Discover our high-performing ML models for geospatial analysis that can be quickly deployed with our tools: GeoAP — a ready-made platform for your AI-powered geo-analytical solutions with our open-source models or SoilMate — an easy-to-use service for quick geospatial analysis with built-in ML models.
Automated land usage detectionGeneral
Land Use/Land Cover map produced by Microsoft annually. The map is a composite of land use/land cover predictions for 9 classes each year from 2017
Blooming index detectionAgriculture
White trees flowering intensity calculation (e.g., almonds). Useful in pollination helping agronomists control the annual cycle. This model represents the implementation of the article "An enhanced bloom index for quantifying floral phenology using multi-scale remote sensing observations" by Bin Chen, Yufang Jin, and Patrick H. Brown.
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Growth anomalies detection. Performed through NDVI index calculation within the area of interest (AoI) and statistical methods application.
Moisture anomaly detectionAgriculture
Moisture index detection. Performed for a given AoI at the desired timeframe, selecting the least cloudy date.
Basic objects detectionGeneral
Vehicles and basic objects detection. Detects the most visible classes with a resolution of 0.3-0.5 m per pixel.
NDVI index calculationAgriculture
NDVI index calculation. Performed for a given AoI at the desired timeframe, selecting the least cloudy date.