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A prototype auto-human support system for spatial analysis

Progress in Natural Science:Materials International 2006年第9期16卷 954-966页

作者： LI Lianfa and WANG Jinfeng (state key {2. of Resources & Environmental Information System, Institute of Geographical Sciences & Natural Resources Research, chinese academy of Sciences, beijing 100101, china) [a]state key {2. of Resources & Environmental Information System Institute of Geographical Sciences & Natural Resources Research Chinese Academy Sciences Beijing China

Spatial analysis is a multidisciplinary field that involves multiple influential factors, variation and uncertainty, and modeling of geospatial data is a complex procedure affected by spatial context, mechanism and assumptions. In order to make spatial modeling easier, some scholars have suggested a lot of knowledge from exploratory data analysis (EDA), specification of the model, fitness and diagnosis of the model, to interpretation of the model. Also an amount of software has improved some functionalities of spatial analysis, e. g. EDA by the dynamic link (GeoDa) and robust statistical calculation (R). However, there are few programs for spatial analysis that can automatically deal with unstructured declarative issues and uncertainty in machine modeling using the domain knowledge. Under this context, this paper suggests a prototype support system for spatial analysis that can automatically use experience and knowledge from the experts to deal with complexity and uncertainty in modeling. The knowledge base component, as the major contribution of the system, in support of the expert system shell, codes and stores declarative modeling knowledge, e.g. spatial context, mechanisms and prior knowledge to deal with declarative issues during the modeling procedure. With the open architecture, the system integrates functionalities of other components, e.g. gis’ visualization, DBMS, and robust calculation in an interactive environment. An application case of spatial sampling, design and implementation of spatial modeling with such a system is demonstrated.

关键词： spatial analysis automatic support system modeling of spatial data artificial inference for modeling.

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Characteristics of the Middle-Late Triassic sedimentary facies assemblages in the Songpan-Ruoergai area

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Progress in Natural Science:Materials International 2007年第3期17卷 305-313页

作者： YAN Zhen, YU Liangjun, LI Jiliang, BIAN Qiantao, WANG Zongqi and YANG Yongcheng ( Institute of Geology, chinese academy of Geological Sciences, {2. 100037, china state key laboratory of Lithospheric Evolution, Institute of Geology and Geophysics, chinese academy of Sciences, {2. 10002., china Shaanxi Insititute of Geology Survey, Xianyang 712.00, china) [a]Institute of Geology Chinese Academy of Geological Sciences Beijing China [b]state key {2. of Lithospheric Evolution Institute of Geology and Geophysics Chinese Academy of Sciences Beijing China [c]Shaanxi Insititute of Geology Survey Xianyang China

The Middle-Late Triassic sedimentary rocks in the Songpan-Ruoergai area mainly consist of calcareous siltstone, muddy limestone, lithic arkose, feldspathic litharenite, mudstone, wormkalk, oolithic limestone, and conglomerate. Except for limestone bed increasing eastward longitudinally and vertically, the calcareous component of the sandstones increases obviously. Abundant benthic and plant fossils and their clasts occur within these rocks. The sedimentary structures predominately contain flaser, parallel, tabular, wavy, and herringbone cross beddings. These data coevally imply that the Middle-Late Triassic sediments deposited in the fluvial, lake and tide environments. Additionally, the rocks display graded, parallel, hummocky beddings, and sandy lamination, a feature characteristic of storm deposits.

关键词： Middle-Upper Triassic fluvial-lake environments tide environment tempestite Songpan-Ruoergai

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Object oriented land cover classification using ALS and GeoEye imagery over mining area

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中国有色金属学会会刊：英文版 2011年第S3期21卷 733-737页

作者： YU Hai-yang, CHENG Gang, GE Xiao-san, LU Xiao-ping key laboratory of Mine Spatial Information Technologies of {2. Bureau of surveying and mapping, Henan Polytechnic University, Jiaozuo 454000, china key laboratory of Mine Spatial Information Technologies of {2. Bureau of surveying and mapping Henan Polytechnic University Jiaozuo 454000 China

