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

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

Rede neural não supervisionada baseada em transformada Karhunen-Loève para processamento, compressão e reconhecimento de imagens

The merit of the Karhunen-Loève transform is well known. Since its basis is the eigenvector set of the covariance matrix, a statistical, not functional, representation of the variance in pattern ensembles is generated. By using the Karhunen-Loève transform coefficients as a natural feature representation of a character image, the eigenvector set can be regarded as an feature extractor for a classifier.

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.

Comparação de métodos de classificação de imagens, visando o gerenciamento de áreas citrícolas

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Desenvolvimento de um programa computacional para classificação do uso da terra em imagens CBERS 2

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

Método de detecção e classificação de lesões de pele em imagens digitais a partir do modelo Chan-Vese e máquina de vetor de suporte

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação de áreas de favelas a partir de imagens ikonos: viabilidade de uso de uma abordagem orientada a objetos

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Classificação de tábuas de madeira usando processamento de imagens digitais e aprendizado de máquina

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

Classificação da cobertura da terra da RPPN Foz do Rio Aguapeí: abordagem booleana para a integração de imagens TM-Landsat e dados multifonte

The Companhia Energetica de Sao Paulo - CESP owns six hydroelectric dams in the state of São Paulo. The dams, both in its construction and in operation, cause some environmental impacts, most of them negatives, for example, the flooding in regions before not flooded, deviation of the river’s course, among others, bringing harm to flora and fauna of these environments. As a way to compensating these damages, the CESP has acquired a region that was influenced by Sérgio Motta Hydroelectric Plant Engineer, or Porto Primavera, and turned it into Reserva Particular do Patrimônio Natural Foz do Rio Aguapeí. By law it fits in a Conservation Unit, and thus should be contemplate for a management plan, ie, a multidisciplinary technical document which allows, simply, the practice of actions within and around in a sustainably way. This work aimed at developing a land cover map of the reserve for this plan can be made and executed more efficiently. Initially, the project included field visits and meetings with members of the CESP to be specified classes contained on the map. Later, we ran different types of classifications of multispectral images (TM / Landsat 5)... (Complete abstract click electronic access below)

Avaliação do método de classificação baseada no objeto em imagens de alta resolução espacial aplicado para o monitoramento de faixa de dutos: estudo de caso no entorno da refinaria de Capuava em Mauá - SP

The metropolitan region of São Paulo is the most populous of the country, this happens because of its great importance in the national economy and the job opportunities that are offered to the population. These factors result in intense population growth and urban expansion, reaching some non-habitable places of the metropolis, as areas of pipelines, which are very important for the transportation of natural gas, oil and its derivatives. Before the population growth of the region, these sites were unoccupied, do not presenting problems for the population. However, with the disorderly occupation is generated great anthropogenic pressure on the pipeline stitches, causing risks to people who are around them. Therefore it is extremely important to monitor the strip of pipelines through products and techniques of remote sensing and geoprocessing, enabling, through high spatial resolution images, identification of objects or phenomena that occur on Earth's surface that can alter the functioning and safety of pipelines. Therefore, this study aims to monitor a stretch of the area of the pipeline mesh GASPAL/OSVAT and Capuava Refinery (RECAP), located on the outskirts of the metropolitan area of São Paulo in the city of Mauá, who suffer great human pressure, proving thus the techniques of remote sensing and geographic information system (GIS) as effective tools for monitoring phenomena occurred in urban areas of great complexity. The monitoring was done by object-based classification applied in orbital images Ikonos II and RapidEye, of high spatial resolution and, image processing, detection of objects, segmentation, classification and editing were developed through the eCognition and ArcGis softwares. To determine the statistical accuracy of the mapping of the land cover of the stretch of pipeline in Maua, the results were analyzed by error matrix... (Complete abstract click electronic access below)

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)

Análise do descritor de padrões mapeados localmente em multiescala para classificação de textura em imagens digitais

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)