坡位渐变信息的模糊推理

坡位的空间变化通常是渐变的,定量的坡位空间渐变信息对于精细尺度上的坡面土壤侵蚀、预测性土壤制图等应用具有重要意义。现有基于栅格DEM的坡位模糊识别方法,或是仅在属性域内模糊聚类,忽略了空间信息;或是需要繁琐的规则进行模糊分类,实用性受限。本文建立了一种基于相似度的模糊推理方法,根据各类坡位在空间上的典型位置,计算其他位置与典型位置间的相似度,从而对坡位空间渐变信息进行系统、定量的描述。应用表明本方法能够合理地描述山脊、坡肩、背坡、坡脚、沟谷等重要坡位类型的渐变信息,所获得的坡位渐变信息也能够合理地解释土壤样点的A层土壤含砂量随坡位渐变的变化趋势。     

模糊坡位信息在精细土壤属性空间推测中的应用

坡位的空间渐变特征影响着小流域及坡面尺度上的土壤、水文、地貌等现象和过程,因此对精细尺度下的地理建模(如土壤空间信息推理)有重要作用。虽然目前已有多种模糊坡位信息定量提取方法,但所得到的模糊坡位信息还缺乏实际应用。本文以精细尺度下的土壤属性空间分布推测为例,对此展开探索。应用模型假设:(1)在小流域内,地形因素主导着土壤属性空间分布的变化;(2)典型坡位上对应分布着典型的土壤属性值,土壤属性与坡位之间存在协同变化关系。据此建立以模糊坡位信息对各类典型坡位上土壤样点属性值的加权平均模型,推测土壤属性的空间分布。模型应用于黑龙江省嫩江流域一个地形平缓的小区(面积约60 km²),通过一个以坡位典型位置作为原型的模糊坡位定量方法提取5类坡位(山脊、坡肩、背坡、坡脚、沟谷)的空间渐变信息,对土壤表层有机质含量的空间分布进行推测。推测结果通过研究区70个土壤采样点进行评价,以推测结果与评价样点集之间的相关系数、平均绝对误差、均方根误差作为定量评价指标,与使用常用地形属性的多元线性回归模型推测结果进行对比。评价结果表明,仅使用极少建模点的加权平均模型的推测结果优于多元线性回归模型的推测结果。     

坡向和微地形对大型土壤动物空间分布格局的影响

尽管在景观和区域尺度上对土壤动物空间分布格局的研究已较多,但在小尺度上对局部微生境条件如何影响土壤动物多样性及其空间分布格局的研究还很少。以典型温带次生林为研究对象,采用样方法系统调查了林地阴坡和阳坡4个不同地形部位大型土壤动物群落的密度,并测定了不同地形部位的生境条件。采用三因子方差分析和对应分析等方法定量研究了坡向和地形部位对大型土壤动物群落密度的空间分布格局的影响。主要表现在：①在采集到的160个土壤样品中共检测到动物个体4 148个,分别隶属于26个不同的土壤动物类群;②坡向和地形部位对土壤动物的空间分布格局有显著的影响,但不同土壤动物类群对坡向和地形部位的响应模式存在一定的差异,这种差异的形成可能与不同土壤动物类群的生活习性和生物学特征密切相关。其结论是：在小尺度上,林地的坡向和微地形条件主要通过影响局部小生境的生物和非生物因子组合特征而对土壤动物的空间分布格局产生重要影响。     

地形信息对确定DEM适宜分辨率的影响

分辨率会直接影响基于栅格数字高程模型（DEM）的数字地形分析结果,因此在实际应用中,需要选择适宜的DEM分辨率。目前采取的基本方法,基于某种地形信息定量刻画尺度效应曲线,从而确定DEM适宜分辨率,但对于采用不同地形信息时所产生的影响尚缺乏研究。本文针对该方法中通常采用的坡度、剖面曲率、水平曲率等3 种地形信息,每种地形信息提取时,分别使用两种不同的常用算法,在3 个不同地形特征的研究区中,逐一计算其在不同分辨率下的局部方差均值,以刻画尺度效应曲线,确定相应的DEM适宜分辨率,并进行对比分析。结果表明：① 采用剖面曲率或水平曲率所得适宜分辨率结果基本相同,但采用坡度所得出的适宜分辨率结果则有明显差别,后者所得的适宜分辨率更粗;② 采用不同地形信息时,越是在平缓地形为主的研究区,所得的适宜分辨率结果越相近,在复合地形特征的研究区所得到的适宜分辨率区间均明显较宽;③ 地形属性计算时所用的算法对适宜分辨率结果的影响不明显。     

