- Long-term PM and NO2 exposure mapping for mental health burden studies — Chronic exposure to PM2.5 and NO2 is associated with depression, anxiety and cognitive decline. Satellite-derived multi-year exposure grids from TROPOMI, MODIS AOD and OMI are now standard inputs for cohort studies, but exposure misclassification remains the central methodological problem.
- Disproportionate air pollution burden mapping across income and race strata — Satellite-derived NO2 and PM2.5 surfaces, joined to census demographic data, can quantify whether low-income and minority communities bear pollution burdens that exceed their share of emission sources. The method is powerful and the limits are real.
- Agricultural ammonia plume mapping and respiratory disease burden — TROPOMI measures atmospheric ammonia columns at 3.5 km resolution, exposing livestock and fertiliser hotspots invisible to ground networks. Secondary PM2.5 chemistry links those columns to respiratory disease burden across downwind populations.
- Geogenic arsenic groundwater risk mapping via surface geology proxies — Naturally occurring arsenic in alluvial aquifers cannot be seen from orbit, but the sedimentary and redox conditions that concentrate it leave spectral fingerprints. Satellite-derived geology proxies produce probabilistic risk surfaces that guide where to test, not what the water contains.
- Traffic-related benzene exposure mapping from satellite VOC columns — Ground monitors for benzene are rare and unevenly sited. Satellite VOC columns from TROPOMI, combined with road-network density and land-use regression, let analysts estimate surface benzene concentrations across entire cities at roughly 5 km resolution.
- Black carbon deposition on glaciers and downstream drinking-water health risk — Black carbon deposited on glaciers cuts surface albedo, accelerates melt and shifts the chemistry of downstream drinking water. Combining MODIS and VIIRS albedo anomalies with MERRA-2 aerosol transport reveals source regions and the downstream populations at risk.
- Chagas disease triatomine vector habitat suitability mapping — Landsat land cover, MODIS vegetation phenology and SRTM elevation feed species distribution models that flag where triatomine habitat is most suitable across Latin America's dry forests and scrublands. Satellite data maps the environment, not the insect itself.
- Coastal cholera risk from sea surface temperature and phytoplankton bloom mapping — Vibrio cholerae persists in marine reservoirs tied to phytoplankton and zooplankton blooms. SST anomalies and chlorophyll-a signals from MODIS, VIIRS and Sentinel-3 can precede clinical case surges by one to three weeks, giving health authorities a narrow but real warning window.
- Coastal algal bloom alerts for beach management — Ocean-colour satellites detect chlorophyll-a and phycocyanin proxies at coastal scales, giving beach managers days of warning before harmful algal blooms reach swimmers. This page explains the sensors, methods, honest limits and analytic products.
- Agricultural crop-residue burning and acute PM2.5 episode attribution — Post-harvest burning in South Asia and sub-Saharan Africa produces PM2.5 spikes that overwhelm ground monitors. VIIRS fire radiative power, MODIS aerosol optical depth, and HYSPLIT back-trajectories can attribute specific burning events to specific downwind populations.
- Cyanobacterial bloom detection for drinking water toxin risk — Cyanobacteria produce microcystins and other toxins that overwhelm conventional water treatment. Sentinel-2 and Sentinel-3 OLCI can track bloom onset and drift toward drinking-water intakes, though cloud cover and sub-pixel patches remain real operational limits.
- Dengue transmission risk mapping using urban heat and greenness — Urban heat islands and patchy vegetation create the thermal and habitat conditions that Aedes mosquitoes exploit. Satellite-derived land surface temperature, greenness and rainfall anomalies can map where those conditions converge weekly, giving health authorities a spatial head start before case counts rise.
- Dust storm detection and health-warning forecasting — Mineral dust plumes from the Sahara, Arabian Peninsula and Gobi routinely push PM10 past WHO thresholds within hours of lofting. Satellites detect the plume; models translate it into surface concentrations and 72-hour health warnings.
- Flood-driven waterborne disease risk from SAR inundation mapping — SAR satellites map flood extents through monsoon cloud cover within hours of acquisition. Overlaid with sanitation infrastructure and population data, those extents become actionable cholera, typhoid and hepatitis A risk surfaces for public health responders.
- Glyoxal column mapping for biomass-burning secondary aerosol exposure — TROPOMI's 3.5 km glyoxal retrievals let analysts trace secondary organic aerosol formation back to specific fire events and vegetation types, though bright surfaces and mixed land cover complicate source attribution.
