SPATIOTEMPORAL ANALYSIS OF LAND USE AND LAND COVER USING REMOTE SENSING

ABSTRACT Land use and land cover (LULC) changes, essential to understanding environmental dynamics under human influence, are significantly intensified by the agricultural sector. This study aims to characterize and analyze spatiotemporal changes in an area primarily influenced by agricultural activities, using geoprocessing and remote sensing. The methodology involved acquiring satellite images from the wet and dry seasons of 1990, 2000, 2010, 2020, and 2023, then delineating and analyzing LULC classes. Among the analyzed periods, the most significant change was the shift from temporary crops to exposed soil, attributed to the fallow period. In contrast, forest areas, buildings, pastures, lagoons, transmission lines, motorways, and access roads underwent only minor alterations. Since 1990, pastures, forest cover, and temporary crops have been the most prevalent classes, totaling 735, 686, and 533 hectares, respectively, during the 2023 rainy season. In conclusion, the methods used here can be adapted to any region, and the resulting products provide essential tools for managers to devise strategies that enhance agricultural and environmental management.

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Publication Details

Journal
Engenharia Agrícola
Published
2025-01-01
DOI
https://doi.org/10.1590/1809-4430-eng.agric.v45nespe120240180/2025
Citations
1
Primary Topic
Remote Sensing and Land Use
Type
article
Field-Weighted Citation Impact
1.30

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article

SPATIOTEMPORAL ANALYSIS OF LAND USE AND LAND COVER USING REMOTE SENSING

Ana Cláudia Pereira Carvalho, Fabrício Rossi, Tamara Maria Gomes, Ana Cristina Carvalho
1 citations
Engenharia Agrícola
Remote Sensing and Land Use
1.30
article

SPATIOTEMPORAL ANALYSIS OF LAND USE AND LAND COVER USING REMOTE SENSING

Ana Cláudia Pereira Carvalho, Fabrício Rossi, Tamara Maria Gomes, Ana Cristina Carvalho
article en
1 citations

Abstract

ABSTRACT Land use and land cover (LULC) changes, essential to understanding environmental dynamics under human influence, are significantly intensified by the agricultural sector. This study aims to characterize and analyze spatiotemporal changes in an area primarily influenced by agricultural activities, using geoprocessing and remote sensing. The methodology involved acquiring satellite images from the wet and dry seasons of 1990, 2000, 2010, 2020, and 2023, then delineating and analyzing LULC classes. Among the analyzed periods, the most significant change was the shift from temporary crops to exposed soil, attributed to the fallow period. In contrast, forest areas, buildings, pastures, lagoons, transmission lines, motorways, and access roads underwent only minor alterations. Since 1990, pastures, forest cover, and temporary crops have been the most prevalent classes, totaling 735, 686, and 533 hectares, respectively, during the 2023 rainy season. In conclusion, the methods used here can be adapted to any region, and the resulting products provide essential tools for managers to devise strategies that enhance agricultural and environmental management.

Engenharia AgrícolaVol. 45(spe1)
Universidade de São Paulo (BR)
Universidade de São Paulo
Openalex Percentile: Top 24%
Remote Sensing and Land Use
1.30
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SPATIOTEMPORAL ANALYSIS OF LAND USE AND LAND COVER USING REMOTE SENSING — Ana Cláudia Pereira Carvalho, Fabrício Rossi, et al. · Engenharia Agrícola (2025) | TGRS Research Map | TGRS