基于实测重力异常和地形数据确定重力梯度的研究

本文利用澳大利亚北领地West Arnhem Land 地区实测重力异常数据并联合DEM(9")和SRTM3(3")地形高程数据,使用移去-恢复技术和Stokes积分方法计算了该地区两条剖面的重力梯度及其功率谱密度,使用FFT方法解算了整个地区的重力梯度值,结果证明了联合重力异常数据和高分辨率地形高程数据能有效地提高重力梯度的解算精度;功率谱密度的计算结果与国外成熟的重力梯度功率谱密度模型相吻合,表明高于0.3 Hz频率范围的功率谱密度可看做噪声,为重力梯度数据处理中噪声的辨别和剔除提供了借鉴,另外对重力梯度辅助导航基准图的构建以及重力梯度测量系统的标定提供了有益的探索.     

基于GIS和分形的云南省富宁县交通网络研究

应用ArcGIS数字化了云南省富宁县扫描地图,获得了该县各等级公路的矢量数据;以县城为中心,计算出该县公路网的长度-半径分数维为1.409 9,结果显示该县公路网密度分布具有显著的分形特征,从县城向周围衰减;将公路矢量数据栅格化,计算出该县的路网分形维数为1.050 5,低于路网规划的1.585;山地地形是该县路网覆盖度较低的主要成因,基于SRTM DEM数据,得出该县坡度≤6°的土地仅占6.435%,地形崎岖导致公路建设的难度与成本增加;最后应用条带剖面法(swath profile),分析了该县广昆高速公路沿线的地形特征,总体地形自云南高原向广西丘陵降低,起伏大,沿线地貌可划分为西部小起伏中山、中部小起伏低山和东部小起伏低山丘陵三段。     

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.     

Effect of uncertainty in Digital Surface Models on the extent of inundated areas

The impact of uncertainty in ground elevation on the extent of areas that are inundated due to flooding is investigated. Land surface is represented through a Digital Surface Model (DSM). The effect of uncertainty in DSM is compared to that of the uncertainty due to rainfall. The Monte Carlo method is used to quantify the uncertainty. A typical photogrammetric procedure and conventional maps are used to obtain a reference DSM, later altered to provide DSMs of lower accuracy. Also, data from the Shuttle Radar Topography Mission are used. Floods are simulated in two stages. In the first stage, flood hydrographs for typical return periods are synthesized using generated storm hyetographs, the Soil Conservation Service–Curve Number method for effective rainfall, and the Soil Conservation Service synthetic unit hydrograph. In the second stage, hydrographs are routed via a one‐dimensional hydraulic model. Uncertainty in DSM is considered only in the second stage. Data from two real‐world basins in Greece are used. To characterize the inundated area, we employ the 90% quantile of the inundation extent and inundation topwidth for peak water level at specific river cross‐sections. For topwidths, apart from point estimates, also interval estimates are acquired using the bootstrap method. The effect of DSM uncertainty is compared to that for rainfall. Low uncertainty in DSM is found to widen the inundated area; whereas, the opposite occurred with high uncertainty. SRTM data proved unsuitable for our test basins and modelling context.     

局部地形改正的奇异积分研究

现有的地形改正积分核函数存在奇异现象,使得积分在奇异点处不连续.针对此问题,本文提出了采用高斯积分法与核函数项增加常数因子级数展开法来解决这一难题,并推导了高斯积分法处理奇异积分的公式及含可选小常数的地形改正的严密级数展开式.同时文中采用最新公布的3″×3″高分辨率的SRTM3地形数据代替传统的GTOP030数据计算地...     

滇池SRTM DEM数据的流域特征自动提取

以滇池流域为试验对象,在NASA发布的3弧秒SRTM DEM数据的基础上,运用Arc Hydro Tools进行流域特征的提取,结果表明,以3弧秒的SRTM数据为基础提取的流域河网与水利部门提供的数字河网基本相符,而提取的流域面积与实际流域面积十分接近,显示了SRTM DEM数据在中小型湖泊流域地表水文模拟方面的优势.     

