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Comparison of direct and inverse methods of satellite observations downscaling for the coastal zone area

Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
The Earth observation satellite imaging systems have known limitations, especially regarding their spatial and temporal resolution. Therefore, approaches which aim to combine data retrieved from sensors of higher temporal and lower spatial resolution with the data characterized by lower temporal but higher spatial resolution are of high interest. This allows for joint utilization of the advantages of both these types of sensors. As there are several ways to achieve this goal, in this paper two approaches, direct and inverse, of downscaling the land surface temperature (LST) derived from low resolution imagery acquired by the Advanced Very High Resolution Radiometer (AVHRR) were evaluated. The applied downscaling methods utilize biophysical properties of the surface sensed using short wave infrared and thermal band. The presented algorithm evaluation was performed on the basis of a specific test case: the coastal zone area of the Gulf of Gdańsk, Poland. In this context, the objective presented in the study was to compare two methods of downscaling for a specific test case in order to evaluate how the proposed approaches cope with the specific conditions of the coastal zone area.
Czasopismo
Rocznik
Tom
Strony
55--64
Opis fizyczny
Bibliogr. 11 poz., rys., tab.
Twórcy
autor
  • Gdansk University of Technology Faculty of Electronics, Telecommunications and Informatics Narutowicza 11/12, 80-233 Gdansk, Poland
  • Gdansk University of Technology Faculty of Electronics, Telecommunications and Informatics Narutowicza 11/12, 80-233 Gdansk, Poland
Bibliografia
  • [1] J. J. Seetle, N. A. Drake, Linear mixing and the estimation of ground cover proportions b a Department of Geography, International Journal of Remote Sensing, vol. 14:6, pp. 1559-1177, 1997.
  • [2] H. D. Williamson, Estimating sub-pixel components of a semi-arid woodland, International Journal of Remote Sensing, vol. 15, pp. 3303-3307, 1994.
  • [3] A. J. Arnfield, Two decades of urban climate research: A review of turbulence, exchanges of energy and water, and the urban heat island, International Journal of Climatology, 2003.
  • [4] J. Voogt, T. R. Oke, Thermal remote sensing of urban climates. Remote Sens. Environ., vol. 86, pp. 370–384, 2003.
  • [5] S. Liang, Validation and spatial scaling, in: J. Kong (Ed.), Quantitative Remote Sensing of Land Surfaces, pp. 431-471, New Jersey: Wiley & Sons, 2004.
  • [6] C. K. Munechika, J. S. Warnick, C. Salvaggio, J. R. Schott, Resolution enhancement of multispectral image data to improve classification accuracy, Photogrammetric Engineering and Remote Sensing, vol. 59, 1993.
  • [7] M. Stathopoulou, C. Cartalis, Downscaling AVHRR land surface temperatures for improved surface urban heat island intensity estimation, Remote Sensing of Environment, vol. 113, pp. 2592-2605, 2009.
  • [8] B. J. Choudhury, N. U. Ahmed, S. B. Idso, R. J. Reginato, C. S. T. Daughtry, Relations between evaporation coefficients and vegetation indices studied by model simulations. Remote Sensing of Environment, vol. 50, pp. 1-17, 1994.
  • [9] R. R. Gillies, T. N. Carlson, Thermal remote sensing of surface soil water content with partial vegetation cover for incorporation into climate models, Journal of Applied Meteorology, vol. 34, pp. 745-756, 1995.
  • [10] D. O'Leary, Near optimal parameters for Tikhonov regularization and other regularization methods, SIAM Journal on Scientific Computing, vol. 23:4, pp. 1161- 1171, Society of Industrial and Applied Mathematics, 2001.
  • [11] J. C. Jimenez-Munoz, J. A. Sobrino, Split-window Coefficients for Land Surface Temperature Retrieval from Low-Resolution Thermal Infrared Sensors, IEEE Geoscience and Remote Sensing Letters, vol. 5:4, pp. 806-809, 2008.
Uwagi
PL
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę (zadania 2017)
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-4758163f-44ce-481d-bdc1-0eae53f3fa5c
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