数字高程模型坡度误差指标尺度转换分析

针对我国大比例尺DEM数据库尚未建成,但是国家的生产建设又需要1∶5 000DEM所提取的地形因子(如坡度),而目前少有对1∶5 000比例尺DEM转换研究的现状,该研究制定出适合福建全省不同比例尺DEM提取地形因子间互相转换标准。选取福建省典型地貌(山地、丘陵、平原)共7个样区为实验样区,使用python脚本来批量提取7个样区在5种比例尺DEM下的多种地形因子,选取坡度作为研究对象,提出适合中小比例尺DEM向大比例尺DEM转换的3个误差指标:坡度面积、坡度信息熵、坡度鉴别信息,得出1∶10 000、1∶50 000、1∶250 000、1∶500 000DEM所提取坡度因子向1∶5 000转换的定量表达式,制定出中小比例尺DEM提取坡度因子向大比例尺DEM对应因子的转换标准。     

利用雷达摄影测量方法提取DEM及其精度评价

为了解雷达立体摄影测量中各项因素对最终DEM精度的影响,采用马来西亚热带雨林地区具有不同波束模式和入射角的6对Radarsat-1影像,应用两种不同的SAR成像模型,即距离/多普勒模型和等效共线方程模型,对使用雷达摄影测量方法提取DEM进行了试验.首先分析了两种成像模型不同的物理基础,然后通过比较由它们得到的DEM的精度,发现利用距离/多普勒模型提取DEM的精度优于等效共线方程模型;然后,利用研究区的数字地形图等参考资料,分析了不同轨道、不同模式、不同分辨率、不同交角的立体像对组合以及地形因素对DEM精度的影响,要得到高精度的DEM,必须综合考虑立体像对的选取和研究区的地形、地貌等特征.     

基于DEM的龙口市林地表面积调查

以龙口市2004年1∶10000土地利用现状更新调查结果和等高线等地形资料为基础数据,借助于Arc-view软件,首先利用矢量化的等高线生成DEM数据并自动提取坡度信息,然后计算坡度的正割值,再与龙口市的林地栅格数据结合,完成研究区内几种林地在不同坡度级上表面积的统计。最后将该方法获得的林地面积与利用土地类型栅格数据求算的林地投影面积作比较分析。     

低山丘陵区多源数字高程模型误差分析北大核心CSCD

作为多学科交叉与渗透产物的数字高程模型(DEM)已在诸多学科和领域及实际应用中发挥了重要作用,但目前能够免费获取的高分辨全球DEM在不同区域仍存在很大的不确定性,应用之前进行质量评估至关重要。以烟台市为实验区,以大比例尺地形图(1∶10 000)生成的DEM为参照,结合坡度、坡向和土地覆被类型等地学因子,定量分析了目前广泛应用的两个版本ASTER GDEM(先进星载热辐射和反射辐射计全球数字高程模型)ASTETR 1和ASTER 2及不同空间分辨率SRTM DEM(航天飞机雷达地形测绘任务)(SRTM 1:～30m和SRTM 3:～90m)在低山丘陵区高程、坡度及坡向误差。结果表明:在研究区域内,ASTER 1、ASTER 2、SRTM 3、SRTM 1总体高程均方根误差分别为8.7m、6.3m、3.7m和2.9m。ASTER与SRTM的高程精度不同程度地受坡度、坡向以及土地覆被类型等地学因子的影响,DEM误差随坡度增加而增大,其中SRTM 3精度对该因子最敏感。尽管坡向对DEM精度影响不明显(4种DEM在不同坡向上的均方根误差波动范围均不超过2m),但是不同土地覆被类型下这4种DEM精度差异显著。此外,分析4种DEM提取的坡度可知,SRTM 1的均方根坡度误差最低(2.5°)、ASTER 1与ASTER 2的坡度的均方根误差大致相同(3.6°、3.9°)、SRTM 3的坡度均方根误差最高(4.3°)。坡向的精度SRTM 1最高,ASTER 1与ASTER 2次之,SRTM 3最低。研究结果对我国低山丘陵区ASTER GDEM与SRTM DEM的应用与精度评估具有一定的借鉴作用。     

