Regional hydrologic mapping of flows in stream networks

River low flow (LF) is an important hydrological characteristic used in management of the quantity and quality of water resources. A common way to transpose at-station low flow quantiles to ungaged locations involves development of regional multivariate regression models. In site selection studies of water control facilities, need arises to automate the mapping of LF characteristics onto the stream network in a continuous manner. This would allow estimation of LF at any desired ungaged location. A mapping algorithm is introduced that determines the value of regression model's independent variables (input components) over the drainage area of each stream pixel and calculates the flow (output). The mapping algorithm relies mainly on the digital elevation model (DEM) and its derivatives, such as flow direction and flow accumulation. Furthermore, the contribution of each independent variable of the regional model to the total flow may be plotted to represent the flow profiles along the streams. A case study involving LF mapping in rivers of Gilan province, Iran, where LF quantiles are required for issuing water withdrawal permits as well as maintaining water quality standards, is also described in the paper. Overall, the maps and profiles of flow statistics in the region of interest provide convenient visualization and assessment tools for water resource and environmental engineers. The transposition algorithm may also be applied in regional mapping of other flow characteristics such as flood or average flows.     

基于ERDAS的林业局3维虚拟现实系统的研究和实现——以黑龙江省清河林业局地形为例

建立一个基于3维虚拟现实系统,动态交互的环境来显示、分析、处理多种地理数据,具有非常重要的意义.本研究以清河林业局为例,收集该区域的DEM数据、遥感数据,对DEM数据进行镶嵌,对遥感数据进行几何精校正和图像的增强处理,最终构建出清河林业局的3维虚拟现实系统.     

基于DEM的南京市彩色晕渲地图的研制

分析了基于DEM数据的自动晕渲地图生成的意义,介绍了将1:5万数据库中等高线文件转换到CartoShading软件中,利用软件本身功能生成晕渲的方法.     

基于LiDAR数据的DEM和矢量自动提取探讨

近年来LiDAR技术发展迅速,应用潜力巨大.基于TerraSolid软件环境,简要介绍了LiDAR数据的分类,在此基础上,重点讨论了LiDAR数据的DEM和矢量自动提取的相关问题.由LiDAR数据生成的DEM精度较高.但矢量自动提取还未到实用阶段.     

Prediction of uniaxial compression PFC3D model micro‐properties using artificial neural networks

Artificial neural networks are used to predict the micro‐properties of particle flow code in three dimensions (PFC3D) models needed to reproduce macro‐properties of cylindrical rock samples in uniaxial compression tests. Data for the training and verification of the networks were obtained by running a large number of PFC3D models and observing the resulting macro‐properties. Four artificial networks based on two different architectures were used. The networks used different numbers of input parameters to predict the micro‐properties. Multi‐layer perceptron networks using Young's modulus, Poisson's ratio, uniaxial compressive strength, model particle resolution and the maximum‐to‐minimum particle ratio showed excellent performance in both training and verification. Adding one more variable—namely, minimum particle radius—showed degrading performance. Copyright © 2009 John Wiley & Sons, Ltd.     

基于数字高程模型不规则三角网的土方计算方法的实现

本文介绍一种基于数字高程模型(DEM)不规则三角网的土方量计算方法,其利用地形碎部点快速、方便的构建三维实体模型,计算土方精度高.     

规则格网上双方向性插值DEM精度研究

简要介绍双方向性插值方法的原理，并以线性插值和三次插值过程中的误差传播为基础，利用误差传播定律，推导出双方向性插值方法生成的DEM曲面平均高程误差值，并对线性插值和三次插值公式本身的精度进行分析。     

多波束海底地形数据空值区域的插值填补方法分析

由于边界误差剔除、测线布设过于稀疏等因素影响,利用多波束数据生成高分辨率DEM时,常常会存在一些水深空值单元或区域。为了对这些数据空值区域进行可靠填补,在考虑地形特征及空值单元大小的情况下,利用IDW、Spline、Kriging、TIN四种插值方法对某区域多波束海底DEM空值区域进行直接内插填补试验,结果表明插值算法的选取不仅受地形类型限制,而且与空值区域的大小也密切相关。     

利用InSAR技术获取高寒高海拔地区高精度DEM

本文以Sentinel-1A SLC数据为原始影像,利用InSAR技术获取新疆西天山中部高寒高海拔地区小区域DEM,将获得的DEM与常用的SRTM v4 DEM和GDEMDEM进行对比分析。结果表明：利用InSAR技术处理Sentlnel-1A SLC数据可以获得分辨率为15 m的高精度DEM,该DEM数据精度优于SRTM v4 DEM和GDEMDEM,能更好地描绘地表地形细节,可作为输入数据获取地面高精度形变信息,为工程建设和地质灾害评价提供重要的基础数据。此外,该方法对DEM数据的更新也具有重大意义。     

大尺度平原城市精细汇水区分级划分研究

在城市内涝模拟研究中,汇水区划分是十分重要的环节,同时对大尺度平原城市进行汇水区精细划分也是研究者共同研究的技术难点。针对现有基于DEM流向分析的划分方法存在的无法正确反映实际城市复杂地形和流向问题,本文提出了一种顾及地类和流向,适用于大尺度平原城市的精细汇水区分级划分方法。首先,从城市自然地形和主干河流出发,进行一级宏观尺度划分;然后,依据城市主次干道,干渠和管网实现二级中观尺度划分;最后,在二级划分的基础上,结合流向和地类做精细的三级子汇水区微观尺度划分。本文选取东营市30 km²核心主城区进行了验证分析,研究结果表明,划分结果跟实际地物类型和真实流向相吻合,该方法对于大尺度平原城市具有良好的适用性。