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Joanna Jędruszkiewicz and Mariusz Zieliński

References Chavez P.S., jr. (1996) Image-based atmospheric corrections - Revisited and Improved, Photogrammetric Engineering and Remote Sensing, 62, 9, 1025-1036 Chander G., Markham B.L., Helder D.L. (2009) Symmary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors, Remote Sensing of Environment, 113, 893-903 Fortuniak K. (2003) Miejska wyspa ciepła. Podstawy energetyczne, studia eksperymentalne, modele numeryczne i statystyczne., Wydawnictwo UŁ, Łódź (in Polish

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Stanisław Lewiński

. Proc. of the 25 th Symp. Eur. Assoc. Rem. Sens. Laborat. Porto, Portugal, 6-9 June 2005. Global Developments in Environmental Earth Observation from Space. Mitri G.H., Gitas I.Z., 2002. The development of an object-oriented classification model for operational burned area mapping on the Mediterranean island of Thasos using Landsat TM images. Proc. Intern. Conf. Forest Fire Research, Luso - Coimbra, Portugal, 18-23 November, 2002. Neubert M., 2001. Segment-based analysis of high resolution satellite and laser

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Paul Macarof, Stefan Groza and Florian Statescu

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

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Raghvendra Singh and P. Rama Chandra Prasad

REFERENCES 1. M.J.Pringle, M. Schmidt, and J.S.Muir, Geo-statistical interpolation of SLC-off Landsat ETM plus images, ISPRS Journal of Photogrammetry and Remote Sensing, 64,654–664, 2009. 2. Feng Chen, Xiaofeng Zhao, and Hong Ye, Making Use of the Landsat 7 SLC-off ETM+ Image Through Different Recovering Approaches, Data Acquisition Applications, Prof. Zdravko Karakehayov (Ed.), ISBN: 978-953-51-0713-2, InTech, DOI: 10.5772/48535, 2012. Available from: http://www.intechopen.com/books/data-acquisition-applications/making-use-of-the-landsat-7-slc

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Paul Macarof and Florian Statescu

Cover , 2012 Orhan O., Ekercin S., Dadaser-Celik F., Use of Landsat Land Surface Temperature and Vegetation Indices for Monitoring Drought in the Salt Lake Basin Area , 2014 Price J. C., Using spatial context in satellite data to infer regional scale evapotranspiration , 1990 Purevdorj T. S., Tateishi R., Ishiyama T., Relationships between percent vegetation cover and vegetation indices , 1998 Rouse J. W., Haas R. H., and Schell J. A., Monitoring the vernal advancement and retrogradation (greenwave effect) of natural vegetation , Texas A

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Tayeb Sitayeb and Ishak Belabbes

urbanization. ApplGeograp; 29(4): 390-401. Dube, T., Mutanga, O. (2015). Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa. ISPRS J. Photogramm. Remote Sens. 101: 36-46. http://dx.doi.org/10.1016/j.isprsjprs.2014.11.001. Güler M, Yomralio_glu T, Reis S. (2007). Using Landsat data todetermine land use/land cover changes in Samsun, Turkey. Environ Monitor Assess; 127: 155-67. Knorn, J., Rabe, A., Radeloff, V

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M. Hashemimanesh, H. Matinfar, S. Alavipanah and G. Zehtabian

References Brady N. C. and Weil R. R., 1999 . The Nature and Properties of Soils. Prentice Hall Press, Upper Saddle River, NJ, USA. Cheng K. S. and Lei T. C., 2001 . Reservoir trophic state evaluation using Landsat TM images. J. Am. Water Res. Assoc., 37(5), 1321-1334. Czyż E. A. and Dexter A. R., 2009 . Soil physical properties as affected by traditional, reduced and no-tillage for winter wheat. Int. Agrophysics, 23, 319-326. Dahiya R., Ingwersen J., and

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Orsolya Gémes, Zalán Tobak and Boudewijn van Leeuwen

temperature mapping modelling. Climate Researches 60, 51-62. DOI: 10.3354/cr01220 Mallick, J., Singh, C.K., Shashtri, S., Rahman, A., Mukherjee, S. 2012. Land surface emissivity retrieval based on moisture index from LANDSAT TM satellite data over heterogeneous surfaces of Delhi city. International Journal of Applied Earth Observation and Geoinformation 19, 348-358. DOI: 10.1016/j.jag.2012.06.002 Moran, M., Jackson, R., Slater, P., Teillet, P. 1992. Evaluation of simplified procedures for retrieval of land surface reflectance factors from

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Marta Kubiak and Alfred Stach

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 Sensing 22(18): 3719-3746. Sobrino J.A., Jimenez-Munoz J.C., Paolini L., 2004. Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing, Environment 90: 434-440. Stanisz A., 2007. Przystępny kurs statystyki z zastosowaniem STATISTICA PL na przykładach medycznych, Tom 2. Modele

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Hana Vinciková, Jan Procházka and Jakub Brom

classification of neighboring Landsat satellite images. Remote Sens Environ 113: 957-964. Lelong CCD, Pinet PC, Poilve H (1998): Hyperspectral imaging and stress mapping in agriculture: A case study on wheat in Beauce (France). Remote Sens Environ 66: 179-191. Lillesand TM, Kiefer RW, Chipman JW (2004): Remote sensing and image interpretation. John Wiley and Sons, New York. Nellis MD, Tao Y (1999): Reflectance heterogeneity in a tallgrass prairie national preserve based on ground based measurement