Development of a data mining method for land control

Land resources are facing crises of being misused, especially for an intersection area between town and country, and land control has to be enforced. This paper presents a development of data mining method for land control. A vector-match method for the prerequisite of data mining i. e., data cleaning is proposed, which deals with both character and numeric data via vectorizing character-string and matching number. A minimal decision algorithm of rough set is used to discover the knowledge hidden in the data warehouse. In order to monitor land use dynamically and accurately, it is suggested to set up a real-time land control system based on GPS, digital photogrammetry and online data mining. Finally, the means is applied in the intersection area between town and country of Wuhan city, and a set of knowledge about land control is discovered.     

Definitions of natural-language spatial relations: Combining topology and directions

Because SQL for querying data from spatial databases is ineffective, the query based on natural or visual language becomes an attractive research field gradually. However, how to define and represent natural languages related to spatial data are still gigantic problems. Because existing models of direction relations can't describe by use of some common concepts. First of all, detailed direction relations are proposed to describe the directions related to the interior of spatial objects, such as “east part of a region”, “east boundary of a region”, and so on. Secondly, by integrating the detailed directions with exterior direction relations and topological relations, several NLSRs are defined, such as “a road goes across the east part of a lake”, “a river goes along the east boundary of a province”, etc. Finally, based on the NLSRs abovementioned, a natural spatial query language (NSQL) is formed to retrieve data from spatial databases.     

Data model and visualization of 3D city landscape based on integrated databases

Data acquisition and modeling are the two important, difficult and costful aspects in a Cybercity project. 2D-GIS is mature and can manage a lot of spatial data. Thus 3D-GIS should make the best of data and technology of 2D-GIS. Construction of a useful synthetic environment requires integration of multiple types of information like DEM, texture images and 3D representation of objects such as buildings. In this paper, the method for 3D city landscape data model and visualization based on integrated databases is presented. Since, the data volume of raster are very huge, special strategies (for example, pyramid gridded method) must be adopted in order to manage raster data efficiently. Three different methods of data acquisition, the proper data structure and a simple modeling method are presented as well. At last, a pilot project of Shanghai Cybercity is illustrated.     

Accuracy analysis for SST gravity field model in China

Taking China as the region for test the potential of the new satellite gravity technique, satelliteto-satellite tracking for improving the accuracy of regional gravity field model is studied. With WDM94 as reference, the gravity anomaly residuals of three models, the latest two GRACE global gravity field model (EIGEN_GRACE02S, GGM02S) and EGM96, are computed and compared. The causes for the differences among the residuals of the three models are discussed. The comparison between the residuals shows that in the selected region, EIGEN_GRACE02S or GGM02S is better than EGM96 in lower degree part (less than 110 degree). Additionally, through the analysis of the model gravity anomaly residuals, it is found that some systematic errors with periodical properties exist in the higher degree part of EIGEN and GGM models, the results can also be taken as references in the validation of the SST gravity data.     

Space,time, and situational awareness in natural hazards: a case study of Hurricane Sandy with social media data

ABSTRACT

Various methods have been developed to investigate the geospatial information, temporal component, and message content in disaster-related social media data to enrich human-centric information for situational awareness. However, few studies have simultaneously analyzed these three dimensions (i.e. space, time, and content). With an attempt to bring a space–time perspective into situational awareness, this study develops a novel approach to integrate space, time, and content dimensions in social media data and enable a space–time analysis of detailed social responses to a natural disaster. Using Markov transition probability matrix and location quotient, we analyzed the Hurricane Sandy tweets in New York City and explored how people’s conversational topics changed across space and over time. Our approach offers potential to facilitate efficient policy/decision-making and rapid response in mitigations of damages caused by natural disasters.     

Point grid map: a new type of thematic map for statistical data associated with geographic points

ABSTRACT

Social, economic, and environmental statistical data associated with geographic points are currently globally available in large amounts. When conventional thematic maps, such as proportional symbol maps or point diagram maps, are used to represent these data, the maps appear cluttered if the point data volumes are relatively large or cover a relatively dense region. To overcome these limitations, we propose a new type of thematic map for statistical data associated with geographic points: the point grid map. In a point grid map, an input point data set is transformed into a grid in which each point is represented by a square grid cell of equal size while preserving the relative position of each point, which leads to a clear and uncluttered appearance, and the grid cells can be shaded or patterned with symbols or diagrams according to the attributes of the points. We present an algorithm to construct a point grid map and test it with several simulated and real data sets. Furthermore, we present some variants of the point grid map.     

Error analysis of the 3D similarity coordinate transformation

The 3D similarity coordinate transformation with the Gauss–Helmert error model is investigated. The first-order error analysis of an analytical least-squares solution to this problem is developed in detail. While additive errors are assumed in the translation and scale estimates, a 3 × 1 multiplicative error vector is defined to effectively parameterize the rotation matrix estimation error. The propagation of the errors in the coordinate measurements to the errors in the estimated transformation parameters is derived step-by-step, and the formulae for calculating the variance–covariance matrix of the estimated parameters are presented.     

A Target Detection Method for Hyperspectral Imagery Based on Two-Time Detection

To solve the low detection efficiency problem of Constrained Energy Minimization (CEM) method used for hyperspectral remote sensing imagery, this paper firstly presents two improved detection methods: principal component CEM (PCCEM) and matrix taper CEM (MTCEM). Then, based on these two methods, a more optimized Two-Time detection (TTD) method is proposed. Primarily, the targets of interest in the hyperspectral image are detected by using the PCCEM and MTCEM method. Then the autocorrelation matrix of non-target pixels is estimated according to the target detection results. Finally, based on this autocorrelation matrix, a new weight vector is constructed for the second detection. Under the effect of this new weight vector, the output energy of the target can be kept at unity and the output energy of the background is suppressed at the same time. Then, the improvement of target detection result can be realized. Experimental results on a real world hyperspectral data show the efficiency of the proposed TTD method to improve the detection performance.     

3S技术与智能交通

地球空间信息技术是当前世界范围内发展最快的三大重要高新技术之一,随着其不断地发展和完善,其基础理论和技术方法已经日趋成熟,并正在从规划、国土、测绘、军事等专业应用向社会生活的众多行业和领域渗透和拓展,3S技术在交通领域的应用已成为当前国内外研究和应用的热点。着重介绍了地球空间信息技术在道路交通领域的应用背景,阐述了3S技术与道路交通结合的理论支撑和技术方法,进而介绍了其在交通管理、物流管理、智能导航、交通信息服务和交通安全等方面的典型应用,并展望了3S技术在现代交通领域的发展前景。     

CBERS-02B星HR与多光谱影像融合及评价

CBERS-02B星搭载了高分辨率全色相机HR和多光谱传感器CCD,HR影像可以与CCD影像融合,优势互补形成新的影像,既保持HR的高空间分辨率又保持CCD的光谱分辨率,HR影像同样可以与其它传感器影像融合形成新的影像。本文使用6种不同的融合方法融合HR与多光谱CCD以及SPOT5多光谱影像,并对融合结果进行了定性和定量评价,得到了HR与SPOT5多光谱影像融合较好的方法,表明了HR与其它传感器影像融合的潜力,同时也对HR和SPOT5多光谱融合影像及与CCD融合影像进行了初步的对比分析。