Gan, R.、Zhang, Y.Q.、Shi, H.、Yang, Y.T.，Eamus, D.，Cheng, L.、Chiew, F.H.S.、Yu, Q.、2018 年。Use of satellite leaf area index estimating
evapotranspiration and gross assimilation for Australian ecosystems.
Ecohydrology，doi:10.1002/eco.1974
[null,null,[],[[["\u003cp\u003eThe PML_V2 dataset provides evapotranspiration (ET), its three components, and gross primary product (GPP) at 500m and 8-day resolution from 2000-2023.\u003c/p\u003e\n"],["\u003cp\u003eIt covers a spatial range from -60°S to 90°N and offers coupled estimates of transpiration and GPP via canopy conductance.\u003c/p\u003e\n"],["\u003cp\u003eThe dataset partitions ET into transpiration, soil evaporation, and interception from vegetation canopy.\u003c/p\u003e\n"],["\u003cp\u003ePML_V2 products have been validated against observations at 95 flux sites globally and show comparable or superior performance to other leading ET and GPP products.\u003c/p\u003e\n"],["\u003cp\u003eThis version (v0.1.8) extends the temporal coverage, uses MODIS Terra LAI, and features recalibrated parameters.\u003c/p\u003e\n"]]],["The PML_V2 dataset provides 8-day resolution evapotranspiration (ET) and gross primary product (GPP) data from 2000 to 2023, covering -60°S to 90°N, at a 500m pixel size. ET is partitioned into vegetation transpiration, soil evaporation, and canopy interception. Key features include coupled transpiration/GPP estimates and updated temporal coverage using MODIS C6.1. Data is accessible via Google Earth Engine using the provided code snippet and licensed under CC-BY 4.0, dataset source is [PML_V2](https://github.com/kongdd/PML).\n"],null,["# PML_V2 0.1.8: Coupled Evapotranspiration and Gross Primary Product (GPP)\n\nDataset Availability\n: 2000-02-26T00:00:00Z--2023-12-27T00:00:00Z\n\nDataset Provider\n:\n\n\n [PML_V2](https://github.com/kongdd/PML)\n\nCadence\n: 8 Days\n\nTags\n:\n[evapotranspiration](/earth-engine/datasets/tags/evapotranspiration) [gpp](/earth-engine/datasets/tags/gpp) [plant-productivity](/earth-engine/datasets/tags/plant-productivity) [water-vapor](/earth-engine/datasets/tags/water-vapor) \n\n#### Description\n\nPenman-Monteith-Leuning Evapotranspiration V2 (PML_V2) products include\nevapotranspiration (ET), its three components, and\ngross primary production (GPP) at 500m and 8-day resolution during 2000-2023\nand with spatial range from -60°S to 90°N. The major advantages of the\nPML_V2 products are:\n\n1. Coupled estimates of transpiration and GPP via canopy conductance (Gan et al., 2018; Zhang et al., 2019)\n2. Partitioning ET into three components: transpiration from vegetation, direct evaporation from the soil, and vaporization of intercepted rainfall from vegetation (Zhang et al., 2016).\n\nThe PML_V2 products perform well against observations\nat 95 flux sites across the globe, and are similar to or noticeably better than\nmajor state-of-the-art ET and GPP products widely used by water and ecology\nresearch communities (Zhang et al., 2019).\n\nKey changes in v0.1.8 compared with the original v0.1.4:\n\n1. Temporal coverage is lengthened to the latest (may update annually) with the MODIS C6.1 data.\n2. MODIS Terra LAI (MOD15A2H) is used rather than the composite LAI (MCD15A3H).\n3. Parameters are recalibrated with the change in LAI, while other forcings remain the same.