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

Year 2015, Volume 2, Issue 2, 63 - 76, 03.08.2015
https://doi.org/10.30897/ijegeo.303545

Abstract

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.

References

  • 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).

Year 2015, Volume 2, Issue 2, 63 - 76, 03.08.2015
https://doi.org/10.30897/ijegeo.303545

Abstract

References

  • 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).

Details

Journal Section Research Articles
Authors

Elif SERTEL>
Istanbul Technical University, Department of Geomatics Engineering, Istanbul
0000-0003-4854-494X
Türkiye


Semih Sami AKAY>
Istanbul Technical University, Center for Satellite Communication and Remote Sensing, Istanbul
0000-0002-7367-8555
Türkiye

Publication Date August 3, 2015
Published in Issue Year 2015, Volume 2, Issue 2

Cite

Bibtex @research article { ijegeo303545, journal = {International Journal of Environment and Geoinformatics}, eissn = {2148-9173}, address = {}, publisher = {Cem GAZİOĞLU}, year = {2015}, volume = {2}, number = {2}, pages = {63 - 76}, doi = {10.30897/ijegeo.303545}, title = {High resolution mapping of urban areas using SPOT-5 images and ancillary data}, key = {cite}, author = {Sertel, Elif and Akay, Semih Sami} }
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 . DOI: 10.30897/ijegeo.303545
MLA Sertel, E. , Akay, S. S. "High resolution mapping of urban areas using SPOT-5 images and ancillary data" . International Journal of Environment and Geoinformatics 2 (2015 ): 63-76 <https://dergipark.org.tr/en/pub/ijegeo/issue/28165/303545>
Chicago Sertel, E. , Akay, S. S. "High resolution mapping of urban areas using SPOT-5 images and ancillary data". International Journal of Environment and Geoinformatics 2 (2015 ): 63-76
RIS TY - JOUR T1 - High resolution mapping of urban areas using SPOT-5 images and ancillary data AU - ElifSertel, Semih SamiAkay Y1 - 2015 PY - 2015 N1 - doi: 10.30897/ijegeo.303545 DO - 10.30897/ijegeo.303545 T2 - International Journal of Environment and Geoinformatics JF - Journal JO - JOR SP - 63 EP - 76 VL - 2 IS - 2 SN - -2148-9173 M3 - doi: 10.30897/ijegeo.303545 UR - https://doi.org/10.30897/ijegeo.303545 Y2 - 2015 ER -
EndNote %0 International Journal of Environment and Geoinformatics High resolution mapping of urban areas using SPOT-5 images and ancillary data %A Elif Sertel , Semih Sami Akay %T High resolution mapping of urban areas using SPOT-5 images and ancillary data %D 2015 %J International Journal of Environment and Geoinformatics %P -2148-9173 %V 2 %N 2 %R doi: 10.30897/ijegeo.303545 %U 10.30897/ijegeo.303545
ISNAD Sertel, Elif , Akay, Semih Sami . "High resolution mapping of urban areas using SPOT-5 images and ancillary data". International Journal of Environment and Geoinformatics 2 / 2 (August 2015): 63-76 . https://doi.org/10.30897/ijegeo.303545
AMA Sertel E. , Akay S. S. High resolution mapping of urban areas using SPOT-5 images and ancillary data. International Journal of Environment and Geoinformatics. 2015; 2(2): 63-76.
Vancouver Sertel E. , Akay S. S. High resolution mapping of urban areas using SPOT-5 images and ancillary data. International Journal of Environment and Geoinformatics. 2015; 2(2): 63-76.
IEEE E. Sertel and S. S. Akay , "High resolution mapping of urban areas using SPOT-5 images and ancillary data", International Journal of Environment and Geoinformatics, vol. 2, no. 2, pp. 63-76, Aug. 2015, doi:10.30897/ijegeo.303545

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