Araştırma Makalesi
BibTex RIS Kaynak Göster

Evaluation of the urban ecosystem and local climate changes caused by urbanization in İzmir in terms of long-term UHI formation with the SSI method

Yıl 2023, Cilt: 7 Sayı: 1, 11 - 58, 30.06.2023
https://doi.org/10.32569/resilience.1172781

Öz

Even if urbanization offers various opportunities to people living in todays world. It also comes with some side effects such as worsening climate conditions by creating thermal pollution due to certain urban activities, sectoral urban designs and consequent patterns in cities. In local sense, the old climatic conditions beforete the change because of urbanization in rural areas can be called natural when they are compared with new conditions deteriorated by widespread urbanization. Thus, thermal pollution changes city’s local climate over time and negatively affects city’s resilience.

Here in this research, it is determined themperature related local climate variation caused by specific city activities in the city of Izmir by analysing time series thermal data distribution over the entire city over a certain period of time and for this analyse even a novel approach is introduced and suggested which is a Simulated Single Image (SSI) method based on Simulated Single Data (SSD) statistical analyze. The method uses not only trend or average values of time series data as being as usual but it uses both and also standart deviation of the data to support a single output from the time series data analyse. Thus, outputs were obtained as single images from the the LANDSAT time series data to represent where generally Urban Hot Spots (UHS) appear and Urban Heat Islands (UHI) develop in the city. Stereo representation of the study region is also used to visually examine the topographical effect on UHI distribution in the city.

Izmir which is the third mostly populated city of Turkey located on the Izmir Gulf of Egean Sea is chosen as study area and the study clearly demonstrated that industrial regions and roads with large surfaces, bare lands with sparse bushes, empty or sparse grassy urban lands and more significantly the urban land parts faced to certain directions are the main urban land cover and structure types contributing UHSs to appear and UHI developments in the city.

