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High resolution mapping of urban areas using SPOT-5 images and ancillary data

Yıl 2015, Cilt: 2 Sayı: 2, 63 - 76, 03.08.2015
https://doi.org/10.30897/ijegeo.303545

Öz

This research aims to propose new rule sets to be used for object based classification of SPOT-5
images to accurately create detailed urban land cover/use maps. In addition to SPOT-5 satellite
images, Normalized Difference Vegetation Index (NDVI) and Normalized Difference Water Index
(NDWI) maps, cadastral maps, Openstreet maps, road maps and Land Cover maps, were also
integrated into classification to increase the accuracy of resulting maps. Gaziantep city, one of the
highly populated cities of Turkey with different landscape patterns was selected as the study area.
Different rule sets involving spectral, spatial and geometric characteristics were developed to be
used for object based classification of 2.5 m resolution Spot-5 satellite images to automatically
create urban map of the region. Twenty different land cover/use classes obtained from European
Urban Atlas project were applied and an automatic classification approach was suggested for high
resolution urban map creation and updating. Integration of different types of data into the
classification decision tree increased the performance and accuracy of the suggested approach. The
accuracy assessment results illustrated that with the usage of newly proposed rule set algorithms in
object-based classification, urban areas represented with seventeen different sub-classes could be
mapped with 94 % or higher overall accuracy.

Kaynakça

  • Akay, S. S. “A Case Study for Urban Atlas Project: Gaziantep City,” Master Thesis, Istanbul Technical University, Istanbul (2014).
  • Blaschke, T., G. J. Hay, Q. Weng, and B. Resch, “Collective Sensing: Integrating Geospatial Technologies to Understand Urban Systems,” An Overview, Remote Sensing 3(8), 1743–1776 (2011).
  • Campbell, J. Introduction to Remote Sensing, 4th ed., The Guilford Press, New York (2007).
  • City Development Information. Available online: http://tr.wikipedia.org/wiki/ (accessed on 14 October 2014)
  • City Population. Available online: http://www.tuik.gov.tr/PreTablo.do?alt_id=1059, (accessed on 20 April 2014).
  • Deng, J.S. K. Wang, Y. Hong, and J. G. Qi, “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 (2009).
  • eCognition, eCognition Developer (8.64.0) Reference Book, Trimble Germany GmbH, Munich, (2010).
  • Gamba, P. F. Dell’Acqua, and B. Dasarathy, “Urban Remote Sensing Using Multiple Datasets: Past, Present, And Future,” Information Fusion 6, 319–326 (2005).
  • Herold, H., M. E. Gardner, and D. A. Roberts, “Spectral Resolution Requirements for Mapping Urban Areas,” IEEE Transactions on Geoscience and Remote Sensing 41(9), 1907-1919 (2003).
