N: 54 S: -54 E: 180 W: -180
Description
The ECO2CLD Version 1 data product was decommissioned on May 21, 2025. Users are encouraged to use the ECO_L2_CLOUD Version 2 and ECO_L2G_CLOUD Version 2 data products.
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 globally between 52 degrees N and 52 degrees S latitudes.
The ECO2CLD Version 1 data product provides a cloud mask that can be used to determine cloud cover for the ECO1BRAD, ECO2LSTE, ECO3ETPTJPL, ECO4ESIPTJPL, and ECO4WUE data products. The ECOSTRESS Level 2 cloud product is derived using the five calibrated thermal bands in a multispectral cloud-conservative thresholding approach. The details of the algorithm are provided in the Algorithm Theoretical Basis Document (ATBD). The corresponding ECO1BGEO data product is required to georeference the ECO2CLD data product.
The ECO2CLD Version 1 data product contains a single cloud mask layer. Information on how to interpret the bit fields in the cloud mask is provided in section 3.1 of the User Guide.
Known Issues
- Data acquisition gap: ECOSTRESS was launched on June 29, 2018, and moved to autonomous science operations on August 20, 2018, following a successful in-orbit checkout period. On September 29, 2018, ECOSTRESS experienced an anomaly with its primary mass storage unit (MSU). ECOSTRESS has a primary and secondary MSU (A and B). On December 5, 2018, the instrument was switched to the secondary MSU and science operations resumed. On March 14, 2019, the secondary MSU experienced a similar anomaly temporarily halting science acquisitions. On May 15, 2019, a new data acquisition approach was implemented and science acquisitions resumed. To optimize the new acquisition approach TIR bands 2, 4, and 5 are being downloaded. The data products are as previously, except the bands not downloaded contain fill values (L1 radiance and L2 emissivity). This approach was implemented from May 15, 2019, through April 28, 2023.
- Data acquisition gap: From February 8 to February 16, 2020, an ECOSTRESS instrument issue resulted in a data anomaly that created striping in band 4 (10.5 micron). These data products have been reprocessed and are available for download. No ECOSTRESS data were acquired on February 17, 2020, due to the instrument being in SAFEHOLD. Data acquired following the anomaly have not been affected.
- Data acquisition: ECOSTRESS has now successfully returned to 5-band mode after being in 3-band mode since 2019. This feature was successfully enabled following a Data Processing Unit firmware update (version 4.1) to the payload on April 28, 2023. To better balance contiguous science data scene variables, 3-band collection is currently being interleaved with 5-band acquisitions over the orbital day/night periods.
Product Summary
Citation
Citation is critically important for dataset documentation and discovery. This dataset is openly shared, without restriction, in accordance with the EOSDIS Data Use and Citation Guidance.
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File Naming Convention
The file name begins with the Sensor (ECOSTRESS) followed by the Processing Level (L2), Geophysical Parameter (CLOUD), Orbit Number (36876), Scene Identifier (031), Date and Time of Acquisition designated as YYYYMMDDTHHMMSS (20250106T174738), Build Identifier of product generation software (0601), Product Iteration Number (01), and the Data Format (h5).
