结合GPS和GLAS数据生成Dome-A区域DEM

详细阐述了利用GLAS数据和GPS数据生成Dome-A地区DEM的方法。首先进行GLAS数据转化,便于与GPS数据结合,提出一种快速搜索GLAS和其光斑(Footprint)覆盖GPS点的算法,比较GLAS数据和GPS数据发现,均值差异最大为1.118m,最小为0.997m,而标准差稳定为5—6cm,在进行椭球变换修正之后,差值最大为0.405m,最小为0.284m;之后利用改进的角度限差法沿测线对GPS数据进行特征点提取,得到抽稀之后的数据;再利用抽稀之后的GPS数据和处理后的GLAS数据使用克里金插值方法生成研究区DEM。利用1199个GPS点和53个GLAS检验点对最后生成的DEM进行了精度分析,残差中误差为5cm,最大残差绝对值为12cm。利用原始GPS数据,原始GPS数据和GLAS数据,处理后GPS数据利用克立金插值方法分别生成了研究区的DEM,通过等高线提取分析以及检验点的误差分析,处理后的GPS数据生成的DEM要优于原始GPS数据的,证明GPS处理的必要性。     

复杂地形条件下多密度级无人机LiDAR点云DEM精度研究 ——以2022年北京冬奥会延庆赛区为例

为进一步提升复杂地形条件下无人机激光雷达(Light Detection and Ranging,LiDAR)点云数据构建数字高程模型的效率与精度,以2022年北京冬奥会延庆赛区场馆建设用地为实验区,按照不同抽稀比例,对实验区原始无人机激光雷达点云中分类出的地面点数据进行抽稀处理,利用克里金插值算法对不同密度地面点数据进行插值处理,结合高程中误差、平均绝对误差对生成的数字高程模型进行双重精度评定,得出以下结论:对于复杂地形而言,随着点云数据密度的下降,数字高程模型建模效率明显提升,但地形特征逐渐模糊,数据精度级别逐级降低,其中高程中误差由0.381 m增大至1.914 m,平均绝对误差值由0.335 m增大至1.357 m.在满足精度要求的前提下,对LiDAR点云数据进行适度抽稀处理,可保障生产成本与时效.     

基于星载激光雷达和雷达高度计数据的南极冰盖表面高程制图

南极数字高程模型DEMs(Digital Elevation Models)是研究极区大气环流模式,南极冰盖动态变化和南极科学考察非常重要的基础数据。目前,科学家已经发布了五种不同的南极数字表面高程模型。这些数据都是由卫星雷达高度计,激光雷达和部分地面实测数据等制作而成。尽管如此,由于海洋与冰盖交接的南极冰盖边缘区随时间的快速变化,有必要根据新的卫星数据及时更新南极冰盖表面高程数据。因此,我们利用雷达高度计数据(Envisat RA-2)和激光雷达数据(ICESat/GLAS)制作了最新的南极冰盖高程数据。为提高ICESat/GLAS数据的精度,本文采用了五种不同的质量控制指标对GLAS数据进行处理,滤除了8.36%的不合格数据。这五种质量控制指标分别针对卫星定位误差、大气前向散射、饱和度及云的影响。同时,对Envisat RA-2数据进行干湿对流层纠正、电离层纠正、固体潮汐纠正和极潮纠正。针对两种不同的测高数据,提出了一种基于Envisat RA-2和GLAS数据光斑脚印几何相交的高程相对纠正方法,即通过分析GLAS脚印点与Envisat RA-2数据中心点重叠的点对,建立这些相交点对的高度差(GLAS-RA-2)与表征地形起伏的粗糙度之间的相关关系,对具有稳定相关关系的点对进行Envisat RA-2数据的相对纠正。通过分析南极冰盖不同区域的测高点密度,确定最终DEM的分辨率为1000 m。考虑到南极普里兹湾和内陆地区的差异性,将南极冰盖分为16个区,利用半方差分析确定最佳插值模型和参数,采用克吕金插值方法生成了1000 m分辨率的南极冰盖高程数据。利用两种机载激光雷达数据和我国多次南极科考实测的GPS数据对新的南极DEM进行了验证。结果显示,新的DEM与实测数据的差值范围为3.21—27.84 m,其误差分布与坡度密切关系。与国际上发布的南极DEM数据相比,新的DEM在坡度较大地区和快速变化的冰盖边缘地区精度有较大改进。     

