Analysis of Climate Change in the Area of Vojvodina-Republic of Serbia and Possible Consequences

Updata:01-01-1970

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By:Mirko Andreja Borisov

DOI: https://doi.org/10.30564/jgr.v2i2.952

Abstract:

Climate change conditions a wide range of impacts such as the impact on weather, but also on ecosystems and biodiversity, agriculture and forestry, human health, hydrological regime and energy. In addition to global warming, local factors affecting climate change are being considered. Presentation and analysis of the situation was carried out using geoinformation technologies (radar recording, remote detection, digital terrain modeling, cartographic visualization and geostatistics). This paper describes methods and use of statistical indicators such as LST, NDVI and linear correlations from which it can be concluded that accelerated construction and global warming had an impact on climate change in period from 1987 to 2018 in the area of Vojvodina – Republic of Serbia. Also, using the global SRTM DEM, it is shown how the temperature behaves based on altitude change. Conclusions and possible consequences in nature and society were derived.

References:

[1] Carlson, T.N. and Ripley, D.A. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 1997, 2(3): 241–252. [2] 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, 2009, 113(5): 893-903. [3] Danodia, A., Nikam, R. B., Kumar, S., Patel, N.R. Land surface temperature retrieval by radiative transfer equation and single channel algorithms using landsat-8 satellite data. Indian Institute of Remote Sensing- ISRO, 4- Kalidas road, Dehradun-248001, 2017. [4] Dos Santos, G.M., Meléndez-Pastor, I., Navarro-Pedreño, J., Gómez Lucas, I., A Review of Landsat TM/ETM based Vegetation Indices as Applied to Wetland Ecosystems. Journal of Geographical Research, 2019, 2(1): 35-49. [5] Easterling, D.R., Meehl, G.A., Parmesan, C., Changnon, S.A., Karl, T.R., Mearns, L.O. Climate extremes: observations, modeling, and impacts. Science, 2000, 289: 2068–2074. [6] Greenough, G., McGeehin, M., Bernard, S.M., Trtanj, J., Riad, J. and Engelberg, D. The potential impacts of climate variability and change on health impacts of extreme weather events in the United States. Environmental Health Perspectives 109 Suppl. 2, 2001, 191–198. [7] Kerr, Y.H., Lagouarde, J.P., Nerry, F., Ottlé, C. Land surface temperature retrieval techniques and applications. In D. A. Quattrochi, & J. C. Luvall (Eds.), Thermal remote sensing in land surface processes. Boca Raton, Fla.: CRC Press, 2000: 33–109. [8] Li, Z.-L. and Becker, F. Feasibility of land surface temperature and emissivity determination from AVHRR data. Remote Sensing of Environment, 1993, 43(1): 67–85. [9] Mallick, J. Kant, Y., Bharat, B.D. Estimation of land surface temperature over Delhi using Landsat-7 ETM+. Journal of Indian Geophysical Union, 2008, 12(3): 131-140. [10] Nikam, B. R., Ibragimov, F., Chouksey, A., Garg, V., Aggarwal, S. P. Retrieval of land surface temperature from Landsat 8 TIRS for the command area of Mula irrigation project. Environmental Earth Sciences, 2016, 75: 1-17. [11] Pettorelli, N., Vik, J.O., Mysterud, A., Gaillard, J., Tucker, C.J., Stenseth, N.C. Using the satellite-derived NDVI to assess ecological responses to environmental change. Trends in Ecology and Evolution, 2005, 20: 503–510. [12] Popović, T., Đurđević, V., Živković, M., Jović, B., Jovanović, M. Promena klime u Srbiji“, Agencija za zaštitu životne sredine, Ministarstvo životne sredine i prostornog planiranja, Institut za meteorologiju, Fizički fakultet, Univerzitet u Beogradu, 2009. [13] Robinson, W.H. Urban Insects and Arachnids: a Handbook of Urban Entomology. Cambridge University Press, Cambridge, UK, 2005. [14] Rolston, H. Conserving Natural Value. Columbia University Press, New York, USA, 1994. [15] Rouse, J.W., Haas, R.H., Schell, J.A., Deering, D.W. Monitoring vegetation systems in the Great Plains with ERTS. Proceedings of 3rd ERTS Symposium, NASA SP-351 I, 1973: 309–317. [16] Saini, V. and Tiwari, K. Effect of urbanization on land surface temperature and NDVI: a case study of dehradun, India. Conference: 38th Asian Conference on Remote Sensing, New Delhi, 2017. [17] Sobrino, J. A., Jiménez-Muñoz, J. C., Paolini, L. Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of Environment, 2004, 90: 434-440. [18] Tucker, C. J. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing Environment, 1979, 8: 127-150. [19] Valor, E. and Caselles, V. Mapping land surface emissivity from NDVI: application to European, African, and South American areas. Remote Sensing of Environment, 1996, 57(3): 167–184. [20] Van de Griend, A. A. and Owe, M. On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. International Journal of Remote Sensing, 1993, 14(6): 1119–1131. [21] Weng, Q., Lu, D., Schubring, J. Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 2004, 89(4): 467-483. [22] Yu, X., Guo, X., Wu, Z. Land Surface Temperature Retrieval from Landsat 8 TIRS- Comparison between Radiative Transfer Equation-Based Method, Split Window Algorithm and Single Channel Method. Remote sensing, 2014, 6: 9829-9852.

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