An object oriented coal mining land cover classification method based on semantically meaningful image segmentation and image combination of GeoEye imagery and airborne laser scanning (ALS) data was presented. First, DEM, DSM and nDSM (normalized Digital Surface Model, nDSM) were extracted from ALS data. The GeoEye imagery and DSM data were combined to create segmented objects based on neighbor regions merge method. Then 10 kinds of objects were extracted. Different kinds of vegetation objects, including crop, grass, shrub and tree, can be extracted by using NDVI and height value of nDSM. Water and coal pile field was extracted by using NDWI and the standard deviation of DSM method. Height differences also can be used to distinguish buildings from road and vacant land, and accurate building contour information can be extracted by using relationship of neighbor objects and morphological method. The test result shows that the total classification accuracy of the presented method is 90.78% and the kappa coefficient is 0.891 4.

关键词： airborne laser scanning GeoEye nDSM object oriented classification mining areas

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Freshening of the intermediate water of the South china Sea between the 1960s and the 1980s

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chinese Journal of Oceanology and Limnology 2012年第6期30卷 1010-1015页

作者：刘长建王东晓陈举杜岩谢强 state key {2. of Tropical Oceanography South China Sea Institute of OceanologyChinese Academy of Sciences South china Sea Marine engineering {2. Center State Oceanic Administration Graduate University of chinese academy of Sciences Sanya Institute of Deep-sea Science and engineering Chinese Academy of Sciences

Variation in intermediate water salinity in the South china Sea (SCS) between the 1960s and 1980s was studied using historical hydrographic data. The results demonstrate that the water was significantly fresher in the 1980s than in the 1960s, indicating that vertical mixing at intermediate water depth was reduced in the 1980s. This was partially because of the change of the SCS meridional overturning circulation (MOC) connecting local intermediate water with deep water. Data assimilation showed a 0.5Sv (1 Sv=10 6m 3/s) reduction in the strength of the MOC, which is about one third of the mean SCS MOC. Because the SCS MOC is linked to the Pacific Ocean, such an interdecadal variation in the intermediate water SCS may reflect anthropogenic climate change in the world ocean.

关键词： decadal variability intermediate water meridional overturning circulation South china Sea (SCS)

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A fusion algorithm for remote sensing images based on nonsubsampled pyramids and bidimensional empirical decomposition

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Science china(Technological Sciences) 2010年第S1期53卷 196-204页

作者： ZHANG XiaoDong 1,WANG WenBo 2.WANG DiFeng 3 & ZHANG Yu 4 1 state key {2. of Information engineering in surveying,mapping and Remote Sensing,Wuhan University,Wuhan 430079,china 2.College of Sciences,Wuhan University of Science and Technology,Wuhan 430065,china 3state key {2. of Satellite Ocean Environment Dynamics,Second Institute of Oceanography,state Oceanic Administration,Hangzhou 310012.china 4 Spatial Information Technology Application Research Institute,Changjiang River Scientific Research Institute,Wuhan 430010,china Wuhan Univ State Key Lab Informat Engn Surveying Mapping & R Wuhan 430079 Peoples R China Wuhan Univ Sci & Technol Coll Sci Wuhan 430065 Peoples R China state Ocean Adm Inst Oceanog 2 State Key Lab Satellite Ocean Environm Dynam Hangzhou 310012 Zhejiang Peoples R China Changjiang River Sci Res Inst Spatial Informat Technol Applicat Res Inst Wuhan 430010 Peoples R China

In order to improve the quality of remote sensing image fusion,a new method combining nonsubsampled Laplacian pyramid (NLP)and bidimensional empirical mode decomposition(BEMD)is ***,the high resolution panchromatic image (PAN)is decomposed using NLP until the approximate component and the low resolution multispectral image(MS)contain features with a similar ***,the approximation component and the MS are decomposed by BEMD,resulting in a number of bidimensional intrinsic mode functions(BIMF)and a residue *** instantaneous frequency is computed in 4 directions of the *** the positive or negative coefficients in the corresponding position,a weighted algorithm is designed for fusing the high frequency details using the instantaneous frequency and the coefficient absolute value of the BIMFs as fusion *** fused image is then obtained through inverse BEMD and *** results have illustrated the advantage of this method over the IHS,DWT andà-Trous wavelet in both spectral and spatial detail qualities.

