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2016 | 23 | 1 |

Tytuł artykułu

Characterizing surface and air temperature in the Baltic Sea coastal area using remote sensing techniques and GIS

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Estimation of surface temperature using multispectral imagery retrieved from satellite sensors constitutes several problems in terms of accuracy, accessibility, quality and evaluation. In order to obtain accurate results, currently utilized methods rely on removing atmospheric fluctuations in separate spectral windows, applying atmospheric corrections or utilizing additional information related to atmosphere or surface characteristics like atmospheric water vapour content, surface effective emissivity correction or transmittance correction. Obtaining accurate results of estimation is particularly critical for regions with fairly non-uniform distribution of surface effective emissivity and surface characteristics such as coastal zone areas. The paper presents the relationship between retrieved land surface temperature, air temperature, sea surface temperature and vegetation indices (VI) calculated based on remote observations in the coastal zone area. An indirect comparison method between remotely estimated surface temperature and air temperature using LST/VI feature space characteristics in an operational Geographic Information System is also presented

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  • Gdansk University of Technology, 11/12 Narutowicza St., 80-233 Gdansk, Poland
  • Gdansk University of Technology, 11/12 Narutowicza St., 80-233 Gdansk, Poland
  • Gdansk University of Technology, 11/12 Narutowicza St., 80-233 Gdansk, Poland


