基于CA-Markov模型的海口市城市热岛模拟预测

doi:10.7523/j.ucas.2021.0006

摘要/Abstract

摘要： 随着城市化进程的快速发展，地表覆被类型发生着前所未有的变化，也加剧了热岛效应的发展。基于Landsat数据分析海口市城市热岛的空间变化，运用CA-Markov 模型模拟预测城市热岛的发展趋势及空间分布特征，并建立城市热岛与归一化差值植被指数(NDVI)、归一化差值建成指数(NDBI)的回归模型。结果表明：1)利用CA-Markov模型模拟预测2016年海口市热环境分布情况，各热岛强度等级平均误差较小，Kappa系数为80.49%，模拟精度较高，并得到2024年海口市热环境分布情况；2)2000—2016年间，海口市热岛效应愈发明显，主要向琼州海峡沿岸、南渡河西岸以及高铁周围延伸。强热岛范围增加11.60 km²，热岛范围减少2.26 km²，大致保持不变，绿岛范围增加38.64 km²，是16年中热岛强度转变最大的。预测2024年的热岛强度分布将有向东南方向移动的趋势；3)在多元线性回归分析中，NDVI指数每升高0.1，城乡地区地表温度差降0.22~0.45 ℃；而NDBI指数每升高0.1，将对城乡地区地表温度造成0.20~1.42 ℃的温度差。此研究成果可为缓解城市热岛及规划城市未来发展方向提供科学依据和参考。

关键词: 城市热岛效应, CA-Markov模型, 预测, 多元线性回归

Abstract: With rapid development of urbanization, great changes of surface coverage have intensified urban heat island effect. Using Landsat data, we analyzed the spatial variation of urban heat island in Haikou City, and CA-Markov model was applied to simulate and predict the trending of spatial distribution characteristics of the urban heat island. Moreover, we constructed a regression model between the urban heat island and the normalized difference vegetation index (NDVI) and normalized difference built-up index (NDBI). The results show that: 1) By using the CA-Markov model to simulate and predict the distribution of thermal environment in Haikou in 2016, the average error of each urban heat island intensity level was small, and the Kappa coefficient was 80.49%. The simulation accuracy was high, and the thermal environment distribution of Haikou in 2024 was obtained. 2) From 2000 to 2016, the heat island effect in Haikou became increasingly obvious, mainly extending along the Qiongzhou Strait, the west bank of the Nandu River, and around the high-speed rail. The extent of the intense heat island has increased by 11.60 km², and the extent of the heat island has decreased by 2.26 km² and remained roughly unchanged. The extent of the green island has increased by 38.64 km², which was the largest change in the urban heat island intensity in 16 years. It is predicted that the distribution of urban heat island intensity in 2024 will move toward the southeast direction. 3) In the multiple linear regression analysis, every increase of 0.1 in the NDVI index will reduce the difference in surface temperature between urban and rural areas by 0.22-0.45 ℃. And every 0.1 increase in NDBI index will cause a temperature difference of 0.20-1.42 ℃ in urban and rural areas. The results can provide scientific basis and reference for alleviating urban heat island effect and planning the future development direction of the cities.

Key words: urban heat island effect, CA-Markov model, prediction, multiple linear regression

中图分类号:

TP79

王子安, 孟庆岩, 张琳琳, 胡蝶, 杨天梁. 基于CA-Markov模型的海口市城市热岛模拟预测[J]. 中国科学院大学学报, 2022, 39(6): 742-753.

WANG Zi, MENG Qingyan, ZHANG Linlin, HU Die, YANG Tianliang. Simulation and prediction of urban heat island in Haikou City based on CA-Markov model[J]. Journal of University of Chinese Academy of Sciences, 2022, 39(6): 742-753.

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