Bangladesh Comprehensive Geospatial Analysis Platform

A multi-domain satellite-based geospatial analysis platform for Bangladesh, covering water resources, urbanization, poverty, nighttime lights, vegetation, air quality, climate, land cover, infrastructure, crop detection, slum mapping, coastal dynamics, soil analysis, health risk, and renewable energy — all powered by Google Earth Engine across 20+ satellite datasets spanning 1975–2025.

Analysis Domains

Domain	Module	Key Datasets	Period
Water Detection	`water_classification.py`	Landsat 5/7/8/9, Sentinel-2	1985–2025
River Migration	`river_analysis.py`	Landsat, JRC Water	1985–2025
Flood Mapping	`flood_analysis.py`	Landsat, Sentinel-2	1985–2025
Water Change	`water_change.py`	Landsat, JRC Water	1985–2025
Wetland/Haor	`haor_analysis.py`	Landsat, SRTM DEM	1985–2025
Nighttime Lights	`nightlights.py`	DMSP-OLS, VIIRS DNB	1992–2025
Urbanization	`urbanization.py`	GHSL, Dynamic World	1975–2025
Vegetation	`vegetation.py`	MODIS NDVI/EVI, Hansen GFC	2000–2025
Land Cover	`land_cover.py`	MODIS, Dynamic World, ESA WorldCover	2001–2025
Air Quality	`air_quality.py`	Sentinel-5P TROPOMI	2018–2025
Climate	`climate.py`	CHIRPS, MODIS LST, ERA5	1981–2025
Poverty Proxy	`poverty.py`	Lights + Pop + Built + NDVI	2000–2020
Infrastructure	`infrastructure.py`	Dynamic World, GHSL	2015–2025
Crop Detection	`crop_detection.py`	Landsat, MODIS NDVI, Dynamic World	2000–2025
Slum Mapping	`slum_mapping.py`	GHSL, VIIRS, MODIS LST, WorldPop	2000–2020
Coastal Analysis	`coastal.py`	Landsat, SRTM, ESA WorldCover, MODIS	1985–2025
Soil Analysis	`soil_analysis.py`	OpenLandMap, SRTM, CHIRPS	Static + annual
Health Risk	`health_risk.py`	MODIS LST, Sentinel-5P, WorldPop	2000–2025
Energy Potential	`energy.py`	ERA5, MODIS NDVI, VIIRS	2000–2025

Study Area

Configurable scope via --scope:

Scope	Coverage
`national` (default)	All 8 divisions of Bangladesh
`sylhet`	Sylhet Division haor wetlands
`<division>`	Any specific division (e.g., `dhaka`, `chittagong`)

Geographic features tracked:

16 rivers: Padma, Jamuna, Meghna, Brahmaputra, Ganges, Teesta, Surma, Kushiyara, Kalni, Kangsha, Gorai, Arial Khan, Dharla, Karnaphuli, Sangu, Matamuhuri
19 wetlands/haors: Tanguar Haor (Ramsar), Hakaluki Haor, Sundarbans, Chalan Beel, and more
10 urban centers: Dhaka, Chittagong, Khulna, Rajshahi, Sylhet, Rangpur, Barishal, Comilla, Gazipur, Narayanganj
7 economic zones: Dhaka EPZ, Chittagong EPZ, Mongla EPZ, and more
8 extreme flood years: 1987, 1988, 1998, 2004, 2007, 2017, 2020, 2022
9 known slum areas: Korail, Kamrangirchar, Mirpur, Bhashantek, and more
8 arsenic hotspots: Chandpur, Comilla, Munshiganj, Gopalganj, and more
8 cyclone landfall points: Sidr 2007, Aila 2009, Amphan 2020, Mocha 2023, and more
14 coastal districts: Satkhira to Cox's Bazar

