Arazi Örtüsü ile Kentsel Isı Adası Etkisi Arasındaki İlişki: Ordu Kent Merkezi (Türkiye) Örneği
Yıl 2025,
Cilt: 15 Sayı: 1, 35 - 55, 30.06.2025
Mesut Güzel
,
Pervin Yeşil
Öz
Bu çalışmada, üç temel arazi örtüsü tipi ile Arazi Yüzey Sıcaklığı (AYS) ve Kentsel Isı Adası (KIA) etkisi arasındaki ilişkinin ortaya konulması amaçlanmıştır. Bu amaç doğrultusunda; AYS’nin hesaplanmasında Landsat 8 OLI/TIRS görüntüleri ve arazi örtüsünün sınıflandırılmasında denetimsiz sınıflandırma algoritmaları kullanılmıştır. Elde edilen bulgular istatistiksel yöntemler kullanılarak incelenmiştir. Çalışmanın sonuçları, Karadeniz kıyı kentlerinden biri olan Ordu’da KIA etkisinin ve AYS’nin mekânsal dağılımının arazi örtüsünün tipine göre değiştiğini göstermiştir. AYS ortalaması, yapılaşmış alanlarda bitki örtüsü ile kaplı alanlara göre ortalama 3 °C ve su yüzeylerine göre 8.3 °C daha yüksektir. Kent merkezindeki KIA ve KIA olmayan alanlar arasında ise 4.7 °C’lik sıcaklık farkı bulunmaktadır. Sonuç olarak; KIA etkisinin mekânsal örüntüsü ortaya konulmuş ve Ordu kent merkezi ölçeğinde, iklim değişikliğinin zararlı etkilerine karşı etkili stratejilerin geliştirilmesi noktasında karar vericilere referans sağlanmıştır.
Etik Beyan
Bu makalenin yayınlanmasıyla ilgili herhangi bir etik sorun bulunmamaktadır.
Kaynakça
-
Abbas, A. W., Minallh, N., Ahmad, N., Abid, S. A. R. ve Khan, M. A. A. (2016). K-Means and ISODATA clustering algorithms for landcover classification using remote sensing. Sindh University Research Journal, 48(2), 315-318. http://sujo.usindh.edu.pk/index.php/SURJ/article/view/2358/2008
-
Akbari, H., Cartalis, C., Kolokotsa, D., Muscio, A., Pisello, A. L., Rossi, F. ve Zinzi, M. (2016). Local climate change and urban heat island mitigation techniques-the state of the art. Journal of Civil Engineering and Management, 22(1), 1-16. https://doi.org/10.3846/13923730.2015.1111934
-
Algretawee, H., Rayburg, S. ve Neave, M. (2019). Estimating the effect of park proximity to the central of Melbourne city on Urban Heat Island (UHI) relative to Land Surface Temperature (LST). Ecological Engineering, 138, 374-390. https://doi.org/10.1016/j.ecoleng.2019.07.034
-
Almeida, C. R. D., Teodoro, A. C. ve Gonçalves, A. (2021). Study of the urban heat island (UHI) using remote sensing data/techniques: A systematic review. Environments, 8(10), 105. https://doi.org/10.3390/environments8100105
-
Amiri, R., Weng, Q., Alimohammadi, A. ve Alavipanah, S. K. (2009). Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran. Remote Sensing of Environment, 113, 2606-2617. https://doi.org/10.1016/j.rse.2009.07.021
-
Artis, D. A. ve Carnahan, W. H. (1982). Survey of emissivity variability in thermography of urban areas. Remote Sensing of Environment, 12(4), 313-329. https://doi.org/10.1016/0034-4257(82)90043-8
-
Azevedo, J., Chapman, L. ve Muller, C. (2016). Quantifying the daytime and night-time urban heat island in birmingham, uk: a comparison of satellite derived land surface temperature and high resolution air temperature observations. Remote Sensing, 8(2), 153. https://doi.org/10.3390/rs8020153
-
Bao, T., Li, X., Zhang, J., Zhang, Y. ve Tian, S. (2016). Assessing the distribution of urban green spaces and its anisotropic cooling distance on urban heat island pattern in Baotou, China. ISPRS International Journal of Geo-information, 5(2), 12. https://doi.org/10.3390/ijgi5020012
-
Bouzekri, S., Lasbet, A. A. ve Lachehab, A. A. (2015). New spectral index for extraction of built-up area using Landsat-8 data. Journal of the Indian Society of Remote Sensing, 43, 867-873. https://doi.org/10.1080/10106049.2018.1497094
-
Buyantuyev, A. ve 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. https://doi.org/10.1007/s10980-009-9402-4
-
Cao, S., Yin, W., Su, J., Chen, F., Du, Y., Jun, Z., … & Li, Y. (2023). Spatial and temporal evolution of multi-scale green space environments and urban heat islands: A case study of Beijing sub-center. Sensors and Materials, 35(2), 589. https://doi.org/10.18494/sam4189
-
Carlson, T. N. ve Ripley, D. A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241-252. https://doi.org/10.1016/S0034-4257(97)00104-1
-
Chen, X. ve Zhang, Y. (2017). Impacts of urban surface characteristics on spatiotemporal pattern of land surface temperature in Kunming of China. Sustainable Cities and Society, 32, 87-99. https://doi.org/10.1016/j.scs.2017.03.013
-
Chen, Q., Cheng, Q., Chen, Y., Li, K., Wang, D. ve Cao, S. (2021). The influence of sky view factor on daytime and nighttime urban land surface temperature in different spatial-temporal scales: A case study of Beijing. Remote Sensing, 13(20), 4117. https://doi.org/10.3390/rs13204117
-
Congalton, R. G. ve Green, K. (2019). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. CRC Press.
-
Congedo, L. (2021). Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS. Journal of Open Source Software, 6(64), 3172. https://doi.org/10.21105/joss.03172
-
Crippen, R. E. (1990). Calculating the vegetation index faster. Remote Sensing of Environment, 34(1), 71-73. https://doi.org/10.1016/0034-4257(90)90085-Z
-
Du, H., Zhou, F., Li, C., Cai, W., Jiang, H. ve Cai, Y. (2020). Analysis of the impact of land use on spatiotemporal patterns of surface urban heat island in rapid urbanization, a case study of Shanghai, China. Sustainability, 12(3), 1171. https://doi.org/10.3390/su12031171
-
EEA (2012). Urban adaptation to climate change in Europe challenges and opportunities for cities together with supportive national and European policies. Retrieved from https://www.eea.europa.eu/publications/urban-adaptation-to-climate-change. Accessed March 17, 2022
-
Everitt, J. H., Fletcher, R. S., Elder, H. S. ve Yang, C. (2008). Mapping giant salvinia with satellite imagery and image analysis. Environmental Monitoring and Assessment, 139, 35-40. https://doi.org/10.1007/s10661-007-9807-y.
