


LP DAAC
The Land Processes Distributed Active Archive Center (LP DAAC) operates as a partnership between the United States Geological Survey (USGS) and the National Aeronautics and Space Administration (NASA) dedicated to enabling natural resource managers, disaster responders, academia, and industry to investigate, characterize, and monitor land surface processes. By providing access to trusted, well-documented earth science datasets at no cost, LP DAAC supports a large community of users across science applications ranging from agriculture and geology to urban heat and wildfire mitigation.
LP DAAC processes, archives, and distributes more than 14 petabytes of land remote sensing data from major missions such as Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER), Moderate Resolution Imaging Spectroradiometer (MODIS), and Visible Infrared Imaging Radiometer Suite (VIIRS), ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS), Global Ecosystem Dynamics Investigation (GEDI), Earth surface Mineral dust source InvesTigation (EMIT), and Harmonized Landsat Sentinel-2, (HLS). Users may obtain all data products distributed by LP DAAC by usingEarthdata Search or the many customizeddata tools.
In addition to archiving and distributing data, LP DAAC also provides resources like Python Jupyter notebooks through the LPDAAC Data ResourcesGitHub, and convenient data transformation tools like the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS). AppEEARS allows users to conduct point and area sub-setting of popular geospatial datasets from the LP DAAC and other federal archives.
NASA's Earth Observing System (EOS) program comprises a series of polar-orbiting and low-inclination satellites designed to monitor and understand Earth systems through long-term global observations. LP DAAC archives data for a number of EOS missions.
MODIS
The Moderate Resolution Imaging Spectroradiometer (MODIS) instrument is operating aboard both the Terra and Aqua spacecraft. It views the entire surface of the Earth every one to two days. MODIS data contribute to a range of land and water application areas including wildfire monitoring, temperature and emissivity changes, land surface change, vegetation and ecosystem dynamics, natural disasters, and agriculture studies. View a list ofMODIS products archived by LP DAAC.
ASTER
Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) data contribute to a wide array of global change-related application areas including vegetation and ecosystem dynamics, hazard monitoring, geology and soils, hydrology, and land cover change. The ASTER instrument is aboard the Terra satellite and is taskable and able to be scheduled for on-demand data acquisition requests. View a list ofASTER products archived by LP DAAC.
VIIRS
The Visible Infrared Imaging Radiometer Suite (VIIRS) is aboard both the NASA/NOAA Suomi National Polar-orbiting Partnership (Suomi NPP) and the NOAA-20 satellites. VIIRS observes the entire Earth’s surface twice each day, once during the day and once at night. VIIRS data contribute to a range of land and water application areas including wildfire monitoring, temperature and emissivity changes, land surface change, vegetation and ecosystem dynamics, natural disasters, and agriculture studies. Generated in a similar format to the Moderate Resolution Imaging Spectroradiometer (MODIS), VIIRS data products aim to provide continuity with the MODIS mission. View a list ofVIIRS products archived by LP DAAC.
ECOSTRESS
Principal Investigator: Simon Hook, NASA/Caltech Jet Propulsion Laboratory
The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) is aboard the International Space Station (ISS) and measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS addresses three overarching science questions: How is the terrestrial biosphere responding to changes in water availability? How do changes in diurnal vegetation water stress impact the global carbon cycle? Can agricultural vulnerability be reduced through advanced monitoring of agricultural water consumptive use and improved drought estimation? ECOSTRESS uses a multispectral thermal infrared radiometer to measure the surface temperature. The radiometer obtains detailed images of the Earth’s surface that can provide information on the temperature of an individual farmer’s field. View a list ofECOSTRESS products archived by LP DAAC.
EMIT
Principal Investigator: Robert O. Green, NASA Jet Propulsion Laboratory
The Earth Surface Mineral Dust Source Investigation (EMIT) instrument aboard the International Space Station (ISS) measures visible to short-wave infrared (VSWIR) wavelengths of the surface mineralogy of arid dust source regions via imaging spectroscopy. The data collected by the EMIT instrument will be used to map relative abundance of source minerals to advance our understanding of the current and future role of mineral dust in the radiative forcing (warming or cooling) of the atmosphere. View a list ofEMIT products archived by LP DAAC.
