Akbari, E.; Ebrahimi, M.; Fiezizadeh, B. & Nezhadsoleimani, H. 2016. Evaluating Land Surface Temperature related to the Land use Change Detection by Satellite Image (Case study: Taleghan Basin). Geography and Environmental Planning, 26(4): 151-170 (In Persian).
Alavi Panah, K. 2009. Thermal Remote Sensing and Its Application in Earth Sciences, University of Tehran, Second Edition, 524 pages (In Persian).
Allen, R. G.; Bastiaanssen, W. G. M.; Tasumi, M.; Trezza, R. & Waters, R. 2002. Surface Energy Balance Algorithms for Land (SEBAL); Advanced Training and User's Manual.
Anderson, M. C.; Kustas, W. P.; Norman, J. M.; Hain, C. R.; Mecikalski, J. R. & Schultz, L. 2011. Mapping daily evapotranspiration at fi eld to continental scales using geostationary and polar orbiting satellite imagery. Hydrology and Earth System Sciences, 15(1): 223–239.
Bastiaanssen, W. G. M.; Menenti, M.; Feddes, R. A. & Holtslag, A. A. M. 1998. A remote sensing surface energy balance algorithm for land (SEBAL): 1.Formulation. Journal of Hydrology, 198–212.
Carlson, T. 2007. An overview of the “triangle method” for estimating surface evapotranspiration and soil moisture from satellite imagery. Sensors, 7(8): 1612–1629.
Carnahan, W. H. & Larson, R. C. 1990. An analysis of an urban heat sink. Remote Sensing of Environment, 33: 65-71.
Dashtakian, K. & Dehghani, M. A. 2006. Survey of land surface temperature in relation to vegetation and urban development using remote sensing and geographic information systems in desert areas, Case study: Yazd-Ashkzar region. Research and construction in natural resources. 4 (20): 169-179 (In Persian).
Ebrahimi Heravi, B.; Rengzen, k.; Riahi Bakhtiari, H. & Taghizadeh, A. 2016. Determining the most suitable method for extracting the surface temperature using Landsat 8 satellite images in Karaj metropolis. Iranian Journal of Remote Sensing & GIS, 8(3): 59-76 (In Persian).
Feizizadeh, B.; Didehban, K. & Gholamnia, K. 2016. Extraction of Land Surface Temperature (LST) based on Landsat Satellite Images and Split Window Algorithm Study area: Mahabad Catchment. Scientific- Research Quarterly of Geographical Data (SEPEHR), 25(98): 171-181 (In Persian).
Ghorbannia, V.; Mirsanjari, M.; Liaghati, H. & Armin, M. 2017. Estimating land surface temperature of land use and land cover in Dena County using single window algorithm and landsat 8 satellite data. Environmental Sciences, 15(2): 55-74 (In Persian).
Gillies, R. R.; Carlson, T. N.; Cui, J.; Kustas, W. P. & Humes, K. S. 1997. A verification of the ‘triangle’ method for obtaining surface soil water content and energy fluxes from remote measurements of the Normalized Difference Vegetation Index (NDVI) and surface radiant temperature. International Journal of Remote Sensing, 18(15): 3145–3166.
Harlan, S. L.; Brazel, A. J.; Prashad, L.; Stefanov, W. L. & Larsen, L. 2006. Neighborhood microclimates and vulnerability to heat stress. Social Science & Medicine, 63(11): 2847–2863.
Hatefi Ardekani, M. & Rezaei Moghaddam, M. H. 2016. Application of Satellite Images and GIS in the Feasibility of the Use of Solar Energy for Providing Lighting Systems (Case Study: Zanjan - Tabriz Highway). Arid Regions Geographic Studies, 6 (21):105-124 (In Persian).
Hong, S.; Lakshmi, V. & Small, E. E. 2007. Relationship between vegetation biophysical properties and surface temperature using multisensor satellite data. Journal of climate, 20(22): 5593-5606.
Huete, A. R. 1988. A soil-adjusted vegetation index (SAVI). Remote sensing of environment, 25(3): 295-309.
Jahanbakhsh, S.; Zahedi, M. & Valizadeh Kamran, K. 2012. Land Surface Temperature Calculation Using SEBAL and Decision Tree Methods Based on ETM + Image in RS, GIS Environment in the Maragheh Central Region. Geography and Planning, 16(38): 19-42 (In Persian).
