Agriculture and food security
Harvest forecasts that do not depend on the survey.
Every crop has a spectral fingerprint. Few countries have mapped theirs.Crop type classification from multispectral imagery
Multispectral time-series imagery lets analysts distinguish wheat from maize from soya by tracking how each crop's reflectance evolves through the growing season. The method is proven but demands dense, cloud-free observations and reliable ground truth.
Sentinel-2 MSI (ESA)Planet SuperDoveLandsat 8/9 OLI
Clouds block optical sensors. C-band backscatter does not care.Crop yield estimation using SAR and optical fusion
Combining Sentinel-1 SAR backscatter with Sentinel-2 vegetation indices lets analysts predict end-of-season crop yield at field or district scale, even through the cloud cover that makes optical-only approaches unreliable in humid growing regions.
Sentinel-1 A/B (C-band SAR)Sentinel-2 A/B (MSI)MODIS Terra/Aqua
Crops show drought stress before farmers can see itVegetation condition indices for agricultural drought monitoring
VCI and TCI normalise live NDVI and land surface temperature against multi-decade baselines to reveal moisture stress weeks before yield loss becomes visible. MODIS, VIIRS and Sentinel-3 SLSTR supply the archive depth and revisit frequency that make the baselines statistically meaningful.
MODIS Terra/Aqua (NASA)VIIRS SNPP / NOAA-20Sentinel-3 SLSTR (ESA/Copernicus)
Farmers cannot hide water. Radar sees it anyway.Irrigated area mapping using SAR coherence and backscatter
Sentinel-1 SAR coherence loss and seasonal backscatter shifts expose irrigated fields that optical imagery misses under cloud. This page covers the physics, the method, and the honest limits of mapping irrigation at national scale.
Sentinel-1 A/B (C-band SAR, 5.6 cm wavelength)ALOS-2 PALSAR-2 (L-band SAR, 23.6 cm wavelength)RADARSAT Constellation Mission (C-band SAR)
The surface dries first. Roots don't care about the surface.Root-zone soil moisture estimation for crop water status
Satellite sensors measure the top few centimetres of soil. Getting from that signal to the root-zone moisture that actually governs plant stress requires physics, modelling and honest accounting of what each sensor cannot see.
SMAP L-band Radiometer (NASA)SMOS MIRAS L-band Radiometer (ESA/CNES)Sentinel-1 SAR (ESA, C-band, 5.405 GHz)
The soil is bare, then it is not. That transition is everything.Planting date and crop establishment detection from dense time series
Detecting the precise date a crop establishes itself from satellite time series lets governments and traders act on supply signals weeks before any field survey. The method rests on catching an abrupt reflectance or backscatter shift as seedlings break the soil surface.
Planet SuperDoveSentinel-2 MSI (ESA)Sentinel-1 SAR (ESA)
Crops disappear in days. Satellites can watch every field.Harvest progress monitoring at regional scale
Harvest is the fastest phenological transition in the agricultural calendar, and missing it costs governments and traders dearly. Sequential optical and SAR observations detect the abrupt canopy-removal signal, distinguish harvest from crop failure, and map regional progress at sub-weekly cadence.
Planet SuperDoveSentinel-2 MSISentinel-1 SAR (C-band)
Locusts follow rain. Satellites watch the rain first.Desert locust breeding habitat risk mapping
Desert locust outbreaks begin in remote semi-arid zones where moist soils and green flush create brief breeding windows. Satellite-derived soil moisture, vegetation anomalies, and rainfall estimates can flag those windows days to weeks before ground teams can reach them.
SMAP L-band radiometer (NASA)Sentinel-2 MSI (ESA/Copernicus)MODIS Terra and Aqua (NASA)
Leaves signal disease in chemistry before they show it in colour.Crop disease and pest stress detection using hyperspectral sensing
Pathogen infection and pest feeding alter leaf pigments, water content, and cell structure days before visible symptoms appear. Narrow-band hyperspectral sensing can read those chemical shifts; broadband multispectral sensors mostly cannot.
