Skip to main content
padlock icon - secure page this page is secure

Remotely sensed retrieval of midday air temperature considering atmospheric and surface moisture conditions

Buy Article:

$60.00 + tax (Refund Policy)

Near-surface air temperature (T a) is an important variable for various scientific communities, and many previous studies have attempted to estimate T a with high spatial resolution using remotely sensed data. The present study proposes a new, practical method for estimating T a near the land surface based on moisture conditions of the atmosphere and surface. First, match-up data sets of ground observations from 76 meteorological stations and satellite remote-sensing observations were established over the Republic of Korea during 2006. Four cases of atmospheric and surface moisture conditions were then determined using Moderate Resolution Imaging Spectroradiometer brightness temperatures (at 11 and 12 μm) and the normalized difference water index for all match-ups. Using stepwise multiple regression analysis for each case, land surface temperature and the normalized difference vegetation index were statistically selected as significant independent variables for estimating T a using the development data set (75% of the match-ups for each case). The T a values estimated from the multiple regression algorithm with different constants and coefficients for each case showed reasonably good performance (nearly zero mean bias and approximately 3°C root mean square error) compared with the measured T a values used as the validation data set (25% of the match-ups for each case). Thus, the proposed T a estimation approach based on moisture conditions of the atmosphere and surface is not confined to a specific season or land type and can be applied to all areas and seasons in the Republic of Korea.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Document Type: Research Article

Affiliations: 1: Brain Korea 21 Graduate School of Earth Environmental System,Pukyong National University, Busan,608-737, Korea 2: Department of Spatial Information Engineering,Pukyong National University, Busan,608-737, Korea

Publication date: January 10, 2013

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more