Jiang, J. & Tian, G. 2010. Analysis of the impact of land use/land cover change on land surface temperature with remote sensing. Procedia environmental sciences, 2: 571-575.
Jin, M. L.; Dickinson, R. E. & Zhang, D. L. 2005. The footprint of urban areas on global climate as characterized by MODIS. Journal of Climate, 18(10): 1551–1565.
Lafortezza, R; Carrus, G; Sanesi, G. & Davies, C. 2009. Bene fi ts and well-being perceived by people visiting green spaces in periods of heat stress. Urban Forestry & Urban Greening, 8(2): 97–108.
Larson, R. C. & Carnahan, W. H. 1997. The influence of surface characteristics on urban radiant temperatures. Geocarto International, 12: 5-16.
Liu, H. & Weng, Q. 2009. An examination of the effect of landscape pattern, land surface temperature, and socioeconomic conditions on WNV dissemination in Chicago. Environmental Monitoring and Assessment, 159(1–4): 143–161.
Molnár, G. 2016. Analysis of land surface temperature and NDVI distribution for Budapest using Landsat 7 ETM+ data. Acta Climatologica ET Chorologica, 49: 49-61.
Moran, M. S. 2004. Thermal infrared measurement as an indicator of plant ecosystem health. Thermal Remote Sensing in Land Surface Processes, 257–282.
Nduati, E. W.; Mundia, C. N. & Ngigi, M. M. 2013. Effects of Vegetation Change and Land Use/Land Cover Change on Land Surface Temperature in the Mara Ecosystem, International Journal of Science and Research (IJSR), India Online, 2(8): 22- 28.
Rajeshwari, A. & Mani, N. D. 2014. Estimation of Land Surface Temperature of Dindigul District using Landsat 8 Data, IJRET: International Journal of Research in Engineering and Technology, 5(3): 122-126.
Rasooli, A. 2008. Fundamentals of Applied Remote Sensing with Emphasis on Satellite Image Processing, Tabriz University Press, First Edition, 806 pages (In Persian).
Reisen, W.; Lothrop, H.; Chiles, R.; Madon, M.; Cossen, C. & Woods, L. 2004. West Nile virus in California. Emerging Infectious Diseases, 10(8): 1369–1378.
Ruiz, M. O.; Chaves, L. F.; Hamer, G. L.; Sun, T.; Brown, W. M. & Walker, E. D. 2010. Local impact of temperature and precipitation on West Nile virus infection in Culex species mosquitoes in northeast Illinois, USA. Parasites & Vectors, 3(19).
Sun, Y. J.; Wang, J. F.; Zhang, R. H.; Gillies, R. R.; Xue, Y. & Bo, Y. C. 2005. Air temperature retrieved from remote sensing data based on thermodynamics. Theoretical and Applied Climatology, (80)1: 37-48.
Tavosi, T. & Delara, G. 2010. Climate Classification of Ardebil Province. Nivar, 34(71-70): 47-52 (In Persian).
Teillet, P. M.; Staenz, K. & Willams, D. J. 1997. Effects of spectral, spatial, and radiometric characteristics on remote sensing vegetation indices of forested regions. Remote Sensing of Environment, 61: 139–149.
Thenkabail, P. S.; Gamage, M. S. D. N. & Samakhtin, V. U. 2002. Evaluation of narrowband and broadband vegetation indices for determining optimal hyper spectral wavebands for agricultural crop characterization. Photogrammetric Engineering and Remote Sensing, 68: 607–621.
Trenberth, K. E. 1992. Climate system modeling. Cambridge, UK: Cambridge University Press.
Tucker, C. J. 1979. Red and photographic infrared linear combinations for monitoring vegetation, Remote Sensing of Environment, 8: 127–150.
Valizadeh Kamran, Kh.; Rahimpour, T. & Nakhostin Rohi, m. 2016. Estimation of surface temperature using Sabal algorithm and Landsat 8 satellite images (Case study: Urmia). First International Congress on Earth, Space and Clean Energy. Ardabil. Mohaghegh Ardabili University.
https://www.civilica.com/Paper-ATTITTDE01-ATTITTDE01_439.html (In Persian).
Weng, Q. 2009. Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends. ISPRS Journal of Photogrammetry and Remote Sensing, 64(4): 335–344.
Weng, Q.; Lu, D. & Schubring, J. 2004. Estimation of land surface temperature-vegetation abundance relationship for urban heat island studies. Remote sensing of environment, 89: 467-483.