Remote sensing applied to biophysical parameters and land cover to identify urban heat islands in Recife (PE), Brazil

Haylla Rebeka de Albuquerque Lins Leonardo; Débora Natália Oliveira de Almeida; Alessandro Rodrigues de Amorim; Anderson Luiz Ribeiro de Paiva; Leidjane Maria Maciel de Oliveira; Sylvana Melo dos Santos

doi:10.5327/Z2176-94782107

Authors

Haylla Rebeka de Albuquerque Lins Leonardo Federal University of Pernambuco (UFPE) - Brazil https://orcid.org/0000-0001-6404-3366
Debora Natália Oliveira de Almeida Federal University of Pernambuco (UFPE) - Brazil https://orcid.org/0000-0001-6000-6138
Alessandro Rodrigues de Amorim Federal University of Pernambuco (UFPE) - Brazil https://orcid.org/0009-0001-2839-8036
Anderson Luiz Ribeiro de Paiva Federal University of Pernambuco (UFPE) - Brazil https://orcid.org/0000-0003-3475-1454
Leidjane Maria Maciel de Oliveira Federal University of Pernambuco (UFPE) - Brazil https://orcid.org/0000-0003-1251-6998
Sylvana Melo dos Santos Federal University of Pernambuco (UFPE) - Brazil https://orcid.org/0000-0003-3106-5301

DOI:

https://doi.org/10.5327/Z2176-94782107

Keywords:

Built-Up Index; biophysical indexes; Google Earth Engine.

Abstract

Urban growth results in several changes, mainly related to demographic, social, economic, and environmental aspects, leading to a new connotation in the use and occupation of land. This new scenario impacts the local energy balance, creating what is called an “urban heat island”. This study aims to investigate the occurrence of urban heat islands in Recife city, the capital of Pernambuco, Brazil, based on the processing of biophysical parameters, the classification of land use and occupation, and surface temperature. The orbital images of the study region were obtained and processed using the Google Earth Engine cloud processing platform from 2013 to 2021. The results showed an increase in areas with greater urban density and a reduction in areas with vegetation. It was realized that in regions with greater urban density, the surface temperature observed was up to 5.20°C higher than in the area with vegetation.

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