基于DEM的地形单元多样性指数及其算法

在阐述地形信息表达研究进展的基础上,提出基于DEM地形单元多样性指数的概念和算法。地形单元多样性指数综合了高程、坡度、坡位、坡向、汇流量和水域信息等要素。其算法集成地形位置指数和地形湿度指数算法,采用图层叠加分析,设定分类、分级指标,进行重分类组合,划分地形单元类型,利用窗口分析法计算地形单元多样性指数。以四川省为试验区,利用精度为100 m的DEM数据和水域分布数据进行模拟计算,地形单元划分为13种典型类型,统计窗口半径设为900 m,计算出的多样性指数值小于0.5的区域仅占总面积的11%,大于0.75的区域达57%,符合实验区地形特征,并对算法进行了可行性分析和验证。结果表明,该算法提取的地形单元多样性指数可以有效反映地表形态的多样性特征及其变化。该研究结果为进一步探讨基于DEM地表形态信息的概念体系,以及从微观到宏观的地形信息空间分析研究创造了条件。     

地形湿度指数算法误差的定量评价

地形湿度指数(TWI)能够定量指示地形对土壤湿度空间分布的控制,是一种应用广泛的地形属性.目前基于栅格DEM的TWI计算方法结果各异,因此有必要对'TWI算法进行定量评价.对TWI算法通常是应用实际DEM数据进行评价.但实际DEM中存在的数据源误差会干扰对算法误差的评价.针对该问题,本文介绍了一种用不含数据源误差的人造...     

Soil-landscape modelling and spatial prediction of soil attributes

Abstract

Explicit and quantitative models for the spatial prediction of soil and landscape attributes are required for environmental modelling and management. In this study, advances in the spatial representation of hydrological and geomorphological processes using terrain analysis techniques are integrated with the development of a field sampling and soil-landscape model building strategy. Statistical models are developed using relationships between terrain attributes (plan curvature, compound topographic index, upslope mean plan curvature) and soil attributes (A horizon depth, Solum depth, E horizon presence/absence) in an area with uniform geology and geomorphic history. These techniques seem to provide appropriate methodologies for spatial prediction and understanding soil landscape processes.     

DEM resolution dependencies of terrain attributes across a landscape

This paper documents resolution dependencies in terrain analysis and describes how they vary across landform location. Six terrain attributes were evaluated as a function of DEM resolution—slope, plan curvature, profile curvature, north–south slope orientation, east–west slope orientation, and topographic wetness index. The research highlights the effect of varying spatial resolution through a spatial sampling/resampling scheme while maintaining sets of indexed sample points at various resolutions. Tested sample points therefore coincide exactly between two directly compared resolutions in terms of their location and elevation value. An unsupervised landform classification procedure based on statistical clustering algorithms was employed to define landform classes in a reproducible manner. Correlation and regression analyses identified sensitive and consistent responses for each attribute as resolution was changed, although the tested terrain attributes responded in characteristically different ways. These responses displayed distinguishable patterns among various landform classes, a conclusion that was further verified by a series of two‐sample, two‐tailed t‐tests.     

地形指数的物理意义分析

地形指数模型 ( TOPMODEL)用地形指数在流域中的空间格局来确定流域饱和缺水量的空间分布和产流区的空间位置与范围 ,物理意义明确。本文介绍了地形指数的物理基础及其与土壤水分的关系。分析了地形指数空间变化与汇流面积 a及局地坡度空间变化的关系 ,a范围内有效汇流面积的变化 ,提出了一种确定 a上限值的方法。     

Direct induction of compact rule-based classifiers for resource mapping

Abstract

Rule-based classifiers are used regularly with geographical information systems to map categorical attributes on the basis of a set of numeric or unordered categorical attributes. Although a variety of methods exist for inducing rule-based classifiers from training data, these tend to produce large numbers of rules when the data has noise. This paper describes a method for inducing compact rule-sets whose classification accuracy can, at least in some domains, compare favourably with that achieved by larger less succinct rule-sets produced by alternative methods. One rule is induced for each output class. The condition list for this rule represents a box in n-dimensional attribute space, formed by intersecting conditions which exclude other classes. Despite this simplicity, the classifier performed well in the test application prediction of soil classes in the Port Hills, New Zealand, on the basis of regolith type and topographic attributes obtained from a digital terrain model.     

