[1]冯晓刚,撒利伟,李凤霞,等.基于CA-Markov模型的西安市热环境模拟研究[J].西安建筑科技大学学报(自然科学版),2016,48(05):731-737.[doi:10.15986/j.1006-7930.2016.05.019]
 FENG Xiaogang,S A Liwei,LI Fengxia,et al.The simulation on Xians u rban heat environment based on CA-Markov model[J].J. Xi’an Univ. of Arch. & Tech.(Natural Science Edition),2016,48(05):731-737.[doi:10.15986/j.1006-7930.2016.05.019]
点击复制

基于CA-Markov模型的西安市热环境模拟研究()
分享到:

西安建筑科技大学学报(自然科学版)[ISSN:1006-7930/CN:61-1295/TU]

卷:
48
期数:
2016年05期
页码:
731-737
栏目:
出版日期:
2016-10-31

文章信息/Info

Title:
The simulation on Xians u rban heat environment based on CA-Markov model
文章编号:
1006-7930(2016)05-0731-07
作者:
冯晓刚撒利伟李凤霞李 萌 周在辉袁龙飞
(西安建筑科技大学建筑学院,陕西 西安710055)
Author(s):
FENG Xiaogang S A Liwei LI Fengxia LI Meng ZHOU ZaihuiYUAN Longfei
(School of Architecture, Xi an Univ. of Arch . & Tech .Xian 710055, China)
关键词:
元胞自动机马尔可夫模型热环境模拟西安市
Keywords:
CA model Markov model thermal environment simulation Xi’an city
分类号:
TU18
DOI:
10.15986/j.1006-7930.2016.05.019
文献标志码:
A
摘要:
将元胞自动机理论和马尔可夫模型相结合,构造了可用于城市热环境模拟与预测分析的CA-Markov模型.以西安市为例,基于单窗算法反演了西安市2000年和2006年两个不同时相城市热环境数据,并利用构建的CA-Markov耦合模型,模拟分析了西安市2018年城市热环境格局分布特征.结果表明:(1) CA-Markov模型具有较高的模拟精度,可用于城市热环境的模拟研究;(2) 2018年西安市不同热岛类型面积由高到低依次为:常温区>绿岛区>热岛区>强热岛区>强绿岛区,所占面积比例分别为:70.20 %、13.06 %、12.01 %、3.67 %、1.06 %;2006~2018年12a间强热岛区、热岛区、常温区、绿岛区和强绿岛区的面积变化分别为:0.31 %、–0.60 %、1.2 %、–0.84 %、–0.08 %;(3) 2018年西安市热环境状况整体趋于良好,常温区占绝对优势,但局部地区热环境表现为小幅加剧的趋势.因此,建议西安城市规划建设中热环境规划作为一项重要内容予以考虑.
Abstract:
A CA-Markov model was developed for urban heat environmental simulation. As a case study of Xi’an?s, land surface temperature (LST) were retried by Single-Window algorithm in 2000 and 2006. Based on the Urban Heat environment pattern of Xi’an and by using the CA-Markov model, this paper simulated Xi’an?s heat environment pattern in 2018. The results showed that:①the CA-Markov model has a better simulation accuracy, which be used for the simul ation of the thermal environment trend.②The area size of different UHI types in 2018 from high to low were normal temperature zone>green zone>heat island zone>strong heat island zone> strong green zone, with the respective ratio of different UHI types area being 70.2 %、13.06 %、12.01 %、3.67 %、1.06 %;the changes radio of the different UHI types from 2006 to 2018 being 0.31 %、?0.60 %、1.2 %、?0.84 %、?0.08 %.③The future thermal environment of Xi?an tends to be better and the normal temperature area is dominated, but it may have further deterioration trend locally . Therefore, the proposal in urban planning and construction of the thermal environment planning for the resident should be considered as an important component

参考文献/References:

[1] 冯晓刚, 石辉. 西安城市热环境格局的动态演变[J]. 生态学杂志,2011,31(11): 2821-2925.

FENG Xiaogang, SHI Hui. Dynamic changes of urban heat environment pattern in Xi?an of Northwest China [J]. Chinese Journal of Ecology, 2011,31(11):2821-2925.

[2] HOWARD L. Climate of London deduced from meteorological observation [J]. Harvey and Darton,1833, 1(3): 1-24.

[3] 陈志, 俞炳丰, 胡汪洋, 等. 城市热岛效应的灰色评价与预测[J]. 西安交通大学学报, 2004,38(9): 985-988.

CHEN Zhi, YU Bingfeng, HU Wangyang, et al. Grey assessment and prediction of the urban heat island effect in city [J]. Journal of Xi’an JiaoTong University, 2004 ,38(9): 985-988.

[4] 韦海东, 赵有益, 陈英. 兰州市城市热岛效应评价与灰色预测[J]. 中国沙漠, 2009, 29(3):571-576.

WEI Haidong, ZHAO Youyi, CHEN Ying. Grey assessment and prediction of the urban heat island effect in Lanzhou city [J]. Journal of Desert Research, 2009, 29(3):571-576.

