Measuring Dynamic Changes in the Spatial Pattern and Connectivity of Surface Waters Based on Landscape and Graph Metrics: A Case Study of Henan Province in Central China

Bo Mu, Guohang Tian, Gengyu Xin, Miao Hu, Panpan Yang, Yiwen Wang, Hao Xie, Audrey L. Mayer and Yali Zhang
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Bo Mu: College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
Guohang Tian: College of Landscape Architecture and Art, Henan Agricultural University, Zhengzhou 450002, China
Gengyu Xin: College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
Miao Hu: College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
Panpan Yang: College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
Yiwen Wang: College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
Hao Xie: College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China
Audrey L. Mayer: School of Forest Resources and Environmental Science, Michigan Technological University, Houghton, MI 49931, USA
Yali Zhang: College of Resources and Environmental Sciences, Henan Agricultural University, Zhengzhou 450002, China

Land, 2021, vol. 10, issue 5, 1-21

Abstract: An understanding of the scientific layout of surface water space is crucial for the sustainable development of human society and the ecological environment. The objective of this study was to use land-use/land-cover data to identify the spatiotemporal dynamic change processes and the influencing factors over the past three decades in Henan Province, central China. Multidisciplinary theories (landscape ecology and graph theory) and methods (GIS spatial analysis and SPSS correlation analysis) were used to quantify the dynamic changes in surface water pattern and connectivity. Our results revealed that the water area decreased significantly during the periods of 1990–2000 and 2010–2018 due to a decrease in tidal flats and linear waters, but increased significantly in 2000–2010 due to an increase in patchy waters. Human construction activities, socioeconomic development and topography were the key factors driving the dynamics of water pattern and connectivity. The use of graph metrics (node degree, betweenness centrality, and delta probability of connectivity) in combination with landscape metrics (Euclidean nearest-neighbor distance) can help establish the parameters of threshold distance between connected habitats, identify hubs and stepping stones, and determine the relatively important water patches that require priority protection or development.

Keywords: surface water space; landscape pattern; graph connectivity; dynamic change; Henan Province (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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