探索CA-马尔科夫模型对南京旧城区城市功能区域的预测能力
Xinyu Hu1, Wei Zhu2, Ximing Shen2
1College of Landscape Architecture, Nanjing Forestry University, Nanjing, 210037, China. sherry@njfu.edu.cn.
Scientific reports
|August 8, 2024
概括
本研究使用兴趣点 (POI) 数据,用CA-马尔科夫模型预测城市功能区域. 该模型显示单一功能的稳定性,但与混合的城市功能作斗争.
科学领域:
- 城市规划和发展
- 地理信息系统 (GIS) 是指地理信息系统.
- 时间空间数据分析
背景情况:
- 可持续发展的城市发展研究越来越多地使用着"感兴趣点" (POI) 数据.
- 现有关于城市功能区域的研究通常依赖于单一时期的数据,限制了预测验证.
- 预测未来的城市功能区域仍然是当前方法的挑战.
研究的目的:
- 通过多年POI数据,提出和验证一种用于预测城市功能区域的新方法.
- 评估CA-Markov模型在城市功能区域预测中的准确性,稳定性和适用性.
- 评估模型在单一和混合城市功能区域的性能.
主要方法:
- 利用了几年的南京市的POI数据进行分析.
- 应用CA-马尔科夫模型来识别和预测城市功能区域分布.
- 进行多个实验组来评估预测的准确性,稳定性和稳定性.
主要成果:
- 该CA-马尔科夫模型在多年内对单个功能区域进行了稳定和准确的预测.
- 模型的稳定性得到证实,可以根据长期数据预测城市功能区域.
- 混合功能区域的预测被发现是不准确的,严重依赖基准年数据.
结论:
- CA-马尔科夫模型是一个可参考的工具,用于预测单个城市功能区域的变化.
- 该模型目前的局限性阻止了混合城市功能区域的准确模拟和预测.
- 需要进一步的研究来完善预测复杂,混合的城市功能动态的模型.
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