正射影像辅助下的LiDAR点云构建DEM方法

提出了结合两类数据的DEM生成方法,该方法先将原始LiDAR点云自动滤波得出粗略地面点,经数据抽稀后提取地面关键点点集,再利用航迹文件和相机文件进行空三加密生成数字正射影像。在此基础上将粗分类点云与正射影像匹配,在少量人工干预下,对点云进行二次分类获得精确地面点点集,构建DEM。实验结果表明该方法是可行和有效的。     

湖盆数据未知的湖泊动态库容遥感监测方法

针对现有库容遥感监测方法对无湖盆数据区域的湖泊动态库容难以直接测算问题,提出了未知湖泊水下地形数据的遥感湖泊动态库容监测方法。该方法通过多源遥感数据,匹配相对时相的湖泊面积和水位信息,构建并模拟湖盆DEM数据,据此来估算湖泊的动态库容。在算法实现上,首先采用分布迭代水体提取从遥感影像提取湖泊的多期动态边界;其次,从ICEsat GLAS激光测高数据中反演出湖泊的动态水位高程;第三,依据时间水位信息,通过邻近时相匹配,将水位高程赋给湖泊边界线,生成湖泊等水位线;第四,通过等水位线构建TIN(triangulated irregular network)和Kriging插值,得到模拟湖盆数字高程模型;最后,依据模拟湖盆DEM和水体面积分布、水位信息,计算湖泊动态库容。试验通过对博斯腾湖的多年动态库容监测与真实性检验,结果显示:最大误差为2.21×108 m3,最小误差为0.000 02×108 m3,平均误差为0.044×108 m3,均方根为0.59,相关系数达到0.99。     

基于CryoSat-2测高数据的南极局部地区DEM的建立与精度评定

南极数字高程模型(DEM)是南极冰盖变化研究的基础数据,在我国南极重点考察地区Dome A及中山站至Dome A考察断面,利用新一代测高卫星CryoSat-2,对常用的几种插值方法如反距离加权、克里金、径向基函数、局部多项式和最近邻点插值方法的插值精度进行交叉比较,结果显示克里金插值方法的精度最高。利用中国第21次南极科学考察队采集的GPS数据,对克里金插值方法生成的两个区域的DEM精度进行验证。结果表明,坡度较小的Dome A区域DEM精度较高,平均高差为1.248 m,标准差为0.51 m;坡度较大的中山站至Dome A断面区域DEM精度较低,平均高程差达到3.87 m,标准差为9.358 m。     

基于机载LiDAR数据提取城区数字高程模型

地形分析是评估景观、土壤变迁和生态功能不可或缺的一部分,因此研究提取城区数字高程模型(DEM)的方法非常有意义.本文采用机载激光雷达(LiDAR)三维点云数据提取DEM,首先对研究区原始点云用不规则三角网算法进行滤波,获得所有的地表面点云并进行抽稀,然后应用自然领域插值法进行内插生成DEM,最后再与该区参考DEM进行对比分析.结果显示,本文提出的方法能够高精度获取城区数字高程模型.     

基于规则格网的DEM插值实验

通过地形建模,将6个地形隶属函数按照101×101,112×112,126×126,144×144,168×168,201×201,257×257 7种格网密度生成6种局部地形单元的规则格网DEM;使用反距离加权(IDW)等7种插值算法,将前6种格网密度下的DEM插值成257×257规格;从原始257×257DEM中随机抽取检查点计算残差,并对残差中误差进行分析。通过分组插值实验,运用控制变量法、方差分析等方法研究地貌类型、采样密度和插值算法对DEM插值精度的影响。     

机载LiDAR点云密度对DEM精度的影响

机载激光雷达技术(LiDAR)作为一项先进的遥感技术,是植被覆盖区DEM获取的重要手段之一,而不同地形坡度条件及点云密度对DEM产品质量有重要影响。本文以辽宁省某市的机载LiDAR数据为基础,选取5种不同地形坡度的点云数据,通过随机、等间距及基于曲率3种不同的点云抽稀方法,按照点云保留率为80%、60%、40%、20%和10%共5个不同梯度的抽稀倍数对原始点云进行抽稀简化处理,生成与之对应的DEM并对其进行精度评价,以此研究地形坡度、点云抽稀方法、抽稀倍数对DEM精度的影响。结果表明,DEM精度与地形坡度呈负相关关系,即RMSE随地形坡度升高不断增加;基于曲率的抽稀方法在地形坡度＞30°时,相较于其他两种方法RMSE较小,具有明显优势;40%的点云保留率是平衡DEM精度与数据存储效率的一个节点,当点云保留率<40%时,DEM的高程RMSE会迅速增大。该研究对于利用机载LiDAR进行大范围DEM生产具有一定的指导和借鉴意义。     

