Accounting for Spatial Uncertainty in Optimization with Spatial Decision Support Systems

Spatial decision support systems (SDSS) are designed to make complex resource allocation problems more transparent and to support the design and evaluation of allocation plans. Recent developments in this field focus on the design of allocation plans using optimization techniques. In this paper we analyze how uncertainty in spatial (input) data propagates through, and affects the results of, an optimization model. The optimization model calculates the optimal location for a ski run based on a slope map, which is derived from a digital elevation model (DEM). The uncertainty propagation is a generic method following a Monte Carlo approach, whereby realizations of the spatially correlated DEM error are generated using 'sequential Gaussian simulation'. We successfully applied the methodology to a case study in the Austrian Alps, showing the influence of spatial uncertainty on the optimal location of a ski run and the associated development costs. We also discuss the feasibility of routine incorporation of uncertainty propagation methodologies in an SDSS.     

旋转森林模型在滑坡易发性评价中的应用研究

以三峡库区万州段为研究区,从多源空间数据中提取29个致灾因子作为区域滑坡易发性分析的评价指标,在数字高程模型基础上采用集水区重叠法划分斜坡单元,构建旋转森林集成学习模型,定量预测滑坡空间易发性,并生成滑坡易发性分区图。在易发性分区图中,高易发区占11.6%,主要分布在万州主城区和长江及支流两岸;不易发区占45.6%,主要分布在人类工程活动低、植被覆盖度高的区域。采用受访者工作特征曲线和曲线下面积对旋转森林模型的滑坡易发性进行评价,结果显示该模型的预测精度为90.7%,其预测能力优于C4.5决策树。研究表明,应用旋转森林进行滑坡易发性评价具有预测能力强、精度高等优点。     

Evaluation of Lidar and Medium Scale Photogrammetry for Detecting Soft-Cliff Coastal Change

Lidar and photogrammetry have both been evaluated for detecting shortterm coastal change using the Black Ven mudslide, Dorset as a case study. A lidar-generated digital elevation model (DEM) was obtained and initially compared with a DEM generated using available 1:7500 scale aerial photography and automated digital photogrammetry. The quality of these two data sets was assessed using a third DEM, derived using a total station and conventional ground survey methods. The vertical accuracies (rms error) of the lidar and photogrammetry were 0.26m and 0.43m respectively, although both data sets displayed a tendency to generate heights slightly lower than the elevation of the terrain surface. The quality of the two data sets was then assessed with respect to local slope angle. The accuracy of photogrammetrically derived elevations varied with slope and more so than in the case of lidar
From these basic tests, lidar has proved to be more accurate than photogrammetry for soft-cliff. monitoring. Further research is required to establish whether this trend is applicable to other data sets and specifically for photogrammetric data acquired using larger scale imagery     

A causal analysis of error in viewsheds from USGS digital elevation models

Users of GIS are faced with the ongoing and difficult problem of estimating the validity of a GIS output given the uncertainty of the quality of digital mapped data. This research project examines the manner in which error from a digital elevation model (DEM) results in error in an estimate of a viewshed. The data set includes two DEMs for the same study area. A 10-metre DEM serves as the control model to test a United States Geological Survey (USGS) DEM. The amount and spatial pattern of the error in the test DEM is determined by comparing it to the control DEM. A viewshed analysis is then performed at a set of 61 sites. After determining the relative accuracy of the viewsheds thus estimated, a causal model of viewshed error is developed, which links the sources of the DEM error with the error in the viewshed. The most important factor in DEM error is terrain roughness. The error in the viewsheds is a result of the error being propagated from the DEM, with landscape characteristics of the viewpoinr playing a role due to their effect on the error in the DEM. The conceptual path model developed sets the stage for a quancitative approach that will attempt to predict viewshed error from the landscape characteristics without direct knowledge of the error in the DEM.     

Incorporating the effect of ALS-derived DEM uncertainty for quantifying changes due to the landslide in 2011, Mt. Umyeon,Seoul

ABSTRACT

The landslide, which occurred at Umyeon mountain (Mt. Umyeon) in Seoul, Korea in 2011, was a prime example that raised awareness about the landslide in the highly urbanized area. Although many studies have been done on Umyeon landslide, there is a lack of research that detects the area where the landslide occurred and quantifies the elevation changes through remote sensing data. In this regard, this paper aims to detect and assess topographic changes quantitatively over Mt. Umyeon by using digital elevation models (DEMs) derived from airborne laser scanning (ALS) data. Since Mt. Umyeon was hilly and covered with dense trees during summer, traces of the landslide were detected by estimating the spatially distributed uncertainty of ALS-derived DEMs. The probabilistic analysis with Bayes'? theorem considering the spatially distributed DEM of difference (DoD) uncertainty enabled to detect the landslide traces efficiently and was less affected by the influence of ALS errors. The results indicated that ALS-derived DEMs have the potential to detect landslides with their uncertainty estimation, although the ALS data were acquired in hilly and densely vegetated areas. Moreover, quantifying topographic changes due to landslides with high reliability is considered to be beneficial and practically helpful for disaster recovery.     

