Spectral Characteristics Of Soybean During The Vegetative Cycle With Landsat 5/tm Images In The Western Paraná, Brazil [características Espectrais Da Soja Ao Longo Do Ciclo Vegetativo Com Imagens Landsat 5/tm Em área Agrícola No Oeste Do Paraná]

The objective of this study was to analyze changes in the spectral behavior of the soybean crop through spectral profiles of the vegetation indexes NDVI and GVI, expressed by different physical values such as apparent bi-directional reflectance factor (BRF), surface BRF, and normalized BRF derived from images of the Landsat 5/TM. A soybean area located in Cascavel, Paraná, was monitored by using five images of Landsat 5/TM during the 2004/2005 harvesting season. The images were submitted to radiometric transformation, atmospheric correction and normalization, determining physical values of apparent BRF, surface BRF and normalized BRF. NDVI and GVI images were generated in order to distinguish the soybean biomass spectral response. The treatments showed different results for apparent, surface and normalized BRF. Through the profiles of average NDVI and GVI, it was possible to monitor the entire soybean cycle, characterizing its development. It was also observed that the data from normalized BRF negatively affected the spectral curve of soybean crop, mainly, during the phase of vegetative growth, in the 12-9-2004 image.292328338Canty, M.J., Nielsen, A.A., Schmidt, M., (2004) Automatic radiometric normalization of multitemporal satellite imagery, 91, pp. 441-451. , Remote Sensing of Environment, New YorkChander, G., Markham, B., (2003) Revised Landsat 5/TM radiometric calibration procedures and postcalibration dynamic ranges, 41 (11), pp. 2.764-2.677. , IEEE Transactions on Geosciense and Remote Sensing, New York(2007) Cooperativa Central De Pesquisa Agrícola, , http://www.coodetec.com.br/, Coodetec. Atividades de pesquisa: soja. NET, Cascavel, jan. 2007. Disponível em: Acesso em: 12 fevCrist, E.P., (1985) A TM tasseled cap equivalent transformation for reflectance factor data, 95 (17), pp. 301-306. , Remote Sensing of Environment, New YorkDu, Y., Teillet, P.M., Cihlar, J., (2002) Radiometric normalization of multitemporal high-resolution images with quality control for land cover change detection, 82 (1), pp. 123-134. , Remote Sensing of Environment, New YorkEastman, J.R., (2003) Idrisi Kilimanjaro - Guide to GIS and image processing, p. 328. , Worcester: Clark LaboratoryGomes, F.P., (2000) Curso de estatística experimental, p. 477. , 14.ed. Piracicaba: ESALQHall, F.G., Strebel, D.E., Nickeson, J.E., Goets, S.J., (1991) Radiometric rectification: toward a common radiometric response among multidate, multisensor imagens, 35 (1), pp. 11-27. , Remote Sensing of Environment, New YorkMoreira, R.C., (2000) Influência do posicionamento e da largura de bandas de sensores remotos e dos efeitos atmosféricos na determinação de índices de vegetação, , 2000. 114 f. Dissertação (Mestrado em Sensoriamento Remoto) - Instituto de Pesquisas Espaciais, São José dos CamposNielsen, A.A., Conradsen, K., Simpson, J.J., (1998) Multivariate alteration detection (MAD) and MAF processing in multispectral, bitemporal image data: New approaches to change detection studies, 64 (1), pp. 11-19. , Remote Sensing of Environment, New YorkRouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W., Monitoring vegetation systems in the great plains with ERTS (1973) Earth Resources Technology Satellite-1 Symposium, 1, pp. 309-317. , Washington. Proceedings... Washington, DC: NASA, 3., 1973. (NASA SP-351)(2006) Guia do ENVI em português, , http://www.envi.com.br/, Sulsoft. Version 4.0. NET, nov. Disponível em: Acesso em: 12 fev. 2007Song, C., Woodcock, C.E., Monitoring forest succession with multitemporal landsat images: factors of uncertainty (2003) IEEE Transactions on Geosciences and Remote Sensing, 41 (11), pp. 280-392. , New YorkVermote, E.F., Vermeulen, A., Atmospheric correction algorithm: spectral reflectances (Mod09), p. 2004. , http://modis.gsfc.nasa.gov/data/atbd/atbd_mod08.pdf, Version 4.0. NET, EUA, nov.1999. Disponível em: Acesso em: 20 agoyuan, D., Elvidge, C.D., Comparison of relative radiometric normalization techniques (1996) ISPRS Journal of Photogremmetry & Remote Sensing, 94 (51), pp. 117-126. , New YorkZullo Júnior, J., (1994) Correção atmosférica de imagens de satélite e aplicações, , 189 f. Tese (Doutorado em Engenharia Elétrica) - Faculdade de Engenharia Elétrica, Universidade Estadual de Campinas, Campina

Comparison of maps of spatial variability of soil resistance to penetration constructed with and without covariables using a spatial linear model Comparação de mapas de variabilidade espacial da resistência do solo à penetração construídos com e sem covariáveis usando um modelo espacial linear

A study about the spatial variability of data of soil resistance to penetration (RSP) was conducted at layers 0.0-0.1 m, 0.1-0.2 m and 0.2-0.3 m depth, using the statistical methods in univariate forms, i.e., using traditional geostatistics, forming thematic maps by ordinary kriging for each layer of the study. It was analyzed the RSP in layer 0.2-0.3 m depth through a spatial linear model (SLM), which considered the layers 0.0-0.1 m and 0.1-0.2 m in depth as covariable, obtaining an estimation model and a thematic map by universal kriging. The thematic maps of the RSP at layer 0.2-0.3 m depth, constructed by both methods, were compared using measures of accuracy obtained from the construction of the matrix of errors and confusion matrix. There are similarities between the thematic maps. All maps showed that the RSP is higher in the north region.<br>Realizou-se um estudo sobre a variabilidade espacial de dados de resistência do solo à penetração (RSP), nas camadas de 0,0-0,1 m, 0,1-0,2 m e 0,2-0,3 m de profundidade, utilizando métodos estatísticos em forma univariada, isto é, utilizando a geoestatística tradicional, construindo os mapas temáticos por krigagem ordinária para cada camada em estudo. Foi analisada a RSP na camada de 0,2-0,3 m de profundidade por meio de um modelo espacial linear (SLM), em que se consideraram as camadas de 0,0-0,1 m e 0,1-0,2 m como covariáveis, obtendo um modelo de estimação e um mapa temático por krigagem universal. Os mapas temáticos da RSP da camada de 0,2-0,3 m de profundidade, construídos por ambos os métodos, foram comparados por meio de medidas de acurácia obtidas a partir da construção da matriz de erros e da matriz de confusão. Verificou-se semelhança entre os mapas temáticos. Todos os mapas mostraram que a RSP é mais alta na região norte