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Landsat-8 uydu verilerini kullanarak Kütahya'daki kentsel isı adasının (UHI) mekansal değerlendirmesi

Yıl 2025, , 122 - 131, 15.01.2025
https://doi.org/10.28948/ngumuh.1527341

Öz

Kentsel Isı Adası (UHI) etkisi, şehir alanlarının, insan faaliyetleri ve değişiklikleri nedeniyle, kırsal çevreye göre önemli ölçüde daha yüksek sıcaklıklara maruz kalması olarak tanımlanabilir. Bu değişiklikler arasında doğal arazi örtüsünün geçirimsiz yüzeylerle değişmesi, bitki örtüsünün azalması ve ısıyı emen malzemelerin artması yer almaktadır. Kütahya merkez ilçesinin, yoğun nüfusu ve bina yerleşimi UHI etkisinin artmasına neden olmaktadır. Coğrafi Bilgi Sistemi (CBS) ve araçları, kentsel alanlardaki UHI'yi değerlendirmede yaygın olarak kullanılmakta olup, hem araştırmacılara hem de yerel yetkililere önemli bilgiler sunmaktadır. Çalışma kapsamında Landsat-8 uydu verileri kullanılarak Kütahya’daki kentsel ısı adasının mekansal olarak değerlendirilmesi amaçlanmıştır. Çalışma alanı için Kentsel Isı Adası (UHI) haritası oluşturmak amacıyla 8 Ağustos 2023'te (Path: 179, Row: 33, Cloud Cover: %0) alınan Landsat-8 görüntüleri kullanılmış, 10.60 - 11.19 µm aralığında çalışan verilerinden yararlanılmıştır. Kütahya şehir merkezi için Landsat-8 verileri kullanılarak yapılan mekansal analizle altı farklı sınıf tanımlanmış olup, arazi yüzey sıcaklığı değerleri kullanılarak UHI haritası oluşturulmuştur. En yüksek ve en düşük UHI değerleri sırasıyla 4.245°C ile -3.457°C arasında değişmektedir. Yoğun bina yapısının bulunmadığı, kaya yüzeyleri ve sınırlı yeşil alanlarla karakterize edilen bölgelerde ortalama UHI'nin %12 arttığı gözlemlenmiştir. Buna karşılık, parklar, ormanlar ve seyrek yerleşim alanları olan bölgelerde UHI %10 azalmaktadır. Bu çalışma ile Kütahya şehir merkezi için kapsamlı bir UHI değerlendirmesi yapılmıştır. Elde edilen sonuçların araştırmacılar ve yerel yetkililer için önemli bir kaynak olması beklenirken, mühendislik jeolojisi, kentsel jeoloji ve şehir planlama alanlarında da faydalı olması öngörülmektedir.

Proje Numarası

2024-01

Kaynakça

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Spatial assessment of urban heat island (UHI) in Kütahya using Landsat-8 satellite data

Yıl 2025, , 122 - 131, 15.01.2025
https://doi.org/10.28948/ngumuh.1527341

Öz

The Urban Heat Island (UHI) effect refers to the phenomenon where urban areas experience significantly higher temperatures than their rural surroundings due to human activities and modifications, such as replacing natural land cover with impervious surfaces, reducing vegetation, and increasing heat-absorbing materials. Kütahya central district has a dense population and building layout, which contributes to the intense UHI. Geographic Information System (GIS) and its tools are widely used in assessing UHI in urban areas, providing insights for both researchers and local authorities. The study aims to spatially evaluate the urban heat island in Kütahya using Landsat-8 satellite data. Landsat-8 images, operating in the 10.60 - 11.19 µm range acquired on August 8, 2023 (Path: 179, Row: 33, Cloud Cover: 0%) were utilized to create the Urban Heat Island (UHI) map for the study area. Through spatial analysis using Landsat-8 data for Kütahya city center, six different classes were defined, with the UHI map created using land surface temperature values. The highest and lowest UHI values vary between 4.245°C and -3.457°C. It has been observed that the average UHI increases by 12% in areas lacking dense building structures, characterized by rock surfaces and limited green areas. Conversely, in areas with parks, forests, and sparse settlements, the UHI decreases by 10%. With this study, a comprehensive evaluation of UHI was conducted for Kütahya city center. While the results obtained are expected to be an important resource for researchers and local authorities, they are also anticipated to be beneficial in the fields of engineering geology, urban geology, and urban planning.

