Atmosphere-Land Exchange Inverse / Disaggregation of the Atmosphere-Land
Exchange Inverse (ALEXI/DisALEXI)
DisALEXI wurde vor Kurzem im Rahmen des OpenET-Frameworks auf Google Earth Engine portiert. Die grundlegende ALEXI/DisALEXI-Modellstruktur wird von Anderson et al. (2012, 2018) beschrieben. Das ALEXI-Modell zur Evapotranspiration (ET) verwendet speziell zeitliche Differenzmessungen der LST (Land Surface Temperature, Landoberflächentemperatur) von geostationären oder polar umlaufenden Plattformen mit mittlerer Auflösung, um regionale ET-Karten zu erstellen. Mit DisALEXI wird die regionale ALEXI-ET mithilfe von Landsat-Daten (30 m; zweiwöchentlich) auf feinere Skalen heruntergebrochen, um einzelne landwirtschaftliche Flächen und andere Landschaftsmerkmale zu erfassen.
Weitere Informationen
Bänder
Pixelgröße 30 Meter
Bänder
Name
Einheiten
Pixelgröße
Beschreibung
et
mm
Meter
DisALEXI ET-Wert
count
Anzahl
Meter
Anzahl der Cloud-Free-Werte
Bildattribute
Bildattribute
Name
Typ
Beschreibung
build_date
STRING
Datum, an dem die Assets erstellt wurden
cloud_cover_max
DOUBLE
Maximaler CLOUD_COVER_LAND-Prozentwert für Landsat-Bilder, die in die Interpolation einbezogen werden
Sammlungen
STRING
Liste der Landsat-Sammlungen für Landsat-Bilder, die in die Interpolation einbezogen werden
core_version
STRING
OpenET-Kernbibliotheksversion
end_date
STRING
Enddatum des Monats
et_reference_band
STRING
Band in „et_reference_source“, das die täglichen Referenz-ET-Daten enthält
et_reference_resample
STRING
Räumlicher Interpolationsmodus zum Resamplen von täglichen Referenzdaten für die ET
et_reference_source
STRING
Sammlungs-ID für die täglichen Referenzdaten für die geschätzte Transpiration
interp_days
DOUBLE
Maximale Anzahl von Tagen vor und nach dem Datum jedes Bildes, die in die Interpolation einbezogen werden sollen
interp_method
STRING
Methode, die zum Interpolieren zwischen Landsat-Modellschätzungen verwendet wird
interp_source_count
DOUBLE
Anzahl der verfügbaren Bilder in der Interpolationsquelle für den Zielmonat
mgrs_tile
STRING
MGRS-Gitterzonen-ID
model_name
STRING
OpenET-Modellname
model_version
STRING
OpenET-Modellversion
scale_factor_count
DOUBLE
Skalierungsfaktor, der auf das Zählband angewendet werden soll
scale_factor_et
DOUBLE
Skalierungsfaktor, der auf das ET-Band angewendet werden soll
Anderson, M., Gao, F., Knipper, K., Hain, C., Dulaney, W., Baldocchi, D .,
Eichelmann, E., Hemes, K., Yang, Y., Medellin-Azuara, J. und Kustas, W.,
2018. Bewertung der Land- und Wassernutzungsänderungen im California Delta auf Feldebene mithilfe von Fernerkundung. Remote Sensing, 10(6), S.889.
doi:10.3390/rs10060889
Anderson, M.C., Norman, J.M., Mecikalski, J.R., Otkin, J.A. und Kustas,
W.P., 2007. Eine klimatologische Studie zu Evapotranspiration und Feuchtigkeitsstress in den kontinentalen Vereinigten Staaten auf der Grundlage von thermischer Fernerkundung: 1. Modellformulierung: Journal of Geophysical Research:
Atmospheres, 112(D10).
