应用遥感技术开展土地动态监测方法评述与定

基于土地动态监测理论在国内外发展情况,文章具体分析了动态监测的几种常用方法原理,并汇总各种方法的优缺点,在理论分析基础上,给出了基于图斑的变化监测精度定量评价方法.在比较了几种方法的应用特点后,指出在土地利用中遥感动态监测需要注意的问题.     

基于特征的时空数据模型研究及在土地利用变化动态监测中的应用

介绍基于特征的时空数据模型的研究及在土地利用动态监测中的应用.在超图理论基础之上对基于特征的时空数据模型和数据结构的理论进行新探索.同时,以基于特征的时空数据模型为基础,探讨特征选取和时空赋值,设计基于特征的时空数据库,并在土地利用动态监测中建立原形系统,该应用实例证明本研究在理论和方法上的可行性.     

土地遥感动态监测信息管理系统设计与功能实现

土地遥感动态监测管理信息系统(LRSDM-MIS)是土地动态监测的重要组成部分。本文以图像信息系统设计为理论基础,对系统的设计与图像查询方法作了详细的阐述,分析了遥感图像数据库、详查数据库的基本构成及其相互关系,并基于扩展关系数据库使系统功能得以实现。     

eCognition在土地动态监测中的应用

基于eCognition的多尺度影像分割与识别技术,进行了土地变化监测研究。首先选取同一区域不同时相的两幅影像,通过实验确定适宜变化监测的尺度参数、形状参数和紧致度参数,然后进行影像分割,最后进行各类地物信息提取,探测不同时相同一地物的不同形态,进而发现地类图斑变化。实验表明,基于eCognition,可以分析出地类图斑的细致变化,完成土地动态监测。通过对比实测数据,基于eCognition的地类图斑点识别精度合格率在90%以上,不失为一种高精度土地动态监测新方法,同时也为土地变化信息监测提供了一种经济、科学的技术方案。     

利用卫星遥感技术进行土地动态监测的研究

利用卫星遥感技术对土地利用情况进行监测,能够及时、准确地发现土地利用动态变化。介绍了土地动态监测的2种方法,阐述了土地利用动态监测的关键步骤及作业过程中积累的一些经验和技巧。     

基于“一张图”的土地动态监测系统研究

基于国土资源"一张图",探讨土地动态监测系统的架构,采用卫星遥感、低空遥感、车载GPS、移动GIS等作为信息采集手段,设计土地动态监测系统,其中包含移动执法客户端系统和土地动态监察后台管理系统,从而构建空地一体化的土地动态监测平台。     

利用遥感进行土地利用动态监测的实践探讨

基于杭州市土地利用动态遥感监测项目的实施,阐述了如何利用遥感影像发现新增建设用地,并对影像预处理、变化信息提取和制图输出等几个关键环节进行了论述。     

遥感与地理信息系统在土地利用动态监测中的应用

通过国内外研究动态和RS与GIS在土地检测中的实际应用,阐述了遥感与地理信息系统在土地利用动态监测中的应用,论证了遥感与地理信息系统在土地利用动态监测中的应用方法,得出了利用遥感与地理信息系统技术监测土地利用变化可快速发现并能反应研究区域的变化趋势.RS,GIS技术的结合也为有效进行土地利用动态监测和快速决策提供了科学...     

浅谈土地利用动态遥感监测技术

土地利用动态遥感监测技术是指应用遥感技术,监测土地利用及其动态变化的一种方法。土地利用动态遥感监测成果不仅为土地调查评价、土地利用规划修编等提供了现势资料,还可准确掌握建设用地的变化趋势、布局及规模,为国家宏观调控提供基础信息和技术支持。     

基于知识的土地利用动态监测信息管理系统的实现

合理进行土地开发和利用是实现可持续发展的保障，利用卫星遥感与GIS快速、准确、及时的特点进行土地利用现状动脉监测，构建土地利用动态监测信息管理系统，可为各级政府部门的宏观决策提供科学的依据和技术的支持。在GIS中嵌入智能化思想，能增强GIS的辅助决策作用。文章探讨了基于知识的土地利用动态监测信息管理系统的总体框架、系统功能和实现方法。     

