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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	Spatial Resolution	Data Format
Siberian Boreal Forest Aboveground Biomass and Fire Scar Maps, Russia, 1969-2007	1	FIELD INVESTIGATION, Terra, LANDSAT-7, LANDSAT-5, LANDSAT	STEEL MEASURING TAPE, MODIS, ETM+, TM, MSS	1969-07-01 to 2007-07-26	N: 69.8981 S: 64.7678 E: 166.474 W: 156.612		GeoTIFF
SISTER: Experimental Workflows, Product Generation Environment, and Sample Data, V004	4	NOAA Twin Otter, NASA ER-2	AVIRIS	2011-05-13 to 2018-01-26	N: 39.0817 S: 21.2023 E: -107.962 W: -158.055		multiple
SMAPVEX08 Land Cover Classification Map V001	1	FIELD SURVEYS, IRS-P6, SPOT-1	SOIL MOISTURE PROBE, SOIL TEMPERATURE PROBE, AWIFS, HRV	2008-06-01 to 2008-10-31	N: 39.1 S: 38.8 E: -75.6 W: -76.3	10 Meters x 10 Meters	Binary, ASCII
SMAPVEX12 Land Cover Classification Map V001	1	RADARSAT-2, SPOT-4	SAR, HRVIR	2012-06-07 to 2012-07-19	N: 50.21 S: 49.31 E: -98.27 W: -98.97	20 Meters x 20 Meters	GeoTIFF
SMAPVEX12 PALS Soil Moisture Data V001	1	AIRCRAFT	PALS	2012-06-12 to 2012-07-19	N: 49.96 S: 49.44 E: -97.85 W: -98.51	1500 Meters x 1500 Meters	CSV
SMAPVEX15 PALS Soil Moisture Data V001	1	AIRCRAFT	PALS	2015-08-02 to 2015-08-18	N: 31.87 S: 31.51 E: -109.84 W: -110.96	1500 Meters x 1500 Meters	CSV
SMAPVEX16 Iowa PALS Brightness Temperature and Soil Moisture Data V001	1	AIRCRAFT	PALS	2016-05-28 to 2016-08-16	N: 42.66 S: 42.28 E: -93.21 W: -93.58	500 Meters x 500 Meters	CSV
SMAPVEX16 Manitoba Land Cover Classification Map V001	1	LANDSAT-8, RADARSAT-2	OLI, SAR	2016-06-01 to 2016-07-31	N: 49.997539 S: 49.145916 E: -97.435997 W: -98.363559		GeoTIFF, TAR
SMAPVEX16 Manitoba PALS Brightness Temperature and Soil Moisture Data V001	1	AIRCRAFT	PALS	2016-06-08 to 2016-07-22	N: 49.79 S: 49.36 E: -97.75 W: -98.12	500 Meters x 500 Meters	CSV
SNF Forest Cover by Species/Strata	1	FIELD INVESTIGATION	VISUAL OBSERVATIONS	1976-01-01 to 1986-12-31	N: 48.1697 S: 47.6575 E: -91.7658 W: -92.5058		ASCII
Soil Moisture Active Passive (SMAP) L1-L3 Ancillary Static Data V001	1	NOT APPLICABLE	NOT APPLICABLE	2015-01-14 to Present	N: 86.4 S: -86.4 E: 180 W: -180		Binary, HDF5, ASCII
Soil Moisture Active Passive (SMAP) L4 Carbon Ancillary Parameters V001	1	NOT APPLICABLE	NOT APPLICABLE	2015-01-31 to Present	N: 86.4 S: -86.4 E: 180 W: -180		HDF5
Stocks of Surface Soil Organic Carbon Fractions, Great Plains Region, USA, 2007-2010	1	LABORATORY, FIELD INVESTIGATION, MODELS	CARBON ANALYZERS, SOIL SAMPLER, Computer	2007-05-01 to 2010-10-01	N: 45.8303 S: 31.2183 E: -94.4349 W: -111.932		multiple
Sub-global Scenarios that Extend the Global SSP Narratives: Literature Database, Version 1, 2014-2021	1.00	MODELS	Computer	2014-01-01 to 2021-12-31	N: 90 S: -90 E: 180 W: -180		Excel
Suomi-NPP VIIRS Level-2 Regional Normalized Difference Vegetation Index Data, version 2022.0	2022.0	Suomi-NPP	VIIRS	2012-01-02 to Present	N: 90 S: -90 E: 180 W: -180		netCDF-4
Suomi-NPP VIIRS Level-3 Global Mapped Normalized Difference Vegetation Index Data, version R2022.0	R2022.0	Suomi-NPP	VIIRS	2012-01-02 to Present	N: 90 S: -90 E: 180 W: -180		netCDF-4
Urban Biogenic CO2 fluxes: GPP, Reco and NEE Estimates from SMUrF, 2010-2019	1	Models, SATELLITES	Computer, MODIS	2010-01-01 to 2019-12-31	N: 60 S: -40 E: 155 W: -125		netCDF-4 classic
Urban Land Cover Maps for Mekelle, Ethiopia and Polokwane, South Africa, 2020	1	PlanetScope, WORLDVIEW-3	PSB.SD, WV110	2020-01-01 to 2020-12-31	N: 13.5692 S: -23.9404 E: 39.5708 W: 29.3151		multiple
Urban Landsat: Cities from Space	1.00	LANDSAT-5, LANDSAT-7	TM, ETM+	1999-01-01 to 2003-12-31	N: 90 S: -55 E: 180 W: -180		PDF, PNG
U.S. EPA National Priorities List (NPL) Sites Point Data with CIESIN Modifications, Version 2	2.0	MODELS	Computer	2014-02-27	N: 64.823 S: -14.3601 E: 151.78372 W: -176.6525		Excel, PNG, PDF, WMS
VEMAP 2: Annual Ecosystem Model Responses to U.S. Climate Change, 1994-2100	1	NOT APPLICABLE	NOT APPLICABLE	1994-01-01 to 2100-12-31	N: 50 S: 26 E: -66 W: -124		netCDF-3
VEMAP 2: Monthly Ecosystem Model Responses to U.S. Climate Change, 1994-2100	1	NOT APPLICABLE	NOT APPLICABLE	1994-01-01 to 2100-12-31	N: 50 S: 26 E: -66 W: -124		netCDF-3
Yale Center for Earth Observation (YCEO) Surface Urban Heat Islands, Version 4, 2003-2018	4.00	MODELS	Computer	2003-01-01 to 2018-12-31	N: 90 S: -90 E: 180 W: -180		GeoTIFF, 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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