Documents
USER'S GUIDE
ALGORITHM THEORETICAL BASIS DOCUMENT (ATBD)
GENERAL DOCUMENTATION
Publications Citing This Dataset
| Title | Year Sort ascending | Author | Topic |
|---|---|---|---|
| Advancing point-to-grid scale ET mapping: comparative assessment of ECOSTRESS and MODIS LST and ET across heterogeneous landscapes | Park, Kijin, Baik, Jongjin, Kim, Kiyoung, Park, Jongmin | Evapotranspiration, Latent Heat Flux, Geolocation, Land Use/Land Cover Classification, Land Surface Temperature, Emissivity, Clouds | |
| Canopy Temperature Reveals Disparities in Urban Tree Benefits | Wilkening, Jean V., Feng, Xue | Land Surface Temperature, Emissivity, Clouds | |
| Spaceborne estimates of canopy temperature and soil moisture predict daily and annual subalpine tree growth | Estey, Eli W., Eitel, Jan U.H., Vierling, Lee A., Peven, Grace L., Cawse-Nicholson, Kerry A., Hook, Simon J., Griffin, Kevin L. | Land Surface Temperature, Emissivity, Geolocation, Clouds, Brightness Temperature, Surface Soil Moisture | |
| Characterization and Validation of ECOSTRESS Sea Surface Temperature Measurements at 70 m Spatial Scale | Wethey, David S., Weidberg, Nicolas, Woodin, Sarah A., Vazquez-Cuervo, Jorge | Land Surface Temperature, Emissivity, Sea Surface Temperature, Sea Surface Temperature, Clouds, Sea Surface Temperature, Infrared Radiance, THERMAL INFRARED, Sea Surface Temperature, Geolocation | |
| Combining GOES-R and ECOSTRESS land surface temperature data to investigate diurnal variations of surface urban heat island | Chang, Yue, Xiao, Jingfeng, Li, Xuxiang, Zhou, Decheng, Wu, Yiping | Land Surface Temperature, Emissivity, Clouds | |
| Multi-sensor approach for high space and time resolution land surface temperature | Desai, Ankur R., Khan, Anam M., Zheng, Ting, Paleri, Sreenath, Butterworth, Brian, Lee, Temple R., Fisher, Joshua B., Hulley, Glynn, Kleynhans, Tania, Gerace, Aaron, Townsend, Philip A., Stoy, Paul, Metzger, Stefan | Clouds | |
| ECOSTRESS estimates gross primary production with fine spatial resolution for different times of day from the International Space Station | Li, Xing, Xiao, Jingfeng, Fisher, Joshua B., Baldocchi, Dennis D. | Land Use/Land Cover Classification, Reflectance, Anisotropy, Land Surface Temperature, Emissivity, Clouds | |
| Evaluation of ecostress thermal data over south florida estuaries | Shi, Jing, Hu, Chuanmin | Land Surface Temperature, Emissivity, Clouds | |
| Exploring diurnal thermal variations in urban local climate zones with ECOSTRESS land surface temperature data | Chang, Yue, Xiao, Jingfeng, Li, Xuxiang, Middel, Ariane, Zhang, Yunwei, Gu, Zhaolin, Wu, Yiping, He, Shan | Land Surface Temperature, Emissivity, Geolocation, Clouds | |
| Global Intercomparison of Hyper-Resolution ECOSTRESS Coastal Sea Surface Temperature Measurements from the Space Station with VIIRS-N20 | Weidberg, Nicolas, Wethey, David S., Woodin, Sarah A. | Land Surface Temperature, Emissivity, Geolocation, Infrared Radiance, THERMAL INFRARED, Clouds, Sea Surface Temperature | |
| Comparison of thermal infrared-derived maps of irrigated and non-irrigated vegetation in urban and non-urban areas of southern California | Coleman, Red Willow, Stavros, Natasha, Hulley, Glynn, Parazoo, Nicholas | Land Surface Temperature, Emissivity, Geolocation, Clouds, Potential Evapotranspiration |
Variables
The table below lists the variables contained within a single granule for this dataset. Variables often contain observed or derived geophysical measurements collected from a variety of sources, including remote sensing instruments on satellite and airborne platforms, field campaigns, in situ measurements, and model outputs. The terms variable, parameter, scientific data set, layer, and band have been used across NASA’s Earth science disciplines; however, variable is the designated nomenclature in NASA’s Common Metadata Repository (CMR). Variable metadata attributes such as Name, Description, Units, Data Type, Fill Value, Valid Range, and Scale Factor allow users to efficiently process and analyze the data. The full range of attributes may not be applicable to all variables. Additional information on variable attributes is typically available in the data, user guide, and/or other product documentation.
For questions on a specific variable, please use the Earthdata Forum.
| Name Sort descending | Description | Units | Data Type | Fill Value | Valid Range | Scale Factor | Offset |
|---|---|---|---|---|---|---|---|
| Cloud Mask | Cloud Mask | Bit Field | uint8 | N/A | 0 to 255 | N/A | N/A |