中国农业科学院农业信息研究所 中国农学会
Agricultural Information Institute of CAAS China Association of Agricultural Science Societies
En
Ch
中国农业科学院农业信息研究所 中国农学会 主办

AI检索

订阅

返回顶部
当前位置: 首页 > 文章 > 面向子流域单元的典型黄土地貌分类研究 干旱区研究 2019 (6) 1592-1598
Position: Home > Articles > 面向子流域单元的典型黄土地貌分类研究 Arid Zone Research 2019 (6) 1592-1598

面向子流域单元的典型黄土地貌分类研究

作  者：
王乐;周毅;李阳
单  位：
陕西师范大学地理科学与旅游学院
关键词：
子流域;地貌分类;流域分割;格网DEM;铜川;陕西
摘  要：
基于格网DEM的数字地貌形态类型自动划分是当前地貌研究的热点.根据基本分析单元的粒度大小,可将现有的分类方法划分为以栅格为分析单元和不规则坡面多边形为分析单元.然而,上述2种方法都无可避免地存在分类结果中地貌实体不完整性的问题.本文将分析单元提升至小流域级别,提出面向"细胞"级的微小尺度的子流域为分析对象的分类思想,利用GIS空间分析方法,构建子流域地理属性数据库,依据研究区已有的地貌资料,遴选出高程、起伏度、平均坡度、坡谱偏度4个核心分类指标,采用层次分类法,设定相应的地形因子阈值,将陕西省铜川市耀州区划分为:河漫滩、黄土残塬、黄土台塬、陡坡冲沟、墚峁状丘陵沟壑、石质小起伏平缓中山、石质小起伏陡峭中山以及水域等8大类型.分类结果最大程度保证了地貌实体的相对完整性,与用GPS进行的实地采样观测结果对比分析表明,该方案的分类精度达到88. 19%,可望成为基于面向子流域单元进行数字地貌分类研究的有益探索.
作  者：
WANG Le;ZHOU Yi;LI Yang;School of Geography Science and Tourism,Shaanxi Normal University;National Experimental Teaching Demonstration Center for Geography;
关键词：
subcatchment;;landform classification;;drainage basin;;grid DEM;;Tongchuan;;Shaanxi
摘  要：
In this paper,the analysis units were upgraded to the minor drainage basin level,and the subcatchments of the micro-scale oriented to the "cell"level were proposed as the classification idea of analysis object. The GIS spatial analysis was used to construct the geographic attribute database for subcatchments based on the available geomorphic data of the study area. Four key classification indicators including the elevation,relief degree of land surface,average slope and slope skewness were selected. The hierarchical classification method was used to set the thresholds of the corresponding topographic factors,and 8 types of landforms,i. e. the flood plains,residual loess tableland,loess platform,steep-slope gully,girder-like hilly gully,small rocky undulating temperate mid-mountain,small stone undulating steep-mountain and waters in Yaozhou District of Tongchuan City,Shaanxi Province were divided. The relative integrity of the landforms was maintained in the classification as much as possible. Compared with the field sampling observations performed by GPS,the classification accuracy of the study was as high as88. 19%,which is expected to be a digital geomorphological classification based on subcatchment.

相似文章

导出引用
计量
文章访问数: 7
HTML全文浏览量: 0
PDF下载量: 0

所属期刊

推荐期刊

友情链接Friendly link
农业信息研究所Agricultural information institute 农业智能知识服务平台Agricultural intelligent knowledge service platform 农业学术服务平台Agricultural Knowledge Service System 中国知网CNKI 维普网VIP 万方WANFANG DATA
联系我们Contact us

电话Tell：010-82109652-808

邮箱E-mail：agrijournal@caas.cn

服务Service
关于我们About us 意见建议Opinions and suggest
版权说明Copyright
单位：中国农业科学院农业信息研究所 中国农学会 © 2017中国农业科学院农业信息研究所 ICP备案号：京ICP备09089781号-46