Method for estimating the degree of temperature homogeneity of the underlying surface from satellite data
https://doi.org/10.25587/SVFU.2022.27.3.004
Abstract
Spatial resolution is usually understood as the ability to distinguish nearby pixels on a surface. At the same time, if the surface is homogeneous, an additional sign of homogeneity may be required to confirm the fact of equality of pixel estimates. The article considers the possibility of forming a new extreme spectral signature characterizing the degree of temperature homogeneity of the surface of the Earth’s surface based on the measurement of surface temperature by satellite means. A temperature-homogeneous area is usually called those areas in which the brightness temperature at the upper boundary of the atmosphere does not depend on the emissivity, i.e. the TC(E) function is equal to a constant value. However, the equality TC(E)=C; C=const is possible in two cases: (a) if E changes from E_min to E_max, however, TC does not change;(b) if E is unchanged and is equal to a constant value, then TC also does not change. A method for estimating the temperature homogeneity of the studied surface of the earth is proposed. A new indicator of the temperature uniformity of the studied areas of the Earth’s surface has been formed. Using the variational optimization method, it is shown that if the brightness temperature at the upper boundary of the atmosphere is constant within the radiance of the studied area then the proposed new indicator reaches a maximum with the some accepted restriction. The fact of maximum of newly accepted indicator can be used as a sign of the temperature uniformity of the site.
About the Authors
F. G. Agaev
National Aerospace Agency
Azerbaijan
Azerbaijan
AGAEV Fakhraddin Gyulali oglu – Doctor of Technical Sciences, Professor, Director of the Institute of Space Research of Natural Resources
Baku
H. H. Asadov
National Aerospace Agency
Azerbaijan
Azerbaijan
ASADOV Hikmet Hamid oglu – Doctor of Technical Sciences, Professor, Head of a department,. Research Institute of Aerospace Informatics
Baku
E. A. Mammadova
National Aerospace Agency
Azerbaijan
Azerbaijan
MAMEDOVA Esmira Amil gizi – Senior Researcher, Institute of Space Research of Natural Resources
Baku
Yu. G. Danilov
M.K Ammosov North-Eastern Federal University
Russian Federation
Russian Federation
DANILOV Yury Georgievich – Candidate of Geographical Sciences, Professor, Department of Ecology and Geography¸ Institute of Natural Sciences
Yakutsk
References
1. Li Z.L., Tang B.H., Wu H., Ren H., Yan G., Wan Z., Trigo I.F., Sobrino J.A. Satellite-derived land surface temperature: current status and perspectives// Remote Sens. Environ. – 2013. – vol. 131. – P. 14-37.
2. Barsi J.A., Barker J.L., Schott J.R. An atmospheric correction parameter calculator for a single thermal band earth-sensing instrument // In processdings of the 2003 IEEE International Geoscience and Remote Sensing Semposium. IGARSS 03. Melbourne, Australia. 21 – 25 July 2003. – vol. 5. – P. 3014-3016.
3. Tang H., Li Z.L. Introduction // In quantitative remote sensing in thermal infrared. – Springer: Germany, 2014. – P. 1-4.
4. Li Z.L., Wu H., Wang N., Qiu S., Sobrino J.A., Wan Z., Tang B.H., Yan G. Land surface emissivity retrieval from satellite data // Int. J. Remote Sens. – 2013. – vol. 34. – P. 3084-3127.
5. Walker J.J., De Beurs K.M., Wynne R.H., Gao F. Evaluation of landsat and MODIS data fusion products for analysis of dryland forest phenology // Remote Sens. Environ. – 2012. – vol. 117. – P. 381-393.
6. Copertino V.A., Di Pietro M., Scavone G., Telesca V. Comparison of algorithms to retrieve land surface temperature from Landsat-7 ETM+IR data in the Basilicata Ionian band // Tethys. – 2012. – vol. 9. – P. 25-34.
7. US Geological Survey Landsat Missions. [Jelektronnyj resurs]. – Rezhim dostupa: https://www.usgs.gov/core-science-systems/nli/landsat/landsat-5?qt-science_support_page_related_con=0#qt-science_support_page_related_con (data obrashhenija: 12.09.2021).
8. US Geological Survey Landsat Missions. [Jelektronnyj resurs]. – Rezhim dostupa: https://www.usgs.gov/core-science-systems/nli/landsat/landsat-7?qt-science_support_page_related_con=0#qt-science_support_page_related_con (data obrashhenija: 12.09.2020).
9. US Geological Survey Landsat Missions. [Jelektronnyj resurs]. – Rezhim dostupa: https://www.usgs.gov/core-science-systems/nli/landsat/landsat-8?qt-science_support_page_related_con=0#qt-science_support_page_ elated_con (data obrashhenija: 12.09.2020).
10. Guillevic P., Göttsche F., Nickeson J., Hulley G., Ghent D., Yu Y., Trigo I., Hook S., Sobrino J.A., Remedios J., Roman M., Camacho F. Land surface temperature product validation best practice protocol version 1.1 // Good Practices for Satellite-Derived Land Product Validation. Land Product Validation Subgroup. – 2018. – vol. 58, DOI:10.5067/doc/ceoswgcv/lpv/lst.001.
11. Avdan U., Jovanovska G. Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data // J. Sensors. – vol. 2016. – 8 p., DOI:10.1155/2016/1480307.
12. US Geological Survey Using the USGS Landsat Level-1 data product. [Jelektronnyj resurs]. – Rezhim dostupa: https://www.usgs.gov/core-science-systems/nli/landsat/using-usgs-landsat-level-1-data-product (data obrashhenija: 25.07.2021).
13. Qin Z., Karnieli A., Berliner P. A mono-window algorithm for retrieving land surface temperature from landsat TM data and its application to the Israel – Egypt border region // International Journal of Remote Sensing. – 2010. – vol. 22(18). – P. 3719-3746.
14. Carlson T.N., Ripley D.A. On the relation between NDVI, fractional vegetation cover, and leaf area index // Remote Sens. Environ. – 1997. vol. 62. -P. 241-252, DOI:10.1016/S0034-4257(97)00104-1.
15. Sobrino J.A., Jimenez-Munoz J.C., Paolinin L. Land surface temperature retrieval from LANDSAT TM5 // Remote. Sens. Environ. – 2004. – vol. 90. – P. 434-440, DOI:10.1016/j.rse.2004.02.003.
16. Rouse J.W., Haas R.H., Schell J.A., Deering D.W. Monitoring Vegetation Sestems in the Great Plains with ERTS // NASA: Washington, DC, 1974. – Pp. 309-317.
Review
For citations:
Agaev F.G., Asadov H.H., Mammadova E.A., Danilov Yu.G. Method for estimating the degree of temperature homogeneity of the underlying surface from satellite data. Vestnik of North-Eastern Federal University Series "Earth Sciences". 2022;(3):44-51. (In Russ.) https://doi.org/10.25587/SVFU.2022.27.3.004
Views:
194
Email this article 