Abstract
Determination of LULC (land use/land cover) changes in urban planning studies is very important. However, LST (land surface temperature) and UHI (urban heat island) directly associated with LU changes are the parameters that should be considered in similar studies. Therefore, Remote Sensing (RS) and Geographic Information Systems (GIS) are commonly used for obtaining this kind of information. In this study, the relationship between LULC, NDVI (Normalized Difference Vegetation Index) and LST in Sivas city center and its surroundings was studied by using Landsat satellite images from 1989 to 2015 and UHI intensity was also demonstrated. The results clearly show that the urban built-up areas and agricultural lands increased while barren land decreased over the study period. The changes in LST can be monitored depending on the construction materials such as the presence of green areas, the city’s unique geographical location and topography. Urban built-up and bare lands have the highest LST and the urban built-up surface temperature showed a fluctuating trend while the rural area temperature showed a tendency to decrease. The urban built-up areas increased, a positive UHI intensity was observed and also an urban heat island formation was determined.
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Alonso, M.S., Fidalgo, M.R., Labajo, J.L.: The urban heat island in Salamanca (Spain) and its relationship to meteorological parameters. Clim. Res. 34, 39–46 (2007)
Amanollahi, J., Tzanis, C., Abdullah, A.M., Ramli, M.F., Pirasteh, S.: Development of the models to estimate particulate matter from thermal infrared band of Landsat enhanced thematic mapper. Int. J. Environ. Sci. Technol. 10, 1245–1254 (2013)
Amanollahi, J., Tzanis, C., Ramli, M.F., Abdullah, A.M.: Urban heat evolution in a tropical area utilizing Landsat imagery. Atmos. Res. 167, 175–182 (2016)
Agarwal, M., Tandon, A.: Modeling of the urban heat island in the form of mesoscale wind and of its effect on air pollution dispersal. Appl. Math. Model. 34, 2520–2530 (2010)
Anderson, J. R., E. E. Hardy, J. T. Roach, and R. E. Witmer, 1976: A land use and land cover classification system for use with remote sensor data. US government printing office. DC: U.S. Geological Survey. No. Professional Paper 964, Washington
Bagan, H., Takeuchi, W., Kinoshita, T., Bao, Y., Yamagata, Y.: Land cover classification and change analysis in the Horqin sandy land from 1975 to 2007. IEEE J Sel Top Appl Earth Obs Remote Sens. 3(2), 168–177 (2010)
Bagan, H., Yamagata, Y.: Landsat analysis of urban growth: how Tokyo became the world's largest megacity during the last 40 years. Remote Sens. Environ. 127, 210–222 (2012)
Bakr, N., Weindorf, D.C., Bahnassy, M.H., Marei, S.M., Badawi, M.M.E.: Monitoring land cover changes in a newly reclaimed area of Egypt using multi-temporal Landsat data. Appl. Geogr. 30, 592–605 (2010)
Balcik, F.B.: Determining the impact of urban components on land surface temperature of Istanbul by using remote sensing indices. Environ. Monit. Assess. 186(2), 859–872 (2014)
Bokaie, M., Zarkesh, M.K., Arasteh, P.D., Hosseini, A.: Assessment of urban heat island based on the relationship between land surface temperature and land use/ land cover in Tehran. Sustain. Cities Soc. 23, 94–104 (2016)
Butt, A., Shabbir, R., Ahmad, S.S., Aziz, N.: Land use change mapping and analysis using remote sensing and GIS: a case study of Simly watershed, Islamabad, Pakistan. Egyptian J Remote Sens Space Sci. 18, 251–259 (2015)
Carlson, T.N., Ripley, D.A.: On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sens. Environ. 62, 241–252 (1997)