doi:10.1029/2006JD007506
Atmosphere-Land Exchange Inverse / Disaggregation of the Atmosphere-Land Exchange Inverse (ALEXI/DisALEXI): DisALEXI wurde vor Kurzem im Rahmen des OpenET-Frameworks in Google Earth Engine portiert. Die grundlegende ALEXI/DisALEXI-Modellstruktur wird von Anderson et al. (2012, 2018) beschrieben. Das ALEXI-Modell zur Evapotranspiration (ET) verwendet speziell zeitliche Differenzen der Landoberfläche…
[null,null,[],[[["\u003cp\u003eThe OpenET DisALEXI dataset provides monthly evapotranspiration (ET) data for the contiguous United States (CONUS) at a 30-meter resolution, derived from Landsat and GRIDMET data.\u003c/p\u003e\n"],["\u003cp\u003eDisALEXI, part of the OpenET framework, uses a model based on land surface temperature changes to estimate ET and is further disaggregated using Landsat for finer-scale detail.\u003c/p\u003e\n"],["\u003cp\u003eData is available from January 2008 to December 2023 and is provided by OpenET, Inc.under a CC-BY-4.0 license.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset includes two bands: 'et' representing the DisALEXI ET value in millimeters and 'count' indicating the number of cloud-free values used in the calculation.\u003c/p\u003e\n"],["\u003cp\u003eUsers can explore and analyze this dataset within Google Earth Engine for research, education, and non-profit purposes.\u003c/p\u003e\n"]]],["The OpenET DisALEXI dataset, available from 2001-01-01 to 2023-12-01, provides monthly evapotranspiration (ET) data at a 30-meter resolution. It uses the ALEXI/DisALEXI model, which combines land surface temperature data with Landsat data to estimate ET, including a band with the 'et' value and a 'count' of cloud-free observations. The data can be accessed via Earth Engine using a provided code snippet and is licenced with a CC-BY-4.0 use license.\n"],null,["# OpenET DisALEXI Monthly Evapotranspiration v2.0\n\nDataset Availability\n: 2001-01-01T00:00:00Z--2024-12-01T00:00:00Z\n\nDataset Provider\n:\n\n\n [OpenET, Inc.](https://openetdata.org/)\n\nCadence\n: 1 Month\n\nTags\n:\n[evapotranspiration](/earth-engine/datasets/tags/evapotranspiration) [gridmet-derived](/earth-engine/datasets/tags/gridmet-derived) [landsat-derived](/earth-engine/datasets/tags/landsat-derived) [monthly](/earth-engine/datasets/tags/monthly) [openet](/earth-engine/datasets/tags/openet) [water](/earth-engine/datasets/tags/water) [water-vapor](/earth-engine/datasets/tags/water-vapor) \n\n#### Description\n\nAtmosphere-Land Exchange Inverse / Disaggregation of the Atmosphere-Land\nExchange Inverse (ALEXI/DisALEXI)\n\nDisALEXI was recently ported to Google Earth Engine as part of the OpenET\nframework and the baseline ALEXI/DisALEXI model structure is described by\nAnderson et al. (2012, 2018). The ALEXI evapotranspiration (ET) model\nspecifically uses time differential land surface temperature (LST)\nmeasurements from geostationary or moderate resolution polar orbiting\nplatforms to generate regional ET maps. DisALEXI then disaggregates the\nregional ALEXI ET to finer scales using Landsat data (30 m; biweekly) to\nresolve individual farm fields and other landscape features.\n[Additional information](https://openetdata.org/methodologies/)\n\n### Bands\n\n\n**Pixel Size**\n\n30 meters\n\n**Bands**\n\n| Name | Units | Pixel Size | Description |\n|---------|-------|------------|-----------------------------|\n| `et` | mm | meters | DisALEXI ET value |\n| `count` | count | meters | Number of cloud free values |\n\n### Image Properties\n\n**Image Properties**\n\n| Name | Type | Description |\n|-----------------------|--------|----------------------------------------------------------------------------------------------|\n| build_date | STRING | Date assets were built |\n| cloud_cover_max | DOUBLE | Maximum CLOUD_COVER_LAND percent value for Landsat images included in interpolation |\n| collections | STRING | List of