- Dataset Availability
- 2013-01-01T00:00:00Z–2023-12-01T00:00:00Z
- Dataset Provider
- OpenET, Inc.
- Earth Engine Snippet
-
ee.ImageCollection("OpenET/DISALEXI/CONUS/GRIDMET/MONTHLY/v2_0")
- Tags
Description
Atmosphere-Land Exchange Inverse / Disaggregation of the Atmosphere-Land Exchange Inverse (ALEXI/DisALEXI)
DisALEXI was recently ported to Google Earth Engine as part of the OpenET framework and the baseline ALEXI/DisALEXI model structure is described by Anderson et al. (2012, 2018). The ALEXI evapotranspiration (ET) model specifically uses time differential land surface temperature (LST) measurements from geostationary or moderate resolution polar orbiting platforms to generate regional ET maps. DisALEXI then disaggregates the regional ALEXI ET to finer scales using Landsat data (30 m; biweekly) to resolve individual farm fields and other landscape features. Additional information
Bands
Resolution
30 meters
Bands
Name | Units | Description |
---|---|---|
et |
mm | DisALEXI ET value |
count |
count | Number of cloud free values |
Image Properties
Image Properties
Name | Type | Description |
---|---|---|
build_date | STRING | Date assets were built |
cloud_cover_max | DOUBLE | Maximum CLOUD_COVER_LAND percent value for Landsat images included in interpolation |
collections | STRING | List of Landsat collections for Landsat images included in the interpolation |
core_version | STRING | OpenET core library version |
end_date | STRING | End date of month |
et_reference_band | STRING | Band in et_reference_source that contains the daily reference ET data |
et_reference_resample | STRING | Spatial interpolation mode to resample daily reference ET data |
et_reference_source | STRING | Collection ID for the daily reference ET data |
interp_days | DOUBLE | Maximum number of days before and after each image date to include in interpolation |
interp_method | STRING | Method used to interpolate between Landsat model estimates |
interp_source_count | DOUBLE | Number of available images in the interpolation source image collection for the target month |
mgrs_tile | STRING | MGRS grid zone ID |
model_name | STRING | OpenET model name |
model_version | STRING | OpenET model version |
scale_factor_count | DOUBLE | Scaling factor that should be applied to the count band |
scale_factor_et | DOUBLE | Scaling factor that should be applied to the et band |
start_date | STRING | Start date of month |
Terms of Use
Terms of Use
Citations
Anderson, M., Gao, F., Knipper, K., Hain, C., Dulaney, W., Baldocchi, D ., Eichelmann, E., Hemes, K., Yang, Y., Medellin-Azuara, J. and Kustas, W., 2018. Field-scale assessment of land and water use change over the California Delta using remote sensing. Remote Sensing, 10(6), p.889. doi:10.3390/rs10060889
Anderson, M.C., Norman, J.M., Mecikalski, J.R., Otkin, J.A. and Kustas, W.P., 2007. A climatological study of evapotranspiration and moisture stress across the continental United States based on thermal remote sensing: 1. Model formulation. Journal of Geophysical Research: Atmospheres, 112(D10). doi:10.1029/2006JD007506
DOIs
Explore with Earth Engine
Code Editor (JavaScript)
var dataset = ee.ImageCollection('OpenET/DISALEXI/CONUS/GRIDMET/MONTHLY/v2_0') .filterDate('2020-01-01', '2021-01-01'); // Compute the annual evapotranspiration (ET) as the sum of the monthly ET // images for the year. var et = dataset.select('et').sum(); var visualization = { min: 0, max: 1400, palette: [ '9e6212', 'ac7d1d', 'ba9829', 'c8b434', 'd6cf40', 'bed44b', '9fcb51', '80c256', '61b95c', '42b062', '45b677', '49bc8d', '4dc2a2', '51c8b8', '55cece', '4db4ba', '459aa7', '3d8094', '356681', '2d4c6e', ] }; Map.setCenter(-100, 38, 5); Map.addLayer(et, visualization, 'OpenET DisALEXI Annual ET');