QUALITY CONTROL OF PHOTOGRAMMETRICALLY SAMPLED DIGITAL ELEVATION MODELS

The object of this paper is to study the geometric accuracy of photogrammetrically sampled digital elevation models (DEMs)obtained by using an on line graphical DEM editor. As a reference, DEMs obtained by regular grid measurements have been used. Three different test areas are used in the study, each representing different ground types and degrees of homogeneity. The DEMs have been evaluated with respect to their standard errors in elevation, slope and curvature. The results show that the standard errors are not improved by using the on line DEM editor. It is also demonstrated that an increased point density decreases the standard error in elevation while its effect on the standard error in slope is limited. The standard error in curvature is almost independent of the point density.     

基于ICESat-2 ATLAS数据的DEM高程精度评价

为探究ASTER GDEMV3、SRTM1 DEM和AW3D30 DEM 3种开源DEM数据的高程精度,本文以高精度ICESat-2 ATLAS测高数据为参考数据,利用GIS统计分析、误差相关分析及数理统计对DEM的高程精度进行对比评价。结果表明：①AW3D30的质量最稳定;SRTM1 DEM在平原精度最高;在高原山地精度由高到低依次为AW3D30 DEM、ASTER GDEMV3、SRTM1 DEM。②DEM数据高程精度受地表覆盖影响较大,且与地形因素密切相关,在相同地表覆盖的两个研究区中DEM数据高程精度表现情况不一致,SRTM在平原地表覆盖下精度表现最好,平均误差为3.15 m,AW3D30 DEM在山地地表覆盖下精度表现最好,平均误差为7.61 m。③坡度对DEM数据的高程精度影响较大,在两个研究区3种DEM数据的高程误差均随坡度的增加而增加;坡向对DEM数据的高程精度影响较小,未发现明显的规律。     

利用不确定度的海底数字高程模型构建

综合考虑水深点不确定度信息和距离对格网节点的影响,提出了利用不确定度和距离联合确定权函数方法构建海底数字高程模型(DEM)。利用不确定度信息传递模型和海底DEM格网分辨率选取标准,在DEM精度和数据容量之间保持平衡,为生成多种形式、满足多种需要的海洋数字产品提供了基础。     

DEM内插算法与精度评定研究

本文分析了DEM数据产品的误差源、内插算法的误差模型,简要介绍了目前DEM数据产品精度评定的指标与方法途径.通过介绍DEM引出了数字高程模型内插方法,比较了各种DEM内插方法,并且分析了模型精度.     

"莫拉克"台风引起的滑坡泥石流灾害HJ-1图像遥感监测研究

利用HJ-1星2009年"莫拉克"台风前后获取的2个时相图像,通过去相关拉伸 (Decorrelation Stretch)、光谱信息增强和最大似然法分类提取滑坡、泥石流区域,并结合TRMM (Tropical Rainfall Measuring Mission)卫星降雨量数据和DEM (Digital Elevat...     

Landscape drainage modelling to enhance Landsat classification accuracies

Studies integrating digital elevation models (DEMs) with multispectral digital satellite data have typically concentrated on geographic areas characterized by moderate to high topographic relief. Variables such as elevation, slope gradient and aspect contribute most significantly to the zonation of vegetation in these environments. In areas where relief is low, vegetation zonation is based not on individual form elements but rather on physical processes. The purpose of this research was to investigate the potential of integrating multispectral and ancillary process data in such a low relief environment. For this a study area was chosen in the Boreal forest of west central Alberta where the zonation of vegetation is based, to a large extent, on landscape drainage. An initial classification of forest cover based on Landsat multispectral data yielded overall classification accuracies of 58%. A DEM was developed from a digitized 1:50,000 topographic map sheet. The differential geometry of the DEM was mapped as a series of coverages: slope, aspect, and directional curvatures (down ‐ and across slope). Two additional coverages, relief and flow paths, were also developed and mapped. A data set was extracted from the DEM through which landscape drainage could be evaluated. A univariate analysis of drainage using the form variables resulted in a 45% to 47% explanation of the observed variation. Multivariate analysis combining slope gradient, across and down slope curvatures, relief, and flow paths increased the explanation to 68%. The MSS data were reinterpreted integrating the DEM ‐ based landscape drainage model. The resulting classification accuracy was increased to 73%.     

Developing a Fine-Resolution Digital Elevation Model to Support Hydrological Modeling and Ecological Studies in the Northern Everglades

Accurate high-resolution terrain data are essential for hydrological modeling in lowlands. This study integrates elevation survey data and vegetation data at the point and 50 m scales to develop a fine-resolution digital elevation model (DEM) for the northern Everglades of Florida. The terrain was divided into two vertical strata (lowland and highland) based on a 50 m scale vegetation map. The DEM in highlands was interpolated with all the survey points and later adjusted using an association between vegetation and hydroperiod (the number of days per year that land is flooded). The DEM in lowlands was interpolated with elevation surveys tagged as lowland types. The two DEMs were then combined, forming a new DEM with a 7.7 cm mean absolute validation error—a significant (2.3 cm) improvement over the previous DEM.     

