利用时间序列模型预测城市化导致的土地覆盖变化及其对当地气候的影响——以达卡市为例

Ripan Debnath
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引用次数: 0

摘要

城市化导致的自然景观变化往往导致环境退化,进而导致当地气候变化。因此,除了全球气候变化之外,达卡市持续的快速城市增长可能会显著改变当地未来的气候模式。本研究探讨了达卡市从1975年开始到2035年预测情景的城市化(人口)、土地覆盖和气候(温度)之间的过渡关系。分析了卫星图像、地理、人口和气候数据。核心城市土地覆盖(面积)的变化被视为人口增长的函数,并使用线性回归技术进行建模。该研究开发并验证了一个用于预测平均最高温度变化的时间序列(ARIMA)模型,其中(预测的)土地覆盖情景是回归变量。在整个研究期间,该市呈现出日益增长的城市化趋势,这表明未来城市核心土地覆盖率将持续增长。因此,该市的平均最高气温在2016年至2035年期间可能比1996年至2015年期间平均上升1.5摄氏度左右。预计这项研究的结果可能有助于轻松认识到城市化导致的气候变化,这对有效的气候变化管理行动和城市规划至关重要。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Anticipating urbanization-led land cover change and its impact on local climate using time series model: a study on Dhaka city
Urbanization-led changes in natural landscape often result in environmental degradation and subsequently contribute to local climate variability. Therefore, apart from global climate change, Dhaka city’s ongoing rapid urban growth may result in altering future local climate patterns significantly. This study explores transition relationships between urbanization (population), land cover, and climate (temperature) of Dhaka city beginning in 1975 through to forecast scenarios up to 2035. Satellite image, geographic, demographic, and climatic data were analyzed. Change in core urban land cover (area) was regarded as a function of population growth and was modeled using linear regression technique. The study developed and validated a time series (ARIMA) model for predicting mean maximum temperature change where (forecasted) land cover scenarios were regressors. Throughout the studied period, the city exhibited an increasing urbanization trend that indicated persistent growth of core urban land cover in future. As a result, the city’s mean maximum temperature was found likely to increase by around 1.5-degree Celsius during 2016–2035 on average from that of observed 1996–2015 period. It is expected that findings of this study may help in recognizing urbanization-led climate change easily, which is crucial to effective climate change management actions and urban planning.
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