Advanced software solutions, live dashboards and spatial mapping.
We partner with researchers, businesses, and government agencies to integrate geospatial analysis into their programs and operations, helping them turn complex spatial data into actionable insights for better planning, decision-making, and impact. Our advanced GIS tools make analysis faster, more accurate, and easy to use, so organizations can respond effectively to the challenges they face.
Our geospatial data and related services are designed to help our clients make informed decisions and solve complex problems related to geography and spatial relationships. Whether you need maps, spatial analysis, or custom geospatial solutions, we have the expertise and resources to meet your needs.
Our tools and technologies are designed to help our clients make the most of their geospatial data and solve complex problems related to geography and spatial relationships. Whether you need maps, spatial analysis, or custom geospatial solutions, we have the tools and expertise to meet your needs.
Our commitment to research and innovation allows us to stay at the forefront of the geospatial field and provide our clients with the most advanced and accurate products and services available. This we do by collaborating with academic and industry partners, investing in R&D, participating in conferences and workshops and by conducting internal research.
A geospatial analysis that maps the flooding impact of Cyclone Alfred using Sentinel-1 SAR data, identifying newly flooded areas and estimating affected populations across Queensland and Northern NSW.
A predictive modeling project that estimates fire severity (NBR) in Queensland using vegetation health, climate variables, topography, and atmospheric pollution indicators, followed by a multi-year trend analysis (2020–2025).
A statistical and temporal analysis exploring how vegetation, climate, hydrology, and terrain influence wildebeest population trends across East Africa over multiple years.
Multi-epoch LULC maps for Rwanda using Landsat7 (2000/2010) and Sentinel-2 (2020/2025). Random Forest classification, accuracy assessment, and post-processing.
Multi-epoch LULC focused on Mangrove, Bareland and Water across 2007–2025. Random Forest classification + NDTI turbidity analysis.
Semantic segmentation pipeline using U-Net on high-resolution drone orthomosaic to map tree species and landcover classes with patching, training, inference, and stitching outputs.
Object-Based Image Analysis (OBIA) for Marereni across epochs (2000, 2005, 2010, 2015, 2020, 2025) using SLIC segmentation, segment-level statistical features, then Random Forest classification.
Upgrade of KilimoSTAT into a geospatial decision support system combining agricultural statistics with geospatial layers and machine learning prediction tools for Kenya’s agricultural sector.
Professional web mapping applications built with modern geospatial tools
All projects feature interactive maps built with Leaflet/OpenLayers, React, and PostGIS