基于点云数据内插DEM的精度比较研究

利用3维激光扫描技术,以云南元谋干热河谷地区冲沟为研究对象,扫描获得大量具有冲沟坐标信息的点云数据。离散的点云数据之间没有明显的拓扑关系,不能表达连续的地表形态,通过建立格网DEM可视化表达地形信息,利用不同的内插方法生成DEM并进行精度评定,以便在不同的地貌区和采点方式下选用最佳的内插模型。点云数据经过数据配准拼接以及噪声剔除,在ArcGIS软件中,通过数据格式转换,利用反距离加权插值、克里金插值、自然领域法插值三种不同的内插方法生成DEM模型,通过检查点法分析已有的固定点高程和内插相应点的高程值做误差比较,分析不同的内插精度。实验表明,反距离加权插值法和克里金插值中误差基本相同,自然领域法插值中误差最大。分析比较不同的内插精度,对地表的坡度、坡向、等高线的研究具有重要的意义。     

多源DEM融合的高差拟合神经网络方法

本文侧重于介绍智能化摄影测量机器学习的高差拟合神经网络方法。观测手段和处理方式等限制导致全球高质量无缝DEM数据的缺乏,进而制约了它在水文、地质、气象及军事等领域的应用。本文提出了一种基于高差拟合神经网络的多源DEM融合方法,尝试融合全球DEM产品SRTM1、ASTER GDEM v2和激光雷达测高数据ICESat GLAS。首先,根据ICESat GLAS的相关参数及与DEM数据的高程差值,结合坡度自适应的思想设置高差阈值对ICESat GLAS进行滤波,剔除异常数据点。然后,以ICESat GLAS数据为控制点,利用神经网络模型拟合ASTER GDEM v2的误差分布。以地形坡度信息和经纬度坐标作为网络输入,ICESat GLAS和ASTER GDEM v2的高程差值作为目标输出,训练得到预测高差,将其与ASTER GDEM v2高程值相加即可获得校正结果。最后,引入TIN差分曲面的方法,利用校正后的ASTER GDEM v2高程值对SRTM1的数据空洞进行填充,融合生成空间无缝DEM。本文通过随机选取数据进行真实试验,对模型进行了精度验证,并给出了处理结果的定量评价和目视效果。结果表明,不论是空洞还是整体区域,本文方法相比其他DEM数据集和其他方法的处理结果都能够在RMSE上表现出优势,同时,本文提出的方法能够有效克服ASTER GDEM中异常值的影响,得到空间无缝DEM。     

多准则约束的ICESat/GLAS高程控制点筛选

激光测高卫星在获取全球高程控制点方面具有独特的优势,本文针对ICESat(Ice,Cloud and land Elevation Satellite)卫星上搭载的地球激光测高系统GLAS(Geo-science Laser Altimetry System),提出了一种多准则约束的高程控制点筛选算法。算法综合利用全球公开版的SRTM(Shuttle Radar Topography Mission)DEM数据对GLAS进行粗差剔除,然后利用GLA14产品中的云量、姿态质量标记、饱和度参数、增益参数等多种与测距有关的属性参数进行粗粒度的筛选,保留受云层、大气、地表反射率等影响较小的激光足印点,最后结合GLA01的波形特征参数做进一步精细筛选,提取出高精度的激光点作为高程控制点。本文还采用天津、河北两个实验区的数据,利用高精度的DEM成果数据对筛选的结果进行了验证。实验结果表明,经多准则约束筛选后的激光足印点具有很高的高程精度,能够作为1∶50000甚至1∶10000立体测图时的高程控制点使用,研究结论可为国产高分辨率卫星在境外地区进行无地面控制点的立体测图提供参考。     

Initial results of precise orbit and clock determination for COMPASS navigation satellite system

