Konferans Bildirisi
BibTex RIS Kaynak Göster
Yıl 2020, Cilt: 5 Sayı: 2, 218 - 223, 30.06.2020
https://doi.org/10.35229/jaes.681179

Öz

Teşekkür

Bu çalışma, International Symposium on Applied Geoinformatics (ISAG) 2019'da sözlü sunum olarak sunulmuştur.

Kaynakça

  • Avdan, U. and Jovanovska, G. (2016). Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data, Journal of Sensors.
  • Barsi, J. A., Schott, J. R., Hook, S. J., Raqueno, N. G., Markham, B. L. and Radocinski, R. G. (2014). Landsat-8 thermal infrared sensor (TIRS) vicarious radiometric calibration, Remote Sensing, 6 (11), pp. 11607–11626.
  • 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, pp. 133–146.
  • Estoque, R. C., Murayama, Y., and 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, pp. 349–359.
  • Fitzpatrick – Lins, K. (1981). Comparison of sampling procedures and data analysis for a land use and land cover map. Photogrammetric Engineering and Remote Sensing, 47, pp. 343 – 351.
  • Jiang, J. and Tian, G. (2010). Analysis of the impact of land use/land cover change on land surface temperature with remote sensing, Procedia Environmental Sciences 2, pp. 571–575.
  • Li, J., Song, C., Cao, L., Zhu, F., Meng, X. and Wu, J. (2011). Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China, Remote Sensing of Environment 115, pp. 3249–3263.
  • Lillesand, T. M., Kiefer, R. W. and Chipman, J. W., (2004). Remote Sensing and Image Interpretation. 5th Edition, Wiley, USA.
  • Markham B. L. and Barker, J. L. (1985). Spectral characterization of the Landsat Thematic Mapper sensors, International Journal of Remote Sensing, 6 (5), pp. 697–716.
  • Url-1 https://tr.wikipedia.org/wiki/Trabzon, 29.09.2019
  • Url-2 https://www.usgs.gov/media/images/landsat-8-band-designations, 29.09.2019
  • Url-3 https://www.usgs.gov/faqs/what-are-best-landsat-spectral-bands-use-my-research?qt-news_science_products=0#qt-news_science_products, 29.09.2019
  • Pal, S. and Ziaul, S. (2017). Detection of land use and land cover change and land surface temperature in English Bazar urban centre, The Egyptian Journal of Remote Sensing and Space Sciences 20, pp. 125–145.
  • Ratnayake, R. (2002). Forest cover estimation using Normalised Difference Vegetation Index (NDVI) in plantation forest, Remote Sensing for Agriculture, Ecosystems, and Hydrology III, Manfred Owe, Guido D'Urso, Editors, Proceedings of SPIE, 4542 SPIE · 0277-786X/02.
  • Sobrino, J. A., Jimenez-Munoz, J. C. and Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5, Remote Sensing of Environment, 90 (4), pp. 434–440.
  • Sobrino J. A. and Raissouni, N. (2000). Toward remote sensing methods for land cover dynamic monitoring: application to Morocco, International Journal of Remote Sensing, 21 (2), pp. 353–366.
  • 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), pp. 358–368.
  • Van Genderen, J.L. and Lock, B.F. (1977). Testing land use map accuracy. Photogrametric Engineering and Remote Sensing, 43, pp. 1135 – 1137.
  • Wang, F., Qin, Z., Song, C., Tu, L., Karnieli, A. and Zhao, S. (2015). An improved mono-window algorithm for land surface temperature retrieval from landsat 8 thermal infrared sensor data, Remote Sensing, 7 (4), pp. 4268–4289.
  • Wang, S., Ma, Q., Ding, H., and Liang, H. (2018). Detection of urban expansion and land surface temperature change using multi-temporal Landsat images, Resources, Conservation and Recycling 128, pp. 526–534.
  • Weng, Q., Lub, D., and Schubringa, J. (2004). Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies, Remote Sensing of Environment 89, pp. 467–483.
  • Yamak, B., Yagci, Z., Bilgilioglu, B. B. and Comert, R. (2019). Investigation of the effect of urbanization on land surface temperature: Bursa Case Study, https://www.researchgate.net/publication/333758700, Conference paper, pp. 189-195 (In Turkish).
  • Zhang, X., Zhong, T., Wang, K. and Cheng, Z. (2009). Scaling of impervious surface area and vegetation as indicators to urban land surface temperature using satellite data, International Journal of Remote Sensing, 30 (4), pp. 841-859.

Relationship Of Urban Development With The Heat Islands, Trabzon Case Study

Yıl 2020, Cilt: 5 Sayı: 2, 218 - 223, 30.06.2020
https://doi.org/10.35229/jaes.681179

Öz

Trabzon, a developing port town province that is located near the Black Sea region of Turkey. Trabzon, the 29th most crowded province of Turkey shows the intensity of urbanization on the coastal zone. The reason for this is that the settlement areas are mostly available in coastal areas and the province is mostly covered with rough terrain. The province also has plenty of rainfall due to its climatic characteristics and has a vegetation of dense forests. It is known how important urbanization is in terms of planning processes. For this reason, urban development should be determined in a short time and with high accuracy. Remote sensing data and methods are among the most common methods for local administrators and planners. In this study, it is aimed to examine the urban development of Trabzon province by using various remote sensing methods and data. Depending on the characteristic of urban development within the boundaries of the province, the change in the artificial surfaces has been investigated by using optical remote sensing methods in the selected test region. For this purpose, LANDSAT images of the study area, 1989, 2000, 2006 and 2018 were provided. Pixel-based supervised classification was applied to the images and the land use and land cover (LULC) classes of the study area were determined. In the second stage of the study, the development of artificial surfaces was investigated by using thermal remote sensing methods. For this purpose, the surface temperature map of the region has been established. As a result of the study, the urban development and change taking place in Trabzon by using different remote sensing data and methods were examined.

