Classificador neural híbrido para imagens obtidas por sensoriamento remoto

Remote sensing is one technology of extreme importance, allowing capture of data from the Earth's surface that are used with various purposes, including, environmental monitoring, tracking usage of natural resources, geological prospecting and monitoring of disasters. One of the main applications of remote sensing is the generation of thematic maps and subsequent survey of areas from images generated by orbital or sub-orbital sensors. Pattern classification methods are used in the implementation of computational routines to automate this activity. Artificial neural networks present themselves as viable alternatives to traditional statistical classifiers, mainly for applications whose data show high dimensionality as those from hyperspectral sensors. This work main goal is to develop a classiffier based on neural networks radial basis function and Growing Neural Gas, which presents some advantages over using individual neural networks. The main idea is to use Growing Neural Gas's incremental characteristics to determine the radial basis function network's quantity and choice of centers in order to obtain a highly effective classiffier. To demonstrate the performance of the classiffier three studies case are presented along with the results.

Segmentação fuzzy de imagens coloridas com características texturais: uma aplicação a rochas sedimentares

Image segmentation is the process of labeling pixels on di erent objects, an important step in many image processing systems. This work proposes a clustering method for the segmentation of color digital images with textural features. This is done by reducing the dimensionality of histograms of color images and using the Skew Divergence to calculate the fuzzy a nity functions. This approach is appropriate for segmenting images that have colorful textural features such as geological, dermoscopic and other natural images, as images containing mountains, grass or forests. Furthermore, experimental results of colored texture clustering using images of aquifers' sedimentary porous rocks are presented and analyzed in terms of precision to verify its e ectiveness.

Evolução geomorfológica, (des)caracterização e formas de uso das Lagoas da cidade do Natal-RN

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Caracterização geológica, geomorgológica e geotécnica de um corpo de dunas na cidade de Natal-RN

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

O ultra-som terapêutico de 1 MHz, na dose de 0,5 W cm-2, sobre o tecido ósseo de cães avaliado por densitometria óptica em imagens radiográficas

As lesões tendíneas nas extremidades distais dos membros estão entre as mais freqüentes alterações do aparelho locomotor na rotina clínico-cirúrgica humana e animal e, não raro, necessitam de terapias adjuvantes para seu completo retorno às funções fisiológicas. O ultra-som terapêutico (UST) é a modalidade mais utilizada nas clínicas de reabilitação para tratar lesões tendíneas, mas devido à falta ou a divergências de estudos específicos sobre seus efeitos no tecido ósseo, sua utilização sobre as regiões distais dos membros, ricas em protuberâncias ósseas e áreas desprovidas de cobertura muscular, sempre preocuparam os profissionais da área médica. No intuito de esclarecer os efeitos do UST sobre o tecido ósseo, seis cães receberam tratamento ultra-sônico contínuo, de 1MHz, durante cinco minutos diários, por um período de 20 dias sobre a região craniodistal do rádio e da ulna. A intensidade do UST aplicada foi de 0,5W cm-2 no membro torácico direito, ficando o membro contralateral como controle. A região distal de ambos os membros torácicos foi radiografada para análise de densitometria óssea em imagens radiográficas, antes do início da terapia e ao final do tratamento. Não houve alterações significativas de densidade mineral óssea entre os membros tratados e os controles. Conclui-se que dentro dos parâmetros utilizados no experimento a utilização do UST em regiões ósseas protuberantes ou desprovidas de cobertura muscular pode ser feita com segurança.

Historical land-cover/use in different slope and riparian buffer zones in watersheds of the state of São Paulo, Brazil

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

Fotointerpretacao comparativa de fotografias pancromaticas, imagens de radar e de satelite

Three types of imagery were evaluated for mapping drainage patterns and vegetation in a 100 000 ha area of Sao Paulo State, Brazil. The drainage measurements were drainage density, frequency of channels and texture ratio, studied on circular samples of 10 km2 for panchromatic photography and 100 km2 for radar and satellite images. The vegetation types were forest, pasture, sugar cane and rice, studied on circular samples of 100 km2. Radar images were the most convenient method to study drainage patterns and the land forms of large areas, while Landsat imagery was most efficient for the study of vegetative cover, although panchromatic photographs were the most accurate method.-from Field Crop Abstracts

Estudo da influencia do relevo nos dados de reflectancia da superficie do terreno atraves de imagens Landsat.

Presents a study of the spectral response of a specific vegetative cover under the same soil elevation angle, but in different classes of slope, through Landsat transparencies. The site located in the region of Presidente Prudente was studied through topo sheets to define the classes of slope. Densitometric readings were obtained of selected areas, representing the terrain reflectance in different relief conditions. The cluster analysis was used to classify the densitometric data according to the classes of slope. The map of classes of slope/reflectance of the terrain surface showed a high correlation, mainly for the classes A (0-10%) and B (10-20%). -from English summary

Mapeamento do uso da terra, vegetação e impactos ambientais por meio de sensoriamento remoto e geoprocessamento

The mapping of the land use, vegetation and environmental impacts using remote sensing ana geoprocessmg allow detection, spatial representation and quantification of the alterations caused by the human action on the nature, contributing to the monitoring and planning of those activities that may cause damages to the environment. This study apply methodologies based on digital processing of orbital images for the mapping of the land use, vegetation and anthropic activities that cause impacts in the environment. It was considered a test area in the district of Assistência and surroundings, in Rio Claro (SP) region. The methodology proposed was checked through the crossing of maps in the software GIS - Idrisi. These maps either obtained with conventional interpretation of aerial photos of 1995, digitized in the software CAD Overlay and geo-referenced in the AutoCAD Map, or with the application of digital classification systems on SPOT-XS and PAN orbital images of 1995, followed by field observations. The crossing of conventional and digital maps of a same area with the CIS allows to verify the overall results obtained through the computational handling of orbital images. With the use of digital processing techniques, specially multiespectral classification, it is possible to detect automatically and visually the impacts related to the mineral extraction, as well as to survey the land use, vegetation and environmental impacts.

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.

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)

SIG e sensoriamento remoto aplicado ao estudo dos processos de inundação e mapeamento da cobertura vegetal na planície fluvial do alto Rio Paraná

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

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)

Concepção, desenvolvimento e aplicação do banco de imagens georreferenciadas no contexto do mapeamento terrestre móvel

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