Component Temperature Estimation from Simulated Geostationary Meteorological Satellite Data Based on MAP Criterion and Markov Models

  • 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China;
    2. Institute of Mountain Hazards and Environment, CAS, Chengdu 610041, China

Received date: 2012-11-29

  Revised date: 2013-02-02

  Online published: 2013-06-17


Land surface temperature (LST) is one of the key parameters in the physics of land surface processes, and satellite observation is the major way to derive regional LST distribution. However, the pixel observed by satellite is usually a mixture of different land cover types and the temperature of each type seems more meaningful land useful than the mixed pixel temperature. Therefore, component temperature estimation is an important research field. To take use of the rich temporal information imbedded in the geostationary satellite data, a practical approach was proposed to derive the component temperature based on MAP criterion and Markov models in this study. The approach was on the basis of mixed pixel temperature theory and under the assumption that there were only two components in the mixed pixel (vegetation and soil) and the nearby pixels had the same temperature for each component. The method was applied to simulated geostationary satellite data, and the component temperature estimation results showed good agreement with the true values. The RMSEs of vegetation and soil temperature were within 2K for most cases. In addition, the sensitivity analysis of the method to the mixed pixel temperature estimation error, the vegetation fraction cover (FVC) estimation error and its range of the pixels considered in the estimation were conducted. The results indicated that the pixel temperature error and the FVC error showed little effect on the estimation results while the FVC range played an important role in the estimation because of its determinant function on the first guess of the component temperature.

Cite this article

DIAO Wei, LI Ai-Nong, LI Shao-Liang . Component Temperature Estimation from Simulated Geostationary Meteorological Satellite Data Based on MAP Criterion and Markov Models[J]. Journal of Geo-information Science, 2013 , 15(3) : 422 -430 . DOI: 10.3724/SP.J.1047.2013.00422


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