Abstract:Pedron (4) , Alexandre ten Caten (5) & Luis Fernando Chimelo Ruiz (6) RESUMO A espectroscopia de reflectância difusa (ERD) pode ser utilizada como alternativa para quantificação de atributos como granulometria e matéria orgânica do solo (MOS). Essa técnica pode ser opção para quantificar esses atributos em grande volume de amostras de solos, visto ser rápida, com menor custo e sem a geração de resíduos químicos. O objetivo deste estudo foi desenvolver modelos usando análise de regressão linear múltipla par… Show more
“…Using the partial least squares model (PLSR), of the five sample sets, three obtained good results for SOC in g kg -¹ (Regional and General), one for soil bulk density (Db) (Regional), and one for soil organic carbon stock (CS) (Aterrado Farm). Summers et al (2011), also using PLSR, obtained R² values of 0.57 for SOC at validation, and 0.68 for a percentage of SOC, with a sample set of 303 samples of various types of soil in Rio Grande do Sul (DOTTO et al, 2014). Such results are similar to those obtained in the present study (R²= 0.67), which used a regional set of 322 samples.…”
Current procedures for determining soil organic carbon (SOC) content are costly, time-consuming, and generate polluting chemical waste. Therefore, developing new protocols using aerial and orbital remote sensing and diffuse reflectance spectroscopy (DRS) for digitally mapping the stock of soil organic carbon (CS) is essential for promoting actions of research and monitoring SOC in Brazilian soils. Given this, three areas of commercial plots in the region of the Middle North of Mato Grosso were studied, where sampling was carried out for the determination of SOC in the layer from 0 to 30 cm, evaluated by the dry combustion method and estimated through DRS in the visible to near -infrared region - Vis-NIR-SWIR/350-2500 nm). To obtain the images by aerial remote sensing, the Carcará II® Unmanned Aerial Vehicle was used, with a MicaSense® multispectral camera (RGB + NIR + RedEdge) attached. The orbital sensors used were the Sentinel 2® and Planet® satellites. This study showed that soil carbon stock values could be predicted using different modeling approaches based on field and laboratory spectral measurements. Predictive models to estimate SOC can be established using remote and near sensing, thus allowing a better understanding of spatial patterns of SOC in crop fields.
“…Using the partial least squares model (PLSR), of the five sample sets, three obtained good results for SOC in g kg -¹ (Regional and General), one for soil bulk density (Db) (Regional), and one for soil organic carbon stock (CS) (Aterrado Farm). Summers et al (2011), also using PLSR, obtained R² values of 0.57 for SOC at validation, and 0.68 for a percentage of SOC, with a sample set of 303 samples of various types of soil in Rio Grande do Sul (DOTTO et al, 2014). Such results are similar to those obtained in the present study (R²= 0.67), which used a regional set of 322 samples.…”
Current procedures for determining soil organic carbon (SOC) content are costly, time-consuming, and generate polluting chemical waste. Therefore, developing new protocols using aerial and orbital remote sensing and diffuse reflectance spectroscopy (DRS) for digitally mapping the stock of soil organic carbon (CS) is essential for promoting actions of research and monitoring SOC in Brazilian soils. Given this, three areas of commercial plots in the region of the Middle North of Mato Grosso were studied, where sampling was carried out for the determination of SOC in the layer from 0 to 30 cm, evaluated by the dry combustion method and estimated through DRS in the visible to near -infrared region - Vis-NIR-SWIR/350-2500 nm). To obtain the images by aerial remote sensing, the Carcará II® Unmanned Aerial Vehicle was used, with a MicaSense® multispectral camera (RGB + NIR + RedEdge) attached. The orbital sensors used were the Sentinel 2® and Planet® satellites. This study showed that soil carbon stock values could be predicted using different modeling approaches based on field and laboratory spectral measurements. Predictive models to estimate SOC can be established using remote and near sensing, thus allowing a better understanding of spatial patterns of SOC in crop fields.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.