Skip to main content

Thermal infrared inverse model for component temperatures of mixed pixels

Buy Article:

$63.00 plus tax (Refund Policy)

Multiangular remote sensing data can be used to retrieve land surface component temperatures, which will have a broad application in the future. For higher resolution pixels of satellite radiometers, the component temperatures may be separated adequately by some methods. However, for coarse resolution pixels that contain a mixture of vegetation and bare soil, the component temperatures may not be retrieved robustly by traditional inversion methods. In this study, a thermal model-based algorithm was developed for mixed pixels. A simulation method was implemented to assess the performance of the algorithm. The method consisted of extensive radiative transfer simulations under a wide variety of Leaf Area Index (LAI) values in the vegetation part of directional thermal infrared (TIR) radiation, vegetation and soil emissivity, vegetation and soil temperatures, bare soil area ratio and downwelling longwave atmospheric radiation. The results indicate that the inversion error of the component temperatures does not exceed 0.5° when LAI values are less than 6.0. A field experiment was also conducted to assess the accuracy of the model. The experimental results indicate that even if the differences between the nadir and off-nadir radiative temperatures over a mixed pixel are small, the model can still determine the component temperatures accurately. A sensitivity analysis shows that an accuracy of less than 10% for LAI in the vegetation part and the bare soil area ratio is required to achieve a precision of 1 K for the component temperatures derived. An error of 1 K in the radiometric temperature leads to an error of 1 K in the component temperatures retrieved.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Data/Media
No Metrics

Document Type: Research Article

Affiliations: Department of Geography, Nanjing University of Information Science and Technology, Nanjing, China

Publication date: 2011-04-01

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
X
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