Using multispectral and hyperspectral bands to predict soil organic carbon in mata atlântica and amazon forest biomes

• Autor(a) principal: Padilha, Manuela Corrêa de Castro
• Data de Publicação: 2022
• Tipo de documento: Dissertação
• Idioma: eng
• Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
• Texto Completo: http://hdl.handle.net/10348/11570
• topic: Linear multiple regression (LMR); Soil organic carbon (SOC)

Soil organic carbon (SOC) is one of the regulatory properties of soil fertility, and consequently of the plantation production present there. Remote sensing can be used as a tool to provide, more quickly, information on how to manage the soil, given its spectral response to the physical, chemical, biological, and mineralogical attributes of the soil. The objective of this research was to evaluate, through the construction of a linear multiple regression model (LMR), the spectral response of high and medium resolution satellite bands, RapidEye and Sentinel-2, respectively, added to other physical attributes, such as relief and mineralogical slope such as clay in the municipality of Piracicaba, State of São Paulo, Brazil. With the application of this SOC prediction model, it is possible to obtain satisfactory results for better management of crops, and consequently for the reduction of greenhouse gas (GHG) emissions.