Classificação de áreas de favelas a partir de imagens IKONOS: Viabilidade de uso de uma abordagem orientada a objeto

The growth of large cities is usually accelerated and disorganized, which causes social, economical and infrastructural conflicts and frequently, occupation in illegal areas. For a better administration of these areas, the public manager needs information about their location. This information can be obtained through land utilization and land cover maps, where orbital images of remote sensing are used as one of the most traditional sources of data. In this context, the present work tested the applicability of the object-based classification to categorize two slum areas, taking into account the structure of the streets, size of the huts, distance between the houses, among other parameters. These area combinations of physical aspects were analyzed using the image IKONOS II and the software eCognition. Slum areas tend to be, to the contrary of the planned areas, disarranged, with narrow streets, small houses built with a variety of materials and without definition of blocks. The results of land cover classification for slum areas are encouraging because they are accurate and little ambiguous in the classification process. Thus, it would allow its utilization by urban managers.

Um filtro gaussiano adaptativo para análise comparativa de imagens de radares e satélites meteorológicos

Meteorological satellite and radar data comparative analysis allows to correlate the precipitation structures observed in both images. Such analysis would make feasible the extension of the range of ground-based meteorological radars. In addition to the different spatial and temporal resolution of these images this comparative analysis presents difficulties due to the effects of rotation and distortion, besides the different formats, projections, and coordinate systems. This work employed an approach based on a Gaussian adaptive filter in order to compare such images. The statistical results obtained from the comparison of the images are matched to those produced by other methods.

Extração de vias combinando métodos de detecção de regiões e linhas em imagens de intensidade de pulso laser

This paper aims at extracting street centerlines from previously isolated street regions by using the image of laser scanning intensity. In this image, streets are easily identified, since they manifest as dark, elongate ribbons contrasting with background objects. The intensity image is segmented by using the region growing technique, which generates regions representing the streets. From these regions, the street centerlines are extracted in two manners. The first one is through the Steger lines detection method combined with a line length thresholding by which lines being shorter than a minimum length are removed. The other manner is by combining the skeletonization method of regions based on the Medial Axis Transform and with a pruning process to eliminate as much as possible the ramifications. Experiments showed that the Steger-based method provided results better than the method based on skeletonization.

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.

Análise de imagens no estudo da porosidade em latossolo cultivado com batata (Solanum tuberosum L.) sob dois sistemas de irrigação

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Detecção da área e extração do campo em imagens de impressão digital

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Extração semi-automática de rodovias no espaço-objeto: uso integrado de um estéreo par de imagens aéreas e um MDT

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Ajuste radiométrico de imagens aéreas digitais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Imagens multitemporais ALOS/PALSAR baseada em orientação a objeto na discriminação da cobertura da terra

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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)

Determinação automática da altura de edifícios em imagens aéreas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Métodos para extração de informações a partir de imagens multiespectrais de escalas grandes

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Detecção de rodovias em imagens digitais de alta resolução com o uso da teoria de morfologia matemática

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Fototriangulação em bloco de imagens orbitais com modelos rigorosos baseados em pontos e retas

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Formação de imagens multiespectrais por meio de fusão de imagens adquiridas por múltiplas câmaras

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)