Data Sources

Dataset	Period	Resolution	Used For
Landsat 5/7/8/9	1985–2025	30m	Water, vegetation, construction
Sentinel-2	2015–2025	10m	Water, vegetation
JRC Global Surface Water	1984–2021	30m	Water validation
SRTM / ALOS DEM	Static	30m	Elevation, haor delineation
DMSP-OLS Nighttime Lights	1992–2013	1km	Historical light intensity
VIIRS DNB Monthly	2014–2025	500m	Modern light intensity
MODIS Land Cover (MCD12Q1)	2001–2023	500m	LULC classification
Dynamic World	2015–2025	10m	Near real-time LULC, construction
ESA WorldCover	2020–2021	10m	High-res land cover, cropland
Copernicus Global Land Cover	2015–2019	100m	LULC validation
MODIS NDVI/EVI (MOD13A2)	2000–2025	1km	Vegetation health
Hansen Global Forest Change	2000–2023	30m	Forest loss/gain
Sentinel-5P TROPOMI	2018–2025	1.1km	NO2, SO2, CO, Aerosol, HCHO
MODIS LST (MOD11A2)	2000–2025	1km	Temperature, urban heat island
CHIRPS Precipitation	1981–2025	5.5km	Rainfall analysis
ERA5-Land	1950–2025	11km	Climate reanalysis
WorldPop	2000–2020	100m	Population density
GHSL Built Surface	1975–2030	100m	Built-up area tracking
GHSL Settlement Model	1975–2030	1km	Urban/rural classification
OpenLandMap Soils	Static	250m	Soil properties

Quick Start

pip install -r requirements.txt

# Basic tests
python run_pipeline.py --test                       # GEE auth + water test
python run_pipeline.py --scope sylhet --test        # Fastest scope

# Individual modules
python run_pipeline.py --nightlights                # Nighttime lights only
python run_pipeline.py --urbanization               # Urbanization only
python run_pipeline.py --airquality                 # Air quality only
python run_pipeline.py --crops                      # Crop detection
python run_pipeline.py --coastal                    # Coastal & mangrove
python run_pipeline.py --health                     # Health risk mapping

# Full pipelines
python run_pipeline.py --full                       # All water modules
python run_pipeline.py --full-extended              # ALL modules
python run_pipeline.py --scope sylhet --full-extended

CLI Options

--scope SCOPE       Analysis scope: national | sylhet | <division name>

Water Analysis (original):
  --test              Quick test (2020 dry vs monsoon)
  --full              Full 40-year water pipeline
  --rivers            River erosion analysis only
  --floods            Flood extent mapping only
  --changes           Water change detection only
  --haors             Haor/wetland analysis only

Extended Analysis:
  --nightlights       Nighttime lights & electrification
  --urbanization      Built-up area & urban sprawl
  --vegetation        NDVI/EVI, forest change, agriculture
  --landcover         LULC classification & change
  --airquality        Sentinel-5P pollutant mapping
  --climate           Rainfall, temperature, drought
  --poverty           Multi-indicator poverty proxy mapping
  --infrastructure    Construction change, economic zones

Domain-Specific Analysis:
  --crops             Crop detection & rice phenology
  --slums             Slum/informal settlement mapping
  --coastal           Coastal zone, mangrove, cyclone impact
  --soil              Soil properties, erosion, salinity
  --health            Health risk proxy mapping
  --energy            Renewable energy potential

Full Pipeline:
  --full-extended     Run ALL modules (water + extended + domain)

Outputs

All outputs saved to outputs/:

Directory	Contents
`outputs/rivers/`	Per-river erosion rates, migration maps
`outputs/floods/`	Flood time series, extreme flood maps
`outputs/haors/`	Haor area trends, boundary maps
`outputs/changes/`	Water persistence, decade-wise change
`outputs/nightlights/`	Light time series, electrification maps, city stats
`outputs/urbanization/`	Built-up growth, expansion maps, settlement classification
`outputs/vegetation/`	NDVI trends, forest loss, cropland maps
`outputs/landcover/`	LULC time series, change maps
`outputs/airquality/`	Pollutant trends, hotspot maps, AQI composite
`outputs/climate/`	Rainfall/LST trends, UHI, drought maps
`outputs/poverty/`	Poverty index maps, division/district rankings
`outputs/infrastructure/`	Construction maps, economic zone growth, connectivity
`outputs/crops/`	Rice paddy maps, crop type classification, yield proxy
`outputs/slums/`	Slum index maps, known slum stats, growth tracking
`outputs/coastal/`	LECZ maps, shoreline change, mangrove health, cyclone impacts
`outputs/soil/`	Erosion risk, salinity zones, agricultural suitability
`outputs/health/`	Health risk index, waterlogging, heat stress, arsenic zones
`outputs/energy/`	Solar/wind potential, biomass proxy, energy access
`outputs/report_maps/`	Publication-quality static figures

