Developing an SDSS for optimal sustainable roof covering planning based on UHI variation at neighborhood scale.

N Mostofi, H Aghamohammadi Zanjirabad, A Vafaeinejad, M Ramezani, A Hemmasi

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Article in Environmental monitoring and assessment, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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5 authors.

N MostofiDepartment of Remote Sensing and Geographic Information System, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran.

H Aghamohammadi ZanjirabadDepartment of Remote Sensing and Geographic Information System, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran. aghamohammadi@srbiau.ac.ir.ORCID http://orcid.org/0000-0002-9497-6295

A VafaeinejadFaculty of Civil, Water and Environmental Engineering, Shahid Beheshti University , Tehran, Iran.

M RamezaniDepartment of Environmental Science, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran.

A HemmasiDepartment of Wood and Paper Engineering, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, Tehran, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nowadays, academics have paid special attention to global warming, because it has several issues such as urban heat island (UHI) related to the quality of life. For this purpose, a spatial decision support system (SDSS) has been developed to investigate the effect of parcels' roof covering type on surface heat island (SHI) values and its variation at the neighborhood scale in Tehran, Iran. This SDSS, as the innovation of the present research, consists of two main steps including estimating the UHI value in the study area and adopting the optimum set of parcels to change their roofs' cover with three types of vegetation, high-albedo material, and flagstone. The first step is accomplished by aggregating various indices related to land cover obtained from Landsat 8 images. The aggregation is done by linear regression method (LRM) with an RMSE and R

Indexed as

Hot TemperatureQuality of LifeCitiesEnvironmental MonitoringIranIslandsGenetic algorithmLandsat 8 imageryLinear regressionSDSSUHI

Identifiers

PMID34061262

DOI10.1007/s10661-021-09151-6

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