Kaynakça

  • Ahmad, F. and Goparaju, L. (2016). Geospatial Technology in Urban Forest suitability: Analysis for Ranchi, Jharkhand, India. Ecological Questions, 24/2016: 45 – 57. http://dx.doi.org/10.12775/EQ.2016.011.
  • Akbari, H., Pomerantz, M., & Taha, H. (2001). Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Solar Energy, 70(3), 295–310.
  • Almazroui, M., Mashat, A., Assiri, M.E. et al. (2017). Application of Landsat Data for Urban Growth Monitoring in Jeddah. Earth Syst Environ, 1, 25. https://doi.org/10.1007/s41748-017-0028-4
  • Amir, S. M., Dongyun, L., Li, P., Rasool, U., Ullah, K. T., Javaid, A. F. T., Wang, L., Fan, B., Rasool, M.A. (2020). Assessment and simulation of land use and land cover change impacts on the land surface temperature of Chaoyang District in Beijing, China. PeerJ, 8:e9115 http://doi.org/10.7717/peerj.9115
  • Amiri, R., Weng, Q., Alimohammadi, A., & 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://www.sciencedirect.com/science/article/pii/S0034425712000326)
  • Anderson, M. C., Allen, R. G., Morse, A., Kustas, W. P. (2012). Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sensing of Environment, Volume 122, Pages 50-65, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2011.08.025.
  • Asgarian, A., Amiri, B.J., & Sakieh, Y. (2015). Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach. Urban Ecosystems, 18, 209–222.
  • Ayanlade, A. (2016). Seasonality in the daytime and night-time intensity of land surface temperature in a tropical city are. Science of The Total Environment, Volumes 557–558, Pages 415-424, ISSN 0048-9697,https://doi.org/10.1016/j.scitotenv.2016.03.027.
  • Bala, R., Prasad, R., Yadav, V. P. (2020). A comparative analysis of day and night land surface temperature in two semi-arid cities using satellite images sampled in different seasons. Advances in Space Research, Volume 66, Issue 2, Pages 412-425, ISSN 0273-1177, https://doi.org/10.1016/j.asr.2020.04.009.
  • Bendib, A., Dridi, H., & Kalla, M.I. (2017). Contribution of Landsat 8 data for the estimation of land surface temperature in Batna city, Eastern Algeria. Geocarto International, 32(5), 503–513.
  • Boryan, C., Yang, Z., Mueller, R., Craig, M. (2011). Monitoring US agriculture: The US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program. Geocarto Int. 26, 341–358.
  • Bowker, David E. (2010). Spectral Reflectances of Natural Targets for Use in Remote Sensing Studies 1139. cilt/NASA reference publication (NASA)/USA, 5 Eki 2010, 185 p.
  • Buyadi, S. N. A., Wan Mohd, W. M. N., & Misni, A. (2013). The Impact of Land Use Changes on the Surface Temperature Distribution of Area Surrounding the National Botanic Garden, Shah Alam. AMER International Conference on Quality of Life (p. 10). Pulau Langkawi.
  • Buyantuyev, A., & 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.
  • Camilloni, I., Barros, V. (1997). On the urban heat island effect dependence on temperature trends. Clim. Change. 37, 665-681.
  • Chander, G., and Markham, B. (2003). Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges. IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 11, pp. 2674-2677, Nov. 2003. doi: 10.1109/TGRS.2003.818464.
  • Chander, G., Markham, B. L., Barsi, J.A. (2007). Revised Landsat-5 Thematic Mapper Radiometric Calibration. IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 3, pp. 490-494, July 2007. doi: 10.1109/LGRS.2007.898285.
  • Chander, G., Markham, B. L., Helder, D. L. (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, Volume 113, Issue 5, Pages 893-903. ISSN 0034-4257, https://doi.org/10.1016/j.rse.2009.01.007.
  • Chaudhuri, S., Kumar, A. (2021). Evaluating the contribution of urban ecosystem services in regulating thermal comfort. Spat. Inf. Res. 29, 71–82. https://doi.org/10.1007/s41324-020-00336-8
  • Chen, A., Yao, X.A., Sun, R., & Chen, L. (2014). Effect of urban green patterns on surface urban cool islands and its seasonal variations. Urban Forestry & Urban Greening, 13, 646–654.
  • Chen, Q., Ren, J., Li, Z., Ni, C. (2009). Urban Heat Island Effect Research in Chengdu City Based on MODIS Data. In Proceedings of 3rd International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2009, Beijing, China, 11–13 June 2009. pp. 1-5.
  • Chen, X., Ding, J., Wang, J., Ge, X., Raxidin, M., Liang, J., Chen, X., Zhang, Z., Cao, X., Ding, Y. (2020). Retrieval of Fine-Resolution Aerosol Optical Depth (AOD) in Semiarid Urban Areas Using Landsat Data: A Case Study in Urumqi, NW China. Remote Sens., 12, 467.
  • Chen, X.C., Zhao, H.M., Li, P.X., & Yin, Z.Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104(2), 133–146.
  • Chen, Y., Wang, J., & Li, X. (2002). A study on urban thermal field in summer based on satellite remote sensing. Remote Sensing for Land Management and Planning, 4, 55–59.
  • Chen, Y.C., Chiu, H.W., Su, Y.F., Wu, Y.C., Cheng, K.S. (2016). Does urbanization increase diurnal land surface temperature variation? Evidence and implications. Landsc. Urban Plan., 157, 247–258. http://dx.doi.org/10.1016/j.landurbplan.2016.06.014.
  • Cheng, K.S., Su, Y.F., Kuo, F.T., Hung, W.C., Chiang, J.L. (2008). Assessing the effect of landcover on air temperature using remote sensing images: a pilot study in northern Taiwan. Landsc. Urban Plan., 85(2) 85–96. http://dx.doi.org/10.1016/j.landurbplan.2007.09.014.
  • Choi, H., Lee, W., & Byun, W. (2012). Determining the Effect of Green Spaces on Urban Heat Distribution Using Satellite Imagery. Asian Journal of Atmospheric Environment, 6(June), 127-135. doi:http://dx.doi.org/10.5572/ajae.2012.6.2.127.
  • Corumluoglu, O., Asri, I. (2015). The effect of urban heat island on Izmir’s city ecosystem and climate. Environ Sci. Pollut. Res., 22, 3202–3211. https://doi.org/10.1007/s11356-014-2874-z
  • Coseo, P., & Larsen, L. (2014). How factors of land use/land cover, building configuration, and adjacent heat sources and sinks explain urban heat islands in Chicago. Landscape and Urban Planning, 125, 117–129.
  • Coutts, A.M., White, E.C., Tapper, N.J., Beringer, J., & Livesley, S.J. (2016). Temperature and human thermal comfort effects of street trees across three contrasting street canyon environments. Theoretical and Applied Climatology, 124(55), 55–68.
  • Dadras, M., Shafri, H. Z. M., Ahmad, N., Pradhan, Bi., Safarpour, S. (2014). Land Use/Cover Change Detection and Urban Sprawl Analysis in Bandar Abbas City, Iran. The Scientific World Journal. vol. 2014, Article ID 690872, 12 pages. https://doi.org/10.1155/2014/690872.
  • DanInAfterEffects. (2011). Cross Eye 3D [Video]. Youtube. https://www.youtube.com/watch?v=4L-We9onn9s.
  • Deilami, K., & Kamruzzaman, M. (2017). Modelling the urban heat island effect of smart growth policy scenarios in Brisbane. Land Use Policy, 64, 38–55.
  • Detwiller, J. (1970). Deep soil temperature trends and urban effects at Paris. J. Appl. Meteorol., 9, 178-180.
  • Dong, Q., Wang, C., Xiong, C., Li, X., Wang, H., & Ling, T. (2019). Investigation on the Cooling and Evaporation Behavior of Semi-Flexible Water Retaining Pavement based on Laboratory Test and Thermal-Mass Coupling Analysis. Materials (Basel, Switzerland), 12(16), 2546. https://doi.org/10.3390/ma12162546
  • Dousset, B., Gourmelon, F., (2003). Satellite multi-sensor data analysis of urban surface temperatures and landcover. ISPRS J. Photogramm. Remote Sens., 58:43–54. http://dx.doi. org/10.1016/S0924-2716(03)00016-9.
  • Du, H.,Wang, D.,Wang, Y., Zhao, X., Qin, F., Jiang, H.,&Cai, Y. (2016a). Influences of land cover types, meteorological conditions, anthropogenic heat and urban area on surface urban heat island in the Yangtze River Delta urban agglomeration. Science of the Total Environment, 571, 461–470.
  • Du, S., Xiong, Z., Wang, Y., & Guo, L. (2016b). Quantifying the multilevel effects of landscape composition and configuration on land surface temperature. Remote Sensing of Environment, 178, 84–92.
  • El Garouani, A., Mulla, D.J., El Garouani, S., Knight, J. (2017). Analysis of urban growth and sprawl from remote sensing data: Case of Fez, Morocco. International Journal of Sustainable Built Environment. Volume 6, Issue 1, Pages 160-169, ISSN 2212-6090. https://doi.org/10.1016/j.ijsbe.2017.02.003.
  • Estoque, R.C., Murayama, Y., & Myint, S.W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of southeast Asia. Science of the Total Environment, 577, 349–359.
  • Feyisa, G.L., Meilby, H., Jenerette, G.D., & Pauliet, S. (2016). Locally optimized separability enhancement indices for urban land cover mapping: Exploring thermal environmental consequences of rapid urbanization in Addis Ababa, Ethiopia. Remote Sensing of Environment, 175, 14–31.
  • Filho, W. L., Icaza, L. E., Neht, A., Klavins, M., Morgan, E. A. (2018). Coping with the impacts of urban heat islands. A literature based study on understanding urban heat vulnerability and the need for resilience in cities in a global climate change context. Journal of Cleaner Production, Volume 171, 2018, Pages 1140-1149. ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2017.10.086.
  • Firoozi, F., Mahmoudi, P., Jahanshahi, S.M.A. et al. (2020). Modeling changes trend of time series of land surface temperature (LST) using satellite remote sensing productions (case study: Sistan plain in east of Iran). Arab J Geosci, 13, 367 (2020). https://doi.org/10.1007/s12517-020-05314-w
  • Forkel, M., Carvalhais, N., Verbesselt, J., Mahecha, M.D., Neigh, C.S.R., Reichstein, M. (2013). Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology. Remote Sensing. 5(5):2113-2144. https://doi.org/10.3390/rs5052113
  • Fukui, E. (1970). The recent rise of temperature in Japan. In Japanese Progress in Climatology; Tokyo University of Education: Tokyo, Japan, pp. 46-65. Gao, B.C. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens. Environ. 58, 257–266.
  • Gartland, L. (2008). Heat Islands: Understanding and Mitigating Heat in Urban Areas (1st ed.). London, United Kingdom. Earthscan. https://doi.org/10.4324/9781849771559
  • Georgescu, M., Moustaoui, M., Mahalov, A., & Dudhia, J. (2011). An alternative explanation of the semiarid urban area “oasis effect”. Journal of Geophysical Research, 116, D24113.
  • Giannopoulou, K., Santamouris, M., Livada, I. et al. (2010). The Impact of Canyon Geometry on Intra Urban and Urban: Suburban Night Temperature Differences Under Warm Weather Conditions. Pure Appl. Geophys. 167, 1433–1449. https://doi.org/10.1007/s00024-010-0099-8
  • Gong, P., Wang, J., Yu, L., Zhao, Y., Liang, L., Niu, Z., Huang, X., Fu, H., Liu, S., Li, C., et al. (2013). Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data. Int. J. Remote Sens. 34, 2607–2654.
  • Guha, S., Govil, H. (2021). An assessment on the relationship between land surface temperature and normalized difference vegetation index. Environ Dev Sustain. 23, 1944–1963. https://doi.org/10.1007/s10668-020-00657-6
  • Guha, S., Govil, H., Dey, A., 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, Vol. 51, No. 1, 667–678. https://doi.org/10.1080/22797254.2018.1474494
  • Guha, S., Govil, H., Sandip, M. (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
  • Gunlu, E., Pirnar, İ., Yagci, K. (2009). Preserving Cultural Heritage and Possible Impacts on Regional Development: Case of İzmir. International Journal of Emerging and Transition Economies, Vol.2, Issue 2, 213-229.
  • Guo-Yu Ren (2015). Urbanization as a major driver of urban climate change. Advances in Climate Change Research, Volume 6, Issue 1, Pages 1-6. ISSN 1674-9278. https://doi.org/10.1016/j.accre.2015.08.003.
