Identifying local spatial association in flow data

In this paper we develop a spatial association statistic for flow data by generalizing the statistic of Getis-Ord, G _i (and G _i ^*). This local measure of spatial association, G _ij, is associated with each origin-destination pair. We define spatial weight matrices with different metrics in flow space. These spatial weight matrices focus on different aspects of local spatial association. We also define measures which control for generation or attraction nonstationarity. The measures are implemented to examine the spatial association of residuals from two different models. Using the permutation approach, significance bounds are computed for each statistic. In contrast to the G _i statistic, the normal approximation is often appropriate, but the statistics are still correlated. Small sample properties are also briefly discussed. Received: 18 February 1998/Accepted: 29 September 1998     

Preparation of volume table of SAL (Shorea robusta) - an approach using satellite data

Sal (Shorea robusta) is an important forest tree species in north and north-eastern India. Large-scale plantations of this species have been raised there under taungya and coppice system of management. The conventional volume table prepared for high sal forest is referred to infer the volume of production of this species. Earlier workers have used aerial remote sensing data to develop volume tables of this species. In the present study a volume table for sal is developed based on remotely sensed satellite data using a regression technique. A two-step method was developed to estimate mean tree volume from satellite data. In step 1, mean crown diameter — an intermediate variable - was estimated from satellite data. In step 2, the estimated mean crown diameter was used to estimate the mean tree volume. Addition of age of the crop as an independent variable improved the predictive ability of the regression equation.     

知识引导的稀疏时间序列遥感数据拟合

在多云多雨的地区,光学遥感存在着获取无云数据困难的难题,这会导致时间序列应用中可用数据匮乏。因此,本文面向稀疏时间序列遥感数据,根据噪声造成遥感影像上归一化差分植被指数(NDVI)被低估的事实,提出了一种知识引导的拟合方法。首先,在遥感影像预处理的基础上,利用先验知识和时序差分法对噪声进行识别和剔除;然后,采用高斯二阶模型对原始数据进行拟合;最后,根据拟合残差更新权重,进行迭代拟合,重复上述过程直至获得稳定的结果。本文以Landsat 8 OLI作为数据源,对浙江省杭州地区的森林数据进行拟合,结果表明:在稀疏时间序列数据的情况下,本文方法与MODIS数据拟合结果的相关系数达到0.92,关键时点(如NDVI峰值点等)的时间误差在5 d;相比当前主流方法的0.88与8 d具有更高的精度。     

The CNSDTF topological vector model and structure

Geo-Spatial Data Transfer Standard is an important part of "National Spatial Data Infrastructure(NSDI)" ,as well as a necessary means for data sharing. "Chinese National Geo-Spatial Data Transfer Format (CNSDTF)" was approved by National Quality Technology Supervise Bureau in 1999 with the standard serial number of 17798-1999. It is designed to support vector and raster spatial data. This paper describes the vector part of CNSDTF, including design ideas, main characters, conceptual model, definition of spatial object, and file structure.     

Evaluating urban public facilities of Shenzhen by application of open source data

Abstract

This article applies open source data of public facilities through data mining, not only to evaluate the public facilities from an objective dimension, but also to reflect the sensory opinions of the group factually, eventually realizing the evaluation measurement of urban public facilities. The research takes Shenzhen city as an empirical case and chooses typical public facilities to mine data, resolve address and weight to explore the application of public facilities evaluation under dimension reduction of open source data. The empirical study consists of three parts. First, as the objective evaluation, we estimate the density distribution and per capita of public facility through data mining and address resolution. Second, as the subjective evaluation, we carry on the location analysis to high-score public facility through attention and satisfaction data of Internet evaluation. Finally, as mentioned above, we calculate the weight of objective and subjective evaluation of public facility, eventually formatting the comprehensive evaluation of public facilities.     

高精度矢量数据的路面三维自动建模方法

为了解决路面手工三维建模速度慢、工作量大等问题,本文面向规范化处理的高精度矢量数据,对不同路口进行精细化设计,自动生成路面三维模型.首先使用道路高精度三维信息采集软件,在获取的点云数据中半自动化提取准确的道路边线、道路标识线等矢量信息;然后针对不同路口进行精细化线形设计,提出连续四边形重建方法、弯道平滑处理方法、交叉口...     

顾及局部统计特征的均值滤波方法及其应用

针对Caris软件自动滤波结果中仍存在较多异常数据点、手工剔除需要耗费较长时间的问题,提出了一种基于局部统计特征的均值滤波方法。先利用局部统计特征剔除局部异常点,再结合均值滤波方法估计格网点水深值。实验结果表明,方法处理结果与手工编辑结果水深差值中误差仅为0.121 m,而处理时长极大缩短,对工作效率的提升很大。     

基于线要素动态化简的匹配算法比较与评价

矢量线要素数据来源多样,细节层次不一,限制了已有匹配算法正确率的提高,同时也给算法评价带来困难。化简可以减少线要素细节层次,提取其主要形态,据此提出一种基于线要素动态化简的匹配算法评价新方法。对不同匹配算法采用相同数据,在相同化简算法支撑下进行匹配,从而实现对不同匹配算法的评价。首先,阐述动态化简方法提取线要素主要形态的过程;其次,利用动态化简分别辅助4种已有匹配算法,获取每个匹配算法的最优匹配正确率;最后,将4种匹配算法的原始匹配结果与加入动态化简后的匹配结果进行对比,分析化简对匹配结果的影响,并把该影响运用到匹配算法的比较和评价中来。其中,1通过匹配正确率变化、误匹配等分析了匹配算法的数据适用性;2通过化简比例系数K变化时新增匹配数量的统计,评价了匹配算法对线要素局部细节的敏感程度并提出该指标的量化方法;3结合匹配算法采用的匹配相似度指标对其作出评价。     

顾及拓扑与尖角的分类矢量数据分组压缩算法

针对现有拆分重组法对存在复杂内环以及复杂相交岛屿多边形的分类矢量数据的压缩结果中包含裂缝、重叠及大量尖锐夹角的问题,提出了一种顾及拓扑一致性与尖角的分组压缩方法。依据分类矢量数据中多边形与多边形及其内环的相交关系对矢量矢量数据分组,以修正后拆分重组法结合直接分割法和间接分割法对分类矢量数据分组压缩,压缩结果中不存在裂缝与重叠现象,维护了分类矢量数据的拓扑一致性;通过取回尖角点前后被删除的点,解决了压缩结果中尖角过多的问题。以Landsat8遥感影像分类矢量数据实验验证了文章算法,并与直接分割法、间接分割法、拆分重组法进行了对比分析,验证了本文方法的有效性。     

基于MapGIS的地理国情普查研究与应用

随着第一次全国地理国情普查工作的全面开展,出现了众多地理国情信息数据处理软件,数据的采集和制作也遇到了各种各样的问题,我们利用MapGIS平台对软件的内部模块和功能进行了有效的利用,并得到了很好的应用效果。