Theoretical and Applied Climatology

, Volume 120, Issue 1–2, pp 211–226 | Cite as

A method to estimate maximum and minimum air temperature using MODIS surface temperature and vegetation data: application to the Maipo Basin, Chile

  • Eduardo BustosEmail author
  • Francisco J. Meza
Original Paper


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.


Root Mean Square Error Normalize Difference Vegetation Index Land Surface Temperature Land Cover Type MODIS Land Surface Temperature 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



The MODIS data were obtained through the online Data Pool at the NASA Land Processes Distributed Active Archive Center (LP-DAAC). This study was partially funded by CORFO-INNOVA grant 2009-5704 to the Centro Interdisciplinario de Cambio Global at the Pontificia Universidad Católica de Chile and with the aid of a grant from the Inter-American Institute for Global Change Research (IAI) CRN3056 which is supported by the US National Science Foundation (Grant GEO-1128040). We thank Fondecyt (Grant 1120713) for additional support. The authors would like to thank Professor Willem Van Leuween from University of Arizona and an anonymous reviewer for their helpful comments.


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Copyright information

© Springer-Verlag Wien 2014

Authors and Affiliations

  1. 1.Centro Interdisciplinario de Cambio GlobalPontificia Universidad Católica de ChileSantiagoChile
  2. 2.Departamento de Ecosistemas y Medioambiente, Facultad de Agronomía e Ingeniería ForestalPontificia Universidad Católica de ChileSantiagoChile

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