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Previous issue date: 2016-02-26 / CAPES / 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. / O levantamento e a an?lise da espacializa??o dos atributos do solo atrav?s de ferramentas de geoestat?stica s?o fundamentais para que cada hectare de terra seja cultivado segundo as suas reais aptid?es. As imagens de radar de abertura sint?tica (SAR) t?m um grande potencial para a estima??o de umidade do solo e, desta forma, estes sensores podem auxiliar no mapeamento de propriedades f?sicas e f?sico-h?dricas dos solos. O objetivo geral deste estudo foi avaliar o potencial de utiliza??o de imagens de radar (micro-ondas) ALOS/PALSAR na identifica??o de solos em uma ?rea da Forma??o Botucatu, dominada por solos de textura arenosa e m?dia no munic?pio de Mineiros - GO. A ?rea tem aproximadamente 946 ha, com o relevo da regi?o variando de plano a suave ondulado e geologia da ?rea ? composta basicamente, por Arenitos da Forma??o Botucatu. No presente estudo foram amostrados 84 pontos para calibra??o e 25 pontos para valida??o, coletados nas profundidades de 0-20 cm e 60-80 cm. As amostras de solo analisadas para a determina??o de areia, silte, argila, capacidade de campo (CC), ponto de murcha permanente (PMP) e ?gua total dispon?vel (AD). Para o desenvolvimento do trabalho foram adquiridas imagens de cinco datas e diferentes polariza??es, totalizando 14 imagens, que foram processadas para a corre??o geom?trica e corre??o radiom?trica, utilizando o MDE. Tamb?m foram gerados covari?veis dos atributos do terreno: eleva??o (ELEV), declividade (DECLIV), posi??o relativa da declividade (PR-DECL), dist?ncia vertical do canal de drenagem (DVCD), fator-ls (FATOR-LS) e dist?ncia euclidiana (D-EUCL). A predi??o dos atributos do solo foi realizada utilizando os m?todos Random Forest (RF) e Random Forest Krigagem (RFK), tendo como covari?veis preditoras as imagens de radar e os atributos do terreno. O processamento das imagens do radar ALOS/PALSAR possibilitou as corre??es geom?trica e radiom?trica, transformando os dados em unidades de coeficiente de retroespalhamento (??) corrigidos pelo modelo digital de eleva??o (MDE). As imagens adquiridas representaram de forma ampla as varia??es de ?? ocorridos em diferentes datas. Os solos da ?rea de estudo s?o predominantemente arenosos, com a maioria dos pontos amostrados classificados como NEOSSOLOS QUARTZAR?NICOS, seguidos dos LATOSSOLOS. Os modelos RF empregados para a predi??o dos atributos f?sicos e f?sico-h?dricos dos solos proporcionaram a an?lise da contribui??o das covari?veis preditoras. Os atributos do terreno que exerceram maior influ?ncia na predi??o dos atributos estudados est?o relacionados ? eleva??o. As imagens de 03/05/2009 (HH1, VV1, HV1 e VH1) e 26/09/2010 (HH3 e HV3), obtidas em per?odos mais secos, tiveram melhores correla??es com os atributos do solo. As an?lises dos semivariogramas dos res?duos da predi??o dos modelos RF demonstraram maior depend?ncia espacial na camada de 60 a 80 cm. A abordagem da Krigagem somada ao modelo RF contribu?ram para a melhoria da predi??o dos atributos areia, argila, CC e PMP. O uso de imagens de radar ALOS/PALSAR e atributos do terreno como covari?veis em modelos RFK mostrou potencial para estimar os atributos f?sicos (areia e argila) e f?sico-h?dricos (CC e PMP), que podem auxiliar no mapeamento de solos associados aos materiais de origem da Forma??o Botucatu.
| Identifer | oai:union.ndltd.org:IBICT/oai:localhost:jspui/2317 |
| Date | 26 February 2016 |
| Creators | BERNINI, Thiago Andrade |
| Contributors | Antunes, Mauro Antonio Homem, Chagas, Cesar da Silva, Chagas, Cesar da Silva, Sano, Edson Eyji, Pinheiro, Helena Saraiva Koenow, Anjos, L?cia Helena Cunha dos, Carvalho J?nior, Waldir de |
| Publisher | Universidade Federal Rural do Rio de Janeiro, Programa de P?s-Gradua??o em Ci?ncia, Tecnologia e Inova??o em Agropecu?ria, UFRRJ, Brasil, Pr?-Reitoria de Pesquisa e P?s-Gradua??o |
| Source Sets | IBICT Brazilian ETDs |
| Language | Portuguese |
| Detected Language | English |
| Type | info:eu-repo/semantics/publishedVersion, info:eu-repo/semantics/doctoralThesis |
| Format | application/pdf |
| Source | reponame:Biblioteca Digital de Teses e Dissertações da UFRRJ, instname:Universidade Federal Rural do Rio de Janeiro, instacron:UFRRJ |
| Rights | info:eu-repo/semantics/openAccess |
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