TerraAid combines satellite imagery, IoT sensors, and AI analysis to detect forest encroachment, wildfires, droughts, floods, and rainfall anomalies — in real time.
From sub-meter satellite resolution to predictive AI models — TerraAid gives governments, NGOs, and researchers the tools to respond before it's too late.
Sub-30m resolution change detection using multispectral NDVI analysis. Compares historical baselines against current imagery to flag illegal clearing, agricultural expansion, and logging.
Thermal infrared satellite scans combined with wind pattern modeling to detect active fires, predict spread trajectories, and calculate estimated containment timelines.
GPM IMERG and ground-station fusion to detect precipitation anomalies up to 14 days ahead. Visualize deficit and surplus zones at 10km resolution with historical comparisons.
Standardized Precipitation Index (SPI) and Vegetation Health Index (VHI) computed monthly for all monitored regions. Early-warning scoring integrated with food security models.
DEM-based hydrological modeling combined with radar precipitation to simulate flood extents in near-real-time. Population exposure and infrastructure impact scoring included.
Cross-reference land-use changes against protected species habitat ranges. Automatically generate IUCN threat assessments when encroachment zones overlap critical corridors.
Connect soil moisture sensors, weather stations, stream gauges, and air quality monitors. All data streams normalised and fused into unified geospatial layers on the platform.
Transformer-based models trained on 20+ years of Earth observation data. Forecast encroachment risk, fire probability, and rainfall anomalies up to 30 days ahead with confidence intervals.
SMS, email, and webhook alerts the moment thresholds are breached. Configurable per-region severity levels. Full audit trail for compliance reporting and donor accountability.
Multi-source satellite data from Sentinel-2, Landsat-9, MODIS, and commercial providers is ingested and pre-processed every 12 hours.
Deep learning models classify land-cover changes, detect thermal anomalies, and compute environmental indices across all monitored zones simultaneously.
Each detected event receives a severity score, confidence interval, and projected impact estimate based on population density and ecological sensitivity.
Stakeholders receive targeted alerts with precise GPS coordinates, severity classification, recommended response protocols, and exportable incident reports.
Join 400+ government agencies and NGOs using TerraAid to monitor and protect critical ecosystems.