Biophysical factors of remote sensing approach in urban green analysis
Greenery in an urban environment is an important consideration when studying temperature, and such enquiry can benefit human health. The purpose of this paper is to investigate how ambient temperature in urban areas is affected by forests and parks. The focus is on biophysical parameters related to...
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iium-452512015-10-21T06:41:42Z http://irep.iium.edu.my/45251/ Biophysical factors of remote sensing approach in urban green analysis Ibrahim, Illyani Abu Samah, Azizan Fauzi, Rosmadi G Geography (General) T Technology (General) Greenery in an urban environment is an important consideration when studying temperature, and such enquiry can benefit human health. The purpose of this paper is to investigate how ambient temperature in urban areas is affected by forests and parks. The focus is on biophysical parameters related to these green areas, such as impervious surface percentages, albedo, areal coverage, elevation, and leaf area index (LAI). Geographic information systems and remote sensing were used to quantify green spaces using a pixel-based method. It was found that coverage area has little correlation with temperature. Factor analysis was used to determine the minimum number of independent factors, which explained 63% of the variance of that temperature. Only elevation, LAI and albedo were significant biophysical factors. Guidelines for greenery programmes should include these significant data-sets to understand the influence of green areas on heat reduction. Taylor & Francis 2014 Article PeerReviewed application/pdf en http://irep.iium.edu.my/45251/1/journal_geocarto_illyani.pdf Ibrahim, Illyani and Abu Samah, Azizan and Fauzi, Rosmadi (2014) Biophysical factors of remote sensing approach in urban green analysis. Geocarto International, 29 (7). pp. 1-12. http://www.tandfonline.com/doi/abs/10.1080/10106049.2013.859306 10.1080/10106049.2013.859306 |
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English |
topic |
G Geography (General) T Technology (General) |
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G Geography (General) T Technology (General) Ibrahim, Illyani Abu Samah, Azizan Fauzi, Rosmadi Biophysical factors of remote sensing approach in urban green analysis |
description |
Greenery in an urban environment is an important consideration when studying temperature, and such enquiry can benefit human health. The purpose of this paper is to investigate how ambient temperature in urban areas is affected by forests and parks. The focus is on biophysical parameters related to these green areas, such as impervious surface percentages, albedo, areal coverage, elevation, and leaf area index (LAI). Geographic information systems and remote sensing were used to quantify green spaces using a pixel-based method. It was found that coverage area has little correlation with temperature. Factor analysis was used to determine the minimum number of independent factors, which explained 63% of the variance of that temperature. Only elevation, LAI and albedo were significant biophysical factors. Guidelines for greenery programmes should include these significant data-sets to understand the influence of green areas on heat reduction. |
format |
Article |
author |
Ibrahim, Illyani Abu Samah, Azizan Fauzi, Rosmadi |
author_facet |
Ibrahim, Illyani Abu Samah, Azizan Fauzi, Rosmadi |
author_sort |
Ibrahim, Illyani |
title |
Biophysical factors of remote sensing approach in urban green analysis |
title_short |
Biophysical factors of remote sensing approach in urban green analysis |
title_full |
Biophysical factors of remote sensing approach in urban green analysis |
title_fullStr |
Biophysical factors of remote sensing approach in urban green analysis |
title_full_unstemmed |
Biophysical factors of remote sensing approach in urban green analysis |
title_sort |
biophysical factors of remote sensing approach in urban green analysis |
publisher |
Taylor & Francis |
publishDate |
2014 |
url |
http://irep.iium.edu.my/45251/ http://irep.iium.edu.my/45251/ http://irep.iium.edu.my/45251/ http://irep.iium.edu.my/45251/1/journal_geocarto_illyani.pdf |
first_indexed |
2023-09-18T21:04:25Z |
last_indexed |
2023-09-18T21:04:25Z |
_version_ |
1777410837122646016 |