基于数据同化与CA模型的包头市热岛模拟预测研究

Simulation of heat island based on data assimilation and CA model in Baotou City

以内蒙古第一大工业城市包头市市区作为研究区,以1996年、2001年、2006年和2011年Landsat5的遥感影像以及2016年的Landsat8的遥感影像作为基础研究数据,用IB算法对地表温度进行反演,引入三种常用的数据同化算法对包头市市区进行热岛模拟预测并与传统的CA-Markov模型进行对比,选择最适算法对包头市市区2020年的热岛分布进行模拟预测。结果表明:引入数据同化算法能够提高CA模型模拟精度,En SRF-CA模型在包头市热岛模拟上要优于其他模型,精度能达到88.35%。根据预测得到的热岛模拟影像,到了2020年,包头市市区整体升温效果依旧明显,强绿岛区大幅度向绿岛区转移,强热岛区面积增加了44.21km^2,黄河流域水流量的减少降低了降温效果,应加强对南海湿地生态系统的保护力度以及适当增加城市绿地以减弱热岛效应。

The numerical simulation is an important component of urban heat island. A study of numerical simulation has been conducted, with the aim to improve predicted accuracy of urban heat island. Baotou, the largest industrial city in Inner Mongolia, was taken as the study area. Remote sensing images of Landsat 5 in 1996, 2001,2006 and 2011, as well as the remote sensing images of Landsat 8 in 2016 were used as the basic data. The IB algorithm was used to retrieve the land surface temperature initially. Then three common algorithms of data assimilation combined with CA model were used to simulate the urban heat island in this city. Instead of the traditional CA-Markov model, the optimal algorithm was selected to simulate the urban heat island in Baotou in 2020. Results show that using algorithm of data assimilation can improve the accuracy of CA model. The EnSRF-CA model is better than the other models in simulation of heat island in Baotou and its accuracy could reach 88.35%. According to the prediction of heat island, the overall warm- ing effect of urban area in Baotou will still be obvious in 2020. A large area of strong green island will be transferred to the green island, and the area of strong heat island will increase by 55.33km2. The decrease of water flow in the Yellow River basin has reduced the cooling effect of heat island. To alleviate the heat island effect, the protection of Nanhai wetland ecosystem should be strengthened and the urban green area should be increased in the future.