DisALEXI baru-baru ini di-porting ke Google Earth Engine sebagai bagian dari framework OpenET dan struktur model dasar ALEXI/DisALEXI dijelaskan oleh Anderson et al. (2012, 2018). Model evapotranspirasi (ET) ALEXI
secara khusus menggunakan pengukuran suhu permukaan tanah (LST) diferensial waktu
dari platform orbit kutub beresolusi sedang atau geostasioner
untuk menghasilkan peta ET regional. DisALEXI kemudian menguraikan ET ALEXI regional ke skala yang lebih halus menggunakan data Landsat (30 m; dua mingguan) untuk menyelesaikan petak sawah individu dan fitur lanskap lainnya.
Informasi tambahan
Band
Ukuran Piksel 30 meter
Band
Nama
Unit
Ukuran Piksel
Deskripsi
et
mm
meter
Nilai DisALEXI ET
count
jumlah
meter
Jumlah nilai gratis cloud
Properti Gambar
Properti Gambar
Nama
Jenis
Deskripsi
build_date
STRING
Tanggal aset dibuat
cloud_cover_max
DOUBLE
Nilai persentase CLOUD_COVER_LAND maksimum untuk gambar Landsat yang disertakan dalam interpolasi
koleksi
STRING
Daftar koleksi Landsat untuk gambar Landsat yang disertakan dalam interpolasi
core_version
STRING
Versi library inti OpenET
end_date
STRING
Tanggal akhir bulan
et_reference_band
STRING
Band di et_reference_source yang berisi data ET referensi harian
et_reference_resample
STRING
Mode interpolasi spasial untuk mengambil sampel ulang data ET referensi harian
et_reference_source
STRING
ID pengumpulan data untuk data ET referensi harian
interp_days
DOUBLE
Jumlah maksimum hari sebelum dan sesudah setiap tanggal gambar yang akan disertakan dalam interpolasi
interp_method
STRING
Metode yang digunakan untuk menginterpolasi antara estimasi model Landsat
interp_source_count
DOUBLE
Jumlah gambar yang tersedia dalam koleksi gambar sumber interpolasi untuk bulan target
mgrs_tile
STRING
ID zona petak MGRS
model_name
STRING
Nama model OpenET
model_version
STRING
Versi model OpenET
scale_factor_count
DOUBLE
Faktor penskalaan yang harus diterapkan ke rentang jumlah
scale_factor_et
DOUBLE
Faktor penskalaan yang harus diterapkan ke band et
Anderson, M., Gao, F., Knipper, K., Hain, C., Dulaney, W., Baldocchi, D .,
Eichelmann, E., Hemes, K., Yang, Y., Medellin-Azuara, J. dan Kustas, W.,
2018. Penilaian skala lapangan terhadap perubahan penggunaan lahan dan air di Delta California menggunakan penginderaan jauh. Remote Sensing, 10(6), hlm.889.
doi:10.3390/rs10060889
Anderson, M.C., Norman, J.M., Mecikalski, J.R., Otkin, J.A. dan Kustas,
W.P., 2007. Studi klimatologi tentang evapotranspirasi dan tekanan kelembapan di seluruh benua Amerika Serikat berdasarkan penginderaan jauh termal: 1. Formulasi model. Journal of Geophysical Research:
Atmospheres, 112(D10).
doi:10.1029/2006JD007506
Inversi Pertukaran Atmosfer-Lahan / Disagregasi Inversi Pertukaran Atmosfer-Lahan (ALEXI/DisALEXI) DisALEXI baru-baru ini di-porting ke Google Earth Engine sebagai bagian dari framework OpenET dan struktur model dasar ALEXI/DisALEXI dijelaskan oleh Anderson et al. (2012, 2018). Model evapotranspirasi (ET) ALEXI secara khusus menggunakan permukaan lahan diferensial waktu …
[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)"]]