The development of the COMPASS satellite system is introduced, and the regional tracking network and data availability are described. The precise orbit determination strategy of COMPASS satellites is presented. Data of June 2012 are processed. The obtained orbits are evaluated by analysis of post-fit residuals, orbit overlap comparison and SLR (satellite laser ranging) validation. The RMS (root mean square) values of post-fit residuals for one month’s data are smaller than 2.0 cm for ionosphere-free phase measurements and 2.6 m for ionosphere-free code observations. The 48-h orbit overlap comparison shows that the RMS values of differences in the radial component are much smaller than 10 cm and those of the cross-track component are smaller than 20 cm. The SLR validation shows that the overall RMS of observed minus computed residuals is 68.5 cm for G01 and 10.8 cm for I03. The static and kinematic PPP solutions are produced to further evaluate the accuracy of COMPASS orbit and clock products. The static daily COMPASS PPP solutions achieve an accuracy of better than 1 cm in horizontal and 3 cm in vertical. The accuracy of the COMPASS kinematic PPP solutions is within 1–2 cm in the horizontal and 4–7 cm in the vertical. In addition, we find that the COMPASS kinematic solutions are generally better than the GPS ones for the selected location. Furthermore, the COMPASS/GPS combinations significantly improve the accuracy of GPS only PPP solutions. The RMS values are basically smaller than 1 cm in the horizontal components and 3–4 cm in the vertical component.     

GPS sidereal filtering: coordinate- and carrier-phase-level strategies

Multipath error is considered one of the major errors affecting GPS observations. One can benefit from the repetition of satellite geometry approximately every sidereal day, and apply filtering to help minimize this error. For GPS data at 1 s interval processed using a double-difference strategy, using the day-to-day coordinate or carrier-phase residual autocorrelation determined with a 10-h window leads to the steadiest estimates of the error-repeat lag, although a window as short as 2 h can produce an acceptable value with > 97% of the optimal lag’s correlation. We conclude that although the lag may vary with time, such variation is marginal and there is little advantage in using a satellite-specific or other time-varying lag in double-difference processing. We filter the GPS data either by stacking a number of days of processed coordinate residuals using the optimum “sidereal” lag (23 h 55 m 54 s), and removing these stacked residuals from the day in question (coordinate space), or by a similar method using double-difference carrier-phase residuals (observational space). Either method results in more consistent and homogeneous set of coordinates throughout the dataset compared with unfiltered processing. Coordinate stacking reduces geometry-related repeating errors (mainly multipath) better than carrier-phase residual stacking, although the latter takes less processing time to achieve final filtered coordinates. Thus, the optimal stacking method will depend on whether coordinate precision or computational time is the over-riding criterion.     

Improving the estimation of fractional-cycle biases for ambiguity resolution in precise point positioning

Ambiguity resolution dedicated to a single global positioning system (GPS) station can improve the accuracy of precise point positioning. In this process, the estimation accuracy of the narrow-lane fractional-cycle biases (FCBs), which destroy the integer nature of undifferenced ambiguities, is crucial to the ambiguity-fixed positioning accuracy. In this study, we hence propose the improved narrow-lane FCBs derived from an ambiguity-fixed GPS network solution, rather than the original (i.e. previously proposed) FCBs derived from an ambiguity-float network solution. The improved FCBs outperform the original FCBs by ensuring that the resulting ambiguity-fixed daily positions coincide in nature with the state-of-the-art positions generated by the International GNSS Service (IGS). To verify this improvement, 1?year of GPS measurements from about 350 globally distributed stations were processed. We find that the original FCBs differ more from the improved FCBs when fewer stations are involved in the FCB estimation, especially when the number of stations is less than 20. Moreover, when comparing the ambiguity-fixed daily positions with the IGS weekly positions for 248 stations through a Helmert transformation, for the East component, we find that on 359 days of the year the daily RMS of the transformed residuals based on the improved FCBs is smaller by up to 0.8?mm than those based on the original FCBs, and the mean RMS over the year falls evidently from 2.6 to 2.2?mm. Meanwhile, when using the improved rather than the original FCBs, the RMS of the transformed residuals for the East component of 239 stations (i.e. 96.4% of all 248 stations) is clearly reduced by up to 1.6?mm, especially for stations located within a sparse GPS network. Therefore, we suggest that narrow-lane FCBs should be determined with ambiguity-fixed, rather than ambiguity-float, GPS network solutions.     

Stereo Cartosat-1 satellite remote sensing data in assessing topographic potential of soil erosion

Stereo Cartosat-1 satellite data was processed to generate high spatial resolution digital elevation model (DEM) using ground control points (GCPs) collected through geodetic single frequency GPS in differential GPS mode. DEM was processed to generate bare earth DEM by removing heights of natural and man made features from DEM. The bare earth DEM was further analysed in GIS environment to generate terrain-topographic indices viz. wetness index (WI), stream power index (SPI) and sediment transport index (STI) to characterize topographic potential of soil erosion. Hillslopes in the studied watershed (part of Shiwalik hills of Dehradun district, Uttarakhand state) were characterized as low wetness index values indicating dry areas whereas high wetness index values at lower reaches of the watershed indicating as possible source areas for generation of saturated overland flow. Higher STI values were observed in hilly as well as upper part of the piedmont plain and at along sides of the streams in upper piedmont indicating areas susceptible to severe soil erosion. GIS based these topographic indices provided an easy and quick appraisal and scientific basis to identify spatial variability of soil erosion risk in a hilly watershed.     

