Document Type
Article
Publication Date
5-1-2021
Department
College of Forest Resources and Environmental Science
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.
Publication Title
Land
Recommended Citation
Mu, B.,
Tian, G.,
Xin, G.,
Hu, M.,
Yang, P.,
Wang, Y.,
Xie, H.,
Mayer, A. L.,
&
Zhang, Y.
(2021).
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.
Land,
10(5).
http://doi.org/10.3390/land10050471
Retrieved from: https://digitalcommons.mtu.edu/michigantech-p/14870
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Version
Publisher's PDF
Publisher's Statement
© 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Publisher’s version of record: https://doi.org/10.3390/land10050471