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Proceedings Paper

Simulating the spatial representativeness of the meteorological observed data on rugged terrain
Author(s): Lifeng Gong; Xiaozhou Xin; Hailong Zhang; Li Li; Shanshan Yu; Qinhuo Liu
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Paper Abstract

The solar radiation incidence on the horizontal plane is not the true solar radiation (also called surface solar radiation) on the earth surface, it not take the influence of the rugged terrain into account. Topographic correction process is established which necessarily take integrated consideration of the geographic factors and the local topographic factors (i.e. slope, aspect, terrain inter-shielding effect). Based on the high resolution Digital Elevation Model (DEM) data and the horizontal solar radiation as the input data of topographic correction process, using the mountain solar radiation correction model to simulate the topographic correction process and to present the spatial distribution of surface solar radiation in China Ganzi region on June 30, 2010. Because of the influence of the rugged terrain, the spatial distribution of surface solar radiation is accompanied by the strong spatial heterogeneity, and the spatial representativeness of the observed data of meteorological station is limited. By use of the variogram model to calculate the spatial representativeness and to associate the strength of spatial representativeness with the distance. The results indicated that: 1) rugged terrain mainly makes the solar radiation the redistribution effect significantly on sunny/shady slope of local region, and the increase of slope has a subduction effect on radiation. The terrain factor is essential on determining the solar radiation over the complex terrain. 2) The spatial representativeness of Ganzi meteorological station is approximately 350 meters, the strength of spatial representativeness has the negatively correlation with the distance. There is a necessary to consider the spatial representativeness when verifying the retrieved data.

Paper Details

Date Published: 21 October 2014
PDF: 11 pages
Proc. SPIE 9239, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI, 923923 (21 October 2014); doi: 10.1117/12.2067348
Show Author Affiliations
Lifeng Gong, Institute of Remote Sensing and Digital Earth (China)
Univ. of Electronic Science and Technology of China (China)
Xiaozhou Xin, Institute of Remote Sensing and Digital Earth (China)
Hailong Zhang, Institute of Remote Sensing and Digital Earth (China)
Li Li, Institute of Remote Sensing and Digital Earth (China)
Shanshan Yu, Institute of Remote Sensing and Digital Earth (China)
Qinhuo Liu, Institute of Remote Sensing and Digital Earth (China)


Published in SPIE Proceedings Vol. 9239:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVI
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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