Spatial optimization for land acquisition problems: A review of models,solution methods,and GIS support

This article reviews the interdisciplinary research field of spatial optimization for land acquisition problems. We start with a theoretical framework to identify three categories of spatial optimization models: problems with aspatial constraints, location models, and problems with topological constraints. Exact, heuristic, and metaheuristic approaches to solving these problems are critically discussed. Tools that are available in commercial and open‐source GIS packages are reviewed from four aspects. We first survey the off‐the‐shelf support and then the development environments in these packages. A case study of the one‐center problem is used to illustrate the computational performance of different solution methods. Finally the advantages and disadvantages of current GIS data models are discussed. The article concludes with challenges and future directions for solving spatial optimization problems for land acquisition.     

Geographic Object-Based Image Analysis – Towards a new paradigm

The amount of scientific literature on (Geographic) Object-based Image Analysis – GEOBIA has been and still is sharply increasing. These approaches to analysing imagery have antecedents in earlier research on image segmentation and use GIS-like spatial analysis within classification and feature extraction approaches. This article investigates these development and its implications and asks whether or not this is a new paradigm in remote sensing and Geographic Information Science (GIScience). We first discuss several limitations of prevailing per-pixel methods when applied to high resolution images. Then we explore the paradigm concept developed by Kuhn (1962) and discuss whether GEOBIA can be regarded as a paradigm according to this definition. We crystallize core concepts of GEOBIA, including the role of objects, of ontologies and the multiplicity of scales and we discuss how these conceptual developments support important methods in remote sensing such as change detection and accuracy assessment. The ramifications of the different theoretical foundations between the ‘per-pixel paradigm’ and GEOBIA are analysed, as are some of the challenges along this path from pixels, to objects, to geo-intelligence. Based on several paradigm indications as defined by Kuhn and based on an analysis of peer-reviewed scientific literature we conclude that GEOBIA is a new and evolving paradigm.     

陀螺经纬仪定向精度分析

通过应用WILD GAK-1陀螺经纬仪进行逆转点法、中天法及时差法的定向实验,论述了3种定向方法的理论精度,并和实际定向精度进行了比较。     

What about people in pedestrian navigation?

Pedestrian navigation has become an important theoretical and practical research topic in many disciplines such as cartography, geographical information science, global and indoor positioning, spatial behavior, psychology, sociology, and neuroscience. Many research studies view pedestrian navigation using process-oriented and goal-directed approaches. However, this paper revisits people’s needs in pedestrian navigation and classifies their needs as three layers: physical sense layer, physiological safety layer, and mental satisfaction layer according to Maslow’s theory. This paper introduces a people-centric framework for pedestrian navigation theory based on these three layers and discusses theoretical challenges for meeting each layer of people’s needs. These challenging theories may represent promising and valuable research and promote usage of pedestrian navigation systems or devices in the future.     

A study on the effect of the soil texture on passive microwave remote sensing

Consideration of soil moisture in terms of percentage of field capacity of the soils for the minimization of textural dependence of microwave emission of soils has been studied by several investigators using experimental data (air borne, field and laboratory experiments) and also theoretical procedures. Their conslusions seem to be not in agreement with each other, thus giving way for further investigations into the problem. To derive information on the choice of parameter through which the textural dependence of microwave emission can be minimized, three test sites have been selected with different soil textures and emission characteristics of these soils are calculated using theoretical approaches. The results of the analysis indicate that the minimal textural dependence is seen on microwave emission when the soil moisture is expressed in terms of volumetric moisture content (m_v) reduced by the amount of transition moisture (W_t).     