Proje Numarası

2024-01

Kaynakça

  • M.K. Anser, M. Alharthi, B. Aziz, S. Wasim, Impact of urbanization, economic growth, and population size on residential carbon emissions in the SAARC countries, Clean Technologies and Environmental Policy. 22, 923-936, 2022. doi:10.1007/s10098-020-01833-y.
  • L. Howard, The Climate of London, Harvey and Dorton. I-II (1883).
  • K. Kłysik, K. Fortuniak, Temporal and spatial characteristics of the urban heat island of Łódź, Poland, Atmospheric Environment. 33 3885-3895, 1999. doi:10.1016/S1352-2310(99)00131-4.
  • H. Li, Y. Zhou, G. Jia, K. Zhao, J. Dong, Quantifying the response of surface urban heat island to urbanization using the annual temperature cycle model, Geoscience Frontiers. 13 101141, 2022. doi:10.1016/j.gsf.2021.101141.
  • L. Li, Y. Zha, R. Wang, Relationship of surface urban heat island with air temperature and precipitation in global large cities, Ecological Indicators. 117, 106683, 2020. doi:10.1016/j.ecolind.2020.106683.
  • S. Barrao, R. Serrano-Notivoli, J.M. Cuadrat, E. Tejedor, M.A. Saz Sánchez, Characterization of the UHI in Zaragoza (Spain) using a quality-controlled hourly sensor-based urban climate network, Urban Climate.44 101207, 2022. doi:10.1016/j.uclim.2022.1 01207.
  • X. Gui, L. Wang, R. Yao, D. Yu, C. Li, 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, 2019. doi:10.1007/s11356-019-06273-w.
  • H. Takebayashi, M. Moriyama, Relationships between the properties of an urban street canyon and its radiant environment: Introduction of appropriate urban heat island mitigation technologies, Solar Energy. 86, 2255-2262, 2012. doi:10.1016/j.solener.2012.04.019.
  • G. Ferguson, A.D. Woodbury, Urban heat island in the subsurface, Geophysical Research Letters. 34, GL032324, 2007. doi:10.1029/2007GL032324.
  • K. Menberg, P. Blum, A. Schaffitel, P. Bayer, Long-Term Evolution of Anthropogenic Heat Fluxes into a Subsurface Urban Heat Island, Environmental Science & Technology. 47, 9747-9755, 2013. doi:10.10 21/es401546u.
  • H.N. Pollack, S. Huang, P.-Y. Shen, Climate Change Record in Subsurface Temperatures: A Global Perspective, Science. 282, 279-281, 1998. doi:10.11 26/science.282.5387.279.
  • K.P. Gallo, T.W. Owen, Satellite-Based Adjustments for the Urban Heat Island Temperature Bias, Journal of Applied Meteorology. 38, 806-813, 1999. doi:10.1175/1520-0450(1999)038<0806:SBAFTU> 2.0.CO;2.
  • F. Perrier, J.-L. Le Mouël, J.-P. Poirier, M.G. Shnirman, Long-term climate change and surface versus underground temperature measurements in Paris, International Journal of Climatology. 25, 1619-1631, 2005. doi:10.1002/joc.1211.
  • R.A. Spronken-Smith, T.R. Oke, Scale Modelling of Nocturnal Cooling in Urban Parks, Boundary-Layer Meteorology. 93, 287-312, 1999. doi:10.1023/A:10 02001408973.
  • M. Taniguchi, T. Uemura, K. Jago‐on, Combined Effects of Urbanization and Global Warming on Subsurface Temperature in Four Asian Cities, Vadose Zone Journal. 6 591-596, 2007. doi:10.2136/vzj2006 .0094.
  • K. Kataoka, F. Matsumoto, T. Ichinose, M. Taniguchi, Urban warming trends in several large Asian cities over the last 100 years, Science of The Total Environment. 407, 3112-3119, 2009. doi:10.1016/ j.scitotenv.2008.09.015.
