This package provides tools for extracting, processing, analyzing, and visualizing conflict event data from the Armed Conflict Location & Event Data Project, a global dataset on political violence and protest events. It supports data retrieval, geospatial and temporal aggregation, and the creation of publication-quality maps and charts.

A Python toolkit for analyzing high-frequency human mobility data to support urban resilience and disaster risk management. It provides tools to process mobility trajectories, detect behavioral responses to extreme events, and generate spatial and temporal indicators for disaster impact assessment.

A Python package in development for processing, visualizing, and analyzing mobility data to quantify activity levels and movement patterns. It provides tools for data preprocessing, activity analysis, tessellation generation, and mobility metric calculation.

An R package for querying real-time traffic data from Google Maps and converting it into georeferenced rasters for spatial analysis. It supports traffic extraction around points and polygons and enables integration of traffic congestion data with other geospatial datasets.

A Python package for fetching, processing, and analyzing Enhanced Vegetation Index (EVI) data from MODIS satellite products through the Microsoft Planetary Computer. It supports zonal statistics, temporal aggregation, phenology analysis, anomaly detection, and land cover masking for vegetation monitoring and agricultural analysis.

A Python package for downloading and processing nighttime lights data from NASA’s Black Marble project. It automates tile retrieval from NASA LAADS DAAC, converts HDF5 files to georeferenced rasters, and supports time series analysis and zonal statistics for user-defined geographic areas.

A Python package for automating Enhanced Vegetation Index (EVI) analysis for agricultural monitoring using Google Earth Engine data. It extracts EVI time series for specified countries and time periods, computes historical baselines, and identifies anomalous vegetation conditions associated with drought or crop stress.

Modular pipeline for monitoring agricultural productivity using MODIS EVI and Google Earth Engine, with support for cropland masking, zonal statistics, anomaly detection, and automated export.

A package for scaling interpretive qualitative analysis of open-ended survey responses using NLP. It extends small sets of human-coded labels to larger document collections through text vectorization and classification workflows, with built-in tests for bias, interpretability, and reliability. Applied to interviews on parental aspirations.