Smart Irrigation — Agriculture, Food Security & Rural Land Systems — Satellize

3.4Subsection · 5 applications

Smart Irrigation

Farmer crouching beside drip irrigation tubing in a crop field — Flooded farm fields like this one can be managed more efficiently when satellite data guides precise irrigation decisions.

Satellite Data Directing Precise Crop Irrigation

1
Satellite constellation
Captures NDVI, soil moisture, land surface temperature
2
Ground downlink
Regional hub receives imagery every 12–24 hours
3
Analytics platform
Evapotranspiration models compute field water deficit
4
Farmer alert
SMS or app sends valve-open timing and volume

Satellite imagery feeds evapotranspiration models that send precise, timely irrigation instructions directly to smallholder farmers.

Other areas in Agriculture, Food Security & Rural Land Systems

3.3 · Previous

Agricultural Risk Intelligence

All of agriculture

Subsection 3.4 — Agriculture, Food Security & Rural Land Systems

Smart Irrigation

5 applications.

Applications

3.4.1 Soil Moisture Monitoring — Measuring volumetric water content across agricultural soils at field scale using satellite L-band microwave radiometry and radar backscatter, updated multiple times per week.
3.4.2 Water Stress Monitoring — Detecting crop and soil water stress across agricultural landscapes by fusing thermal infrared, multispectral and microwave satellite data into actionable irrigation triggers.
3.4.3 Irrigation Automation — Closing the loop between satellite-derived crop water demand and field-level irrigation hardware, so water is applied at the right rate, in the right place, at the right time.
3.4.4 Watershed Intelligence — Mapping snowpack, glacier retreat, runoff generation and catchment storage across entire river basins using multi-sensor satellite observations to govern water allocation before it reaches the field.
3.4.5 Agricultural Water Forecasting — Combining satellite-derived soil moisture, evapotranspiration and precipitation estimates with numerical weather models to forecast agricultural water demand and supply at field scale.