  • Lobo, A. “Image Segmentation and Discriminant Analysis for The Identification of Land Cover Units in Ecology,” IEEE Transactions on Geoscience and Remote Sensing 33, 1136–1145 (1997).
  • Lu, D. and Q. Weng, “Use of Impervious Surface in Urban Land-use Classification,” Remote Sensing of Environment 102(1-2), 146-160 (2006).
  • Ludlow, D. and W. Steinborn, “The European Urban Atlas,” Towards eEnvironment Conference, Prague (2009).
  • Mapping Guide for a European Urban Atlas, European Environmental Agency web page. Available online: http://ec.europa.eu/regional_policy/tender/pdf/2012066/annexe2.pdf (accessed on 29 April 2014)
  • Matikainen, L. and K. Karila, “Segment-Based Land Cover Mapping of A Suburban Area—Comparison of High-Resolution Remotely Sensed Datasets Using Classification Trees and Test Field Points,” Remote Sensing 3, 1777–1804 (2011).
  • Mohapatra, R. P. and C. Wu, “High Resolution Impervious Surface Estimation: An Integration of IKONOS and Landsat-7 ETM+ Imagery,” Photogrammetric Engineering and Remote Sensing 76, 1329–1341 (2010).
  • Myint, S.W., P. Gober, A. Brazel, S. G. Clark, and Q. Weng, “Per-Pixel vs. Object-Based Classification of Urban Land Cover Extraction Using High Spatial Resolution Imagery,” Remote Sensing Environment, 115(5), 1145–1161 (2011).
  • Salehi, B., Y. Zhang, M. Zhong, and V. Dey, “Object-Based Classification of Urban Areas Using VHR Imagery and Height Points Ancillary Data,” Remote Sensing, 2072-4292 (2012).
  • Seifert, F. M. “Global Mapping of Human Settlement: Experiences, Datasets and Prospects,” Chapter 11: Improving Urban Monitoring Toward a European Urban Atlas, Taylor and Francis Group, Boca Raton, FL (2009).
  • Sertel, E., N. Findik, S. Kaya, D. Z. Seker, and A. Samsunlu, “Assessment of Landscape Changes in the Kizilirmak Delta, Turkey Using Remotely Sensed Data and GIS,” Environmental Engineering Science 25(3), 353-362 (2008).
  • Thapa, R. B. and Y. Murayama, “Urban Mapping, Accuracy and Image Classification: A Comparison of Multiple Approaches in Tsukuba City, Japan,” Applied Geography 29, 135–144 (2009).
  • Thomas, N., C. Hendrix and R. Congalton. “A comparison of urban mapping methods using high-resolution digital imagery”, Photogrammetric Engineering & Remote Sensing, 69(9), 963-972 (2003).
  • Urban Atlas Final Report. Urban Atlas Delivery of Land Use/Cover Maps of Major European Urban Agglomerations. Available online: http://ec.europa.eu/regional_policy/tender/pdf/ 2012066/urban_atlas_final_report_112011.pdf (accessed on 29 April 2014)
  • Walker, J. S. and T. Blaschke, “Object‐Based Land‐Cover Classification for the Phoenix Metropolitan Area: Optimization vs. Transportability,” International Journal of Remote Sensing 29(7), 2021-2040 (2008).
  • Weng, Q. “Remote Sensing of Impervious Surfaces in The Urban Areas: Requirements, Methods, and Trends,” Remote Sensing of Environment 117, 34-49 (2012).
Yıl 2015, Cilt: 2 Sayı: 2, 63 - 76, 03.08.2015
https://doi.org/10.30897/ijegeo.303545