  • He, C.Y., Liu, Z.F., Tian, J., Ma, Q. (2014). Urban expansion dynamics and natural habitat loss in China: A multiscale landscape perspective. Glob. Chang. Biol. 20, 2886–2902.
  • Howard, L. (1833). The Climate of London; London Harvey and Dorton: London, UK. Volume 2.
  • Huang, M., Cui, P., 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
  • Jenerette, G.D., Harlan, S.L., Brazel, A., Jones, N., Larsen, L., & Stefanov, W.L. (2007). Regional relationships between surface temperature, vegetation, and human settlement in a rapidly urbanizing ecosystem. Landscape Ecology, 22, 353–365.
  • Jia, G., Zhang, L., Zhu, L., Xu, R., Liang, D., Xu, X., Ba, T. (2020). Digital Earth for Climate Change Research. In: Guo H., Goodchild M.F., Annoni A. (eds). Manual of Digital Earth. Springer, Singapore. https://doi.org/10.1007/978-981-32-9915-3_14
  • Joshi, J. P. and Bhatt, B., (2012). Estimating temporal land surface temperature using remote sensing: a study of vadodara urban, Gujarat. International Journal of Geology, Earth and Environmental Sciences, vol. 2, pp. 123–130.
  • Gunawardena, K.R., Wells, M.J., Kershaw, T. (2017). Utilising green and bluespace to mitigate urban heat island intensity. Science of The Total Environment, Volumes 584–585, Pages 1040-1055. ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2017.01.158.
  • Gupta, N., Mathew, A., Khandelwal, S. (2019). Analysis of cooling effect of water bodies on land surface temperature in nearby region: A case study of Ahmedabad and Chandigarh cities in India. The Egyptian Journal of Remote Sensing and Space Science, Volume 22, Issue 1, Pages 81-93. ISSN 1110-9823, https://doi.org/10.1016/j.ejrs.2018.03.007.
  • Kafer, P. S., Rolim, S. B. A., Diaz, L. R., Rocha, N. S., Iglesias, M. L., Rex, F. E. (2020). Comparative Analysis Of Split-Window And Single-Channel Algorithms For Land Surface Temperature Retrieval of A Pseudo-Invariant Target. Boletim de Ciências Geodésicas, 26(2), e2020008. Epub June 12, 2020. https://doi.org/10.1590/s1982-21702020000200008
  • Kalma, J.D., McVicar, T.R., McCabe, M.F. (2008). Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data. Surv. Geophys, 29, 421–469.
  • Kalnay, E., & Cai, M. (2003). Impact of urbanization and land-use change on climate. Nature, 423, 528–553.
  • Kershaw, T. (2017). The urban heat island (UHI), Climate Change Resilience in the Urban Environment. IOP Publishing, 2053-2563, Book Chapter, 4-44, 2017. doi = 10.1088/978-0-7503-1197-7ch4, isbn 978-0-7503-1197-7.
  • Kii, M., Nakamura, K. (2017). Development of a suitability model for estimation of global urban land cover. Transp. Res. Procedia., 25, 3165–3177.
  • Kim, H.H. (1992). Urban Heat Island. Int. J. Remote Sens., 13, 2319-2336.
  • Kleerekoper, L., van Esch, M., & Salcedo, T.B. (2012). How to make a city climate-proof, addressing the urban heat island effect. Resource Conservation Recycling, 64, 30–38. ISSN 0921-3449, https://doi.org/10.1016/j.resconrec.2011.06.004.
  • Koomen, E., Diogo, V. (2017). Assessing potential future urban heat island patterns following climate scenarios, socio-economic developments and spatial planning strategies. Mitig Adapt Strateg Glob Change, 22, 287–306. https://doi.org/10.1007/s11027-015-9646-z
  • Kuang, W.H., Liu, J.Y.; Zhang, Z.X.; Liu, D.S.; Xiang, B. (2013). Spatiotemporal dynamics of impervious surface areas across China during the early 21st century. Chin. Sci. Bull., 58, 1691–1701.
  • Kumar, K. S., Bhaskar, P. U., & Padmakumari, K. (2012). Estimation of Land Surface Temperature to Study Urban Heat Island Effect Using Landsat ETM + IMAGE. International Journal of Engineering Science and Technology (IJEST), 4(02), 771–778.
  • Landsberg, H.E. (1981). The Urban Climate; Academic Press: New York, NY, USA. pp. 84-89.
  • Li, J.,Wang, Y., Shen, X.,&Song, Y. (2004). Landscape pattern analysis along an urban–rural gradient in the Shanghai metropolitan region. Acta Ecologica Sinica, 24, 1973–1980.
  • Li, Y., Schubert, S., Kropp, J.P., Kropp, J. P., Rybskio, D. (2020). On the influence of density and morphology on the Urban Heat Island intensity. Nat Commun., 11, 2647. https://doi.org/10.1038/s41467-020-16461-9
  • Lim, H. S., MatJafri, M. Z., Abdullah, K. and Wong, C. J. (2009). Air Pollution Determination Using Remote Sensing Technique. Advances in Geoscience and Remote Sensing, Gary Jedlovec, IntechOpen, DOI: 10.5772/8319. Available from: https://www.intechopen.com/books/advances-in-geoscience-and-remote-sensing/air-pollution-determination-using-remote-sensing-technique
  • Liu, L., Zhang, Y. (2011). Urban Heat Island analysis using the Landsat TM data and ASTER data: a case study in Hong Kong. Remote Sens. 3:1535–1552. http://dx.doi.org/10.3390/rs3071535.
  • Lopez, J.M.R., Heider, K., & Scheffran, J. (2017). Frontiers of urbanization: Identifying and explaining urbanization hot spots in the south of Mexico City using human and remote sensing. Applied Geography, 79, 1–10.
  • Lu, D.S., Li, G.Y., Kuang, W.H., Moran, E. (2014). Methods to extract impervious surface areas from satellite images. Int. J. Digit. Earth. 7, 93–112.
  • Lu, Y., Feng, P., Shen, C., Sun, J. (2009). Urban Heat Island in Summer of Nanjing Based on TM Data. Proceedings of 2009 Joint Urban Remote Sensing Event, Shanghai, China, 20–22 May 2009, pp. 1-5.
  • Lutz, W., Sanderson, W., Scherbov, S. (2001). The end of world population growth. Nature. 412, 543–545. Plos ONE. 6, e23777.
  • Majkowska, A., Kolendowicz, L., Półrolniczak, M., Hauke, J., Czernecki, B. (2017). The urban heat island in the city of Poznań as derived from Landsat 5 TM. Theor Appl Climatol, 128, 769–783. https://doi.org/10.1007/s00704-016-1737-6
  • Mallick, J., Kant, Y., Bharath, B. D. (2008). Estimation of Land Surface Temperature Over Delhi using Landsat-7 ETM +. J. Ind. Geophys. Union, 12(3), 131–140.
  • Mejbel, S. M., Zakariya, J. O., Hassoon, I. K., & Jameel, A. A. (2018). Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera. International Journal of Engineering & Technology, 7(4.20), 608-612. doi:http://dx.doi.org/10.14419/ijet.v7i4.20.27402
  • Memon, R. A., Leung, D. Y. C., & Chunho, L. (2008). A Review on the Generation, Determination and Mitigation of Urban Heat Island. Journal of Environmental Sciences (China), 20(1), 120–8. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18572534
  • Miralles, D.G., Holmes, T.R.H., de Jeu, R.A.M., Gash, J.H., Meesters, A.G.C.A., Dolman, A.J. (2011). Global land-surface evaporation estimated from satellite-based observations. Hydrol. Earth Syst. Sci., 15, 453–469.
  • Mohajerani, A., Bakaric, J., Jeffrey-Bailey, T. (2017). The urban heat island effect, its causes, and mitigation, with reference to the thermal properties of asphalt concrete, Journal of Environmental Management, Volume 197, Pages 522-538, ISSN 0301-4797. https://doi.org/10.1016/j.jenvman.2017.03.095.
  • Mohammad, P., Goswami, A., & Bonafoni, S. (2019). The Impact of the Land Cover Dynamics on Surface Urban Heat Island Variations in Semi-Arid Cities: A Case Study in Ahmedabad City, India, Using Multi-Sensor/Source Data. Sensors (Basel, Switzerland), 19(17), 3701. https://doi.org/10.3390/s19173701
  • Mohammed, Y., Salman, A. (2018). Effect of urban geometry and green area on the formation of the urban heat island in Baghdad city. MATEC Web Conf., 162 05025. DOI: https://doi.org/10.1051/matecconf/201816205025
  • Mohan, M., (2000). Climate change: evaluation of ecological restoration of Delhi ridge using remote sensing and GIS technologies. International Archives of Photogrammetry and Remote Sensing, vol. 33, pp. 886–894.
  • Mushore, T. D., Mutanga, O., Odindi, J., Dube, T. (2017). Assessing the potential of integrated Landsat 8 thermal bands, with the traditional reflective bands and derived vegetation indices in classifying urban landscapes. Geocarto International, 32:8, 886-899, DOI: 10.1080/10106049.2016.1188168
  • Mutiibwa, D., Strachan, S. and Albright, T. (2015). Land Surface Temperature and Surface Air Temperature in Complex Terrain. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 10, pp. 4762-4774, Oct. 2015, doi: 10.1109/JSTARS.2015.2468594.
  • Nazeer, M., Nichol, J. E., Yung, Y.-K. (2014). Evaluation of atmospheric correction models and Landsat surface reflectance product in an urban coastal environment. International Journal of Remote Sensing, 35:16, 6271-6291, DOI: 10.1080/01431161.2014.951742
  • Ng, E., Chen, L., Wang, Y., & Yuan, C. (2012). A study on the cooling effects of greening in a high from-density city : an experience Hong Kong. Building and Environment, 47, 256 271. doi:10.1016/j.buildenv.2011.07.014 ,
  • Nichol, J. E., Fung, W. Y., Lam, Ka-se, Wong, M. S. (2009). Urban heat island diagnosis using ASTER satellite images and ‘in situ’ air temperature. Atmospheric Research, Volume 94, Issue 2, Pages 276-284. ISSN 0169-8095 https://doi.org/10.1016/j.atmosres.2009.06.011.
  • Nie, Q., Man, W., Li, Z., & Huang, Y. (2016). Spatiotemporal impact of urban impervious surface on land surface temperature in Shanghai, China. Canadian Journal of Remote Sensing, 42(6), 680–689.
  • Oke, T.R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108, 1–24.
  • Oke, T.R. (1997). Urban climates and global change. In A. Perry & R. Thompson (Eds.). Applied climatology: Principles and practices, pp. 273–287. London: Routledge.
  • Peng, J., Xie, P., Liu, Y., & Ma, J. (2016). Urban thermal environment dynamics and associated landscape pattern factors: A case study in the Beijing metropolitan region. Remote Sensing of Environment, 173, 145–155.
  • Pickett, S.T.A., Cadenasso, M.L., Grove, J.M., Boone, C.G., Groffman, P.M., Irwin, E., Kaushal, S.S., Marshall, V., McGrath, B.P., Nilon, C.H., Pouyat, R.V., Szlavecz, K., Troy, A., Warren, P. (2011). Urban ecological systems: scientific foundations and decade of progress. J. Environ. Manag. 92 (3), 331–362. http://dx.doi.org/10.1016/j.jenvman.2010.08.022.
  • Putra, M. I. J., Affandani, A. Y., Widodo, T., & Wibowo, A. (2019). Spatial Multi-Criteria Analysis for Urban Sustainable Built Up Area Based on Urban Heat Island in Serang City. IOP Conference Series: Earth and Environmental Science, 338(1), [012025]. https://doi.org/10.1088/1755-1315/338/1/012025
  • Qin, Z., Zhang, M., Amon, K., Pedro, B. (2001). Mono-window Algorithm for retrieving land surface temperature from Landsat TM 6 data. Acta Geogr. Sinica 2001, 56, 456-466).
  • Reza, A., Weng, Q.H., Abbas, A., Seyed, K.A. (2009). Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area. Remote Sens. Environ. 113, 2606–2617.
  • Rizwan, A.M., Dennis, L.Y.C., & Liu, C. (2008). A review on the generation, determination and mitigation of urban heat island. Journal of Environmental Sciences, 20, 120–128.
  • Robinove, C.J. (1982). Computation with physical values from Landsat digital data. Photogrammetric Engineering and Remote Sensing, USGS Publications Warehouse, 48, 5, pp 781-784. http://pubs.er.usgs.gov/publication/70011466
  • Sangiorgio, V., Fiorito, F. & Santamouris, M. (2020). Development of a holistic urban heat island evaluation methodology. Scientific Reports, 10, 17913 (2020). https://doi.org/10.1038/s41598-020-75018-4
  • Santamouris, M. (2013). Using cool pavements as a mitigation strategy to fight urban heat island: a review of the actual developments. Renew. Sust. Energ. Rev. 26:224–240. http://dx.doi.org/10.1016/j.rser.2013.05.047.