  • 1. Chen F., Dudia J.: Coupling an advanced land-surface / hydrology model with the Penn State/NCAR MM5 modeling system. Monthly Weather Review, 129/2001, 569-585.
  • 2. Chen, F., K. Mitchell, J. Schaake, Y. Xue, H. Pan, V. Koren, Y. Duan, M. Ek, and A. Betts, 1996: Modeling of landsurface evaporation by four schemes and comparison with FIFE observations. J. Geophys. Res., 101, 7251-7268.
  • 3. Cracknell A. P.: The Advanced Very High resolution Radiometer (AVHRR). Taylor and Francis, 1997.
  • 4. Cristobal J., Poyatos R., Ninyerola M., Llorens P.: Combining remote sensing and GIS climate modelling to estimate daily forest evapotranspiration in a Mediterranean mountain area. Hydrology and Earth System Sciences Discussions, 15/2011, 1563-1575.
  • 5. Dąbrowski J., Kulawiak M., Moszyński M., Bruniecki K., Kamiński Ł., Chybicki A., Stepnowski A.: Real-time web-based GIS for analysis, visualization and integration of marine environment data. In: Information Fusion and Geographic Information Systems, Springer Berlin Heidelberg, 2009, 277-288.
  • 6. Dash P.: Land Surface Temperature and Emissivity Retrieval from Satellite Measurements. Institut fur Meteorologie und Klimaforshung, 2005.
  • 7. Donner L. J., Wyman B. L., Hemler R. S., Horowitz L.W., Ming Y., Zhao M., Golaz J.-C., Ginoux P., Lin S.J., Schwarzkopf M. D., Austin J., Alaka G., Cooke W. F., Delworth T. L., Freidenreich S. M., Gordon C. T., Griffies S. M., Held I. M., Hurlin W. J., Klein S. A., Knutson T. R., Langenhorst A. R., Lee H.-C., Lin Y., Magi B. I., Malyshev S. L., Milly P. C., Naik V., Nath M. J., Pincus R., Ploshay J. J., Ramaswamy V., Seman C. J., Shevliakova E., Sirutis J. J., Stern W. F., Stouffer R. J., Wilson R.J., Winton M., Wittenberg A. T., Zeng F.: The dynamical core, physical parameterizations, and basic simulation characteristics of the atmospheric component AM3 of the GFDL Global Coupled Model CM3. Journal of Climate, 24(13)/2011, 3484-3519.
  • 8. Ferrier B. S., An efficient mixed-phase cloud and precipitation scheme for use in operational NWP models, Eos, Trans. Amer. Geophys. Union, 86(18)/2005.
  • 9. Gillies R. R., Carlson T. N., Cui J., Kustas W. P., Humes K. S.: Verification of the ‘triangle’ method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index NDVI and surface radiant temperature. International Journal of Remote Sensing 18/1997, 3145-3166.
  • 10. Grell, G. A., D. Devenyi: A generalized approach to parameterizing convection combining ensemble and data assimilation techniques. Geophys. Res. Lett., 29/2002, 1693-1696.
  • 11. Jain S. K., Hariprasad V., Choudhry A.: Water Balance Study for a Basin Integrating Remote Sensing Data and GIS. Journal of the Indian Society of Remote Sensing 39/2011, 259-270.
  • 12. Janjic Z. I., Gerrity J. P., Nickovic S.: An Alternative Approach to Nonhydrostatic Modeling. Monthly Weather Review, 129/2001, 1164-1178.
  • 13. Janowski A., Nowak A., Przyborski M., Szulwic J.: Mobile indicators in GIS and GPS positioning accuracy in cities. In: Rough Sets and Intelligent Systems Paradigms, Springer International Publishing, 2014, 309-318.
  • 14. Julien Y., Sobrino J. A., Mattar C., Ruescas A. B., JimenezMunoz J. C., Soria G., Hidalgo V., Atitar M., Franch B., Cuenca J.: Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001. International Journal of Remote Sensing, 32/2011, 2057-2068.
  • 15. Kulawiak M., Chybicki A., Moszyński M.: Web-based GIS as a tool for supporting marine research. Marine Geodesy, 33/2010, 135-153.
  • 16. Kulawiak M., Łubniewski Z.: SafeCity - A GIS-based tool profiled for supporting decision making in urban development and infrastructure protection. Technological Forecasting and Social Change, 89/2014, 174-187.
  • 17. Lillesand T. M., Kiefer R. W.: Remote Sensing and Image Interpretation. John Wiley, New York, 1987.
  • 18. McClain E. P., Pichel W. G., Walton C. C.: Comparative performance of AVHRR-based multichannel sea surface temperatures. Journal of Geophysical Research, 90/1985, 11587-11601.
  • 19. Michalakes J., Dudhia J., Gill D., Henderson T., Klemp J., Skamrock W., Wang W.: The Weather Research and Forecast Model: Software Architecture and Performance. Proceedings of the 11th ECMWF Workshop on the Use of High Performance Computing in Meteorology, 25-29 October 2004, Reading, U.K., Ed. George Mozdzynski.
  • 20. Moszyński M., Kulawiak M., Chybicki A., Bruniecki K., Bieliński T., Łubniewski Z., Stepnowski A., Innovative Web-Based Geographic Information System for Municipal Areas and Coastal Zone Security and Threat Monitoring Using EO Satellite Data, Marine Geodesy, Volume 38(3)/2015, 203-224.
  • 21. Pons X., Ninyerola M.: Mapping a topographic global solar radiation model implemented in a GIS and refined with ground data. International Journal of Climatology 28/2008, 1821-1834.
  • 22. Prihodko L., Goward S. N.: Estimation of air temperature from remotely sensed surface observations. Remote Sensing of Environment, 60/1997, 335-346.
  • 23. Qin Z., Dall’Olmo G., Karnieli A., Berliner P.: Derivation of split window algorithm and its sensitivity analysis for retrieving land surface temperature from NOAA Advanced Very High Resolution Radiometer data. Journal of Geophysical Research: Atmospheres (1984–2012), 106/2001, 22655-22670.
  • 24. Riddering J. P., Queen L. P.: Estimating near-surface air temperature with NOAA AVHRR. Canadian Journal of Remote Sensing, 32/2006, 33-43.
  • 25. Sobrino J. A., Raissouni N.: Toward remote sensing methods for land cover dynamic monitoring: application to Morocco. International Journal of Remote Sensing 21/2000, 353-366.
  • 26. Ulivieri C., Castronuovo M. M., Francioni R., Cardillo A.: A split window algorithm for estimating land surface temperature from satellites. Advances in Space Research, 14/1996, 279-1292.
  • 27. Vidal A.: Atmospheric and emissivity correction of land surface temperature measured from satellite using ground measurements or satellite data, International Journal of Remote Sensing, 12/1991, 2449-2460.
  • 28. Wilson J., Rocha C.: Regional scale assessment of Submarine Groundwater Discharge in Ireland combining medium resolution satellite imagery and geochemical tracing techniques. Remote Sensing of Environment, 119/2012, 21-34.
  • 29. Zheng X., Zhu J., Yan Q.: Monthly Air Temperatures over Northern China Estimated by Integrating MODIS Data with GIS Techniques. Journal of Applied Meteorology and Climatology, 52/2013, 1987-2000.
  • 30. Zurita-Milla R., Blok C., Retsios V.: Geovisual analytics of Satellite Image Time Series. International Environmental Modelling and Software Society (iEMSs) 2012 International Congress on Environmental Modelling and Software. Managing Resources of a Limited Planet: Pathways and Visions under Uncertainty, Sixth Biennial Meeting, Leipzig, Germany, 2012.

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