关键词： bidimensional empirical mode decomposition nonsubsampled pyramid instantaneous frequency remote sensing image fusion

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A new learning statistic for adaptive filter based on predicted residuals

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Progress in Natural Science:Materials International 2006年第8期16卷 833-837页

作者： YANG Yuanxi and GAO Weiguang (Xi'an Research Institute of surveying and mapping, Xi'an710054,{2. Institute of surveying and mapping, University of Information engineering, Zhengzhou 450052.{2.) [a]Xi' an Research Institute of surveying and mapping Xi' an China [b]Institute of surveying mapping University of Information Engineering Zhengzhou China

A key problem for an adaptive filter is to establish a suitable adaptive factor for balancing the contributions of the measurements and the predicted state information from some kinematic models. The reasonable adaptive factor needs a reliable learning statistics to judge the state kinematic model errors. After analyzing the existing two kinds of learning statistics based on the state discrepancy and variance component ratio, a new learning statistic based on predicted residuals is set up, which is different from the exiting learning statistics. The new learning statistic does not need to estimate the kinemetic state parameters before the filtering process, Of course, it does not need necessary measurements to estimate state parameters for all observation epochs. The new learning statistic can be applied together with the learning factor constructed by the state discrepancy. The advantages and shortcomings of the new learning factor are analyzed, and an example is given.

关键词： adaptive factor adaptive filter kinematic model predicted residual.

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Vision navigation algorithm for mine agent based on quaternion

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中国有色金属学会会刊：英文版 2011年第S3期21卷 610-615页

作者： LI Ke-zhao1, 4, LEI Wei-wei1, 2. GUO Zeng-zhang1, 2. WU Li-xin3, ZHANG Qin4 1. School of Survey and Land Information engineering, Henan Polytechnic University, Jiaozuo 454003, china 2. {2. laboratory of Mine Spatial Information Technologies of state Bureau of surveying and mapping, Henan Polytechnic University, Jiaozuo 454003, china 3. College of Resources and Civil engineering, Northeastern University, Shenyang 110819, china 4. College of Geology engineering and Geomatics, Chang’an University, Xi’an 710054, china [a] School of Survey and Land Information engineering Henan Polytechnic University Jiaozuo 454003 China [b] key laboratory of Mine Spatial Information Technologies of {2. Bureau of surveying and mapping Henan Polytechnic University Jiaozuo 454003 China [c] College of Resources and Civil engineering Northeastern University Shenyang 110819 China [d] College of Geology engineering and Geomatics Chang'an University Xi'an 710054 China

Autonomous relative navigation is the key technology in mining or rescuing. On the basis of mine requirement and the theories of machine vision, an autonomous relative navigation algorithm for mine agent based on quaternion was proposed. In rotation transformation, this algorithm was represented by using quaternion. Because the Jacobi matrix of this method is lower than that of Hall algorithm, the calculation efficiency is improved by using this algorithm. The results of these experiments show that the computation burden of this algorithm based on quaternion is about half that of Hall algorithm. This algorithm based on quaternion is improved as a valid way to solve the problem of mine real-time navigation.

关键词： quaternion mine agent vision navigation

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The roles of a decision support system in applying forest ecosystem management in Northeast china

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Science china(Technological Sciences) 2006年第z1期49卷 9-18页

作者： DAI Limin, ZHENG Bofu, Guofan Shao & ZHOU Li state key Lab of Systems Ecology, Research Center for Eco-Environmental Sciences, {2. academy of Sciences, beijing 100085, china Institute of Applied Ecology, {2. academy of Sciences, Shenyang 110016, china Department of Forestry and Natural Resources, Purdue University, West Lafayette, IN 47907, USA Graduate University of {2. academy of Sciences, beijing 100101, china 1. state key Lab of Systems Ecology Research Center for Eco-Environmental Sciences Chinese Academy of Sciences Beijing 100085 China2. Institute of Applied Ecology Chinese Academy of Sciences Shenyang 110016 China3. Department of Forestry and Natural Resources Purdue University West Lafayette IN 47907 USA4. Graduate University of Chinese Academy of Sciences Beijing 100101 China

