Local Models for Spatial Analysis
Local Models for Spatial Analysis
复制标题
DOI：
10.1201/9780203022825
复制
发表时间：
2006-10
期刊：
影响因子：
--
通讯作者：
C. Lloyd
中科院分区：
文献类型：
--
作者：
C. Lloyd
本书简介：本地模式与方法什么是本地？空间依赖性空间尺度平稳性空间数据模型用于说明目的的数据集注释概述局部适应的局部建模方法空间数据分层或分割移动窗口/核方法局部变化模型参数转换和去趋势空间数据概述网格数据探索单变量空间变化全局单变量统计网格数据局部单变量统计网格数据分析网格移动窗口分析小波分割分析数字高程模型概述空间关系空间自相关：全局测度空间自相关：局部测度全局回归局部回归回归和空间数据空间自回归模型允许模型参数局部变化的多水平建模移动窗口回归（MWR）地理加权回归（GWR）空间加权分类概述空间预测确定性方法点插值全局方法局部方法区域插值一般方法：覆盖局部模型和局部数据限制：点和区域插值概述空间预测2：地质统计学随机函数模型平稳性全球模型探索空间变化克里格样条等价和克里格条件模拟支持的变化问题其他方法局部方法非平稳模型非平稳均值预测的非平稳模型纹理分析中的非平稳变异函数的变异函数摘要点模式点模式视觉检查点模式密度和距离方法点模式统计检验全局方法距离方法其他问题局部方法密度方法对处于危险中的人口进行统计局部K功能点模式和聚类检测空间分析局部模型综述关键问题、软件未来发展摘要参考索引
Introduction Remit of This Book Local Models and Methods What Is Local? Spatial Dependence Spatial Scale Stationarity Spatial Data Models Data Sets Used for Illustrative Purposes A Note on Notation Overview Local Modeling Approaches to Local Adaptation Stratification or Segmentation of Spatial Data Moving Window/Kernel Methods Locally Varying Model Parameters Transforming and Detrending Spatial Data Overview Grid Data Exploring Spatial Variation in Single Variables Global Univariate Statistics Local Univariate Statistics Analysis of Grid Data Moving Windows for Grid Analysis Wavelets Segmentation Analysis of Digital Elevation Models Overview Spatial Relations Spatial Autocorrelation: Global Measures Spatial Autocorrelation: Local Measures Global Regression Local Regression Regression and Spatial Data Spatial Autoregressive Models Multilevel Modeling Allowing for Local Variation in Model Parameters Moving Window Regression (MWR) Geographically Weighted Regression (GWR) Spatially Weighted Classification Overview Spatial Prediction 1: Deterministic Methods Point Interpolation Global Methods Local Methods Areal Interpolation General Approaches: Overlay Local Models and Local Data Limitations: Point and Areal Interpolation Overview Spatial Prediction 2: Geostatistics Random Function Models Stationarity Global Models Exploring Spatial Variation Kriging Equivalence of Splines and Kriging Conditional Simulation The Change of Support Problem Other Approaches Local Approaches: Nonstationary Models Nonstationary Mean Nonstationary Models for Prediction Nonstationary Variogram Variograms in Texture Analysis Summary Point Patterns Point Patterns Visual Examination of Point Patterns Density and Distance Methods Statistical Tests of Point Patterns Global Methods Distance Methods Other Issues Local Methods Density Methods Accounting for the Population at Risk The Local K Function Point Patterns and Detection of Clusters Overview Summary: Local Models for Spatial Analysis Review Key Issues Software Future Developments Summary References Index