- Active wildfire front detection from thermal infrared — Mid-wave and thermal infrared sensors detect actively burning fire fronts by measuring radiance that saturates standard land channels, enabling near-real-time alerts. Latency, resolution floors and cloud cover set hard limits on what any system can reliably report.
- Satellite-derived triggers for anticipatory humanitarian action — Anticipatory action frameworks release pre-positioned humanitarian funds before a disaster peaks, using objective satellite and model-derived triggers. This page explains the data inputs, trigger logic, and honest uncertainty limits that any government or humanitarian agency must understand before committing to the approach.
- Power-outage and blackout mapping with nighttime lights — VIIRS Day/Night Band radiance composites detect city-block-scale electricity loss at 500 m resolution by comparing pre- and post-disaster light fields. Cloud cover, moonlight and fire glow all confound the retrieval, and honest analysis accounts for each.
- Flood-driven waterborne disease risk mapping — Combining SAR flood extent, land-use classification and population density, satellite analytics identify where inundation is most likely to drive waterborne disease. The output is a spatial prior for field surveillance, not a pathogen forecast.
- Agricultural land abandonment and food-system disruption in conflict areas — Conflict disrupts agriculture through displacement, deliberate destruction, and fear of movement. Time-series analysis of Sentinel-2 NDVI and Sentinel-1 backscatter can detect uncultivated fields at 10 m resolution, separating war-driven abandonment from drought or voluntary fallow.
- Conflict-related building destruction detection with SAR — SAR coherence loss and backscatter change between pre- and post-event image pairs can locate collapsed urban structures in conflict zones where no ground access exists. The method has been applied publicly in Syria, Ukraine, and Gaza by UNOSAT and academic groups.
- Critical infrastructure flood exposure from LiDAR-fused elevation models — Coarse global DEMs misplace flood risk for hospitals, substations and water-treatment plants by metres. Fusing airborne LiDAR bare-earth models with SAR-derived flood extents narrows that uncertainty to operationally useful bounds.
- Glacial lake outburst flood hazard monitoring — Glacial lake outburst floods give little warning at ground level but leave a long satellite record of precursor signals. Multi-sensor monitoring of lake area, dam deformation and ice velocity can push that warning window from minutes to weeks.
- Cyclone and tropical storm structural damage assessment — Post-cyclone structural damage assessment uses very-high-resolution optical imagery and SAR intensity change to grade buildings from destroyed to moderately damaged. Speed and cloud cover are the two variables that determine whether the map arrives in time to matter.
- Dam and reservoir integrity monitoring after seismic or flood events — SAR coherence loss, InSAR displacement, and optical change detection give emergency managers the first quantitative read on dam integrity within hours of an earthquake or extreme flood, before ground teams can safely approach.
- Refugee and IDP camp growth monitoring from space — Very-high-resolution optical satellites can detect new shelters, access tracks, and latrine pits within days of their appearance, giving UNHCR and UNOSAT population proxies where ground access is denied or unsafe.
- Vegetation stress and drought severity for food-security early warning — Satellite vegetation indices detect agricultural drought stress two to six weeks before food insecurity becomes visible on the ground. This page explains the operational methods, honest resolution limits, and the workflows used by FEWS NET and WFP VAM.
- Earthquake building-damage proxies via SAR coherence loss — Interferometric SAR coherence drops sharply where structures have collapsed or shifted, giving emergency managers a damage proxy within hours of an earthquake. The signal is real but indirect: coherence loss is not a body count or a building count, and field validation remains essential.
- Earthquake surface deformation measurement with InSAR — Differential InSAR turns phase shifts between two SAR passes into centimetre-scale maps of coseismic ground displacement, revealing fault geometry and slip distribution within days of a major earthquake.
- Earthquake-triggered landslide inventory from change detection — Co-seismic landslides can outnumber building collapses as a cause of earthquake fatalities, yet they are invisible to ground teams for days. Satellite change detection cuts that gap to hours, producing georeferenced inventories that guide search-and-rescue routing and infrastructure triage.
