OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION

Lütfiye KUŞAK, (Aydın Adnan Menderes Üniversitesi)
Ufuk Fatih KÜÇÜKALİ (İstanbul Aydın Üniversitesi)
International Journal of Engineering and Geosciences
3 0
Yıl: 2019 Cilt: 4 Sayı: 1 Sayfa Aralığı: 1 - 7 Metin Dili: İngilizce DOI: 10.26833/ijeg.404426 İndeks Tarihi: 28-04-2020

OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION

Öz:
Unplanned and rapid urbanization is one of the reasons for the rising surface temperature in urban areas.There is a large amount of literature demonstrating the association of urbanization with surface temperatures.Küçükçekmece Lake, an important lake that has been meeting the utility water needs of Istanbul, and the unplanned andrapid urbanization around it, has been affected by this inevitable change for years. Although surface temperaturesgenerally correlate strongly with each other, very high and very low temperature values should not be disregarded andneed to be investigated. The current study was conducted with the assumption that these values could be outliers; thus,they were analyzed using the box plot method for the selected region. Correlations between land surface temperature(LST) values obtained for Küçükçekmece and its vicinity were examined using Landsat Operational Land Imager (OLI)images from June 20, 2016 and June 23, 2017, and LST outliers and regions with common outliers on both days weredetermined. In the study, 310 LST outliers were identified for June 20, 2016 and 34 LST outliers for June 23, 2017; inboth images, 33 outliers were found to be common and these clustered in two different buildings. The reasons for theoutliers outside the standard surface temperature values as well as the recommended solutions were discussed.
Anahtar Kelime:

