An Overview of Data for Drought, Vegetation, Water and Environmental Analysis
Climate and Earth-observation data are often distributed as raster products: spatial grids in which every cell represents a measured, modeled, or classified condition. Depending on the dataset, a raster cell may contain precipitation, temperature, soil moisture, vegetation cover, evapotranspiration, snow depth, land-cover class, or a drought index. These products make it possible to compare environmental conditions across farms, watersheds, counties, ecosystems, and entire countries.
The raster datasets available through the Climate Engine data catalog come from numerous scientific and government providers, including NASA, NOAA, the USGS, the European Space Agency, ECMWF, the U.S. Forest Service, universities, and other research organizations. The catalog includes climate and hydrology grids, satellite observations, drought products, forecasts, hazard layers, atmospheric data, climate projections, and land-cover overlays.
This analysis focuses on the raster products themselves, what they measure, and how they can be applied.
What Is a Climate Raster Product?
A raster divides a geographic area into regularly spaced cells or pixels. Each pixel contains a value associated with a variable or category.
For example:
- A precipitation raster may report daily rainfall in millimeters.
- A temperature raster may contain the maximum temperature for each grid cell.
- A vegetation raster may report an NDVI value or percentage of plant cover.
- A land-cover raster may assign each cell to forest, cropland, urban land, or water.
- A drought raster may show standardized departures from normal moisture conditions.
Raster products are especially useful because they preserve spatial variation. A single weather station describes conditions at one location, while a raster can represent conditions continuously across a landscape.
The available products range from approximately 10-meter satellite imagery to climate and forecasting grids with cells several kilometers or tens of kilometers wide. Product selection therefore depends on both the environmental question and the geographic scale of the decision.
Major Categories of Climate and Earth-Observation Raster Products
| Product category | Representative datasets and variables | Common applications |
| Climate and hydrology | CHIRPS, gridMET, PRISM, ERA5-Land, TerraClimate, NLDAS, GPM | Drought analysis, crop-weather monitoring, water balance, climate trends |
| Satellite imagery | Landsat, Sentinel-2, HLS, MODIS, VIIRS | Crop condition, vegetation change, surface water, burn severity, land monitoring |
| Drought and water stress | SPI, SPEI, EDDI, ESI, VegDRI, ForDRI, GRACE drought indicators | Early warning, flash-drought detection, agricultural drought assessment |
| Evapotranspiration | OpenET, SSEBop, PML and MODIS- or VIIRS-based ET | Irrigation assessment, consumptive water use, water allocation |
| Vegetation and rangelands | NDVI, EVI, RAP, RCMAP, tree canopy cover | Forage monitoring, restoration, land degradation and habitat assessment |
| Snow and cold-region hydrology | SNODAS, ERA5-Land snow variables, NDSI | Snowpack monitoring, runoff planning, water-supply analysis |
| Fire and hazards | CEMS fire products, MODIS burned area, MTBS, ERC | Fire detection, fuel dryness, burn extent and recovery monitoring |
| Forecast products | GEPS, CFS-gridMET, drought outlooks, reference ET forecasts | Short-term planning, irrigation scheduling, drought preparedness |
| Climate projections | NEX-GDDP-CMIP6 and future drought layers | Climate adaptation, infrastructure planning, scenario analysis |
| Land and resource overlays | NLCD, Cropland Data Layer, ESA WorldCover, wetland and valley-bottom layers | Exposure mapping, stratification, land-use analysis and reporting |
1. Precipitation Raster Products
Precipitation is one of the most widely used raster variables in agriculture, hydrology, and drought monitoring.
CHIRPS
The Climate Hazards Group InfraRed Precipitation with Station data, or CHIRPS, combines satellite observations, climatology, and rain-gauge information. Its daily product provides approximately 4.8-kilometer rainfall estimates from 1981 to the near-present across much of the globe. It is particularly useful for rainfall trend analysis and seasonal drought monitoring in regions where weather-station coverage is limited.
