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Extraction of Urban Impervious Surface Areas in Samsun-Atakum Using Spectral Indices from Sentinel-2 Satellite Images

Year 2023, , 49 - 76, 30.04.2023
https://doi.org/10.33688/aucbd.1164879

Abstract

Impervious surfaces are increasing rapidly and causing many environmental and ecological problems because of rapid urbanization. It is important to monitor impervious surfaces through effective methods, such as remote sensing. In this study, impervious surface areas were extracted from the Sentinel-2 satellite image (July 7, 2022) in Samsun-Atakum district using UI, NDBI, IBI, CBCI, and NISI indices in the GIS environment and the indices performances were compared using the spectral discrimination index and error matrix approach. NISI was the most accurate index with a spectral discrimination index of 1.3605, an overall accuracy of 89.20%, and a kappa value of 0.7850. According to NISI, the impervious surface areas were over 40% in 5 of the 30 neighborhoods and between 30–40% in 2 neighborhoods. The results showed that Sentinel-2 satellite images have considerable potential in the extraction of impervious surfaces, and the success of impervious surface extraction can be increased by using the optimum index determined by comparing different indices.

References

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Samsun-Atakum’da Kentsel Geçirimsiz Yüzey Alanlarının Sentinel-2 Uydu Görüntülerinden Spektral İndeksler Kullanılarak Belirlenmesi

Year 2023, , 49 - 76, 30.04.2023
https://doi.org/10.33688/aucbd.1164879

Abstract

Günümüzde hızlı kentleşmeyle birlikte geçirimsiz yüzeyler hızla artmakta ve çeşitli çevresel ve ekolojik sorunlara neden olmaktadır. Bu nedenle geçirimsiz yüzeylerin uzaktan algılama gibi etkin yöntemlerle takibi önem kazanmaktadır. Bu çalışmada yüksek kentleşme oranına sahip Samsun-Atakum ilçesinde 07.07.2022 tarihli Sentinel-2 uydu görüntüsünden UI, NDBI, IBI, CBCI ve NISI indeksleri kullanılarak Coğrafi Bilgi Sistemleri (CBS) ortamında geçirimsiz yüzey alanları çıkarılmış, indekslerin performansı spektral ayrım indeksi ve hata matrisi yaklaşımı ile değerlendirilmiştir. Analizlerin sonucunda çalışma alanında en başarılı indeksin NISI olduğu belirlenmiştir. NISI indeksi 1,3605 spektral ayrım indeksi, % 89,20 genel doğruluk ve 0,7850 kappa değeriyle yüksek performans göstermiş, hem binaların hem de yolların çıkarımında başarılı olmuştur. NISI indeksi sonuçlarına göre çalışma alanında incelenen 30 mahallenin 5’inde geçirimsiz yüzey alanlarının %40’ın üzerinde ve 2’sinde % 30–40 arasında olduğu belirlenmiştir. Çalışmadan elde edilen sonuçlar Sentinel-2 uydu görüntülerinin geçirimsiz yüzey çıkarımında önemli bir potansiyel taşıdığını ve farklı indekslerin karşılaştırılması sonucunda belirlenen optimum indeksin kullanılmasıyla geçirimsiz yüzey çıkarım başarısının artırılabileceğini ortaya çıkarmıştır.

