Application of Spatial Modeling of Biophysical Variables in an Urbanized Area in the Amazon: The Case of the Metropolitan Area of Belém-Pará

Madson Tavares Silva,Carlos Antonio Costa Dos Santos,Bernardo Barbosa Da Silva,Eduardo Da Silva Margalho,Amanda Cartaxo De Souza,Edivaldo Afonso De Oliveira Serrão,Caroline De Sá Soares

doi:10.1590/0102-77863620063

Madson Tavares Silva, Carlos Antonio Costa Dos Santos + Show 5 more

Open Access

https://doi.org/10.1590/0102-77863620063

Copy DOI

Abstract

Abstract The type of land use and land cover plays a decisive role in land surface temperature (LST). As cities are composed of varied covers, including vegetation, built-up areas, buildings, roads and areas without vegetation, understanding LST patterns in complex urban spaces is becoming increasingly important. The present study investigated the relationship between LST and albedo, NDVI, NDWI, NDBI and NDBaI in the period between 1994 and 2017. Images from Thematic Mapper (TM) and Thermal Infrared Sensor (TIRS) onboard the Landsat 5 and 8 satellites, respectively, were used in the study. The images were processed, resampled (spatial resolution of 120 m) in the environment of the QGIS 3.0 software and, finally, centroids were extracted resulting in a total of 1252 points. A classical regression (CR) model was applied to the variables, followed by spatial autoregressive (SARM) and spatial error (SEM) models, and the results were compared using accuracy indices. The results showed that the highest correlation coefficient was found between albedo and NDBaI (r = 0.88). The relationship between albedo and LST (r = 0.7) was also positive and significant at р < 0.05. The global Moran's I index showed spatial dependence and non-stationarity of the LST (I = 0.44). The SEM presented the best accuracy metrics (AIC = 3307.15 and R2 = 0.65) for the metropolitan region of Belém, explaining considerably more variations in the relationship between explanatory factors and LST when compared to conventional CR models.

Highlights

In several places around the world, cities are the main areas for the development of human activities and interactions
Changes generated in the environment due to the expansion of urban areas represent the main indicator of increased air and surface temperatures, which form urban heat islands (UHI)
The correlation coefficients between land surface temperature (LST) and biophysical variables are shown as a dispersion matrix in Fig. 2 and the three images used in the present study were constructed from the average of the pixel values (1994, 2008 and 2017)

Summary

Introduction

In several places around the world, cities are the main areas for the development of human activities and interactions Such environments have faced extensive changes in land use and land cover (LULC) (Li et al, 2011; Silva et al, 2014; Silva et al, 2015; Silva et al, 2016; Silva et al, 2018; de Oliveira Serrão et al, 2020; Margalho et al, 2020) directly associated with population growth and economic development. UHI consist of an atmospheric phenomenon observed in urban environments, caused by anthropogenic action in the change and use of the soil Such geographical changes caused by man have as one of their consequences the increase in air and surface temperature (Guha et al, 2018; Li et al, 2018)

Methods

Discussion

Conclusion