Chakraborty, S.D., Kant, Y., Bharath, B.D.: Study of land surface temperature in Delhi city to managıng the thermal effect on urban developments. Int J Advanced Sci Tech Res. 4(1), 439–450 (2014)
Chakraborty, S.D., Kant, Y., Mitra, D.: Assessment of land surface temperature and heat fluxes over Delhi using remote sensing data. J. Environ. Manag. 148, 143–152 (2015)
Chaudhuri, G., Mishra, N.B.: Spatio-temporal dynamics of land cover and land surface temperature in Ganges-Brahmaputra delta: a comparative analysis between India and Bangladesh. Appl. Geogr. 68, 68–83 (2016)
Chen, X.L., Zhao, H.M., Li, P.X., Yin, Z.Y.: Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sens. Environ. 104(2), 133–146 (2006)
Chen, Y.C., Chiu, H.W., Su, Y.F., Wu, Y.C., Cheng, K.S.: Does urbanization increase diurnal land surface temperature variation? Evidence and implications. Landsc. Urban Plan. 157, 247–258 (2017)
Cheung, H.K.W.: An Urban Heat Island Study for Building and Urban Design, a Thesis Submitted to The University Of Manchester for the Degree of Doctor of Philosophy in the Faculty of Engineering and Physical Sciences. School of Mechanical, Aerospace and Civil Engineering (2011)
Churches, C.E., Wampler, P.J., Sun, W., Smith, A.J.: Evaluation of forest cover estimates for Haiti using supervised classification of Landsat data. Int. J. Appl. Earth Obs. Geoinf. 30, 203–216 (2014)
Congalton, R.G.: A review of assessing the accuracy of classifications of remotely sensed data. Remote Sens. Environ. 37(1), 35–46 (1991)
Deosthali, V.: Impact of rapid urban growth on heat and moisture islands in Pune City, India. Atmos. Environ. 34, 2745–2754 (2000)
Dhalluin, A., Bozonnet, E.: Urban heat islands and sensitive building design-a study in some French cities context. Sustain. Cities Soc. 19, 292–299 (2015)
Ding, F., Xu, H.Q.: Comparison of three algorithms for retrieving land surface temperature from Landsat TM thermal infrared band. J Fujian Norm Univ (Nat Sci Ed). 24(1), 91–96 (2008)
Du, M., Wang, Q., Cai, G.: Temporal and spatial variations of urban heat island effect in Beijing using ASTER and TM data. In Urban Remote Sensing Event. 1–5 (2009)
Effat, H.A., Hassan, O.A.K.: Change detection of urban heat islands and some related parameters using multi-temporal Landsat images; a case study for Cairo city, Egypt. Urban Climate. 10, 171–188 (2014)
Effat, H.A., Taha, L.G.E., Mansour, K.F.: Change detection of land cover and urban heat islands using multi-temporal landsat images, application in Tanta City, Egypt. Open J Remote Sens Positioning. 1(2), 1–15 (2014)
Efstathiou, M.N., Varotsos, C.A., Singh, R.P., Cracknell, A.P., Tzanis, C.: On the longitude dependence of total ozone trends over middle-latitudes. Int. J. Remote Sens. 24, 1361–1367 (2003)
EPA, 2008: Urban Heat Island basics. In Reducing Urban Heat Islands: Compendium of Strategies; Chapter 1; Draft Report, United States Environmental Protection Agency: Washington, DC, USA. Available online: http://www.epa.gov/heatisland/resources/compendium.htm (accessed on June 2018)
FAO, 1997: Estimating Biomass and Biomass Change in Tropical Forests. Food and Agriculture Organization of the United Nations. http://www.fao.org/docrep/W4095E/W4095E00.htm. Accessed July, 2018
Feng, H., Liu, H., Wu, L.: Monitoring the relationship between the land surface temperature change and urban growth in Beijing, China. IEEE J. Select. Top. Appl. Earth Observ. Rem. Sens. 7(10), 4010–4019 (2014)
Fu, P., Weng, Q.: 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 (2016)
Gandhi, G.M., Parthiban, S., Thummalu, N., Christy, A.: NDVI: vegetation change detection using remote sensing and gis – a case study of Vellore District. Procedia Comput Sci. 57, 1199–1210 (2015)