Common applications include:
- Monitoring delayed rainy-season onset
- Calculating seasonal rainfall accumulation
- Identifying rainfall deficits in rainfed agricultural regions
- Comparing current rainfall with historical conditions
- Supporting food-security and humanitarian early-warning systems
- Mapping dry spells during critical crop-development periods
GPM, PERSIANN and Other Satellite Precipitation Products
Satellite precipitation products can provide broader and more frequent coverage than many station networks. They are useful for near-real-time monitoring, especially across remote, mountainous or data-sparse regions.
However, satellite rainfall estimates should not automatically be treated as without error. Performance can vary by terrain, storm type, season and region. Where possible, satellite estimates should be checked against gauges or local hydrological records.
PRISM, gridMET and Regional Climate Grids
For the lower 48 US states, products such as PRISM and gridMET provide spatially detailed climate information.
GridMET offers daily surface meteorological data at approximately four-kilometer resolution. It combines the spatial characteristics of PRISM with temporal information from NLDAS-2 and includes precipitation, temperature, humidity, wind, radiation, reference evapotranspiration, and several drought-related variables. It is designed for ecological, agricultural, and hydrological modeling.
Typical uses include:
- Crop-weather assessments
- Growing-degree-day calculations
- Reference evapotranspiration estimation
- Wildfire fuel-condition analysis
- Watershed modeling
- Agricultural insurance and risk studies
- Historical climate comparisons
2. Temperature, Humidity, Radiation and Wind Products
Climate rasters frequently include more than temperature and precipitation. Variables such as humidity, solar radiation, vapor-pressure deficit, and wind speed may be equally important.
These variables support analysis of:
- Heat stress
- Crop water demand
- Livestock exposure
- Wildfire potential
- Evaporative demand
- Frost and freeze risk
- Solar-energy potential
ERA5-Land is a global reanalysis product. Reanalysis combines historical observations with physically based modeling to produce spatially complete and coherent records. The daily ERA5-Land collection includes temperature, dew point, precipitation, radiation, wind, snow, and derived drought variables at approximately 11.1-kilometer resolution.
Reanalysis products are valuable when consistent multi-decade coverage is more important than local field-scale detail. They are often used for regional studies, historical reconstruction, model inputs, and comparisons between countries.
3. Satellite Surface-Reflectance Products
Surface-reflectance imagery measures the portion of incoming radiation reflected by the Earth’s surface after atmospheric effects have been reduced. These products form the foundation for many vegetation, water, soil, and disturbance indices. They allow for broad coverage of traditionally data-sparse regions.
Sentinel-2
Sentinel-2 surface-reflectance imagery provides visible, near-infrared, and shortwave-infrared bands at resolutions as fine as 10 meters. The available raster variables include raw spectral bands and derived metrics such as NDVI, EVI, NDRE, SAVI, MSAVI, NDWI, NDSI, NBR, bare-soil indices, and false-color composites.
Applications include:
- Mapping crop strength within fields
- Detecting vegetation stress
- Monitoring irrigation patterns
- Identifying surface-water changes
- Mapping snow cover
- Evaluating burn severity
- Detecting bare soil and erosion
- Monitoring wetland and riparian vegetation
- Comparing restoration sites with surrounding land
The relatively fine spatial resolution makes Sentinel-2 suitable for farms, restoration sites, urban areas and other localized applications. Its optical sensors cannot observe the surface clearly through clouds, however.
Landsat
Landsat provides a longer historical record than Sentinel-2 and is well suited to multi-decadal land-change analysis. Although its 30-meter pixels are coarser than Sentinel-2’s highest-resolution bands, the Landsat archive is valuable for examining long-term changes in vegetation, irrigation, urbanization, water bodies, wildfire effects, and land use.
Harmonized Landsat and Sentinel-2
Harmonized Landsat and Sentinel-2 products combine observations from both satellite systems into a more consistent record.
MODIS and VIIRS
MODIS and VIIRS products have coarser spatial resolution than Landsat or Sentinel-2 but generally offer more frequent observations and broad geographic coverage.
They are often better suited to:
- Regional vegetation monitoring
- National drought assessment
- Large-area land-surface-temperature analysis
- Phenology and seasonal vegetation tracking
- Rapid environmental screening
- Continental or global comparisons
The choice between high-resolution and high-frequency imagery depends on whether the analysis must distinguish small features or detect change quickly across large areas.
