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czynniki klimatu . Wydawnictwo Naukowe PWN, Warszawa: 232-244. Kubiak M., 2009. Metodyka charakterystyki termalnej powierzchni ziemi w oparciu o dane teledetekcyjne. In: L. Kasprzak (ed.), Badania podstawowe i aplikacyjne w naukach geograficznych , Zakład Graficzny UAM, Poznań: 15-21. Paszyński J., 1980. Metody sporządzania map topoklimatycznych. Dokumentacja Geograficzna 3: 13-28. Qin Z., Karnieli A., Berliner P., 2001. A mono-window algorithm for retrieving land surface temperature from Landsat TM data and its application to the Israel-Egypt border region. Remote

). The vulnerability of global cities to climate hazards. Environment and Urbanization , 19, 39-64. Dou, P. and Chen, Y. (2017). Dynamic monitoring of land-use/land-cover change and urban expansion in Shenzhen using Landsat imagery from 1988 to 2015, International Journal of Remote Sensing, 38 (19), 5388-5407. Duan, S.-B., Li, Z.-L. Wang, C., Zhang, S., Tang, B.-H., Leng, P. & Gao, M.-F. (2019). Land-surface temperature retrieval from Landsat 8 single- channel thermal infrared data in combination with NCEP reanalysis data and ASTER GED product. International

References Anbazhagan S., Paramasivam C.R., (2016). Statistical Correlation between Land Surface Temperature (LST) and Vegetation Index (NDVI) using Multi-Temporal Landsat TM Data. Int. Journal of Advanced Earth Science and Engineering 2016, Vol. 5, pp. 333-346. Bannari A., Morin D., Bonn F., Huete A.R., (1995). A review of vegetation indices, Journal Remote Sensing Reviews Volume 13, 1995 - Issue 1-2, Barsi J. C., Tu Q., Davidson E. H., (2014). General approach for in vivo recovery of cell typespecific effector gene sets. Genome Res. Vol. 24, pp. 860

References Alavipanah S., Wegmann, M., Qureshi, S., Weng, Q., Koellner, T. 2015. The Role of Vegetation in Mitigating Urban Land Surface Temperatures: A Case Study of Munich, Germany during the Warm Season, Sustainability , 7 , 4689–4706; DOI: 10.3390/su7044689. Buyantuyev, A., Wu, J. 2010. Urban heat islands and landscape heterogeneity: linking spatiotemporal variations in surface temperatures to land-cover and socioeconomic patterns. Landscape Ecology 25 : 17–33. DOI: 10.1007/s10980-009-9402-4 Carver, S. J. 1991. Integrating multi-criteria evaluation with

olive grove canopy temperature from MODIS thermal imagery is more accurate than interpolation from meteorological stations. Agricultural and Forest Meteorology, 176: 90-93. Blum, M., Lensky, I.M., Rempoulakis, P., Nestel, D. 2015. Modeling insect population fluctuations with satellite land surface temperature. Ecological Modelling , 311: 39–47. Blum, M., Nestel, D., Cohen, Y., Goldshtein, E., Helman, D., Lensky, I.M. 2018. Predicting Heliothis ( Helicoverpa armigera ) pest population dynamics with an age-structured insect population model driven by satellite data

: Getis-Ord Gi* (Spatial Statistics) works [WWW Document]. URL (accessed 2.21.18). Fu, P., Weng, Q., (2016). A time series analysis of urbanization induced land use and land cover change and its impact on land surface temperature with Landsat imagery. Remote Sens. Environ. 175, 205-214. Gaur, A., Eichenbaum, M.K., Simonovic, S.P., (2018). Analysis and modelling of surface Urban Heat Island in

Satellite Derived Land Surface Temperature and High Resolution Air Temperature Observations. Remote Sensing 2016:8:153. [9] Oke T. R. The Heat Island of the Urban Boundary Layer: Characteristics, Causes and Effects . Dordrecht: Springer Netherlands, 1995. [10] Al-Hafiz B. Contribution to the Study of the Impact of Building Materials on the Urban Heat Island and the Energy Demand of Buildings. Environmental Engineering . Ensa Nantes. 2017. [11] Wong E., Akbari H., Bell R., Cole D. Urban Heat Island Basics. Heat Island Compendium

Research and Development Centre, Bandung. [12] Faridah, S. A. N., Krisbiantoro, A. 2014. Land Surface Temperature Distribution Analysis in Potential Area of Geothermal Using Remote Sensing Techniques on Mount Lamongan, Tiris. Berkala Fisika, 17(2), 67–72. [13] Darge, Y. M., Hailu, B. T., Muluneh, A. A., Kidane, T. 2019. Detection of Geothermal Anomalies Using Landsat 8 TIRS Data in Tulu Moye Geothermal Prospect, Main Ethiopian Rift. International Journal Applied Earth Observation and Geoinformation, 74, 16–26. [14] Wright, J., Lillesand, T. M., Kiefer, R. W. 1980. Remote

years to prepare effective methods for deriving this variable from satellite data and applying it to crop estimations for wheat, barley, and maize in Europe and Asia ( Lopez-Lozano et al. 2015 ; Wei et al. 2019 ). On the other hand, among Essential Climatic Variables (ECV), remote-sensing based on the land surface temperature (LST) can be used to estimate plant water-vapor loss (g l , water vapor) ( Miguel Costa et al. 2013 ). This is potentially an indicator of stomatal opening, which in turn is strongly correlated with photosynthesis ( Chaves et al. 2003 ; Jones

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