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Terrestrial surface temperature through orbital data of the TIRS/Landsat-8 sensor: A case study of the neighborhood Cidade Operária and surroundings
Author(s) -
Isabela Cristina de Souza Penha,
Ítalo Belo Pereira,
Fabrício Sousa da Silva
Publication year - 2020
Publication title -
ciência e natura
Language(s) - English
Resource type - Journals
eISSN - 2179-460X
pISSN - 0100-8307
DOI - 10.5902/2179460x41211
Subject(s) - vegetation (pathology) , remote sensing , land cover , environmental science , cover (algebra) , field (mathematics) , vegetation cover , thermal infrared , thermal , land use , built up area , urban area , meteorology , geography , physical geography , infrared , physics , civil engineering , mathematics , medicine , mechanical engineering , optics , pathology , pure mathematics , engineering , economy , economics
The study of urban climate is an area of knowledge inherent to climatology that benefits from remote sensing, since it is possible to map the thermal behavior of the terrestrial surface through the thermal bands. This study aimed to identify and analyze the behavior of the Superficial Superficial Terrestrial (TST), in the neighborhood of the Operational City and in the surroundings. To obtain the proposals, the following materials and procedures were required: Operational Land Imager (OLI) and Thermal Infrared Sensor (TIRS) scenes from 07/2018, related to the infrared, red, green and thermal bands; Field recognition with photographic record; Extraction of thermal values and Supervised classification. Through field incursion, reduce the presence of two representative classes of local use and coverage: Vegetation and Urban Area. The maximum and minimum TST values were 19.7 ° c and 27.5 ° c, so in the southeastern neighborhood of the Working City, check to see if there is an extension of the area with higher values, including if you understand the neighbors Janaína and Jardim América. The lowest TST values are related to vegetation cover or thin cloud cover when in densely populated areas, while the highest values are directly related to urban density.

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