Know your spatial world.
Geonuvo uses drones, LiDAR and satellite imagery to help you understand your land, and to spot crop disease, forest stress and land change early, while there is still time to act. Built in Ghana, with research-grade methods from Europe.
Mapping, monitoring and early warning
Every project comes in the formats your team already uses: shapefiles, GeoPackage, KML, GeoTIFF, printed maps or a web map you can open on your phone.
Crop health and disease detection
Drone and satellite indices combined with machine learning to find stressed or diseased plants in cocoa, plantain, cashew and maize farms.
Multispectral UAV · Sentinel-2 10 mForest health and carbon
Early detection of drought and heat stress, deforestation monitoring, and biomass estimates for carbon and EUDR reporting.
Hyperspectral · LiDAR · PlanetScopeDrone and LiDAR surveys
RTK drone flights producing orthomosaics, surface and terrain models, canopy height maps and stockpile volumes.
DJI M300 RTK · cm-level accuracyLand cover and land change
Validated land cover maps and change detection for mining expansion, urban growth and land degradation.
Random Forest · SVM · field validationFlood risk and urban heat
Flood exposure mapping and land surface temperature analysis for district assemblies, planners and developers.
Sentinel-1 radar · Landsat thermalWeb maps and GIS training
Interactive web maps and dashboards for your data, plus hands-on QGIS, ArcGIS and Google Earth Engine training for your staff.
ArcGIS Online · QGIS · GEEMonitoring and evaluation
Spatial monitoring and evaluation for development, agriculture, forestry and climate projects. We map baselines, track indicators over time with satellite and drone data, collect field data, and turn results into clear maps, dashboards and reports for donors, NGOs and government.
Baseline & endline mapping · indicator tracking · field data collection · impact reportsPersonal tuition
One-on-one or small-group lessons in GIS and remote sensing for students and professionals. Get help with coursework, thesis and dissertation analysis, or learn a tool from scratch, at your own pace. Lessons run online or in person.
QGIS · ArcGIS Pro · Google Earth Engine · Python · R · thesis supportThe right resolution for the question
A regional forest map and a 2-acre farm need very different data. We pick the source that answers your question at the lowest cost, and check results on the ground so they hold up.
| Source | Resolution | Revisit | Best for |
|---|---|---|---|
| Sentinel-2 | 10 m | 5 days | Crop health, land cover |
| Sentinel-1 radar | 10 m | 6–12 days | Floods, rainy-season imaging |
| Landsat 8/9 | 30 m | 8 days | Long-term change, heat |
| PlanetScope | 3 m | Daily | Forest species, farm plots |
| Drone + LiDAR | 2–5 cm | On request | Disease, canopy, volumes |
Founded by a remote sensing researcher from Ghana
Geonuvo was started by Raymond Kwame Nagbija, a University of Ghana graduate now doing a PhD in remote sensing at Charles University in Prague. His research detects stress in trees before any damage is visible. Geonuvo brings that same approach home to Ghanaian farms, forests and communities.
Raymond Kwame Nagbija
- PhD, Applied Geoinformatics & Remote SensingCharles University, Prague · lead researcher on LEAF2SAT, linking lab, drone and satellite data
- MSc, Geo-information Science & Earth ObservationUniversity of Twente (ITC), Netherlands · bark beetle mapping with DESIS and Sentinel-2
- Drone surveys, Bavarian Forest National ParkLiDAR and RGB processing for forest monitoring, Germany
- African Drone and Data Technology certificateBuilt a drone and used deep learning to detect banana bunchy top virus, Malawi
- BA Geography & Resource DevelopmentUniversity of Ghana, Legon · research assistant at the Centre for Climate Change and Sustainability Studies
From first call to final map
Scope
We agree the area, the question to answer and the deliverables, with a fixed quote.
Acquire
We source satellite imagery, fly the drone and collect ground data in the field.
Analyse
We process the data, run machine-learning models and validate results against field points.
Deliver
You receive maps, data files and a short report, plus a walkthrough with your team.
Tell us about your project
Send a short description and the location. We usually reply within one working day.