  • M. Karaca, Ü. Anteplioĝlu, H. Karsan, Detection of urban heat island in Istanbul, Turkey, Il Nuovo Cimento C. 18 (1), 995, 49-55. doi:10.1007/BF02 561458.
  • Y. Ezber, O. Lutfi Sen, T. Kindap, M. Karaca, Climatic effects of urbanization in istanbul: a statistical and modeling analysis, International Journal of Climatology. 27, 667-679, 2007. doi:10.1002/joc.1420.
  • O.S. Pinho, M.D.M. Orgaz, The urban heat island in a small city in coastal Portugal, International Journal of Biometeorology. 44, 198-203, 2020. doi:10.1007/ s004840000063
  • A.S. Öngen, Z.A. Ergüler, The effect of urban heat island on groundwater located in shallow aquifers of Kutahya city center and shallow geothermal energy potential of the region, Bulletin Of The Mineral Research and Exploration. 1-24, 2020. doi:10.19111/ bulletinofmre.820395.
  • R.U. Acar, C. Özkul, Investigation of heavy metal pollution in roadside soils and road dusts along the Kütahya–Eskişehir Highway, Arabian Journal of Geosciences. 13, 216, 2020. doi:10.1007/s12517-020-5206-2.
  • R.U. Acar, E. Zengi̇n, Performance Assessment of Landsat 8 and Sentinel-2 Satellite Images for the Production of Time Series Land Use/Land Cover (LULC) Maps, Journal of Scientific Reports-A. 1-15, 2023. doi:10.59313/jsr-a.1213548.
  • M. Bagyaraj, V. Senapathi, S. Karthikeyan, S.Y. Chung, R. Khatibi, A.A. Nadiri, B. Asgari Lajayer, A study of urban heat island effects using remote sensing and GIS techniques in Kancheepuram, Tamil Nadu, India, Urban Climate. 51, 101597, 2023. doi:10.1016/ j.uclim.2023.101597.
  • B. Doğan, F. Şen, E. Zengin, S. Alaçam, N. Çakıcı Alp, Tectonic Model of the Surface Ruptures Geometry of M 7.7 and M 7.6 Earthquakes, of Their Source Faults of Kahramanmaraş (Türkiye) on 06/02/2023, içinde: Chamber of Geological Engineers of Türkiye, Ankara, Türkiye, 2023.
  • R. Eker, A. Aydın, J. Hübl, Unmanned aerial vehicle (UAV)-based monitoring of a landslide: Gallenzerkogel landslide (Ybbs-Lower Austria) case study, Environmental Monitoring and Assessment. 190, 28, 2017. doi:10.1007/s10661-017-6402-8.
  • Z.A. Erguler, E. Zengin, G. Kalyoncu Erguler, Time-dependent physicomechanical behavior of ballasts used for railway between Sabuncupinar and Kütahya in Western Turkey, Environmental Earth Sciences. 75 918, 2016. doi:10.1007/s12665-016-5724-0.
  • K.M. Nissen, M. Wilde, T.M. Kreuzer, A. Wohlers, B. Damm, U. Ulbrich, A decrease in rockfall probability under climate change conditions in Germany, Natural Hazards and Earth System Sciences. 23, 2737-2748, 2023. doi:10.5194/nhess-23-2737-2023.
  • E. Zengin, Inundation risk assessment of Eastern Mediterranean Coastal archaeological and historical sites of Türkiye and Greece, Environmental Monitoring and Assessment. 195, 968, 2023. doi:10.10 07/s10661-023-11549-3.
  • E. Zengin, A Combined Assessment of Sea Level Rise (SLR) Effect on Antalya Gulf (Türkiye) and Future Predictions on Land Loss, Journal of the Indian Society of Remote Sensing. 51, 1121-1133, 2023. doi:10.1007/s12524-023-01694-0.
  • E. Zengin, Z.A. Erguler, Experimental investigation of pore-fracture relationship on failure behaviour of porous rock materials, Bulletin of Engineering Geology and the Environment. 81, 351, 2022. doi:10.1007/s10064-022-02857-y.