- Formaldehyde column mapping as a secondary ozone and VOC precursor indicator — Tropospheric formaldehyde columns retrieved from satellite UV measurements act as a proxy for volatile organic compound emissions, a primary driver of ground-level ozone and secondary organic aerosol. Distinguishing biogenic from anthropogenic sources requires careful multi-day averaging and source attribution, but the public record of TROPOMI and OMI data makes it tractable.
- Health facility catchment and physical access mapping using terrain and road data — Satellite-derived elevation, road extraction and gridded population data combine to produce travel-time surfaces that show which communities genuinely cannot reach a clinic within an hour. Static maps lie; this method quantifies the gap.
- Wet-bulb globe temperature estimation for outdoor worker heat stress — Wet-bulb globe temperature integrates heat, humidity, wind and solar load into the occupational standard for outdoor work limits. Satellite inputs from MODIS, VIIRS, CERES and ERA5 can estimate gridded WBGT where no ground station exists, but a ±2–3°C uncertainty is real and must be declared to any user making work-rest decisions.
- Satellite land surface temperature for heatwave mortality lag-exposure modelling — Weather-station networks are too sparse to reconstruct the spatially continuous heat-exposure histories that distributed lag non-linear models require. MODIS and Landsat land surface temperature time series fill that gap, letting health authorities calibrate city-specific alert thresholds against locally observed mortality.
- Household solid-fuel combustion mapping as indoor air quality proxy — Where household surveys are thin, combining VIIRS nighttime fire detections, MODIS active fire radiative power, and census fuel-use priors lets analysts estimate district-level biomass and coal combustion intensity as a proxy for indoor PM2.5 burden.
- Legacy lead contamination risk mapping via spectral soil proxies — Hyperspectral sensors identify bare-soil mineral assemblages that co-occur with lead contamination at smelter fallout zones, mine tailings and demolition sites, producing spatial risk priors for childhood blood-lead exposure. Satellite data cannot directly detect lead or see through vegetation.
- Malaria vector habitat mapping from land surface and water data — Sentinel-2, Landsat and MODIS land surface temperature data can locate Anopheles breeding habitat weeks before peak transmission, giving vector-control teams a spatial head start. Cloud cover during the wet season is the hard limit.
- Co-emitted methane and CO as combustion health-exposure proxies — Where ground-level PM monitors are absent, co-emitted CH4 and CO columns from TROPOMI and MOPITT reveal incomplete combustion intensity and let analysts map downwind health-exposure corridors, with honest limits on vertical resolution.
- Mine tailings dust emission mapping for silicosis exposure burden — Dry mine tailings and haul roads emit respirable crystalline silica that causes irreversible silicosis. Sentinel-2 spectral indices, MODIS aerosol optical depth and ERA5 wind fields can map emission potential and downwind exposure corridors around active and legacy sites.
- Nighttime light as a proxy for health infrastructure reliability and energy poverty — VIIRS Day/Night Band radiance time series can expose chronic power instability at health facilities long before a ministry's grid reports register a fault. This page explains the physics, the products, and the honest limits of the method.
- Prenatal NO2 exposure mapping for adverse birth outcome risk — TROPOMI measures tropospheric NO2 at 3.5 km resolution with near-daily global coverage. Combined with land-use regression and trimester-resolved residential records, those columns can estimate gestational exposure windows linked to preterm birth and low birthweight at neighbourhood scale.
- School-proximity NO2 exposure mapping for child respiratory burden — Children breathe the air outside their classrooms for hours each day, yet most cities lack the monitoring density to quantify that exposure school by school. TROPOMI, GEMS and road-proximity downscaling change that calculus.
- River blackfly breeding habitat mapping for onchocerciasis transmission risk — Simulium blackflies breed only in fast, well-oxygenated river reaches. Combining Sentinel-1 SAR, Sentinel-2 vegetation indices and DEM-derived stream-power models lets public-health teams map those reaches and focus larviciding where it counts.
- PM2.5 surface concentration estimation via aerosol optical depth — Satellite aerosol optical depth measures how much sunlight a column of air scatters, not what anyone inhales at street level. Converting AOD to PM2.5 requires physical and statistical modelling that is honest about its own limits.
