Modeling Spatio-Temporal Land Transformation and Its Associated Impacts on land Surface Temperature (LST)
Mumtaz, Faisal2,3; Tao, Yu2,3,4,5; de Leeuw, Gerrit6,9; Zhao, Limin2,3; Fan, Cheng3,6; Elnashar, Abdelrazek1,3,8; Bashir, Barjeece2,3; Wang, Gengke2,3,4; Li, LingLing2,3; Naeem, Shahid7
刊名REMOTE SENSING
2020-09-01
卷号12期号:18页码:23
关键词urbanization land use land cover (LULC) LULC transition CA-Markov model linear regression
DOI10.3390/rs12182987
通讯作者Tao, Yu(YuTao@Aircas.ac.cn)
英文摘要Land use land cover (LULC) of city regions is strongly affected by urbanization and affects the thermal environment of urban centers by influencing the surface temperature of core city areas and their surroundings. These issues are addressed in the current study, which focuses on two provincial capitals in Pakistan, i.e., Lahore and Peshawar. Using Landsat data, LULC is determined with the aim to (a) examine the spatio-temporal changes in LULC over a period of 20 years from 1998 to 2018 using a CA-Markov model, (b) predict the future scenarios of LULC changes for the years 2023 and 2028, and (c) study the evolution of different LULC categories and investigate its impacts on land surface temperature (LST). The results for Peshawar city indicate the significant expansion in vegetation and built-up area replacing barren land. The vegetation cover and urban area of Peshawar have increased by 25.6%, and 16.3% respectively. In contrast, Lahore city urban land has expanded by 11.2% while vegetation cover decreased by (22.6%). These transitions between LULC classes also affect the LST in the study areas. Transformation of vegetation cover and water surface into built-up areas or barren land results in the increase in the LST. In contrast, the transformation of urban areas and barren land into vegetation cover or water results in the decrease in LST. The different LULC evolutions in Lahore and Peshawar clearly indicate their effects on the thermal environment, with an increasing LST trend in Lahore and a decrease in Peshawar. This study provides a baseline reference to urban planners and policymakers for informed decisions.
资助项目project of Aerospace information research institute, Chinese Academy of Sciences. Evaluation on application technology of space earth integrated satellite[Y7K00100KJ]
WOS关键词USE/LAND-COVER CHANGE ; CELLULAR-AUTOMATA MODEL ; URBAN HEAT-ISLAND ; CLIMATE-CHANGE ; MARKOV-CHAIN ; LOGISTIC-REGRESSION ; METROPOLITAN-AREA ; SPATIAL DYNAMICS ; REGIONAL CLIMATE ; GROWTH
WOS研究方向Remote Sensing
语种英语
出版者MDPI
WOS记录号WOS:000580861000001
资助机构project of Aerospace information research institute, Chinese Academy of Sciences. Evaluation on application technology of space earth integrated satellite
内容类型期刊论文
源URL[http://ir.igsnrr.ac.cn/handle/311030/157073]  
专题中国科学院地理科学与资源研究所
通讯作者Tao, Yu
作者单位1.Chinese Acad Sci, Aerosp Informat Res Inst, State Key Lab Remote Sensing Sci, Beijing 100094, Peoples R China
2.Chinese Acad Sci, Aerosp Informat Res Inst, Beijing 100101, Peoples R China
3.Univ Chinese Acad Sci UCAS, Beijing 101408, Peoples R China
4.North China Inst Aerosp Engn, Sch Remote Sensing & Informat Engn, Langfang 065000, Peoples R China
5.Hebei Collaborat Innovat Ctr Aerosp Remote Sensin, Langfang 065000, Peoples R China
6.Chinese Acad Sci, Aerosp Informat Res Inst, State Environm Protect Key Lab Satellite Remote S, Beijing 100101, Peoples R China
7.Inst Geog Sci & Nat Resources Res IGSNRR, Beijing 100101, Peoples R China
8.Cairo Univ, Fac African Postgrad Studies, Dept Nat Resources, Giza 12613, Egypt
9.Royal Netherlands Meteorol Inst KNMI, R&D Satellite Observat, NL-3731 GA De Bilt, Netherlands
推荐引用方式
GB/T 7714
Mumtaz, Faisal,Tao, Yu,de Leeuw, Gerrit,et al. Modeling Spatio-Temporal Land Transformation and Its Associated Impacts on land Surface Temperature (LST)[J]. REMOTE SENSING,2020,12(18):23.
APA Mumtaz, Faisal.,Tao, Yu.,de Leeuw, Gerrit.,Zhao, Limin.,Fan, Cheng.,...&Arshad, Arfan.(2020).Modeling Spatio-Temporal Land Transformation and Its Associated Impacts on land Surface Temperature (LST).REMOTE SENSING,12(18),23.
MLA Mumtaz, Faisal,et al."Modeling Spatio-Temporal Land Transformation and Its Associated Impacts on land Surface Temperature (LST)".REMOTE SENSING 12.18(2020):23.
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