• DocumentCode
    1035267
  • Title

    Inverse problems theory and application: analysis of the two-temperature method for land-surface temperature and emissivity estimation

  • Author

    Peres, Leonardo F. ; DaCamara, Carlos C.

  • Author_Institution
    Centro de Geofisica, Univ. de Lisboa, Lisbon, Portugal
  • Volume
    1
  • Issue
    3
  • fYear
    2004
  • fDate
    7/1/2004 12:00:00 AM
  • Firstpage
    206
  • Lastpage
    210
  • Abstract
    The two-temperature method (TTM) allows the separation of land-surface temperature and land-surface emissivity information from radiance measurements, and therefore, the solution can be uniquely determined by the data. However, the inverse problem is still an ill-posed problem, since the solution does not depend continuously on the data. Accordingly, we have used some mathematical tools, which are suited for analyses of ill-posed problems in order to show TTM properties, evaluate it, and optimize its estimations. Related to this last point, we have shown that it is necessary to constrain the problem, either by defining a region of physically admissible solutions and/or by using regularization methods, in order to obtain stable results. Besides, the results may be improved by using TTM with systems that possess a high temporal resolution, as well as by acquiring observations near the maximum and minimum of the diurnal temperature range.
  • Keywords
    inverse problems; terrain mapping; emissivity estimation; ill-posed problems; inverse problems theory; land-surface emissivity information; land-surface temperature; radiance measurements; regularization methods; two-temperature method; Information analysis; Information retrieval; Information theory; Inverse problems; Land surface; Land surface temperature; Satellites; Temperature distribution; Temperature sensors; Time to market; Emissivity; LST; SVD; information theory; infrared imaging; inverse problems; land surface temperature; remote sensing; singular value decomposition;
  • fLanguage
    English
  • Journal_Title
    Geoscience and Remote Sensing Letters, IEEE
  • Publisher
    ieee
  • ISSN
    1545-598X
  • Type

    jour

  • DOI
    10.1109/LGRS.2004.830613
  • Filename
    1315633