Análise temporal do uso do solo e comparação entre os índices de vegetação ndvi e savi no município de Santa Cruz do Rio Pardo - SP usando imagens landsat-5

This work aims to analyze the land use evolution in the city of Santa Cruz do Rio Pardo - SP through supervised classification of Landsat-5 TM satellite images according to the maximum likelihood (Maxlike), as well as verifying the mapping accuracy through Kappa index, comparing NDVI and SAVI vegetation indexes in different adjustment factors for the canopy substrate and determining the vegetal coverage percentage in all methods used on 2007, May 26 th; 2009, January 7 th and 2009, April 29 th. The Maxlike classification showed several spatial changes in land use over the study period. The most appropriated vegetation indexes were NDVI and SAVI - 0,25 factor, which showed similar values of vegetal coverage percentage, but discrepant from the inferred value for Maxlike classification.

Proposta de atualização de cadastro urbano a partir de detecção de alterações em imagens QUICK BIRD tomadas em diferentes épocas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Uma análise da infestação por plantas aquáticas utilizando imagens multiescala e redes neurais artificiais

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Geoestística e sensoriamento remoto na classificação de imagens em áreas cultivadas com citros

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sensoriamento remoto e geoprocessamento aplicado ao estudo temporal do uso da terra e na comparação entre classificação não supervisionada e análise visual

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Detecção de regiões de via integrando dados de varredura a LASER aerotransportado e imagens de alta resolução

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Classificação de cobertura do solo utilizando árvores de decisão e sensoriamento remoto

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Nature-Inspired Framework for Hyperspectral Band Selection

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Aplicação de técnicas de geoprocessamento para a avaliação da expansão urbana no municípo de Duque de Caxias (RJ) como subsídio ao monitoramento de dutos: trecho da faixa de dutos Rio de Janeiro - Belo Horizonte

Different forms of human pressure may occur in the pipeline ranges, due to the large extensions and various configurations of land use, which can pass through the pipelines. Due to the dynamics of these pressures, it is necessary to monitor temporal changes of land use and cover the surface. Under this theme, appears as extremely important to use products and techniques of remote sensing, as they allow the identification of objects of the land surface that may compromise the security and monitoring of the pipeline, and allows the extraction of information conditions on land use at different periods of time. Based on the above, this paper aims to examine in a temporal approach, the process of urban expansion in the municipality of Duque de Caxias, located on the outskirts of the metropolitan area of the state of Rio de Janeiro, as well as settlement patterns characteristic of areas that the changes occurred in the period 1987 to 2010. We used the technique of visual analysis to perform the change detection and the technique of image classification, aimed at monitoring human pressure over a stretch of track pipeline Rio de Janeiro - Belo Horizonte, located in the state of Rio de Janeiro. The stages of work involved the characterization of the study area, urban sprawl and the existing settlement patterns, through the analysis of bibliographic data. The processing of Landsat 5 images and the application of the technique of change detection were performed in three scenes for the years 1987, 1998 and 2010, while the classification process was performed on the image RapidEye for the year 2010. Can be noted an increase in urban area of approximately 22.38% and the change of land cover from natural to built. This growth is concentrated outside to the area of direct influence of the duct, occurring in the area of indirect influence of the enterprise. Regarding the settlement patterns of growth areas, it was observed that these are predominantly

Fisiografia e uso da terra de uma bacia hidrográfica em área de afloramento do sistema aquífero Guarani (SAG): o caso do Ribeirão do Jacú, Tejupá/SP (UGRHI-14)SP

Pós-graduação em Agronomia (Irrigação e Drenagem) - FCA

Imagens aéreas multiespectrais na identificação de zonas de manejo em áreas de algodão para aplicação localizada de insumos

Crop yield is influenced by several factors with variability in time and space that are associated with the variations in the plant vigor. This variability allows the identification of management zones and site-specific applications to manage different regions of the field. The purpose of this study was the use of multispectral image for management zones identification and implications of site-specific application in commercial cotton areas. Multispectral airborne images from three years were used to classify a field into three vegetation classes via the Normalized Difference Vegetation Index (NDVI). The NDVI classes were used to verify the potential differences between plant physical measurements and identify management zones. The cotton plant measurements sampled in 8 repetitions of 10 plants at each NDVI class were Stand Count, Plant Height, Total Nodes and Total Bolls. Statistical analysis was performed with treatments arranged in split plot design with Tukey’s Test at 5% of probability. The images were classified into five NDVI classes to evaluate the relationship between cotton plant measurement results and sampling location across the field. The results have demonstrated the possibility of using multispectral image for management zones identification in cotton areas. The image classification into three NDVI classes showed three different zones in the field with similar characteristics for the studied years. Statistical differences were shown for plant height, total nodes and total bolls between low and high NDVI classes for all years. High NDVI classes contained plants with greater height, total nodes and total bolls compared to low NDVI classes. There was no difference in Stand Count between low and high NDVI classes for the three studied years. The final plant stand was the same between all NDVI classes for 2001 and 2003 as it was expected due to the conventional seeding application with the same rate of seeds for the entire field.

Métodos de classificação de imagens na identificação de áreas cultivadas com citros

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Comparação de métodos de classificação de imagens na identificação de áreas cultivadas com citros

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Classification of masses in mammographic image using wavelet domain features and polynomial classifier

Breast cancer is the most common cancer among women. In CAD systems, several studies have investigated the use of wavelet transform as a multiresolution analysis tool for texture analysis and could be interpreted as inputs to a classifier. In classification, polynomial classifier has been used due to the advantages of providing only one model for optimal separation of classes and to consider this as the solution of the problem. In this paper, a system is proposed for texture analysis and classification of lesions in mammographic images. Multiresolution analysis features were extracted from the region of interest of a given image. These features were computed based on three different wavelet functions, Daubechies 8, Symlet 8 and bi-orthogonal 3.7. For classification, we used the polynomial classification algorithm to define the mammogram images as normal or abnormal. We also made a comparison with other artificial intelligence algorithms (Decision Tree, SVM, K-NN). A Receiver Operating Characteristics (ROC) curve is used to evaluate the performance of the proposed system. Our system is evaluated using 360 digitized mammograms from DDSM database and the result shows that the algorithm has an area under the ROC curve Az of 0.98 ± 0.03. The performance of the polynomial classifier has proved to be better in comparison to other classification algorithms. © 2013 Elsevier Ltd. All rights reserved.

Land cover classification of Lago Grande de Curuai floodplain (Amazon, Brazil) using multi-sensor and image fusion techniques

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)