Gaylan, F.G.: Urban land use land cover changes and their effect on land surface temperature: case study using Dohuk City in the Kurdistan region of Iraq. Climate. 5(1), 3 (2017)
GCM: 1/25.000 scale digital topographic map of the study area. National Defense Department General Command of Mapping, Ankara (2005)
GDMRE, 1997: Environmental geology and natural resources of Sivas city. General Directorate of Mineral Research and Exploration, Central Anatolia 1st Regional Directorate Geological Studies Directorate 168p, Sivas
GDMRE: 1/25.000 scale digital geology map of the study area. General Directorate of Mineral Research and Exploration, Ankara (2005)
GEOG, 2016: Department of Geography. PennState College of Earth and Mineral Sciences, Remote Sensing Analysis and Applications https://www.e-education.psu.edu/geog883/node/524. Accessed 25 June 2018
Ghebrezgabher, M.G., Yang, T., Yang, X., Wang, X., Khan, M.: Extracting and analyzing forest and woodland cover change in Eritrea based on landsat data using supervised classification. Egypt J Remote Sens Space Sci. 19, 37–47 (2016)
Gophen, M.: Land-use, albedo and air temperature changes in the hula valley (Israel) during 1946-2008. Open J Mod Hydrol. 4(04), 101–111 (2014)
Guo, G., Zhou, X., Wu, Z., Xiao, R., Chen, Y.: Characterizing the impact of urban morphology heterogeneity on land surface temperature in Guangzhou, China. Environ. Model Softw. 84, 427–439 (2016)
Hansen, H.S.: Modelling the future coastal zone urban development as implied by the IPCC SRES and assessing the impact from sea level rise. Landsc. Urban Plan. 98, 141–149 (2010)
Hegazy, I.R., Kaloop, M.R.: Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia governorate Egypt. Int J Sustain Built Environ. 4, 117–124 (2015)
Heinl, M., Hammerle, A., Tappeiner, U., Leitinger, G.: Determinants of urban-rural land surface temperature differences-a landscape scale perspective. Landsc. Urban Plan. 134, 33–42 (2015)
Herold, M., Goldstein, N.C., Clarke, K.C.: The spatiotemporal form of urban growth: measurement, analysis and modeling. Remote Sens. Environ. 86, 286–302 (2003)
Hove, L. W. A. V., G. J. Steeneveld, C. M. J. Jacobs, B. G. Heusinkveld, J. A. Elbers, E. J. Moors, and A. A. M. Holtslag, 2011: Exploring the urban heat island intensity of Dutch cities. Alterra report 2170 Alterra, part of Wageningen UR Wageningen
Imhoff, M.L., Zhang, P., Wolfe, R.E., Bounoua, L.: Remote sensing of the urban heat island effect across biomes in the continental USA. Remote Sens. Environ. 114, 504–513 (2010)
Ji, X., Niu, X.: The attribute accuracy assessment of land cover date in the national geography conditions survey. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci. 2(4), 35–40 (2014)
Jiang, Y., Fu, P., Weng, Q.: Assessing the impacts of urbanization-associated land use/cover change on land surface temperature and surface moisture: a case study in the midwestern United States. Remote Sens. 7(4), 4880–4898 (2015)
Johansen, B., Tømmervik, H.: The relationship between phytomass, NDVI and vegetation communities on Svalbard. Int. J. Appl. Earth Obs. Geoinf. 27, 20–30 (2014)
Julien, Y., Sonrino, J.A., Verhoef, W.: Changes in land surface temperatures and NDVI values over Europe between 1982 and 1999. Remote Sens. Environ. 103, 43–55 (2006)
Kaplan, G., Avdan, U., Avdan, Z.Y.: Urban heat island analysis using the Landsat 8 satellite data: a case study in Skopje, Macedonia. In Multidisciplinary Digital Publishing Institute Proceedings. 2(7), 58 (2018)
Karakus, C.B., Kavak, K.S., Cerit, O.: Determination of variations in land cover and land use by remote sensing and geographic information systems around the city of Sivas (Turkey). Fresenius Environ. Bull. 23(3), 667–677 (2014)
