我国东部地区ASTER GDEM高程精度评价

为了解我国ASTER GDEM数据高程精度,在考虑空间分布的情况下,选取我国东部辽宁、山东、浙江和海南4个地区的平原、丘陵、山地等作为典型研究区,并以1∶5万DEM为假定真值、以1∶25万DEM为参照,通过DEM面误差可视化分析和DEM面误差信息熵模型等方法对ASTER GDEM数据的高程精度做了分析。结果表明:ASTER GDEM数据高程误差在整个地图上分布是否均匀与其高程精度高低无决定关系;在山地和丘陵地形研究区,其数据高程精度要高于SRTM DEM和1∶25万DEM。总体来看,中国东部地区ASTER GDEM数据高程精度整体上要高于SRTM DEM和1∶25万DEM,但低于1∶10万DEM。     

利用车载动态PPP技术检核SRTM、ASTER GDEM和AW3D模型的高程精度

SRTM、ASTER GDEM和AW3D是比较有代表性的全球数字高程模型。本文探讨了采用车载动态PPP技术对上述3类模型的区域高程精度进行检核,首先沿广州至肇庆公路进行连续数据采集,采用动态精密单点定位（PPP）技术解算动态点的WGS-84坐标;然后利用EGM2008重力场模型和仪器高获得动态点的正常高;最后采用4种不同的插值方法对SRTM、ASTER GDEM和AW3D模型进行高程检验。检核结果显示：不同的插值方法具有较好的一致性,SRTM3 V4.1、ASTER GDEM V2、AW3D30的高程标准差分别优于3.4 m、4.1 m和3.3 m,均优于其全球标称高程精度;本文检核方法快速高效,有较好的适用性。     

从SRTM数据提取长沙市的数字高程模型

航天干涉成像雷达技术是最近几年发展起来的对全球进行3维地形快速测图的高新技术,它标志着空间遥感技术从2维信息获取进入到3维信息获取的新阶段.本文以从SRTM数据中提取长沙市数字高程模型为例,介绍了通过逐步处理SRTM数据,得到应用于实践中的数字高程模型.同时还简要介绍了处理数据过程中所使用的一些软件.如Surfer,MATLAB,ENVI等.     

中国地区3"SRTM高程误差特征

系统评估了中国地区航天飞机雷达地形测绘任务（Shuttle Radar Topography Mision,SRTM）3″高程误差的分布及其与地形和地表覆盖因素的关系。通过单因子分析法,使用从50多万个样本点中提取的地表特征属性确定误差的变化规律。结果显示:SRTM高程误差与不同地形和地表覆盖类型关系密切;坡度增大误差由正变负,误差绝对值增大;正误差集中在偏北坡向,负误差集中在西南坡向;误差随植被覆盖增加而增大;冰川、沙漠、湿地区域误差整体为负,城镇建筑区的误差整体为正;坡度作为主导因素,同时影响其他因素对高程误差的作用。数据在某些区域存在明显高程异常,在平坦地区存在条带现象。整体上SRTM高程误差在中国地区呈现复杂的变化规律。     

ASTER GDEM V2的南极冰川高程误差校正及精度分析

ASTER GDEM V2是研究南极冰盖表面的一种重要DEM数据源。由于南极冰雪区反射率高且缺乏地形特征,导致ASTER GDEM V2存在大量的坑、隆起等噪声,难以直接用于南极地形分析。本文以ICESat/GLAS激光点高程数据作为参考,采用修正等高线法对南极伯德（Byrd）冰川ASTER GDEM V2进行了误差校正,并将其与ICESat-1 DEM的垂直精度进行了对比分析。结果表明：ASTER GDEM V2的RMSE由校正前的26.56 m下降到校正后的18.77 m,远低于ICESat-1 DEM的RMSE（121.24 m）;校正后的ASTER GDEM V2高程精度受坡度影响较小,不存在明显的系统误差,而ICESat-1 DEM的高程精度受坡度的影响较大。本研究进一步通过地形剖面分析得到：校正前的ASTER GDEM V2噪声主要分布于高程较低、地形平坦的区域,通过修正等高线的方法可以有效去除这些噪声,去除噪声后的ASTER GDEM V2可作为研究伯德冰川理想的DEM数据源。     

利用弹性反馈神经网络融合ASTER GDEM和SRTM1高程数据

由于数据获取与后期处理方式不同,先进星载热发射和反射辐射仪全球数字高程模型(advanced spaceborne thermalemissionandreflectionradiometerglobaldigitalelevationmodel,ASTERGDEM)和航天飞机雷达地形测绘任务(shuttle radar topography mission,SRTM)数据在高程精度上存在差异,采用弹性反馈（resilient backpropagation,RProp）神经网络算法对二者进行融合处理,实现优势互补以提升高程精度。选取两个黄土丘陵沟壑地貌样区分别用于模型建立与效果验证,1∶10 000高程精度为参考数据,在建模样区应用RProp神经网络算法构建ASTER GDEM高程校正模型、SRTM1高程校正模型、ASTER GDEM与SRTM1高程融合模型,同时应用误差反向传播(back propagation,BP)神经网络建立ASTER GDEM与SRTM1高程融合模型,将这些模型的高程精度优化效果进行对比,并在验证样区检验RProp融合模型的可行性。结果表明,RProp融合模...     

