首页    期刊浏览 2024年11月24日 星期日
登录注册

文章基本信息

  • 标题:Spatiotemporal Change Analysis and Future Scenario of LULC Using the CA-ANN Approach: A Case Study of the Greater Bay Area, China
  • 本地全文:下载
  • 作者:Zaheer Abbas ; Guang Yang ; Yuanjun Zhong
  • 期刊名称:Land
  • 印刷版ISSN:2073-445X
  • 出版年度:2021
  • 卷号:10
  • 期号:6
  • 页码:584
  • DOI:10.3390/land10060584
  • 语种:English
  • 出版社:MDPI, Open Access Journal
  • 摘要:Land use land cover (LULC) transition analysis is a systematic approach that helps in understanding physical and human involvement in the natural environment and sustainable development. The study of the spatiotemporal shifting pattern of LULC, the simulation of future scenarios and the intensity analysis at the interval, category and transition levels provide a comprehensive prospect to determine current and future development scenarios. In this study, we used multitemporal remote sensing data from 1980–2020 with a 10-year interval, explanatory variables (Digital Elevation Model (DEM), slope, population, GDP, distance from roads, distance from the city center and distance from streams) and an integrated CA-ANN approach within the MOLUSCE plugin of QGIS to model the spatiotemporal change transition potential and future LULC simulation in the Greater Bay Area. The results indicate that physical and socioeconomic driving factors have significant impacts on the landscape patterns. Over the last four decades, the study area experienced rapid urban expansion (4.75% to 14.75%), resulting in the loss of forest (53.49% to 50.57%), cropland (21.85% to 16.04%) and grassland (13.89% to 12.05%). The projected results (2030–2050) also endorse the increasing trend in built-up area, forest, and water at the cost of substantial amounts of cropland and grassland.
国家哲学社会科学文献中心版权所有