-
Farrah, M. M., Siti, A. R., Siti, L. Z., Norida, M., Nur, A. A. ve Nor, A. H. (2017). Remote sensing derivation of Land Surface Temperature for insect pest monitoring. Asian Journal of Plant Sciences, 16(4), 160-171. https://doi.org/10.3923/ajps.2017.160.171
-
Fang, Z., Wang, N., Wu, Y. ve Zhang, Y. (2023). Greenland-Ice-Sheet Surface Temperature and Melt Extent from 2000 to 2020 and Implications for Mass Balance. Remote Sensing, 15(4), 1149. https://doi.org/10.3390/rs15041149
-
Feizizadeh, B., Blaschke, T., Nazmfar, H., Akbari, E. ve Kohbanani, H. R. (2013). Monitoring land surface temperature relationship to land use/land cover from satellite imagery in Maraqeh County, Iran. Journal of Environmental Planning and Management, 56(9), 1290-1315. https://doi.org/10.1080/09640568.2012.717888
-
Gao, B. C. (1995). A normalized difference water index for remote sensing of vegetation liquid water from space. In M. R. Descour, J. M. Mooney, D. L. Perry ve L. Illing (Eds.), Imaging spectrometry (pp. 257-266). SPIE.
-
Galagoda, R. U., Jayasinghe, G. Y., Halwatura, R. U. ve Rupasinghe, H. T. (2018). The impact of urban green infrastructure as a sustainable approach towards tropical micro-climatic changes and human thermal comfort. Urban Forestry & Urban Greening, 34, 1-9. https://doi.org/10.1016/j.ufug.2018.05.008
-
Girardet, H. (2020). People and nature in an urban world. One Earth, 2(2), 135-137. https://doi.org/10.1016/j.oneear.2020.02.005
-
Grigoras G. ve Uritescu, B. (2019). Land use/land cover changes dynamics and their effects on surface urban heat island in Bucharest, Romania. International Journal of Applied Earth Observation and Geoinformation, 80, 115-126. https://doi.org/10.1016/j.jag.2019.03.009
-
Grilo, F., Pinho, P., Aleixo, C., Catita, C., Silva, P. ve Lopes, N. (2020). Using green to cool the grey: modelling the cooling effect of green spaces with a high spatial resolution. Science of The Total Environment, 724, 138182. https://doi.org/10.1016/j.scitotenv.2020.138182
-
Guha, S., Govil, H. ve Mukherjee, S. (2017). Dynamic analysis and ecological evaluation of urban heat islands in Raipur city, India. Journal of Applied Remote Sensing, 11(3), 036020. https://doi.org/10.1117/1.JRS.11.036020
-
Guha, S., Govil, H., Dey, A. ve Gill, N. (2018). Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy. European Journal of Remote Sensing, 51(1), 667-678. https://doi.org/10.1080/22797254.2018.1474494
-
Gui, X., Wang, L., Yao, R., Yu, D. ve Li, C. A. (2019). Investigating the urbanization process and its impact on vegetation change and urban heat island in Wuhan, China. Environmental Science and Pollution Research, 26, 30808-30825. https://link.springer.com/article/10.1007/s11356-019-06273-w
-
He, C., Shi, P., Xie, D. ve Zhao, Y. (2010). Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach. Remote Sensing Letters, 1, 213-221. https://doi.org/10.1080/01431161.2010.481681
-
Herbei, M. V., Sala, F. ve Boldea, M. (2015, March). Using mathematical algorithms for classification of Landsat 8 satellite images. In AIP Conference Proceedings (Vol. 1648, No. 1). AIP Publishing. https://doi.org/10.1063/1.4912899
-
Hu, J., Yang, Y., Pan, X., Zhu, Q., Zhan, W., Wang, Y., Ma, W. ve Su, W. (2019). Analysis of the spatial and temporal variations of land surface temperature based on local climate zones: A case study in Nanjing, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(11), 4213-4223. https://ieeexplore.ieee.org/document/8781808
-
Huang, M., Cui, P. ve He, X. (2018). Study of the cooling effects of urban green space in harbin in terms of reducing the heat island effect. Sustainability, 10(4), 1101. https://doi.org/10.3390/su10041101
-
Huang, K., Li, X., Liu, X. ve Seto, K. C. (2019). Projecting global urban land expansion and heat island intensification through 2050. Environmental Research Letters, 14(11), 114037. https://doi.org/10.1088/1748-9326/ab4b71
-
Huang, X. ve Wang, Y. (2019). Investigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data: A case study of Wuhan, Central China. ISPRS Journal of Photogrammetry and Remote Sensing, 152, 119-131. https://doi.org/10.1016/j.isprsjprs.2019.04.010
-
Huang, X., Huang, J., Wen, D. ve Li, J. (2021). An updated MODIS global urban extent product (MGUP) from 2001 to 2018 based on an automated mapping approach. International Journal of Applied Earth Observation and Geoinformation, 95, 102255. https://doi.org/10.1016/j.jag.2020.102255
-
Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295-309. https://doi.org/10.1016/0034-4257(88)90106-X
-
Huq, S., Kovats, S., Reid, H. ve Satterthwaite, D. (2007). Reducing risks to cities from disasters and climate change. Environment and Urbanization, 19(1), 3-15. https://doi.org/10.1177/0956247807078058
Icaza, L. and Hoeven, F. (2017). Regionalist principles to reduce the urban heat island effect. Sustainability, 9(5), 677. https://doi.org/10.3390/su9050677
-
Ismail, M. H. ve Jusoff, K. (2008). Satellite data classification accuracy assessment based from reference dataset. International Journal of Computer and Information Science and Engineering, 2(3), 23-29.
-
Jensen, R. J. (2015). Introductory digital image processing: A remote sensing perspective (4th ed.). Pearson.
-
Jieli, C., Manchun, L., Yongxue, L., Chenglei, S. ve Wei, H. (2010). Extract residential areas automatically by New Built-up Index. 18th International Conference on Geoinformatics, 1-5. https://doi.org/10.1109/GEOINFORMATICS.2010.5567823
-
Jones H. G. ve Vaughan, R. A. (2010). Remote sensing of vegetation: Principles, techniques, and applications. Oxford University Press, New York, pp. 53.
-
Kawamura, M., Jayamana, S. ve Tsujiko, Y. (1996). Relation between social and environmental conditions in Colombo Sri Lanka and the urban index estimated by satellite remote sensing data. International Archives of Photogrammetry and Remote Sensing, 31, 321-326.