Kaufmann, R.K., Zhou, L., Myneni, R.B., Tucker, C.J., Slayback, D., Shabanov, N.V., Pinzon, J.: The effect of vegetation on surface temperature: a statistical analysis of NDVI and climate data. Geophys. Res. Lett. 30(22), 2137 (2003)
Kaya, S., Basar, U.G., Karaca, M., Seker, D.Z.: Assessment of urban heat islands using remotely sensed data. Ecology. 21(84), 107–113 (2012)
Kumar, D., Shekhar, S.: Statistical analysis of land surface temperature–vegetation indexes relationship through thermal remote sensing. Ecotoxicol. Environ. Saf. 121, 39–44 (2015)
Kumar, K.S., Bhaskar, P.U., Padmakumarı, K.: Estimation of land surface temperature to study urban heat island effect using Landsat ETM+ image. Int J Eng Sci Technol (IJEST). 4(2), 771–778 (2012)
Lambin, E.F., Rounsevell, M.D.A., Geist, H.J.: Are agricultural land-use models able to predict changes in land-use intensity? Agric. Ecosyst. Environ. 82, 321–331 (2000)
Landsat Project Science Office, 2002: Landsat 7 Science Data user's Handbook. Washington, DC, Goddard Space Flight Center, NASA. http://ltpwww.gsfc.nasa.gov/IAS/handbook/handbook_toc.html. Accessed 13 May 2018
Landsat Project Science Office, 2016: Landsat 8 science data user’s handbook. Retrieved 13 September 2016, fromhttps://landsat.usgs.gov/documents/Landsat8DataUsersHandbook.pdf. Accessed 13 May 2018
Lee, T.W., Lee, J.Y., Wang, Z.H.: Scaling of the urban heat island intensity using time-dependent energy balance. Urban Climate. 2, 16–24 (2012)
Leong, Y.P., Chng, L.K., Ong, J., Choo, C.M., Laili, N.: Preliminary study of the impacts of land use and land cover change on land surface temperature with remote sensing technique: a case study of the Klang Valley and Penang Island, Malaysia. Segi. 9, 5–29 (2015)
Li, W., Bai, Y., Chen, Q., Hee, K., Ji, X., Han, C.: Discrepant impacts of land use and land cover on urban heat islands: a case study of Shanghai, China. Ecol. Indic. 47, 171–178 (2014)
Li, Y., Zhang, H., Kainz, W.: Monitoring patterns of urban heat islands of the fast-growing Shanghai metropolis, China: using time-series of Landsat TM/ETM+ data. Int. J. Appl. Earth Obs. Geoinf. 19, 127–138 (2012)
Liu, T., Yang, X.: Monitoring land changes in an urban area using satellite imagery, GIS and landscape metrics. Appl. Geogr. 56, 42–54 (2015)
Liu, Y., Huang, X., Yang, H., Zhong, T.: Environmental effects of land-use/cover change caused by urbanization and policies in Southwest China karst area-a case study of Guiyang. Habitat Int. 44, 339–348 (2014)
Lo, C.P., Quattrochi, D.A.: Land-use and land-cover change, urban heat island phenomenon, and health implications: a remote sensing approach. Photogramm. Eng. Remote Sens. 69(9), 1053–1063 (2003)
Lo, C.P., Quattrochi, D.A., Luvall, J.C.: Application of high-resolution thermal infrared remote sensing and GIS to assess the urban heat island effect. Int. J. Remote Sens. 18, 287–303 (1997)
Lu, D., Weng, Q.: A survey of image classification methods and techniques for improving classification performance. Int. J. Remote Sens. 28(5), 823–870 (2007)
Ma, Y., Kuang, Y., Huang, N.: Coupling urbanization analyses for studying urban thermal environment and its interplay with biophysical parameters based on TM/ETM+ imagery. Int. J. Appl. Earth Obs. Geoinf. 12(2), 110–118 (2010)
Mahiroğulları, A. M., 2003: Today’s City of Sivas Dating Back to Ancient Times. Typography Sivas, 199p
Malaret, E., Bartolucci, L.A., Lozano, D.F., Anuta, P.E., McGillem, C.D.: Landsat-4 and Landsat-5 thematic mapper data quality analysis. Photogramm. Eng. Remote Sens. 51, 1407–1416 (1985)
Mallick, J., Kant, Y., Bharath, B.D.: Estimation of land surface temperature over Delhi using Landsat-7 ETM+. J Indian Geophys Union. 12(3), 131–140 (2008)