A Comparison Between Contour Elevation Data Sources for DEM Creation and Soil Carbon Prediction, Coshocton, Ohio

A raster and vector GIS was created for the North Appalachian Experimental Watershed (NAEW) from legacy (1960) 1:2,400‐scale contour maps. The intent of the study was to use terrain data for the spatial modeling of soil organic carbon. It was hypothesized that DEMs derived from these data would be more accurate and therefore more useful for terrain‐based soil modeling than those from USGS 1:24,000‐scale contour data. Central tasks for this study were to digitally capture the 1:2,400‐scale maps, convert digital contour data sources to raster DEMs at multiple resolutions, and derive terrain attributes. A flexible approach was adopted, using software outside of mainstream GIS sources where scientifically or practically advantageous. Elevation contours and streamlines were converted to raster DEMs using ANUDEM. DEMs ranging in resolution from 0.5–30 m were tested for accuracy against precision carrier‐phase GPS data. The residual standard deviation was 1.68 meters for the USGS DEM and 0.36 meters for the NAEW DEM. The optimal horizontal resolution for the NAEW DEM was 5 m and for the USGS 10 m. Five and 10 m resolution DEMs from both data sources were tested for carbon prediction. Multiple terrain parameters were derived as proxies for surficial processes. Soil samples (n = 184) were collected on four zero‐order watersheds (conventional tillage, no‐till, hay and pasture). Multiple least squares regressions (m.l.s.) were used to predict mass C (kg m^?2, 30 cm depth) from topographic information. Model residuals were not spatially autocorrelated. Statistically significant topographic parameters were attained most consistently from the 5 m NAEW DEM. However, topography was not a strong predictor of carbon for these watersheds, with r² ranging from 0.23 to 0.58.     

Validation of Indian National DEM from Cartosat-1 Data

CartoDEM is an Indian National DEM generated from Cartosat-1 stereo data. Cartosat-1, launched in May, 2005, is an along track (aft ?5°, Fore +26°) stereo with 2.5 m GSD, give base-height ratio of 0.63 with 27 km swath. The operational procedure of DEM generation comprises stereo strip triangulation of 500?×?27 km segment with 10 m posting along with 2.5 m resolution ortho image and free—access posting of 30 m has been made available (bhuvan.nrsc.gov.in). A multi approach evaluation of CartoDEM comprising (a) absolute accuracy with respect to ground control points for two sites namely Jagatsinghpur -flat and Dharamshala- hilly; second site i.e. Alwar-plain and hilly with high resolution aerial DEM, (b) relative difference between SRTM and ASTERDEM (c) absolute accuracy with ICESat GLAS for two sites namely Jagatsinghpur-plain and Netravathi river, Western Ghats-hilly (d) relative comparison of drainage delineation with respect to ASTERDEM is reported here. The absolute height accuracy in flat terrain was 4.7 m with horizontal accuracy of 7.3 m, while in hilly terrain it was 7 m height with a horizontal accuracy of 14 m. While comparison with ICESat GLAS data absolute height difference of plain and hilly was 5.2 m and 7.9 m respectively. When compared to SRTM over Indian landmass, 90 % of pixels reported were within ±8 m difference. The drainage delineation shows better accuracy and clear demarcation of catchment ridgeline and more reliable flow-path prediction in comparison with ASTER. The results qualify Indian DEM for using it operationally which is equivalent and better than the other publicly available DEMs like SRTM and ASTERDEM.     

邵阳市区域尺度GPS高程异常分析

针对工程测量中GPS大地高代替水准正常高的问题,该文根据邵阳市实测GPS、水准数据,采用二次曲面拟合模型得到了该地区高程拟合参数。通过正常高与拟合高程进行比较,最大拟合残差为3.9cm,最小为0cm,高程异常模型拟合中误差为1.85cm,证明了该区域GPS高程拟合参数可以满足工程建设中大地高代替正常高的要求。根据GPS高程拟合参数得到的邵阳市辖区及周边地区高程异常曲面具有由西北至东南递减且变化梯度逐渐递减的特征,该区域最大高程异常15.65m,最小高程异常14.75m。