ASI PRISMADESIS on ISSEMIT on ISS
Grass reflects what it weighs. Satellites can read the scales.Pasture biomass and livestock carrying capacity estimation
Satellite-derived vegetation indices and SAR backscatter can estimate above-ground herbaceous biomass across rangelands and managed pastures, converting canopy signals into carrying capacity metrics that inform stocking decisions at paddock scale.
Sentinel-2 MSIPlanet SuperDoveMODIS Terra/Aqua
Satellites see the crop stress. They cannot see who goes hungry.Satellite data integration for food security early warning systems
Rainfall anomalies, vegetation departure, land surface temperature, and flood extent are the physical signals satellites contribute to food security early warning. They matter only when combined with market data, population vulnerability, and analyst judgement inside frameworks like FEWS NET and the IPC.
CHIRPS (Climate Hazards Group InfraRed Precipitation with Station data)MODIS Terra and Aqua (NASA)VIIRS SNPP and NOAA-20
Farmers know when a storm hit. Insurers need proof that holds up.Farm-level crop loss verification for index and indemnity insurance
High-resolution optical and SAR imagery can verify crop losses at individual field level, but resolution floors, cloud cover, and evidentiary standards vary sharply by sensor and peril type.
Sentinel-1 SAR (C-band, ESA)Planet SuperDoveMaxar WorldView-3
The canopy tells you where nitrogen is short. The question is resolution.Within-field variability mapping for precision agriculture prescriptions
Sub-metre to 3-metre multispectral imagery can resolve within-field nutrient zones that 10-metre sensors miss, but map accuracy and agronomic response are not the same thing. This page explains the physics, the sensors, and the honest limits.
Planet SuperDoveMaxar WorldView-3Sentinel-2 MSI
Fields look identical from the road. Their water bills differ by a factor of three.Actual evapotranspiration and crop water use mapping
Surface energy balance models applied to satellite thermal imagery can estimate actual crop water use at field scale, exposing irrigation inefficiency invisible to ground sensors. The method is powerful and genuinely difficult to get right.
Landsat 8/9 TIRSSentinel-3 SLSTRMODIS Terra/Aqua
Floodwater retreats in days. The crop losses it leaves are permanent.Flood inundation extent and cropland damage assessment
SAR backscatter change detection maps flood extent over farmland within hours of a satellite pass, even through cloud. Intersecting that extent with crop-type maps and calendars converts pixels into tonnes of likely production loss.
Sentinel-1 (ESA)ALOS-2 PALSAR-2 (JAXA)RADARSAT Constellation Mission (CSA)
Carbon-rich soil is darker. Satellites can read that difference.Soil organic carbon mapping in cropland using bare-soil composites
Topsoil organic carbon can be estimated from satellite optical imagery when fields are bare, exploiting the reflectance contrast between carbon-rich and carbon-depleted soils. Sentinel-2 and Landsat archives make cloud-free bare-soil composites feasible at regional scale, though the method is strictly surface-limited without ground-truth depth profiles.
Sentinel-2 MSILandsat 8/9 OLIPRISMA (ASI)
Polyethylene reflects what crops absorb. That contrast is the map.Greenhouse and protected agriculture structure mapping
Plastic greenhouses and polytunnels produce a distinctive high-reflectance signature in visible and SWIR bands that saturates standard vegetation indices. Detecting them accurately requires resolving the confusion with salt pans, rooftops, and sand, and knowing where optical sensors alone fall short.
Sentinel-2 MSIPlanet SuperDoveMaxar WorldView-2 / WorldView-3
Bare soil and buried carbon tell different stories at 2100 nm.Crop residue cover and tillage practice detection
Post-harvest fields carry a spectral fingerprint that distinguishes no-till from ploughed ground. Short-wave infrared absorption by cellulose and lignin makes tillage practice legible from orbit, with important caveats about resolution and cloud.
ASI PRISMA (PRecursore IperSpettrale della Missione Applicativa)DLR/GFZ EnMAP (Environmental Mapping and Analysis Programme)USGS/NASA Landsat 8 and 9 OLI
A field harvested twice looks identical to one harvested once. Until you watch it.Cropping intensity and double-crop detection from time series
Dense vegetation-index time series reveal how many crop cycles a field completes each year, information that static imagery cannot provide. Harmonic regression on Sentinel-2, Landsat 8/9 and MODIS stacks separates single, double and triple-cropped land with enough confidence to feed national food-balance models.