Mathew, A., Khandelwal, S., Kaul, N.: Spatial and temporal variations of urban heat island effect and the effect of percentage impervious surface area and elevation on land surface temperature: study of Chandigarh City, India. Sustain. Cities Soc. 26, 264–277 (2016)
Mei, A., Manzo, C., Fontinovo, G., Bassani, C., Allegrini, A., Petracchini, F.: Assessment of land cover changes in Lampedusa Island (Italy) using Landsat TM and OLI data. J. Afr. Earth Sci. 122, 15–24 (2016)
Melesse, A.M.: Spatiotemporal dynamics of land surface parameters in the Red River of the North Basin. Phys. Chem. Earth. 29, 795–810 (2004)
Mirzaei, P.A., Haghighat, F., Nakhaie, A.A., Yagouti, A., Giguère, M., Keusseyan, et al.: Indoor thermal condition in urban heat island-development of a predictive tool. Build. Environ. 57, 7–17 (2012)
Mohan, M., Kandya, A.: Impact of urbanization and land-use/land-cover change on diurnal temperature range: a case study of tropical urban airshed of India using remote sensing data. Sci. Total Environ. 506, 453–465 (2015)
Mundia, C.N., Aniya, M.: Analysis of land use/cover changes and urban expansion of Nairobi City using remote sensing and GIS. Int. J. Remote Sens. 26, 2831–2849 (2005)
Myhre, G., Myhre, A.: Uncertainties in radiative forcing due to surface albedo changes caused by land-use changes. J. Clim. 16, 1511–1524 (2003)
Odindi, J.O., Bangamwabo, V., Mutanga, O.: Assessing the value of urban green spaces in mitigating multi-seasonal urban heat using MODIS land surface temperature (LST) and Landsat 8 data. Int J Environ Res. 9(1), 9–18 (2015)
Oke, T.R.: City size and the urban heat island. Atmos. Environ. 7, 769–779 (1973)
Omran, E.S.E.: Detection of land-use and surface temperature change at different resolutions. J. Geogr. Inf. Syst. 4, 189–203 (2012)
Ozesmi, S.L., Bauer, M.E.: Satellite remote sensing of wetlands. Wetl. Ecol. Manag. 10, 381–402 (2002)
Pegau, W.S., Paulson, C.A.: The albedo of Arctic leads in summer. Ann. Glaciol. 33, 221–224 (2001)
Peng, S., Piao, S., Ciais, P., Friedlingstein, P., Ottle, C., Bréon, F.M., Nan, H., Zhou, L., Myneni, R.B.: Surface urban heat island across 419 global big cities. Environ Sci Technol. 46, 696–703 (2012)
Pu, R., Gong, P., Michishita, R., Sasagawa, T.: Assessment of multi-resolution and multi-sensor data for urban surface temperature retrieval. Remote Sens. Environ. 104, 211–225 (2006)
Ramachandra, T.V., Kumar, U.: Urban land surface temperature with land cover dynamics: multi-resolution, spatio-temporal data analysis of greater Bangalore. Int J Geoinformatics. 5(3), 43–53 (2009)
Raynolds, M.K., Comiso, J.C., Walker, D.A., Verbyla, D.: Relationship between satellite-derived land surface temperatures, arctic vegetation types, and NDVI. Remote Sens. Environ. 112, 1884–1894 (2008)
Rembold, F., Carnicelli, S., Nori, M., Ferrari, G.A.: Use of aerial photographs, Landsat TM imagery and multidisciplinary field survey for land-cover change analysis in the lakes region. Int. J. Appl. Earth Obs. Geoinf. 2(3–4), 181–189 (2000)
Saadat, H., Adamowski, J., Bonnell, R., Sharifi, F., Namdar, M., Ebrahim, S.A.: Land use and land cover classification over a large area in Iran based on single date analysis of satellite imagery. ISPRS J. Photogramm. Remote Sens. 66, 608–619 (2011)
Sajikumar, N., Remya, R.S.: Impact of land cover and land use change on runoff characteristics. J. Environ. Manag. 161, 460–468 (2015)
Schneider, A., Woodcock, C.E.: Compact, dispersed, fragmented, extensive? A comparison of urban growth in twenty-five global cities using remotely sensed data, pattern metrics and census information. Urban Stud. 45(3), 659–692 (2008)