  • Santamouris, M. (2019). Chapter 8 - Mitigating the Local Climatic Change and Fighting Urban Vulnerability, Editor(s): Matthaios Santamouris, Minimizing Energy Consumption, Energy Poverty and Global and Local Climate Change in the Built Environment: Innovating to Zero, Elsevier, Pages 223-307, ISBN 9780128114179, https://doi.org/10.1016/B978-0-12-811417-9.00008-8.
  • Schneider, A. (2012). Monitoring land cover change in urban and pen-urban areas using dense time stacks of Landsat satellite data and a data mining approach. Remote Sens. Environ. 124, 689–704.
  • Sekertekin, A., Bonafoni, S. (2020). Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation. Remote Sens., 12, 294. https://doi.org/10.3390/rs12020294
  • Senanayake, I. P., Welivitiya, W. D. D. P., & Nadeeka, P. M. (2013). Remote Sensing Based Analysis of Urban Heat Islands with Vegetation Cover in Colombo city, Sri Lanka using Landsat-7 ETM+ data. Urban Climate, doi:10.1016/j.uclim.2013.07.004.
  • Shafaghat, A., Manteghi, G., Keyvanfar, A., Bin Lamit, H., Saito, K., Ossen, D. R. (2016). Street Geometry Factors Influence Urban Microclimate in Tropical Coastal Cities: A Review. Environmental and Climate Technologies, 17(1), 61-75. doi: https://doi.org/10.1515/rtuect-2016-0006
  • Shahmohamadi, P., Che-Ani, A. I., Maulud, K. N. A., Tawil, N. M., Abdullah, N. A. G. (2011). The Impact of Anthropogenic Heat on Formation of Urban Heat Island and Energy Consumption Balance. Urban Studies Research, vol. 2011, Article ID 497524, 9 pages. https://doi.org/10.1155/2011/497524
  • Solecki, W. D., Rosenzweig, C., Pope, G., Chopping, M., & Goldberg, R. (2004). Urban Heat Island and Climate Change : An Assessment of Interacting and Possible Adaptations in the Camden, New Jersey Region. New Jersey. p 5. www.nj.gov/dep/dsr/research/Urban Heat Island and Climate Change-RPS.pdf
  • Son, Nguyen-Thanh, Thanh, Bui-Xuan (2018). Decadal assessment of urban sprawl and its effects on local temperature using Landsat data in Cantho city, Vietnam. Sustainable Cities and Society. Volume 36, Pages 81-91, ISSN 2210-6707, https://doi.org/10.1016/j.scs.2017.10.010.
  • Song, Dan-Xia, Huang, C., Sexton, J.O., Channan, S., Feng, M., Townshend, J.R., (2015). Use of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil. ISPRS Journal of Photogrammetry and Remote Sensing, Volume 103, Pages 81-92. ISSN0924-2716, https://doi.org/10.1016/j.isprsjprs.2014.09.005.(http://www.sciencedirect.com/science/article/pii/S0924271614002305)
  • Song, J., Du, S., Feng, X., & 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.
  • Song, Z., Li, R., Qiu, R., Liu, S., Tan, C., Li, Q., Ge, W., Han, X., Tang, X., Shi, W., Song, L., Yu, W., Yang, H., Ma, M. (2018). Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016. Remote Sensing, 10(12):2034. https://doi.org/10.3390/rs10122034
  • Stone, B., Jr. (2007). Urban sprawl and air quality in large US cities. Journal of Environmental Management, 86, 688–698.
  • Streutker, D.R. (2002). A remote sensing study of the urban heat island of Houston, Texas. Int. J. Remote Sens. 23, 2595-2608.
  • Sun, Q., Tan, J., Xu, Y. (2010). An ERDAS image processing method for retrieving LST and describing urban heat evolution: a case study in the Pearl River Delta Region in South China. Environ. Earth Sci. 59 (5), 1047–1055.
  • Sun, Y., Zhao, S.Q., Qu,W.Y. (2015). Quantifying spatiotemporal patterns of urban expansion in three capital cities in Northeast China over the past three decades using satellite data sets. Environ. Earth Sci. 73, 7221–7235.
  • Sun Z., Wang, Q., Batkhishig, O., Ouyang, Z. (2016). Relationship between Evapotranspiration and Land Surface Temperature under Energy- and Water-Limited Conditions in Dry and Cold Climates. Advances in Meteorology, vol. 2016, Article ID 1835487, 9 pages. https://doi.org/10.1155/2016/1835487
  • Takeuchi, W., Hashim, N., & Thet, K. M. (2010). Application of RS and GIS for Monitoring UHI in KL Metropolitan Area. MAp Asia 2010 & ISG 2010. Kuala Lumpur.
  • Tan, C., Ma, M., Kuang, H. (2017). Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010. Remote Sensing. 9(2):150. https://doi.org/10.3390/rs9020150
  • Tan, J., Yu, D., Li, Q., Tan, X., Zhou, W. (2020). Spatial relationship between land-use/land-cover change and land surface temperature in the Dongting Lake area, China. Sci Rep, 10, 9245. https://doi.org/10.1038/s41598-020-66168-6
  • Tang, F. and Xu, H. (2016). A Study on the quantitative relationship between impervious surface and land surface temperature based on remote sensing technology. 4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA), Guangzhou, 2016, pp. 368-372, doi: 10.1109/EORSA.2016.7552831.
  • Tozer L. (2018). Urban climate change and sustainability planning: an analysis of sustainability and climate change discourses in local government plans in Canada. Journal of Environmental Planning and Management, 61:1, 176-194, DOI: 10.1080/09640568.2017.1297699.
  • Tran, D.X., Pla, F., Carmona, P.L., Myint, S.W., Caetano, M., & Kieua, P.V. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119–132.
  • Tsoka, S., Tsikaloudaki, K., Theodosiou, T., Bikas, D. (2020). Urban Warming and Cities’ Microclimates: Investigation Methods and Mitigation Strategies—A Review. Energies, 13, 1414.
  • Ujang, U., Azri, S., Zahir, M., Abdul Rahman, A., Choon, T. L. (2018). Urban Heat Island Micro-Mapping via 3D City Model. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W10, 201–207, https://doi.org/10.5194/isprs-archives-XLII-4-W10-201-2018.
  • Unal, Y.S., Tan, E. & Mentes, S.S. (2013). Summer heat waves over western Turkey between 1965 and 2006. Theor Appl Climatol, 112, 339–350. https://doi.org/10.1007/s00704-012-0704-0
  • Urban, M, Eberle, J, Hüttich, C, Schmullius, C, Herold, M. (2013). Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale. Remote Sensing, 5(5):2348-2367. https://doi.org/10.3390/rs5052348
  • U.S. Geological Survey (2020). Data Management and Information Distribution (DMID). Last accessed September 11, 2020 at URL https://earthexplorer.usgs.gov.
  • Wei, J., Huang, B., Sun, L., Zhang, Z., Wang, L., & Bilal, M. (2017). A simple and universal aerosol retrieval algorithm for Landsat series images over complex surfaces. Journal of Geophysical Research: Atmospheres, 122, 13,338–13,355. https://doi.org/10.1002/ 2017JD026922
  • Weng, Q. (2001). A remote sensing – GIS Evaluation of Urban Expansion and Its Impact on Surface Temperature in the Zhujiang Delta , China. International Journal of Remote Sensing, 22(10), 1999–2014.
  • Weng, Q., Yang, S. (2004). Managing the adverse thermal effects of urban development in a densely populated Chinese city. Journal of Environmental Management, 70(2), 145–156.
  • Willett, K.M., Sherwood, S. (2012). Exceedance of heat index thresholds for 15 regions under a warming climate using the wet-bulb globe temperature. International Journal of Climatology, 32(2), 161–177.
  • Williams, V. J., Davis, C. (2007). A case study of urban heat islands in the Carolinas. Environmental Hazards, 7(4):353-359, DOI:10.1016/j.envhaz.2007.09.005.
  • Wulder, M. A., Thomas, Loveland, R. D., Roy, P., Crawford C. J., Masek, J. G., Woodcock, C. E., Allen, R. G., Martha C. Anderson, Alan S. Belward, Warren B. Cohen, John Dwyer, Angela Erb, Feng Gao, Patrick Griffiths, Dennis Helder, Txomin Hermosilla, James D. Hipple, Patrick Hostert, M. Joseph Hughes, Justin Huntington, David M. Johnson, Robert Kennedy, Ayse Kilic, Zhan Li, Leo Lymburner, Joel McCorkel, Nima Pahlevan, Theodore A. Scambos, Crystal Schaaf, John R. Schott, Yongwei Sheng, James Storey, Eric Vermote, James Vogelmann, Joanne C. White, Randolph H. Wynne, Zhu, Z. (2019). Current status of Landsat program, science, and applications. Remote Sensing of Environment, Volume 225, Pages 127-147. ISSN 0034-4257. https://doi.org/10.1016/j.rse.2019.02.015.
  • Xiao, Rong-bo, Ouyang, Zhi-yun, Zheng, H., Li, Wei-feng, Schienke, E. W, Wang, Xiao-ke (2007). Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China. Journal of Environmental Sciences, Volume 19, Issue 2, Pages 250-256, ISSN 1001-0742, https://doi.org/10.1016/S1001-0742(07)60041-2.
  • Yan, H., Wang, X., Hao, P., & Dong, L. (2012). Study on the Microclimatic Characteristics and Human Comfort of Park Plant Communities in Summer. Procedia Environmental Sciences. 13(2011), 755 765.doi:10.1016/j.proenv.2012.01.069
  • Yucekaya, A. (2018). An Analysis For Industrial Development In Turkey. I: Distribution of The Largest Companies. Journal of Engineering Technology and Applied Sciences. 3 (1), 83-105.
  • Young, N. E., Anderson, R. S., Chignell, S. M., Vorster, A. G., Lawrence, R., Evangelista, P. H. (2017). A survival guide to Landsat preprocessing. Ecology, 98 4: 920-932.
  • Zhang, Y. (2006). Land surface temperature retrieval from CBERS-02 IRMSS thermal infrared data and its applications in quantitative analysis of urban heat island effect. Journal of Remote Sensing, 10, 789–797.
  • Zhang, Y., Pena-Arancibia, J.L., McVicar, T.R., Chiew, F.H.S., Vaze, J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y.Y., et al. (2016b). Multi-decadal trends in global terrestrial evapotranspiration and its components. Sci. Rep. 6, 19124.
  • Zhang, Z., He, G., Wang, M., Long, T., Wang, G., Zhang, X., & Jiao, W. (2016a). Towards an operational method for land surface temperature retrieval from Landsat 8 data. Remote Sensing Letters, 7(3), 279–288.
  • Zhang, Z., He, G., Wang, X. (2010). A practical DOS model-based atmospheric correction algorithm. International Journal of Remote Sensing, 31:11, 2837-2852, DOI: 10.1080/01431160903124682
  • Zhao, H.M., Chen, X.L. (2005). Use of Normalized Difference Bareness Index in Quickly Mapping Bare Areas from TM/ETM+. Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium. Seoul, Korea, 29–29 July 2005; Volume 3, pp. 1666–1668.
  • Zhao H., Tan J., Ren Z., Wang Z. (2020). Spatiotemporal Characteristics of Urban Surface Temperature and Its Relationship with Landscape Metrics and Vegetation Cover in Rapid Urbanization Region. Complexity, vol. 2020, Article ID 7892362, 12 pages. https://doi.org/10.1155/2020/7892362
  • Zhao, L., Oleson, K., Bou-Zeid, E., Krayenhoff, E. S., Bray, A., Zhu, Q., Zheng, Z., Chen, C., Oppenheimer, M. (2021). Global multi-model projections of local urban climates. Nat. Clim. Chang. 11, 152–157. https://doi.org/10.1038/s41558-020-00958-8
  • Zhong, L., Gong, P., Biging, G.S. (2014). Efficient corn and soybean mapping with temporal extendibility: A multi-year experiment using Landsat imagery. Remote Sens. Environ. 140, 1–13.
  • Zhou, D., Xiao, J., Bonafoni, S., Berger, C., Deilami, K., Zhou, Y., Frolking, S., Yao, R., Qiao, Z., Sobrino, J.A. (2019). Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives. Remote Sensing. 11(1):48. https://doi.org/10.3390/rs11010048
  • Zhou, J., Hu, D., Weng, Q. (2010). Analysis of surface radiation budget during the summer and winter in the metropolitan area of Beijing, China. J. Appl. Rem. Sens. 4(1) 04351. https://doi.org/10.1117/1.3374329
  • Zhou, W., Qian, Y., Li, X., Li, W., & Han, L. (2014). Relationships between land cover and the surface urban heat island: Seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures. Landscape Ecology, 29, 153–167.
  • Zoran, M. A., Zoran, L. F. V. (2005). Mapping of dispersion of urban air pollution using remote sensing and in-situ monitoring data. Proc. SPIE 5979, Remote Sensing of Clouds and the Atmosphere X, 597914 (1 November 2005). https://doi.org/10.1117/12.627775
  • Zurina, M., Hukil, S. (2012). Appraising Good Governance in Malaysia Based on Sustainable Development Values. Journal of ASIAN Behavioral Studies: Sustainability Science and Management, 7(2), 247–253. doi: ISSN: 1823-8556.