黄土丘陵沟壑区县域土壤有机质空间分布特征及预测

分析、预测土壤属性空间变异及其动态是区域土地质量评价和可持续土地利用的一个重要组成部分。在陕西省横山县采集了254个耕层(0~20cm)土样,利用数字地形与遥感影像分析技术,提取了相关地形与遥感指数,分析不同土地利用类型、不同地形条件下土壤有机质空间变异及分布特征,并利用相关因子进行回归预测分析。结果表明,县域土壤有机质平均含量很低,变异性较大。不同土地利用类型土壤有机质差异显著,其中以水稻田有机质含量最高,而林地和灌木林地相对较低。不同土地利用类型土壤有机质含量次序为:水稻田>川地>梯田>坝地>荒草地>坡耕地>林地>灌木林地。不同坡度分析表明,“0~3°”这一坡度等级有机质含量显著高于其它坡度等级;不同坡向有机质含量差异不显著,但不同坡向有机质含量存在一个明显的趋势,阴坡有机质含量整体上要比阳坡高。相关分析表明土壤有机质与高程h呈现负相关关系,与坡向的余弦值COSα正相关,与复合地形指数CTI正相关;土壤有机质和修正后的土壤调节植被指数(MSAVI)以及湿度指数(WI)正相关。利用相关环境变量及遥感指数进行多元线性逐步回归分析,预测结果不甚理想,存在一个平滑效应,对于残差解释相对较低,须进一步研究以更好的解释残差。     

基于少量典型样点土壤属性空间分布推测模型中的土壤属性参数敏感性分析

针对基于少量典型样点土壤属性空间分布推测模型中的土壤属性参数敏感性问题,以坡位渐变信息结合典型土壤样点的加权平均模型为例,利用东北地形平缓小流域的土壤表层有机质含量样点集,使用阶乘设计、箱线图分析、扰动分析法和本文新设计的MR指数评价该模型的参数敏感性。结果表明,该模型中土壤属性参数敏感性较大,其大小与典型样点空间分布有关。敏感性主要由应用该模型时采用的坡位分类体系的不确定性引起。该文的分析方法可用于对基于少量典型样点的土壤属性空间分布推测模型进行参数敏感性综合分析。     

Loess terrain segmentation from digital elevation models based on the region growth method

Regional automatic segmentation – automatic terrain segmentation according to terrain features – is significant for modern geographical analysis. We propose a new approach of terrain region segmentation based on the region growth method. This method features actual runoff nodes as seed points. The corresponding growth threshold is defined based on statistical analysis of quantitative indexes of topographic features. Terrain segmentation of some regions is completed using the growth threshold. The corresponding edge boundaries of different terrain regions are extracted by image processing. Thus, the automatic segmentation of the terrain region is realized by the edge boundary. The application of the method to a typical Chinese loess landform area and automatic segmentation of three types of terrain regions – gully interfluve land, gully slope land, and gully groove land – are achieved by analyzing characteristics of the curvature structure of surface profiles. Segmentation results, compared with results of visual interpretation from a high-precision digital orthophoto map, show an average accuracy of segmentation of 93.51%. Topographic factor features of segmentation results are statistically analyzed. This study presents an effective and practical approach for segmenting terrain regions. This approach may be incorporated into the theory and method system of digital terrain analysis.     

