TY - JOUR
T1 - Analysis of a landscape intensely modified by agriculture in the tietê-jacaré watershed, Brazil.
AU - Trevisan, Diego Peruchi
AU - da Conceição Bispo, Polyanna
AU - Gou, Yaqing
AU - de Souza, Bianca Fogaça
AU - Liesenberg, Veraldo
AU - Harris, Angela
AU - Balzter, Heiko
AU - Moschini, Luiz Eduardo
N1 - Publisher Copyright:
© 2021 by the authors.
PY - 2021/8/19
Y1 - 2021/8/19
N2 - 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.
AB - 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.
KW - Environmental planning
KW - Land cover
KW - Land use
KW - Landscape analysis
KW - Watershed management
U2 - 10.3390/su13169304
DO - 10.3390/su13169304
M3 - Article
AN - SCOPUS:85113591691
VL - 13
JO - Sustainability
JF - Sustainability
SN - 2071-1050
IS - 16
M1 - 9304
ER -
