Google Earth Engine ——数据全解析专辑（PML_V2: Coupled Evapotranspiration and Gross Primary Product）
Google Earth Engine ——数据全解析专辑（PML_V2: Coupled Evapotranspiration and Gross Primary Product）
Penman-Monteith-Leuning Evapotranspiration V2 (PML_V2) products include evapotranspiration (ET), its three components, and gross primary product (GPP) at 500m and 8-day resolution during 2002-2017 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 al., 2018; Zhang et al., 2019)
- partitioning ET into three components: transpiration from vegetation, direct evaporation from the soil and vaporization of intercepted rainfall from vegetation (Zhang et al., 2016).
The PML_V2 products perform well against observations at 95 flux sites across globe, and are similar to or noticeably better than major state-of-the-art ET and GPP products widely used by water and ecology science communities (Zhang et al., 2019).
Penman-Monteith-Leuning V2 (PML_V2) 产品包括 2002-2017 年期间 500m 和 8 天分辨率的蒸散量 (ET)、其三个分量和初级产品总值 (GPP)，空间范围从 -60°S 到 90 °N。 PML_V2 产品的主要优点是：
通过冠层电导对蒸腾作用和 GPP 的耦合估计（Gan 等人，2018 年；Zhang 等人，2019 年）
将 ET 分为三个部分：植被蒸腾作用、土壤直接蒸发和植被截留降雨的蒸发（Zhang et al., 2016）。
PML_V2 产品在全球 95 个通量站点的观测中表现良好，与水和生态科学界广泛使用的主要最先进的 ET 和 GPP 产品相似或明显更好（Zhang 等，2019） .Dataset Availability
2002-07-04T00:00:00 - 2017-12-27T00:00:00
Dataset Provider
Collection Snippet
ee.ImageCollection("CAS/IGSNRR/PML/V2")
Resolution
500 meters
Bands Table
Name | Description | Min* | Max* | Units |
|---|---|---|---|---|
GPP | Gross primary product | 0 | 39.01 | gC m-2 d-1 |
Ec | Vegetation transpiration | 0 | 15.33 | mm d-1 |
Es | Soil evaporation | 0 | 8.2 | mm d-1 |
Ei | Interception from vegetation canopy | 0 | 12.56 | mm d-1 |
ET_water | Water body, snow and ice evaporation. Penman evapotranspiration is regarded as actual evaporation for them. | 0 | 20.11 | mm d-1 |
数据引用:
Zhang, Y., Kong, D., Gan, R., Chiew, F.H.S., McVicar, T.R., Zhang, Q., and Yang, Y., 2019. Coupled estimation of 500m and 8-day resolution global evapotranspiration and gross primary production in 2002-2017. Remote Sens. Environ. 222, 165-182, https://doi.org/10.1016/j.rse.2018.12.031
Gan, R., Zhang, Y.Q., Shi, H., Yang, Y.T., Eamus, D., Cheng, L., Chiew, F.H.S., Yu, Q., 2018. Use of satellite leaf area index estimating evapotranspiration and gross assimilation for Australian ecosystems. Ecohydrology, https://doi.org/10.1002/eco.1974
Zhang, Y., Peña-Arancibia, J.L., McVicar, T.R., Chiew, F.H.S., Vaze, J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y.Y., Miralles, D.G., Pan, M., 2016. Multi-decadal trends in global terrestrial evapotranspiration and its components. Sci. Rep. 6, 19124. https://doi.org/10.1038/srep19124
代码：
var dataset = ee.ImageCollection("CAS/IGSNRR/PML/V2");
var visualization = {
bands: ['GPP'],
min: 0.0,
max: 9.0,
palette: [
"a50026","d73027","f46d43","fdae61","fee08b","ffffbf",
"d9ef8b","a6d96a","66bd63","1a9850","006837",
]
};
Map.setCenter(0.0, 15.0, 2);
Map.addLayer(dataset, visualization, "PML_V2 GPP");