- Emergency shelter material and density classification after displacement — Sub-metre multispectral and panchromatic imagery, combined with texture analysis and supervised classification, can distinguish tarpaulin, canvas, and corrugated-metal shelter types within newly established displacement camps to inform logistics and protection planning.
- Flood water depth estimation by DEM differencing — Combining SAR-derived flood extents with high-resolution elevation models lets analysts estimate water depth and inundated volume, but DEM vertical error sets a hard floor on what the method can honestly claim.
- Flood extent mapping with optical imagery — Multispectral satellites can delineate inundated surfaces within hours of a flood peak, but only when skies clear. This page explains the spectral physics, the indices, and the honest limits of optical flood mapping.
- Flood extent mapping with synthetic aperture radar — Synthetic aperture radar detects flooded land by the near-total absence of backscatter from smooth open water, day or night, through cloud. The method is fast and operationally proven, but flooded vegetation and wind chop introduce systematic errors that demand careful handling.
- Flood insurance loss estimation using SAR-derived inundation duration — Flood damage scales with how long water sits on a property, not just how far it spreads. Multi-date Sentinel-1 SAR time series can reconstruct inundation recession curves at parcel level, giving insurers and reinsurers an independent, physics-based input to actuarial loss models.
- Crop loss estimation from flood recession timing — Multi-temporal SAR and optical imagery can pinpoint the day floodwater leaves each agricultural parcel, then cross-reference that duration against crop submergence thresholds to estimate yield loss before harvest.
- Urban heat island intensification and population vulnerability during heatwaves — Landsat-9 TIRS-2 and ECOSTRESS resolve intra-urban land surface temperature to 70–100 m, exposing the thermal inequality that determines who bears the greatest physiological risk during a heatwave. Knowing the gradient is the first step toward targeted intervention.
- Informal settlement mapping for pre-disaster exposure assessment — Corrugated metal and tarpaulin roofs have a spectral and textural signature that formal construction lacks. Mapping that signature before a disaster, then overlaying hazard zones, turns a satellite image into a population-exposure register.
- International Charter Space and Major Disasters rapid-mapping workflow — The International Charter on Space and Major Disasters routes satellite tasking and derived maps to civil protection authorities within hours of activation. This page explains the mechanics: who triggers it, what data arrives, and where the workflow breaks down.
- Slow-moving landslide velocity mapping with InSAR time series — Persistent Scatterer and Small Baseline Subset InSAR time series detect millimetre-to-centimetre annual surface creep on slow-moving landslides, distinguishing background deformation from the episodic acceleration that often precedes catastrophic failure.
- Landslide mapping and post-event inventory from satellite — Fresh landslide scars have a distinct spectral signature that satellite sensors can detect within one to two days of an event. This page explains how optical change detection and SAR coherence loss combine to build event inventories that feed susceptibility models.
- Search-and-rescue priority zone delineation after structural collapse — After an earthquake or explosion, satellite-derived damage proxies combined with building inventory and population data can rank urban blocks by probable casualty concentration, giving search-and-rescue commanders a probabilistic triage map within hours, not days.
- Nighttime light recovery tracking as a reconstruction progress proxy — Nighttime light radiance from VIIRS Day-Night Band composites gives disaster responders and donors an objective, neighbourhood-scale measure of power restoration after earthquakes, hurricanes, and conflict. The method is fast, free, and honest about what it cannot see.
- Disaster-triggered oil spill and chemical release detection from SAR — Earthquakes, floods, and industrial accidents release hydrocarbons into waterways before optical sensors can see through cloud cover. SAR detects surface oil films through Bragg-scattering suppression, producing dark signatures in C- and X-band imagery within hours of an event.
- Post-cyclone mangrove canopy loss and coastal protection deficit mapping — Cyclone damage to mangroves is routinely invisible to optical sensors for weeks. L-band SAR and Sentinel-2 red-edge indices together reveal structural loss and the coastal flood exposure that follows.
- Post-earthquake road network accessibility assessment — After a major earthquake, knowing which roads are passable can determine whether aid reaches survivors within hours or days. This page explains how sub-metre optical and commercial SAR imagery, combined with road-network graph analysis, produces actionable accessibility maps.
