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http://dx.doi.org/10.7780/kjrs.2004.20.2.65

A New Look at the Statistical Method for Remote Sensing of Daily Maximum Air Temperature  

변민정 (부경대학교 환경대기과학과)
한경수 (프랑스 기상청 기상연구소)
김영섭 (부경대학교 위성정보과학과)
Publication Information
Korean Journal of Remote Sensing / v.20, no.2, 2004 , pp. 65-76 More about this Journal
Abstract
This study aims to estimate daily maximum air temperature estimated using satellite-derived surface temperature and Elevation Derivative Database (EDD). The analysis is focused on the establishment of a semi-empirical estimation technique of daily maximum air temperature through the multiple regression analysis. This tests the contribution of EDD in the air temperature estimation when it is added into regression model as an independent variable. The better correlation is shown with the EDD data as compared with the correlation without this data set. In order to provide a progressive estimation technique, we propose and compare three approaches: 1) seasonal estimation non-considering landcover, 2) seasonal estimation considering landcover, and 3) estimation according to landcover type and non-considering season. The last method shows the best fit with the root-mean-square error between 0.56$^{\circ}C$ and 3.14$^{\circ}C$. A cross-validation procedure is performed for third method to valid the estimated values for two major landcover types (cropland and forest). For both landcover types, the validation results show reasonable agreement with estimation results. Therefore it is considered that the estimation technique proposed may be applicable to most parts of South Korea.
Keywords
Daily Maximum Air Temperature; Elevation Derivative Database; Landcover; Cross-Validation;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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