Öz

Kaynakça

  • Akay, S. S. “A Case Study for Urban Atlas Project: Gaziantep City,” Master Thesis, Istanbul Technical University, Istanbul (2014).
  • Blaschke, T., G. J. Hay, Q. Weng, and B. Resch, “Collective Sensing: Integrating Geospatial Technologies to Understand Urban Systems,” An Overview, Remote Sensing 3(8), 1743–1776 (2011).
  • Campbell, J. Introduction to Remote Sensing, 4th ed., The Guilford Press, New York (2007).
  • City Development Information. Available online: http://tr.wikipedia.org/wiki/ (accessed on 14 October 2014)
  • City Population. Available online: http://www.tuik.gov.tr/PreTablo.do?alt_id=1059, (accessed on 20 April 2014).
  • Deng, J.S. K. Wang, Y. Hong, and J. G. Qi, “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 (2009).
  • eCognition, eCognition Developer (8.64.0) Reference Book, Trimble Germany GmbH, Munich, (2010).
  • Gamba, P. F. Dell’Acqua, and B. Dasarathy, “Urban Remote Sensing Using Multiple Datasets: Past, Present, And Future,” Information Fusion 6, 319–326 (2005).
  • Herold, H., M. E. Gardner, and D. A. Roberts, “Spectral Resolution Requirements for Mapping Urban Areas,” IEEE Transactions on Geoscience and Remote Sensing 41(9), 1907-1919 (2003).
  • Lobo, A. “Image Segmentation and Discriminant Analysis for The Identification of Land Cover Units in Ecology,” IEEE Transactions on Geoscience and Remote Sensing 33, 1136–1145 (1997).
  • Lu, D. and Q. Weng, “Use of Impervious Surface in Urban Land-use Classification,” Remote Sensing of Environment 102(1-2), 146-160 (2006).
  • Ludlow, D. and W. Steinborn, “The European Urban Atlas,” Towards eEnvironment Conference, Prague (2009).
  • Mapping Guide for a European Urban Atlas, European Environmental Agency web page. Available online: http://ec.europa.eu/regional_policy/tender/pdf/2012066/annexe2.pdf (accessed on 29 April 2014)
  • Matikainen, L. and K. Karila, “Segment-Based Land Cover Mapping of A Suburban Area—Comparison of High-Resolution Remotely Sensed Datasets Using Classification Trees and Test Field Points,” Remote Sensing 3, 1777–1804 (2011).
  • Mohapatra, R. P. and C. Wu, “High Resolution Impervious Surface Estimation: An Integration of IKONOS and Landsat-7 ETM+ Imagery,” Photogrammetric Engineering and Remote Sensing 76, 1329–1341 (2010).
  • Myint, S.W., P. Gober, A. Brazel, S. G. Clark, and Q. Weng, “Per-Pixel vs. Object-Based Classification of Urban Land Cover Extraction Using High Spatial Resolution Imagery,” Remote Sensing Environment, 115(5), 1145–1161 (2011).
  • Salehi, B., Y. Zhang, M. Zhong, and V. Dey, “Object-Based Classification of Urban Areas Using VHR Imagery and Height Points Ancillary Data,” Remote Sensing, 2072-4292 (2012).
  • Seifert, F. M. “Global Mapping of Human Settlement: Experiences, Datasets and Prospects,” Chapter 11: Improving Urban Monitoring Toward a European Urban Atlas, Taylor and Francis Group, Boca Raton, FL (2009).
  • Sertel, E., N. Findik, S. Kaya, D. Z. Seker, and A. Samsunlu, “Assessment of Landscape Changes in the Kizilirmak Delta, Turkey Using Remotely Sensed Data and GIS,” Environmental Engineering Science 25(3), 353-362 (2008).
  • Thapa, R. B. and Y. Murayama, “Urban Mapping, Accuracy and Image Classification: A Comparison of Multiple Approaches in Tsukuba City, Japan,” Applied Geography 29, 135–144 (2009).
  • Thomas, N., C. Hendrix and R. Congalton. “A comparison of urban mapping methods using high-resolution digital imagery”, Photogrammetric Engineering & Remote Sensing, 69(9), 963-972 (2003).
  • Urban Atlas Final Report. Urban Atlas Delivery of Land Use/Cover Maps of Major European Urban Agglomerations. Available online: http://ec.europa.eu/regional_policy/tender/pdf/ 2012066/urban_atlas_final_report_112011.pdf (accessed on 29 April 2014)
  • Walker, J. S. and T. Blaschke, “Object‐Based Land‐Cover Classification for the Phoenix Metropolitan Area: Optimization vs. Transportability,” International Journal of Remote Sensing 29(7), 2021-2040 (2008).
  • Weng, Q. “Remote Sensing of Impervious Surfaces in The Urban Areas: Requirements, Methods, and Trends,” Remote Sensing of Environment 117, 34-49 (2012).
Toplam 24 adet kaynakça vardır.

Ayrıntılar

Bölüm Research Articles
Yazarlar

Elif Sertel

Semih Sami Akay

Yayımlanma Tarihi 3 Ağustos 2015
Yayımlandığı Sayı Yıl 2015 Cilt: 2 Sayı: 2

Kaynak Göster

APA Sertel, E., & Akay, S. S. (2015). High resolution mapping of urban areas using SPOT-5 images and ancillary data. International Journal of Environment and Geoinformatics, 2(2), 63-76. https://doi.org/10.30897/ijegeo.303545

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