-
Kleerekoper, L., van Esch, M. ve Salcedo, T. B. (2012). How to make a city climate-proof, addressing the urban heat island effect. Resource Conservation Recycling, 64, 30-38. https://doi.org/10.1016/j.resconrec.2011.06.004
-
Kruskal, W. H. ve Wallis, W. A. (1952). Use of Ranks in One-Criterion Variance Analysis. Journal of the American Statistical Association, 47, 583-621. https://doi.org/10.2307/2280779
-
Kuang, W., Liu, Y., Dou, Y., Chi, W., Chen, G., Cheng-feng, G., … ve Zhang, R. (2014). What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in beijing, china. Landscape Ecology, 30(2), 357-373. https://doi.org/10.1007/s10980-014-0128-6
-
Kumar, B. P., Babu, K. R., Anusha, B. N. ve Rajasekhar, M. (2022). Geo-environmental monitoring and assessment of land degradation and desertification in the semi-arid regions using Landsat 8 OLI/TIRS, LST, and NDVI approach. Environmental Challenges, 8, 100578. https://doi.org/10.1016/j.envc.2022.100578
-
Levene, H. (1960). Robust Tests for Equality of Variances. Stanford University Press.
-
Li, D., Bou‐Zeid, E. ve Oppenheimer, M. (2014). The effectiveness of cool and green roofs as urban heat island mitigation strategies. Environmental Research Letters, 9(5), 055002. https://doi.org/10.1088/1748-9326/9/5/055002
-
Li, W., Bai, Y., Chen, Q., He, K., Ji, X. ve Han, C. (2014). Discrepant impacts of land use and land cover on urban heat islands: A case study of Shanghai, China. Ecological Indicators, 47, 171-178. https://doi.org/10.1016/j.ecolind.2014.08.015
-
Lillesand, T., Kiefer, R. W. ve Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.
Liu, Y., Li, Q., Yang, L., Mu, K., Zhang, M. ve Liu, J. (2020). Urban heat island effects of various urban morphologies under regional climate conditions. Science of The Total Environment, 743, 140589. https://doi.org/10.1016/j.scitotenv.2020.140589
Liu, Y., Wang, Z., Li, X. ve Zhang, B. (2021). Complexity of the relationship between 2d/3d urban morphology and the land surface temperature: A multiscale perspective. Environmental Science and Pollution Research, 28(47), 66804-66818. https://doi.org/10.1007/s11356-021-15177-7
-
McFeeters, S. K. (1996). The use of the normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7), 1425-1432. https://doi.org/10.1080/01431169608948714
-
McKnight, P. E. ve Najab, J. (2010). Mann‐Whitney U Test. The Corsini Encyclopedia of Psychology, 1-1.
MGM (2022). Turkish State Meteorological Service. https://mgm.gov.tr/eng/about.aspx. adresinden 1 Nisan 2022 tarihinde erişilmiştir.
-
Mittermüller, J., Erlwein, S., Bauer, A., Trokai, T., Duschinger, S. ve Schönemann, M. (2021). Context-specific, user-centred: Designing urban green infrastructure to effectively mitigate urban density and heat stress. Urban Planning, 6(4), 40-53. https://doi.org/10.17645/up.v6i4.4393
-
Mohamed, S. A. (2021). Comparison of Satellite Images Classification Techniques Using Landsat-8 Data for Land Cover Extraction in Alexandria, Egypt. International Journal of Intelligent Computing & Information Sciences, 21(3), 29-43. http://dx.doi.org/10.21608/ijicis.2021.78853.1098
-
Mohammady, M., Moradi, H. R., Zeinivand, H. ve Temme, A. J. A. M. (2015). A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran. International Journal of Environmental Science and Technology, 12, 1515-1526. https://doi.org/10.1007/s13762-014-0728-3
-
Mustafa, M. T., Hassoon, K. I., Hassan M. ve Abd, M. H. (2017). Using water indices (NDWI, MNDWI, NDMI, WRI and AWEI) to detect physical and chemical parameters by apply remote sensing and GIS techniques. International Journal of Research, 10, 117-128. http://dx.doi.org/10.5281/zenodo.1040209
-
Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V., Woodcock, C. E. ve Wulder, M. A. (2014). Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148, 42-57. https://doi.org/10.1016/j.rse.2014.02.015
-
Pandey, P. C., Chauhan, A. ve Maurya, N. K. (2022). Evaluation of earth observation datasets for LST trends over India and its implication in global warming. Ecological Informatics, 72, 101843. https://doi.org/10.1016/j.ecoinf.2022.101843
-
Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H. ve Sorooshian, S. (1994). A modified soil adjusted vegetation index. Remote Sensing of Environment, 48, 119-126. https://doi.org/10.1016/0034-4257(94)90134-1
-
Rajab, M. A. ve George, L. E. (2021). Stamps extraction using local adaptive k-means and ISODATA algorithms. Indonesian Journal of Electrical Engineering and Computer Science, 21(1), 173-145. http://doi.org/10.11591/ijeecs.v21.i1.pp137-145
-
Ren, Z., He, X., Zheng, H., Zhang, D., Yu, X., Shen, G., … & Guo, R. (2013). Estimation of the relationship between urban park characteristics and park cool island intensity by remote sensing data and field measurement. Forests, 4(4), 868-886. https://doi.org/10.3390/f4040868
-
Ross, A. ve Willson, V. L. (2017). Independent samples T-test. In Basic and advanced statistical tests (pp. 13-16). Brill.
-
Sfîcă, L., Corocăescu, A. C., Crețu, C. Ș., Amihăesei, V. A. ve Ichim, P. (2023). Spatiotemporal Features of the Surface Urban Heat Island of Bacău City (Romania) during the Warm Season and Local Trends of AYS Imposed by Land Use Changes during the Last 20 Years. Remote Sensing, 15(13), 3385. https://doi.org/10.3390/rs15133385
-
Shapiro, S. S. ve Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4), 591-611. https://doi.org/10.2307/2333709
-
Shen, L. ve Li, C. (2010). Water body extraction from landsat etm ımagery using adaboost algorithm. In Proceedings of the 18th International Conference on Geoinformatics, pp. 1-4. https://doi.org/10.1109/GEOINFORMATICS.2010.5567762
-
Singh, C., Madhavan, M., Arvind, J. ve Bazaz, A. (2021). Climate change adaptation in Indian cities: A review of existing actions and spaces for triple wins. Urban Climate, 36, 100783. https://doi.org/10.1016/j.uclim.2021.100783
-
Song, J., Du, S., Feng, X. ve Guo, L. (2014). The relationships between landscape compositions and land surface temperature: Quantifying their resolution sensitivity with spatial regression models. Landscape and Urban Planning, 123, 145-157. http://dx.doi.org/10.1016/j.landurbplan.2013.11.014
-
Stathopoulou, M., Cartalis, C. ve Petrakis, M. (2007). Integrating Corine Land Cover data and Landsat TM for surface emissivity definition: Application to the urban area of Athens, Greece. International Journal of Remote Sensing, 28(15), 3291-3304. http://dx.doi.org/10.1080/01431160600993421
-
Stehman, S. V. (2009). Sampling designs for accuracy assessment of land cover. International Journal of Remote Sensing, 30(20), 5243-5272. http://dx.doi.org/10.1080/01431160903131000
-
Stewart, I. D. ve Mills, G. (2021). The Urban Heat Island. Elsevier.
