项目名称: 基于数字指标体系的典型黄土地貌定量演化模式的构建研究
项目编号: No.41301469
项目类型: 青年科学基金项目
立项/批准年度: 2014
项目学科: 天文学、地球科学
项目作者: 赵尚民
作者单位: 太原理工大学
项目金额: 25万元
中文摘要: 土壤侵蚀是黄土高原地区面临的首要问题。黄土地貌演化作为土壤侵蚀的必然结果和外在表征,其定量演化模式的建立为研究土壤侵蚀的速度、进程及特点提供重要基础。本项目以典型黄土地貌类型- - 黄土塬、黄土梁和黄土峁为研究对象,在其地貌实体及要素的基本几何特征、地表形态特征和遥感影像特征的基础上,构建对应的数字指标并通过有机组合形成各典型黄土地貌类型的数字指标体系;通过基于高精度DEM和高分辨率遥感影像数据的数字指标体系的识别与提取研究,获取典型黄土地貌类型的空间分布特征、数字指标体系的数值分布特征和自动提取方法;对不同黄土地貌类型数字指标体系的数值分布特征进行深入分析,建立其一一对应关系并研究各指标在不同地貌类型下的变化规律,从而探索典型黄土地貌类型的形成过程、相互转化过程与演化规律,进而基于此开发其定量演化模式。本项目为精细黄土地貌的定量研究提供一条途径,具有较为重要的科学意义和实践价值。
中文关键词: 典型黄土地貌类型;定量演化模式;数字指标体系;数字高程模型数据;遥感影像
英文摘要: Soil erosion is an important problem in Loess Plateau, which leads to the evolution of loess geomorphology. So the geomorphologic evolving construction of the loess geomorphology can provide important foundation for the research to the velocity, progress and characteristics of the soil erosion. Taking typical loess geomorphologic types - loess tableland, loess ridge and loess hill as study objects, this research constructs the digital indexes based on the basic geometric features, topographic features and remote sensing image features of the geomorphologic bodies and elements, and then form the digital indexes system for the typical loess geomorphology types through organic combination; through the research to the recognition and extraction of the digital indexes system based on DEM data with high accuracy and remote sensing images data with high resolution, this research acquires the spatial distribution characteristics, the numerical distribution characteristics of digital indexes system and automatic extraction methods of typical loess geomorphologic types; making deep analysis to the numerical distribution characteristics of digital indexes system for different loess geomorphology types, constructs their one-to-one correspondence and studies the change rule of the indexes under different geomorphologic types
英文关键词: Typical loess geomorphology types;Quantitative evolution mode;Digital index system;Digital elevation model data;Remote sensing image