Sentinel-2 MSI (ESA)Landsat 8/9 OLI (USGS/NASA)MODIS MOD13Q1 (NASA Terra)
Frost kills cells in hours. The signal persists for weeks.Winter crop area estimation and freeze-damage detection
SAR backscatter and optical NDVI together track winter wheat and barley from sowing through vernalisation, then expose canopy damage after hard freezes before spring regrowth closes the window for accurate loss assessment.
Sentinel-1 C-band SAR (ESA)Sentinel-2 MSI (ESA)MODIS Terra and Aqua (NASA)
The mill schedule depends on a number the field cannot easily give you.Sugarcane yield and sucrose content estimation
Canopy reflectance in the red-edge and shortwave-infrared bands tracks chlorophyll decline and fibre accumulation as sugarcane matures, giving mills and governments an independent estimate of stalk biomass and sucrose content weeks before harvest.
Sentinel-2 MSIPRISMA (ASI)Landsat 8/9 OLI
Subsidies are paid per tree. Satellites can count them.Orchard tree count and individual canopy area mapping
Very-high-resolution optical imagery and canopy height models let analysts count individual orchard trees and measure each crown. The results feed subsidy verification, insurance underwriting and productive-capacity assessments for permanent crops including olives, almonds and citrus.
Maxar WorldView-3Airbus Pléiades NeoPlanet SuperDove
Rice paddies hide under clouds. SAR sees through both.Flooded rice paddy mapping for methane emission inventories
Flooded paddy fields are the largest single agricultural source of methane. Combining Sentinel-1 radar backscatter with Sentinel-2 optical phenology lets analysts map inundation extent and flood duration at field scale, the two variables that drive UNFCCC emission factor calculations.
Sentinel-1 C-band SAR (ESA)Sentinel-2 MSI (ESA)ALOS-2 PALSAR-2 L-band SAR (JAXA)
The bolls open in days. The harvest window is shorter.Cotton boll opening and harvest-readiness detection
Sentinel-2 SWIR bands and Landsat OLI track the sharp spectral shift as cotton bolls open and leaves defoliate, giving gin operators and agronomists field-scale readiness signals across large cotton belts. Cloud cover during the narrow harvest window is the method's principal constraint.
Sentinel-2 MSILandsat 8/9 OLIPlanet SuperDove
Same grape variety, same rootstock, wildly different fruit. Satellites explain why.Within-vineyard vigour zoning and microclimate variability mapping
Very-high-resolution multispectral imagery from WorldView-3 and Pléiades Neo resolves individual vine rows at 30–50 cm, mapping canopy vigour zones that correlate with yield and berry sugar content. Thermal data from ECOSTRESS adds water-stress signals that reflectance indices alone cannot capture.
Maxar WorldView-3Airbus Pléiades NeoNASA ECOSTRESS (ISS-mounted)
Standing crops and flattened ones look identical to a yield model.Crop lodging detection using SAR and optical change analysis
When cereal crops collapse from wind, rain or pest damage, conventional yield models keep estimating as if nothing happened. SAR backscatter and optical texture change sharply at lodging, giving a two-to-five-day detection window before the damage compounds.
Sentinel-1 SAR (C-band, 5.405 GHz)Sentinel-2 MSILandsat 8/9 OLI
Fields that no cadastre records still show up from orbit.Smallholder field boundary delineation in fragmented landscapes
Deep-learning segmentation on very-high-resolution imagery can delineate farm parcels well below one hectare in landscapes where no official boundary records exist, enabling farm-level insurance, subsidy targeting and yield estimation across sub-Saharan Africa and South Asia.
Planet SuperDoveMaxar WorldView-3Airbus Pléiades Neo
A field that never greens up is still telling you something.Fallow and abandoned cropland detection within agricultural zones
Comparing seasonal NDVI trajectories against multi-year baselines reveals which parcels within a cropland mask were left fallow or permanently abandoned. The distinction shapes food-balance sheets and rural land-use policy.
