Regional terrain complexity evaluation based on GIS and K-means clustering model: A case study of Ningdu County, China

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Abstract

In order to accurately quantify the terrain complexity, a simple and accurate terrain complexity assessment (TCA) model is proposed. Taking Ningdu county in Jiangxi Province of China as an example, firstly, six terrain factors (named slope, topographic relief degree, surface cutting depth, surface roughness, elevation variation coefficient and topographic factors) of Ningdu county are extracted based on the Digital Elevation Model (DEM) with 30 m resolution and ARCGIS 10.2 software. Secondly, terrain complexity indexes of Ningdu County are obtained using k-means clustering. Results show that a current and effective spatial distribution characteristic of topographic complexity in Ningdu county is produced, and the very low and low terrain complexity indexes account for 33.28%, 28.35% respectively. The terrain complexity can be evaluated effectively by k-means clustering model. The terrain complexity can be provided for environmental protection and land use planning.

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Kang, W., Huang, F., Du, Y., Liu, D., & Cao, Z. (2019). Regional terrain complexity evaluation based on GIS and K-means clustering model: A case study of Ningdu County, China. In IOP Conference Series: Earth and Environmental Science (Vol. 300). Institute of Physics Publishing. https://doi.org/10.1088/1755-1315/300/2/022025

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