基于SRTMv4的异龙湖流域地形因子提取

以最新SRTMv4版DEM作为基础数据,选择异龙湖流域为研究区域,利用ArcGIS 10平台中的水文分析扩展模块提取异龙湖流域的流域边界和流域水文特征两方面的流域地形因子。根据提取结果与获取到的实测数据进行有效性检验:①与实际调查数据的水系网和1∶5万水系图对照比较,发现基于SRTM DEM所提取出的流域地形因子等信息是合理有效的。②与1∶5万DEM所提取流域水网进行对比发现基于SRTM DEM所提取的数据精度较为满意,在相同河网密度情况下,基于SRTM的DEM与1∶5万DEM的水网细节表现高度一致,具有可靠性。     

低山丘陵区多源数字高程模型误差分析

作为多学科交叉与渗透产物的数字高程模型(DEM)已在诸多学科和领域及实际应用中发挥了重要作用,但目前能够免费获取的高分辨全球DEM在不同区域仍存在很大的不确定性,应用之前进行质量评估至关重要。以烟台市为实验区,以大比例尺地形图(1∶10 000)生成的DEM为参照,结合坡度、坡向和土地覆被类型等地学因子,定量分析了目前广泛应用的两个版本ASTER GDEM(先进星载热辐射和反射辐射计全球数字高程模型)ASTETR 1和ASTER 2及不同空间分辨率SRTM DEM(航天飞机雷达地形测绘任务)(SRTM 1:～30m和SRTM 3:～90m)在低山丘陵区高程、坡度及坡向误差。结果表明:在研究区域内,ASTER 1、ASTER 2、SRTM 3、SRTM 1总体高程均方根误差分别为8.7m、6.3m、3.7m和2.9m。ASTER与SRTM的高程精度不同程度地受坡度、坡向以及土地覆被类型等地学因子的影响,DEM误差随坡度增加而增大,其中SRTM 3精度对该因子最敏感。尽管坡向对DEM精度影响不明显(4种DEM在不同坡向上的均方根误差波动范围均不超过2m),但是不同土地覆被类型下这4种DEM精度差异显著。此外,分析4种DEM提取的坡度可知,SRTM 1的均方根坡度误差最低(2.5°)、ASTER 1与ASTER 2的坡度的均方根误差大致相同(3.6°、3.9°)、SRTM 3的坡度均方根误差最高(4.3°)。坡向的精度SRTM 1最高,ASTER 1与ASTER 2次之,SRTM 3最低。研究结果对我国低山丘陵区ASTER GDEM与SRTM DEM的应用与精度评估具有一定的借鉴作用。     

复杂地貌地形图等高线内插DEM算法的精度分析

对复杂地貌条带地形图进行了等高线矢量化,利用5种典型的插值方法生成DEM,探讨基于等高线插值生成DEM不同算法的精度并评价生成的DEM的质量.结果表明,IDW算法生成的DEM精度较高,且在其上提取的等高线与原始等高线吻合度较好,分层设色图能够较好地反映研究区的真实地形.TIN精度仅次于IDW,但此方法是目前最为成熟和快速的一种算法.自然邻域法的精度与TIN相近,高于样条函数法;kriging插值算法精度最差,不宜在复杂地貌区域使用.     

1∶1万DEM的生成及SPOT-5卫星数据正射校正

丘陵、山区利用地面高程模型(DEM)进行正射校正是消除或限制投影误差的重要方法。通过对丘陵、山区1∶1万地形图中的等高线、高程点、特征线等地形要素进行数字化处理及不同坐标系的转换等,制作生成符合规范要求的高精度的1∶1万DEM。对SPOT-5卫星影像数据进行了配准、融合及几何校正,辅助利用1∶1万DEM制作完成符合精度要求的正射影像图。1∶1万DEM及正射影像图的制作完成对全省类似地区的图件更新及地理信息系统建设具有重要的参考价值。     

应用DEM数据进行耕地坡度分级量算方法研究

数字高程模型(DEM)的应用对全省各县开展的二次土地调查具有指导性意义。以榆中县为实验区,通过应用DEM进行耕地坡度分级量算并对其适宜性进行分析,通过对不同坡度计算模型的对比分析,对耕地坡度与地形坡度差异的分析,对用不同比例尺(不同分辨率)DEM量算耕地坡度的成果对比分析,对不同坡度值确定方法所表达的坡度值的准确性对比分析,得出以下结论: 在黄土高原沟壑区可采用地形坡度代替耕地坡度,并且选择20 m等高距DEM进行耕地坡度量算是最优选择 |采用坡度图与数据库叠加进行耕地坡度等级量算的耕地坡度派生方法中,使用概率坡度模型较为可行。     

