Volume XLII-3/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 17-22, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-17-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 17-22, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-17-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Mar 2018

06 Mar 2018

LAND USE/LAND COVER CHANGE DETECTION USING MULTI–TEMPORAL SATELLITE DATASET: A CASE STUDY IN ISTANBUL NEW AIRPORT

D. Akyürek1, Ö. Koç1, E. M. Akbaba1, and F. Sunar2 D. Akyürek et al.
  • 1ITU, Civil Engineering Fac., Geomatics Department, Undergraduate Program, 80626 Maslak Istanbul, Turkey
  • 2ITU, Civil Engineering Fac., Geomatics Department, 80626 Maslak Istanbul, Turkey

Keywords: Multi-temporal satellite dataset, Land Use/Land Cover, Landsat-8, Sentinel 2A, Change detection

Abstract. In recent years, especially in metropolitan cities such as Istanbul, the emerging needs of the increasing population and demand for better air transportation capacity have led to big environmental changes. One of them is originated due to the construction of the new airport (Istanbul Grand Airport – IGA), located on the Black Sea coast on the European side of Turkey and expected as “The biggest hub in Europe” by the early 2020s. The construction has five phases and first construction phase is scheduled to finish up by the end of 2018. With an advanced space technologies including remote sensing, environmental consequences due to Land Use/Land Cover changes (LULC) can be monitored and determined efficiently. The aim of this paper is to analyse LULC changes especially in the forest areas and water bodies by using two different satellite image dataset. In this context, supervised classification method and different spectral indices are applied to both Landsat-8 (2013–2017) and Sentinel 2A (2015–2017) image datasets to demonstrate the total and annual changes during the construction of the first phase. The efficiency of two datasets is outlined by comparison of the output thematic map accuracies.