Journal
THEORETICAL AND APPLIED CLIMATOLOGY
Volume 120, Issue 1-2, Pages 211-226Publisher
SPRINGER WIEN
DOI: 10.1007/s00704-014-1167-2
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Funding
- CORFO-INNOVA grant [2009-5704]
- Inter-American Institute for Global Change Research (IAI) [CRN3056]
- Inter-American Institute for Global Change Research (IAI) - US National Science Foundation [GEO-1128040]
- Fondecyt [1120713]
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We present a method to estimate minimum and maximum air temperatures that uses land surface information from the Moderate Resolution Imaging Spectroradiometer (MODIS). The method is based on an analysis of the distribution of the Normalized Difference Vegetation Index (NDVI) and Land Surface Temperature (LST) obtained from the MODIS sensor. We select the pixels with high values of NDVI for each set of NDVI-LST images to represent vegetation pixels with adequate water conditions, ensuring that temperature values between surface and air surrounding are similar. Then, these pixels are spatially interpolated in order to obtain whole region maps of maximum and minimum air temperature. Estimates were compared with observed values for 12 meteorological stations distributed in the study area. After correcting for bias and lags between satellite and surface observation times, the majority of the stations show air temperature estimates that have no significant differences compared to the observed air temperature values. Except for urban areas, results show a correct representation of spatial and temporal distribution of maximum and minimum temperatures for all surface types.
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