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Data Details

1 km/daily Evapotranspiration Product over China and the Association of Southeast Asian Nations for 2013

JIA Li1HU Guangcheng1ZhENG Chaolei1ZHOU Jie1WANG Kun1LI Zhansheng1LIU Qinhuo1
1 State Key Laboratory of Remote Sensing Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing 100101 China


Published:Jun. 2015

Visitors:31382       Data Files Downloaded:10461      
Data Downloaded:3044180.54 MB      Citations:

Key Words:



Terrestrial actual evapotranspiration (ET), including evaporation from soil and water surfaces, evaporation of rainfall interception, transpiration of vegetation canopy and sublimation of snow and glaciers, is an important component of the terrestrial water cycle in China and the Association of Southeast Asian Nations (ASEAN). In addition, ET is a crucial component of the land surface energy balance, and links the hydrological, energy, and carbon cycles. Considering the diverse landscapes and multi-climatic features in China and the ASEAN, a hybrid remotely sensed ET estimation model named ETMonitor was developed to estimate the daily actual evapotranspiration of China and the ASEAN for 2013 at a spatial resolution of 1 km (MuSQ-ET-1km-2013). The ETMonitor model uses a variety of biophysical parameters derived from microwave and optical remote sensing observations to estimate the daily ET for all sky conditions. The China–ASEAN ET product is produced and distributed in 40 adjacent non-overlapping Sinusoidal tiles that are approximately 10��10� (at the equator). The data type is 16-bit signed integer, the scale factor is 0.001, and the unit is mm/day.

Foundation Item:

Data Citation:

JIA Li, HU Guangcheng, ZhENG Chaolei, ZHOU Jie, WANG Kun, LI Zhansheng, LIU Qinhuo. 1 km/daily Evapotranspiration Product over China and the Association of Southeast Asian Nations for 2013[J/DB/OL]. Digital Journal of Global Change Data Repository, 2015.

Jia, L., Hu, G. C., Zheng, C. L., et al. 1 km/daily evapotranspiration data product over China-ASEAN (2013) [J]. Journal of Global Change Data & Discovery, 2017, 1(3): 282-289. DOI: 10.3974/geodp.2017.03.05.

Data Product:

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