A framework of region-based spatial relations for non-overlapping features and its application in object based image analysis

Object based image analysis (OBIA) is an approach increasingly used in classifying high spatial resolution remote sensing images. Object based image classifiers first segment an image into objects (or image segments), and then classify these objects based on their attributes and spatial relations. Numerous algorithms exist for the first step of the OBIA process, i.e. image segmentation. However, less research has been conducted on the object classification part of OBIA, in particular the spatial relations between objects that are commonly used to construct rules for classifying image objects and refining classification results. In this paper, we establish a context where objects are areal (not points or lines) and non-overlapping (we call this “single-valued” space), and propose a framework of binary spatial relations between segmented objects to aid in object classification. In this framework, scale-dependent “line-like objects” and “point-like objects” are identified from areal objects based on their shapes. Generally, disjoint and meet are the only two possible topological relations between two non-overlapping areal objects. However, a number of quasi- topological relations can be defined when the shapes of the objects involved are considered. Some of these relations are fuzzy and thus quantitatively defined. In addition, we define the concepts of line-like objects (e.g. roads) and point-like objects (e.g. wells), and develop the relations between two line-like objects or two point-like objects. For completeness, cardinal direction relations and distance relations are also introduced in the proposed context. Finally, we implement the framework to extract roads and moving vehicles from an aerial photo. The promising results suggest that our methods can be a valuable tool in defining rules for object based image analysis.     

基于语法层的地图综合信息量原则

地图自动综合的一个首要问题是对地图信息进行数量化,信息量正是对地图表达效率数量化的一种重要手段。本文讨论了地图综合在符号语言学上的层次结构,提出在"典型化"约束下,地图综合应遵循的信息量数量变化规律。该规律为地图自动综合结果的评价提供了数学基础,也能用作基于信息量的渐进式自动综合的评价函数。试验证明,该规律符合地图综合实践的结果。     

土地利用基础图件更新技术体系研究与软件系统构建

全面、现势的土地利用基础图件是一个国家摸清其土地资源家底,进行土地资源合理利用、规划和科学管理的基础和前提条件。本文从数据源、处理手段与采用的技术方法对土地利用基础图件更新的技术体系进行了研究,基于图件更新技术流程的三个主要环节对图件更新方法进行了系统分析和分类总结,继而提出了一套集RS/GIS/GPS技术于一体的图件更新技术方法与流程;同时依托具有自主知识产权的遥感数据处理平台CASM Im-ageInfo,将整个作业流程一体化,构建了适合我国具体国情的实用和可操作性强的土地利用基础图件更新软件系统,实现了土地利用基础图件的快速更新。     

An Improved Hilbert Curve for Parallel Spatial Data Partitioning

A novel Hilbert-curve is introduced for parallel spatial data partitioning, with consideration of the huge-amount property of spatial information and the variable-length characteristic of vector data i...     

Java多线程及多点连接技术在WebGIS数据传输中的应用

目前空间数据的传输效率低下已成为制约WebGIS发展的主要瓶颈之一。多线程技术以及多点连接在提高系统吞吐率、有效利用系统资源、改善用户任务之间的通信效率等方面有着显著作用。本文采用地图分层和图面分割的方法以及Java多线程和多点连接技术实现了WebGIS空间数据的高效传输。     

松辽平原区荒漠化形成与发展的地质基础

利用卫星数据,结合实地地质调查、光释光（Optically Stimulated Luminecence, OSL）测年及孢粉数据,从地层、新构造和沉积环境等角度阐述了松辽平原晚更新世晚期湖积环境的形成与变化,提出了松辽平原晚更新世晚期湖积环境或湖积物质是区内荒漠化形成与发展的地质基础。     

利用地面激光扫描数据进行建筑物变化检测

利用地面激光扫描仪具有的数据获取速度快、精度高、实时性强、能全天候工作等优点,在快速获取三维点云的基础上,通过点云自动拼接、Hausdorff距离检测不同时期建筑物的三维模型变化,并改进了检测算法,提高了算法的执行效率。通过拟合平面构建Delaunay三角网求解变化区域的面积来评估灾害对建筑物的破坏程度,从而为灾害应急响应以及保险理赔等提供了可靠的决策依据。     

XML与动态指标管理在土地适宜性评价中的应用

以增强土地适宜性评价系统的可移植性为目的,研究基于XML的动态指标管理技术,并以ArcGIS为开发平台,设计并实现基于GIS的土地适宜性评价系统.系统主要由数据库管理、动态指标管理、适宜性评价与潜力分析、统计分析和人机接口5部分构成,具有数据输入与输出、查询统计、空间分析等功能,能够对各类数据进行动态管理,可依据建立的...     

Monitoring global land surface drought based on a hybrid evapotranspiration model

The latent heat of evapotranspiration (ET) plays an important role in the assessment of drought severity as one sensitive indicator of land drought status. A simple and accurate method of estimating global ET for the monitoring of global land surface droughts from remote sensing data is essential. The objective of this research is to develop a hybrid ET model by introducing empirical coefficients based on a simple linear two-source land ET model, and to then use this model to calculate the Evaporative Drought Index (EDI) based on the actual estimated ET and the potential ET in order to characterize global surface drought conditions. This is done using the Global Energy and Water Cycle Experiment (GEWEX) Surface Radiation Budget (SRB) products, AVHRR-NDVI products from the Global Inventory Modeling and Mapping Studies (GIMMS) group, and National Centers for Environmental Prediction Reanalysis-2 (NCEP-2) datasets. We randomly divided 22 flux towers into two groups and performed a series of cross-validations using ground measurements collected from the corresponding flux towers. The validation results from the second group of flux towers using the data from the first group for calibration show that the daily bias varies from −6.72 W/m² to 12.95 W/m² and the average monthly bias is −1.73 W/m². Similarly, the validation results of the first group of flux towers using data from second group for calibration show that the daily bias varies from −12.91 W/m² to 10.26 W/m² and the average monthly bias is −3.59 W/m². To evaluate the reliability of the hybrid ET model on a global scale, we compared the estimated ET from the GEWEX, AVHRR-GIMMS-NDVI, and NECP-2 datasets with the latent heat flux from the Global Soil Wetness Project-2 (GSWP-2) datasets. We found both of them to be in good agreement, which further supports the validity of our model's global ET estimation. Significantly, the patterns of monthly EDI anomalies have a good spatial and temporal correlation with the Palmer Drought Severity Index (PDSI) anomalies from January 1984 to December 2002, which indicates that the method can be used to accurately monitor long-term global land surface drought.     

基于BJ -1小卫星遥感数据的矿区土地覆盖变化检测

为了评价利用北京一号小卫星(BJ-I)遥感数据监测煤矿区土地利用/地表覆盖变化的效果,针对其数据特点,选择基于图像信息运算和图像信息变换的直接变化检洲法以及分类后比较法,对徐州东矿区2007～2008年土地利用/地表覆盖变化情况进行检测,以对比、评价各种方法在土地利用/地表覆盖变化检测中的应用效果和BJ -1数据的适用...