4. Vegetation Indices and Crop-Condition Products
Vegetation indices transform spectral bands into indicators related to plant greenness, canopy structure, chlorophyll, or moisture disturbance.
NDVI
The Normalized Difference Vegetation Index is the most widely recognized vegetation index. It is useful for tracking general vegetation greenness and seasonal development.
NDVI can support:
- Crop-condition monitoring
- Drought-impact assessment
- Rangeland productivity analysis
- Identification of unusually green or stressed areas
NDVI should not be treated as a direct measurement of yield or biomass without calibration. It can also saturate in dense vegetation.
EVI
The Enhanced Vegetation Index can perform better than NDVI in areas with dense vegetation and is designed to reduce some atmospheric and soil-background effects.
NDRE and Chlorophyll-Sensitive Indices
The Normalized Difference Red Edge index and related red-edge metrics can be sensitive to chlorophyll and canopy conditions. They are commonly considered for crop nitrogen assessment, later-season crop monitoring, and detection of stress before changes become visually obvious.
SAVI and MSAVI
The Soil Adjusted Vegetation Index and Modified Soil Adjusted Vegetation Index are useful where vegetation cover is sparse and exposed soil strongly influences reflectance. They may be preferable to NDVI in arid lands, recently planted fields and degraded landscapes.
NDWI and Related Moisture Indices
Different formulations of the Normalized Difference Water Index can be used to investigate vegetation moisture, surface water or moisture-related land conditions. Because several NDWI formulas exist, analysts must verify which spectral bands are used before interpreting the result.
5. Drought Raster Products
No single drought raster fully represents drought. Meteorological, agricultural, hydrological, and ecological drought develop over different time scales and affect different parts of the environment.
A stronger drought-monitoring workflow combines several indicators.
Standardized Precipitation Index
SPI compares accumulated precipitation with the historical distribution for the same location and time scale.
Short accumulation periods may identify rapidly developing rainfall deficits, while longer periods may be more relevant to reservoirs, groundwater, and prolonged drought.
Standardized Precipitation Evapotranspiration Index
SPEI incorporates both precipitation and atmospheric water demand. This can make it more responsive than precipitation-only indicators during unusually hot conditions.
Evaporative Demand Drought Index
EDDI focuses on anomalies in atmospheric evaporative demand. It can help identify conditions that increase moisture loss from soils and vegetation even before severe precipitation deficits become apparent.
Evaporative Stress Index
The Evaporative Stress Index identifies anomalies in actual evapotranspiration using remotely sensed land-surface-temperature information. Four- and twelve-week ESI products can reveal areas where vegetation is using unusually little or unusually large amounts of water.
Because land-surface temperature responds quickly to declining moisture availability, ESI can help identify crop stress and emerging flash drought associated with hot, dry, and windy conditions.
GRACE, VegDRI and ForDRI
GRACE-derived drought products provide information related to changes in terrestrial water storage, including deeper water components that may not be visible in surface vegetation indices.
VegDRI (Vegetation Drought Response Index) integrates vegetation observations with climate and environmental information to represent vegetation-related drought stress. ForDRI (Forest Drought Response Index) applies a similar concept to forested environments.
Together, these products allow analysts to distinguish between:
- Short-term vegetation stress
- Rainfall deficits
- High evaporative demand
- Soil-moisture depletion
- Longer-term water-storage decline
6. Evapotranspiration and Agricultural Water-Use Products
Evapotranspiration is the combined transfer of water to the atmosphere through evaporation and plant transpiration. It is central to agricultural water management because it represents a major component of consumptive water use.
OpenET provides monthly 30-meter evapotranspiration estimates across the contiguous United States. It includes outputs from multiple satellite-driven models and an ensemble value created after filtering model outliers.
ET rasters can be used for:
- Comparing water use among fields
- Evaluating irrigation performance
- Identifying unusually high or low crop water consumption
- Estimating seasonal consumptive use
- Examining drought impacts on vegetation
- Prioritizing areas for field inspection
ET must be interpreted carefully. High ET can indicate vigorous, well-watered vegetation, but it can also represent high water consumption. Low ET may indicate efficient water use, sparse vegetation, harvested fields, fallow land, or severe stress. Land cover and crop calendars are therefore essential context.
