首页|基于DEM的喀斯特峰丛洼地地貌信息提取及形态特征分析

基于DEM的喀斯特峰丛洼地地貌信息提取及形态特征分析

扫码查看
文章以桂西南典型喀斯特地貌——峰丛洼地为研究对象,基于DEM数据采用水文法、鞍座法提取出峰丛洼地,在此基础上借助于空间分析方法、分形理论等对研究区的峰丛洼地结构形态特征、空间分布进行定量分析和研究.结果表明:(1)运用水文分析方法能有效提取鞍部点,有效识别出洼地凹陷,提取鞍部点精度为50.00%,而鞍座法提取鞍部点的精度为79.80%;(2)94%的峰丛洼地形态为盆形,小部分为深锥形和碟状形.研究区洼地斑块周长-面积的关系为y=0.5772x+0.2674,二者的相关系数R2=0.9462,周长—面积的分维数D=1.15,洼地图斑镶嵌结构较稳定;(3)80%的峰丛洼地分布于研究区南部、北部的石灰岩与白云岩互层地区和连续性石灰岩上,中部碎屑岩岩层上峰丛洼地发育不明显.
Geomorphic information extraction and morphological characteristics analysis of karst peak-cluster depressions based on DEM
The largest area of karst in the world is distributed in China.In the karst area,the peak-cluster depression is regarded as one of the typical landforms.The positive and negative landforms in peak-cluster depressions control the spatial distribution pattern of soil and water resources,and significantly affect regional landforms,soil erosion and quality of regional ecological environment.In the southwest of Guangxi Zhuang Autonomous Region(hereinafter referred to as southwest Guangxi),the distribution of karst landforms is relatively concentrated,and their unique and steep terrain greatly restricts the development of regional economy.Consequently,this remote and border region became a poverty-stricken area in which are located old revolutionary bases and is inhabited by minority nationalities.The landform of karst peak-cluster depression together with urban architecture formed a unique mosaic landscape in southwest Guangxi,which is vulnerable in ecological environment.Although the traditional method of artificial vectorization can accurately obtain the positive and negative topographic features of peak-cluster depressions,this method has its disadvantages such as high working intensity,low working efficiency and long working period,which may pose challenges to the information extraction of peak-cluster depressions on a large regional scale,and which may also limit the detailed study on the ecosystem of peak-cluster depression basins.Therefore,it is of great significance for us to explore the formation mechanism of peak-cluster depressions and the evolution of regional geographic environment so that we can provide a scientific basis for the protection and sustainable development of regional ecological environment.In this study,with the use of software such as ArcGIS and Google Earth,information of peak-cluster depressions was extracted based on Digital Elevation Model(DEM)and satellite remote sensing images by two methods:hydrology method and saddle method.By means of spatial analysis and fractal theory,the structural morphological characteristics and spatial distribution of peak-cluster depressions were quantitatively analyzed.The results show as follows.(1)In terms of extraction methods,the saddle method can extract the depression boundary based on the features of the saddle,while the hydrology method can effectively identify the depression by simulating the convergence process of water flow.Compared with the hydrologic method,the saddle method can improve the accuracy of extracting saddle points by 29.80%.(2)In the morphological analysis of peak-cluster depressions,94%of the depressions in the study area are basin-shaped,and the rest are deep cone-shaped and dish-shaped.The main morphology of peak-cluster depressions in the study area is basin-shaped with a shallow depth and a small area.In addition,the analysis of the relationship between the circumference and the area of the depression patch finds that there is a high correlation between the two,and its fractal dimension is 1.15.The mosaic structure of the depression patch is relatively stable.(3)In terms of spatial distribution,80%of the peak-cluster depressions in the study area are concentrated in the interbedding areas of limestone and dolomite and in the contiguous areas of limestone in the south and north of the study area,while the development of peak-cluster depressions in the central clastic rock strata is not obvious.

digital elevation modelhydrologic analysiskarstpeak-cluster depressionmorphological characteristicssouthwest Guangxi

何佶泳、田义超、张强、王栋华、张亚丽、周慧娟

展开 >

北部湾大学资源与环境学院/北部湾海洋发展研究中心,广西钦州 535000

北部湾大学广西北部湾海洋环境变化与灾害研究重点实验室/海洋地理信息资源开发利用重点实验室,广西钦州 535000

桂林理工大学环境科学与工程学院,广西桂林 541004

DEM 水文分析 喀斯特 峰丛洼地 形态特征 桂西南

国家自然科学基金广西基地和人才项目广西自然科学基金联合培育项目广西壮族自治区创新驱动发展专项北部湾大学高层次人才引进项目广西壮族自治区高等学校中青年教师科研基础能力提升项目(2021)

420610202019AC200882018JJA150135AA181180382019KYQD282021KY0431

2024

中国岩溶
中国地质科学院岩溶地质研究所

中国岩溶

CSTPCD北大核心
影响因子:0.908
ISSN:1001-4810
年,卷(期):2024.43(3)