İzmir'de kentleşmenin neden olduğu kent ekosistemi ve yerel iklim değişikliklerinin uzun süreli KIA oluşumu açısından STG yöntemiyle değerlendirilmesi

Yıl 2023, Cilt: 7 Sayı: 1, 11 - 58, 30.06.2023
https://doi.org/10.32569/resilience.1172781

Öz

Kentleşme, insanlara daha iyi ve daha konforlu bir yaşam sürmeleri için çeşitli fırsatlar sunarken, kötüleşen iklim koşulları gibi bazı yan etkileri de beraberinde getirir. Yerel anlamda, kentleşmenin dönüştürdüğü kırsal alanlardaki eski iklim koşulları, yaygın kentleşmenin bozduğu yeni iklim koşullarıyla karşılaştırıldığında doğal olarak adlandırılabilir. Kentleşmenin yan etkilerinden biri de belirli kentsel faaliyetler ile farklı kentsel bölge tasarımlarına bağlı olarak ortaya çıkan özel arazi örtülerden kaynaklanan termal kirliliktir. Termal kirlilik zamanla şehrin doğal iklimini değiştirir ve şehrin konfor durumunu negatif olarak etkiler. Farklı zamanlarda elde edilmiş tüm bir şehri kapsayan termal veri dağılımlarının zaman serileri şeklindeki analizlerini içeren bazı çalışmalar olup bu alanda ciddi katkılar sağlamaktadırlar.
Bu çalışmada, zaman serilerine bağlı analizleri içeren çalışmalar için istatistiki bir yaklaşım olarak önerilen simile edilmiş tek veri seti (STV) metodundan üretilen simile edilmiş tek görüntü (STG) yöntemi önerilmekte ve tanıtılmaktadır. Bu nedenle STG yöntemi; şehirlerde beliren Kentsel Sıcak Noktaların (KSN) ve Kentsel Isı Adalarının (KIA) gelişimini ortaya çıkarmak için uzaktan algılama LANDSAT uydu görüntü bantlarına özellikle de termal bantlara uygulanmıştır. Şehirlerdeki KIA'larının dağılımı üzerindeki topografyanın etkisini ortaya koymak için de bölgenin stereo görüntüleri kullanılmıştır. Bu analizler, zaman serisi verilerinin birbirini sürekli doğrulamış sonuçlarından istatistiki olarak simile edilmiş tek bir görüntü şeklindeki bir çıktısıdır.
Bu çalışma, kentlerde KSN'lerin ortaya çıkası ve KIA'ların gelişmesinde; endüstriyel bölgelerin, geniş alan kaplayan yolların, seyrek çalılıklı çıplak alanların, boş veya seyrek çimenlik dağılımlarının olduğu kent alanlarının ve özelliklede yüzeyi belli yönlere dönük olan olan alanların etkin kent örtüleri ve yapıları olduğunu ortaya koymuştur. Bu sonuçlar zaman serisi görüntülerden üretilmiş STG görüntülerinde pek çok kez doğrulanmış olarak belirdiklerinden bu faktörlerin şehrin önceleri doğal olan iklim alanlarını yutarak bu alanlarda yerel iklim değişikliklerinin oluşmasında etkin olduklarını ifade etmektedir. Şehrin bu bölgeleri yerel otoriteler tarafından dikkate alınması ve iyileştirilerek eski doğal iklim ve çevre şartlarına döndürülmeleri gereken, fakat kronik termal iklim şartlarına maruz kalan en riskli bölgelerdir. Çalışmanın sonuç bölümünde ayrıca, şehrin bu bölgelerinde etkin olan faktörlerin etkisini azaltmaya yönelik doğa temelli bazı çözüm ve önerilere de yer verilmektedir.

