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Land Use/Land Cover Data Access and Tools

NASA data range from global assessments of snow cover albedo to food insecurity cropland extent measurements. Our datasets and tools help researchers translate these interconnected data points into actionable knowledge.

Commonly Used Land Cover/Crop Extent Data at a Glance

Spatial Resolution	Spatial Coverage	Temporal Resolution	Temporal Coverage	Spectral Resolution	Satellite/ Platform	Sensor(s)/ Model Name	Observation or Model	File Format
500 m	Global	1-2 days	2001-2021	36 bands ranging from 0.4 µm to 14.4 µm	Terra and Aqua	MODIS	Observation	HDF-EOS
30 m, 90 m, 1 km	Regional datasets	Multi-year	2007-2016 (varies)	Varies	Derived from Landsat data	GFSAD	Observation	GeoTIFF
30 m	Global	Yearly	2001-2019	Varies	Derived from Landsat data	GLanCE	Observation	GeoTIFF

Land Use/Land Cover Datasets

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Filters

Dataset Sort descending	Version	Platform	Instrument	Temporal Extent	Spatial Extent	Data Format
PROVE Surface albedo of Jornada Experimental Range, New Mexico, 1997	1	FIELD INVESTIGATION	PYRANOMETERS, CAMERAS	1997-05-22 to 1997-05-27	N: 32.5 S: 32.5 E: -106.75 W: -106.75	CSV
Resilience of Coastal Wetlands to Sea Level Rise, CONUS, 1996-2100	1	MODELS	Computer	1996-01-01 to 2100-12-31	N: 49.2069 S: 22.7276 E: -64.9678 W: -127.984	multiple
RLC AVHRR-Derived Land Cover, Former Soviet Union, 15-km, 1984-1993	1	NOAA-9	AVHRR	1984-01-01 to 1993-12-31	N: 75 S: 35.2389 E: 180 W: 19.816	multiple
RLC AVHRR-Derived Land Cover, Former Soviet Union, Far East, 1-km, 1990	1	NOAA-9	AVHRR	1990-05-15 to 1990-08-17	N: 71 S: 23.21 E: 180 W: 25	multiple
RLC Forest Cover Map of the Former Soviet Union, 1990	1	NOT APPLICABLE	NOT APPLICABLE	1990-01-01 to 1990-12-31	N: 71 S: 23.21 E: 180 W: 25	BMP
RLC Forest Cover of the Former Soviet Union, 1973	1	NOT APPLICABLE	NOT APPLICABLE	1973-01-01 to 1973-12-31	N: 75 S: 35.1659 E: 170 W: 19.8165	multiple
RLC Generalized Forest Map of the Former Soviet Union, 1-km	1	NOT APPLICABLE	NOT APPLICABLE	1998-01-01 to 1998-12-31	N: 71 S: 23.21 E: 180 W: 25	BMP
RLC Vegetative Cover of the Former Soviet Union, 1990	1	MAPS	DIGITIZER	1973-01-01 to 1973-12-31	N: 75 S: 35.1659 E: 170 W: 19.8165	multiple
Russian Boreal Forest Disturbance Maps Derived from Landsat Imagery, 1984-2000	1	Terra, LANDSAT-5	MODIS, TM, ETM+	1984-06-01 to 2000-08-31	N: 65.3219 S: 43.7625 E: 138.627 W: 30.9828	GeoTIFF
SAFARI 2000 ALI/ETM+ Tandem Image Pair for Skukuza, South Africa, May 2001	1	EO-1, LANDSAT-7	ALI, SPECTRORADIOMETERS, ETM+	2001-05-30 to 2001-05-30	N: -23.5902 S: -25.5025 E: 33.1174 W: 30.7568	Binary
SAFARI 2000 AVHRR-derived Land Surface Temperature Maps, Africa, 1995-2000	1	NOAA-14	AVHRR	1995-01-01 to 2000-12-31	N: 43.71 S: -42.24 E: 64.52 W: -24.6	multiple
SAFARI 2000 Carbon in Live Vegetation, 0.5-Deg (Olson)	1	NOT APPLICABLE	NOT APPLICABLE	1960-01-01 to 1980-12-31	N: 5 S: -35 E: 60 W: 5	multiple
SAFARI 2000 Estimated BVOC Emissions for Southern African Land Cover Types	1	METEOROLOGICAL STATIONS, Terra	THERMOMETERS, MODIS	2001-01-01 to 2001-12-31	N: 5 S: -35 E: 60 W: 5	CSV
SAFARI 2000 Hydrographic Data, 1-Deg, Release 2.2 (Cogley)	1	NOT APPLICABLE	NOT APPLICABLE	1970-01-01 to 1990-01-01	N: 5 S: -35 E: 60 W: 5	multiple
SAFARI 2000 Land Cover from AVHRR, 1-Deg, 1987 (Defries and Townshend)	1	NOAA-9, NOAA-10, NOAA-11	AVHRR	1987-01-01 to 1987-12-31	N: 5 S: -35 E: 60 W: 5	multiple
SAFARI 2000 Land Cover from AVHRR, 1-km, 1992-1993 (Hansen et al.)	1	NOAA-11, NOAA-9, NOAA-10	AVHRR	1992-01-01 to 1993-12-31	N: 5 S: -35 E: 60 W: 5	Shapefile
SAFARI 2000 Land Cover from AVHRR, 8-km, 1984 (DeFries et al.)	1	NOAA-10, NOAA-9, NOAA-11	AVHRR	1984-01-01 to 1984-12-31	N: 5 S: -35 E: 60 W: 5	multiple
SAFARI 2000 MODIS L3 Albedo and Land Cover Data, Southern Africa, Dry Season 2000	1	Terra	MODIS	2000-07-11 to 2000-10-15	N: 5 S: -30 E: 60 W: 5	Shapefile
SAFARI 2000 MODIS Water and Heat Fluxes, Maun, Botswana, Dry Season 2001	1	FIXED OBSERVATION STATIONS, FIELD INVESTIGATION, Terra, MODELS	PRESSURE SENSORS, WIND MONITOR, HUMIDITY SENSORS, NET RADIOMETERS, EDDY CORRELATION DEVICES, SOIL HEAT FLUX TRANSDUCER, MODIS, Computer	2001-09-02 to 2001-09-29	N: -17.9946 S: -21.0004 E: 24.5004 W: 21.4946	Shapefile
SAFARI 2000 NBI Vegetation Map of the Savannas of Southern Africa	1	FIELD INVESTIGATION	DIGITIZER	1968-01-01 to 2000-12-31	N: 0 S: -35 E: 43 W: 8	Shapefile
SAFARI 2000 Potential Vegetation, 5-min (Ramankutty and Foley)	1	NOT APPLICABLE	NOT APPLICABLE	1753-01-01 to 1992-12-31	N: 5 S: -35 E: 60 W: 5	multiple
SAFARI 2000 Soil Profile Data (ISRIC-WISE)	1	NOT APPLICABLE	NOT APPLICABLE	1950-01-01 to 1995-12-31	N: 5 S: -35 E: 60 W: 5	Text File
SAFARI 2000 Tree Cover from AVHRR, 1-km, 1992-1993 (DeFries et al.)	1	NOAA-9, NOAA-10, NOAA-11	AVHRR	1992-01-01 to 1993-12-31	N: 5 S: -35 E: 60 W: 5	multiple
SAFARI 2000 Vegetation and Soils, 1-Deg (Wilson and Henderson-Sellers)	1	NOT APPLICABLE	NOT APPLICABLE	1900-01-01 to 1999-12-31	N: 5 S: -35 E: 60 W: 5	Binary
SAR Subsets for Selected Field Sites, 2007-2010	1	ALOS	PALSAR	2007-06-05 to 2010-12-14	N: 78.9459 S: -11.3224 E: -28.8805 W: -150.714	Shapefile

