The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume XLVIII-3-2024
https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-437-2024
https://doi.org/10.5194/isprs-archives-XLVIII-3-2024-437-2024
07 Nov 2024
 | 07 Nov 2024

Assessment of Urban Heat Islands in an Eastern Amazonian city

Lucas Lima Raiol, Yuri Antonio da Silva Rocha, Dayla Carolina Rodrigues Santos, Aline Maria Meiguins de Lima, and Andrés Velastegui-Montoya

Keywords: Land Surface Temperature, Urban Heat Island, Amazon, Google Earth Engine, Moran Index

Abstract. The increase in heat islands in large cities, especially in tropical areas, has been a significant problem, as the rise in temperature can cause health issues for people. Therefore, this research aimed to analyze changes in land surface temperature (LST) and urban heat islands (UHI) in 1986 and 2023. The methodological procedures were carried out in four steps: I) Calculation of LST and UHI using the Landsat collection; II) Zonal statistics of the mean, the median, the minimum, maximum, and standard deviation of LST and UHI in each neighbourhood; III) Kruskal-Wallis Test applied to the average LST between 1986 and 2023; and IV) Assessment of the spatial autocorrelation of neighbourhoods using Bivariate Global and Local Moran’s I Index between LST and UHI. The results showed that in 2023, there was an increase in heat islands in central city neighbourhoods compared to 1986, as demonstrated by the Kruskal-Wallis test, which showed significant differences in LST. The global Moran’s I Index presented a value of 0.642, indicating a robust spatial autocorrelation in local studies. The neighbourhoods that showed high correlations were Campina, Cidade Velha, Cremação, Condor, Fátima, Jurunas, Nazaré, Pedreira, Reduto, São Braz, and Umarizal. The neighbourhoods that showed low correlations were Águas Lindas, Aurá, Curió-Utinga, Guanabara, and Parque Guajará. These results are directly linked to the intensification of urbanization and low vegetation cover, especially in central areas of the city, which showed a high correlation. These findings can aid decision-makers and support urban planning, focusing on neighbourhoods with higher average temperatures.