Kaynakça

  • Ahmad, F. and Goparaju, L. (2016). Geospatial Technology in Urban Forest suitability: Analysis for Ranchi, Jharkhand, India. Ecological Questions, 24/2016: 45 – 57. http://dx.doi.org/10.12775/EQ.2016.011.
  • Akbari, H., Pomerantz, M., & Taha, H. (2001). Cool surfaces and shade trees to reduce energy use and improve air quality in urban areas. Solar Energy, 70(3), 295–310.
  • Almazroui, M., Mashat, A., Assiri, M.E. et al. (2017). Application of Landsat Data for Urban Growth Monitoring in Jeddah. Earth Syst Environ, 1, 25. https://doi.org/10.1007/s41748-017-0028-4
  • Amir, S. M., Dongyun, L., Li, P., Rasool, U., Ullah, K. T., Javaid, A. F. T., Wang, L., Fan, B., Rasool, M.A. (2020). Assessment and simulation of land use and land cover change impacts on the land surface temperature of Chaoyang District in Beijing, China. PeerJ, 8:e9115 http://doi.org/10.7717/peerj.9115
  • Amiri, R., Weng, Q., Alimohammadi, A., & 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://www.sciencedirect.com/science/article/pii/S0034425712000326)
  • Anderson, M. C., Allen, R. G., Morse, A., Kustas, W. P. (2012). Use of Landsat thermal imagery in monitoring evapotranspiration and managing water resources. Remote Sensing of Environment, Volume 122, Pages 50-65, ISSN 0034-4257, https://doi.org/10.1016/j.rse.2011.08.025.
  • Asgarian, A., Amiri, B.J., & Sakieh, Y. (2015). Assessing the effect of green cover spatial patterns on urban land surface temperature using landscape metrics approach. Urban Ecosystems, 18, 209–222.
  • Ayanlade, A. (2016). Seasonality in the daytime and night-time intensity of land surface temperature in a tropical city are. Science of The Total Environment, Volumes 557–558, Pages 415-424, ISSN 0048-9697,https://doi.org/10.1016/j.scitotenv.2016.03.027.
  • Bala, R., Prasad, R., Yadav, V. P. (2020). A comparative analysis of day and night land surface temperature in two semi-arid cities using satellite images sampled in different seasons. Advances in Space Research, Volume 66, Issue 2, Pages 412-425, ISSN 0273-1177, https://doi.org/10.1016/j.asr.2020.04.009.
  • Bendib, A., Dridi, H., & Kalla, M.I. (2017). Contribution of Landsat 8 data for the estimation of land surface temperature in Batna city, Eastern Algeria. Geocarto International, 32(5), 503–513.
  • Boryan, C., Yang, Z., Mueller, R., Craig, M. (2011). Monitoring US agriculture: The US Department of Agriculture, National Agricultural Statistics Service, Cropland Data Layer Program. Geocarto Int. 26, 341–358.
  • Bowker, David E. (2010). Spectral Reflectances of Natural Targets for Use in Remote Sensing Studies 1139. cilt/NASA reference publication (NASA)/USA, 5 Eki 2010, 185 p.
  • Buyadi, S. N. A., Wan Mohd, W. M. N., & Misni, A. (2013). The Impact of Land Use Changes on the Surface Temperature Distribution of Area Surrounding the National Botanic Garden, Shah Alam. AMER International Conference on Quality of Life (p. 10). Pulau Langkawi.
  • Buyantuyev, A., & 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.
  • Camilloni, I., Barros, V. (1997). On the urban heat island effect dependence on temperature trends. Clim. Change. 37, 665-681.
  • Chander, G., and Markham, B. (2003). Revised Landsat-5 TM radiometric calibration procedures and postcalibration dynamic ranges. IEEE Transactions on Geoscience and Remote Sensing, vol. 41, no. 11, pp. 2674-2677, Nov. 2003. doi: 10.1109/TGRS.2003.818464.
  • Chander, G., Markham, B. L., Barsi, J.A. (2007). Revised Landsat-5 Thematic Mapper Radiometric Calibration. IEEE Geoscience and Remote Sensing Letters, vol. 4, no. 3, pp. 490-494, July 2007. doi: 10.1109/LGRS.2007.898285.
  • Chander, G., Markham, B. L., Helder, D. L. (2009). Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors. Remote Sensing of Environment, Volume 113, Issue 5, Pages 893-903. ISSN 0034-4257, https://doi.org/10.1016/j.rse.2009.01.007.
  • Chaudhuri, S., Kumar, A. (2021). Evaluating the contribution of urban ecosystem services in regulating thermal comfort. Spat. Inf. Res. 29, 71–82. https://doi.org/10.1007/s41324-020-00336-8
  • Chen, A., Yao, X.A., Sun, R., & Chen, L. (2014). Effect of urban green patterns on surface urban cool islands and its seasonal variations. Urban Forestry & Urban Greening, 13, 646–654.
  • Chen, Q., Ren, J., Li, Z., Ni, C. (2009). Urban Heat Island Effect Research in Chengdu City Based on MODIS Data. In Proceedings of 3rd International Conference on Bioinformatics and Biomedical Engineering, ICBBE 2009, Beijing, China, 11–13 June 2009. pp. 1-5.
  • Chen, X., Ding, J., Wang, J., Ge, X., Raxidin, M., Liang, J., Chen, X., Zhang, Z., Cao, X., Ding, Y. (2020). Retrieval of Fine-Resolution Aerosol Optical Depth (AOD) in Semiarid Urban Areas Using Landsat Data: A Case Study in Urumqi, NW China. Remote Sens., 12, 467.
  • Chen, X.C., Zhao, H.M., Li, P.X., & Yin, Z.Y. (2006). Remote sensing image-based analysis of the relationship between urban heat island and land use/cover changes. Remote Sensing of Environment, 104(2), 133–146.
  • Chen, Y., Wang, J., & Li, X. (2002). A study on urban thermal field in summer based on satellite remote sensing. Remote Sensing for Land Management and Planning, 4, 55–59.
  • Chen, Y.C., Chiu, H.W., Su, Y.F., Wu, Y.C., Cheng, K.S. (2016). Does urbanization increase diurnal land surface temperature variation? Evidence and implications. Landsc. Urban Plan., 157, 247–258. http://dx.doi.org/10.1016/j.landurbplan.2016.06.014.
  • Cheng, K.S., Su, Y.F., Kuo, F.T., Hung, W.C., Chiang, J.L. (2008). Assessing the effect of landcover on air temperature using remote sensing images: a pilot study in northern Taiwan. Landsc. Urban Plan., 85(2) 85–96. http://dx.doi.org/10.1016/j.landurbplan.2007.09.014.
  • Choi, H., Lee, W., & Byun, W. (2012). Determining the Effect of Green Spaces on Urban Heat Distribution Using Satellite Imagery. Asian Journal of Atmospheric Environment, 6(June), 127-135. doi:http://dx.doi.org/10.5572/ajae.2012.6.2.127.
  • Corumluoglu, O., Asri, I. (2015). The effect of urban heat island on Izmir’s city ecosystem and climate. Environ Sci. Pollut. Res., 22, 3202–3211. https://doi.org/10.1007/s11356-014-2874-z
  • Coseo, P., & Larsen, L. (2014). How factors of land use/land cover, building configuration, and adjacent heat sources and sinks explain urban heat islands in Chicago. Landscape and Urban Planning, 125, 117–129.
  • Coutts, A.M., White, E.C., Tapper, N.J., Beringer, J., & Livesley, S.J. (2016). Temperature and human thermal comfort effects of street trees across three contrasting street canyon environments. Theoretical and Applied Climatology, 124(55), 55–68.
  • Dadras, M., Shafri, H. Z. M., Ahmad, N., Pradhan, Bi., Safarpour, S. (2014). Land Use/Cover Change Detection and Urban Sprawl Analysis in Bandar Abbas City, Iran. The Scientific World Journal. vol. 2014, Article ID 690872, 12 pages. https://doi.org/10.1155/2014/690872.
  • DanInAfterEffects. (2011). Cross Eye 3D [Video]. Youtube. https://www.youtube.com/watch?v=4L-We9onn9s.
  • Deilami, K., & Kamruzzaman, M. (2017). Modelling the urban heat island effect of smart growth policy scenarios in Brisbane. Land Use Policy, 64, 38–55.
  • Detwiller, J. (1970). Deep soil temperature trends and urban effects at Paris. J. Appl. Meteorol., 9, 178-180.
  • Dong, Q., Wang, C., Xiong, C., Li, X., Wang, H., & Ling, T. (2019). Investigation on the Cooling and Evaporation Behavior of Semi-Flexible Water Retaining Pavement based on Laboratory Test and Thermal-Mass Coupling Analysis. Materials (Basel, Switzerland), 12(16), 2546. https://doi.org/10.3390/ma12162546
  • Dousset, B., Gourmelon, F., (2003). Satellite multi-sensor data analysis of urban surface temperatures and landcover. ISPRS J. Photogramm. Remote Sens., 58:43–54. http://dx.doi. org/10.1016/S0924-2716(03)00016-9.
  • Du, H.,Wang, D.,Wang, Y., Zhao, X., Qin, F., Jiang, H.,&Cai, Y. (2016a). Influences of land cover types, meteorological conditions, anthropogenic heat and urban area on surface urban heat island in the Yangtze River Delta urban agglomeration. Science of the Total Environment, 571, 461–470.
  • Du, S., Xiong, Z., Wang, Y., & Guo, L. (2016b). Quantifying the multilevel effects of landscape composition and configuration on land surface temperature. Remote Sensing of Environment, 178, 84–92.
  • El Garouani, A., Mulla, D.J., El Garouani, S., Knight, J. (2017). Analysis of urban growth and sprawl from remote sensing data: Case of Fez, Morocco. International Journal of Sustainable Built Environment. Volume 6, Issue 1, Pages 160-169, ISSN 2212-6090. https://doi.org/10.1016/j.ijsbe.2017.02.003.
  • Estoque, R.C., Murayama, Y., & Myint, S.W. (2017). Effects of landscape composition and pattern on land surface temperature: An urban heat island study in the megacities of southeast Asia. Science of the Total Environment, 577, 349–359.
  • Feyisa, G.L., Meilby, H., Jenerette, G.D., & Pauliet, S. (2016). Locally optimized separability enhancement indices for urban land cover mapping: Exploring thermal environmental consequences of rapid urbanization in Addis Ababa, Ethiopia. Remote Sensing of Environment, 175, 14–31.
  • Filho, W. L., Icaza, L. E., Neht, A., Klavins, M., Morgan, E. A. (2018). Coping with the impacts of urban heat islands. A literature based study on understanding urban heat vulnerability and the need for resilience in cities in a global climate change context. Journal of Cleaner Production, Volume 171, 2018, Pages 1140-1149. ISSN 0959-6526, https://doi.org/10.1016/j.jclepro.2017.10.086.
  • Firoozi, F., Mahmoudi, P., Jahanshahi, S.M.A. et al. (2020). Modeling changes trend of time series of land surface temperature (LST) using satellite remote sensing productions (case study: Sistan plain in east of Iran). Arab J Geosci, 13, 367 (2020). https://doi.org/10.1007/s12517-020-05314-w
  • Forkel, M., Carvalhais, N., Verbesselt, J., Mahecha, M.D., Neigh, C.S.R., Reichstein, M. (2013). Trend Change Detection in NDVI Time Series: Effects of Inter-Annual Variability and Methodology. Remote Sensing. 5(5):2113-2144. https://doi.org/10.3390/rs5052113
  • Fukui, E. (1970). The recent rise of temperature in Japan. In Japanese Progress in Climatology; Tokyo University of Education: Tokyo, Japan, pp. 46-65. Gao, B.C. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sens. Environ. 58, 257–266.
  • Gartland, L. (2008). Heat Islands: Understanding and Mitigating Heat in Urban Areas (1st ed.). London, United Kingdom. Earthscan. https://doi.org/10.4324/9781849771559
  • Georgescu, M., Moustaoui, M., Mahalov, A., & Dudhia, J. (2011). An alternative explanation of the semiarid urban area “oasis effect”. Journal of Geophysical Research, 116, D24113.
  • Giannopoulou, K., Santamouris, M., Livada, I. et al. (2010). The Impact of Canyon Geometry on Intra Urban and Urban: Suburban Night Temperature Differences Under Warm Weather Conditions. Pure Appl. Geophys. 167, 1433–1449. https://doi.org/10.1007/s00024-010-0099-8
  • Gong, P., Wang, J., Yu, L., Zhao, Y., Liang, L., Niu, Z., Huang, X., Fu, H., Liu, S., Li, C., et al. (2013). Finer resolution observation and monitoring of global land cover: First mapping results with Landsat TM and ETM+ data. Int. J. Remote Sens. 34, 2607–2654.
  • Guha, S., Govil, H. (2021). An assessment on the relationship between land surface temperature and normalized difference vegetation index. Environ Dev Sustain. 23, 1944–1963. https://doi.org/10.1007/s10668-020-00657-6
  • Guha, S., Govil, H., Dey, A., 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, Vol. 51, No. 1, 667–678. https://doi.org/10.1080/22797254.2018.1474494
  • Guha, S., Govil, H., Sandip, M. (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
  • Gunlu, E., Pirnar, İ., Yagci, K. (2009). Preserving Cultural Heritage and Possible Impacts on Regional Development: Case of İzmir. International Journal of Emerging and Transition Economies, Vol.2, Issue 2, 213-229.
  • Guo-Yu Ren (2015). Urbanization as a major driver of urban climate change. Advances in Climate Change Research, Volume 6, Issue 1, Pages 1-6. ISSN 1674-9278. https://doi.org/10.1016/j.accre.2015.08.003.
  • He, C.Y., Liu, Z.F., Tian, J., Ma, Q. (2014). Urban expansion dynamics and natural habitat loss in China: A multiscale landscape perspective. Glob. Chang. Biol. 20, 2886–2902.