Schultz, P.A., Halpert, M.S.: Global correlation of temperature, NDVI and precipitation. Adv. Space Res. 13(5), 277–280 (1993)
Sekertekin, A.İ., Kutoglu, S.H., Kaya, S.: Evaluation of spatio-temporal variability in land surface temperature: a case study of Zonguldak, Turkey. Environ. Monit. Assess. 188(1), 1–15 (2016)
Shahmohamadi, P., Ani, A.I.C., Ramly, A., Maulud, K.N.A., Nor, M.F.I.M.: Reducing urban heat island effects: A systematic review to achieve energy consumption balance. Int J Phys Sci. 5(6), 626–636 (2010)
Shalaby, A., Tateishi, R.: Remote sensing and GIS for mapping and monitoring land cover and land use changes in the northwestern coastal zone of Egypt. Appl. Geogr. 27, 28–41 (2007)
Shen, G., Ibrahim, A.N., Wang, Z., Ma, C., Gong, J.: Spatial–temporal land-use/land-cover dynamics and their impacts on surface temperature in Chongming Island of Shanghai, China. Int. J. Remote Sens. 36(15), 4037–4053 (2015)
Silleos, N.G., Alexandridis, T.K., Gitas, I.Z., Perakis, K.: Vegetation indices: advances made in biomass estimation and vegetation monitoring in the last 30 years. Geocarto Int. 21(4), 21–28 (2006)
Sinha, S., Sharma, L.K., Nathawat, M.S.: Improved land-use/land-cover classification of semi-arid deciduous forest landscape using thermal remote sensing. Egypt J Remote Sens Space Sci. 18, 217–233 (2015)
Sivas Governorship, 2006: Sivas 2023 Strategic Provincial Development Plan. T.C. Governorship of Sivas Provincial Social and Economic Planning Center Sivas, 291p
Streutker, D.R.: A remote sensing study of the urban heat island of Houston, Texas. Int. J. Remote Sens. 23(13), 2595–2608 (2002)
Tran, D.X., Pla, F., Latorre-Carmona, P., Myint, S.W., Caetano, M., Kieu, H.V.: Characterizing the relationship between land use land cover change and land surface temperature. ISPRS J. Photogramm. Remote Sens. 124, 119–132 (2017)
Trenberth, K.E., Jones, P.D., Ambenje, P., Bojariu, R., Easterling, D., Tank, A.K., Parker, D., Rahimzadeh, F., Renwick, J.A., Rusticucci, M., Soden, B., Zhai, P.: Observations: surface and atmospheric climate change. In: Solomon, S., Qin, D., Manning, M., Chen, Z., Marquis, M., Averyt, K.B., Tignor, M., Miller, H.L. (eds.) Climate Change 2007: The Physical Science Basis. Contribution of Working Group Ito the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press (2007)
Trlica, A., Hutyra, L.R., Schaaf, C.L., Erb, A., Wang, J.A.: Albedo, land cover, and daytime surface temperature variation across an urbanized landscape. Earth’s Future. 5(11), 1084–1101 (2017)
TUIK, 2015: Turkish statistical institute, results of population censuses. 1935-2000 and results of address based population registration system (2007-2015)
United Nations, 2014: Population division world urbanization prospects. United Nations, Department of Economic and Social Affairs, the 2014 revision
Varotsos, C.: The southern hemisphere ozone hole split in 2002. Environ. Sci. Pollut. R. 9, 375–376 (2002)
Varotsos, C.A., Melnikova, I.N., Cracknell, A.P., Tzanis, C., Vasilyev, A.V.: New spectral functions of the near-ground albedo derived from aircraft diffraction spectrometer observations. Atmos. Chem. Phys. 14(13), 6953–6965 (2014)
Wang, S., Ma, Q., Ding, H., Liang, H.: Detection of urban expansion and land surface temperature change using multi-temporal landsat images. Resour. Conserv. Recycl. 128, 526–534 (2016)
Wardlow, B.D., Kastens, J.H., Egbert, S.L.: Using USDA crop progress data for the evaluation of Greenup onset date calculated from MODIS 250 meter data. Photogramm. Eng. Remote. Sens. 72, 1225–1234 (2006)
Weng, Q.: Thermal infrared remote sensing for urban climate and environmental studies: methods, applications, and trends. ISPRS J. Photogramm. Remote Sens. 64(4), 335–344 (2009)