-
Sun, Q., Wu, Z. ve Tan, J. (2012). The relationship between land surface temperature and land use/land cover in Guangzhou, China. Environmental Earth Sciences, 65(6), 1687-1694. https://doi.org/10.1007/s12665-011-1145-2
-
Talukdar, S., Singha, P., Mahato, S., Pal, S., Liou, Y. A. ve Rahman, A. (2020). Land-use land-cover classification by machine learning classifiers for satellite observations-A review. Remote Sensing, 12(7), 1135. https://doi.org/10.3390/rs12071135
-
Tan, J., Zheng, Y., Tang, X., Guo, C., Zhang, L., Song, G., … ve Chen, H. (2009). The urban heat island and its impact on heat waves and human health in Shanghai. International Journal of Biometeorology, 54(1), 75-84. https://doi.org/10.1007/s00484-009-0256-x
-
Taufik, A., Syed Ahmad, S. S. ve Azmi, E. F. (2019). Classification of Landsat 8 satellite data using unsupervised methods. In Intelligent and Interactive Computing: Proceedings of IIC 2018 (pp. 275-284). Springer Singapore. https://doi.org/10.1007/978-981-13-6031-2_46
-
Thornthwaite, C. W. (1948). An approach toward a rational classification of climate. Geographical Review, 38(1), 55-94. https://doi.org/10.2307/210739
-
Touchaei, A. G. ve Wang, Y. (2015). Characterizing urban heat island in Montreal (Canada)-Effect of urban morphology. Sustainable Cities and Society, 19, 395-402. https://doi.org/10.1016/j.scs.2015.03.005
-
Tran, D., Pla, F., Carmona, P., Myint, S., Caetano, M. ve Kieu, H. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119-132. https://doi.org/10.1016/j.isprsjprs.2017.01.001
-
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation? Remote Sensing of Environment, 8, 127-150. https://doi.org/10.1016/0034-4257(79)90013-0
-
Tukey, J. (1949). Comparing individual means in the analysis of variance. Biometrics, 5(2), 99-114. https://doi.org/10.2307/3001913
-
TÜİK (2023). Turkish Statistical Institute. Retrieved form https://www.tuik.gov.tr/Home/Index adresinden 20 Haziran 2023 tarihinde erişilmiştir.
-
UN (2019). World Urbanization Prospects 2018 Highlights, Department of Economic and Social Affairs, Trends in Urbanization. https://population.un.org/wup/publications/files/wup2018-highlights.pdf adresinden 2 Mart 2021 tarihinde erişilmiştir.
-
UNFPA (2022). World Population Dashboard. Retrieved from https://www.unfpa.org/data/world-population-dashboard adresinden 4 Nisan 2022 tarihinde erişilmiştir.
-
USGS (2013). Product guide: Landsat climate data record (CDR). Surface Reflectance, Version 5.3, Department of the Interior U.S. Geological Survey: Washinton, DC, USA, December 2013.
-
Wang, Z. (2019). The relationship between land use, land cover change, and the heat island effect in xi’an city, china. Applied Ecology and Environmental Research, 17(4). https://doi.org/10.15666/aeer/1704_77957806
-
Weng, Q., Lu, D. ve Schubring, J. (2004). Estimation of land surface Temperature vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467-483. https://doi.org/10.1016/j.rse.2003.11.005
-
Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), 3025-3033. https://doi.org/10.1080/01431160600589179
-
Yang, Y., Fan, S., Ma, J., Zheng, W., Song, L. ve Wei, C. (2022). Spatial and temporal variation of heat islands in the main urban area of zhengzhou under the two-way influence of urbanization and urban forestry. Plos One, 17(8), e0272626. https://doi.org/10.1371/journal.pone.0272626
-
Yesil, P. ve Guzel, M. (2021). Evaluation of land cover/land use change in Ordu province (1990-2018) Using CORINE Data. Suleyman Demirel University Journal of Natural and Applied Sciences, 25(3), 492-498. https://doi.org/10.19113/sdufenbed.809991
-
Yilmaz, O. S., Gulgen, F., Balik Sanli, F. ve Ates, A. M. (2023). The performance analysis of different water ındices and algorithms using sentinel-2 and landsat-8 ımages in determining water surface: Demirkopru dam case study. Arabian Journal for Science and Engineering, 48(6), 7883-7903. https://link.springer.com/article/10.1007/s13369-022-07583-x
-
Yucekaya, M. ve Tirnakci, A. (2023). Microclimatic effect of urban renewal: A case study of Kayseri/Turkey. Landscape and Ecological Engineering, 19(3), 471-483. https://doi.org/10.1007/s11355-023-00554-w
-
Zha, Y., Gao, J. ve Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24, 583-594. https://doi.org/10.1080/01431160304987
-
Zhong, X., Wang, L., Zhou, J., Li, X., Qi, J., Song, L. ve Wang, Y. (2020). Precipitation dominates long-term water storage changes in Nam Co Lake (Tibetan Plateau) accompanied by intensified cryosphere melts revealed by a basin-wide hydrological modelling. Remote Sensing, 12(12), 1926. https://doi.org/10.3390/rs12121926
-
Zhou, X. ve Hong, C. (2018). Impact of urbanization-related land use land cover changes and urban morphology changes on the urban heat island phenomenon. Science of The Total Environment, 635, 1467-1476. https://doi.org/10.1016/j.scitotenv.2018.04.091
-
Zou, F., Li, H. ve Hu, Q. (2020). Responses of vegetation greening and land surface temperature variations to global warming on the Qinghai-Tibetan Plateau, 2001-2016. Ecological Indicators, 119, 106867. https://doi.org/10.1016/j.ecolind.2020.106867
Relationship Between Land Cover and Urban Heat Island Effect: The Case of Ordu City Center (Türkiye)
Yıl 2025,
Cilt: 15 Sayı: 1, 35 - 55, 30.06.2025
Mesut Güzel
,
Pervin Yeşil
Öz
This study aims to reveal the relationship between three land cover types and Land Surface Temperature (LST) and Urban Heat Island (UHI) effects. For this purpose, Landsat 8 OLI/TIRS images were used in calculating LST, and unsupervised classification algorithms were used in classifying land cover. The findings were examined using statistical methods. The results of the study showed that the spatial distribution of LST and UHI in Ordu, one of the Black Sea coastal cities, varies according to the type of land cover. The mean LST is 3 °C higher in built-up areas than in vegetated areas and 8.3 °C higher than in water bodies. There is a temperature difference of 4.7 °C between UHI and non-UHI areas in the city center. As a result, the spatial pattern of the UHI effect was revealed, and a reference was provided to decision makers in terms of developing effective strategies against the detrimental effects of global climate change at the Ordu city center.
