying the most optimal location for a new pharmacy using spatial criteria, buffer analysis, and Model Builder workflows.

Data

DS Division Boundary, Road Network, Hospitals & Clinics, Dispensaries, Settlements, Government Buildings, Population Distribution, Land Use (Agriculture & Water Bodies)

Methods

Buffer Analysis, Suitability & Unsuitability Mapping, Competitor Analysis, Accessibility Analysis, Model Builder Workflow, Append & Erase Tools

Software

ArcGIS Desktop (Model Builder)

Outcome

Identification of an optimal pharmacy location based on population demand, accessibility, competition, and urban proximity

What I Learned: Applied Model Builder to automate multi-criteria spatial analysis and integrate suitable and unsuitable factors for real-world healthcare site selection.
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District-level GIS mapping of dengue distribution in Sri Lanka (2018–2020)

GIS Mapping of Dengue Distribution

Sri Lanka (District Level)

This project presents a district-level spatial analysis of dengue incidence in Sri Lanka for the years 2018, 2019, and 2020. Using GIS-based thematic mapping techniques, the study visualizes spatial and temporal variations in dengue case distribution, highlighting high-burden districts and year-to-year changes. The outputs demonstrate the value of GIS in public health surveillance and disease trend communication.

Data

District-level dengue case data (2018–2020), administrative boundary datasets, and base map layers used for academic and analytical purposes

Methods

Data preprocessing and validation, attribute joining, thematic mapping using graduated colour symbology, and temporal comparison across multiple years

Software

QGIS for spatial data processing, thematic map creation, and professional cartographic layout design

Output

Year-wise district-level dengue distribution maps (2018, 2019, 2020) with legends, scale bars, north arrows, and national context inset maps

What I Learned: Strengthened skills in public health GIS, thematic mapping, spatial data interpretation, and effective visual communication of disease patterns using GIS.
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Geospatial Analysis of Conflict Data in Pakistan

Geospatial Analysis of Conflict Data

Pakistan (Nationwide)

Spatial and temporal analysis of conflict-related deaths in Pakistan from 1989 to 2023 using advanced GIS-based spatial statistics and interpolation techniques.

Data

Uppsala Conflict Data Program (UCDP) conflict death records (1989–2023), Pakistan administrative boundary shapefile (HDX)

Methods

Optimized Hotspot Analysis, Kernel Density (Heat Map), Cluster & Outlier Analysis (Anselin Local Moran’s I), Inverse Distance Weighted (IDW) Spatial Interpolation

Software

ArcGIS Pro (Spatial Analyst & Spatial Statistics Tools)

Outcome

Identification of statistically significant conflict hotspots, spatial clusters, and intensity gradients to support conflict mitigation and peacebuilding strategies

What I Learned: Applied advanced spatial statistics and interpolation techniques to analyze long-term conflict patterns and interpret spatial dynamics for evidence-based decision-making.
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