Utiliza??o de imagens ALOS/PALSAR no mapeamento digital de atributos f?sicos dos solos

• Autor(a) principal: Bernini, Thiago Andrade
• Data de Publicação: 2016
• Tipo de documento: Tese
• Idioma: por
• Título da fonte: Biblioteca Digital de Teses e Dissertações da UFRRJ
• Texto Completo: https://tede.ufrrj.br/jspui/handle/jspui/2317
• topic: Microwave; Botucatu sandstone formation; Micro-ondas; Forma??o Botucatu; Random Forest; Geoci?ncias

The survey and analysis of the spatial distribution of soil attributes through geostatistics tools are essential for agricultural land use according to soil capability. The images of synthetic aperture radar (SAR) have great potential for soil moisture estimation and, thus, these sensors can assist in mapping the physical-hydric and physical properties of soils. The overall objective of this study was to evaluate the potential use of radar images (microwave) ALOS/PALSAR on the identification of soils in an area of the Botucatu formation, dominated by sandy and medium texture soils in the municipality of Mineiros, Goi?s State, Brazil. The area has approximately 946 hectares, with the relief of the region ranging from plain to low undulating hills and the geology of the area is composed basically by sandstones of the Botucatu formation. In the present study there were sampled 84 points for calibration and 25 points for validation, collected in the depths of 0-20 cm and 60-80 cm. The soil samples were analyzed for the determination of sand, silt, clay, field capacity (CC), permanent wilting point (PMP) and total water available (AD). For the development of the work were acquired ALOS/PALSAR radar images of five dates and different polarizations, totaling 14 images, which were processed for the geographic and radiometric corrections, using a DEM. Were also generated covariates of terrain attributes: high (ELEV), slope (DECLIV), relative position of the slope (PR-DECL), vertical distance of the drainage channel (DVCD), ls factor (FACTOR-LS) and Euclidean distance (D-EUCL). Prediction of soil attributes was performed using Random Forest methods (RF) and Random Forest Kriging (RFK), having as predictive covariates the radar imaging and terrain attributes. Image processing of the ALOS/PALSAR radar images enabled the geographical and radiometric corrections, transforming the data into backscatter coefficient (??) in units of dB, corrected by digital elevation model (MDE). The acquired images represented broad range of ?? between the different dates. The soils of the study area are predominantly sandy, with most of the sampled points classified as Neossolos Quartzar?nicos (Entisols), followed by Latossolos (Oxisols). The RF models employed for prediction of physical-hydric and physical attributes of soils provided an analysis of the contribution of these covariates in the predictive models. The landscape attributes that caused the largest impact in the prediction of the studied attributes are related to the altitude. The images of 5/3/2009 (HH1, VV1, HV1 and VH1) and 9/26/2010 (HH3 and HV3), obtained in drier periods, had best correlations with the soil attributes. The analysis of the semivariograms of the RF prediction models residues demonstrated greater spatial dependence in the 60 to 80 cm layer. The Kriging approach coupled with RF model contributed to the improvement of the prediction of sand, clay, CC and PMP. Using ALOS/PALSAR radar images and terrain attributes as covariates in RFK models showed potential to estimate the physical (sand and clay) and physical-hydric (CC and PMP) attributes, which can assist in mapping of soils associated with the Botucatu formation parent materials.