Kaynakça

  • Avdan, U. and Jovanovska, G. (2016). Algorithm for automated mapping of land surface temperature using LANDSAT 8 satellite data, Journal of Sensors.
  • Barsi, J. A., Schott, J. R., Hook, S. J., Raqueno, N. G., Markham, B. L. and Radocinski, R. G. (2014). Landsat-8 thermal infrared sensor (TIRS) vicarious radiometric calibration, Remote Sensing, 6 (11), pp. 11607–11626.
  • 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, pp. 133–146.
  • Estoque, R. C., Murayama, Y., and 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, pp. 349–359.
  • Fitzpatrick – Lins, K. (1981). Comparison of sampling procedures and data analysis for a land use and land cover map. Photogrammetric Engineering and Remote Sensing, 47, pp. 343 – 351.
  • Jiang, J. and Tian, G. (2010). Analysis of the impact of land use/land cover change on land surface temperature with remote sensing, Procedia Environmental Sciences 2, pp. 571–575.
  • Li, J., Song, C., Cao, L., Zhu, F., Meng, X. and Wu, J. (2011). Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China, Remote Sensing of Environment 115, pp. 3249–3263.
  • Lillesand, T. M., Kiefer, R. W. and Chipman, J. W., (2004). Remote Sensing and Image Interpretation. 5th Edition, Wiley, USA.
  • Markham B. L. and Barker, J. L. (1985). Spectral characterization of the Landsat Thematic Mapper sensors, International Journal of Remote Sensing, 6 (5), pp. 697–716.
  • Url-1 https://tr.wikipedia.org/wiki/Trabzon, 29.09.2019
  • Url-2 https://www.usgs.gov/media/images/landsat-8-band-designations, 29.09.2019
  • Url-3 https://www.usgs.gov/faqs/what-are-best-landsat-spectral-bands-use-my-research?qt-news_science_products=0#qt-news_science_products, 29.09.2019
  • Pal, S. and Ziaul, S. (2017). Detection of land use and land cover change and land surface temperature in English Bazar urban centre, The Egyptian Journal of Remote Sensing and Space Sciences 20, pp. 125–145.
  • Ratnayake, R. (2002). Forest cover estimation using Normalised Difference Vegetation Index (NDVI) in plantation forest, Remote Sensing for Agriculture, Ecosystems, and Hydrology III, Manfred Owe, Guido D'Urso, Editors, Proceedings of SPIE, 4542 SPIE · 0277-786X/02.
  • Sobrino, J. A., Jimenez-Munoz, J. C. and Paolini, L. (2004). Land surface temperature retrieval from LANDSAT TM 5, Remote Sensing of Environment, 90 (4), pp. 434–440.
  • Sobrino J. A. and Raissouni, N. (2000). Toward remote sensing methods for land cover dynamic monitoring: application to Morocco, International Journal of Remote Sensing, 21 (2), pp. 353–366.
  • 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), pp. 358–368.
  • Van Genderen, J.L. and Lock, B.F. (1977). Testing land use map accuracy. Photogrametric Engineering and Remote Sensing, 43, pp. 1135 – 1137.
  • Wang, F., Qin, Z., Song, C., Tu, L., Karnieli, A. and Zhao, S. (2015). An improved mono-window algorithm for land surface temperature retrieval from landsat 8 thermal infrared sensor data, Remote Sensing, 7 (4), pp. 4268–4289.
  • Wang, S., Ma, Q., Ding, H., and Liang, H. (2018). Detection of urban expansion and land surface temperature change using multi-temporal Landsat images, Resources, Conservation and Recycling 128, pp. 526–534.
  • Weng, Q., Lub, D., and Schubringa, J. (2004). Estimation of land surface temperature–vegetation abundance relationship for urban heat island studies, Remote Sensing of Environment 89, pp. 467–483.
  • Yamak, B., Yagci, Z., Bilgilioglu, B. B. and Comert, R. (2019). Investigation of the effect of urbanization on land surface temperature: Bursa Case Study, https://www.researchgate.net/publication/333758700, Conference paper, pp. 189-195 (In Turkish).
  • Zhang, X., Zhong, T., Wang, K. and Cheng, Z. (2009). Scaling of impervious surface area and vegetation as indicators to urban land surface temperature using satellite data, International Journal of Remote Sensing, 30 (4), pp. 841-859.
Toplam 23 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Bölüm Makaleler
Yazarlar

Burak Kazancı Bu kişi benim 0000-0001-8652-7142

Fulya Başak Sarıyılmaz 0000-0002-4950-3771

Yayımlanma Tarihi 30 Haziran 2020
Gönderilme Tarihi 28 Ocak 2020
Kabul Tarihi 10 Haziran 2020
Yayımlandığı Sayı Yıl 2020 Cilt: 5 Sayı: 2

Kaynak Göster

APA Kazancı, B., & Sarıyılmaz, F. B. (2020). Relationship Of Urban Development With The Heat Islands, Trabzon Case Study. Journal of Anatolian Environmental and Animal Sciences, 5(2), 218-223. https://doi.org/10.35229/jaes.681179


13221            13345           13349              13352              13353              13354          13355    13356   13358   13359   13361     13363   13364                crossref1.png            
         Paperity.org                  13369           EBSCOHost Logo        Scilit logo                  
JAES/AAS-Journal of Anatolian Environmental and Animal Sciences/Anatolian Academic Sciences&Anadolu Çevre ve Hayvancılık Dergisi/Anadolu Akademik Bilimler-AÇEH/AABcabi-logo-black.svg