Konular: Mühendislik, Jeoloji Yeşil, Sürdürülebilir Bilim ve Teknoloji Görüntüleme Bilimi ve Fotoğraf Teknolojisi Jeoloji
Belge Türü: Makale Makale Türü: Araştırma Makalesi Erişim Türü: Erişime Açık
  • Aggarwal, C. C. (2015). Outlier analysis. In Data mining (pp. 237-263). Springer, Cham.
  • Alhawitti, R. H., and Mitsova, D. (2016). Using Landsat-8 data to explore the correlation between urban heart island and urban land uses. IJRET: International Journal of Research in Engineering and Technology, 5(3), 457-466.
  • Bramer, M. (2007). Principles of data mining (Vol. 180). London: Springer.
  • Chen, L., Li, M., Huang, F., and Xu, S. (2013, December). Relationships of LST to NDBI and NDVI in Wuhan City based on Landsat ETM+ image. In Image and Signal Processing (CISP), 2013 6th International Congress on (Vol. 2, pp. 840-845). IEEE.
  • Chen, X. L., Zhao, H. M., Li, P. X., and 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.
  • Cipolla, S. S., and Maglionico, M. (2014). Heat recovery from urban wastewater: Analysis of the variability of flow rate and temperature. Energy and Buildings, 69, 122-130.
  • Cui, L., and Shi, J. (2012). Urbanization and its environmental effects in Shanghai, China. Urban Climate, 2, 1-15.
  • Deng, J. S., Wang, K., Hong, Y., and Qi, J. G. (2009). Spatio-temporal dynamics and evolution of land use change and landscape pattern in response to rapid urbanization. Landscape and urban planning, 92(3-4), 187-198.
  • Du, H., Song, X., Jiang, H., Kan, Z., Wang, Z., and Cai, Y. (2016). Research on the cooling island effects of water body: A case study of Shanghai, China. Ecological indicators, 67, 31-38.
  • Gunawardena, K. R., Wells, M. J., and Kershaw, T. (2017). Utilising green and bluespace to mitigate urban heat island intensity. Science of the Total Environment, 584, 1040-1055.
  • Han, J., Pei, J., and Kamber, M. (2011). Data mining: concepts and techniques. Elsevier.
  • Hasanlou, M., and Mostofi, N. (2015). Investigating urban heat island estimation and relation between various land cover indices in Tehran city using Landsat 8 imagery. In Proceeding.
  • Iglewicz, Boris and David Hoaglin (1993), How to Detect and Handle Outliers. American Society for Quality Control, Milwaukee WI.
  • Jenerette, G. D., Harlan, S. L., Brazel, A., Jones, N., Larsen, L., and Stefanov, W. L. (2007). Regional relationships between surface temperature, vegetation, and human settlement in a rapidly urbanizing ecosystem. Landscape ecology, 22(3), 353-365.
  • Kaya, S., Basar, U. G., Karaca, M., and Seker, D. Z. (2012). Assessment of urban heat islands using remotely sensed data. Ecology, 21(84), 107-113.
  • Kucukali, U. F., and Kuşak, L. (2017). Environmental, Social, and Economic Indicators of Urban Land Use Conflicts. Urbanization and Its Impact on Socio- Economic Growth in Developing Regions, pp. 285, IGI Global,USA.
  • Kumar, M. and Mathur, R., (2014). April. Outlier detection based fault-detection algorithm for cloud computing. In Convergence of Technology (I2CT), 2014 International Conference for (pp. 1-4). IEEE.
  • Li, W., Cao, Q., Lang, K., and Wu, J. (2017). Linking potential heat source and sink to urban heat island: Heterogeneous effects of landscape pattern on land surface temperature. Science of the Total Environment, 586, 457-465.
  • Liao, J., Jia, Y., Tang, L., Huang, Q., Wang, Y., Huang, N., and Hua, L. (2017). Assessment of urbanizationinduced ecological risks in an area with significant ecosystem services based on land use/cover change scenarios. International Journal of Sustainable Development and World Ecology, 1-10.
  • Liu, Y., Chen, Z. M., Xiao, H., Yang, W., Liu, D., and Chen, B. (2017). Driving factors of carbon dioxide emissions in China: an empirical study using 2006-2010 provincial data. Frontiers of Earth Science, 11(1), 156- 161.
  • Mendenhall, W. M., and Sincich, T. L. (2016). Statistics for Engineering and the Sciences. Chapman and Hall/CRC.
  • Nacef, L., Bachari, N. E. I., Bouda, A., & Boubnia, R. (2016). “Variability and decadal evolution of temperature and salinity in the mediterranean sea surface”. International Journal of Engineering and Geosciences, 1(1), 20-29.
  • Olson, D. L., and Delen, D. (2008). Advanced data mining techniques. Springer Science and Business Media.
  • Ranagalage, M., Estoque, R. C., and Murayama, Y. (2017). An urban heat island study of the Colombo metropolitan area, Sri Lanka, based on Landsat data (1997–2017). ISPRS International Journal of Geo- Information, 6(7), 189.
  • Rousseeuw, P. J., and Hubert, M. (2017). Anomaly detection by robust statistics. Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery.
  • Seo, S. (2006). A review and comparison of methods for detecting outliers in univariate data sets (Doctoral dissertation, University of Pittsburgh).
  • Shen, H., Huang, L., Zhang, L., Wu, P., and Zeng, C. (2016). Long-term and fine-scale satellite monitoring of the urban heat island effect by the fusion of multitemporal and multi-sensor remote sensed data: A 26- year case study of the city of Wuhan in China. Remote Sensing of Environment, 172, 109-125.
  • Sobrino, J. A., Jiménez-Muñoz, J. C., and Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5. Remote Sensing of environment, 90(4), 434-440.
  • Sobrino, J. A., Raissouni, N., and Li, Z. L. (2001). A comparative study of land surface emissivity retrieval from NOAA data. Remote Sensing of Environment, 75(2), 256-266.
