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.

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.

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.