\n\n### Bands\n\n\n**Pixel Size**\n\n500 meters\n\n**Bands**\n\n| Name | Units | Min | Max | Pixel Size | Description |\n|------------|------------|-----|---------|------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------|\n| `GPP` | gC m-2 d-1 | 0\\* | 39.01\\* | meters | Gross primary production |\n| `Ec` | mm/d | 0\\* | 15.33\\* | meters | Vegetation transpiration |\n| `Es` | mm/d | 0\\* | 8.2\\* | meters | Soil evaporation |\n| `Ei` | mm/d | 0\\* | 12.56\\* | meters | Interception from vegetation canopy |\n| `ET_water` | mm/d | 0\\* | 20.11\\* | meters | Evaporation from water bodies, snow, and ice. Calculated using the Penman equation, which is considered a good estimate of actual evaporation for these surfaces. |\n\n\\* estimated min or max value\n\n### Terms of Use\n\n**Terms of Use**\n\nAcknowledgements\n\nWhenever PML datasets are used in a scientific publication, the given\nreferences should be cited.\n\nLicense\n\nThe dataset is licensed under the\n[CC-BY 4.0 license](https://creativecommons.org/licenses/by/4.0/).\n\n### Citations\n\nCitations:\n\n- Zhang, Y., Kong, D., Gan, R., Chiew, F.H.S., McVicar, T.R., Zhang, Q.,\n and Yang, Y., 2019. Coupled estimation of 500m and 8-day resolution global\n evapotranspiration and gross primary production in 2002-2017.\n Remote Sens. Environ. 222, 165-182,\n [doi:10.1016/j.rse.2018.12.031](https://doi.org/10.1016/j.rse.2018.12.031)\n- Gan, R., Zhang, Y.Q., Shi, H., Yang, Y.T., Eamus, D., Cheng, L.,\n Chiew, F.H.S., Yu, Q., 2018. Use of satellite leaf area index estimating\n evapotranspiration and gross assimilation for Australian ecosystems.\n Ecohydrology, [doi:10.1002/eco.1974](https://doi.org/10.1002/eco.1974)\n- Zhang, Y., Peña-Arancibia, J.L., McVicar, T.R., Chiew, F.H.S., Vaze, J.,\n Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y.Y., Miralles, D.G., Pan,\n M., 2016. Multi-decadal trends in global terrestrial evapotranspiration\n and its components. Sci. Rep. 6, 19124.\n [doi:10.1038/srep19124](https://doi.org/10.1038/srep19124)\n\n### DOIs\n\n- \u003chttps://doi.org/10.1002/eco.1974\u003e\n- \u003chttps://doi.org/10.1038/srep19124\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('CAS/IGSNRR/PML/V2_v018');\n\nvar visualization = {\n bands: ['GPP'],\n min: 0.0,\n max: 9.0,\n palette: [\n 'a50026', 'd73027', 'f46d43', 'fdae61', 'fee08b', 'ffffbf',\n 'd9ef8b', 'a6d96a', '66bd63', '1a9850', '006837',\n ]\n};\n\nMap.setCenter(0.0, 15.0, 2);\n\nMap.addLayer(\n dataset.first(), visualization, 'PML_V2 0.1.8 Gross Primary Product (GPP)');\n```\n[Open in Code Editor](https://code.earthengine.google.com/?scriptPath=Examples:Datasets/CAS/CAS_IGSNRR_PML_V2_v018) \n[PML_V2 0.1.8: Coupled Evapotranspiration and Gross Primary Product (GPP)](/earth-engine/datasets/catalog/CAS_IGSNRR_PML_V2_v018) \nPenman-Monteith-Leuning Evapotranspiration V2 (PML_V2) products include evapotranspiration (ET), its three components, and gross primary production (GPP) at 500m and 8-day resolution during 2000-2023 and with spatial range from -60°S to 90°N. The major advantages of the PML_V2 products are: Coupled estimates of transpiration and GPP via canopy conductance (Gan et ... \nCAS/IGSNRR/PML/V2_v018, evapotranspiration,gpp,plant-productivity,water-vapor \n2000-02-26T00:00:00Z/2023-12-27T00:00:00Z \n-60 -180 90 180 \nGoogle Earth Engine \nhttps://developers.google.com/earth-engine/datasets\n\n- [https://doi.org/10.1038/srep19124](https://doi.org/https://github.com/kongdd/PML)\n- [https://doi.org/10.1038/srep19124](https://doi.org/https://developers.google.com/earth-engine/datasets/catalog/CAS_IGSNRR_PML_V2_v018)"]]