Forest ecosystems provide a variety of services and forest ecosystem management (FEM) is an effective approach to maximize the services. Because of the complexity of forest ecosystems, the applications of FEM can be facilitated with decision support systems (DSS) that recognize and incorporate ecological and socio-economic variables. With the rapid development of computation and information technologies, DSS have been advanced in many ways. Traditional forest management within a forestry unit in china is planned on a yearly basis. The planning itself remains primarily a verbal concept as there are no quantitative decision-support tools available to translate the concept into forest management actions. For the purposes of FEM at the management level, a forest management DFF, FORESTAR, has been developed under a framework of geographic information system (gis) and forest models. The paper explained the intelligent modeling mechanisms and demonstrated how the applications of FEM can be strengthened with the applications of FORESTAR.

关键词： forest functions, forested landscapes, forest services, forest models, geographic information systems.

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Susceptibility Assessment of Landslides Caused by the Wenchuan Earthquake Using a Logistic Regression Model

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Journal of Mountain Science 2010年第3期7卷 234-245页

作者： SU Fenghuan key laboratory of Mountain Hazards and Land Surface Processes Chinese Academy of Sciences Chengdu China Institute of Mountain Hazards and Environment Chinese Academy of Sciences Chengdu China Graduate University of the chinese academy of Sciences Beijing China

The Wenchuan earthquake on May 12.2.08 caused numerous collapses,landslides,barrier lakes,and debris *** susceptibility mapping is important for evaluation of environmental capacity and also as a guide for post-earthquake *** this paper,a logistic regression model was developed within the framework of gis to map landslide *** County,a heavily affected area,was selected for the *** of landslides was prepared by interpretation of multi-temporal and multi-resolution remote sensing images(ADS40 aerial imagery,SPOT5 imagery and TM imagery,etc.) and field *** Certainly Factor method was used to find the influencial factors,indicating that lithologic groups,distance from major faults,slope angle,profile curvature,and altitude are the dominant factors influencing *** weight of each factor was determined using a binomial logistic regression *** susceptibility mapping was based on spatial overlay analysis and divided into five *** faults have the most significant impact,and landslides will occur most likely in areas near the *** of the area has a high or very high susceptibility,located in the northeast,south and southwest,including 65.3% of all landslides coincident with the *** susceptibility map can reveal the likelihood of future failures,and it will be useful for planners during the rebuilding process and for future zoning issues.

关键词： Landslide susceptibility WenchuanEarthquake gis logistic regression certainty factor

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Information flow and controlling in regularization inversion of quantitative remote sensing

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Science china Earth Sciences 2005年第1期48卷 74-83页

作者： YANG Hua, XU Wangli, ZHAO Hongrui, CHEN Xue & WANG Jindi Research Center for Remote Sensing and gis, School of Geography, beijing Normal University, {2. key laboratory of Remote Sensing Science, beijing key laboratory for Remote Sensing of Environment and Digital Cities, beijing 100875, china Department of Mathematics, beijing Normal University, beijing 100875, china 1. Research Center for Remote Sensing and gis School of Geography Beijing Normal University State Key Laboratory of Remote Sensing Science Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities 100875 Beijing China 2. Department of Mathematics Beijing Normal University 100875 Beijing China

In order to minimize uncertainty of the inversed parameters to the largest extent by making full use of the limited information in remote sensing data, it is necessary to understand what the information flow in quantitative remote sensing model inversion is, thus control the information flow. Aiming at this, the paper takes the linear kernel-driven model inversion as an example. At first, the information flow in different inversion methods is calculated and analyzed, then the effect of information flow controlled by multi-stage inversion strategy is studied, finally, an information matrix based on USM is defined to control information flow in inversion. It shows that using Shannon entropy decrease of the inversed parameters can express information flow more properly. Changing the weight of a priori knowledge in inversion or fixing parameters and partitioning datasets in multi-stage inversion strategy can control information flow. In regularization inversion of remote sensing, information matrix based on USM may be a better tool for quantitatively controlling information flow.

关键词： regularization inversion, information flow, Shannon entropy decrease, information matrix.

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