  • C. Keeratikasikorn, S. Bonafoni, Urban Heat Island Analysis over the Land Use Zoning Plan of Bangkok by Means of Landsat 8 Imagery, Remote Sensing. 10, 440, 2018. doi:10.3390/rs10030440.
  • V.I. Kashtan, K.L. Serhieieva, O.V. Korobko, D.V. Ivanov, Search and assessment of urban heat islands on digital satellite images, System Technologies. 3, 87-98, 2023. doi:10.34185/1562-9945-3-146-2023-09.
  • G. Seeberg, A. Hostlowsky, J. Huber, J. Kamm, L. Lincke, C. Schwingshackl, Evaluating the Potential of Landsat Satellite Data to Monitor the Effectiveness of Measures to Mitigate Urban Heat Islands: A Case Study for Stuttgart (Germany), Urban Science. 6, 82, 2022. doi:10.3390/urbansci6040082.
  • N. Aslan, D. Koc-San, The Use of Land Cover Indices for Rapid Surface Urban Heat Island Detection from Multi-Temporal Landsat Imageries, ISPRS International Journal of Geo-Information. 10, 416, 2021. doi:10.3390/ijgi10060416.
  • C.R.D. Almeida, L. Furst, A. Gonçalves, A.C. Teodoro, Remote Sensing Image-Based Analysis of the Urban Heat Island Effect in Bragança, Portugal, Environments. 9, 98, 2022. doi:10.3390/environme nts9080098.
  • N. Na, D. Xu, W. Fang, Y. Pu, Y. Liu, H. Wang, Automatic Detection and Dynamic Analysis of Urban Heat Islands Based on Landsat Images, Remote Sensing. 15, 4006, 2023. doi:10.3390/rs15164006.
  • M. Kottek, J. Grieser, C. Beck, B. Rudolf, F. Rubel, World Map of the Köppen-Geiger Climate Classification Updated, Meteorologische Zeitschrift. 15, 259-263, 2006. doi:10.1127/0941-2948/2006/01 30.
  • M.C. Anderson, J.M. Norman, W.P. Kustas, R. Houborg, P.J. Starks, N. Agam, A thermal-based remote sensing technique for routine mapping of land-surface carbon, water and energy fluxes from field to regional scales, Remote Sensing of Environment. 112, 4227-4241, 2008. doi:10.1016/j.rse.2008.07.009.
  • N.A. Brunsell, R.R. Gillies, Length Scale Analysis of Surface Energy Fluxes Derived from Remote Sensing, Journal of Hydrometeorology. 4, 1212-1219, 2003. doi:10.1175/1525-7541(2003)004<1212:LSAOSE>2 .0.CO;2.
  • A. Karnieli, N. Agam, R.T. Pinker, M. Anderson, M.L. Imhoff, G.G. Gutman, N. Panov, A. Goldberg, Use of NDVI and Land Surface Temperature for Drought Assessment: Merits and Limitations, Journal of Climate. 23, 618-633, 2010. doi:10.1175/2009JCL I2900.1.
  • U. Avdan, G. Jovanovska, Algorithm for Automated Mapping of Land Surface Temperature Using LANDSAT 8 Satellite Data, Journal of Sensors. e1480307, 2016. doi:10.1155/2016/1480307.
  • J.A. Barsi, J.R. Schott, S.J. Hook, N.G. Raqueno, B.L. Markham, R.G. Radocinski, Landsat-8 Thermal Infrared Sensor (TIRS) Vicarious Radiometric Calibration, Remote Sensing. 6, 11607-11626, 2014. doi:10.3390/rs61111607.
  • H.D. Young, R.A. Freedman, University Physics with Modern Physics, Pearson Education, 2015.
  • S. Mohanasundaram, T. Baghel, V. Thakur, P. Udmale, S. Shrestha, Reconstructing NDVI and land surface temperature for cloud cover pixels of Landsat-8 images for assessing vegetation health index in the Northeast region of Thailand, Environmental Monitoring and Assessment. 195, 211, 2022. doi:10. 1007/s10661-022-10802-5.
  • A. Naga Rajesh, S. Abinaya, G. Purna Durga, T.V. Lakshmi Kumar, Long-term relationships of MODIS NDVI with rainfall, land surface temperature, surface soil moisture and groundwater storage over monsoon core region of India, Arid Land Research and Management. 37, 51-70, 2023. doi:10.1080/15324982 .2022.2106323.
