基于CA-Markov模型的南京市热环境格局演变及预测分析

摘要/Abstract

摘要： 基于Landsat5 TM和Landsat8 OLI/TIRS数据,利用辐射传输方程法反演南京市地表温度,结合景观格局指数进行热环境格局
演变分析,并利用CA-Markov模型预测了2024年南京市热环境变化。结果表明,2000~2017年南京市高温区面积增加了456.55 km²,
增幅为149.75%,中温区、低温区及次低温区面积呈现持续减少的趋势;在斑块类型水平上,高温区斑块在热力景观格局中的
优势度在迅速上升,2000~2010年热岛高温区斑块破碎度下降,斑块复杂程度降低,而2010~2017年则与之相反。
在景观水平上,南京市热力景观格局破碎程度降低,各类型斑块面积趋于均匀化,斑块间聚集程度增加。基于CA-Markov模型
模拟的2017年南京市热环境空间分布具有较高的精度,各热岛类型平均误差小于6%,模型总体Kappa系数为78.36%。
2024年南京市热环境的预测结果表明,2024年南京市热岛高温区及次高温区面积分别增加了94.96 km²、126.91 km²,
中温区、次低温区及低温区面积延续了减少的趋势。

关键词: 热岛效应;热环境, CA-Markov模型;南京市

Abstract: Based on Landsat5 TM and Landsat8 OLI/TIRS data, the land surface temperature of Nanjing city is
retrieved by radiative transfer equation, and the thermal landscape pattern evolution is analyzed
by landscape pattern indices. Then the thermal environment change of Nanjing in 2024
is predicted by CA-Markov model. The results show that, from 2000 to 2017, the area of high
temperature zone in Nanjing increased by 456.55 km² and 149.75%, and the area of mid-temperature
zone, low and sub-low temperature zone decreased continuously. On the patch-class level, the
dominance of high temperature patch in thermal landscape pattern was rising rapidly. From 2000
to 2010, the fragmentation and complexity of the high temperature patch decreased, which is
contrary to that from 2010 to 2017. On the landscape level, the fragmentation degree of
thermal landscape pattern in Nanjing decreased, the area of various patches tended to be
uniform, and the degree of aggregation among patches increased. It is shown that the
simulation result of thermal environment of Nanjing in 2017 based on CA-Markov model
has a high simulation accuracy, with the average error of each heat island type less than
6% and the Kappa index of the model of 78.36%. The prediction results of thermal environment
of Nanjing in 2024 show that the area of high temperature and sub-high temperature zone will
increase by 94.96 km² and 126.91 km² respectively, and the area of mid-temperature zone,
low and sub-low temperature zone will continue to decrease.

Key words: heat island effect, thermal environment, CA-Markov model, Nanjing

郭继强, 潘洁. 基于CA-Markov模型的南京市热环境格局演变及预测分析[J]. 大气与环境光学学报, 2020, 15(2): 143-153.

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