Analysis of a Landscape Intensely Modified by Agriculture in the Tietê–Jacaré Watershed, Brazil

Diego Peruchi Trevisan, Polyanna da Conceição Bispo, Yaqing Gou, Bianca Fogaça de Souza, Veraldo Liesenberg, Angela Harris, Heiko Balzter and Luiz Eduardo Moschini
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Diego Peruchi Trevisan: Department of Environmental Sciences, Federal University of São Carlos (UFSCar), Washington Luiz Road, São Carlos 13565-905, SP, Brazil
Polyanna da Conceição Bispo: Department of Geography, School of Environment, Education and Development, University of Manchester, Oxford Road, Manchester M13 9PL, UK
Yaqing Gou: Centre for Landscape and Climate Research, School of Geography, Geology and the Environment, University of Leicester, Leicester LE1 7RH, UK
Bianca Fogaça de Souza: Department of Environmental Sciences, Federal University of São Carlos (UFSCar), Washington Luiz Road, São Carlos 13565-905, SP, Brazil
Veraldo Liesenberg: Department of Forest Engineering, Santa Catarina State University (UDESC), 2090 Luiz de Camões Avenue, Lages 88520-000, SC, Brazil
Angela Harris: Department of Geography, School of Environment, Education and Development, University of Manchester, Oxford Road, Manchester M13 9PL, UK
Heiko Balzter: Centre for Landscape and Climate Research, School of Geography, Geology and the Environment, University of Leicester, Leicester LE1 7RH, UK
Luiz Eduardo Moschini: Department of Environmental Sciences, Federal University of São Carlos (UFSCar), Washington Luiz Road, São Carlos 13565-905, SP, Brazil

Sustainability, 2021, vol. 13, issue 16, 1-24

Abstract: Anthropogenic actions influence landscapes, and the resulting mosaic is a mix of natural and anthropogenic elements that vary in size, shape, and pattern. Considering this, our study aimed to analyse the land use and land cover changes in the Tietê–Jacaré watershed (São Paulo state, Brazil), using the random forest (RF) algorithm and Sentinel-2 satellite data from 2016 to 2018 to detect landscape changes. By overlapping the environmental data and the proposed model evaluation, it was possible to observe the landscape structure, produce information about the state of this region, and assess the environmental responses to anthropic impacts. The land use and land cover analysis identified eight classes: exposed soil, citriculture, pasture, silviculture, sugar cane, urban area, vegetation, and water. The RF classification for the three years reached high accuracy with a kappa index of 0.87 in 2016, 0.85 in 2017, and 0.85 in 2018. The model developed was essential for the temporal analysis since it allowed us to comprehend the driving forces that act in this landscape and contribute to the discussions about their impacts over time. The results showed a predominance of agricultural activities over the three years, with approximately 900.000 ha (76% of the area), mainly covered by sugarcane cultivation.

Keywords: watershed management; landscape analysis; environmental planning; land use; land cover (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2021
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