Comparação de métodos de classificação de imagens, visando o gerenciamento de áreas citrícolas
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Data
2009-08-14
Autores
Barbosa, Ana Paula [UNESP]
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
Dada a significativa importância da atividade citrícola no Estado de São Paulo, verifica-se a necessidade de um constante monitoramento destas áreas, contribuindo para a tomada de decisões rápidas e abrangentes, visando à manutenção desta exploração. Mesmo com sua extraordinária capacidade de analisar e interpretar dados de sensoriamento remoto, o ser humano tende à subjetividade ao registrar as informações observadas nas imagens. Muitas vezes, o conhecimento do analista sobre a área de estudo é limitado, o que faz do processo de classificação uma tarefa que demanda maior esforço e tempo para identificação dos objetos representados na superfície. A classificação de imagens é o processo de extração de informação para reconhecer padrões e objetos homogêneos e são utilizados em sensoriamento remoto para mapear áreas da superfície terrestre que correspondem aos temas de interesse. O trabalho teve por objetivo a comparação da eficiência de métodos de classificação de imagens orbitais em áreas cultivadas com citros, utilizando técnicas de geoprocessamento visando o planejamento e o gerenciamento localizado das áreas de produção de citros. A área de estudo utilizada corresponde a Fazenda Água Branca, município de Bariri/ SP. O SIG - Idrisi 15.0, foi utilizado no processamento das imagens do satélite LANDSAT-5 TM, órbita/ponto: 221/75, passagens de 16/06/2003 e 26/05/2007. Do trabalho realizado constatou-se que os resultados na avaliação de acurácia da classificação foram satisfatórios, sendo que a classificação do algoritmo CLUSTER apresentou qualidade excelente (0,9276) e muito boa (0,6485); o algoritmo MAXVER apresentou classificações excelentes, com Kappa de 0,8338 e 0,8818; e o índice gerado pelo método de classificação relativa...
The significative activity of the citrus crop in São Paulo State requires a constant monitoring of these areas, contributing to make the quick and comprehensive decisions, aiming to maintain this operation. Even with the extraordinary ability to analyze and interpret data from remote sensing, human beings tend to subjectivity to register the information in the observed images. Often, knowledge of the analyst about the study area is limited, which makes the process of classifying a task that demands more time and effort to identify the objects represented on the surface. The images classification is the process of extraction of information to recognize patterns and homogeneous objects and it is used in remote sensing to map areas of the surface that correspond to themes of interest. This study aimed to compare the efficiency of methods of classification of orbital images in areas cultivated with citrus, using GIS techniques to the planning and management located in the areas of citrus production. The study area is located in Água Branca Farm, city of Bariri/SP. The GIS - Idrisi 15.0 was used in the image processing. It noted that the evaluation results of the classification accuracy were satisfactory, which the classifications of the CLUSTER algorithm had excellent quality (0.9276) and very good (0.6485), the MAXVER algorithm had excellent ratings, with kappa of 0.8338 and 0.8818, and the index obtained by the method of Fuzzy classification submitted a rating between very good (0.7260) and good (0.5235) for 2003 and 2007, respectively. The methods used for the discrimination of areas cultivated with citrus showed different efficiencies in the classification of images. In general, the classifications for the 2003 images showed the best performance when compared... (Complete abstract click electronic access below)
The significative activity of the citrus crop in São Paulo State requires a constant monitoring of these areas, contributing to make the quick and comprehensive decisions, aiming to maintain this operation. Even with the extraordinary ability to analyze and interpret data from remote sensing, human beings tend to subjectivity to register the information in the observed images. Often, knowledge of the analyst about the study area is limited, which makes the process of classifying a task that demands more time and effort to identify the objects represented on the surface. The images classification is the process of extraction of information to recognize patterns and homogeneous objects and it is used in remote sensing to map areas of the surface that correspond to themes of interest. This study aimed to compare the efficiency of methods of classification of orbital images in areas cultivated with citrus, using GIS techniques to the planning and management located in the areas of citrus production. The study area is located in Água Branca Farm, city of Bariri/SP. The GIS - Idrisi 15.0 was used in the image processing. It noted that the evaluation results of the classification accuracy were satisfactory, which the classifications of the CLUSTER algorithm had excellent quality (0.9276) and very good (0.6485), the MAXVER algorithm had excellent ratings, with kappa of 0.8338 and 0.8818, and the index obtained by the method of Fuzzy classification submitted a rating between very good (0.7260) and good (0.5235) for 2003 and 2007, respectively. The methods used for the discrimination of areas cultivated with citrus showed different efficiencies in the classification of images. In general, the classifications for the 2003 images showed the best performance when compared... (Complete abstract click electronic access below)
Descrição
Palavras-chave
Landsat (Satelites), Conjuntos difusos, Copo calibrador, Fuzzy, Satellite, Images classifiers
Como citar
BARBOSA, Ana Paula. Comparação de métodos de classificação de imagens, visando o gerenciamento de áreas citrícolas. 2009. xii, 65 f. Dissertação (mestrado) - Universidade Estadual Paulista, Faculdade de Ciências Agronômicas de Botucatu, 2009.