Featured Land Use/Land Cover Observation Method: Sentinel-1

Sentinel-1 is a European Space Agency (ESA) satellites designed to acquire Earth-observation measurements and carries a C-band synthetic aperture radar (SAR) to provide all-weather, day-and-night imagery of Earth's surface. The platform was launched on April 3, 2014, and images Earth every six days. Sentinel-1 SAR data can reveal the surface roughness of the land, oil and vegetation moisture content, and vegetation density. The dadar data can also be used to determine water surface conditions such as waviness and identify water inundation into inland areas and beneath forest canopies.

Learn More About Sentinel-1

Earthdata graphic identifier on top of image of Earth

Sentinel-1 Images Reveal Changes in the Earth’s Surface Over One Year

NASA's ASF DAAC released the Global Seasonal Sentinel-1 Interferometric Coherence and Backscatter Dataset.

HLS data near Columbus, Nebraska from 2022

HLS: Two Together Better than Two Apart

The purpose of the Harmonized Landsat Sentinel-2 (HLS) project led by IMPACT, is to combine two or more data streams into a single data set and increase their value.

Automatically Generate a Radiometrically Terrain-Corrected Sentinel-1 Image Using Cloud Computing

Learn how to use the CloudFormation Template to automate the processing of Sentinel-1 radiometrically terrain-corrected (RTC) products.

The rectangular image is a map of the St. Simons Island area of coastal Georgia. Land is colored white, roadways are black, inundated vegetation area are green, and water is colored blue. The Atlantic Ocean is in the lower-right of the image and its blue shaded area extends into waterways along the coast.

New Product Provides Detailed Maps of Water In and Around Landmasses

Sentinel-1 synthetic aperture radar (SAR) data are used to create maps of surface water extent for research, planning, and disaster response.

Land Use/Land Cover Data Tools

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