- Post-flood sediment and debris deposition mapping — Spectral turbidity indices and DEM differencing reveal where floods deposited sediment and debris, quantifying volume changes that field surveys rarely capture at scale. Cloud cover and vertical accuracy set hard limits on what satellites can honestly deliver.
- Storm surge and coastal inundation extent from SAR — When a tropical cyclone makes landfall, optical sensors go blind and the surge boundary moves by the hour. X-band SAR from ICEYE and Capella Space cuts through cloud to deliver sub-metre flood extent within hours, though mangrove and salt-marsh returns demand careful interpretation.
- Tropical cyclone surface wind field retrieval from SAR — C-band SAR retrieves ocean surface wind speed and direction inside tropical cyclone wind fields where conventional observations are absent, using geophysical model functions to map the asymmetric structure that drives storm surge and inland damage.
- Tsunami inundation extent and coastal infrastructure damage mapping — Comparing pre- and post-event optical and SAR imagery reveals how far a tsunami ran inland and which coastal structures survived. The method rests on sediment deposition, vegetation removal and coherence loss, but the usable window is narrow.
- Urban flash flood runoff modelling from impervious surface mapping — Satellite-derived impervious surface maps at sub-10 m resolution feed directly into runoff models, replacing coarse land-use datasets that routinely underestimate sealed area in rapidly urbanising cities.
- Volcanic ash cloud detection for aviation hazard — Volcanic ash plumes can destroy jet engines with no visible warning. Geostationary infrared sensors and hyperspectral sounders give aviation authorities the detection speed and chemical confirmation they need to close airspace before aircraft enter the cloud.
- Volcanic edifice deformation monitoring with InSAR — Time-series InSAR turns repeated C- and L-band radar passes into surface displacement maps that reveal magma intrusion, chamber volume change, and flank creep weeks to months before a volcanic crisis becomes visible.
- Volcanic lahar flow path and deposit mapping from SAR and optical — Lahars can bury roads, bridges and settlements within hours of an eruption, often under thick volcanic cloud. Sentinel-1 SAR amplitude change detection maps deposit extent regardless of weather; Sentinel-2 optical composites refine boundaries once skies clear.
- Volcanic SO2 emission and plume dispersion tracking — Sentinel-5P TROPOMI and Aura OMI detect sulphur dioxide by its ultraviolet absorption signature, tracking plume mass and trajectory from eruption onset through dispersal. This page covers detection thresholds, ash interference, dispersion modelling, and the latency that separates a satellite overpass from an operational alert.
- Volcanic thermal anomaly detection for eruption onset warning — Shortwave and thermal infrared radiance from MODIS, VIIRS, Sentinel-2 and Landsat-9 reveal volcanic heating days to weeks before an eruption breaks the surface. MIROVA and MODVOLC translate raw radiance into alert thresholds that civil-protection agencies can act on.
- Post-wildfire burn scar extent and severity mapping — Burned area extent and fire severity are mapped from space using the differenced Normalised Burn Ratio, combining pre- and post-fire Sentinel-2 or Landsat imagery. Where smoke or cloud persists, SAR backscatter change from Sentinel-1 fills the gap.
- Wildfire perimeter dynamics and evacuation route accessibility — Near-real-time perimeter extraction from VIIRS, Sentinel-3 SLSTR and GOES-16/17 ABI, overlaid on road networks, tells emergency managers which evacuation corridors are already compromised and which will be within the hour.
- Post-wildfire erosion and debris-flow susceptibility mapping — Intense wildfire destroys the vegetation and soil structure that hold slopes together. Combining burn severity from satellite spectral indices with slope, soil type, and storm intensity data produces debris-flow susceptibility maps that can reach emergency managers before the first post-fire rain.
- Wildfire smoke aerosol optical depth and population health exposure — Satellite aerosol optical depth from MODIS, VIIRS, and Sentinel-5P TROPOMI can estimate how many people are breathing hazardous air during a wildfire event, though cloud cover and coarse resolution introduce real uncertainty that any honest analysis must quantify.