7. Rangeland and Ecosystem Products
Rangeland raster products translate satellite observations and field measurements into estimates of vegetation cover, production, and ecological composition.
The Rangeland Analysis Platform provides annual fractional-cover estimates for annual grasses and forbs, perennial grasses and forbs, shrubs, trees, litter, and bare ground. Its 30-meter annual cover product provides pixel-level percentages across the contiguous United States.
Applications include:
- Monitoring annual-grass expansion
- Mapping bare-ground exposure
- Evaluating restoration outcomes
- Screening for erosion and degradation risk
- Supporting grazing and habitat assessments
Other vegetation products, including RCMAP, tree-canopy cover and remotely sensed production estimates, can extend this analysis to ecosystem structure, biomass and long-term land-condition change.
8. Snow, Surface Water and Hydrological Products
Snow-related rasters include snow cover, snow depth, snow-water equivalent and snow indices.
SNODAS (Snow Data Assimilation System) and other snow products can support:
- Seasonal water-supply forecasting
- Watershed runoff assessment
- Reservoir planning
- Flood-risk screening
- Drought recovery analysis
- Mountain ecosystem monitoring
NDSI (Normalized Difference Snow Index) derived from optical satellite imagery helps map snow-covered areas, while modeled or assimilated snow products can provide estimates of snow depth and water equivalent.
Surface-water analysis can also use spectral indices, land-cover products and multi-date satellite imagery to identify reservoir changes, wetland inundation, flood extent and seasonal water persistence.
9. Wildfire and Disturbance Products
Raster products support wildfire analysis before, during and after an event.
Before a fire, meteorological products can describe:
- Temperature
- Humidity
- Wind
- Fuel moisture
- Vapor-pressure deficit
- Drought and vegetation dryness
During or shortly after a fire, active-fire and burned-area products can identify affected locations.
Longer-term products such as Monitoring Trends in Burn Severity can be used to evaluate:
- Burn extent
- Fire severity
- Vegetation loss
- Repeated burning
The Normalized Burn Ratio and related differenced indices can help compare pre-fire and post-fire surface conditions.
10. Forecast Raster Products
Forecast rasters extend geospatial analysis from monitoring into anticipatory decision support and help to quantify uncertainties.
Available forecast categories include short-range and subseasonal weather products, drought outlooks, reference evapotranspiration forecasts, and climate-forecast products.
Potential applications include:
- Estimating irrigation demand for the coming week
- Preparing for crop heat stress
- Identifying areas at risk of continued rainfall deficit
- Planning field operations
- Anticipating elevated fire conditions
- Comparing forecast scenarios with current land conditions
Forecast rasters contain uncertainty and should be treated probabilistically. Their value usually decreases with lead time, particularly for regional precipitation.
11. Climate-Projection Products
Historical data describe what has occurred. Climate-projection rasters explore how conditions may change under different emissions and economic pathways.
NEX-GDDP-CMIP6 provides downscaled global climate scenarios derived from multiple CMIP6 general circulation models. The collection includes numerous models and scenarios such as SSP2-4.5 and SSP5-8.5, allowing users to examine a range of possible future conditions rather than relying on one deterministic forecast.
Applications include:
- Climate-risk screening
- Agricultural suitability studies
- Heat-risk assessment
- Long-term water planning
- Comparison of near-, mid- and late-century conditions
Climate projections should generally be evaluated as ensembles. Agreement across several models may provide stronger evidence than the output of a single model, while model disagreement highlights uncertainty that should remain visible in planning.
12. Land-Cover and Contextual Raster Overlays
Environmental variables become more useful when they are connected to the type of land being affected.
Available raster overlays include the National Land Cover Database, National Wetlands Inventory, USDA Cropland Data Layer, ESA WorldCover, valley-bottom products, and groundwater-dependent ecosystem indicators.
These layers can answer questions such as:
- Which crops are exposed to drought?
