Tang Xiaoyan, Liu Funan, Hu Xinling
College of Civil Engineering and Architecture, Xinjiang University, Urumqi, 830046, China.
Sci Rep. 2024 Sep 10;14(1):21106. doi: 10.1038/s41598-024-71709-4.
Arid regions tend to form compact urban patterns that have significant implications on urban growth and future urban patterns. Spatial simulation and projection using cellular automata (CA)-based models are important for achieving sustainable urban development in arid regions. In response to this need, we developed a new CA model (GSA-CA) using the gravitational search algorithm (GSA) to capture and project urban growth patterns in arid regions. We calibrated the GSA-CA model for the arid city of Urumqi in Northwest China from 2000 to 2010, and validated the model from 2010 to 2020, and then applied to project urban growth in 2040. The results indicated that the optimal performance of the model was achieved when the fraction of the population was 0.5. GSA-CA achieved an overall accuracy of 98.42% and a figure of merit (FOM) of 43.03% for the year 2010, and an overall accuracy of 98.52% with FOM of 37.64% for 2020. The results of the study help to adjust urban planning and development policies. The developed model has the potential to be employed in simulating urban growth and future scenarios in arid regions globally, including Northwest China and Africa.
干旱地区往往形成紧凑的城市格局，这对城市增长和未来城市格局具有重大影响。利用基于元胞自动机（CA）的模型进行空间模拟和预测，对于干旱地区实现可持续城市发展至关重要。针对这一需求，我们利用引力搜索算法（GSA）开发了一种新的CA模型（GSA-CA），以捕捉和预测干旱地区的城市增长模式。我们对中国西北干旱城市乌鲁木齐2000年至2010年的GSA-CA模型进行了校准，并在2010年至2020年对模型进行了验证，然后将其应用于预测2040年的城市增长。结果表明，当人口比例为0.5时，模型达到了最佳性能。2010年，GSA-CA的总体准确率为98.42%，品质因数（FOM）为43.03%；2020年，总体准确率为98.52%，FOM为37.64%。研究结果有助于调整城市规划和发展政策。所开发的模型有潜力用于模拟全球干旱地区（包括中国西北和非洲）的城市增长和未来情景。