[5] 杨梅学, 陈长和. 复杂地形上城市热岛的数值模拟[J]. 兰州大学学报(自然科学版), 1998, 34(3):117-124.

YANG Xuemei, CHEN Changhe. Numerical simulation of the urban heat island on complex terrain [J]. Journal of Lan zhou University (Natural Sciences), 1998, 34(3):117- 124.

[6] ZEHNDER Joseph A. Simple modifications to improve fifth-generation pennsylvania state university-national center for atmospheric research mesoscale model performance for the phoenix, Arizona, Metropolitan Area [J]. Journal of Applied Meteorology, 2002 ,41: 971.

[7] 杨玉华, 徐祥德, 翁永辉. 北京城市边界层热岛的日变化周期模拟[J]. 应用气象学报, 2003, 14(1):61-68.

YANG Yuhua, XU Xiangde, WENG Yonghui. Simulation of daily cycle of boundary layer heat island in Beijing [J]. Journal of Applied Meteorological Science, 2003, 14(1): 61-68.

[8] TONG Hua, ANDREW W, SANG Jianguo, et al. Numerical simulation of the urban boundary-layer over the complex terrain of Hong Kong[J]. Atmospheric Environment, 2005(39):3549.

[9] 李鹍. 基于遥感与CFD仿真的城市热环境研究—以武汉市夏季为例[D]. 武汉: 华中科技大学, 2008.

LI Kun.Study on the thermal environment of wuhan city based on the remote sensing and CFD technology [D], Wuhan: Huazhong Universit y of Science and Technology,2008.

[10] 王翠云. 基于遥感和CFD技术的城市热环境分析与模拟[D]. 兰州: 兰州大学, 2008.

WANG Cuiyun. The urban thermal environment analysis and simulation based on the remote sensing and CFD technology [D]. Lanzhou: Lanzhou University, 2008.

[11] 西安市统计局. 西安统计年鉴2012[M]. 北京:中国统计出版社.2012

Xi?an Statistics Bureau. Xi?an statistical yearbook 2012 [M]. Beijing: China Statistics Press, 2012.

[12] 覃志豪, ZHANG Minghua, KARNIELI Aronon, 等. 用陆地卫星TM6数据演算地表温度的单窗算法[J]. 地理学报, 2001,56(4): 456-466.

QIN Zhihao, ZHANG Minghua, KARNIELI Aronon, et al. Mono-window algorithm for retrieving land surface temperature from Landsat TM6 data [J]. Acta Geographic Sinica, 2001,56(4):456-466.

[13] 覃志豪, 李文娟, 徐斌, 等. 陆地卫星TM6波段范围内地表比辐射率的估计[J]. 国土资源遥感, 2004, 61(3):8-32.

QIN Zhihao, LI Wenjuan, XU Bin, et al. The estimation of land surface emissivity for Landsat TM6 [J]. Remote Sensing for Land & Resources, 2004, 61(3):8-32.

[14] 冯晓刚, 杨鑫, 撒利伟. 不同热岛类型的划分方法适用性研究[J]. 测绘与空间地理信息, 2012, 35(12):41-43.

FENG Xiaogang, YANG Xin, SA Liwei. Applicability research on different types of heat island division [J], Geomatics & Spatial Information Technology, 2012, 35(12):41-43.

[15] 周成虎, 孙战利, 谢一春. 地理元胞自动机研究[M]. 北京:科学出版社, 1999.

ZHOU Chenhu, SUN Zhanli, XIE Yichun. Research on the geographical cellular automata [M]. Beijing: Science Press ,1999.

[16] 熊利亚, 常斌, 周相广. 基于地理元胞自动机的土地利用变化研究[J]. 资源科学,2005, 27(4): 38-43.

XiONG Liya, CHANG Bin, ZHOU Xiangguang. A GeoCA-based study on land use change [J]. Resources Science, 2005, 27(4):38-43.

[17] 张显峰, 崔伟宏. 集成GIS和细胞自动机模型进行地理时空过程模拟与预测的新方法[J]. 测绘学报, 2001,30(2):148-155.

ZHANG Xianfeng, CUI Weihong. Integrating GIS with cellular automaton model establish a new approach for spatio-temporal process simulation and Prediction[J]. Acta Geodaetica et Cartographica Sinica, 2001,30(2): 148-155.

[18] 胡希军, 胡伏湘, 何平, 等. 基于马尔可夫链的城市景观结构演化模拟及预测[J]. 武汉大学学报信息科学版, 2009,34(10):1159-1162.

HU Xijun, HU Fuxian, HE Ping, et al. Simulation and prediction of urban landscape structure evolution [J]. Geometrics and Information Science of Wuhan University. 2009, 34(10):1159-1162.

备注/Memo

备注/Memo:
收稿日期:2014-12-11 修改稿日期:2016-08-25
项目基金:国家自然科学基金资助项目(51608419);陕西省自然科学基金资助项目(2013JQ5011);陕西省教育厅专项基金资助项目(16JK1437)
作者简介:冯晓刚(1979),男,博士,讲师,主要从事环境遥感与全息化古遗址保护的研究.E-mail: fendao_ren@163.com
更新日期/Last Update: 2016-11-24