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Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan
Alteration in Land Use/Cover (LULC) considered a major challenge over the recent decades, as it plays an important role in diminishing biodiversity, altering the macro and microclimate. Therefore, the current study was designed to examine the past 30 years (1987–2017) changes in LULC and Land Surfac...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269704/ https://www.ncbi.nlm.nih.gov/pubmed/35808454 http://dx.doi.org/10.3390/s22134965 |
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author | Rehman, Akhtar Qin, Jun Shafi, Sedra Khan, Muhammad Sadiq Ullah, Siddique Ahmad, Khalid Rehman, Nazir Ur Faheem, Muhammad |
author_facet | Rehman, Akhtar Qin, Jun Shafi, Sedra Khan, Muhammad Sadiq Ullah, Siddique Ahmad, Khalid Rehman, Nazir Ur Faheem, Muhammad |
author_sort | Rehman, Akhtar |
collection | PubMed |
description | Alteration in Land Use/Cover (LULC) considered a major challenge over the recent decades, as it plays an important role in diminishing biodiversity, altering the macro and microclimate. Therefore, the current study was designed to examine the past 30 years (1987–2017) changes in LULC and Land Surface Temperature (LST) and also simulated for next 30 years (2047). The LULC maps were developed based on maximum probability classification while the LST was retrieved from Landsat thermal bands and Radiative Transfer Equation (RTE) method for the respective years. Different approaches were used, such as Weighted Evidence (WE), Cellular Automata (CA) and regression prediction model for the year 2047. Resultantly, the LULC classification showed increasing trend in built-up and bare soil classes (13 km(2) and 89 km(2)), and the decreasing trend in vegetation class (−144 km(2)) in the study area. In the next 30 years, the built-up and bare soil classes would further rise with same speed (25 km(2) and 36.53 km(2)), and the vegetation class would further decline (−147 km(2)) until 2047. Similarly for LST, the temperature range for higher classes (27 -< 30 °C) increased by about 140 km(2) during 1987–2017, which would further enlarge (409 km(2)) until 2047. The lower LST range (15 °C to <21 °C) showed a decreasing trend (−54.94 km(2)) and would further decline to (−20 km(2)) until 2047 if it remained at the same speed. Prospective findings will be helpful for land use planners, climatologists and other scientists in reducing the increasing LST associated with LULC changes. |
format | Online Article Text |
id | pubmed-9269704 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-92697042022-07-09 Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan Rehman, Akhtar Qin, Jun Shafi, Sedra Khan, Muhammad Sadiq Ullah, Siddique Ahmad, Khalid Rehman, Nazir Ur Faheem, Muhammad Sensors (Basel) Article Alteration in Land Use/Cover (LULC) considered a major challenge over the recent decades, as it plays an important role in diminishing biodiversity, altering the macro and microclimate. Therefore, the current study was designed to examine the past 30 years (1987–2017) changes in LULC and Land Surface Temperature (LST) and also simulated for next 30 years (2047). The LULC maps were developed based on maximum probability classification while the LST was retrieved from Landsat thermal bands and Radiative Transfer Equation (RTE) method for the respective years. Different approaches were used, such as Weighted Evidence (WE), Cellular Automata (CA) and regression prediction model for the year 2047. Resultantly, the LULC classification showed increasing trend in built-up and bare soil classes (13 km(2) and 89 km(2)), and the decreasing trend in vegetation class (−144 km(2)) in the study area. In the next 30 years, the built-up and bare soil classes would further rise with same speed (25 km(2) and 36.53 km(2)), and the vegetation class would further decline (−147 km(2)) until 2047. Similarly for LST, the temperature range for higher classes (27 -< 30 °C) increased by about 140 km(2) during 1987–2017, which would further enlarge (409 km(2)) until 2047. The lower LST range (15 °C to <21 °C) showed a decreasing trend (−54.94 km(2)) and would further decline to (−20 km(2)) until 2047 if it remained at the same speed. Prospective findings will be helpful for land use planners, climatologists and other scientists in reducing the increasing LST associated with LULC changes. MDPI 2022-06-30 /pmc/articles/PMC9269704/ /pubmed/35808454 http://dx.doi.org/10.3390/s22134965 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Rehman, Akhtar Qin, Jun Shafi, Sedra Khan, Muhammad Sadiq Ullah, Siddique Ahmad, Khalid Rehman, Nazir Ur Faheem, Muhammad Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan |
title | Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan |
title_full | Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan |
title_fullStr | Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan |
title_full_unstemmed | Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan |
title_short | Modelling of Land Use/Cover and LST Variations by Using GIS and Remote Sensing: A Case Study of the Northern Pakhtunkhwa Mountainous Region, Pakistan |
title_sort | modelling of land use/cover and lst variations by using gis and remote sensing: a case study of the northern pakhtunkhwa mountainous region, pakistan |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9269704/ https://www.ncbi.nlm.nih.gov/pubmed/35808454 http://dx.doi.org/10.3390/s22134965 |
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