GEDI
Principal Investigator: Ralph Dubayah, University of Maryland
The Global Ecosystem Dynamics Investigation (GEDI) is a full-waveform lidar instrument aboard the International Space Station (ISS) that produces detailed observations of the 3-dimensional structure of the Earth’s surface. GEDI precisely measures forest canopy height, canopy vertical structure, and surface elevation which enhances our understanding of global carbon and water cycle processes, biodiversity, and habitat. GEDI is the first of its kind to provide high resolution laser ranging observations optimized for lidar measurements of the Earth’s forests and topography at the highest resolution and densest sampling of any other lidar instrument in orbit. Data from GEDI is archived and distributed by the LP DAAC. View a list ofGEDI products archived by LP DAAC.
HLS
Co-Investigators: Jeffrey Masek, NASA Goddard Space Flight Center and Junchang Ju, University of Maryland
The Harmonized Landsat Sentinel-2 (HLS) project is a NASA initiative to produce seamless, harmonized surface reflectance data from the Operational Land Imager (OLI) aboard the joint NASA/USGS Landsat 8 and Landsat 9 satellites and the Multi-Spectral Instrument (MSI) aboard Europe’s Copernicus Sentinel-2A, Sentinel-2B, and Sentinel-2C satellites. The aim is to produce seamless products with normalized parameters, which include atmospheric correction, cloud and cloud-shadow masking, geographic co-registration and common gridding, bidirectional reflectance distribution function, and spectral band adjustment. This will provide global observation of the Earth’s surface every 2-3 days with 30 meter spatial resolution. Applications that will benefit include agriculture assessment and monitoring, and phenology. View a list ofHLS products archived by LP DAAC.
SNWG OPERA Disturbance
Investigator: Matt Hansen, University of Maryland
The Global Land Disturbance Mapping for JPL Observation Products for End-Users for Remote Sensing Analysis (OPERA) at the University of Maryland, is sponsored by NASA and developed at the Jet Propulsion Laboratory (JPL) in response to scientific gaps identified by the Satellite Needs Working Group (SNWG). The OPERA land Disturbance (DIST) product suite will provide near-global, per-pixel land surface change from Harmonized Landsat Sentinel-2 (HLS) scenes. The primary focus of the DIST product suite is to map vegetation cover loss along with general disturbance trends every 2–3 days with 30 meter spatial resolution. For more information on the OPERA DIST product suite, visit the DISTJPL product site.
Future Missions
VIIRS JPSS-2/NOAA-21
VIIRS is aboard the NOAA-21 satellite, which was launched on November 10, 2022. After its launch, JPSS-2 was renamed NOAA-21. JPSS-2 is the third VIIRS platform, expanding upon the previously launched S-NPP and JPSS-1 platforms.VIIRS S-NPP and JPSS-1 products are distributed by LP DAAC. VIIRS has 22 spectral bands ranging from 412 nm to 12 µm. There are 16 moderate-resolution bands (750m at nadir), five image-resolution bands (375m), and one day-night band (DNB). VIIRS observes the entire Earth’s surface twice each day, once during the day and once at night. VIIRS data contribute to a range of land and water application areas including wildfire monitoring, temperature and emissivity changes, land surface change, vegetation and ecosystem dynamics, natural disasters, and agriculture studies. Generated in a similar format to MODIS, VIIRS data products aim to provide continuity with the MODIS mission.
NASA’s Earth Science Program is dedicated to the advancement of Earth remote sensing and the scientific use of satellite measurements to expand our understanding of Earth systems. LP DAAC collaborates with the Making Earth System Data Records for Use in Research Environments (MEaSUREs) projects to facilitate the introduction of long-term, consistent, high-quality data records to the land remote sensing community.
