Identifying Terrestrial Landscape Character Types in China

Yulian Pan, Yunong Wu, Xi Xu, Bin Zhang and Weifu Li
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Yulian Pan: Department of Landscape Architecture, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan 430070, China
Yunong Wu: Department of Landscape Architecture, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan 430070, China
Xi Xu: Department of Landscape Architecture, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan 430070, China
Bin Zhang: Department of Landscape Architecture, College of Horticulture and Forestry, Huazhong Agricultural University, Wuhan 430070, China
Weifu Li: College of Science, Huazhong Agricultural University, Wuhan 430070, China

Land, 2022, vol. 11, issue 7, 1-19

Abstract: Landscape character assessment (LCA) is a widely used tool that integrates natural, cultural, and perceptual attributes to identify and portray landscape. In this study, we used the LCA method to identify the landscape characteristics of China at the national scale. Furthermore, we applied cultural and landscape structural factors along with spatial transmission to improve the identification system. First, we incorporated all the parameters in the assessment. We selected 15 landscape character factors from four factor types including nature, culture, spatial geographic co-ordinates, and landscape structure. These parameters were analysed using multilevel overlay and spatial connection tools in ArcGis 10.2, which resulted in 2307 landscape description units (LDUs). Second, the spatial structure properties of the LDUs were determined using a semivariogram and the moving window method in ArcGis 10.2 and Fragstats 4.2 software, respectively. Third, for visualisation, we applied the principal component analysis (PCA) using the SPSS software and elbow and k-means clustering methods using MATLAB to determine 110 landscape character types (LCTs) of China’s entire terrestrial landscape. Finally, we determined 1483 landscape character areas through semiautomatic segmentation and manual visual correction using eCognition. Based on the unique characteristics of the entire terrestrial landscape of China, a set of ideas and methods for the overall identification of LCTs was proposed. Our findings can be used to optimise territorial spatial planning and landscape protection and management, and promote multiscale land-use studies in China.

Keywords: China; cluster analysis; landscape character areas (LCAs); landscape character assessment (LCA); landscape structure; landscape character types (LCTs) (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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