Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1169-1174, 2016
https://doi.org/10.5194/isprs-archives-XLI-B8-1169-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
 
24 Jun 2016
DETECTION OF COASTLINE DEFORMATION USING REMOTE SENSING AND GEODETIC SURVEYS
A. Sabuncu, A. Dogru, H. Ozener, and B. Turgut Bogazici University, Kandilli Observatory and Earthquake Research Institute Geodesy Department, Istanbul Turkey
Keywords: Landsat 5, Landsat 7, Geodetic Survey, GPS, Shoreline, Remote Sensing Abstract. The coastal areas are being destroyed due to the usage that effect the natural balance. Unconsciously sand mining from the sea for nearshore nourishment and construction uses are the main ones. Physical interferences for mining of sand cause an ecologic threat to the coastal environment. However, use of marine sand is inevitable because of economic reasons or unobtainable land-based sand resources. The most convenient solution in such a protection–usage dilemma is to reduce negative impacts of sand production from marine. This depends on the accurate determination of criteriaon production place, style, and amount of sand. With this motivation, nearshore geodedic surveying studies performed on Kilyos Campus of Bogazici University located on the Black Sea coast, north of Istanbul, Turkey between 2001-2002. The study area extends 1 km in the longshore. Geodetic survey was carried out in the summer of 2001 to detect the initial condition for the shoreline. Long-term seasonal changes in shoreline positions were determined biannually. The coast was measured with post-processed kinematic GPS.

Besides, shoreline change has studied using Landsat imagery between the years 1986-2015. The data set of Landsat 5 imageries were dated 05.08.1986 and 31.08.2007 and Landsat 7 imageries were dated 21.07.2001 and 28.07.2015. Landcover types in the study area were analyzed on the basis of pixel based classification method. Firstly, unsupervised classification based on ISODATA (Iterative Self Organizing Data Analysis Technique) has been applied and spectral clusters have been determined that gives prior knowledge about the study area. In the second step, supervised classification was carried out by using the three different approaches which are minimum-distance, parallelepiped and maximum-likelihood. All pixel based classification processes were performed with ENVI 4.8 image processing software. Results of geodetic studies and classification outputs will be presented in this paper.

Conference paper (PDF, 1529 KB)


Citation: Sabuncu, A., Dogru, A., Ozener, H., and Turgut, B.: DETECTION OF COASTLINE DEFORMATION USING REMOTE SENSING AND GEODETIC SURVEYS, Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLI-B8, 1169-1174, https://doi.org/10.5194/isprs-archives-XLI-B8-1169-2016, 2016.

BibTeX EndNote Reference Manager XML