基于MATLAB的SRTM数据完善方法的实验研究

本文利用MATLAB工具与编程,以STRM数据填充完善为研究对象,以四川汶川地域截断空值数据为例,实验研究了可变窗口、曲面插值、辅助数据等填补完善的方法与过程,对比分析了实验结果及其适用性,得出可供借鉴的有益结论。     

复杂地形地区WRF模式四种边界层参数化方案的评估

为更加精确地模拟复杂地形地区大气边界层中气象要素,将NASA发布的SRTM3(约90 m分辨率)地形高度数据引入中尺度气象模式WRF(weather research and forecasting)中,结合四种边界层参数化方案(YSU、ACM2、MYN 2.5 level TKE(简称MYN)、Bougeault and Lacarrere TKE(简称BL))及模式自带地形数据GTOPO30(约1 km分辨率),模拟了2008年4月24－25日安徽黄山及周边地区大气边界层气象要素场变化特征,并对模式输出的2m气温、2m露点温度、10 m风速、湿度廓线与模拟区域内19个气象站及2个探空站数据进行比较.结果表明,无论采用哪种地形数据,四种边界层参数化方案中,YSU方案模拟的2m气温误差最小,ACM2方案模拟的2m露点温度和10m风速误差最小;采用SRTM3数据后,四种边界层参数化方案模拟的2 m气温平均均方根误差(root mean squared error,RMSE)分别降低了3.79％(YSU方案)、2.48％(ACM2方案)、3.8％(MYN方案)、0.87％(BL方案);对2 m露点温度模拟,除MYN方案模拟平均RMSE降低了0.59％外,其他三种方案模拟误差分别增加了1.39％(YSU方案)、0.49％(BL方案)、0.89％(ACM2方案);而对10m风速的模拟结果,除ACM2方案模拟平均RMSE降低了2.28％外,其他三种方案模拟误差分别增加了0.22％(YSU方案)、2.32％(MYN方案)、2.45％(BL方案);对2个探空站点湿度廓线的模拟显示,各边界层方案均能模拟出水汽的垂直变化趋势,但模拟效果总体表现为偏湿,采用SRTM3地形数据之后,ACM2方案模拟部分时刻的低层水汽廓线有所改善.     

基于SWBD修复的SRTM DEM的1∶250000水系自动更新——以浙江省瓯江流域为例

以浙江省瓯江流域为例,基于SWBD修复的SRTM DEM数据,采用Arc Hydro Tools水文分析工具自动提取瓯江水系,并分地貌、分河流等级地定量评价水系数据精度,开展1∶250 000水系自动更新的可行性研究。结果表明：①SWBD修复的SRTM DEM的空白区域面积为54.78 km2,有效地弥补了SRTM DEM的数据缺失,进而提高了水系提取的准确度和精度;②与1∶250 000水系数据相比,基于SWBD修复后的SRTM DEM,在小起伏山、中起伏低山、低海拔丘陵上提取的水系数据精度高于其他地貌,而干流、一级支流、二级支流的精度又高于三级支流;③以资源三号卫星ZY-3遥感影像为参照,从水系上采集同名点反复比较点位精度后发现,利用SRTM DEM提取的水系符合制图规范和测绘内业规范（限差1 mm）,可以满足1∶250 000水系自动更新的要求。     

EarthEnv-DEM90: A nearly-global,void-free,multi-scale smoothed, 90m digital elevation model from fused ASTER and SRTM data

A variety of DEM products are available to the public at no cost, though all are characterized by trade-offs in spatial coverage, data resolution, and quality. The absence of a high-resolution, high-quality, well-described and vetted, free, global consensus product was the impetus for the creation of a new DEM product described here, ‘EarthEnv-DEM90’. This new DEM is a compilation dataset constructed via rigorous techniques by which ASTER GDEM2 and CGIAR-CSI v4.1 products were fused into a quality-enhanced, consistent grid of elevation estimates that spans ∼91% of the globe. EarthEnv-DEM90 was assembled using methods for seamlessly merging input datasets, thoroughly filling voids, and smoothing data irregularities (e.g. those caused by DEM noise) from the approximated surface. The result is a DEM product in which elevational artifacts are strongly mitigated from the input data fusion zone, substantial voids are filled in the northern-most regions of the globe, and the entire DEM exhibits reduced terrain noise. As important as the final product is a well defined methodology, along with new processing techniques and careful attention to final outputs, that extends the value and usability of the work beyond just this single product. Finally, we outline EarthEnv-DEM90 acquisition instructions and metadata availability, so that researchers can obtain this high-resolution, high-quality, nearly-global new DEM product for the study of wide-ranging global phenomena.