References

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  • Arnold Jr, C. L., Gibbons, C. J. (1996). Impervious surface coverage: the emergence of a key environmental indicator. Journal of the American planning Association, 62 (2), 243–258. doi:10.1080/01944369608975688
  • Atakum Belediyesi (2014). Atakum Belediyesi 2015–2019 Stratejik Planı. Samsun.
  • Atakum Kaymakamlığı (2013). Değişirken Gelişen Atakum. Samsun.
  • Batra, U., Roy, N. R., Panda, B. (Ed.) (2020). Data science and analytics: 5th international conference on recent developments in science, engineering and technology, REDSET 2019, Gurugram, India, November 15–16, 2019, Revised Selected Papers, Part II.
  • Bauer, M. E., Loffelholz, B. C., Wilson, B. (2007). Estimating and mapping impervious surface area by regression analysis of Landsat imagery. Remote Sensing of Impervious Surfaces içinde (31–48). CRC Press.
  • Bouhennache, R., Bouden, T., Taleb-Ahmed, A., Cheddad, A. (2019). A new spectral index for the extraction of built-up land features from Landsat 8 satellite imagery. Geocarto International, 34 (14), 1531–1551. doi:10.1080/10106049.2018.1497094
  • Carlson, T. N. (2007). Impervious surface area and its effect on water abundance and water quality. Remote Sensing of Impervious Surfaces içinde (381–396). CRC Press.
  • Chen, J., Chen, S., Yang, C., He, L., Hou, M., Shi, T. (2020). A comparative study of impervious surface extraction using Sentinel-2 imagery. European Journal of Remote Sensing, 53 (1), 274–292. doi:10.1080/22797254.2020.1820383
  • Chen, J., Yang, K., Chen, S., Yang, C., Zhang, S., He, L. (2019). Enhanced normalized difference index for impervious surface area estimation at the plateau basin scale. Journal of Applied Remote Sensing, 13 (1), 016502. doi:10.1117/1.JRS.13.016502
  • Congalton, R. G., Green, K. (2019). Assessing the accuracy of remotely sensed data: principles and practices. CRC Press.
  • Deliry, S. I., Avdan, Z. Y., Avdan, U. (2021). Extracting urban impervious surfaces from Sentinel-2 and Landsat-8 satellite data for urban planning and environmental management. Environmental Science and Pollution Research, 28 (6), 6572–6586. doi:10.1007/s11356-020-11007-4
  • Deng, C. B., Wu, C. S. (2012). BCI: A biophysical composition index for remote sensing of urban environments. Remote Sensing of Environment, 127, 247–259. doi:10.1016/j.rse.2012.09.009
  • Deng, Y., Wu, C., Li, M., Chen, R. (2015). RNDSI: A ratio normalized difference soil index for remote sensing of urban/suburban environments. International Journal of Applied Earth Observation and Geoinformation, 39, 40–48. doi:10.1016/j.jag.2015.02.010
  • Du, S., Shi, P., Van Rompaey, A., Wen, J. (2015). Quantifying the impact of impervious surface location on flood peak discharge in urban areas. Natural Hazards, 76 (3), 1457–1471. doi:10.1007/s11069-014-1463-2
  • Earth Resources Observation and Science Center (2022). USGS EROS Archive- Sentinel-2, 16.07.2022 tarihinde https://www.usgs.gov/centers/eros/science/usgs-eros-archive-sentinel-2?qt-science_center_objects=0#qt-science_center_objects adresinden alındı.
  • Ertan, K. (2019). Kentsel yaşam kalitesi ve ütopyalar. Kent ve Çevre Araştırmaları Dergisi, 1(1), 83–103. https://dergipark.org.tr/tr/pub/yykentcevre/issue/50632/643324 adresinden alındı.
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  • Fan, F., Fan, W., Weng, Q. (2015). Improving urban impervious surface mapping by linear spectral mixture analysis and using spectral indices. Canadian Journal of Remote Sensing, 41 (6), 577–586. doi:10.1080/07038992.2015.1112730
  • Foody, G. M. (2002). Status of land cover classification accuracy assessment. Remote Sensing of Environment, 80 (1), 185–201. doi:10.1016/S0034-4257(01)00295-4
  • Ghosh, D. K., Mandal, A. C., Majumder, R., Patra, P., Bhunia, G. S. (2018). Analysis for mapping of built-up area using remotely sensed indices–a case study of Rajarhat Block in Barasat Sadar Sub-Division in West Bengal (India). Journal of Landscape Ecology, 11 (2), 67–76. doi:10.2478/jlecol-2018-0007