Kaynakça
-
Abbas, A. W., Minallh, N., Ahmad, N., Abid, S. A. R. ve Khan, M. A. A. (2016). K-Means and ISODATA clustering algorithms for landcover classification using remote sensing. Sindh University Research Journal, 48(2), 315-318. http://sujo.usindh.edu.pk/index.php/SURJ/article/view/2358/2008
-
Akbari, H., Cartalis, C., Kolokotsa, D., Muscio, A., Pisello, A. L., Rossi, F. ve Zinzi, M. (2016). Local climate change and urban heat island mitigation techniques-the state of the art. Journal of Civil Engineering and Management, 22(1), 1-16. https://doi.org/10.3846/13923730.2015.1111934
-
Algretawee, H., Rayburg, S. ve Neave, M. (2019). Estimating the effect of park proximity to the central of Melbourne city on Urban Heat Island (UHI) relative to Land Surface Temperature (LST). Ecological Engineering, 138, 374-390. https://doi.org/10.1016/j.ecoleng.2019.07.034
-
Almeida, C. R. D., Teodoro, A. C. ve Gonçalves, A. (2021). Study of the urban heat island (UHI) using remote sensing data/techniques: A systematic review. Environments, 8(10), 105. https://doi.org/10.3390/environments8100105
-
Amiri, R., Weng, Q., Alimohammadi, A. ve Alavipanah, S. K. (2009). Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area, Iran. Remote Sensing of Environment, 113, 2606-2617. https://doi.org/10.1016/j.rse.2009.07.021
-
Artis, D. A. ve Carnahan, W. H. (1982). Survey of emissivity variability in thermography of urban areas. Remote Sensing of Environment, 12(4), 313-329. https://doi.org/10.1016/0034-4257(82)90043-8
-
Azevedo, J., Chapman, L. ve Muller, C. (2016). Quantifying the daytime and night-time urban heat island in birmingham, uk: a comparison of satellite derived land surface temperature and high resolution air temperature observations. Remote Sensing, 8(2), 153. https://doi.org/10.3390/rs8020153
-
Bao, T., Li, X., Zhang, J., Zhang, Y. ve Tian, S. (2016). Assessing the distribution of urban green spaces and its anisotropic cooling distance on urban heat island pattern in Baotou, China. ISPRS International Journal of Geo-information, 5(2), 12. https://doi.org/10.3390/ijgi5020012
-
Bouzekri, S., Lasbet, A. A. ve Lachehab, A. A. (2015). New spectral index for extraction of built-up area using Landsat-8 data. Journal of the Indian Society of Remote Sensing, 43, 867-873. https://doi.org/10.1080/10106049.2018.1497094
-
Buyantuyev, A. ve 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. https://doi.org/10.1007/s10980-009-9402-4
-
Cao, S., Yin, W., Su, J., Chen, F., Du, Y., Jun, Z., … & Li, Y. (2023). Spatial and temporal evolution of multi-scale green space environments and urban heat islands: A case study of Beijing sub-center. Sensors and Materials, 35(2), 589. https://doi.org/10.18494/sam4189
-
Carlson, T. N. ve Ripley, D. A. (1997). On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241-252. https://doi.org/10.1016/S0034-4257(97)00104-1
-
Chen, X. ve Zhang, Y. (2017). Impacts of urban surface characteristics on spatiotemporal pattern of land surface temperature in Kunming of China. Sustainable Cities and Society, 32, 87-99. https://doi.org/10.1016/j.scs.2017.03.013
-
Chen, Q., Cheng, Q., Chen, Y., Li, K., Wang, D. ve Cao, S. (2021). The influence of sky view factor on daytime and nighttime urban land surface temperature in different spatial-temporal scales: A case study of Beijing. Remote Sensing, 13(20), 4117. https://doi.org/10.3390/rs13204117
-
Congalton, R. G. ve Green, K. (2019). Assessing the Accuracy of Remotely Sensed Data: Principles and Practices. CRC Press.
-
Congedo, L. (2021). Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS. Journal of Open Source Software, 6(64), 3172. https://doi.org/10.21105/joss.03172
-
Crippen, R. E. (1990). Calculating the vegetation index faster. Remote Sensing of Environment, 34(1), 71-73. https://doi.org/10.1016/0034-4257(90)90085-Z
-
Du, H., Zhou, F., Li, C., Cai, W., Jiang, H. ve Cai, Y. (2020). Analysis of the impact of land use on spatiotemporal patterns of surface urban heat island in rapid urbanization, a case study of Shanghai, China. Sustainability, 12(3), 1171. https://doi.org/10.3390/su12031171
-
EEA (2012). Urban adaptation to climate change in Europe challenges and opportunities for cities together with supportive national and European policies. Retrieved from https://www.eea.europa.eu/publications/urban-adaptation-to-climate-change. Accessed March 17, 2022
-
Everitt, J. H., Fletcher, R. S., Elder, H. S. ve Yang, C. (2008). Mapping giant salvinia with satellite imagery and image analysis. Environmental Monitoring and Assessment, 139, 35-40. https://doi.org/10.1007/s10661-007-9807-y.
-
Farrah, M. M., Siti, A. R., Siti, L. Z., Norida, M., Nur, A. A. ve Nor, A. H. (2017). Remote sensing derivation of Land Surface Temperature for insect pest monitoring. Asian Journal of Plant Sciences, 16(4), 160-171. https://doi.org/10.3923/ajps.2017.160.171
-
Fang, Z., Wang, N., Wu, Y. ve Zhang, Y. (2023). Greenland-Ice-Sheet Surface Temperature and Melt Extent from 2000 to 2020 and Implications for Mass Balance. Remote Sensing, 15(4), 1149. https://doi.org/10.3390/rs15041149
-
Feizizadeh, B., Blaschke, T., Nazmfar, H., Akbari, E. ve Kohbanani, H. R. (2013). Monitoring land surface temperature relationship to land use/land cover from satellite imagery in Maraqeh County, Iran. Journal of Environmental Planning and Management, 56(9), 1290-1315. https://doi.org/10.1080/09640568.2012.717888
-
Gao, B. C. (1995). A normalized difference water index for remote sensing of vegetation liquid water from space. In M. R. Descour, J. M. Mooney, D. L. Perry ve L. Illing (Eds.), Imaging spectrometry (pp. 257-266). SPIE.