- Pollen season onset and allergen load tracking via vegetation phenology — Satellite vegetation indices from MODIS, Sentinel-2 and Landsat track canopy green-up timing as a proxy for pollen season onset. The signal is real but indirect: local calibration against pollen trap networks is required before regional allergen forecasts become actionable.
- Environmental health risk mapping in refugee and displacement settlements — Satellite imagery from Sentinel-1, Sentinel-2 and commercial VHR sensors can map sanitation proximity, vegetation loss and flood-driven waterborne risk across displacement settlements, giving WASH planners spatial evidence they rarely have on the ground.
- Rift Valley fever outbreak risk mapping from flood and vegetation anomalies — Anomalous flooding and rapid vegetation green-up create the temporary breeding pools that amplify Rift Valley fever in Aedes mosquitoes. Sentinel-1 SAR and MODIS NDVI anomalies can flag high-risk dambos 2–4 weeks before outbreak reports reach health authorities.
- Schistosomiasis transmission risk from freshwater snail habitat mapping — Bulinus and Biomphalaria snails colonise slow, warm, vegetated freshwater bodies detectable from orbit. Sentinel-2 water indices and MODIS land surface temperature can map suitable habitat at sub-kilometre scale to focus mass drug administration where transmission risk is highest.
- SO2 plume mapping for industrial pollution health burden assessment — UV backscatter retrievals from TROPOMI and OMI can pinpoint large SO2 point sources at 3.5 × 5.5 km resolution, feed dispersion models, and estimate downwind population exposure for health impact assessments.
- Stratospheric ozone column mapping and UV index health risk — Satellite retrieval of total ozone column in Dobson units, translated into surface UV-B irradiance and WHO UV Index, underpins public health advisories on skin cancer and photokeratitis risk. TROPOMI, OMI, GOME-2 and EPIC together provide daily global coverage with sub-daily revisit near the poles where depletion events matter most.
- Temperature inversion detection for trapped urban pollution health alerts — Thermal inversions cap vertical mixing and compress pollutants into a shallow surface layer that satellite column measurements routinely understate. Combining MODIS/VIIRS land surface temperature, ERA5 boundary-layer height, and TROPOMI NO2 columns makes the trap visible and correctable.
- Tick-borne encephalitis habitat range expansion from vegetation and climate data — Ixodes tick populations are advancing into higher latitudes and elevations as winters shorten. Combining MODIS land surface temperature seasonality, VIIRS snow-cover duration, and Sentinel-2 forest-edge density lets health agencies map where TBE risk is arriving before the first human cases confirm it.
- Tropospheric NO2 exposure mapping from orbit — Satellite spectrometers measure nitrogen dioxide columns daily at sub-city resolution, exposing gaps between reported emissions and actual population exposure. TROPOMI, GEMS and TEMPO together now offer both the spatial detail and the hourly diurnal cycle needed for credible public-health burden estimates.
- Tropospheric ozone burden mapping for surface-level health risk — Tropospheric ozone forms in sunlight from NOx and VOC precursors and peaks in afternoon hours, when respiratory risk is highest. Geostationary sensors TEMPO and GEMS now resolve this diurnal cycle hourly, enabling city-scale exposure mapping that was impossible with daily LEO overpasses alone.
- Urban heat island intensity mapping for preterm birth heat exposure — Urban heat islands impose a thermal burden that regional weather stations systematically underestimate. Landsat and MODIS land surface temperature data, disaggregated to neighbourhood scale, can quantify that extra exposure during the critical third trimester.
- Urban heat health vulnerability mapping for excess mortality risk — Satellite land surface temperature at 30–70 m resolution, combined with census social vulnerability data, pinpoints city blocks where heatwave excess mortality risk is highest. The method is powerful and honest about its limits: LST is not air temperature.
- Visceral leishmaniasis sandfly habitat mapping from land surface data — Phlebotomine sandflies, vectors of visceral leishmaniasis, occupy micro-climatic niches detectable through MODIS land surface temperature, Sentinel-2 bare-soil fraction and SMAP soil moisture. Combined, these layers produce habitat suitability surfaces used to prioritise indoor residual spraying campaigns across South Asia and East Africa.
- Wildfire smoke attribution and downwind population exposure — Satellite fire radiative power retrievals and Lagrangian dispersion modelling can trace PM2.5 episodes at receptor cities back to specific fire events, but separating wildfire smoke from co-located industrial aerosol remains genuinely difficult.