基于多源数据的中国地形海拔分级指标调整研究

doi:10.13249/j.cnki.sgs.2017.10.015

地理科学 ›› 2017, Vol. 37 ›› Issue (10): 1577-1584.doi: 10.13249/j.cnki.sgs.2017.10.015

基于多源数据的中国地形海拔分级指标调整研究

龙晓君^1,^2,³(), 李小建^2,³

1. 广东财经大学地理与旅游学院,广东广州 510220
2.河南财经政法大学城乡协调发展河南省协同创新中心,河南郑州 450046
3. 河南大学环境与规划学院黄河文明与可持续发展研究中心,河南开封 475001

收稿日期:2016-10-14 修回日期:2017-04-29 出版日期:2017-10-20 发布日期:2017-10-20
作者简介:
作者简介：龙晓君（1973-）,女,河南开封市人,博士,讲师,主要研究领域为地质生态环境与地质灾害、灾害经济、人口地理学。E-mail:935627279@qq.com
基金资助:
国家自然科学基金项目(41471117)、教育部人文社会科学重点研究基地重大项目（16JJD770021）、河南省2015博士后科研项目（20160226）和广东省哲学社会科学“十三五”规划2017年度学科共建项目(GD17XGL16)资助

Mountain Attitude Classification Indexes Adjustment Based on Multi-Source Data in China

Xiaojun Long^1,^2,³(), Xiaojian Li^2,³

1. School of Geography and Tourism, Guangdong University of Finance&Economics, Guangzhou 510220, Guangdong, China
2. Collaborative Innovation Center of Urban-Rural Coordinated Development, Henan Province, Henan University of Economics and Law, Zhengzhou 450046, Henan, China
3. College of Environment and Planning, Research Institute of Yellow River Civilization and Sustainable Development, Henan University, Kaifeng 475001, Henan, China

Received:2016-10-14 Revised:2017-04-29 Online:2017-10-20 Published:2017-10-20
Supported by:
National Natural Science Foundation of China (41471117), Key Program of the Social Science and Humanity Research Institute of Ministry of Education, China(16JJD770021), 2015 Henan Postdoctoral Science Foundation(20160226), 2017 Guangdong Planning Project of Philosophy and Social Sciences (GD17XGL16)

摘要/Abstract

摘要：

使用SRTM DEM、土地覆被、冻融侵蚀、河流沟谷等多源数据,对区分海拔等级的指标地物作了具体分析,以指标地物的平均海拔为依据,通过分级指标对象(如冰川、林线)分布高程重合或贴近的多条等高线圈形成分级等高平面,对陆地地貌进行切割划分,用每组指标对象偏离等高平面的值作为控制量(控制点),插值重构分级参考曲面。该方案最大限度突出指标的地理意义,形成的海拔分级结果与中国地理系统分布特征更为贴近,可以为中国大尺度地貌基本形态的划分提供参考。

关键词: 海拔, 分级指标, 参考曲面, 多源数据

Abstract:

Because of the complicated mountain land types in China, it is often difficult for the existing mountain land classification indexes to take all morphogenetic zones into account. As a result, indexes lose indicative significance in local regions. In order to establish altitude classification indexes with clear geographical significance, the altitude characteristics of index surface features that could distinguish between mountain land level was analyzed in the paper through multi-source data, including SRTM, DEM, land cover, freeze-thaw erosion and river valleys. Based on the average altitude of index surface features, the classification planes with equal attitude were formed through classification index objects (such as glacier and forest line) distribution elevation coincidence or adjacent multi-contour line circles. Besides, the mountain land was cut and divided. The values that each group of index object deviated from the plane with equal attitude were considered as the controlled quantity (control points). The classification reference surface was remonstrated via interpolation. The research highlighted the geographical significance of the indexes to the largest degree. The obtained results of mountain land classification was the most close to the distribution characteristics of mountain resources and environment system in China. It is hoped that the research can provide basic reference for the regionalization of mountain land that is oriented from the characteristics resource distribution.

Key words: mountain, classification indexes, reference surface, multi-source data

中图分类号:

P208

龙晓君, 李小建. 基于多源数据的中国地形海拔分级指标调整研究[J]. 地理科学, 2017, 37(10): 1577-1584.

Xiaojun Long, Xiaojian Li. Mountain Attitude Classification Indexes Adjustment Based on Multi-Source Data in China[J]. SCIENTIA GEOGRAPHICA SINICA, 2017, 37(10): 1577-1584.

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	面积(10⁴km²)	比例(%)
低海拔(<1 000 m)	393.32	41.15
中海拔(1 000~3 500 m)	346.56	36.26
高海拔(3 500~5 000 m)	154.79	16.20
极高海拔(>5 000 m)	61.06	6.39

	I区	II区	III区	IV区	V区	VI区
极高海拔-高海拔断点(m)	-	-	-	5000	3953	5342
高海拔-中海拔断点(m)	-	-	3500	4134	3397	4134
中海拔-低海拔断点(m)	867	775	902	775	1000	1000

分级	面积(×10⁴km²)	比例(%)
低海拔	374.83	39.22
中海拔	389.17	40.72
高海拔	152.22	15.93
极高海拔	39.51	4.13

基于多源数据的中国地形海拔分级指标调整研究

Mountain Attitude Classification Indexes Adjustment Based on Multi-Source Data in China

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