不同分辨率DEM提取地面坡度的不确定性模拟:以在黄土高原的试验为例

Slope is one of the crucial terrain variables in spatial analysis and land use planning,especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas,but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

Simulation on slope uncertainty derived from DEMs at different resolution levels： a case study in the Loess Plateau

Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as(0.0015S2 0.031S-0.0325)X-0.0045S2-0.155S 0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

Simulation on slope uncertainty derived from DEMs at different resolution levels: a case study in the Loess Plateau

Slope is one of the crucial terrain variables in spatial analysis and land use planning, especially in the Loess Plateau area of China which is suffering from serious soil erosion. DEM based slope extracting method has been widely accepted and applied in practice. However slope accuracy derived from this method usually does not match with its popularity. A quantitative simulation to slope data uncertainty is important not only theoretically but also necessarily to applications. This paper focuses on how resolution and terrain complexity impact on the accuracy of mean slope extracted from DEMs of different resolutions in the Loess Plateau of China. Six typical geomorphologic areas are selected as test areas, representing different terrain types from smooth to rough. Their DEMs are produced from digitizing contours of 1:10,000 scale topographic maps. Field survey results show that 5 m should be the most suitable grid size for representing slope in the Loess Plateau area. Comparative and math-simulation methodology was employed for data processing and analysis. A linear correlativity between mean slope and DEM resolution was found at all test areas, but their regression coefficients related closely with the terrain complexity of the test areas. If taking stream channel density to represent terrain complexity, mean slope error could be regressed against DEM resolution (X) and stream channel density (S) at 8 resolution levels and expressed as (0.0015S2+0.031S-0.0325)X-0.0045S2-0.155S+0.1625, with a R2 value of over 0.98. Practical tests also show an effective result of this model in applications. The new development methodology applied in this study should be helpful to similar researches in spatial data uncertainty investigation.     

起伏地形下黄河流域太阳直接辐射分布式模拟

1 Introduction Directsolarradiation (DSR)isthe key com ponentofthe globalradiation reaching the Earth.For the influence of terrain factors,calculation of DSR quantity of rugged terrain is considerably com plex (Oliphantetal.,2003). The solarradiation quan…     

起伏地形下黄河流域太阳直接辐射分布式模式

基于数字高程模型(DEM)数据和气象站观测资料建立了起伏地形下太阳直接辐射分布式计算模型,模型充分考虑了地形因子(坡向、坡度、地形相互遮蔽)对起伏地形下太阳直接辐射空间分布的影响;以1km×1km分辨率的DEM数据作为地形的综合反映,计算了起伏地形下黄河流域1km×1km分辨率太阳直接辐射的空间分布;深入分析了起伏地形下太阳直接辐射受地理、地形因子影响的变化规律.结果表明受地形起伏和坡向、坡度等局地地形因子的影响,山区年太阳直接辐射量的空间差异比较明显,向阳山坡(偏南坡)的年直接辐射量明显高于背阴山坡(偏北坡).     

多分析尺度下综合判别的地形元素分类方法

地形元素（如山脊、沟谷等）是地表形态类型基本单元,通过地形元素的不同空间组合可形成更高级别的地貌类型。现有的地形元素提取方法大多依靠地形属性计算,难以克服地形元素的空间相关性表达与局部地形属性计算存在不对应的矛盾,Jasiewicz和Stepinski提出的Geomorphons方法——基于高程相对差异信息进行地形元素分类,可避免这一问题,但Geomorphons方法本质上是在单一分析尺度上选择地形特征点用于判别,易受局部地形起伏的影响而造成误分类。针对这一问题,设计出一种多分析尺度下综合判别的地形元素分类方法。应用结果表明：相比Geomorphons方法,利用该方法得到的地形元素的分类结果更为合理。     

基于分层策略和模糊推理的北方石质山区土壤厚度制图——以滦平县虎什哈流域为例

土壤厚度信息对土壤碳储量估算、水文-生态过程模拟等有着重要影响,但我国北方石质山区缺乏现势性好、分辨率高的土壤厚度分布数据及其快速获取方法。基于北方石质山区土壤厚度的分布特点,先将地貌信息和植被类型叠加生成制图单元,再根据每类单元的特征,针对性地选取地形参数和地表覆被参数作为指示土壤厚度空间分布的环境变量,结合少量土壤样点,依据模糊推理模型,构建了基于分层制图策略的土壤厚度空间推测方法。以河北省滦平县虎什哈流域为例,利用从ASTER GDEMs提取的地形变量和从我国环境减灾卫星影像(HJ-A)提取的地表覆被信息对土壤厚度进行了推测。结果表明,该方法精度较高,是利用免费地形和遥感数据进行低成本快速土壤制图的实用途径。