6, soil properties prediction with neural network...
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SOIL PROPERTIES PREDICTION WITH NEURAL NETWORK AND HYPERSPECTRAL DATA
Yuri A. Gelsleichter1; Lúcia Helena C. dos Anjos2; Mauro A. H. Antunes3
Paula Debiasi4; Helena S. K. Pinheiro5; Gabriela Valente6; Elias M. Costa7
Robson A. T. Marcondes8; Isadora F. Bolpato9
Federal Rural University of Rio de Janeiro; PPGCTIA, Soils Department and Engineer Department{yuriplanta1, lanjosrural2, homemantunes3}@gmail.com, [email protected], {lenask5, gabivalente.ufrrj6, eliasmccosta7, robson.marcondees8}@gmail.com, [email protected].
IntroductionRecent technologies are providing faster and less expressive methods for assessment of soil properties. Hyperspectral and soil properties data correlation are some of them (Gomez et al., 2008; Lagacherie et al., 2010; Demmattê et al., 2017).
ReferencesBarreto C. G. et al. Plano de manejo do Parque Nacional do Itatiaia. Encarte 3. Análise da Unidade de Conservação. Brasília, DF: 2013Demattê, J. A. M. et al. (2017). Chemometric soil analysis on the determination of specific bands for the detection of magnesium and potassium by spectroscopy. Geoderma. https://doi.org/10.1016/j.geoderma.2016.11.013Gomez, C. et al. (2008). Soil organic carbon prediction by hyperspectral remote sensing and field vis-NIR spectroscopy: An Australian case study. Geoderma, 146(3–4), 403–411. https://doi.org/10.1016/j.geoderma.2008.06.011Lagacherie, P. et al. (2010). The use of hyperspectral imagery for digital soil mapping in mediterranean areas The use of hyperspectral imagery for digital soil mapping in mediterranean areas. Digital Soil Mapping, 2(435). Retrieved from https://hal.archives-ouvertes.fr/hal-01137201/documentR Core Team (2016). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.
ObjectiveTo investigate soil properties using proximal and CHRIS Proba hyperspectral data.The study area is at the Itatiaia National Park, located in Rio de Janeiro State mountain region, with elevation above 1.500m. The study frames on the Histosols.
MethodsThe soil properties: organic matter content, texture, and cation exchange capacity, were correlated with proximal hyperspectral data and CHRIS Proba image, and applied for mapping those properties.Neural network technique will be applied using R Core Team (2016) software.
Itatiaia National Park location. Adapted from Barreto et al., (2013).http://www.esa.int