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2023 | OriginalPaper | Chapter

15. Case Study 7: Assessment, Mapping and Prediction of Urban Heat Island in Srinagar City Region

Authors : Manish Kumar, R. B. Singh, Anju Singh, Ram Pravesh, Syed Irtiza Majid, Akash Tiwari

Published in: Geographic Information Systems in Urban Planning and Management

Publisher: Springer Nature Singapore

Abstract

Urban Heat Island (UHI) refers to the manifestation of relatively higher surface and air temperatures in the urban centres with respect to the immediate surroundings where land use/land cover is generally green in nature (forest or agriculture). It is a local climate system in which the temperatures are observed to follow a slope in the direction radially outwards from the city centre. In this study, UHI of the Srinagar City Region has been mapped along the time series from 1991 to 2020 and the scenario has been predicted also for 2030. Land Surface Temperature (LST), retrieved from the thermal bands of Landsat 5 images for 1991, 1999 and 2010, and from Landsat 8 images of 2020 using Mono-window (MW) Algorithm was used to understand the temperature trend and the evolution of UHI zones in the Srinagar City region. The results show that the mean surface temperature of the study area has shifted from 16.04 ℃ in 1991 to 26.21 ℃ in 2020. In the same time period, the area of UHI zone has grown at a rate of 2.85 km2 per year from 1991 to 2020. It expanded from 13.57 km2 (1.82% of total area) in 1991 to 96.18 km2 (12.90% of total area) in 2020. According to Multi-layer Perceptron Neural Network (MLPNN), which was used to predict the mean surface temperature, Srinagar City Region will experience 27.21 ℃ in 2030. This study also predicted the potential scenario of UHI zones for 2030 using Cellular Automata-Markov Chain Integrated Model (CA-Markov). It forecasts that in 2030, with an expansion rate of 12.57 km2 per year, UHI zone of Srinagar City Region will expand to 221.94 km2 covering 29.77% of the total area, if the present scenarios continue.

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Literature
go back to reference Arsanjani JJ, Helbich M, Kainz W, Boloorani AD (2013) Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. Int J Appl Earth Obs Geoinf 21:265–275 Arsanjani JJ, Helbich M, Kainz W, Boloorani AD (2013) Integration of logistic regression, Markov chain and cellular automata models to simulate urban expansion. Int J Appl Earth Obs Geoinf 21:265–275
go back to reference Coppedge BR, Engle DM, Fuhlendorf SD (2007) Markov models of land cover dynamics in a southern Great Plains grassland region. Landscape Ecol 22(9):1383–1393 CrossRef Coppedge BR, Engle DM, Fuhlendorf SD (2007) Markov models of land cover dynamics in a southern Great Plains grassland region. Landscape Ecol 22(9):1383–1393 CrossRef
go back to reference de Faria Peres L, de Lucena AJ, Rotunno Filho OC, de Almeida Franca JR (2018) The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data. Int J Appl Earth Obs Geoinf 64:104–116 de Faria Peres L, de Lucena AJ, Rotunno Filho OC, de Almeida Franca JR (2018) The urban heat island in Rio de Janeiro, Brazil, in the last 30 years using remote sensing data. Int J Appl Earth Obs Geoinf 64:104–116
go back to reference Iacono M, Levinson D, El-Geneidy A, Wasfi R (2015) A Markov chain model of land use change. TEMA J Land Use Mobil Environ 8(3):263–276 Iacono M, Levinson D, El-Geneidy A, Wasfi R (2015) A Markov chain model of land use change. TEMA J Land Use Mobil Environ 8(3):263–276
go back to reference Imhoff ML, Zhang P, Wolfe RE, Bounoua L (2010) Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sens Environ 114(3):504–513 CrossRef Imhoff ML, Zhang P, Wolfe RE, Bounoua L (2010) Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sens Environ 114(3):504–513 CrossRef
go back to reference Mohan M, Kikegawa Y, Gurjar BR, Bhati S, Kandya A, Ogawa K (2012) Urban heat island assessment for a tropical urban airshed in India Mohan M, Kikegawa Y, Gurjar BR, Bhati S, Kandya A, Ogawa K (2012) Urban heat island assessment for a tropical urban airshed in India
go back to reference Nichol JE, To PH (2012) Temporal characteristics of thermal satellite images for urban heat stress and heat island mapping. ISPRS J Photogramm Remote Sens 74:153–162 CrossRef Nichol JE, To PH (2012) Temporal characteristics of thermal satellite images for urban heat stress and heat island mapping. ISPRS J Photogramm Remote Sens 74:153–162 CrossRef
go back to reference Rocha J, Ferreira JC, Simoes J, Tenedório JA (2007) Modelling coastal and land use evolution patterns through neural network and cellular automata integration. J Coastal Res 827–831 Rocha J, Ferreira JC, Simoes J, Tenedório JA (2007) Modelling coastal and land use evolution patterns through neural network and cellular automata integration. J Coastal Res 827–831
go back to reference Rongali G, Keshari AK, Gosain AK, Khosa R (2018) A mono-window algorithm for land surface temperature estimation from Landsat 8 thermal infrared sensor data: a case study of the Beas River Basin, India. Pertanika J Sci Technol 26(2):829–840 Rongali G, Keshari AK, Gosain AK, Khosa R (2018) A mono-window algorithm for land surface temperature estimation from Landsat 8 thermal infrared sensor data: a case study of the Beas River Basin, India. Pertanika J Sci Technol 26(2):829–840
go back to reference Sang L, Zhang C, Yang J, Zhu D, Yun W (2011) Simulation of land use spatial pattern of towns and villages based on CA–Markov model. Math Comput Model 54(3–4):938–943 CrossRef Sang L, Zhang C, Yang J, Zhu D, Yun W (2011) Simulation of land use spatial pattern of towns and villages based on CA–Markov model. Math Comput Model 54(3–4):938–943 CrossRef
go back to reference Surabuddin Mondal M, Sharma N, Kappas M, Garg PK (2013) Modeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques. Geocarto Int 28(7):632–656 CrossRef Surabuddin Mondal M, Sharma N, Kappas M, Garg PK (2013) Modeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques. Geocarto Int 28(7):632–656 CrossRef
Metadata
Title
Case Study 7: Assessment, Mapping and Prediction of Urban Heat Island in Srinagar City Region
Authors
Manish Kumar
R. B. Singh
Anju Singh
Ram Pravesh
Syed Irtiza Majid
Akash Tiwari
Copyright Year
2023
Publisher
Springer Nature Singapore
DOI
https://doi.org/10.1007/978-981-19-7855-5_15

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