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@MastersThesis{Arcoverde:2008:EsEsEs,
               author = "Arcoverde, Gustavo Felipe Balu{\'e}",
                title = "Estratifica{\c{c}}{\~a}o espacial para estimativa da {\'a}rea 
                         de culturas agr{\'{\i}}colas de ver{\~a}o com imagens de 
                         pr{\'e}-plantio",
               school = "Instituto Nacional de Pesquisas Espaciais (INPE)",
                 year = "2008",
              address = "S{\~a}o Jos{\'e} dos Campos",
                month = "2008-08-27",
             keywords = "Estimativa de {\'a}rea agr{\'{\i}}cola, 
                         estratifica{\c{c}}{\~a}o espacial, reconhecimento de 
                         padr{\~o}es em imagens de sat{\'e}lite, mapas 
                         auto-organiz{\'a}veis, {\'a}rvore de decis{\~a}o, agricultural 
                         crop area estimation, spatial stratification, pattern recognition 
                         iin satellite images, self-organizing maps, tree decision.",
             abstract = "O levantamento da {\'a}rea agr{\'{\i}}cola {\'e} uma 
                         informa{\c{c}}{\~a}o fundamental para o planejamento 
                         agr{\'{\i}}cola, econ{\^o}mico, agr{\'a}rio, ambiental, ou 
                         social. Recomenda-se que o c{\'a}lculo da {\'a}rea 
                         agr{\'{\i}}cola seja por vias probabil{\'{\i}}sticas e de 
                         forma estratificada. A estratifica{\c{c}}{\~a}o tem como 
                         principais benef{\'{\i}}cios a redu{\c{c}}{\~a}o da 
                         vari{\^a}ncia global e a otimiza{\c{c}}{\~a}o da 
                         verifica{\c{c}}{\~a}o da verdade amostral. A 
                         estratifica{\c{c}}{\~a}o espacial comumente {\'e} realizada por 
                         interpreta{\c{c}}{\~a}o visual de dados cartogr{\'a}ficos e 
                         imagens de sat{\'e}lite, visando identificar padr{\~o}es de uso 
                         da terra com probabilidades de ocorr{\^e}ncia de determinada 
                         cultura agr{\'{\i}}cola. Este trabalho teve como objetivo 
                         avaliar estratifica{\c{c}}{\~o}es semi-autom{\'a}ticas para 
                         estimativas de {\'a}reas com uso agr{\'{\i}}cola de culturas de 
                         ver{\~a}o no munic{\'{\i}}pio de Barretos (SP). Para tanto 
                         utilizaram-se duas imagens do sensor TM/Landsat-5 de datas de 
                         pr{\'e}-plantio de culturas agr{\'{\i}}colas de ver{\~a}o. Os 
                         estratos foram gerados pela identifica{\c{c}}{\~a}o e 
                         classifica{\c{c}}{\~a}o de padr{\~o}es de cobertura da terra 
                         nas datas de pr{\'e}-plantio, por an{\'a}lise espectral por 
                         pixels (AEP), e por an{\'a}lise de multi-atributos por objeto 
                         (AMO). Na AEP empregaram-se modelo linear de mistura espectral, 
                         an{\'a}lise de vetor de mudan{\c{c}}as, e an{\'a}lise de Mapas 
                         de Regras por m{\'a}xima verossimilhan{\c{c}}a. A AMO foi 
                         abastecida por diferentes atributos extra{\'{\i}}dos pelo 
                         programa DEFINIENS, e empregou classificadores por mapas 
                         auto-organiz{\'a}veis (SOM), {\'a}rvore de decis{\~a}o por 
                         algoritmo C 4.5, e com associa{\c{c}}{\~a}o de ambos. As 
                         estratifica{\c{c}}{\~o}es geradas foram consideradas em sua 
                         maioria como regulares. A principal causa deste desempenho regular 
                         foi a confus{\~a}o que os classificadores apresentaram em 
                         rela{\c{c}}{\~a}o {\`a}s {\'a}reas de 
                         cana-de-a{\c{c}}{\'u}car planta. Houve redu{\c{c}}{\~a}o da 
                         vari{\^a}ncia global da estimativa de {\'a}rea que utilizou os 
                         estratos com maior {\'{\i}}ndice kappa, em 
                         compara{\c{c}}{\~a}o a uma estimativa de {\'a}rea por 
                         amostragem aleat{\'o}ria simples. No entanto, nesta mesma 
                         compara{\c{c}}{\~a}o, n{\~a}o haveria otimiza{\c{c}}{\~a}o 
                         para a verifica{\c{c}}{\~a}o da verdade amostral, posto que foi 
                         necess{\'a}rio atribuir mais elementos amostrais fora dos 
                         estratos definidos para a redu{\c{c}}{\~a}o da vari{\^a}ncia 
