Literature DB >> 31158687

Analysis and simulation of land cover changes and their impacts on land surface temperature in a lower Himalayan region.

Siddique Ullah1, Khalid Ahmad1, Raja Umer Sajjad1, Arshad Mehmood Abbasi1, Abdul Nazeer1, Adnan Ahmad Tahir2.   

Abstract

Rapid urbanization is changing the existing patterns of Land Use Land Cover (LULC) globally which is consequently increasing the Land Surface Temperature (LST) in many regions. Present study was focused on estimating the current and simulating the future LULC and LST trends in the alpine environment of lower Himalayan region of Pakistan. Past patterns of LULC and LST were identified through the Support Vector Machine (SVM) and multi-spectral Landsat satellite images during 1987-2017 data period. The Cellular automata (CA) model and Artificial Neural Network (ANN) were applied to simulate future (years 2032 and 2047) LULC and LST changes, respectively, using their past patterns. CA model was validated for the simulated and the estimated LULC for the year 2017 with an overall Kappa (K) value of 0.77 using validation modules in QGIS and IDRISI software. ANN method was validated by correlating the observed and simulated LST for the year 2017 with correlation coefficient (R) and Mean Square Error (MSE) values of 0.81 and 0.51, respectively. Results indicated a change in the LULC and LST for instance the built-up area was increased by 4.43% while agricultural area and bare soil were reduced by 2.74% and 4.42%, respectively, from 1987 to 2017. The analysis of LST for different LULC classes indicated that built-up area has highest temperature followed by barren, agriculture and vegetation surfaces. Simulation of future LULC and LST showed that the built-up area will be increased by 2.27% (in 2032) and 4.13% (in 2047) which led 42% (in 2032) and 60% (in 2047) of the study area as compared to 26% area (in 2017) to experience LST greater than 27 °C. A strong correlation between built-up area changes and LST was thus found signifying major challenge to urban planners mitigating the consequent of Urban Heat Island (UHI) phenomenon. It is suggested that future urban planning should focus on urban plantation to counter UHI phenomena in the region of lower Himalayas.
Copyright © 2019 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Artificial neural network; Cellular automata model; Land surface temperature; Land use land cover; Support vector machine; Urban heat island

Mesh:

Year:  2019        PMID: 31158687     DOI: 10.1016/j.jenvman.2019.05.063

Source DB:  PubMed          Journal:  J Environ Manage        ISSN: 0301-4797            Impact factor:   6.789


  3 in total

1.  A Review of Driving Factors, Scenarios, and Topics in Urban Land Change Models.

Authors:  Youjung Kim; Galen Newman; Burak Güneralp
Journal:  Land (Basel)       Date:  2020-07-27

2.  Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan.

Authors:  Akhtar Rehman; Jun Qin; Sedra Shafi; Muhammad Sadiq Khan; Siddique Ullah; Khalid Ahmad; Nazir Ur Rehman; Muhammad Faheem
Journal:  Sensors (Basel)       Date:  2022-06-30       Impact factor: 3.847

3.  Analysis of the Spatial and Temporal Evolution of Land Cover and Heat Island Effects in Six Districts of Chongqing's Main City.

Authors:  Qin Lang; Wenping Yu; Mingguo Ma; Jianguang Wen
Journal:  Sensors (Basel)       Date:  2019-11-28       Impact factor: 3.576

  3 in total

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