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Data Details

Photochemical Reflectance Index (PRI) and Light-use Efficiency (LUE) Dataset in Dinghu Mountain Forest Ecosystem Station (Apr. 2014 - Mar. 2015)


LI Yanmu1WANG Shaoqiang1QIAN Zhaohui1ZHANG Leiming1ZHOU Guoyi2MENG Ze2
1 Institute of Geographic Sciences and Natural Resources Research，Chinese Academy of Sciences，Beijing 100101，China2 South China Botanical Garden，Chinese Academy of Sciences，Guangzhou 510650，China

DOI:10.3974/geodb.2018.04.18.V1

Published:Jul. 2018

Visitors：8819       Data Files Downloaded：52      
Data Downloaded：29.46 MB      Citations：

Key Words：

Dinghu mountain,subtropical forest,photochemical reflectance index,light-use efficiency,Geographical Research

Abstract：

The Dinghu mountain forest ecosystem station is located in Zhaoqing of Guangdong province of China. The special observation for photochemical reflectance index (PRI) and light use efficiency (LUE) was made from April 2014 to March 2015. The synchronous data was acquired from canopy spectra and CO2 flux. The open flux observation system installed in Dinghu mountain flux tower sampled 10 times per second, and stored data and calculated the average flux data for half an hour on line automatically. The automatic multi-angle spectral observation system installed at 38 m of flux tower. The spectral band range of this system is 300-1100 nm, with a spectral resolution of 3.3 nm. The spectroscopic observation data stored every 15 minutes were analyzed for half an hour with the flux data by averaging two data. The analysis paper based on the dataset was published at the journal of Geographical Research, vol. 36, No. 11, 2017.

Foundation Item：

National Natural Science Foundation of China (41571192); Chinese Academy of Sciences (XDA05050702); Ministry of Science and Technology of P. R. China (2016YFA0600202)

Data Citation：

LI Yanmu, WANG Shaoqiang, QIAN Zhaohui, ZHANG Leiming, ZHOU Guoyi, MENG Ze. Photochemical Reflectance Index (PRI) and Light-use Efficiency (LUE) Dataset in Dinghu Mountain Forest Ecosystem Station (Apr. 2014 - Mar. 2015)[J/DB/OL]. Digital Journal of Global Change Data Repository, 2018. https://doi.org/10.3974/geodb.2018.04.18.V1.

Data Product:

ID Data Name Data Size Operation
1 PRI&LUEDinghuMt.xlsx 580.20KB
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