GFCC
Principal Investigator: John Townshend, University of Maryland
The Global Forest Cover Change (GFCC) collection is derived from enhanced Landsat Global Land Survey (GLS) datasets and provides global coverage information on surface reflectance, water cover, and forest cover change.
| Short Name | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|
| GFCC30FCC.001 | Land Cover | 30 | Multi-Year |
| GFCC30SR.001 | Land Cover | 30 | Multi-Year |
| GFCC30TC.003 | Land Cover | 30 | Multi-Year |
| GFCC30WC.001 | Land Cover, Water | 30 | Other |
GFSAD
Principal Investigator: Prasad Thenkabail, USGS
The Global Food Security-support Analysis Data (GFSAD) collection provides information on global croplands, including crop density and crop extent. The monitoring of global croplands is critical for policymaking and provides important baseline data that are used in many agricultural studies pertaining to water sustainability and food security.
| Short Name | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|
| GFSAD1KCD.001 | Cropland | 1000 | Multi-Year |
| GFSAD1KCM.001 | Cropland | 1000 | Multi-Year |
| GFSAD30AFCE.001 | Cropland | 30 | Multi-Year |
| GFSAD30AUNZCNMOCE.001 | Cropland | 30 | Multi-Year |
| GFSAD30EUCEARUMECE.001 | Cropland | 30 | Multi-Year |
| GFSAD30NACE.001 | Cropland | 30 | Multi-Year |
| GFSAD30SAAFGIRCE.001 | Cropland | 30 | Multi-Year |
| GFSAD30SACE.001 | Cropland | 30 | Multi-Year |
| GFSAD30SEACE.001 | Cropland | 30 | Multi-Year |
| GFSAD30VAL.001 | Cropland | 90 | Multi-Year |
GLanCE
Principal Investigators: Mark Friedl, Curtis Woodcock, Pontus Olofsson, Thomas Loveland, and Zhe Zhu
The Global Land Cover Mapping and Estimation (GLanCE) data record is an annual product derived from Landsat 5, 7, and 8. This project provides high-quality maps of global land cover, land use, and land cover change at 30 meter spatial resolution annually from 2001 to 2019. These data provide the user community with land cover type, land cover change, metrics characterizing the magnitude and seasonality of greenness of each pixel, and the magnitude of change.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| GLanCE30.001 | MEaSUREs GLanCE | Land Cover, Vegetation Indices (VI) | 30.0 | Yearly |
LSTE
Principal Investigator: Simon Hook, Jet Propulsion Laboratory
Co-investigator: Kerry Anne Cawse-Nicholson, Jet Propulsion Laboratory
The Land Surface Temperature and Emissivity (LSTE) collection provides global LSTE coverage for common use in surface energy balance studies, land surface modeling, climate change modeling, and urban heat island studies.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| CAM5K30CF.002 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| CAM5K30CF.003 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| CAM5K30CFCLIM.003 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| CAM5K30COVCLIM.003 | MEaSUREs LSTE | Emissivity | 25000.0 | Monthly |
| CAM5K30EM.002 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| CAM5K30EM.003 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| CAM5K30EMCLIM.003 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| CAM5K30UC.003 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| CAM5K30UC.002 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| CAM5K30UCCLIM.003 | MEaSUREs LSTE | Emissivity | 5600.0 | Monthly |
| GEOLST4KHR.002 | MEaSUREs LSTE | Land Surface Temperature (LST) | 4000.0 | < Daily |
| LEOLSTCMG30.002 | MEaSUREs LSTE | Land Surface Temperature (LST) | Monthly | |
| LEOLSTCMG30.001 | MEaSUREs LSTE | Land Surface Temperature (LST) | Monthly |
NASADEM
Principal Investigator: Sean Buckley, Jet Propulsion Laboratory
