Agricultural and environmental decisions are only as good as the data behind them. We build AI-powered satellite imagery analytics that transform raw Earth-observation data into actionable crop intelligence for agriculture, forestry, and environmental monitoring.
Credit: NASA
Credit: NASA
Credit: NASA
Intelligent Data Design, Inc. specializes in developing cutting-edge software solutions for satellite data processing and analysis. We create robust, scalable applications that transform massive datasets from Earth observation satellites into actionable insights for agriculture, forestry, and environmental monitoring.
Our AI-powered analytics platforms combine multi-spectral and radar imagery with machine-learning models to enable precision agriculture through high-resolution crop monitoring, yield prediction, and field-level decision support systems. We also apply modern Earth-observation foundation models and next-generation SAR and altimetry missions to emerging problems such as soil-moisture retrieval and contaminant detection.
Empowering agricultural advisors and growers with leaf-level precision data for confident decision-making.
Pull multi-spectral, radar, and weather data from MODIS, Sentinel, Landsat, SWOT, NISAR, and other public and commercial sources.
Apply AI/ML models and Earth-observation foundation models to detect crop health, stress, yield potential, flooding, and environmental change.
Deliver field-level recommendations, alerts, and decision-support dashboards to growers, advisors, and operations teams.
Agricultural Advisors
Crop consultants and agronomists advising large farming operations.
Commodity & Food Companies
Supply-chain and procurement teams monitoring crop area and yield.
Environmental Agencies
Teams tracking floods, water resources, pollution, and land-use change.
Research Labs
Scientists integrating satellite data with models and in-situ observations.
Advanced MODIS and compatible multi-spectral satellite imagery for crop health assessment, vegetation-index trending, and field-scale monitoring across large agricultural regions.
Credit: NASA
Real-time flood detection, surface-water extent mapping, and environmental impact assessment using multi-spectral satellite data analysis and change-detection workflows.
Credit: NASA
Applying TerraMind, IBM/ESA's open any-to-any generative foundation model for Earth Observation, to new SWOT (surface water) and NISAR (L-band SAR) satellite platforms for soil-moisture estimation, hydrology, and other emerging Earth-observation products.
Credit: NASA
Satellite-imagery analytics for environmental contaminant detection, including exploratory work on spectral fingerprinting of PFAS and other pollutants using multi-spectral, hyperspectral, and SAR data fused with hydrologic context.
Credit: NASA