Spatial analysis using clustering methods: Evaluating central point and median approaches

Spatial analysis is an important area of research which continues to make major contributions to the exploratory capabilities of geographical information systems. The use and application of classic clustering methods is being pursued as an exploratory approach for the analysis of spatially referenced data. Numerous potential clustering approaches exist, so research assessing the relative differences of these approaches is important. This paper evaluates the median and central points optimization based clustering approaches for use in the context of exploratory spatial data analysis. Functional and visual comparisons using three spatial applications across a range of cluster values are carried out. The empirical results suggest that these two clustering approaches identify very similar groupings. The significance of this finding is that the development of clustering tools for exploratory analysis may be limited to the median based approach given relative computational and solvability considerations. Received: 28 September 1998/Accepted: 9 August 1999     

提高网络GIS效率的途径及其技术原理

阻碍网络GIS性能的因素分为两大方面：硬件环境和软件环境。聚焦于软件环境,从通用网络GIS的三层体系架构上入手,分别在数据层、逻辑层和层间数据传输上描述了的一些可实施的优化途径及其技术原理,以综合应用来提高网络GIS的效率。     

A comparison of unsupervised segmentation parameter optimization approaches using moderate- and high-resolution imagery

Unsupervised segmentation optimization methods have been proposed to aid in selecting an “optimal” set of scale parameters quickly and objectively for object-based image analysis. The goal of this study was to qualitatively assess three unsupervised approaches using both moderate-resolution Landsat and high-resolution Ikonos imagery from two study sites with different landscape characteristics to demonstrate the continued need for analyst intervention during the segmentation process. The results demonstrate that these methods selected parameters that were optimal for the scene which varied with method, image type, and site complexity. Several takeaways from this exercise are as follows: (1) some methods do not work as intended, (2) single-scale unsupervised optimization procedures cannot be expected to properly segment all the features of interest in the image every time, and (3) many multi-scale approaches require subjectively chosen weights or thresholds or additional testing to determine those values that meet the objective. Visual inspection of segmentation results is still required in order to assess over and under-segmentation as no method can be expected to select the best parameters for land cover classifications every time. These approaches should instead be used to narrow down parameter values in order to save time.     

The Integration of Geographic Visualization with Knowledge Discovery in Databases and Geocomputation

This paper details the research agenda of the International Cartographic Association Commission on Visualization: Working Group on Database-Visualization Links. The paper stresses the need for the closer integration of three largely disparate technologies: geographic visualization, knowledge discovery in databases, and geocomputation. The introduction explains the meaning behind these terms, the ethos behind their practice, and their connections within the broad realm of knowledge construction activities. The state of the art is then described for different approaches to knowledge construction, concentrating where possible on visual and geographically oriented methods. From these sections, a research agenda is synthesized in the form of three sets of research questions addressing: (1) visual approaches to data mining; (2) visual support for knowledge construction and geocomputation; and (3) databases and data models that must be satisfied to make visually-led knowledge construction a reality in the geographic realm. Conclusions relate this agenda to issues of (1) data, (2) geographic knowledge, and (3) the visualization environment and pose significant challenges to the way we currently represent geographic information and knowledge within computational systems.     

Recognizing building groups for generalization: a comparative study

Recognition of building groups is a critical step in building generalization. To find building groups, various approaches have been developed based on the principles of grouping (or the Gestalt laws of grouping), and the effectiveness of these approaches needs to be evaluated. This study presents a comparative analysis of nine typical such approaches, including three approaches that only consider proximity principle and six approaches that consider multiple grouping principles. Real-life dataset at 1:5000, 1:10,000, and 1:50,000 scales provided by National Geomatics Center of China is used to evaluate the performance of these approaches. Buildings at smaller scales are used to construct the benchmarks to test the grouping results at larger scales, and the adjusted Rand index is adopted to indicate the accuracy of the detected groups. Significant tests (Friedman test and Wilcoxon signed-rank test) are also performed to provide both the overall and pairwise comparisons of these approaches. The results show that (1) the average accuracy of most existing approaches is between 0.3 and 0.5, and the performances of these approaches are significantly different; (2) when only proximity is considered, the buffer analysis approach performs significantly better than other approaches; (3) when multiple grouping principles are considered, the local constraint-based approach usually performs better than other approaches; (4) existing approaches that consider similarity and/or continuity seldom improve the performance of building grouping.