NASADEM extends the legacy of the Shuttle Radar Topography Mission (SRTM) by improving the digital elevation model (DEM) height accuracy and data coverage as well as providing several new data products. The improvements were achieved by reprocessing the original SRTM radar signal and telemetry data with updated algorithms and auxiliary data not available at the time of the original SRTM processing.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| NASADEM_HGT.001 | MEaSUREs NASADEM | Elevation | 30.0 | Multi-Day |
| NASADEM_SC.001 | MEaSUREs NASADEM | Elevation | 30.0 | Multi-Day |
| NASADEM_SHHP.001 | MEaSUREs NASADEM | Elevation | 30.0 | Multi-Day |
| NASADEM_SIM.001 | MEaSUREs NASADEM | Elevation | 30.0 | Multi-Day |
| NASADEM_SSP.001 | MEaSUREs NASADEM | Elevation | 30.0 | Multi-Day |
SRTM
Principal Investigator: Michael Kobrick, Jet Propulsion Laboratory
The NASA Shuttle Radar Topography Mission (SRTM) is a collaborative effort by NASA, the National Geospatial-Intelligence Agency (NGA), and the participation of German and Italian space agencies. This collaboration aims to generate a near-global digital elevation model (DEM) of Earth using radar interferometry. SRTM was the primary (and virtually only) payload on the STS-99 mission of the space shuttleEndeavour, which launched February 11, 2000, and flew for 11 days.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| SRTMGL1.003 | MEaSUREs SRTM | Elevation | 30.0 | Multi-Day |
| SRTMGL1N.003 | MEaSUREs SRTM | Elevation | 30.0 | Multi-Day |
| SRTMGL3.003 | MEaSUREs SRTM | Elevation | 90.0 | Multi-Day |
| SRTMGL30.021 | MEaSUREs SRTM | Elevation | 1000.0 | Multi-Day |
| SRTMGL3N.003 | MEaSUREs SRTM | Elevation | 90.0 | Multi-Day |
| SRTMGL3S.003 | MEaSUREs SRTM | Elevation | 90.0 | Multi-Day |
| SRTMIMGM.003 | MEaSUREs SRTM | Elevation | 30.0 | Multi-Day |
| SRTMIMGR.003 | MEaSUREs SRTM | Elevation | 30.0 | Multi-Day |
| SRTMSWBD.003 | MEaSUREs SRTM | Elevation, Land Cover | 30.0 | Multi-Day |
VCF
Principal Investigator: Matthew Hansen, University of Maryland
The Vegetation Continuous Fields (VCF) collection provides global vegetation continuous fields from Advanced Very High Resolution Radiometer (AVHRR) long-term data records version 4 (LTDR v4) from 1982 through 2016. Version 1 of this data product includes a time series of VCF data at 5600 m resolution containing information on percent of tree cover, non-tree vegetation, and bare ground.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| VCF5KYR.001 | MEaSUREs VCF | Vegetation Continuous Fields (VCF) | 5600.0 | Yearly |
VIP
Principal Investigator: Kamel Didan, University of Arizona
The Vegetation Index and Phenology (VIP) collection comprises 34 years of a consistent, global record of vegetation indices and landscape phenology. The VIP collections are based on MODIS, AVHRR, and Satellite Pour l'Observation de la Terre (SPOT) data inputs.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| VIP01.004 | MEaSUREs VIP | Phenology, Vegetation Indices (VI) | 5600.0 | Daily |
| VIP07.004 | MEaSUREs VIP | Phenology, Vegetation Indices (VI) | 5600.0 | Weekly |
| VIP15.004 | MEaSUREs VIP | Phenology, Vegetation Indices (VI) | 5600.0 | Multi-Day |
| VIP30.004 | MEaSUREs VIP | Phenology, Vegetation Indices (VI) | 5600.0 | Monthly |
| VIPPHEN_EVI2.004 | MEaSUREs VIP | Phenology, Vegetation Indices (VI) | 5600.0 | Yearly |
| VIPPHEN_NDVI.004 | MEaSUREs VIP | Phenology, Vegetation Indices (VI) | 5600.0 | Yearly |
WELD and GWELD
Principal Investigator: David Roy, Michigan State University; Zhang Hankui, South Dakota State University
The NASA-funded Web-enabled Landsat Data (WELD) project generated Landsat Enhanced Thematic Mapper Plus (ETM+) mosaics of the conterminous United States and Alaska from 2002 to 2012. The WELD products were developed specifically to provide consistent data that could be used to derive land cover, geophysical and biophysical products for regional assessment of surface dynamics, and to study Earth system functionality. The WELD data products were decommissioned on December 2, 2019.