  • Stathopoulou, M., and Cartalis, C. (2007). Daytime urban heat islands from Landsat ETM+ and Corine land cover data: An application to major cities in Greece. Solar Energy, 81(3), 358-368.
  • Stathopoulou, M., Cartalis, C., and Petrakis, M. (2007). Integrating Corine Land Cover data and Landsat TM for surface emissivity definition: application to the urban area of Athens, Greece. International Journal of Remote Sensing, 28(15), 3291-3304.
  • Tang, B. H., Shao, K., Li, Z. L., Wu, H., and Tang, R. (2015). An improved NDVI-based threshold method for estimating land surface emissivity using MODIS satellite data. International Journal of Remote Sensing, 36(19-20), 4864-4878.
  • Tayyebi, A., Shafizadeh-Moghadam, H., and Tayyebi, A. H. (2018). Analyzing long-term spatio-temporal patterns of land surface temperature in response to rapid urbanization in the mega-city of Tehran. Land Use Policy, 71, 459-469.
  • Tukey, J. W. (1977). Box-and-whisker plots. Exploratory data analysis, 39-43.
  • Valor, E., and Caselles, V. (1996). Mapping land surface emissivity from NDVI: Application to European, African, and South American areas. Remote sensing of Environment, 57(3), 167-184.
  • Van de Griend, A. A., and Owe, M. (1993). On the relationship between thermal emissivity and the normalized difference vegetation index for natural surfaces. International Journal of remote sensing, 14(6), 1119-1131.
  • Vlahov, D. and Galea, S. (2002). Urbanization, urbanicity, and health. Journal of Urban Health, 79(1), pp.S1-S12.
  • Wang, J., Da, L., Song, K., and Li, B. L. (2008). Temporal variations of surface water quality in urban, suburban and rural areas during rapid urbanization in Shanghai, China. Environmental Pollution, 152(2), 387- 393.
  • 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.
  • Xie, S., Dearing, J. A., Bloemendal, J., & Boyle, J. F. (1999). Association between the organic matter content and magnetic properties in street dust, Liverpool, UK. Science of the Total Environment, 241(1-3), 205-214.
  • Xie, Q., Zhou, Z., Teng, M., and Wang, P. (2012). A multi-temporal Landsat TM data analysis of the impact of land use and land cover changes on the urban heat island effect. J. Food Agric. Environ, 10(2), 803-809.
  • Zhang, C., Tang, Y., Luo, L., & Xu, W. (2009). Outlier identification and visualization for Pb concentrations in urban soils and its implications for identification of potential contaminated land. Environmental Pollution, 157(11), 3083-3090.
  • Zhao, S., Da, L., Tang, Z., Fang, H., Song, K., and Fang, J. (2006). Ecological consequences of rapid urban expansion: Shanghai, China. Frontiers in Ecology and the Environment, 4(7), 341-346.
  • URL 1. Web Map Tile Service, http://www.worldometers.info [Accessed 1 Jan 2018]
  • URL 2. Web Map Tile Service, http://www.kdd.org [Accessed 1 Jan 2018]
  • URL 3. Web Map Tile Service, https://towardsdatascience.com [Accessed 12 Dec 2017]
  • URL 4. Web Map Tile Service, http://esdac.jrc.ec.europa.eu [Accessed 30 Jun 2017]
  • URL 5. Web Map Tile Service, http://eusoils.jrc.ec.europa.eu [Accessed 30 Jun 2017]
APA Kuşak L, Küçükali U (2019). OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. , 1 - 7. 10.26833/ijeg.404426
Chicago Kuşak Lütfiye,Küçükali Ufuk Fatih OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. (2019): 1 - 7. 10.26833/ijeg.404426
MLA Kuşak Lütfiye,Küçükali Ufuk Fatih OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. , 2019, ss.1 - 7. 10.26833/ijeg.404426
AMA Kuşak L,Küçükali U OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. . 2019; 1 - 7. 10.26833/ijeg.404426
Vancouver Kuşak L,Küçükali U OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. . 2019; 1 - 7. 10.26833/ijeg.404426
IEEE Kuşak L,Küçükali U "OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION." , ss.1 - 7, 2019. 10.26833/ijeg.404426
ISNAD Kuşak, Lütfiye - Küçükali, Ufuk Fatih. "OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION". (2019), 1-7. https://doi.org/10.26833/ijeg.404426
APA Kuşak L, Küçükali U (2019). OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. International Journal of Engineering and Geosciences, 4(1), 1 - 7. 10.26833/ijeg.404426
Chicago Kuşak Lütfiye,Küçükali Ufuk Fatih OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. International Journal of Engineering and Geosciences 4, no.1 (2019): 1 - 7. 10.26833/ijeg.404426
MLA Kuşak Lütfiye,Küçükali Ufuk Fatih OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. International Journal of Engineering and Geosciences, vol.4, no.1, 2019, ss.1 - 7. 10.26833/ijeg.404426
AMA Kuşak L,Küçükali U OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. International Journal of Engineering and Geosciences. 2019; 4(1): 1 - 7. 10.26833/ijeg.404426
Vancouver Kuşak L,Küçükali U OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION. International Journal of Engineering and Geosciences. 2019; 4(1): 1 - 7. 10.26833/ijeg.404426
IEEE Kuşak L,Küçükali U "OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION." International Journal of Engineering and Geosciences, 4, ss.1 - 7, 2019. 10.26833/ijeg.404426
ISNAD Kuşak, Lütfiye - Küçükali, Ufuk Fatih. "OUTLIER DETECTION OF LAND SURFACE TEMPERATURE: KÜÇÜKÇEKMECE REGION". International Journal of Engineering and Geosciences 4/1 (2019), 1-7. https://doi.org/10.26833/ijeg.404426
Sayfa Oluşturulma Tarihi
17-04-2024 14:8

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