Deep and machine learning methods for the (semi-)automatic extraction of sandy shoreline and erosion risk assessment basing on remote sensing data (case of Jerba island -Tunisia)

Author:

Boussetta AminaORCID,Niculescu SimonaORCID,Bengoufa Soumia,Zagrarni Mohamed Faouzi

Funder

University of Gabes

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Geography, Planning and Development

Reference70 articles.

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3. Coastline change detection using remote sensing;Alesheikh;Int. J. Environ. Sci. Technol.,2007

4. Evaluation of annual mean shoreline position deduced from Landsat imagery as a mid-term coastal evolution indicator;Almonacid-Caballer;Mar. Geol.,2016

5. Comparing supervised and unsupervised multiresolution segmentation approaches for extracting buildings from very high resolution imagery;Belgiu;ISPRS J. Photogrammetry Remote Sens.,2014

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