Weng, Q., Lu, D., Schubring, J.: Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies. Remote Sens. Environ. 89, 467–483 (2004)
Wondrade, N., Dick, Q.B., Tveite, H.: GIS based mapping of land cover changes utilizing multi-temporal remotely sensed image data in Lake Hawassa watershed, Ethiopia. Environ. Monit. Assess. 186(3), 1765–1780 (2014)
Xian, G., Crane, M.: An analysis of urban thermal characteristics and associated land cover in Tampa Bay and Las Vegas using Landsat satellite data. Remote Sens. Environ. 104, 147–156 (2006)
Xiao, H., Weng, Q.: The impact of land use and land cover changes on land surface temperature in a karst area of China. J. Environ. Manag. 85(1), 245–257 (2007)
Xu, H., Ding, F., Wen, X.: Urban expansion and heat island dynamics in the Quanzhou region, China. IEEE J Sel Top Appl Earth Obs Remote Sens. 2(2), 74–79 (2010)
Yang, J., Wong, M.S., Menenti, M., Nichol, J.: Study of the geometry effect on land surface temperature retrieval in urban environment. ISPRS J. Photogramm. Remote Sens. 109, 77–87 (2015)
Yedekci, G., 2015: Urban transformation with the examples applied in the world and Turkey and the original conversion model proposal. Architecture Foundation Economic Business Publications, ISBN 978-605- 86645-6-2, Istanbul
Yuan, F., Bauer, M.E.: Comparison of impervious surface area and normalized difference vegetation index as indicators of surface urban heat island effects in Landsat imagery. Remote Sens. Environ. 106, 375–386 (2007)
Yuan, F., Sawaya, K.E., Loeffelholz, B.C., Bauer, M.E.: Land cover classification and change analysis of the twin cities (Minnesota) metropolitan area by multitemporal landsat remote sensing. Remote Sens. Environ. 98, 317–328 (2005)
Yüksel, İ., Sandalcı, M., Çeribaşı, G., and Ö. Yüksek, 2011: Effects of global warming and climate change on water resources. National 7th Coastal Engineering Symposium, 21–23
Yuksel, U.D.: Examination of the air and surface temperatures in structural and green areas in the city: the case of Ankara. Ecology. 18(69), 66–74 (2008)
Zareie, S., Khosravi, H., Nasiri, A.: Derivation of land surface temperature from Landsat thematic mapper (TM) sensor data and analyzing relation between land use changes and surface temperature. Solid Earth Discuss. 1–15 (2016a)
Zareie, S., Khosravi, H., Nasiri, A., Dastorani, M.: Using Landsat thematic mapper (TM) sensor to detect change in land surface temperature in relation to land use change in Yazd, Iran. Solid Earth. 7, 1551–1564 (2016b)
Zhang, H., Qi, Z.F., Ye, X.Y., Cai, Y.B., Ma, W.C., Chen, M.N.: Analysis of land use/land cover change, population shift, and their effects on spatiotemporal patterns of urban heat islands in metropolitan Shanghai, China. Appl. Geogr. 44, 121–133 (2013)
Zhang, F., Tiyip, T., Kung, H., Johnson, V.C., Maimaitiyiming, M., Zhou, M., Wang, J.: Dynamics of land surface temperature (LST) in response to land use and land cover (LULC) changes in the Weigan and Kuqa river oasis, Xinjiang, China. Arab. J. Geosci. 9(7), 499 (2016)
Zhang, Y., Odeh, I.O.A., Han, C.: Bi-temporal characterization of land surface temperature in relation to impervious surface area, NDVI and NDBI, using a sub-pixel image analysis. Int. J. Appl. Earth Obs. Geoinf. 11, 256–264 (2009)
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Karakuş, C.B. The Impact of Land Use/Land Cover (LULC) Changes on Land Surface Temperature in Sivas City Center and Its Surroundings and Assessment of Urban Heat Island. Asia-Pacific J Atmos Sci 55, 669–684 (2019). https://doi.org/10.1007/s13143-019-00109-w
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DOI: https://doi.org/10.1007/s13143-019-00109-w