Skip to main content
U.S. flag

An official website of the United States government

Official websites use .gov
A .gov website belongs to an official government organization in the United States.

Secure .gov websites use HTTPS
A lock ( ) or https:// means you’ve safely connected to the .gov website. Share sensitive information only on official, secure websites.

Skip to content
This is a Non-Federal dataset covered by different Terms of Use than Data.gov.

ECOSTRESS Evapotranspiration dis-ALEXI Daily L3 CONUS 70 m V001

Metadata Updated: February 22, 2025

The ECOsystem Spaceborne Thermal Radiometer Experiment on Space Station (ECOSTRESS) mission measures the temperature of plants to better understand how much water plants need and how they respond to stress. ECOSTRESS is attached to the International Space Station (ISS) and collects data over the conterminous United States (CONUS) as well as key biomes and agricultural zones around the world and selected FLUXNET (http://fluxnet.fluxdata.org/about/) validation sites. A map of the acquisition coverage can be found on the ECOSTRESS website (https://ecostress.jpl.nasa.gov/science).

The NASA Jet Propulsion Laboratory (JPL) ECO3ETALEXI Version 1 data product provides estimates of daily evapotranspiration (ET) using the ECOSTRESS Level 2 (L2) land surface temperature and emissivity (LST&E) product, along with ancillary meteorological data and remotely sensed vegetation cover information. The ECO3ETALEXI data product is derived using a physics-based surface energy balance (SEB) algorithm, the Atmosphere Land Exchange Inverse (ALEXI) Disaggregation algorithm (DisALEXI). Described in the Algorithm Theoretical Basis Document (ATBD) (https://lpdaac.usgs.gov/documents/1000/ECO3ETALEXI_ATBD_V1.pdf), DisALEXI is based on spatial disaggregation of regional-scale fluxes from the ALEXI SEB model. There are many approaches for spatially mapping ET; however, SEB methods are favored for remote sensing retrievals based on land-surface temperature. ALEXI was initially developed for managed landscapes and has now been evaluated in comparison with micrometeorological flux tower observations over crop, forest, grassland, wetland, and semiarid desert sites. Applications include crop water use, crop phenology monitoring, and drought early warning or water stress detection. ECO3ETALEXI is available for CONUS at 70-meter (m) pixel resolution.

The ECO3ETALEXI Version 1 data product contains layers of daily ET, ET uncertainty, and associated quality flags. A low-resolution browse is also available showing daily ET as a stretched image with a color ramp in JPEG format.

Access & Use Information

Public: This dataset is intended for public access and use. Non-Federal: This dataset is covered by different Terms of Use than Data.gov. License: No license information was provided.

Downloads & Resources

Dates

Metadata Created Date February 22, 2025
Metadata Updated Date February 22, 2025

Metadata Source

Harvested from nasa test json

Additional Metadata

Resource Type Dataset
Metadata Created Date February 22, 2025
Metadata Updated Date February 22, 2025
Publisher LP DAAC
Maintainer
Identifier C1639530522-LPDAAC_ECS
Data First Published 2018-07-15
Language en-US
Data Last Modified 2025-02-19
Category ECOSTRESS, geospatial
Public Access Level public
Bureau Code 026:00
Metadata Context https://project-open-data.cio.gov/v1.1/schema/catalog.jsonld
Schema Version https://project-open-data.cio.gov/v1.1/schema
Catalog Describedby https://project-open-data.cio.gov/v1.1/schema/catalog.json
Harvest Object Id ba7f85bb-9e96-45f2-9bba-cb8ea13e9057
Harvest Source Id a73e0c30-4684-40ef-908e-d22e9e9e5f86
Harvest Source Title nasa test json
Homepage URL https://doi.org/10.5067/ECOSTRESS/ECO3ETALEXI.001
Metadata Type geospatial
Old Spatial -127.0 23.0 -65.0 52.0
Program Code 026:001
Source Datajson Identifier True
Source Hash b1f4c9c69ef12722088a065a155d7cbd7ba4ceb5bce5e8e7a708006c6ddda050
Source Schema Version 1.1
Spatial
Temporal 2018-07-15T00:00:00Z/2023-03-13T00:00:00Z

Didn't find what you're looking for? Suggest a dataset here.