Imagens digitais na análise do uso da terra de uma microbacia como subsídio ao desenvolvimento sustentável

The present work sought to discriminate, to map and to quantify the areas of soil use of the Stream Monte Belo watershed - Botucatu (SP), obtained by digitale images. The cartographic bases were the shart planialtimetric, edited by IBGE (1969) and the satellite images LANDSAT - 7, passages of 21/01/1999, 08/01/2003 and 23/10/2006. The Software Idrisi Andes 15.0 were used for conversion of the analogical information for digital and for determination of the vegetable coverings areas. The results allowed to verify that the SIG - IDRISI Andes 15.0 were efficient in the quantification of the areas with soil use and that the analysis of the data showed a cash progress of the areas of reforestations to the detriment of the areas of pastures, especially from 1999, 2003 to 2006, when the field areas were substituted by the forestry in his totality. In spite of that progress, the forest areas that you correspond to the Permanent Preservation Areas, They are considerably preserved. That result comes to the encounter of the tendency of expansion of the forestry, especially after the installation of cellulose industries in the area, what worsened the environmental problems originating from of the practice of the monoculture.

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.

Imagens digitais aplicadas no estudo da análise multitemporal do uso e ocupação do solo numa microbacia

The knowledge of the soil occupation as for his nature, location, occurrence form, changes happened in certain periods, they are valuable for the programming of activities that you seek to the development agricultural, economical and social of the area. This work aimed at to identify and to quantify the soil occupation of Stream Petiço Watershed - Botucatu (SP), through the Geographical Information System IDRISI and data of sensor Landsat 5 TM of 09/06/97 and 23/08/2013. For the analysis of the results it was verified that the eucalyptus culture, due to existence of great reforestation companies in the watershed, together with the native forests they are predominant in the study area, the remaining of the area is occupied by pastures and soil prepared for the planting of agricultural cultures.

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)

Discriminação de classes de cobertura vegetal utilizando técnicas de classificação digital de imagens de sensoriamento remoto

The aim of this work is to discriminate vegetation classes throught remote sensing images from the satellite CBERS-2, related to winter and summer seasons in the Campos Gerais region Paraná State, Brazil. The vegetation cover of the region presents different kinds of vegetations: summer and winter cultures, reforestation areas, natural areas and pasture. Supervised classification techniques like Maximum Likelihood Classifier (MLC) and Decision Tree were evaluated, considering a set of attributes from images, composed by bands of the CCD sensor (1, 2, 3, 4), vegetation indices (CTVI, DVI, GEMI, NDVI, SR, SAVI, TVI), mixture models (soil, shadow, vegetation) and the two first main components. The evaluation of the classifications accuracy was made using the classification error matrix and the kappa coefficient. It was defined a high discriminatory level during the classes definition, in order to allow separation of different kinds of winter and summer crops. The classification accuracy by decision tree was 94.5% and the kappa coefficient was 0.9389 for the scene 157/128. For the scene 158/127, the values were 88% and 0.8667, respectively. The classification accuracy by MLC was 84.86% and the kappa coefficient was 0.8099 for the scene 157/128. For the scene 158/127, the values were 77.90% and 0.7476, respectively. The results showed a better performance of the Decision Tree classifier than MLC, especially to the classes related to cultivated crops, indicating the use of the Decision Tree classifier to the vegetation cover mapping including different kinds of crops.

Classificação de imagens em áreas cultivadas com citrus por técnicas de sensoriamento remoto e geoestatística

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Calibração e validação de um método de medida da radiação solar global por meio de actinógrafos baseada em técnicas de processamento de imagens digitais

O objetivo do trabalho é desenvolver um sistema informático de digitalização e processamento de actinogramas baseado em técnicas de Processamento de Imagens Digitais e comparar com o sistema tradicional de medidas. Os actinogramas foram fornecidos pela Estação Meteorológica de Botucatu (FCA/UNESP). As análises preliminares indicam um desempenho satisfatório do software proposto, gerando medidas na mesma ordem de grandeza do método de referência para partição diária. O software proposto pertence a um projeto que se encontra ainda em andamento, onde rotinas de técnicas diversas continuam sendo implementadas no reconhecimento da curva de interesse para melhorar a qualidade do processamento das informações gráficas dos actinogramas. Os actinogramas estão em fase de digitalização para que o software possa ser testado com uma base de dados mais consistente, onde poderão ser identificados tendências temporais dos dados resultantes da aplicação das técnicas de Processamento de Imagens Digitais no monitoramento da radiação solar por actinógrafos.

Além das hashtags: a análise de imagens postadas por atletas no Instagram ® e as diferenças relacionadas ao sexo

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Sob o domínio da metáfora: transposição de imagens poéticas (em) entre Edgar Allan Poe e René Magritte

Pós-graduação em Letras - IBILCE

Investigações na construção de imagens

Pós-graduação em Artes - IA

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

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Segmentação de texturas em imagens digitais utilizando wavelets redundantes

Pós-graduação em Matematica Aplicada e Computacional - FCT

Segmentação interativa de imagens utilizando competição e cooperação entre partículas

Pós-graduação em Ciência da Computação - IBILCE

Das letras às telas: a tradução intersemiótica de Ensaio sobre a cegueira

Pós-graduação em Letras - FCLAS