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Local Climate Zones Classification Applied to a Brazilian Amazon City

Bibliographic Data

ID13112930
AuthorsKely Prissila Saraiva Cordovil (0000-0002-0536-6090, Universidade Federal do Oeste do Pará, corresponding author), Yao Télesphore Brou (0000-0002-6273-7636), Osman Abdillahi Guedi (0000-0002-7897-0416, University of Djibouti), Lucas Vaz Peres (0000-0002-5612-5991, Universidade Federal do Oeste do Pará), Wilderclay Machado (0000-0002-0085-5397, Universidade Federal do Oeste do Pará), Avner Brasileiro dos Santos Gaspar (0000-0002-6012-852X, Universidade Federal do Oeste do Pará), Hassan Benchérif (0000-0003-1815-0667, Laboratoire de l'Atmosphère et des Cyclones), Lucas Raphael Mourão Gonçalves (0000-0003-4492-1947, Universidade Federal do Rio Grande), Luciana Gonçalves De Carvalho (0000-0001-7916-9092, Universidade Federal do Oeste do Pará)
Year2024
Volume8
Issue4
Pages253-253
Publication date2024-12-14
Open AccessYes
TypeARTICLE
VenueUrban Science (JOURNAL)
Journal identifiersISSN: 2413-8851 • E-ISSN: 2413-8851
PublisherMDPI AG (PUBLISHER • IT)
DOI10.3390/urbansci8040253
OpenAlexW4405447585
LanguageEN
References cited34

Urban elements influence atmospheric flow, turbulence, and the local microclimate, modifying the transport and composition of pollutants. However, although this focus on cities is crucial for managing climate change, our knowledge of most cities in the world is still quite limited. Thus, the classification of Local Climate Zones (LCZs) aims to increase the accuracy of urban studies and has already been applied in various regions of the world, including, more recently, in Brazil. This article aimed to apply the LCZ to Santarém, a city in the Brazilian Amazon. The methodological procedures included the digital mapping protocol of the World Urban Database and Access Portal Tools (WUDAPT-Level 0) and the supervised classification tool of the LCZ Generator application, resulting in 78 polygons representing 10.02% of the training area and 13.94% of the study area (urban zone). The research identified 7 of the 17 main LCZ classes in Santarém. The use of the NDVI was essential for assessing the vegetation in each class, highlighting variations in green areas and emphasizing that vegetation is reduced in built environments. This approach enhances the understanding of urban morphology and enables future research into urbanization and the climate in the Amazon

Amazon rainforest · Cartography · Environmental resource management · Geography · Meteorology · Microclimate · Physical geography · Remote sensing · Urban climate · Urban heat island · Urbanization · Vegetation (pathology · Environmental Science · Land Use and Ecosystem Services · Urban Green Space and Health · Urban Heat Island Mitigation · Ecology

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