  • Howard, L. (1833). The Climate of London; London Harvey and Dorton: London, UK. Volume 2.
  • Huang, M., Cui, P., 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
  • Jenerette, G.D., Harlan, S.L., Brazel, A., Jones, N., Larsen, L., & Stefanov, W.L. (2007). Regional relationships between surface temperature, vegetation, and human settlement in a rapidly urbanizing ecosystem. Landscape Ecology, 22, 353–365.
  • Jia, G., Zhang, L., Zhu, L., Xu, R., Liang, D., Xu, X., Ba, T. (2020). Digital Earth for Climate Change Research. In: Guo H., Goodchild M.F., Annoni A. (eds). Manual of Digital Earth. Springer, Singapore. https://doi.org/10.1007/978-981-32-9915-3_14
  • Joshi, J. P. and Bhatt, B., (2012). Estimating temporal land surface temperature using remote sensing: a study of vadodara urban, Gujarat. International Journal of Geology, Earth and Environmental Sciences, vol. 2, pp. 123–130.
  • Gunawardena, K.R., Wells, M.J., Kershaw, T. (2017). Utilising green and bluespace to mitigate urban heat island intensity. Science of The Total Environment, Volumes 584–585, Pages 1040-1055. ISSN 0048-9697, https://doi.org/10.1016/j.scitotenv.2017.01.158.
  • Gupta, N., Mathew, A., Khandelwal, S. (2019). Analysis of cooling effect of water bodies on land surface temperature in nearby region: A case study of Ahmedabad and Chandigarh cities in India. The Egyptian Journal of Remote Sensing and Space Science, Volume 22, Issue 1, Pages 81-93. ISSN 1110-9823, https://doi.org/10.1016/j.ejrs.2018.03.007.
  • Kafer, P. S., Rolim, S. B. A., Diaz, L. R., Rocha, N. S., Iglesias, M. L., Rex, F. E. (2020). Comparative Analysis Of Split-Window And Single-Channel Algorithms For Land Surface Temperature Retrieval of A Pseudo-Invariant Target. Boletim de Ciências Geodésicas, 26(2), e2020008. Epub June 12, 2020. https://doi.org/10.1590/s1982-21702020000200008
  • Kalma, J.D., McVicar, T.R., McCabe, M.F. (2008). Estimating land surface evaporation: A review of methods using remotely sensed surface temperature data. Surv. Geophys, 29, 421–469.
  • Kalnay, E., & Cai, M. (2003). Impact of urbanization and land-use change on climate. Nature, 423, 528–553.
  • Kershaw, T. (2017). The urban heat island (UHI), Climate Change Resilience in the Urban Environment. IOP Publishing, 2053-2563, Book Chapter, 4-44, 2017. doi = 10.1088/978-0-7503-1197-7ch4, isbn 978-0-7503-1197-7.
  • Kii, M., Nakamura, K. (2017). Development of a suitability model for estimation of global urban land cover. Transp. Res. Procedia., 25, 3165–3177.
  • Kim, H.H. (1992). Urban Heat Island. Int. J. Remote Sens., 13, 2319-2336.
  • Kleerekoper, L., van Esch, M., & Salcedo, T.B. (2012). How to make a city climate-proof, addressing the urban heat island effect. Resource Conservation Recycling, 64, 30–38. ISSN 0921-3449, https://doi.org/10.1016/j.resconrec.2011.06.004.
  • Koomen, E., Diogo, V. (2017). Assessing potential future urban heat island patterns following climate scenarios, socio-economic developments and spatial planning strategies. Mitig Adapt Strateg Glob Change, 22, 287–306. https://doi.org/10.1007/s11027-015-9646-z
  • Kuang, W.H., Liu, J.Y.; Zhang, Z.X.; Liu, D.S.; Xiang, B. (2013). Spatiotemporal dynamics of impervious surface areas across China during the early 21st century. Chin. Sci. Bull., 58, 1691–1701.
  • Kumar, K. S., Bhaskar, P. U., & Padmakumari, K. (2012). Estimation of Land Surface Temperature to Study Urban Heat Island Effect Using Landsat ETM + IMAGE. International Journal of Engineering Science and Technology (IJEST), 4(02), 771–778.
  • Landsberg, H.E. (1981). The Urban Climate; Academic Press: New York, NY, USA. pp. 84-89.
  • Li, J.,Wang, Y., Shen, X.,&Song, Y. (2004). Landscape pattern analysis along an urban–rural gradient in the Shanghai metropolitan region. Acta Ecologica Sinica, 24, 1973–1980.
  • Li, Y., Schubert, S., Kropp, J.P., Kropp, J. P., Rybskio, D. (2020). On the influence of density and morphology on the Urban Heat Island intensity. Nat Commun., 11, 2647. https://doi.org/10.1038/s41467-020-16461-9
  • Lim, H. S., MatJafri, M. Z., Abdullah, K. and Wong, C. J. (2009). Air Pollution Determination Using Remote Sensing Technique. Advances in Geoscience and Remote Sensing, Gary Jedlovec, IntechOpen, DOI: 10.5772/8319. Available from: https://www.intechopen.com/books/advances-in-geoscience-and-remote-sensing/air-pollution-determination-using-remote-sensing-technique
  • Liu, L., Zhang, Y. (2011). Urban Heat Island analysis using the Landsat TM data and ASTER data: a case study in Hong Kong. Remote Sens. 3:1535–1552. http://dx.doi.org/10.3390/rs3071535.
  • Lopez, J.M.R., Heider, K., & Scheffran, J. (2017). Frontiers of urbanization: Identifying and explaining urbanization hot spots in the south of Mexico City using human and remote sensing. Applied Geography, 79, 1–10.
  • Lu, D.S., Li, G.Y., Kuang, W.H., Moran, E. (2014). Methods to extract impervious surface areas from satellite images. Int. J. Digit. Earth. 7, 93–112.
  • Lu, Y., Feng, P., Shen, C., Sun, J. (2009). Urban Heat Island in Summer of Nanjing Based on TM Data. Proceedings of 2009 Joint Urban Remote Sensing Event, Shanghai, China, 20–22 May 2009, pp. 1-5.
  • Lutz, W., Sanderson, W., Scherbov, S. (2001). The end of world population growth. Nature. 412, 543–545. Plos ONE. 6, e23777.
  • Majkowska, A., Kolendowicz, L., Półrolniczak, M., Hauke, J., Czernecki, B. (2017). The urban heat island in the city of Poznań as derived from Landsat 5 TM. Theor Appl Climatol, 128, 769–783. https://doi.org/10.1007/s00704-016-1737-6
  • Mallick, J., Kant, Y., Bharath, B. D. (2008). Estimation of Land Surface Temperature Over Delhi using Landsat-7 ETM +. J. Ind. Geophys. Union, 12(3), 131–140.
  • Mejbel, S. M., Zakariya, J. O., Hassoon, I. K., & Jameel, A. A. (2018). Land Surface Temperature Retrieval from LANDSAT-8 Thermal Infrared Sensor Data and Validation with Infrared Thermometer Camera. International Journal of Engineering & Technology, 7(4.20), 608-612. doi:http://dx.doi.org/10.14419/ijet.v7i4.20.27402
  • Memon, R. A., Leung, D. Y. C., & Chunho, L. (2008). A Review on the Generation, Determination and Mitigation of Urban Heat Island. Journal of Environmental Sciences (China), 20(1), 120–8. Retrieved from http://www.ncbi.nlm.nih.gov/pubmed/18572534
  • Miralles, D.G., Holmes, T.R.H., de Jeu, R.A.M., Gash, J.H., Meesters, A.G.C.A., Dolman, A.J. (2011). Global land-surface evaporation estimated from satellite-based observations. Hydrol. Earth Syst. Sci., 15, 453–469.
  • Mohajerani, A., Bakaric, J., Jeffrey-Bailey, T. (2017). The urban heat island effect, its causes, and mitigation, with reference to the thermal properties of asphalt concrete, Journal of Environmental Management, Volume 197, Pages 522-538, ISSN 0301-4797. https://doi.org/10.1016/j.jenvman.2017.03.095.
  • Mohammad, P., Goswami, A., & Bonafoni, S. (2019). The Impact of the Land Cover Dynamics on Surface Urban Heat Island Variations in Semi-Arid Cities: A Case Study in Ahmedabad City, India, Using Multi-Sensor/Source Data. Sensors (Basel, Switzerland), 19(17), 3701. https://doi.org/10.3390/s19173701
  • Mohammed, Y., Salman, A. (2018). Effect of urban geometry and green area on the formation of the urban heat island in Baghdad city. MATEC Web Conf., 162 05025. DOI: https://doi.org/10.1051/matecconf/201816205025
  • Mohan, M., (2000). Climate change: evaluation of ecological restoration of Delhi ridge using remote sensing and GIS technologies. International Archives of Photogrammetry and Remote Sensing, vol. 33, pp. 886–894.
  • Mushore, T. D., Mutanga, O., Odindi, J., Dube, T. (2017). Assessing the potential of integrated Landsat 8 thermal bands, with the traditional reflective bands and derived vegetation indices in classifying urban landscapes. Geocarto International, 32:8, 886-899, DOI: 10.1080/10106049.2016.1188168
  • Mutiibwa, D., Strachan, S. and Albright, T. (2015). Land Surface Temperature and Surface Air Temperature in Complex Terrain. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, vol. 8, no. 10, pp. 4762-4774, Oct. 2015, doi: 10.1109/JSTARS.2015.2468594.
  • Nazeer, M., Nichol, J. E., Yung, Y.-K. (2014). Evaluation of atmospheric correction models and Landsat surface reflectance product in an urban coastal environment. International Journal of Remote Sensing, 35:16, 6271-6291, DOI: 10.1080/01431161.2014.951742
  • Ng, E., Chen, L., Wang, Y., & Yuan, C. (2012). A study on the cooling effects of greening in a high from-density city : an experience Hong Kong. Building and Environment, 47, 256 271. doi:10.1016/j.buildenv.2011.07.014 ,
  • Nichol, J. E., Fung, W. Y., Lam, Ka-se, Wong, M. S. (2009). Urban heat island diagnosis using ASTER satellite images and ‘in situ’ air temperature. Atmospheric Research, Volume 94, Issue 2, Pages 276-284. ISSN 0169-8095 https://doi.org/10.1016/j.atmosres.2009.06.011.
  • Nie, Q., Man, W., Li, Z., & Huang, Y. (2016). Spatiotemporal impact of urban impervious surface on land surface temperature in Shanghai, China. Canadian Journal of Remote Sensing, 42(6), 680–689.
  • Oke, T.R. (1982). The energetic basis of the urban heat island. Quarterly Journal of the Royal Meteorological Society, 108, 1–24.
  • Oke, T.R. (1997). Urban climates and global change. In A. Perry & R. Thompson (Eds.). Applied climatology: Principles and practices, pp. 273–287. London: Routledge.
  • Peng, J., Xie, P., Liu, Y., & Ma, J. (2016). Urban thermal environment dynamics and associated landscape pattern factors: A case study in the Beijing metropolitan region. Remote Sensing of Environment, 173, 145–155.
  • Pickett, S.T.A., Cadenasso, M.L., Grove, J.M., Boone, C.G., Groffman, P.M., Irwin, E., Kaushal, S.S., Marshall, V., McGrath, B.P., Nilon, C.H., Pouyat, R.V., Szlavecz, K., Troy, A., Warren, P. (2011). Urban ecological systems: scientific foundations and decade of progress. J. Environ. Manag. 92 (3), 331–362. http://dx.doi.org/10.1016/j.jenvman.2010.08.022.
  • Putra, M. I. J., Affandani, A. Y., Widodo, T., & Wibowo, A. (2019). Spatial Multi-Criteria Analysis for Urban Sustainable Built Up Area Based on Urban Heat Island in Serang City. IOP Conference Series: Earth and Environmental Science, 338(1), [012025]. https://doi.org/10.1088/1755-1315/338/1/012025
  • Qin, Z., Zhang, M., Amon, K., Pedro, B. (2001). Mono-window Algorithm for retrieving land surface temperature from Landsat TM 6 data. Acta Geogr. Sinica 2001, 56, 456-466).
  • Reza, A., Weng, Q.H., Abbas, A., Seyed, K.A. (2009). Spatial-temporal dynamics of land surface temperature in relation to fractional vegetation cover and land use/cover in the Tabriz urban area. Remote Sens. Environ. 113, 2606–2617.
  • Rizwan, A.M., Dennis, L.Y.C., & Liu, C. (2008). A review on the generation, determination and mitigation of urban heat island. Journal of Environmental Sciences, 20, 120–128.
  • Robinove, C.J. (1982). Computation with physical values from Landsat digital data. Photogrammetric Engineering and Remote Sensing, USGS Publications Warehouse, 48, 5, pp 781-784. http://pubs.er.usgs.gov/publication/70011466
  • Sangiorgio, V., Fiorito, F. & Santamouris, M. (2020). Development of a holistic urban heat island evaluation methodology. Scientific Reports, 10, 17913 (2020). https://doi.org/10.1038/s41598-020-75018-4
  • Santamouris, M. (2013). Using cool pavements as a mitigation strategy to fight urban heat island: a review of the actual developments. Renew. Sust. Energ. Rev. 26:224–240. http://dx.doi.org/10.1016/j.rser.2013.05.047.
  • Santamouris, M. (2019). Chapter 8 - Mitigating the Local Climatic Change and Fighting Urban Vulnerability, Editor(s): Matthaios Santamouris, Minimizing Energy Consumption, Energy Poverty and Global and Local Climate Change in the Built Environment: Innovating to Zero, Elsevier, Pages 223-307, ISBN 9780128114179, https://doi.org/10.1016/B978-0-12-811417-9.00008-8.
  • Schneider, A. (2012). Monitoring land cover change in urban and pen-urban areas using dense time stacks of Landsat satellite data and a data mining approach. Remote Sens. Environ. 124, 689–704.
  • Sekertekin, A., Bonafoni, S. (2020). Land Surface Temperature Retrieval from Landsat 5, 7, and 8 over Rural Areas: Assessment of Different Retrieval Algorithms and Emissivity Models and Toolbox Implementation. Remote Sens., 12, 294. https://doi.org/10.3390/rs12020294