Landsat collections for Landsat images included in the interpolation |\n| core_version | STRING | OpenET core library version |\n| end_date | STRING | End date of month |\n| et_reference_band | STRING | Band in et_reference_source that contains the daily reference ET data |\n| et_reference_resample | STRING | Spatial interpolation mode to resample daily reference ET data |\n| et_reference_source | STRING | Collection ID for the daily reference ET data |\n| interp_days | DOUBLE | Maximum number of days before and after each image date to include in interpolation |\n| interp_method | STRING | Method used to interpolate between Landsat model estimates |\n| interp_source_count | DOUBLE | Number of available images in the interpolation source image collection for the target month |\n| mgrs_tile | STRING | MGRS grid zone ID |\n| model_name | STRING | OpenET model name |\n| model_version | STRING | OpenET model version |\n| scale_factor_count | DOUBLE | Scaling factor that should be applied to the count band |\n| scale_factor_et | DOUBLE | Scaling factor that should be applied to the et band |\n| start_date | STRING | Start date of month |\n\n### Terms of Use\n\n**Terms of Use**\n\n[CC-BY-4.0](https://spdx.org/licenses/CC-BY-4.0.html)\n\n### Citations\n\nCitations:\n\n- Anderson, M., Gao, F., Knipper, K., Hain, C., Dulaney, W., Baldocchi, D .,\n Eichelmann, E., Hemes, K., Yang, Y., Medellin-Azuara, J. and Kustas, W.,\n 2018. Field-scale assessment of land and water use change over the\n California Delta using remote sensing. Remote Sensing, 10(6), p.889.\n [doi:10.3390/rs10060889](https://doi.org/10.3390/rs10060889)\n- Anderson, M.C., Norman, J.M., Mecikalski, J.R., Otkin, J.A. and Kustas,\n W.P., 2007. A climatological study of evapotranspiration and moisture\n stress across the continental United States based on thermal remote\n sensing: 1. Model formulation. Journal of Geophysical Research:\n Atmospheres, 112(D10).\n [doi:10.1029/2006JD007506](https://doi.org/10.1029/2006JD007506)\n\n### DOIs\n\n- \u003chttps://doi.org/10.3390/rs10060889\u003e\n\n### Explore with Earth Engine\n\n| **Important:** Earth Engine is a platform for petabyte-scale scientific analysis and visualization of geospatial datasets, both for public benefit and for business and government users. Earth Engine is free to use for research, education, and nonprofit use. To get started, please [register for Earth Engine access.](https://console.cloud.google.com/earth-engine)\n\n### Code Editor (JavaScript)\n\n```javascript\nvar dataset = ee.ImageCollection('OpenET/DISALEXI/CONUS/GRIDMET/MONTHLY/v2_0')\n .filterDate('2020-01-01', '2021-01-01');\n\n// Compute the annual evapotranspiration (ET) as the sum of the monthly ET\n// images for the year.\nvar et = dataset.select('et').sum();\n\nvar visualization = {\n min: 0,\n max: 1400,\n palette: [\n '9e6212', 'ac7d1d', 'ba9829', 'c8b434', 'd6cf40', 'bed44b', '9fcb51',\n '80c256', '61b95c', '42b062', '45b677', '49bc8d', '4dc2a2', '51c8b8',\n '55cece', '4db4ba', '459aa7', '3d8094', '356681', '2d4c6e',\n ]\n};\n\nMap.setCenter(-100, 38, 5);\n\nMap.addLayer(et, visualization, 'OpenET DisALEXI Annual ET');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/OpenET/OpenET_DISALEXI_CONUS_GRIDMET_MONTHLY_v2_0) \n[OpenET DisALEXI Monthly Evapotranspiration v2.0](/earth-engine/datasets/catalog/OpenET_DISALEXI_CONUS_GRIDMET_MONTHLY_v2_0) \nAtmosphere-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 ... \nOpenET/DISALEXI/CONUS/GRIDMET/MONTHLY/v2_0, evapotranspiration,gridmet-derived,landsat-derived,monthly,openet,water,water-vapor \n2001-01-01T00:00:00Z/2024-12-01T00:00:00Z \n25 -126 50 -66 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.3390/rs10060889](https://doi.org/https://openetdata.org/)\n- [https://doi.org/10.3390/rs10060889](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/OpenET_DISALEXI_CONUS_GRIDMET_MONTHLY_v2_0)"]]
