%0 Conference Proceedings
%4 dpi.inpe.br/sbsr@80/2008/
%2 dpi.inpe.br/sbsr@80/2008/
%@isbn 978-85-17-00044-7
%M 0
%T Resultados preliminares da utilização de dados do sensor MODIS para detecção de eventos frios na região Sul do Brasil
%D 2009
%8 25-30 abr. 2009
%A Ummus, Marta Eichemberger,
%A Ferreira, Nelson Jesus,
%A Viana, Denilson Ribeiro,
%@affiliation Instituto Nacional de Pesquisas Espaciais/INPE
%@affiliation Instituto Nacional de Pesquisas Espaciais/INPE
%@affiliation Instituto Nacional de Pesquisas Espaciais/INPE
%@electronicmailaddress marta@dsr.inpe.br
%@electronicmailaddress nelson@cptec.inpe.br
%@electronicmailaddress denilson@dsr.inpe.br
%E Epiphanio, José Carlos Neves,
%E Galvão, Lênio Soares,
%B Simpósio Brasileiro de Sensoriamento Remoto, 14 (SBSR)
%C Natal
%P 1699-1706
%S Anais
%I Instituto Nacional de Pesquisas Espaciais (INPE)
%J São José dos Campos
%1 Instituto Nacional de Pesquisas Espaciais (INPE)
%K MOD11 product, cold events, Land Surface Temperature, eventos frios, Plataforma de Coleta de Dados, Temperatura de Superfície Terrestre.
%X Pronounced declines of temperature in Southern Brazil may lead to several phenomena that can drive to serious consequences for crops and farms, as for instance frosts. One of the most important parameters to understand these occurrences is Land Surface Temperature (LST), once it is the principal indicator of energy balance. Thus, LST data obtained through remote sensing is an important tool for analyses like that, once they can extend over areas not covered by conventional stations for collecting meteorological data. The aim of this study is to correlate LST data estimated by MOD11 product of MODIS sensor aboard Terra platform and data recorded by data collecting landing-stages of National Meteorology Institute (INMET). Besides it was evaluated the ability of remote sensing data, specifically MODIS sensor, to detect cold events. Therefore Root Mean Squared Error (RMSE) and Bias values were calculated so as to regard three perspectives: latitude, geomorphological subdivision and overpass time of sensor. Achieved results show that although there are significant differences between observed and estimated data, RMSE and Bias values are not so high, what shows the feasibility of the use of MODIS data to detect and analyze cold events.
%9 Atmosfera
%@language pt
%3 1699-1706.pdf