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@TechReport{ValerianoPici:2003:GeInAg,
               author = "Valeriano, M{\'a}rcio de Morisson and Picini, Ang{\'e}lica 
                         Giarolla",
                title = "Geoprocessamento de informa{\c{c}}{\~o}es 
                         agroclimatol{\'o}gicas",
          institution = "INPE",
                 year = "2003",
                 type = "RPQ",
               number = "INPE-10128-RPQ/751",
              address = "S{\~a}o Jos{\'e} dos Campos",
             keywords = "modelagem, metodologia, balan{\c{c}}o h{\'{\i}}drico, 
                         erosividade.",
             abstract = "Neste trabalho, s{\~a}o apresentadas metodologias de 
                         processamento de dados de temperatura e precipita{\c{c}}{\~a}o, 
                         desenvolvidas para a gera{\c{c}}{\~a}o de mapas digitais de 
                         vari{\'a}veis agroclim{\'a}ticas. A proposta metodol{\'o}gica 
                         baseia-se na opera{\c{c}}{\~a}o de bases digitais espacializadas 
                         com recursos de Sistemas de Informa{\c{c}}{\~a}o Geogr{\'a}fica 
                         (SIG). A espacializa{\c{c}}{\~a}o pr{\'e}via das vari{\'a}veis 
                         b{\'a}sicas foi feita de maneira individual e otimizada, com 
                         inser{\c{c}}{\~a}o de informa{\c{c}}{\~o}es do relevo para 
                         melhoria dos planos de informa{\c{c}}{\~a}o gerados. O 
                         mapeamento foi elaborado com vistas a estudos regionais na escala 
                         1:1.000.000, com dados termo-pluviom{\'e}tricos do Estado de 
                         S{\~a}o Paulo. A espacializa{\c{c}}{\~a}o da temperatura foi 
                         feita com modelos de regress{\~a}o, calculados mensalmente em 
                         rela{\c{c}}{\~a}o a latitude e {\`a} altitude, com dados 
                         altim{\'e}tricos do sensor RADARSAT-1. Os dados 
                         pluviom{\'e}tricos foram interpolados com subs{\'{\i}}dio de 
                         an{\'a}lises geoestat{\'{\i}}sticas da variabilidade e da 
                         anisotropia, estratificadas em fun{\c{c}}{\~a}o da 
                         predomin{\^a}ncia de alinhamentos no relevo em estruturas 
                         direcionais diferentes. Sobre estes planos foram aplicadas 
                         fun{\c{c}}{\~o}es de SIG para o c{\'a}lculo de vari{\'a}veis 
                         agroclim{\'a}ticas. Foram obtidos planos de 
                         informa{\c{c}}{\~a}o de elementos do balan{\c{c}}o 
                         h{\'{\i}}drico, bem como de fatores clim{\'a}ticos de modelos 
                         de degrada{\c{c}}{\~a}o agr{\'{\i}}cola de solos e {\'a}gua. 
                         S{\~a}o apresentados mapas mensais e anuais das vari{\'a}veis: 
                         armazenamento de {\'a}gua no solo, vapotranspira{\c{c}}{\~a}o 
                         real, excedente h{\'{\i}}drico, defici{\^e}ncia 
                         h{\'{\i}}drica, erosividade (Equa{\c{c}}{\~a}o Universal de 
                         Perda de Solos) e fator Beta (Modelagem da Perda de Produtividade 
                         de Solos). Est{\~a}o apresentadas tamb{\'e}m as linhas de 
                         comando dos procedimentos desenvolvidos, na estrutura de programas 
                         de lote, ou linguagem de macro. ABSTRACT: This work presents 
                         methodologies for processing temperature and rainfall data, 
                         developed to generate digital maps agroclimatic variables. The 
                         methodological approach is based on the operation of previously 
                         spatialized databases in Geographical Information Systems (GIS). 
                         Data spatialization step was optimized individually for each basic 
                         variable, with the insertion of elevation data to improve quality 
                         of the rasterized information. Map generation was projected to 
                         support regional studies in the 1:1,000,000 scale, with 
                         temperature and rainfall data of S{\~a}o Paulo State. Temperature 
                         was mapped through regression models, monthly calculated in 
                         respect to latitude and elevation maps derived from RADARSAT-1 
                         data. Rainfall data were interpolated with guidance of 
                         geostatistical analysis of variability and anisotropy, stratified 
                         according to the local prevailing of relief alignments into 
                         different directional structures. GIS functions were applied on 
                         these raster databases for the calculation of agroclimatic 
                         variables. Information layers of the water budget elements, as 
                         well as the climatic factors of agricultural land and water 
                         degradation models, were obtained. Monthly and annual maps of the 
                         following variables were shown: soil water storage, real 
                         evapotranspiration, water excess and deficit, erosivity (Universal 
                         Soil Loss Equation) and Betha (EPIC: Erosion-Productivity Impacto 
                         Calculator). Also shown were the command lines of the developed 
                         procedures, which were structure in batch job, or macro language, 
                         programs.",
           copyholder = "SID/SCD",
             language = "pt",
                pages = "133",
                  ibi = "6qtX3pFwXQZsFDuKxG/ApqLu",
                  url = "http://urlib.net/rep/6qtX3pFwXQZsFDuKxG/ApqLu",
           targetfile = "publicacao.pdf",
        urlaccessdate = "2020, Sep. 18"
}


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