Landscape classification in karst areas based on DEM:A case study of 1∶50,000 pilot geological mapping of karst areas in southwestern China
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摘要: 数字高程模型可以定量描述地貌,而基于峰丛洼地实体的岩溶地貌量化统计方法目前尚未确立。文章在1:50 000地质测量的基础上,将西南岩溶区地质填图试点地区的地层重新划分组合为火山岩层组、碎屑岩层组、灰岩层组、白云岩层组、泥灰岩层组、灰岩碎屑互层层组、白云岩碎屑岩互层层组7种层组类型;基于1:50 000数字地形图构建了研究区数字高程模型(DEM),通过空间分析技术建立了区域洼地锥峰DEM,以岩溶层组为统计单元,分析出各个单元的锥峰洼地数字特征,并定义锥峰洼地发育系数(k),量化峰丛洼地发育程度,将研究区地貌划分为5种地貌类型:峰丛洼地(k>8.5),锥峰洼地极为发育;峰丛谷地(1.9<k≤8.5),锥峰较为发育,洼地中等发育;丘岭谷地(0.9<k≤1.9),锥峰弱发育,洼地极少发育;溶蚀中山(0<k≤0.9),锥峰、洼地极少发育;侵蚀中山(k=0),发育冲沟,无岩溶形态发育。Abstract: Digital elevation model(DEM)can quantitatively describe landforms. While the statistic approach of karst entities based on peck-cluster depression has not been established yet. Based on 1:50,000 digital topographic maps of Dawan,Muxiang,Yanzikou and Zhuzhong in the Wumengshan mountains, this work builds the DEM of the study area and the peak-cluster depression DEMs by spatial analysis. On the basis of 1:50,000 geology surveys, the strata in the survey area are reclassified into seven karst strata association types, volcanic strata group, clastic strata group, limestone strata group, dolomite strata group, marl strata group, limestone-clastic interbed group and dolomite-clastic interbed group. Taking karst strata association as a statistical unit, the parameters of peak-cluster depression of each unit are analyzed. Peak-cluster depression development coefficient (k) is defined to quantify the development degree of karst. The geomorphology of the survey area is divided into 5 landscape types. Of them, Ppeak-cluster depression, k>8.5, peak depression is extremely developed. Ridged-hill valley, 1.9<k≤8.5, the cone peak is relatively developed, and the depression is moderately developed. Clustered-hill valley, 0.9<k≤1.9, the cone peak is weakly developed, and the depression is rare. Karst mountain,0<k≤0.9, cone peak depression is also rare. Middle mountain,k=0, developed gullies, no karst. The karst geomorphologic types established are consistent with the combined characteristics of karst entities. The classification results reflect the distribution and differentiation characteristics of different karst landscape in a small range.
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Key words:
- Wumengshan mountains /
- karst landscape /
- DEM /
- karst strata association /
- landscape classification
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