基于填挖方分析的DEM精度评价模型

针对DEM高程中误差评价指标的不足,提出了一种基于填挖方分析的DEM精度评价模型以及计算方法,将DEM填挖方误差E_c定义为待评价DEM与参考DEM在同一区域的三维体积差异和与该区域面积之商。探究了DEM填挖方误差和DEM分辨率R以及地形平均坡度S之间的关系,得到DEM填挖方误差的定量估算模型为E_c=0.004 8·R·S。实验表明,模型估算精度达95.85%以上。该模型为在不同地形条件下,确定满足限差要求的DEM分辨率提供了依据。     

一种面向DEM多尺度表达的傅里叶能量谱模型

针对数字高程模型（digital elevation model,DEM）数据的多尺度表达问题,根据DEM格网数据在能量谱密度中“低频-高能-大尺度”的对应关系,在化简中关联地形语义特征,构建了DEM数据的多尺度表达模型。实验结果表明,该模型可以实时动态派生不同尺度下的DEM数据,通过等高线放样观察发现,该模型派生的DEM数据满足地形表达、空间认知和制图综合中的“保留主要地形特征、舍弃次要地形特征”的基本原则。与常用的DEM化简方法进行高程值统计以及坡形变化的定量对比分析,结果表明该方法在统计意义与结构意义上都具有较好的效果。     

Effect of sensor modelling methods on computation of 3-D coordinates from Cartosat-1 stereo data

The orbital and the rational polynomial coefficients (RPC) models are the two most commonly used models to compute a three-dimensional coordinates from an image stereo-pair. But it is still confusing that with the identical user provided inputs, which one of these two models provides more accurate digital elevation model (DEM), especially for mountainous terrain. This study aimed to find out the answer by evaluating the impact of used models on the vertical accuracy of DEM extracted from Cartosat-1 stereo data. We used high-accuracy photogrammetric DEM as the reference DEM. Apart from general variations in statistics, surprisingly in a few instances, both the DEMs provided contrasting results, thus proving the significance of this study. The computed root mean square errors and linear error at 90% (LE90) were lower in case of RPC DEM for various classes of slope, aspect and land cover, thus suggesting its better relative accuracy.     

新源县汇水域单元滑坡灾害易发性评价

针对滑坡灾害易发性难以定量评价的问题,提出了以汇水域为基本统计单元,层次分析法与信息量法相结合的滑坡易发性评价模型。该模型是在综合分析已有监测数据的基础上,建立了坡度、黄土分布、土地表覆被、水系、断层、高程、地表粗糙度、坡向等8类要素与滑坡稳定性的相关性,根据评价结果将滑坡易发性划分为5个不同的等级。基于新疆新源县滑坡易发性评价的实验结果表明,该模型评价结果与滑坡实际分布情况相符,能够准确对不同汇水域灾害易发性进行分级评价,可以为相关部门进行防灾、预警提供一定的数据支持。提出了一种主观判断与客观分析相结合的方法,回答了"什么地方最容易发生地质灾害"的问题。     

Shallow Landslide Susceptibility Mapping Using Stereo Air Photos and Thematic Maps

Overlay (or heuristic) models have been shown to be a reasonable method to generate landslide susceptibility maps. However, overlay models are subjective and rely on expert judgment. The method developed here employs an overlay model but it tries to estimate certain parameters, such as slope angle or distance to streams, in a more quantitative manner. Each individual factor believed to have an influence on mass wasting processes is scaled to a value between 0 and 1. All different factors are then multiplied, producing the degree of stability, D_f, which lies on a ratio scale, rather than a nominal or interval scale. Thus, a pseudo probability of failure can be obtained. The data required are derived partly from thematic maps and partly from stereo air photos. The air photo stereo pair is used to automatically derive a digital elevation model which is then used to create an orthoimage of an area. The air photos are also used to develop a land use map, an important component in estimating landslide susceptibility. This methodology was tested on a section of the Santa Monica Mountains near Malibu, California. The resulting map both visually and statistically appears to successfully identify problematic areas. Although the methodology was primarily developed to identify shallow slides, the crest of a large, deep-seated landslide was also recognized. The general methodology should be easily adaptable to other regions or could be applied with a different set of factors than those considered in this specific case.     

一种面向地貌因子的光照模型

从理论和实验两个方面分析了数字地貌晕渲中Lambert漫反射光照模型和基于坡向光照模型的优缺点,讨论了其中的原因,据此提出一种面向坡度、坡向及高程的光照模型,利用一个坡度随高程逐渐变化的二十四棱锥体和两种不同特征的地形数据对该模型进行了实验,结果表明该模型能够有效克服Lambert漫反射光照模型和基于坡向光照模型的缺点。     

浅谈延清高速公路1∶2000数字高程模型制作

随着计算机技术的不断发展,数字高程模型应用越来越广泛,在测绘领域发挥着越来越重要的作用,具有广阔的应用前景与潜力。本文阐述了数字高程模型的生产方法、数字高程模型生产注意事项及DEM原始数据采集误差来源。