面向分布式水文模型的SRTM无效高程数据处理方法

获取高精度DEM是分布式水文模型开发和应用的基础,而最新发布的全球高分辨率SRTM数据在很大程度上解决了高分辨率DEM数据获取相对困难的问题,对于水文学研究具有重要意义。由于利用雷达技术获取地面高程数据技术本身的限制,SRTM原始DEM数据中存在着很多问题。本文以雪野水库区域为例,利用ASTER数据通过分析两种数据高程差异的分布特点对SRTM高程数据无效区域进行了填充,计算结果表明该方法可以提高无效数据处理结果的精度,是一种有效的获取相对完整地形数据的方法。     

对ASTER GDEM数字高程模型的精度评价及修正

针对ASTER GDEM高程精度还未得到充分验证,以江西省莲花县为试验区,使用ICESat-2数据系统分析了ASTER GDEM在坡度、地形起伏度和土地利用类型中的误差分布.结果表明,ASTER GDEM受坡度、地形起伏度影响严重,随坡度、地形起伏度增加,GDEM误差呈上升趋势;对于不同土地利用类型,GDEM误差存在较...     

中国地区30 m分辨率SRTM质量评估

高分辨率、高质量地形数据有利于地震、火山与滑坡地质灾害等环境变化相关的研究。2014年9月,美国国家地理空间情报局宣布30 m分辨率的SRTM DEM数据逐步向全球用户免费开放。本文对中国境内最新发布的SRTM DEM开展了质量评估与验证工作,讨论了传感器波长、植被覆盖、影像数量等影响DEM质量的关键因素。研究结果表明,30 m分辨率的SRTM DEM高程精度（10 m）与SRTMX DEM相当,并优于ASTER GDEM v2、SRTM v4.1和SRTM v3。     

采用小波分析的SRTM DEM与ASTER DEM数据融合

为了利用航天飞机雷达地形测绘任务数字高程模型(SRTM DEM)与先进星载热反射和反辐射仪数字高程模型(ASTER DEM)的互补信息,提出基于小波分析的多源DEM数据融合方法,以我国秦岭典型高山峡谷地貌类型区为试验样区,选取相同位置的SRTM DEM与ASTER DEM数据,通过重采样、数据配准等步骤形成融合数据源;对小波分解的低频系数作基于邻域像素关联性的融合,高频系数采用像素点绝对值取大的融合,生成融合DEM。并把融合前与融合后的数据分别与1∶5万高程库数据作精度比较,总体统计与抽样检查表明融合DEM精度较源数据均得到了提高。该融合技术为应用SRTM DEM与ASTER DEM生成精度和可靠性更高的DEM产品提供了可行方案。     

中国及周边区域ASTERGDEM与SRTMDEM高程对比分析及互补修复

本文分析了ASTER GDEM和SRTM DEM的获取方式,通过对两者在中国及周边区域高程的对比分析,得出两者高程间存在系统误差,前者高程比后者平均低4.9m。ASTER GDEM在许多区域特别是水域及高山区常存在明显粗差;SRTM DEM在特别是高山区域会出现空白区域,但其有效区域层次清晰、细节分明,无明显粗差,可靠性高。经过填补及高差约束限制修复,生成了无空白区域的SRTM DEM和可靠性更高的ASTER GDEM。     

ASTER GDEM垂直精度评价及其在重力地形改正中的适用性

通过构建ASTER GDEM(advanced spaceborne thermal emission and reflection radiometer global digital elevation model)高程误差与影响因子间的关系模型,可对其高程精度进行有效校正。选取陕北黄土高原境内长武、宜君、甘泉、延川4个不同地貌类型的样区,以1∶5万DEM (digital elevation model)作为参考数据,经过数据预处理后,计算各点位高程误差值及相关地形因子和地表覆盖指数; 提取一定数量的采样点和检验点,引入随机森林回归算法,建立高程误差预测模型,以对高程精度进行校正,并与多元回归模型进行比较分析。实验结果表明,ASTER GDEM的高程误差特征与地形条件有较强的相关性; 随机森林回归预测模型整体上优于多元回归模型,具有较好的适用性与误差校正效果,可分别将长武、宜君、甘泉、延川的高程误差均值减小3.08 m、3.00 m、3.61 m和6.95 m。     

顾及地形坡度的SRTM和ASTER加权融合

为了克服现有SRTM和ASTER各自缺陷,提升公共DEM精度,本文提出了一种顾及地形坡度的SRTM和ASTER加权融合方法。首先对两种DEM进行地理配准;然后计算不同坡度等级下SRTM和ASTER的高程误差,并得到DEM融合权重;最后采用加权平均法对SRTM和ASTER进行融合。高精度控制点的检验表明:融合后DEM精度有明显提高,相比于原始SRTM和ASTER高程误差,标准差分别降低了5.65 m和1.20 m。     