  • W. Ullah, K. Ahmad, S. Ullah, A.A. Tahir, M.F. Javed, A. Nazir, A.M. Abbasi, M. Aziz, A. Mohamed, Analysis of the relationship among land surface temperature (LST), land use land cover (LULC), and normalized difference vegetation index (NDVI) with topographic elements in the lower Himalayan region, Heliyon. 9, e13322, 2023. doi:10.1016/j.heliyon.2023 .e13322.
  • S. Ma, L.-J. Wang, L. Ye, J. Jiang, Vegetation restoration thresholds under different vegetation types and altitude gradients in the Sichuan-Yunnan ecological shelter, China, Journal of Environmental Management. 340, 117910, 2023. doi:10.1016/j.jenv man.2023.117910.
  • C. Ru, S.-B. Duan, X.-G. Jiang, Z.-L. Li, C. Huang, M. Liu, An extended SW-TES algorithm for land surface temperature and emissivity retrieval from ECOSTRESS thermal infrared data over urban areas, Remote Sensing of Environment. 290, 113544, 2023. doi:10.1016/j.rse.2023.113544.
  • Y. Chen, J. Yang, W. Yu, J. Ren, X. Xiao, J.C. Xia, Relationship between urban spatial form and seasonal land surface temperature under different grid scales, Sustainable Cities and Society. 89, 104374, 2023. doi:10.1016/j.scs.2022.104374.
  • A. Tariq, F. Mumtaz, M. Majeed, X. Zeng, Spatio-temporal assessment of land use land cover based on trajectories and cellular automata Markov modelling and its impact on land surface temperature of Lahore district Pakistan, Environmental Monitoring and Assessment. 195, 114, 2022. doi:10.1007/s10661-022-10738-w.
  • M. Zhang, A.-A. Kafy, P. Xiao, S. Han, S. Zou, M. Saha, C. Zhang, S. Tan, Impact of urban expansion on land surface temperature and carbon emissions using machine learning algorithms in Wuhan, China, Urban Climate. 47, 101347, 2023. doi:10.1016/j.uclim.2022 .101347.
  • C. Wang, Z. Ren, Y. Dong, P. Zhang, Y. Guo, W. Wang, G. Bao, Efficient cooling of cities at global scale using urban green space to mitigate urban heat island effects in different climatic regions, Urban Forestry & Urban Greening. 74, 127635, 2022. doi:10.1016/j.ufug.2022.127635.
  • X.D. Xiao, L. Dong, H. Yan, N. Yang, Y. Xiong, The influence of the spatial characteristics of urban green space on the urban heat island effect in Suzhou Industrial Park, Sustainable Cities and Society. 40, 428-439, 2018. doi:10.1016/j.scs.2018.04.002.
  • W. Zhou, W. Yu, Z. Zhang, W. Cao, T. Wu, How can urban green spaces be planned to mitigate urban heat island effect under different climatic backgrounds? A threshold-based perspective, Science of The Total Environment. 890, 164422, 2023. doi:10.1016/j.scitot env.2023.164422.
  • J. Ahmad, J.A. Eisma, Capturing Small-Scale Surface Temperature Variation across Diverse Urban Land Uses with a Small Unmanned Aerial Vehicle, Remote Sensing. 15, 2042, 2023. doi:10.3390/rs15082042.
  • Y.-I. Cho, D. Yoon, M.-J. Lee, Comparative Analysis of Urban Heat Island Cooling Strategies According to Spatial and Temporal Conditions Using Unmanned Aerial Vehicles(UAV) Observation, Applied Sciences. 13, 10052, 2023. doi:10.3390/app131810052.
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Toplam 57 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Mühendislik Jeolojisi
Bölüm Araştırma Makaleleri
Yazarlar

