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Data Details

Meteorological Observation Dataset from HL_RS_TS


Bai Junhua1,2Xiao Qing1Liu Qinhuo1Xu Ziwei2LIU Shaomin2
1 State Key Laboratory of Remote Sensing Science，Aerospace Information Research Institute，Chinese Academy of Sciences，Beijing 100101，China2 Beijing Normal University，Beijing 100088，China

DOI:10.3974/geodb.2020.09.12.V1

Published:Dec. 2020

Visitors：5948       Data Files Downloaded：75      
Data Downloaded：8186.50 MB      Citations：

Key Words：

Weather-observation,Radiation,Meteorology,Soil,Remote Sensing Technology and Application

Abstract：

Huailai Remote Sensing Test Site (HL_RS_TS), located on the border of Beijing city and Zhangjiakou, Hebei Province at 115�47ʹ32.4ʹʹ E, 40�21ʹ26.8ʹʹ N. The meteorological observation dataset from HL_RS_TS is the data collection from January 1 to Novembers 5, 2014, and January 1, 2015, to December 31, The dataset consists of the following data: (1) wind speed, atmospheric temperature, and humidity（3 m, 5 m, 10 m, 15 m, 20 m, 30 m, 40 m above ground），wind direction（10 m above ground）、rainfall（3m above ground）；（2）Soil temperature, soil humidity（2 cm、4 cm、10 cm、20 cm、40 cm、80 cm、120 cm 、160cm underground）soil heat flow data（6 cm underground）；（3）four-component radiation data（4 m above ground）、photosynthetically active radiation data（4m above ground）, surface radiation temperature (SST) data（3.5 m, 8 m above ground）. The dataset is archived in .xlsx data format and composed of 6 data files with data size of 110 MB (compressed to one single file with 109 MB).

Foundation Item：

Chinese Academy of Sciences (2018); State key laboratory of Remote Sensing Science and Chinese Academy of Sciences (2014-2018）

Data Citation：

Bai Junhua, Xiao Qing, Liu Qinhuo, Xu Ziwei, LIU Shaomin. Meteorological Observation Dataset from HL_RS_TS[J/DB/OL]. Digital Journal of Global Change Data Repository, 2020. https://doi.org/10.3974/geodb.2020.09.12.V1.

References：

Bai Junhua, Xiao Qing, Liu Qinghuo, Wen Jianguang. The Research of Constructing the Target Ranges to Validate Remote Sensing Product. Remote Sensing Technology and Application, 2015, 30(3):573-578.
     

Data Product:

ID Data Name Data Size Operation
1 HL_RS_TS_2014-2018.rar 111773.08KB
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