Literature DB >> 32947762

Modeling urban encroachment on ecological land using cellular automata and cross-entropy optimization rules.

Chen Gao1, Yongjiu Feng2, Xiaohua Tong1, Yanmin Jin3, Song Liu4, Peiqi Wu1, Zhen Ye5, Cairong Gu1.   

Abstract

Rapid urban expansion often leads to substantial encroachment on ecological lands and destruction of natural environments. We developed a new cellular automata model (named CACEO) that uses cross-entropy optimization (CEO) to reproduce and project urban expansion into coastal areas and to assess urban encroachment on ecological lands. The CEO algorithm automatically searches for the near-optimal CA parameters and is capable of objectively parameterizing CA models to predict multi-objective scenarios. We calibrated CACEO by simulating urban expansion at Wenzhou from 1995 to 2005, validated the model from 2005 to 2015 using real data, and then predicted urban expansion for 2025 and 2035. End-state overall accuracies were 93.8% for 2005 and 94.4% for 2015, while figure-of-merit metrics were 27.9% for 2005 and 19.1% for 2015. We predicted four different scenarios to year 2025 and 2035: (1) a business-as-usual (BAU)-scenario using benchmark settings; (2) a District-scenario based on a district-oriented urban development strategy; (3) a Road-scenario based on a road network-oriented urban development strategy; and (4) a Coast-scenario based on a coast-oriented urban development strategy. Each scenario predicts a substantially different pattern of urban encroachment on ecological land and significant loss of farmland, forest, wetland and grassland. These scenarios should be useful in adjusting urban development strategies at Wenzhou and elsewhere.
Copyright © 2020 Elsevier B.V. All rights reserved.

Keywords:  Cellular automata (CA); Coastal areas; Cross-entropy optimization (CEO); Scenario prediction; Urban encroachment

Mesh:

Year:  2020        PMID: 32947762     DOI: 10.1016/j.scitotenv.2020.140996

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  Research on the Optimal Allocation of Ecological Land from the Perspective of Human Needs-Taking Hechi City, Guangxi as an Example.

Authors:  Jingheng Wang; Yecui Hu; Rong Song; Wei Wang
Journal:  Int J Environ Res Public Health       Date:  2022-09-29       Impact factor: 4.614

  1 in total

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