Urban Air Pollution & Climate Drivers (Bangladesh)
This project investigates how key climatic and meteorological controls shape the spatiotemporal variability of air pollutants across Bangladesh. I integrate multi-source satellite observations and meteorological datasets to quantify patterns, identify dominant drivers, and produce map-ready outputs for environmental monitoring and decision support.
Methods: spatiotemporal analysis, remote sensing feature engineering, geospatial modeling, reproducible workflows (GEE / Python / R).
Outputs: national-scale maps, trend diagnostics, driver interpretation, publication-ready figures.
Urban Surface Pattern Drivers (Remote Sensing + Spatial Modeling)
This project explains the spatial distribution of urban surfaces using an integrated geospatial framework that combines satellite-derived indicators with spatial analytical methods. The focus is on identifying the environmental and anthropogenic factors that best explain observed urban surface patterns and their spatial heterogeneity.
Methods: spatial statistics, multi-method modeling, urban surface indicators, interpretation of drivers.
Outputs: driver maps, spatial pattern diagnostics, model comparison summaries.
Vegetation Greening/Browning & Physio-Climatic Controls
This project assesses long-term vegetation trajectories and links observed greening/browning patterns to physio-climatic drivers. Using satellite time series, I quantify changes in vegetation condition and evaluate how climate variability and local biophysical conditions influence ecosystem response.
Methods: time-series remote sensing, trend analysis, driver attribution, regional comparison.
Outputs: greening/browning maps, climate–vegetation relationships, spatial summaries for reporting.
Flood Event Impact Mapping (Sylhet & Sunamganj, 2022) using Google Earth Engine
This project demonstrates rapid flood impact assessment using cloud-based satellite processing. I developed a Google Earth Engine workflow to map flood extent and characterize affected areas to support evidence-based reporting and post-event assessment.
Methods: event-based EO analysis, cloud processing in GEE, impact characterization.
Outputs: flood extent products, affected-area summaries, maps for communication.
Climate Trend Projection under Global Climate Scenarios (Coastal Bangladesh)
This project evaluates long-term temperature and precipitation trends for a climate-vulnerable coastal region using scenario-based projections. The workflow includes downscaling, bias correction, validation, and performance evaluation to ensure robust inference about future climate trajectories.
Methods: statistical downscaling, bias correction, validation, trend interpretation.
Outputs: scenario-based trend plots, projected climate summaries, uncertainty-aware interpretation.