Global WELD (GWELD) is an expansion of WELD data products on a global scale using Landsat 4 and 5 Thematic Mapper (TM) and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) Collection 1 (Versions 3.0 and 3.1) and Collection 2 (Version 3.2) data. These global products provide monthly and annual data for terrestrial non-Antarctic locations for six 3-year epochs that occur every 5 years from 1985 to 2010. GWELD Version 3.0 data for the 2010 epoch is currently available. GWELD Version 3.1 data for the 2000, 1990, and 1985 epochs and Version 3.2 data for the 2005 epoch are also available.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| GWELDMO.003 | MEaSUREs WELD and GWELD | Surface Reflectance, Vegetation Indices (VI) | 30.0 | Monthly |
| GWELDMO.031 | MEaSUREs WELD and GWELD | Surface Reflectance, Vegetation Indices (VI) | 30.0 | Monthly |
| GWELDMO.032 | MEaSUREs WELD and GWELD | Surface Reflectance, Vegetation Indices (VI) | 30.0 | Monthly |
| GWELDYR.003 | MEaSUREs WELD and GWELD | Surface Reflectance, Vegetation Indices (VI) | 30.0 | Yearly |
| GWELDYR.031 | MEaSUREs WELD and GWELD | Surface Reflectance, Vegetation Indices (VI) | 30.0 | Yearly |
| GWELDYR.032 | MEaSUREs WELD and GWELD | Surface Reflectance, Vegetation Indices (VI) | 30.0 | Yearly |
Airborne Hyperspectral Reflectance Mosaic
Principal Investigators: John Gamon, Ran Wang, Hamed Gholizadeh, Jeannine Cavender-Bares, Christopher J. Helzer
Airborne Hyperspectral Reflectance datasets were acquired over various plots and sites: Cedar Creek Ecosystem Science Reserve (CCESR), Minnesota; Tallgrass Prairie Preserve, Oklahoma; Wood River, Nebraska; and Indian Cave State Park, Nebraska. These fine resolution mosaics can be used to better understand the optical diversity-biodiversity relationship and to investigate the spatial sensitivity of the optical diversity-biodiversity relationship at local scales.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| AEHYP1TPPOK.001 | Airborne Hyperspectral | Surface Reflectance | 1 | Other |
| AEHYPCCMN300MM.001 | Airborne Hyperspectral | Surface Reflectance | 0.3 | Other |
| AEHYPICNE1M.001 | Airborne Hyperspectral | Surface Reflectance | 1 | Other |
| AEHYPWRNE1M.001 | Airborne Hyperspectral | Surface Reflectance | 1 | Other |
ASTER GED
Principal Investigator: Glynn Hulley, Jet Propulsion Laboratory (JPL)
Using data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) on NASA's Terra spacecraft, NASA/JPL derived the most detailed global emissivity map of the Earth, termed the ASTER Global Emissivity Database (GED).
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| AG100.003 | ASTER GED | Elevation, Emissivity, Land Surface Temperature (LST), Vegetation Indices (VI) | 100 | Other |
| AG1km.003 | ASTER GED | Elevation, Emissivity, Land Cover, Land Surface Temperature (LST), Vegetation Indices (VI) | 1000 | Other |
| AG5KMMOH.041 | ASTER GED | Emissivity, Vegetation Indices (VI) | 5600 | Monthly |
GHISA
Principal Investigator: Prasad Thenkabail, Itiya P. Aneece, Isabella Mariotto
The Global Hyperspectral Imaging Spectral-library of Agricultural crops (GHISA) is a comprehensive hyperspectral library of the world’s major agricultural crops (e.g., wheat, rice, barley, corn, soybeans, cotton, sugarcane, potatoes, chickpeas, lentils, and pigeon peas). Hyperspectral data for GHISA were acquired from spaceborne, airborne, and ground-based platforms.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| GHISACASIA.001 | GHISA | Cropland | Seasonal | |
| GHISACONUS.001 | GHISA | Cropland | Seasonal |
G-LiHT
Principal Investigator: Bruce Cook
Goddard’s Light Detection and Ranging (LiDAR), Hyperspectral, and Thermal Imager (G-LiHT) was developed to simultaneously derive information about the composition, structure, and function of terrestrial ecosystems using a combination of airborne LiDAR, imaging spectroscopy, and thermal measurements.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| GLCHMK.001 | G-LiHT | Canopy Height, Lidar | 1 | Varies |
| GLCHMT.001 | G-LiHT | Canopy Height, Lidar | 1 | Varies |