-
Galagoda, R. U., Jayasinghe, G. Y., Halwatura, R. U. ve Rupasinghe, H. T. (2018). The impact of urban green infrastructure as a sustainable approach towards tropical micro-climatic changes and human thermal comfort. Urban Forestry & Urban Greening, 34, 1-9. https://doi.org/10.1016/j.ufug.2018.05.008
-
Girardet, H. (2020). People and nature in an urban world. One Earth, 2(2), 135-137. https://doi.org/10.1016/j.oneear.2020.02.005
-
Grigoras G. ve Uritescu, B. (2019). Land use/land cover changes dynamics and their effects on surface urban heat island in Bucharest, Romania. International Journal of Applied Earth Observation and Geoinformation, 80, 115-126. https://doi.org/10.1016/j.jag.2019.03.009
-
Grilo, F., Pinho, P., Aleixo, C., Catita, C., Silva, P. ve Lopes, N. (2020). Using green to cool the grey: modelling the cooling effect of green spaces with a high spatial resolution. Science of The Total Environment, 724, 138182. https://doi.org/10.1016/j.scitotenv.2020.138182
-
Guha, S., Govil, H. ve Mukherjee, S. (2017). Dynamic analysis and ecological evaluation of urban heat islands in Raipur city, India. Journal of Applied Remote Sensing, 11(3), 036020. https://doi.org/10.1117/1.JRS.11.036020
-
Guha, S., Govil, H., Dey, A. ve Gill, N. (2018). Analytical study of land surface temperature with NDVI and NDBI using Landsat 8 OLI and TIRS data in Florence and Naples city, Italy. European Journal of Remote Sensing, 51(1), 667-678. https://doi.org/10.1080/22797254.2018.1474494
-
Gui, X., Wang, L., Yao, R., Yu, D. ve Li, C. A. (2019). Investigating the urbanization process and its impact on vegetation change and urban heat island in Wuhan, China. Environmental Science and Pollution Research, 26, 30808-30825. https://link.springer.com/article/10.1007/s11356-019-06273-w
-
He, C., Shi, P., Xie, D. ve Zhao, Y. (2010). Improving the normalized difference built-up index to map urban built-up areas using a semiautomatic segmentation approach. Remote Sensing Letters, 1, 213-221. https://doi.org/10.1080/01431161.2010.481681
-
Herbei, M. V., Sala, F. ve Boldea, M. (2015, March). Using mathematical algorithms for classification of Landsat 8 satellite images. In AIP Conference Proceedings (Vol. 1648, No. 1). AIP Publishing. https://doi.org/10.1063/1.4912899
-
Hu, J., Yang, Y., Pan, X., Zhu, Q., Zhan, W., Wang, Y., Ma, W. ve Su, W. (2019). Analysis of the spatial and temporal variations of land surface temperature based on local climate zones: A case study in Nanjing, China. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 12(11), 4213-4223. https://ieeexplore.ieee.org/document/8781808
-
Huang, M., Cui, P. ve He, X. (2018). Study of the cooling effects of urban green space in harbin in terms of reducing the heat island effect. Sustainability, 10(4), 1101. https://doi.org/10.3390/su10041101
-
Huang, K., Li, X., Liu, X. ve Seto, K. C. (2019). Projecting global urban land expansion and heat island intensification through 2050. Environmental Research Letters, 14(11), 114037. https://doi.org/10.1088/1748-9326/ab4b71
-
Huang, X. ve Wang, Y. (2019). Investigating the effects of 3D urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data: A case study of Wuhan, Central China. ISPRS Journal of Photogrammetry and Remote Sensing, 152, 119-131. https://doi.org/10.1016/j.isprsjprs.2019.04.010
-
Huang, X., Huang, J., Wen, D. ve Li, J. (2021). An updated MODIS global urban extent product (MGUP) from 2001 to 2018 based on an automated mapping approach. International Journal of Applied Earth Observation and Geoinformation, 95, 102255. https://doi.org/10.1016/j.jag.2020.102255
-
Huete, A. R. (1988). A soil-adjusted vegetation index (SAVI). Remote Sensing of Environment, 25(3), 295-309. https://doi.org/10.1016/0034-4257(88)90106-X
-
Huq, S., Kovats, S., Reid, H. ve Satterthwaite, D. (2007). Reducing risks to cities from disasters and climate change. Environment and Urbanization, 19(1), 3-15. https://doi.org/10.1177/0956247807078058
Icaza, L. and Hoeven, F. (2017). Regionalist principles to reduce the urban heat island effect. Sustainability, 9(5), 677. https://doi.org/10.3390/su9050677
-
Ismail, M. H. ve Jusoff, K. (2008). Satellite data classification accuracy assessment based from reference dataset. International Journal of Computer and Information Science and Engineering, 2(3), 23-29.
-
Jensen, R. J. (2015). Introductory digital image processing: A remote sensing perspective (4th ed.). Pearson.
-
Jieli, C., Manchun, L., Yongxue, L., Chenglei, S. ve Wei, H. (2010). Extract residential areas automatically by New Built-up Index. 18th International Conference on Geoinformatics, 1-5. https://doi.org/10.1109/GEOINFORMATICS.2010.5567823
-
Jones H. G. ve Vaughan, R. A. (2010). Remote sensing of vegetation: Principles, techniques, and applications. Oxford University Press, New York, pp. 53.
-
Kawamura, M., Jayamana, S. ve Tsujiko, Y. (1996). Relation between social and environmental conditions in Colombo Sri Lanka and the urban index estimated by satellite remote sensing data. International Archives of Photogrammetry and Remote Sensing, 31, 321-326.
-
Kleerekoper, L., van Esch, M. ve Salcedo, T. B. (2012). How to make a city climate-proof, addressing the urban heat island effect. Resource Conservation Recycling, 64, 30-38. https://doi.org/10.1016/j.resconrec.2011.06.004
-
Kruskal, W. H. ve Wallis, W. A. (1952). Use of Ranks in One-Criterion Variance Analysis. Journal of the American Statistical Association, 47, 583-621. https://doi.org/10.2307/2280779
-
Kuang, W., Liu, Y., Dou, Y., Chi, W., Chen, G., Cheng-feng, G., … ve Zhang, R. (2014). What are hot and what are not in an urban landscape: quantifying and explaining the land surface temperature pattern in beijing, china. Landscape Ecology, 30(2), 357-373. https://doi.org/10.1007/s10980-014-0128-6
-
Kumar, B. P., Babu, K. R., Anusha, B. N. ve Rajasekhar, M. (2022). Geo-environmental monitoring and assessment of land degradation and desertification in the semi-arid regions using Landsat 8 OLI/TIRS, LST, and NDVI approach. Environmental Challenges, 8, 100578. https://doi.org/10.1016/j.envc.2022.100578
-
Levene, H. (1960). Robust Tests for Equality of Variances. Stanford University Press.