基于图像金字塔的山脉线提取方法

借鉴多分辨率分析思想对格网DEM数据进行多尺度处理,设计了一种山脉线的提取方法。该方法利用图像金字塔对格网DEM数据进行逐层分解,对不同尺度空间下的山脊线提取结果进行叠加套和,以获取最终的山脉线。实验结果表明,该方法能够较好的去除原有山脊线中存在的细小分支,提取结果符合地貌认知。     

Evaluating Shuttle radar and interpolated DEMs for slope gradient and soil erosion estimation in low relief terrain

The error in slope gradient estimates provided by digital elevation models propagates to spatial modelling of erosion and other environmental attributes, potentially impacting land management priorities. This study compared the slope estimates of Shuttle Radar Topographic Mission (SRTM) DEMs with those generated by interpolation of topographic contours, at two grid cell resolutions. The magnitude and spatial patterns of error in DEM slope, and derived erosion estimates using the Revised Universal Soil Loss Equation (RUSLE), were evaluated at three sites in eastern Australia. The sites have low-relief terrain and slope gradients less than 15%, characteristics which dominate the global land surface by area and are often highly utilised. Relative to a reference DEM resampled to the same resolution (a measure of DEM ‘quality’), the 90 m (3-s) SRTM DEM provided the best estimates of slopes, being within 20% for each 5% slope class outside alluvial floodplains where it over-predicted by up to 220%. Relative to a hillslope scale 10 m reference DEM, the 30 m (1-s) SRTM-derived DEM-S, provided slope gradient estimates slightly less biased towards under-prediction than the 90 m SRTM and significantly less biased on alluvial floodplains. In contrast, the 20 m vertical contour intervals underpinning the interpolated DEMs resulted in under-prediction of slope gradient by more than a factor of 5 over large contiguous areas (>1 km²). The 30 m DEM-S product provided the best estimate of hillslope erosion, being 3–4% better than the 90 m SRTM. The slope errors in the interpolated DEMs translated into generally poorer and less consistent erosion estimates than SRTM. From this study it is concluded that the SRTM DEM products, in particular the 30 m SRTM-derived DEM-S, provide estimates of slope gradient and erosion which are more accurate, and more consistent within and between low relief study sites, than interpolated DEMs.     

DEM保真精度定量化描述模型研究

等高线回放法是DEM精度评估的重要方法之一,可以用于检测地形的保真程度,但是现有定量评估指标属于相对保真精度的范畴。因此本文基于水系和地形的固有套合特性,提出了水系和地形套合隶属度函数,从两者的套合程度实现DEM保真精度的定量化描述。首先,根据线状要素位移准则、尺度准则、平均坡度准则、最大套合偏移量准则和目视效果准则,运用模糊数学方法建立水系和地形套合隶属度函数;然后,使用四个不同地貌类型实验区域的1:5万地形图作为基础源数据,实验分析了DEM保真精度的评估。实验结果表明水系和地形套合隶属度函数不仅可以用于DEM保真精度的定量评估,而且可以用于DEM最佳分辨率的确定以及DEM尺度转换的适宜范围的确定。     

Deriving terrain and textural information from stereo RADARSAT data for mountainous land cover mapping

A new procedure is proposed for land cover classification in a mountainous area using stereo RADARSAT-1 data. The method integrates a few types of information that can be extracted from the same stereo RADARSAT images: (1) the Digital Elevation Model (DEM) generated from the stereo RADARSAT images; (2) terrain information (elevation, slope and aspect) extracted from the derived DEM; and (3) textural information derived from the same RADARSAT images. An Artificial Neural Network (ANN) classifier is applied for the land cover classification. Performance of the proposed method is evaluated using a mountainous study area in Southern Argentina, where there is a lack of up-to-date information for environmental monitoring. The results show that the integration of textural and terrain information can greatly improve the accuracy of the classification using the ANN classifier. It demonstrates that stereo RADARSAT images provide valuable data sources for land cover mapping, especially in mountainous areas where cloud cover is a problem for optical data collection and topographical data are not always available.     

Construction of a high-resolution DEM of an Arctic ice cap using shape-from-shading

Digital elevation models (DEMs) of ice sheets and ice caps are usually constructed from elevation data acquired from airborne or satellite-borne altimetric systems. Consequently, the DEMs have a spatial resolution of about 1km which limits their use for most glaciological and remote sensing studies. In this paper we investigated the possibility of using a shape-from-shading technique, applied to a Landsat MSS image, to create a high spatial resolution DEM of Austfonna, an ice cap in Svalbard. A high correlation (coefficient of determination = 0.85) was observed between Landsat pixel brightness values, acquired during winter, and the surface slope component parallel to the solar azimuth. This relationship was used to create a DEM by calculating surface elevation profiles across the ice cap, using low spatial resolution radio echo sounding data as tie points. The resulting DEM had an estimated rms error of about 14m, with the error occurring mostly at low spatial frequencies. Shape-from-shading produces less accurate DEMs than interferometric SAR (InSAR) techniques. Nevertheless, in scenarios for which InSAR cannot be used to construct a DEM, shape-from-shading provides an acceptable alternative.     