| GLDSMT.001 | G-LiHT | Canopy Height, Elevation, Lidar | 1 | Varies |
| GLDTMK.001 | G-LiHT | Elevation, Lidar | 1 | Varies |
| GLDTMT.001 | G-LiHT | Elevation, Lidar | 1 | Varies |
| GLHYANC.001 | G-LiHT | Lidar | 1 | Varies |
| GLHYVI.001 | G-LiHT | Lidar, Vegetation Indices (VI) | 1 | Varies |
| GLLIDARPC.001 | G-LiHT | Lidar | 1 | Varies |
| GLMETRICS.001 | G-LiHT | Canopy Height, Lidar, Surface Reflectance, Vegetation Indices (VI) | 15 | Varies |
| GLORTHO.001 | G-LiHT | Lidar | 0.3 | Varies |
| GLRADS.001 | G-LiHT | Lidar, Surface Radiance | 1 | Varies |
| GLREFL.001 | G-LiHT | Lidar, Surface Reflectance | 1 | Varies |
| GLTRAJECTORY.001 | G-LiHT | Elevation | 1 | Varies |
Headwall Hyperspectral Reflectance Mosaic
Principal Investigator: John Gamon, Ran Wang
An imaging spectrometer on an airborne tram system collected images at 1-millimeter spatial resolution for 33 selected plots at the biodiversity (BioDIV) experiment at the CCESR LTER, Minnesota. The hyperspectral range and fine resolution of the data will assist researchers in studying biodiversity in this area. These findings can be used to guide future airborne studies in developing more effective large-scale biodiversity sampling methods.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| HWHYPCCMN1MM.001 | Headwall | Surface Reflectance | 0.001 | Other |
LGRIP30
Principal Investigator: Prasad Thenkabail
The Global Food Security-support Analysis Data (GFSAD) project provides the highest-known spatial-resolution Landsat-derived Global Rainfed and Irrigated area Product (LGRIP) at 30 meter spatial resolution for the nominal year 2015. The LGRIP product maps agricultural lands, calculates irrigated and rainfed areas, and performs accuracy assessment of the product.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| LGRIP30.001 | LGRIP | Cropland, Land Cover, Water | 30 | Multi-Year |
| LGRIP30_L1_IRRI.002 | LGRIP | Cropland, Land Cover, Water | 30 | Multi-Year |
| LGRIP30_L1_RAIN.002 | LGRIP | Cropland, Land Cover, Water | 30 | Multi-Year |
| LGRIP30_L2_IRRI.002 | LGRIP | Cropland, Land Cover, Water | 30 | Multi-Year |
| LGRIP30_L2_RAIN.002 | LGRIP | Cropland, Land Cover, Water | 30 | Multi-Year |
| LGRIP30_L3.002 | LGRIP | Cropland, Land Cover, Water | 30 | Multi-Year |
LPJ-EOSIM
Principal Investigator: Thomas Colligan
The Lund-Potsdam-Jena Earth Observation SIMulator (LPJ-EOSIM) model replicates biospheric processes to estimate how plants of different functional types obtain resources through photosynthesis and competition. The model estimates global wetland methane (CH4) emissions using simulated wetland extent and characteristics including soil moisture, temperature, and carbon content. The wetland CH4 flux data will be used to support the United States Greenhouse Gas Center (US GHG Center) and its mission to study natural GHG fluxes. A carbon dioxide (CO2) product is planned for the near future, along with the possibility of more data products containing biospheric variables such as gross primary production and net primary production.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| LPJ_EOSIM_L2_DCH4E.001 | LPJ-EOSIM | Greenhouse Gases (GHG), Methane (CH4) | 50000 | Daily |
| LPJ_EOSIM_L2_DCH4E_LL.001 | LPJ-EOSIM | Greenhouse Gases (GHG), Methane (CH4) | 50000 | Daily |
| LPJ_EOSIM_L2_MCH4E.001 | LPJ-EOSIM | Greenhouse Gases (GHG), Methane (CH4) | 50000 | Monthly |
| LPJ_EOSIM_L2_MCH4E_LL.001 | LPJ-EOSIM | Greenhouse Gases (GHG), Methane (CH4) | 50000 | Monthly |
LPJ-PROSAIL
Principal Investigator: Bryce Currey