-
Li, D., Bou‐Zeid, E. ve Oppenheimer, M. (2014). The effectiveness of cool and green roofs as urban heat island mitigation strategies. Environmental Research Letters, 9(5), 055002. https://doi.org/10.1088/1748-9326/9/5/055002
-
Li, W., Bai, Y., Chen, Q., He, K., Ji, X. ve Han, C. (2014). Discrepant impacts of land use and land cover on urban heat islands: A case study of Shanghai, China. Ecological Indicators, 47, 171-178. https://doi.org/10.1016/j.ecolind.2014.08.015
-
Lillesand, T., Kiefer, R. W. ve Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.
Liu, Y., Li, Q., Yang, L., Mu, K., Zhang, M. ve Liu, J. (2020). Urban heat island effects of various urban morphologies under regional climate conditions. Science of The Total Environment, 743, 140589. https://doi.org/10.1016/j.scitotenv.2020.140589
Liu, Y., Wang, Z., Li, X. ve Zhang, B. (2021). Complexity of the relationship between 2d/3d urban morphology and the land surface temperature: A multiscale perspective. Environmental Science and Pollution Research, 28(47), 66804-66818. https://doi.org/10.1007/s11356-021-15177-7
-
McFeeters, S. K. (1996). The use of the normalized difference water index (NDWI) in the delineation of open water features. International Journal of Remote Sensing, 17(7), 1425-1432. https://doi.org/10.1080/01431169608948714
-
McKnight, P. E. ve Najab, J. (2010). Mann‐Whitney U Test. The Corsini Encyclopedia of Psychology, 1-1.
MGM (2022). Turkish State Meteorological Service. https://mgm.gov.tr/eng/about.aspx. adresinden 1 Nisan 2022 tarihinde erişilmiştir.
-
Mittermüller, J., Erlwein, S., Bauer, A., Trokai, T., Duschinger, S. ve Schönemann, M. (2021). Context-specific, user-centred: Designing urban green infrastructure to effectively mitigate urban density and heat stress. Urban Planning, 6(4), 40-53. https://doi.org/10.17645/up.v6i4.4393
-
Mohamed, S. A. (2021). Comparison of Satellite Images Classification Techniques Using Landsat-8 Data for Land Cover Extraction in Alexandria, Egypt. International Journal of Intelligent Computing & Information Sciences, 21(3), 29-43. http://dx.doi.org/10.21608/ijicis.2021.78853.1098
-
Mohammady, M., Moradi, H. R., Zeinivand, H. ve Temme, A. J. A. M. (2015). A comparison of supervised, unsupervised and synthetic land use classification methods in the north of Iran. International Journal of Environmental Science and Technology, 12, 1515-1526. https://doi.org/10.1007/s13762-014-0728-3
-
Mustafa, M. T., Hassoon, K. I., Hassan M. ve Abd, M. H. (2017). Using water indices (NDWI, MNDWI, NDMI, WRI and AWEI) to detect physical and chemical parameters by apply remote sensing and GIS techniques. International Journal of Research, 10, 117-128. http://dx.doi.org/10.5281/zenodo.1040209
-
Olofsson, P., Foody, G. M., Herold, M., Stehman, S. V., Woodcock, C. E. ve Wulder, M. A. (2014). Good practices for estimating area and assessing accuracy of land change. Remote Sensing of Environment, 148, 42-57. https://doi.org/10.1016/j.rse.2014.02.015
-
Pandey, P. C., Chauhan, A. ve Maurya, N. K. (2022). Evaluation of earth observation datasets for LST trends over India and its implication in global warming. Ecological Informatics, 72, 101843. https://doi.org/10.1016/j.ecoinf.2022.101843
-
Qi, J., Chehbouni, A., Huete, A. R., Kerr, Y. H. ve Sorooshian, S. (1994). A modified soil adjusted vegetation index. Remote Sensing of Environment, 48, 119-126. https://doi.org/10.1016/0034-4257(94)90134-1
-
Rajab, M. A. ve George, L. E. (2021). Stamps extraction using local adaptive k-means and ISODATA algorithms. Indonesian Journal of Electrical Engineering and Computer Science, 21(1), 173-145. http://doi.org/10.11591/ijeecs.v21.i1.pp137-145
-
Ren, Z., He, X., Zheng, H., Zhang, D., Yu, X., Shen, G., … & Guo, R. (2013). Estimation of the relationship between urban park characteristics and park cool island intensity by remote sensing data and field measurement. Forests, 4(4), 868-886. https://doi.org/10.3390/f4040868
-
Ross, A. ve Willson, V. L. (2017). Independent samples T-test. In Basic and advanced statistical tests (pp. 13-16). Brill.
-
Sfîcă, L., Corocăescu, A. C., Crețu, C. Ș., Amihăesei, V. A. ve Ichim, P. (2023). Spatiotemporal Features of the Surface Urban Heat Island of Bacău City (Romania) during the Warm Season and Local Trends of AYS Imposed by Land Use Changes during the Last 20 Years. Remote Sensing, 15(13), 3385. https://doi.org/10.3390/rs15133385
-
Shapiro, S. S. ve Wilk, M. B. (1965). An analysis of variance test for normality (complete samples). Biometrika, 52(3-4), 591-611. https://doi.org/10.2307/2333709
-
Shen, L. ve Li, C. (2010). Water body extraction from landsat etm ımagery using adaboost algorithm. In Proceedings of the 18th International Conference on Geoinformatics, pp. 1-4. https://doi.org/10.1109/GEOINFORMATICS.2010.5567762
-
Singh, C., Madhavan, M., Arvind, J. ve Bazaz, A. (2021). Climate change adaptation in Indian cities: A review of existing actions and spaces for triple wins. Urban Climate, 36, 100783. https://doi.org/10.1016/j.uclim.2021.100783
-
Song, J., Du, S., Feng, X. ve Guo, L. (2014). The relationships between landscape compositions and land surface temperature: Quantifying their resolution sensitivity with spatial regression models. Landscape and Urban Planning, 123, 145-157. http://dx.doi.org/10.1016/j.landurbplan.2013.11.014
-
Stathopoulou, M., Cartalis, C. ve Petrakis, M. (2007). Integrating Corine Land Cover data and Landsat TM for surface emissivity definition: Application to the urban area of Athens, Greece. International Journal of Remote Sensing, 28(15), 3291-3304. http://dx.doi.org/10.1080/01431160600993421
-
Stehman, S. V. (2009). Sampling designs for accuracy assessment of land cover. International Journal of Remote Sensing, 30(20), 5243-5272. http://dx.doi.org/10.1080/01431160903131000
-
Stewart, I. D. ve Mills, G. (2021). The Urban Heat Island. Elsevier.