Ali Samet Öngen 0000-0002-4019-7157

Enes Zengin 0000-0002-5740-7763

Proje Numarası 2024-01
Erken Görünüm Tarihi 25 Aralık 2024
Yayımlanma Tarihi 15 Ocak 2025
Gönderilme Tarihi 2 Ağustos 2024
Kabul Tarihi 23 Ekim 2024
Yayımlandığı Sayı Yıl 2025

Kaynak Göster

APA Öngen, A. S., & Zengin, E. (2025). Spatial assessment of urban heat island (UHI) in Kütahya using Landsat-8 satellite data. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, 14(1), 122-131. https://doi.org/10.28948/ngumuh.1527341
AMA Öngen AS, Zengin E. Spatial assessment of urban heat island (UHI) in Kütahya using Landsat-8 satellite data. NÖHÜ Müh. Bilim. Derg. Ocak 2025;14(1):122-131. doi:10.28948/ngumuh.1527341
Chicago Öngen, Ali Samet, ve Enes Zengin. “Spatial Assessment of Urban Heat Island (UHI) in Kütahya Using Landsat-8 Satellite Data”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 14, sy. 1 (Ocak 2025): 122-31. https://doi.org/10.28948/ngumuh.1527341.
EndNote Öngen AS, Zengin E (01 Ocak 2025) Spatial assessment of urban heat island (UHI) in Kütahya using Landsat-8 satellite data. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 14 1 122–131.
IEEE A. S. Öngen ve E. Zengin, “Spatial assessment of urban heat island (UHI) in Kütahya using Landsat-8 satellite data”, NÖHÜ Müh. Bilim. Derg., c. 14, sy. 1, ss. 122–131, 2025, doi: 10.28948/ngumuh.1527341.
ISNAD Öngen, Ali Samet - Zengin, Enes. “Spatial Assessment of Urban Heat Island (UHI) in Kütahya Using Landsat-8 Satellite Data”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi 14/1 (Ocak 2025), 122-131. https://doi.org/10.28948/ngumuh.1527341.
JAMA Öngen AS, Zengin E. Spatial assessment of urban heat island (UHI) in Kütahya using Landsat-8 satellite data. NÖHÜ Müh. Bilim. Derg. 2025;14:122–131.
MLA Öngen, Ali Samet ve Enes Zengin. “Spatial Assessment of Urban Heat Island (UHI) in Kütahya Using Landsat-8 Satellite Data”. Niğde Ömer Halisdemir Üniversitesi Mühendislik Bilimleri Dergisi, c. 14, sy. 1, 2025, ss. 122-31, doi:10.28948/ngumuh.1527341.
Vancouver Öngen AS, Zengin E. Spatial assessment of urban heat island (UHI) in Kütahya using Landsat-8 satellite data. NÖHÜ Müh. Bilim. Derg. 2025;14(1):122-31.

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