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	1. A method of quantitative analysis based on deviation coefficient and sliding time window
	ZHANG Zhanyang,YANG Guohua,SUN Qikai,ZHANG Junqing,HE Yadong
	Surveying and Mapping Technology 27 December 2019
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (0 B)

	Abstract:In order to scientifically and accurately describing the shape of deviation distribution curve of the short-level segment data of seismostation, this paper used deviation coefficient and sliding time window to analyze and summarize trends of deviation distribution curves of 2-3(k) segment of Chaoyang seismostation quantitatively before and after Chaoyang M4.6 and M4.3 earthquakes on May 22, 2016: general data anomalies caused by crustal deformation reveal the deviation coefficients get larger and the shapes of deviation distribution curves of the segment deviate from normal distribution before the earthquake, and the deviation coefficients get smaller and the shapes of deviation distribution curves of the segment restore to normal distribution after the earthquake. Then preliminary analysis of earthquake risk near the seismostation was made based on recent data. As a result, the figures prove that this quantitative analysis method has reference valuable for data anomalies recognition before earthquake to a certain extent, which also provides a new way of research for earthquake monitoring and prediction analyzing.
	TO cite this article:ZHANG Zhanyang,YANG Guohua,SUN Qikai, et al. A method of quantitative analysis based on deviation coefficient and sliding time window[J].


	2. Secure service model for remotely sensed data in cloud computing
	Xu Zhengquan,Xiong Lizhi
	Surveying and Mapping Technology 16 May 2016
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (0 B)

	Abstract:Remotely sensed data sharing services are attracting more and more attention. Advanced cloud computing technologies provide huge storage and efficient support for remotely sensed big data services. However, the security of stored remotely sensed data and usage security in the cloud computing environment have become urgent issues. To address these problems we propose a secure model for remote sensing images (RSIs) in the cloud computing environment. The proposed model not only ensures RSI security without relying on the trustworthiness of cloud servers, but also protects RSI copyrights. Theoretical analysis confirms the correctness of the proposed encryption model and justifies the security of the proposed scheme.
	TO cite this article:Xu Zhengquan,Xiong Lizhi. Secure service model for remotely sensed data in cloud computing[OL].[16 May 2016] http://en.paper.edu.cn/en_releasepaper/content/4691102


	3. Noise Analysis of GPS Coordiante Time Series
	LI Lihua
	Surveying and Mapping Technology 10 November 2015
	Show/Hide Abstract \| Cite this paper︱Full-text: PDF (0 B)

	Abstract:The noise property not only affects the accuracy of the parameter estimation, but also reflects the various driving factors of the environment. Therefore, the noise model is the basis of designing the optimal parameter estimation, and it is also the premise of various geometric, physical, and other parameters based on the observation data. Noise analysis is very important in the data processing. The noise property of the GPS coordinate time series has been explored in detail in this paper. Because of the electronic GPS receiver collecting data with high sampling rate, colored noise arise in the GPS coordinate time series. The methods of determining the stochastic model of GPS coordinate noise are discussed in detail. The results show that the GPS real-time measurement deviations have a high autocorrelation, which should be considered in the GPS high-precision positioning.
	TO cite this article:LI Lihua. Noise Analysis of GPS Coordiante Time Series[OL].[10 November 2015] http://en.paper.edu.cn/en_releasepaper/content/4661034


	4. An integrated GIS application system for soil moisture data assimilation
	WANG Di,SHEN Runping
	Surveying and Mapping Technology 16 July 2014
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	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.
	TO cite this article:WANG Di,SHEN Runping. An integrated GIS application system for soil moisture data assimilation[OL].[16 July 2014] http://en.paper.edu.cn/en_releasepape

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