- How much wetland area experienced declining vegetation?
- Are temperature anomalies concentrated in developed land?
- Which land-cover types burned?
- Is high evapotranspiration occurring in irrigated cropland or natural vegetation?
- Are ecosystem changes occurring inside valley bottoms or riparian corridors?
- Which agricultural areas overlap areas of long-term water stress?
Categorical rasters are especially valuable for masking and stratification. Instead of calculating the average drought index across an entire county, an analyst can calculate it only for cropland, forests, wetlands or a particular crop type.
Practical Applications Across Sectors
Agriculture
Climate raster products can support planting decisions, crop-condition monitoring, irrigation assessment, drought early warning, growing-degree-day calculations and regional production-risk analysis.
Using multiple descriptive indicators is often more informative than relying on a single indicator.
Water Resources
Water managers can combine precipitation, snow-water equivalent, evapotranspiration, drought indices, land cover, and climate projections to evaluate supply and demand.
Potential outputs include:
- Irrigation-consumption estimates
- Drought-persistence assessments
- Climate-change stress tests
Agricultural Risk and Resilience
Precipitation, drought, fire, land cover and forecast rasters can be integrated into risk-screening systems. The goal is not simply to map a hazard, but to identify where the hazard overlaps exposed people, infrastructure, agriculture or ecosystems.
How to Select the Right Raster Product
Before choosing a dataset, answer five questions.
1. What process must be measured?
Rainfall, vegetation greenness, crop water use, soil moisture and groundwater storage are related but not interchangeable.
2. What spatial resolution is required?
A 10-meter product may distinguish individual fields or stream corridors. A 10-kilometer climate grid may be appropriate for regional conditions but unsuitable for field-level conclusions.
3. What temporal frequency is required?
Daily products are useful for rapidly changing hazards. Monthly or annual products may be more appropriate for water analysis, land-cover change and long-term planning.
4. Is the objective monitoring, historical analysis or forecasting?
Observed satellite data, reanalysis, forecasts and climate projections answer different questions and carry different forms of uncertainty.
5. What validation information is available?
Local stations, stream gauges, crop records, field observations and administrative reports can help determine whether a raster product performs adequately in the area of interest.
Limitations and Important Considerations
Raster products make large-area analysis possible, but they should not be interpreted without accurate context.
Important limitations include:
- Pixel values represent areas, not exact point measurements.
- Coarse grids may conceal local terrain and land-use differences.
- Optical imagery is affected by clouds, haze, and shadows.
- Satellite indices are often proxies rather than direct measurements.
- Reanalysis products depend on both observations and models.
- Forecast uncertainty generally increases with lead time.
- Climate projections are scenarios, not predictions of a single future.
- Derived indices depend on reference periods and calculation methods.
- Resampling can smooth data and create an appearance of detail that was not present in the original data.
An informative workflow preserves the original resolution, documents processing choices, examines multiple indicators and clearly distinguishes measured, modeled and derived information.
Baseline Questions to ask when building an analysis
Which raster products are best for drought monitoring?
A practical drought-monitoring system may combine precipitation-based indices such as SPI, water-balance indices such as SPEI, evaporative-demand indicators such as EDDI, vegetation or evapotranspiration indicators such as ESI, and longer-term water-storage information from GRACE-derived products.
What is the best raster resolution for agriculture?
Field-level monitoring generally benefits from products between 10 and 30 meters, such as Sentinel-2, Landsat, HLS and OpenET. Regional agricultural monitoring may use coarser products such as MODIS, VIIRS, CHIRPS or gridMET because they provide broader coverage or more frequent observations.
Critical Assessment
Climate raster products provide a practical foundation for environmental analysis because they connect climate, water, vegetation and hazards to specific locations.
The most valuable approach is rarely to select one raster. Instead, analysts should build a small, purpose-driven group of complementary products. Precipitation can describe water input, temperature and vapor-pressure deficit can describe atmospheric stress, and vegetation indices can reveal the landscape response.
When these variables are combined with climate zone elements like land cover, crop type, and wetlands, raster products can support decisions in agriculture, water management, and climate adaptation.