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Proceedings Paper

An integrated GIS application system for soil moisture data assimilation
Author(s): Di Wang; Runping Shen; Xiaolong Huang; Chunxiang Shi
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Paper Abstract

The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

Paper Details

Date Published: 18 November 2014
PDF: 6 pages
Proc. SPIE 9299, International Symposium on Optoelectronic Technology and Application 2014: Optical Remote Sensing Technology and Applications, 92990J (18 November 2014); doi: 10.1117/12.2071153
Show Author Affiliations
Di Wang, Nanjing Univ. of Science and Technology (China)
Runping Shen, Nanjing Univ. of Science and Technology (China)
Xiaolong Huang, Nanjing Univ. of Science and Technology (China)
Chunxiang Shi, National Meteorological Information Ctr. (China)


Published in SPIE Proceedings Vol. 9299:
International Symposium on Optoelectronic Technology and Application 2014: Optical Remote Sensing Technology and Applications
Anatoli G. Borovoi; Dong Liu, Editor(s)

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