Cadastral-level soil mapping in basaltic terrain using Cartosat-1-derived products

Lack of topographic details in cadastral maps and limited terrain information in coarse-resolution digital elevation models (DEMs) are limitations in understanding the soil–environment relationship, identification of soil patterns, and their boundaries. The present study describes the technique of cadastral-level soil mapping using Cartosat-1-derived products. A high-resolution DEM with a posting of 10 m generated from a Cartosat-1 stereo pair was used to derive terrain attributes. Based on erosional and depositional processes, five major landforms, namely plateau top, escarpment, pediment (erosional), alluvial plain, and narrow valley (depositional), have been delineated using 3D perspective viewing of the landscape and 10 m contours generated from the DEM. The pediments and alluvial plain were further divided into upper and lower pediments and alluvial plain based on elevation. A detailed slope map has been generated from the DEM and reclassified into seven slope classes, namely nearly level (0–1%), very gently sloping (1–3%), gently sloping (3–5%), moderately sloping (5–10%), strongly sloping (10–15%), moderately steep to steep (15–25%), and steep to very steep (25–50%). Five land-use/land-cover classes, namely single crop, double crop, wasteland with and without scrub, and degraded forest have been delineated using Cartosat-1-sharpened IRS-P6 LISS-IV data. The landforms, slope, and land-use/land-cover maps were integrated in a GIS framework and 45 precise physiography–land-use (PLU) units were derived. Nine soil series were identified in major landforms. Soils of plateau top, escarpment, and pediment associated with a low weathering front are very shallow to shallow in depth, have moderate to severe erosion, slight stoniness, and clay texture, whereas soils of alluvial plain, developed in Deccan basaltic alluvium, are deep to very deep (>150 cm), fine textured with shrink–swell potential, and calcareous in nature. Different phases of soil series were identified based on tone, texture, and pattern variations in the satellite image. A detailed soil map has been developed from the PLU map using soil series information and augur observations through the PLU–soil relationship. The combined use of the high-resolution DEM and satellite data has immensely helped in understanding the soil-forming environment, identification of soil patterns, and their boundaries for precise and faster mapping compared to conventional soil mapping.     

Combining satellite multispectral image data and a digital elevation model for mapping debris-covered glaciers

Automated glacier mapping from satellite multispectral image data is hampered by debris cover on glacier surfaces. Supraglacial debris exhibits the same spectral properties as lateral and terminal moraines, fluvioglacial deposits, and bedrock outside the glacier margin, and is thus not detectable by means of multispectral classification alone. Based on the observation of low slope angles for debris-covered glacier tongues, we developed a multisource method for mapping supraglacial debris. The method combines the advantages of automated multispectral classification for clean glacier ice and vegetation with slope information derived from a digital elevation model (DEM). Neighbourhood analysis and change detection is applied for further improvement of the resulting glacier/debris map. A significant percentage of the processing can be done automatically. In order to test the sensitivity of our method against different DEM qualities, it was also applied to a DEM obtained from ASTER stereo data. Additionally, we compared our multisource approach to an artificial neural network (ANN) classification of debris, using only multispectral data. While the combination with an ASTER-derived DEM revealed promising results, the ANN classification without DEM data does not.     

规则网格数字高程模型中基于距离与坡度的路径规划算法

针对A^*算法在数字高程模型（DEM）路径规划中的低效问题,提出一种基于距离与坡度的改进A^*寻路算法。该算法面向规则网格DEM,以距离和坡度作为路径搜索评估指标,设计新的评价函数,并以地表障碍评判路径的可通行性。在寻路过程中,根据实际场景DEM数据计算相匹配的参数,使得改进算法能自适应不同场景下DEM数据分辨率的变化;采用动态权值调整完备性函数和启发性函数对评价结果的影响,优化路径选择。仿真测试结果表明,改进算法能够通过参数调整适应DEM分辨率的变化,搜索出优化的路径,降低搜索时间,提高搜索效率。