Characterization of ASTER GDEM elevation data over vegetated area compared with lidar data

Current researches based on areal or spaceborne stereo images with very high resolutions (<1 m) have demonstrated that it is possible to derive vegetation height from stereo images. The second version of the Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) is the state-of-the-art global elevation data-set developed by stereo images. However, the resolution of ASTER stereo images (15 m) is much coarser than areal stereo images, and the ASTER GDEM is compiled products from stereo images acquired over 10 years. The forest disturbances as well as forest growth are inevitable in 10 years time span. In this study, the features of ASTER GDEM over vegetated areas under both flat and mountainous conditions were investigated by comparisons with lidar data. The factors possibly affecting the extraction of vegetation canopy height considered include (1) co-registration of DEMs; (2) spatial resolution of digital elevation models (DEMs); (3) spatial vegetation structure; and (4) terrain slope. The results show that the accurate coregistration between ASTER GDEM and national elevation dataset (NED) is necessary over mountainous areas. The correlation between ASTER GDEM minus NED and vegetation canopy height is improved from 0.328 to 0.43 by degrading resolutions from 1 arc-second to 5 arc-second and further improved to 0.6 if only homogenous vegetated areas were considered.     

资源三号测绘卫星 DSM 与AST ER GDEM 精度对比分析--以高海拔山区为例

为了评价国产资源三号测绘卫星DSM数据质量,选取地貌类型丰富的云南省高海拔山区为试验样区,以1∶10 000实测地形图DEM为假定真值,以30m分辨率ASTER GDEM为评价参照,从高程精度和地形描述精度两方面着手,对国产资源三号测绘卫星DSM数据精确性进行分析。结果表明:国产资源三号测绘卫星DSM数据精度整体高于ASTER GDEM。     

Comparative evaluation of horizontal accuracy of elevations of selected ground control points from ASTER and SRTM DEM with respect to CARTOSAT-1 DEM: a case study of Shahjahanpur district,Uttar Pradesh,India

Digital elevation model (DEM) data of Shuttle Radar Topography Mission (SRTM) are distributed at a horizontal resolution of 90 m (30 m only for US) for the world, Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM data provide 30 m horizontal resolution, while CARTOSAT-1 (IRS-P5) gives 2.6 m horizontal resolution for global coverage. SRTM and ASTER data are available freely but 2.6 m CARTOSAT-1 data are costly. Hence, through this study, we found out a horizontal accuracy for selected ground control points (GCPs) from SRTM and ASTER with respect to CARTOSAT-1 DEM to implement this result (observed from horizontal accuracy) for those areas where the 2.6-m horizontal resolution data are not available. In addition to this, the present study helps in providing a benchmark against which the future DEM products (with horizontal resolution less than CARTOSAT-1) with respect to CARTOSAT-1 DEM can be evaluated. The original SRTM image contained voids that were represented digitally as ?140; such voids were initially filled using the measured values of elevation for obtaining accurate DEM. Horizontal accuracy analysis between SRTM- and ASTER-derived DEMs with respect to CARTOSAT-1 (IRS-P5) DEM allowed a qualitative assessment of the horizontal component of the error, and the appropriable statistical measures were used to estimate their horizontal accuracies. The horizontal accuracy for ASTER and SRTM DEM with respect to CARTOSAT-1 were evaluated using the root mean square error (RMSE) and relative root mean square error (R-RMSE). The results from this study revealed that the average RMSE of 20 selected GCPs was 2.17 for SRTM and 2.817 for ASTER, which are also validated using R-RMSE test which proves that SRTM data have good horizontal accuracy than ASTER with respect to CARTOSAT-1 because the average R-RMSE of 20 GCPs was 3.7 × 10^?4 and 5.3 × 10^?4 for SRTM and ASTER, respectively.     

Vertical accuracy assessment of freely available digital elevation models over low-lying coastal plains

The frequency of coastal flood damages is expected to increase significantly during the twenty-first century as sea level rises in the coastal floodplain. Coastal digital elevation model (DEM) data describing coastal topography are essential for assessing future flood-related damages and understanding the impacts of sea-level rise. The Shuttle Radar Topography Mission (SRTM) and Advanced Spaceborne Thermal Emission and Reflection Radiometer Global Digital Elevation Model (ASTER GDEM) are currently the most accurate and freely available DEM data. However, an accuracy assessment specifically targeted at DEMs over low elevation coastal plains is lacking. The present study focuses on these areas to assess the vertical accuracy of SRTM and ASTER GDEM using Ice, Cloud, and land Elevation Satellite, Geoscience Laser Altimeter System (ICESat/GLAS) and Real Time Kinematic (RTK) Global Positioning System (GPS) field survey data. The findings show that DEM accuracy is much better than the mission specifications over coastal plains. In addition, optical remote sensing image analysis further reveals the relationship between DEM vertical accuracy and land cover in these areas. This study provides a systematic approach to assess the accuracy of DEMs in coastal zones, and the results highlight the limitations and potential of these DEMs in coastal applications.