  • Hidayati, I. N., Suharyadi, R. (2019). A Comparative Study of various Indices for extraction urban impervious surface of Landsat 8 OLI. Forum Geografi, 33 (2), 162–172.
  • Kaur, R., Pandey, P. (2022). A review on spectral indices for built-up area extraction using remote sensing technology. Arabian Journal of Geosciences, 15 (5), 1–22. doi:10.1007/s12517-022-09688-x
  • Kawamura, M., Jayamana, S., Tsujiko, Y. (1996). Relation between social and environmental conditions in Colombo Sri Lanka and the Urban Index estimated by satellite remote sensing data. The International Archives of Photogrammetry and Remote Sensing, 31 (PART B7), 321–326.
  • Kebede, T. A., Hailu, B. T., Suryabhagavan, K. V. (2022). Evaluation of spectral built-up indices for impervious surface extraction using Sentinel-2A MSI imageries: A case of Addis Ababa city, Ethiopia. Environmental Challenges, 8, 100568. doi:10.1016/j.envc.2022.100568
  • Li, C., Shao, Z., Zhang, L., Huang, X., Zhang, M. (2021). A comparative analysis of index-based methods for impervious surface mapping using multiseasonal sentinel-2 satellite data. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 3682–3694. doi:10.1109/JSTARS.2021.3067325
  • Li, J., Song, C., Cao, L., Zhu, F., Meng, X., Wu, J. (2011). Impacts of landscape structure on surface urban heat islands: A case study of Shanghai, China. Remote Sensing of Environment, 115 (12), 3249–3263. doi:10.1016/j.rse.2011.07.008
  • Li, L., Lu, D., Kuang, W. (2016). Examining urban impervious surface distribution and its dynamic change in Hangzhou metropolis. Remote Sensing, 8 (3), 265. doi:10.3390/rs8030265
  • Liu, Y., Meng, Q., Zhang, L., Wu, C. (2022). NDBSI: A normalized difference bare soil index for remote sensing to improve bare soil mapping accuracy in urban and rural areas. Catena, 214, 106265. doi:10.1016/j.catena.2022.106265
  • Liu, Z., Wang, Y., Li, Z., Peng, J. (2013). Impervious surface impact on water quality in the process of rapid urbanization in Shenzhen, China. Environmental Earth Sciences, 68 (8), 2365–2373. doi:10.1007/s12665-012-1918-2
  • Lu, D., Hetrick, S., Moran, E., Li, G. (2010). Detection of urban expansion in an urban-rural landscape with multitemporal QuickBird images. Journal of Applied Remote Sensing, 4 (1), 041880. doi:10.1117/1.3501124
  • Lu, D., Li, G., Kuang, W., Moran, E. (2014). Methods to extract impervious surface areas from satellite images. International Journal of Digital Earth, 7 (2), 93–112. doi:10.1080/17538947.2013.866173
  • Lu, D., Moran, E., Hetrick, S. (2011). Detection of impervious surface change with multitemporal Landsat images in an urban–rural frontier. ISPRS Journal of Photogrammetry and Remote Sensing, 66 (3), 298–306. doi:10.1016/j.isprsjprs.2010.10.010
  • Lu, D., Weng, Q. (2004). Spectral mixture analysis of the urban landscape in Indianapolis with Landsat ETM+ imagery. Photogrammetric Engineering & Remote Sensing, 70 (9), 1053–1062. doi:10.14358/PERS.70.9.1053
  • Luo, X., Peng, Y., Gao, Y. (2017). An improved optimal segmentation threshold algorithm and its application in the built-up quick mapping. Journal of the Indian Society of Remote Sensing, 45 (6), 953–964. doi:10.1007/s12524-016-0656-4
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There are 62 citations in total.

Details

Primary Language Turkish
Subjects Human Geography
Journal Section Research Article
Authors

Derya Öztürk 0000-0002-0684-3127

Early Pub Date April 30, 2023
Publication Date April 30, 2023
Published in Issue Year 2023

Cite

APA Öztürk, D. (2023). Samsun-Atakum’da Kentsel Geçirimsiz Yüzey Alanlarının Sentinel-2 Uydu Görüntülerinden Spektral İndeksler Kullanılarak Belirlenmesi. Coğrafi Bilimler Dergisi, 21(1), 49-76. https://doi.org/10.33688/aucbd.1164879