  • Senanayake, I. P., Welivitiya, W. D. D. P., & Nadeeka, P. M. (2013). Remote Sensing Based Analysis of Urban Heat Islands with Vegetation Cover in Colombo city, Sri Lanka using Landsat-7 ETM+ data. Urban Climate, doi:10.1016/j.uclim.2013.07.004.
  • Shafaghat, A., Manteghi, G., Keyvanfar, A., Bin Lamit, H., Saito, K., Ossen, D. R. (2016). Street Geometry Factors Influence Urban Microclimate in Tropical Coastal Cities: A Review. Environmental and Climate Technologies, 17(1), 61-75. doi: https://doi.org/10.1515/rtuect-2016-0006
  • Shahmohamadi, P., Che-Ani, A. I., Maulud, K. N. A., Tawil, N. M., Abdullah, N. A. G. (2011). The Impact of Anthropogenic Heat on Formation of Urban Heat Island and Energy Consumption Balance. Urban Studies Research, vol. 2011, Article ID 497524, 9 pages. https://doi.org/10.1155/2011/497524
  • Solecki, W. D., Rosenzweig, C., Pope, G., Chopping, M., & Goldberg, R. (2004). Urban Heat Island and Climate Change : An Assessment of Interacting and Possible Adaptations in the Camden, New Jersey Region. New Jersey. p 5. www.nj.gov/dep/dsr/research/Urban Heat Island and Climate Change-RPS.pdf
  • Son, Nguyen-Thanh, Thanh, Bui-Xuan (2018). Decadal assessment of urban sprawl and its effects on local temperature using Landsat data in Cantho city, Vietnam. Sustainable Cities and Society. Volume 36, Pages 81-91, ISSN 2210-6707, https://doi.org/10.1016/j.scs.2017.10.010.
  • Song, Dan-Xia, Huang, C., Sexton, J.O., Channan, S., Feng, M., Townshend, J.R., (2015). Use of Landsat and Corona data for mapping forest cover change from the mid-1960s to 2000s: Case studies from the Eastern United States and Central Brazil. ISPRS Journal of Photogrammetry and Remote Sensing, Volume 103, Pages 81-92. ISSN0924-2716, https://doi.org/10.1016/j.isprsjprs.2014.09.005.(http://www.sciencedirect.com/science/article/pii/S0924271614002305)
  • Song, J., Du, S., Feng, X., & 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.
  • Song, Z., Li, R., Qiu, R., Liu, S., Tan, C., Li, Q., Ge, W., Han, X., Tang, X., Shi, W., Song, L., Yu, W., Yang, H., Ma, M. (2018). Global Land Surface Temperature Influenced by Vegetation Cover and PM2.5 from 2001 to 2016. Remote Sensing, 10(12):2034. https://doi.org/10.3390/rs10122034
  • Stone, B., Jr. (2007). Urban sprawl and air quality in large US cities. Journal of Environmental Management, 86, 688–698.
  • Streutker, D.R. (2002). A remote sensing study of the urban heat island of Houston, Texas. Int. J. Remote Sens. 23, 2595-2608.
  • Sun, Q., Tan, J., Xu, Y. (2010). An ERDAS image processing method for retrieving LST and describing urban heat evolution: a case study in the Pearl River Delta Region in South China. Environ. Earth Sci. 59 (5), 1047–1055.
  • Sun, Y., Zhao, S.Q., Qu,W.Y. (2015). Quantifying spatiotemporal patterns of urban expansion in three capital cities in Northeast China over the past three decades using satellite data sets. Environ. Earth Sci. 73, 7221–7235.
  • Sun Z., Wang, Q., Batkhishig, O., Ouyang, Z. (2016). Relationship between Evapotranspiration and Land Surface Temperature under Energy- and Water-Limited Conditions in Dry and Cold Climates. Advances in Meteorology, vol. 2016, Article ID 1835487, 9 pages. https://doi.org/10.1155/2016/1835487
  • Takeuchi, W., Hashim, N., & Thet, K. M. (2010). Application of RS and GIS for Monitoring UHI in KL Metropolitan Area. MAp Asia 2010 & ISG 2010. Kuala Lumpur.
  • Tan, C., Ma, M., Kuang, H. (2017). Spatial-Temporal Characteristics and Climatic Responses of Water Level Fluctuations of Global Major Lakes from 2002 to 2010. Remote Sensing. 9(2):150. https://doi.org/10.3390/rs9020150
  • Tan, J., Yu, D., Li, Q., Tan, X., Zhou, W. (2020). Spatial relationship between land-use/land-cover change and land surface temperature in the Dongting Lake area, China. Sci Rep, 10, 9245. https://doi.org/10.1038/s41598-020-66168-6
  • Tang, F. and Xu, H. (2016). A Study on the quantitative relationship between impervious surface and land surface temperature based on remote sensing technology. 4th International Workshop on Earth Observation and Remote Sensing Applications (EORSA), Guangzhou, 2016, pp. 368-372, doi: 10.1109/EORSA.2016.7552831.
  • Tozer L. (2018). Urban climate change and sustainability planning: an analysis of sustainability and climate change discourses in local government plans in Canada. Journal of Environmental Planning and Management, 61:1, 176-194, DOI: 10.1080/09640568.2017.1297699.
  • Tran, D.X., Pla, F., Carmona, P.L., Myint, S.W., Caetano, M., & Kieua, P.V. (2017). Characterizing the relationship between land use land cover change and land surface temperature. ISPRS Journal of Photogrammetry and Remote Sensing, 124, 119–132.
  • Tsoka, S., Tsikaloudaki, K., Theodosiou, T., Bikas, D. (2020). Urban Warming and Cities’ Microclimates: Investigation Methods and Mitigation Strategies—A Review. Energies, 13, 1414.
  • Ujang, U., Azri, S., Zahir, M., Abdul Rahman, A., Choon, T. L. (2018). Urban Heat Island Micro-Mapping via 3D City Model. Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W10, 201–207, https://doi.org/10.5194/isprs-archives-XLII-4-W10-201-2018.
  • Unal, Y.S., Tan, E. & Mentes, S.S. (2013). Summer heat waves over western Turkey between 1965 and 2006. Theor Appl Climatol, 112, 339–350. https://doi.org/10.1007/s00704-012-0704-0
  • Urban, M, Eberle, J, Hüttich, C, Schmullius, C, Herold, M. (2013). Comparison of Satellite-Derived Land Surface Temperature and Air Temperature from Meteorological Stations on the Pan-Arctic Scale. Remote Sensing, 5(5):2348-2367. https://doi.org/10.3390/rs5052348
  • U.S. Geological Survey (2020). Data Management and Information Distribution (DMID). Last accessed September 11, 2020 at URL https://earthexplorer.usgs.gov.
  • Wei, J., Huang, B., Sun, L., Zhang, Z., Wang, L., & Bilal, M. (2017). A simple and universal aerosol retrieval algorithm for Landsat series images over complex surfaces. Journal of Geophysical Research: Atmospheres, 122, 13,338–13,355. https://doi.org/10.1002/ 2017JD026922
  • Weng, Q. (2001). A remote sensing – GIS Evaluation of Urban Expansion and Its Impact on Surface Temperature in the Zhujiang Delta , China. International Journal of Remote Sensing, 22(10), 1999–2014.
  • Weng, Q., Yang, S. (2004). Managing the adverse thermal effects of urban development in a densely populated Chinese city. Journal of Environmental Management, 70(2), 145–156.
  • Willett, K.M., Sherwood, S. (2012). Exceedance of heat index thresholds for 15 regions under a warming climate using the wet-bulb globe temperature. International Journal of Climatology, 32(2), 161–177.
  • Williams, V. J., Davis, C. (2007). A case study of urban heat islands in the Carolinas. Environmental Hazards, 7(4):353-359, DOI:10.1016/j.envhaz.2007.09.005.
  • Wulder, M. A., Thomas, Loveland, R. D., Roy, P., Crawford C. J., Masek, J. G., Woodcock, C. E., Allen, R. G., Martha C. Anderson, Alan S. Belward, Warren B. Cohen, John Dwyer, Angela Erb, Feng Gao, Patrick Griffiths, Dennis Helder, Txomin Hermosilla, James D. Hipple, Patrick Hostert, M. Joseph Hughes, Justin Huntington, David M. Johnson, Robert Kennedy, Ayse Kilic, Zhan Li, Leo Lymburner, Joel McCorkel, Nima Pahlevan, Theodore A. Scambos, Crystal Schaaf, John R. Schott, Yongwei Sheng, James Storey, Eric Vermote, James Vogelmann, Joanne C. White, Randolph H. Wynne, Zhu, Z. (2019). Current status of Landsat program, science, and applications. Remote Sensing of Environment, Volume 225, Pages 127-147. ISSN 0034-4257. https://doi.org/10.1016/j.rse.2019.02.015.
  • Xiao, Rong-bo, Ouyang, Zhi-yun, Zheng, H., Li, Wei-feng, Schienke, E. W, Wang, Xiao-ke (2007). Spatial pattern of impervious surfaces and their impacts on land surface temperature in Beijing, China. Journal of Environmental Sciences, Volume 19, Issue 2, Pages 250-256, ISSN 1001-0742, https://doi.org/10.1016/S1001-0742(07)60041-2.
  • Yan, H., Wang, X., Hao, P., & Dong, L. (2012). Study on the Microclimatic Characteristics and Human Comfort of Park Plant Communities in Summer. Procedia Environmental Sciences. 13(2011), 755 765.doi:10.1016/j.proenv.2012.01.069
  • Yucekaya, A. (2018). An Analysis For Industrial Development In Turkey. I: Distribution of The Largest Companies. Journal of Engineering Technology and Applied Sciences. 3 (1), 83-105.
  • Young, N. E., Anderson, R. S., Chignell, S. M., Vorster, A. G., Lawrence, R., Evangelista, P. H. (2017). A survival guide to Landsat preprocessing. Ecology, 98 4: 920-932.
  • Zhang, Y. (2006). Land surface temperature retrieval from CBERS-02 IRMSS thermal infrared data and its applications in quantitative analysis of urban heat island effect. Journal of Remote Sensing, 10, 789–797.
  • Zhang, Y., Pena-Arancibia, J.L., McVicar, T.R., Chiew, F.H.S., Vaze, J., Liu, C., Lu, X., Zheng, H., Wang, Y., Liu, Y.Y., et al. (2016b). Multi-decadal trends in global terrestrial evapotranspiration and its components. Sci. Rep. 6, 19124.
  • Zhang, Z., He, G., Wang, M., Long, T., Wang, G., Zhang, X., & Jiao, W. (2016a). Towards an operational method for land surface temperature retrieval from Landsat 8 data. Remote Sensing Letters, 7(3), 279–288.
  • Zhang, Z., He, G., Wang, X. (2010). A practical DOS model-based atmospheric correction algorithm. International Journal of Remote Sensing, 31:11, 2837-2852, DOI: 10.1080/01431160903124682
  • Zhao, H.M., Chen, X.L. (2005). Use of Normalized Difference Bareness Index in Quickly Mapping Bare Areas from TM/ETM+. Proceedings of the 2005 IEEE International Geoscience and Remote Sensing Symposium. Seoul, Korea, 29–29 July 2005; Volume 3, pp. 1666–1668.
  • Zhao H., Tan J., Ren Z., Wang Z. (2020). Spatiotemporal Characteristics of Urban Surface Temperature and Its Relationship with Landscape Metrics and Vegetation Cover in Rapid Urbanization Region. Complexity, vol. 2020, Article ID 7892362, 12 pages. https://doi.org/10.1155/2020/7892362
  • Zhao, L., Oleson, K., Bou-Zeid, E., Krayenhoff, E. S., Bray, A., Zhu, Q., Zheng, Z., Chen, C., Oppenheimer, M. (2021). Global multi-model projections of local urban climates. Nat. Clim. Chang. 11, 152–157. https://doi.org/10.1038/s41558-020-00958-8
  • Zhong, L., Gong, P., Biging, G.S. (2014). Efficient corn and soybean mapping with temporal extendibility: A multi-year experiment using Landsat imagery. Remote Sens. Environ. 140, 1–13.
  • Zhou, D., Xiao, J., Bonafoni, S., Berger, C., Deilami, K., Zhou, Y., Frolking, S., Yao, R., Qiao, Z., Sobrino, J.A. (2019). Satellite Remote Sensing of Surface Urban Heat Islands: Progress, Challenges, and Perspectives. Remote Sensing. 11(1):48. https://doi.org/10.3390/rs11010048
  • Zhou, J., Hu, D., Weng, Q. (2010). Analysis of surface radiation budget during the summer and winter in the metropolitan area of Beijing, China. J. Appl. Rem. Sens. 4(1) 04351. https://doi.org/10.1117/1.3374329
  • Zhou, W., Qian, Y., Li, X., Li, W., & Han, L. (2014). Relationships between land cover and the surface urban heat island: Seasonal variability and effects of spatial and thematic resolution of land cover data on predicting land surface temperatures. Landscape Ecology, 29, 153–167.
  • Zoran, M. A., Zoran, L. F. V. (2005). Mapping of dispersion of urban air pollution using remote sensing and in-situ monitoring data. Proc. SPIE 5979, Remote Sensing of Clouds and the Atmosphere X, 597914 (1 November 2005). https://doi.org/10.1117/12.627775
  • Zurina, M., Hukil, S. (2012). Appraising Good Governance in Malaysia Based on Sustainable Development Values. Journal of ASIAN Behavioral Studies: Sustainability Science and Management, 7(2), 247–253. doi: ISSN: 1823-8556.
Toplam 157 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yer Bilimleri ve Jeoloji Mühendisliği (Diğer)
Bölüm Makaleler
Yazarlar

Özşen Çorumluoğlu 0000-0002-7876-6589

Yayımlanma Tarihi 30 Haziran 2023
Kabul Tarihi 20 Nisan 2023
Yayımlandığı Sayı Yıl 2023 Cilt: 7 Sayı: 1

Kaynak Göster

APA Çorumluoğlu, Ö. (2023). Evaluation of the urban ecosystem and local climate changes caused by urbanization in İzmir in terms of long-term UHI formation with the SSI method. Resilience, 7(1), 11-58. https://doi.org/10.32569/resilience.1172781