The LPJ-PROSAIL global simulated imaging spectroscopy products are being developed to provide data analogs for the development of future spaceborne global imaging spectroscopy missions including NASA’s Surface Biology and Geology (SBG). The data products consist of simulated imaging spectroscopy data produced by the LPJ-PROSAIL model. The LPJ-PROSAIL model was developed by coupling LPJ, a dynamic global vegetation model, with PROSAIL, a canopy radiative transfer model. LPJ-PROSAIL will consist of multiple products containing dynamic surface reflectance, dynamic top-of-atmosphere radiance, and vegetation traits. The reflectance and radiance products will have a spectral range of 400 to 2500 nanometers (nm) with a spectral resolution of 10 nm at approximately 50 kilometer spatial resolution. Data will be available for each year from 2000 to present. Data availability within that timeframe will vary by product. Each granule will contain a full year of simulated monthly data. For more information visit theLPJ-PROSAIL website.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| LPJ_L2_SSREF.001 | LPJ-PROSAIL | Spectroscopy, Surface Reflectance | 50000 | Monthly |
| LPJ_L2_SSREF.002 | LPJ-PROSAIL | Spectroscopy, Surface Reflectance | 50000 | Monthly |
MuSLI
Principal Investigator: Mark Friedl
NASA’s Multi-Source Land Imaging (MuSLI) Land Surface Phenology (LSP) (MSLSP) provides a 30 m spatial resolution data product containing phenology timing metrics for North America. These data are useful for a wide range of applications including: ecosystem and agro-ecosystem modeling, monitoring of terrestrial ecosystems and their response to climate change and extreme events, as well as mapping land cover, land use, and land cover change.
| Short Name | Collection | Keyword | Spatial Resolution (m) | Temporal Resolution |
|---|---|---|---|---|
| MSLSP30NA.011 | MuSLI | Phenology, Surface Reflectance, Vegetation Indices (VI) | 30 | Yearly |
FUTURE Community
INCA
Principal Investigator: Josh Gray
NASA’s Indicator of National Climate Assessment (INCA) will provide a 500 meter spatial resolution, yearly data product that spans from January 2001 to December 2016; it will contain global phenology metrics based on Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) data. This data product will provide a remote sensing-based land surface phenology climate indicator (LSP-CI) that supports the National Climate Assessment’s need for national scale, long-term monitoring of climate change impacts on ecosystems.
NASA's LP DAAC processes, archives, and distributes land data products to hundreds of thousands of users in the earth science community. Our land data products are made available and support the ongoing monitoring of Earth’s land dynamics and environmental systems to facilitate interdisciplinary research, education, and decision-making.
Process
Raw data collected from specific satellite sensors, such as ASTER aboard NASA’s Terra satellite, are received and processed into a readable and interpretable format here at the LP DAAC, while other data undergo processing in other facilities around the country before arriving to the LP DAAC to be archived and distributed to the public.
Archive
The LP DAAC continually archives a wide variety of land remote sensing data products collected by sensors onboard satellites, aircraft, and the International Space Station (ISS). The archive currently totals more than 14 petabytes of data.
Distribute
All data products in the archive are distributed free of charge throughNASA Earthdata Search. The LP DAAC supports tools and services, like the Application for Extracting and Exploring Analysis Ready Samples (AppEEARS), which allows users to transform and visualize data before download while offering enhanced subsetting and reprojecting capabilities.
Apply
Visit ourNews andLearn pages to learn about LP DAAC data products in various stories and articles and get access to webinars, tutorials, and data recipes. Interact with the land data science community through theEarthdata Forum. Discover tools available to support a variety of research needs on ourData and Tools page.
History
LP DAAC is located just outside of Sioux Falls, South Dakota, at the USGS Earth Resources Observation and Science (EROS) Center. On August 28, 1990, NASA and USGS established EROS as a Distributed Active Archive Center (DAAC).
Our community of users includes scientists, researchers, federal, state, and local government, educational and commercial professionals, application users, and the general public.
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