Key Methodologies

Water Detection: NDWI + MNDWI + AWEI majority voting with Otsu auto-thresholding

Poverty Proxy Index: Composite of (1) nightlight deficit, (2) built-up deficit, (3) population-light gap, (4) vegetation stress — normalized and equally weighted

Urban Heat Island: Difference between urban core MODIS LST and surrounding rural ring LST

Construction Detection: Dynamic World class transitions to "built" class + spectral NDBI/NDVI change

Drought Index: Normalized rainfall anomaly (CHIRPS vs 30-year mean) combined with temperature anomaly (MODIS LST)

Rice Paddy Detection: Phenology-based: monsoon flooding (LSWI > 0) followed by NDVI greening (> 0.4), combined with LULC cropland mask

Slum Index: Weighted composite of building density, vegetation deficit, overcrowding, LST anomaly, and nightlight irregularity — masked to urban areas via GHSL SMOD

Erosion Risk (RUSLE): Simplified RUSLE: rainfall erosivity + soil erodibility (clay/SOC) + slope (SRTM) + vegetation cover (NDVI inverse)

Health Risk Index: Composite of waterlogging, heat stress, population exposure, air pollution, and vegetation deficit — weighted sum normalized to 0–1

Energy Potential: Solar (ERA5 shortwave radiation), wind (ERA5 10m u/v → speed³), biomass (NDVI²), energy access (nightlights × electrification)

Name		Name	Last commit message	Last commit date
Latest commit History 42 Commits
tests		tests
validation		validation
.gitignore		.gitignore
CLAUDE.md		CLAUDE.md
README.md		README.md
air_quality.py		air_quality.py
aquaculture.py		aquaculture.py
brick_kiln.py		brick_kiln.py
calibrate_poverty.py		calibrate_poverty.py
change_alerts.py		change_alerts.py
char_accretion.py		char_accretion.py
climate.py		climate.py
coastal.py		coastal.py
config.py		config.py
crop_detection.py		crop_detection.py
cyclone_damage.py		cyclone_damage.py
data_acquisition.py		data_acquisition.py
dhs_health.py		dhs_health.py
dhs_wealth.py		dhs_wealth.py
download_local.py		download_local.py
energy.py		energy.py
export_utils.py		export_utils.py
flood_analysis.py		flood_analysis.py
generate_chapter_thumbnails.py		generate_chapter_thumbnails.py
generate_pdf_report.py		generate_pdf_report.py
generate_publication_maps.py		generate_publication_maps.py
generate_report_maps.py		generate_report_maps.py
groundwater.py		groundwater.py
haor_analysis.py		haor_analysis.py
health_risk.py		health_risk.py
hies_food_nutrition.py		hies_food_nutrition.py
hies_ground_truth.py		hies_ground_truth.py
infrastructure.py		infrastructure.py
ipums_demographics.py		ipums_demographics.py
ipums_poverty.py		ipums_poverty.py
land_cover.py		land_cover.py
local_compute.py		local_compute.py
local_landcover.py		local_landcover.py
nightlights.py		nightlights.py
poverty.py		poverty.py
pytest.ini		pytest.ini
requirements.txt		requirements.txt
river_analysis.py		river_analysis.py
run_divisions.py		run_divisions.py
run_pipeline.py		run_pipeline.py
sar_flood.py		sar_flood.py
slum_mapping.py		slum_mapping.py
soil_analysis.py		soil_analysis.py
tiling.py		tiling.py
timelapse.py		timelapse.py
transportation.py		transportation.py
urbanization.py		urbanization.py
vegetation.py		vegetation.py
visualization.py		visualization.py
water_change.py		water_change.py
water_classification.py		water_classification.py

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Bangladesh Comprehensive Geospatial Analysis Platform

Analysis Domains

Study Area

Data Sources

Quick Start

CLI Options

Outputs

Key Methodologies

About

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Contributors

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Bangladesh Comprehensive Geospatial Analysis Platform

Analysis Domains

Study Area

Data Sources

Quick Start

CLI Options

Outputs

Key Methodologies

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