We analyze satellite and drone imagery to measure floods, land cover, vegetation health and change over time. Radar sees through cloud, optical bands show crops and water, and AI models classify large areas consistently. You receive figures and maps, not just pictures.
Imagery: Sentinel-2 cloudless 2023 by EOX IT Services, modified Copernicus Sentinel data (CC BY 4.0). Terrain: SRTM via AWS Terrain Tiles. Roads and buildings: © OpenStreetMap contributors (ODbL).
1,045km²
of August 2025 flooding mapped from Sentinel-1 radar
3
multi-hazard risk assessments, from district to site scale
30+
projects delivered across climate, GIS, AI and ESG
5.0
rating on Google reviews
Every analysis starts with the question, then the sensor. We pick radar, optical or drone imagery to suit the season, the scale and the answer you need.
Before and after comparisons that show where land, water or buildings changed, and by how much.
Sentinel-1 radar maps flood extent through cloud and rain, paired with CHIRPS rainfall to explain the event.
NDVI, NDWI and related indices that track crop vigor, drought stress and surface water through the season.
Machine learning models that classify built up land, crops, forest and water across whole districts in one consistent pass.
High resolution UAV imagery for site level detail: progress tracking, ground conditions and features too small for satellites.
Repeat observation of mangroves, shorelines, glaciers and protected land, so you can see trends and report on them.
On the left, a Sentinel-2 scene of Islamabad and the Margalla Hills. On the right, the same pixels sorted into vegetation, built up land, bare ground and water.
Drag the handle to compare. Classification like this is the starting point for change detection, monitoring and reporting. This example is illustrative.
Imagery: Sentinel-2 cloudless 2023 by EOX IT Services, modified Copernicus Sentinel data (CC BY 4.0). Terrain: SRTM via AWS Terrain Tiles. Roads and buildings: © OpenStreetMap contributors (ODbL).
Satellites revisit the same ground every few days. That makes imagery a fast way to see conditions across areas too large or remote to survey on foot.
Flood extent and affected land measured from radar, as in our August 2025 monitoring of Sialkot and Narowal.
Crop condition and drought stress tracked through the season, so relief and advice reach the worst hit areas first.
Mangrove and forest cover assessed to judge how restoration is working, as in our Indus Delta work with WWF-Pakistan.
Glacier retreat, slope movement and land cover change mapped across steep valleys that field teams struggle to reach.
Imagery is only useful once it is calibrated, checked and explained. Each project moves through five stages with a clear output at every step.
We define what to measure, the area, the dates and the detail you need.
Analysis plan and dates
We choose Sentinel, Landsat, MODIS or drone data to match the season and scale.
Image stack for your area
Calibration, cloud masking and terrain correction so every image lines up and compares fairly.
Analysis ready imagery
Indices, change detection or AI classification, then checks against field samples or reference data.
Measured, validated results
Maps, area figures and a plain summary of what changed and why it matters.
Maps, statistics, summary
We choose the data source and the software to fit the job, then deliver in formats your team can open.
Tell us the area, the dates and what you need measured. We will check the available imagery and reply with a plan.
