Accuracy assessment of the temperature of artificial and natural Earth’s surfaces determining by infrared satellite imagery

1Stankevich, SA, 2Pylypchuk, VV, 3Lubskyi, MS, 3Krylova, HB
1State institution «Scientific Centre for Aerospace Research of the Earth of the Institute of Geological Sciences of the National Academy of Sciences of Ukraine», Kyiv, Ukraine
2Yevheniy Bereznyak Military-diplomatic Academy, Kyiv, Ukraine
3State institution «Scientific Centre for Aerospace Research of the Earth Institute of Geological Science National Academy of Sciences of Ukraine», Kyiv, Ukraine
Space Sci.&Technol. 2016, 22 ;(4):19-28
https://doi.org/10.15407/knit2016.04.019
Publication Language: Ukrainian
Abstract: 
The model and the special application software for evaluation of land surface temperature by remote sensing in a thermal infrared band are developed. The model takes into account the atmosphere effect and land surface thermal emissivity. For the evaluation of the model’s accuracy, the ground temperature measurements using portable pyrometer were conducted simultaneously with the satellite imaging of the studied area. The obtained temperature maps help to detect objects that deliver considerable heat load on the environment, to estimate the distribution and dynamics of special effects such as “heat islands” and to develop a strategy on mitigation the negative effects of urban environment heat pollution.
Keywords: emissivity, ground truth measurements., physical temperature, satellite imagery, thermal field
References: 
1. Kriksunov L. Z. Handbook on the Foundations of Infrared Equipment, 400 p. (Sov. Radio, Moscow, 1978) [in Russian].
2. Lubsky M. S., Krylova G. B. The method of calculating the surface temperature data output of the far infrared. Materials of II All-Ukrainian scientific-practical conference "Theoretical and applied aspects of mathematical methods and information technologies in science, education, economics and production”, 82―85 (MSU, Mariupol, 2015) [in Ukrainian].
3. Lutsyk Ya.T., Guk O.P., Lakh O.I., Stadnyk B.I. Temperature measurements: theory and practice, 560 p. (Publishing House «Beskyd Bit», Lviv, 2006) [in Ukrainian].
4. Popov M. O., Stankevych S. A. Method for increase of spatial resolution of multi-spectral aero-space images on basis of classification of spectral signatures of objects. Pat. 84877 Ukraine, MPK G06K 9/00, No. a200602244; Zajavl. 01.03.2006;  published 10.12.2008, Bull. No. 23, [in Ukrainian].
5. Stankevich S., Piestova I., Godyna O., Filozof R. Vegetation quality remote assessment in urban area: Golosiivsky NNP case study. Nauk. dopovidi NUBiP Ukrai'ny,  No. 2 (51), 12 p. (2015) [in Ukrainian]. http://nd.nubip.edu.ua/2015_2/5.pdf
6. Stankevich S. A., Filippovich V. E., Lubsky N. S., et al. Intercalibration of methods for the land surface thermodynamic temperature retrieving inside urban area by thermal infrared satellite imaging. Ukr. zhurn. dystancijnogo zonduvannja Zemli, No. 7, 14―23 (2015) [in Russian].
7. Barsi J. A., Barker J. L., Schott J. R. An atmospheric correction parameter calculator for a single thermal band Earth-sensing instrument. Proceedings of the International Geoscience and Remote Sensing Symposium (IGARRS’03), 3014―3016 (IEEE, Toulouse, 2003).
https://doi.org/10.1109/igarss.2003.1294665 
8. Chander G., Markham B. L., Helder D. L. Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, 113 (5), 893―903 (2009).
https://doi.org/10.1016/j.rse.2009.01.007 
9. Dubuisson P., Giraud V., Chomette O., et al. Fast radiative transfer modeling for infrared imaging radiometry. J. Quant. Spectrosc. and Radiat. Transfer, 95 (2), 201―220 (2005).
https://doi.org/10.1016/j.jqsrt.2004.09.034
10. Ibarra-Castanedo C., González D., Klein M., et al. Infrared image processing and data analysis. Infrared Phys. and Technol., 46 (1-2), 75―83 (2004).
https://doi.org/10.1016/j.infrared.2004.03.011
11. Krylova H. B., Lubskiy N. S. Remote monitoring of the thermal field at urbanized area, taking Kyiv city as an example. Proceeding of 3rd International Conference on GIS and Remote Sensing, 149―156 (Environmental Research and GIS Center, Tsaghkadzor, 2014).
12. Perez Hoyos I.C. Comparison between land surface temperature retrieval using classification based emissivity and NDVI based emissivity. Int. J. Recent Development in Engineering and Technol., 2 (2), 26―30 (2014).
13. Zhang Z. M., Tsai B. K., Machin G. (Eds) Radiometric Temperature Measurements Fundamentals, 356 p. (Academic Press, Amsterdam, 2010).
14. Snyder W. C., Wan Z., Zhang Y., et al. Classification-based emissivity for land surface temperature measurement from space. Int. J. Remote Sensing, 19 (14), 2753―2774 (1998).
https://doi.org/10.1080/014311698214497
15. Stankevich S. A., Filippovich V. E. Infrared satellite imaging for the study of urban heat islands in Ukraine. Proceedings of 8th International Green Energy Conference (IGEC-8), 219―223 (NAU, Kiev, 2013).
16. Van de Griend A. A., Owe M. On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. Int. J. Remote Sensing, 14 (6), 1119―1131 (1993).
https://doi.org/10.1080/01431169308904400

17. Yang H., Zhang L.F., Zhang X., et al. Algorithm of emissivity spectrum and temperature separation based on TASI data. J. Remote Sensing, 15 (6), 1242―1254 (2011).