-
Sun, Q., Wu, Z. ve Tan, J. (2012). The relationship between land surface temperature and land use/land cover in Guangzhou, China. Environmental Earth Sciences, 65(6), 1687-1694. https://doi.org/10.1007/s12665-011-1145-2
-
Talukdar, S., Singha, P., Mahato, S., Pal, S., Liou, Y. A. ve Rahman, A. (2020). Land-use land-cover classification by machine learning classifiers for satellite observations-A review. Remote Sensing, 12(7), 1135. https://doi.org/10.3390/rs12071135
-
Tan, J., Zheng, Y., Tang, X., Guo, C., Zhang, L., Song, G., … ve Chen, H. (2009). The urban heat island and its impact on heat waves and human health in Shanghai. International Journal of Biometeorology, 54(1), 75-84. https://doi.org/10.1007/s00484-009-0256-x
-
Taufik, A., Syed Ahmad, S. S. ve Azmi, E. F. (2019). Classification of Landsat 8 satellite data using unsupervised methods. In Intelligent and Interactive Computing: Proceedings of IIC 2018 (pp. 275-284). Springer Singapore. https://doi.org/10.1007/978-981-13-6031-2_46
-
Thornthwaite, C. W. (1948). An approach toward a rational classification of climate. Geographical Review, 38(1), 55-94. https://doi.org/10.2307/210739
-
Touchaei, A. G. ve Wang, Y. (2015). Characterizing urban heat island in Montreal (Canada)-Effect of urban morphology. Sustainable Cities and Society, 19, 395-402. https://doi.org/10.1016/j.scs.2015.03.005
-
Tran, D., Pla, F., Carmona, P., Myint, S., Caetano, M. ve Kieu, H. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119-132. https://doi.org/10.1016/j.isprsjprs.2017.01.001
-
Tucker, C. J. (1979). Red and photographic infrared linear combinations for monitoring vegetation? Remote Sensing of Environment, 8, 127-150. https://doi.org/10.1016/0034-4257(79)90013-0
-
Tukey, J. (1949). Comparing individual means in the analysis of variance. Biometrics, 5(2), 99-114. https://doi.org/10.2307/3001913
-
TÜİK (2023). Turkish Statistical Institute. Retrieved form https://www.tuik.gov.tr/Home/Index adresinden 20 Haziran 2023 tarihinde erişilmiştir.
-
UN (2019). World Urbanization Prospects 2018 Highlights, Department of Economic and Social Affairs, Trends in Urbanization. https://population.un.org/wup/publications/files/wup2018-highlights.pdf adresinden 2 Mart 2021 tarihinde erişilmiştir.
-
UNFPA (2022). World Population Dashboard. Retrieved from https://www.unfpa.org/data/world-population-dashboard adresinden 4 Nisan 2022 tarihinde erişilmiştir.
-
USGS (2013). Product guide: Landsat climate data record (CDR). Surface Reflectance, Version 5.3, Department of the Interior U.S. Geological Survey: Washinton, DC, USA, December 2013.
-
Wang, Z. (2019). The relationship between land use, land cover change, and the heat island effect in xi’an city, china. Applied Ecology and Environmental Research, 17(4). https://doi.org/10.15666/aeer/1704_77957806
-
Weng, Q., Lu, D. ve Schubring, J. (2004). Estimation of land surface Temperature vegetation abundance relationship for urban heat island studies. Remote Sensing of Environment, 89(4), 467-483. https://doi.org/10.1016/j.rse.2003.11.005
-
Xu, H. (2006). Modification of normalised difference water index (NDWI) to enhance open water features in remotely sensed imagery. International Journal of Remote Sensing, 27(14), 3025-3033. https://doi.org/10.1080/01431160600589179
-
Yang, Y., Fan, S., Ma, J., Zheng, W., Song, L. ve Wei, C. (2022). Spatial and temporal variation of heat islands in the main urban area of zhengzhou under the two-way influence of urbanization and urban forestry. Plos One, 17(8), e0272626. https://doi.org/10.1371/journal.pone.0272626
-
Yesil, P. ve Guzel, M. (2021). Evaluation of land cover/land use change in Ordu province (1990-2018) Using CORINE Data. Suleyman Demirel University Journal of Natural and Applied Sciences, 25(3), 492-498. https://doi.org/10.19113/sdufenbed.809991
-
Yilmaz, O. S., Gulgen, F., Balik Sanli, F. ve Ates, A. M. (2023). The performance analysis of different water ındices and algorithms using sentinel-2 and landsat-8 ımages in determining water surface: Demirkopru dam case study. Arabian Journal for Science and Engineering, 48(6), 7883-7903. https://link.springer.com/article/10.1007/s13369-022-07583-x
-
Yucekaya, M. ve Tirnakci, A. (2023). Microclimatic effect of urban renewal: A case study of Kayseri/Turkey. Landscape and Ecological Engineering, 19(3), 471-483. https://doi.org/10.1007/s11355-023-00554-w
-
Zha, Y., Gao, J. ve Ni, S. (2003). Use of normalized difference built-up index in automatically mapping urban areas from TM imagery. International Journal of Remote Sensing, 24, 583-594. https://doi.org/10.1080/01431160304987
-
Zhong, X., Wang, L., Zhou, J., Li, X., Qi, J., Song, L. ve Wang, Y. (2020). Precipitation dominates long-term water storage changes in Nam Co Lake (Tibetan Plateau) accompanied by intensified cryosphere melts revealed by a basin-wide hydrological modelling. Remote Sensing, 12(12), 1926. https://doi.org/10.3390/rs12121926
-
Zhou, X. ve Hong, C. (2018). Impact of urbanization-related land use land cover changes and urban morphology changes on the urban heat island phenomenon. Science of The Total Environment, 635, 1467-1476. https://doi.org/10.1016/j.scitotenv.2018.04.091
-
Zou, F., Li, H. ve Hu, Q. (2020). Responses of vegetation greening and land surface temperature variations to global warming on the Qinghai-Tibetan Plateau, 2001-2016. Ecological Indicators, 119, 106867. https://doi.org/10.1016/j.ecolind.2020.106867