项目名称: 多尺度NED/DEM生成的数字综合理论和关键技术研究
项目编号: No.41471328
项目类型: 面上项目
立项/批准年度: 2015
项目学科: 天文学、地球科学
项目作者: 游涟
作者单位: 武汉大学
项目金额: 83万元
中文摘要: 美国在全面利用高精度源数据基础上,于2006年推出了新一代DEM- - 国家高程数据集(NED),旨在全球高程数据新型服务。分析表明:NED虽运用了高精度源数据,但仍采用了有缺陷的机械取样建模途径,背离了质量理论中分辨率和数据完整性的科学概念,导致误差仍大、缺乏完整性和高程逻辑一致性等缺陷。本项目旨在前期研究和试验基础上,对目标DEM/NED各节点责任区上用数字综合的特征建模方法,找出特征代表点的技术途径代替机械取样,以递次生成科学多尺度DEM/NED序列。拟实施下列硏究:1. 高程质量主要参数的尺度效应和数字综合理论研究;2. 多尺度构建基础栅格库技术研究;3. 多尺度数字综合实验平台构建及验证实验。力图通过对质量主要参数尺度效应的研究,实现和完善DEM/NED数字综合生成理论和方法研究,实现软件工具和配套设置;给出区域实验,实现优良质量。
中文关键词: 国家高程数据集;数字高程模型;数字綜合;特征建模;机械取样建模
英文摘要: The United States on the basis of comprehensive use of high-precision source data, launched a new generation of DEM - 2006 national elevation data set (NED), aimed at the global new elevation data services. Analysis shows that although NED used a high precision source data, but still adopted the defective mechanical sampling approach, deviated from the scientific quality theoretical concept of resolution and data integrity, cause error is still large, logical consistency defects such as the lack of integrity.This project aims to, based on the previous research and test on the target DEM/NED on each node area with feature modeling method of the digital generalization instead of mechanical sampling, based on recursive generating science sequence of multi-scale DEM/NED. To implement the following extensive investigate 1. The scale effect of main parameters of elevation quality and the theoretical research of digital generalization; 2. The technology research of building foundation raster database; 3. Building experimental platform of Multi-scale digital generalization and verifying experiments.With the help of the scale effect research, we can realize and improve the research of digital generalization theory and method of DEM/NED; realize the form a complete set of software tools and Settings; And high-quality regional experiments are presented.
英文关键词: NED;DEM;Digital Generalization;Feature modeling;Mechanical sampling modeling