regionalização de riscos de ocorrência de temperaturas mínimas absolutas anuais para o estado de são paulo com base em modelos probabilísticos e digitais de elevação frost risk mapping based on probabilistic and digital elevation models for the state of são paulo, brazil

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ID: 229442
2005
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Abstract
É necessário o mapeamento mais consistente dos riscos de ocorrência de temperaturas mínimas adversas à agricultura, sendo possível sua obtenção utilizando maior número de postos meteorológicos, modelos probabilísticos e sistema de informações geográficas (SIG), que introduzem precisão matemática. Visando subsidiar os trabalhos de seguro rural, o planejamento e zoneamento agrícola, os objetivos deste trabalho foram os seguintes: estimar os riscos pontuais de ocorrência de temperaturas mínimas absolutas anuais adversas à agricultura para 28 localidades do Estado de São Paulo utilizando modelo probabilístico "distribuição normal", e regionalizar o Estado quanto às probabilidades de ocorrência de diferentes níveis de temperatura mínima absoluta utilizando SIG e modelos digitais de elevação. Utilizou-se o método de regressão múltipla para caracterizar a variabilidade espacial entre as coordenadas geográficas das estações e os resultados do modelo probabilístico. As variáveis independentes parciais que melhor explicaram a variável dependente probabilidade foram, altitude (R²=0,74-0,78), latitude (R²=0,33-0,44) e longitude (R²=0,15-0,20); as equações finais geradas pela regressão múltipla apresentaram R² entre 0,87 e 0,90. As probabilidades estimadas foram consideradas espacialmente no SIG "Idrisi", com base em modelo digital de elevação (altimetria) e coordenadas geográficas (latitude e longitude). As equações de regressão múltipla geraram variação contínua pixel a pixel do risco de ocorrência de diferentes classes de temperaturas mínimas absolutas. São apresentados mapas com a variação espacial das probabilidades de ocorrência de geadas de 1 e 2 °C.
Adverse meteorological phenomenon's occurrence, such as low air temperature and frost, can cause serius damages to the agriculture of the State of São Paulo. The greater accuracy on the occurrence probability establishment for such events, based on historical data obtained from a larger agrometeorological network, appropriated probabilistic models and modern mapping technical can provides assistance for agricultural risk studies, which are very important for agricultural financing and insurance programs. The probabilistic model "normal distribution" was used to estimate the punctual risks of yearly minimum air temperatures below 0, 1, and 2 °C for 28 localities of the State of São Paulo, Brazil. A digital elevation model previously developed with remote sensing and geographical information system (GIS) techniques were used to map the estimated probabilities of frost occurrence, considering different levels of absolute minimum air temperature. Multiple regression equations were developed to estimate the regional probabilities of frost occurrence, based on altitude, latitude and longitude informations. The partial independent variables that better explained the dependent variable "probability" were, at the following importance order, altitude (R² = 0.74-0.78), latitude (R² = 0.33-0.44) and longitude (R² = 0.15-0.20). The equations generated through multiple regression analyses showed determination coefficients between 0.87 and 0.90. The estimated probabilities were spacialized using the GIS "Idrisi", based on a digital elevation model (altitude) and geographical coordinates (latitude and longitude). The multiple regression equations generated continuous pixel-to-pixel variations for different classes of probability of occurrence of absolute minimum air temperature. Two maps are presented showing the spatial variability of the frost risk occurrence with minimum temperatures below 1 and 2 °C.
Reference Key
astolpho2005bragantiaregionalizao Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Fabiane Astolpho;Marcelo Bento Paes de Camargo;Mário José Pedro Junior;Wander José Pallone Filho;Ludmila Bardin
Journal revista espanola de salud publica
Year 2005
DOI
10.1590/S0006-87052005000100015
URL
http://www.scielo.br/scielo.php?script=sci_arttext&pid=S0006-87052005000100015
Keywords
probability digital elevation

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