Sentinel-2 MSIMODIS MOD13Q1Landsat 8/9 OLI
Aquifers drain silently. The ground above them does not.Groundwater depletion detection in irrigated aquifer systems using InSAR
Interferometric SAR detects millimetre-to-centimetre annual subsidence caused by aquifer compaction in over-pumped irrigation districts, providing spatially continuous evidence of unsustainable extraction that sparse piezometer networks routinely miss.
Sentinel-1 (C-band SAR, ESA)ALOS-2 PALSAR-2 (L-band SAR, JAXA)COSMO-SkyMed (X-band SAR, ASI/Italian MoD)
The calendar says harvest is October. The crops disagree.National crop calendar validation against satellite phenology
Harmonic analysis of MODIS and Sentinel-2 NDVI time series extracts green-up, peak and senescence dates at administrative-unit level, then tests them against FAO GAEZ and national ministry calendars to surface reporting errors and climate-driven shifts.
MODIS MOD13Q1 (Terra/Aqua)Sentinel-2 MSI (Sentinel-2A/2B)Landsat 8/9 OLI
The grain looks fine. The fungus moved in three weeks ago.Aflatoxin contamination risk mapping via drought-stress proxies
Aflatoxin contamination in maize and groundnut is triggered by drought stress during grain fill, weeks before any visible symptom appears. Satellite-derived stress indices can map that window spatially, giving food-safety programmes a probabilistic risk layer to direct ground sampling.
Sentinel-2 MSILandsat 8/9 TIRSSMAP (Soil Moisture Active Passive)
Ponds expand into mangroves at night. Radar sees both.Aquaculture pond extent and water-quality monitoring
Multispectral and SAR imagery maps aquaculture pond extent, detects illegal encroachment into mangrove zones, and tracks surface water-quality proxies tied to productivity and disease risk.
Sentinel-2 MSILandsat 8/9 OLISentinel-1 SAR (C-band)
Salt ruins irrigated land quietly. Satellites catch it before the harvest does.Soil salinity mapping and salt-affected cropland degradation
Spectral signatures of halite, gypsum and carbonate crusts in the shortwave-infrared expose salt-affected soils that look unremarkable to the naked eye. Combining hyperspectral PRISMA data, Sentinel-2 SWIR bands and ALOS-2 L-band SAR dielectric returns produces salinity maps that field surveys alone cannot match at scale.
ASI PRISMA (PRecursore IperSpettrale della Missione Applicativa)ESA Sentinel-2 MSIJAXA ALOS-2 PALSAR-2
Grass disappears slowly. The satellite record makes it undeniable.Grassland degradation and bare-soil encroachment mapping
Multi-year spectral unmixing of Landsat and MODIS time series separates photosynthetic vegetation, dry plant litter and bare soil to track rangeland degradation trajectories and distinguish climate stress from overgrazing.
Landsat 8/9 OLIMODIS MOD09GA (Terra/Aqua)Sentinel-2 MSI
Palms grow older every season. Satellites can now tell you exactly how old.Tree crop age estimation in oil palm and rubber plantations
Canopy height from TanDEM-X and ICESat-2, combined with Landsat planting-date detection, lets commodity traders and development banks map the age class of oil palm and rubber stands with enough precision to drive replanting schedules and carbon accounts.
TanDEM-X (TerraSAR-X add-on for Digital Elevation Measurements)ICESat-2 ATLAS photon-counting lidarLandsat archive (Landsat 5 TM through Landsat 9 OLI-2)
Canopy temperature drops before leaves turn brown. That gap is the opportunity.Potato crop stress early warning from thermal anomalies
Thermal infrared sensors detect canopy cooling and warming anomalies in potato fields days before visible symptoms appear. Combined with ERA5 humidity reanalysis, field-level risk scores give agronomists time to act.