                         global. Concluiu-se que estratifica{\c{c}}{\~o}es espaciais 
                         realizadas pelas abordagens adotadas, realizadas em regi{\~o}es 
                         cuja {\'a}rea de interesse se apresente de forma fragmentada e/ou 
                         com pouca representa{\c{c}}{\~a}o na {\'a}rea total, n{\~a}o 
                         s{\~a}o indicadas para a redu{\c{c}}{\~a}o da vari{\^a}ncia 
                         global e para a otimiza{\c{c}}{\~a}o da verifica{\c{c}}{\~a}o 
                         da verdade amostral de forma associada. ABSTRACT: Agricultural 
                         crop surveys are fundamental information for planning of 
                         agriculture, economics, agraro-environment, or social. It is 
                         recommended that the calculation of the agriculture crop area be 
                         made by probabilistic methods and using stratification procedures. 
                         The stratification has as main benefits the decrease of total 
                         variance and the quality improvement of sampling check. The 
                         spatial stratification is usually carried out by visual 
                         interpretation of cartographic data and satellite images, aiming 
                         to identify patterns of land use with probabilities of occurrence 
                         of specific agriculture crop. This study has the objective to 
                         evaluate semi-automatic stratifications for area estimates of 
                         summer agricultural crops in the municipality of Barretos, State 
                         of S{\~a}o Paulo, Brazil. For this purpose, two TM/Landsat-5 
                         images from pre-planting dates of summer agricultural crops were 
                         used. The strata were generated by the identification and 
                         classification of land cover patterns in pre-planting dates, by 
                         pixel spectral analysis (PSA) and by multi-attributes object 
                         analysis (MOA). In PSA unmixing linear modeling, change vector 
                         analysis and Rule Maps analysis by maximum likelihood were used. 
                         The MOA was supplied with different attributes extracted from 
                         DEFINIENS software, and employed classifiers by self-organizing 
                         maps (SOM), decision tree by C 4.5 algorithm as well as the 
                         association of both. Most of the stratifications generated were 
                         considered to be regular. The main cause of this regular 
                         performance was due to the confusion presented by the classifiers 
                         in relation to the new planted sugar cane areas. There was a 
                         decrease in the total variance of the area estimates that used the 
                         strata with higher kappa index, in comparison to an area estimate 
                         by simple random sampling. However, there wouldnt be improvement 
                         in checking the sampling quality because it was necessary to 
                         allocate more sampling elements outside the defined strata in 
                         order to decrease the total variance estimate. It was concluded 
                         that spatial stratifications adopted here, which were carried out 
                         in regions where interest areas are presented as fragmented spots 
                         and/or with little proportions of the total area, are not 
                         indicated for the reduction of the total variance and for the 
                         improvement of checking the sampling quality.",
            committee = "Renn{\'o}, Camilo Daleles (presidente) and Epiphanio, Jos{\'e} 
                         Carlos Neves (orientador) and Formaggio, Ant{\^o}nio Roberto and 
                         Fonseca, Leila Maria Garcia and Rocha, Jansle Vieira",
           copyholder = "SID/SCD",
         englishtitle = "Spatial stratification for area estimate of summer agricultural 
                         crops using pre-planting images",
             language = "pt",
                pages = "180",
                  ibi = "8JMKD3MGP8W/3448EQH",
                  url = "http://urlib.net/ibi/8JMKD3MGP8W/3448EQH",
           targetfile = "paginadeacesso.htm",
        urlaccessdate = "02 maio 2024"
}


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