Landsat 8/9 TIRSECOSTRESS (ISS-mounted)Sentinel-3 SLSTR
Nitrogen is invisible from orbit. Chlorophyll is not.Soybean leaf chlorophyll and nitrogen status estimation from multispectral indices
Red-edge reflectance from Sentinel-2 and Planet SuperDove lets agronomists estimate soybean leaf chlorophyll concentration as a proxy for canopy nitrogen status, but saturation at high LAI and atmospheric correction quality set real limits on what satellite data can reliably retrieve.
Sentinel-2 MSIPlanet SuperDoveRapidEye (archive)
Canopy colour tells you what the soil is hidingBanana plantation health decline mapping
Progressive banana plantation decline, whether from Fusarium wilt, Sigatoka or other stresses, shows spectral signatures weeks before visual symptoms are obvious. Time-series red-edge and shortwave-infrared indices from Sentinel-2 and PlanetScope can map patch boundaries and guide targeted ground scouting.
Sentinel-2 MSIPlanetScopeWorldView-3
Fire leaves nutrients behind. Knowing where they fell changes the fertiliser bill.Post-fire ash cover and nutrient deposition mapping on cropland
Stubble and field-margin fires deposit ash unevenly across cropland, creating patches of elevated potassium and calcium that standard soil sampling misses. Sentinel-2 and Landsat 8/9 resolve the spectral contrast between ash, char, and bare soil well enough to map that variability at field scale.
Sentinel-2 MSILandsat 8/9 OLIVIIRS 375 m active-fire product (VNP14IMG)
The tree rests every other year. The satellite notices.Olive grove alternate-bearing cycle detection from multi-year NDVI series
Olive groves oscillate between heavy-fruit and light-fruit years, and that rhythm shows up in multi-year NDVI time series. Sentinel-2 at 10 m resolves individual grove blocks; the Landsat archive reaches back to 1984 for multi-cycle validation.
Sentinel-2 MSILandsat 4–9 archiveMODIS MOD13Q1
Cover crops are visible from orbit. Bare fields after harvest are not innocent.Field-scale nitrogen leaching risk mapping from post-harvest bare-soil indices
Post-harvest bare-soil reflectance composites from Sentinel-2, combined with crop-type history and autumn rainfall, let regulators and agronomists identify which fields carry the highest nitrate leaching risk before winter rains mobilise residual nitrogen.
Sentinel-2 MSISentinel-1 SAR C-bandISRIC SoilGrids
The storm track is 3 km wide. Your insurer needs an answer by tomorrow.Hail damage rapid assessment in standing crops
Hail bruises leaves, snaps stems, and strips canopy in hours. Pre/post red-edge and NIR change detection on sub-10 m imagery can map the damage footprint before recovery or disease obscures what the storm actually did.
PlanetScopeSentinel-2 MSIWorldView-3
Satellites cannot taste arsenic. They can map exactly where it forms.Arsenic contamination risk proxy mapping in flooded rice systems
Reductive dissolution of iron oxyhydroxides under prolonged waterlogging releases arsenic into paddy pore water. SAR flood-duration time series combined with published soil geochemical layers can identify which fields carry the highest mobilisation risk before grain uptake occurs.
Sentinel-1 SAR C-band (ESA)ALOS-2 PALSAR-2 L-band (JAXA)MODIS Terra/Aqua (NASA)
Single-date spectral signatures lie. The seasonal curve does not.Winter cover crop species discrimination using phenological timing differences
Common winter cover crops look nearly identical in any one Sentinel-2 image. Their phenological timing differs enough to discriminate species reliably, which matters for carbon credit verification and nutrient auditing.
Sentinel-2 MSI (ESA Copernicus)Planet SuperDoveLandsat 8/9 OLI (USGS/NASA)
Water vanishes invisibly. Physics lets you invoice it anyway.Crop water productivity benchmarking across irrigation schemes
Crop water productivity (yield per cubic metre of evapotranspiration) can be computed at field scale by combining satellite-derived ET from surface energy balance models with vegetation-index yield proxies. The method works across farms, districts and borders, but ET uncertainty of 10–20% propagates directly into the ratio.
ECOSTRESS (ISS-mounted)Landsat 8/9 TIRS + OLISentinel-2 MSI