TY - GEN
T1 - Long-term coastal changes detection system based on remote sensing and image processing around an island
AU - Bouchahma, Maged
AU - Yan, Wanglin
PY - 2012/10/10
Y1 - 2012/10/10
N2 - As an island ecosystem, Djerba, a region of Tunisia located on the southern shore of the Mediterranean Sea, is characterized by limited natural resources and threatened by land degradation due to rapid socio-economic development and heavy human-induced changes to the landscape. The objective of this study is to build a system based on computer vision and remote sensing data for monitoring changes in the coastal zones of an island. We employed monthly Landsat Thematic Mapper (TM) satellite images of the study area ranging from 1984 to 2009. The images were preprocessed using the Speeded Up Robust Features (SURF) algorithm to superimpose remote sensing images at exactly the same coordinates. We then used comparison technique to auto-validate the detection of changes. The technique is based on a window-to-window comparison of the coastal zones. Three highly affected regions were identified. The Bin El-Ouidiane (in the southeast) and Rass Errmal (in the north) regions underwent deposition during the study period, whereas the region of Rass El Kastil (in the north) underwent high erosion.
AB - As an island ecosystem, Djerba, a region of Tunisia located on the southern shore of the Mediterranean Sea, is characterized by limited natural resources and threatened by land degradation due to rapid socio-economic development and heavy human-induced changes to the landscape. The objective of this study is to build a system based on computer vision and remote sensing data for monitoring changes in the coastal zones of an island. We employed monthly Landsat Thematic Mapper (TM) satellite images of the study area ranging from 1984 to 2009. The images were preprocessed using the Speeded Up Robust Features (SURF) algorithm to superimpose remote sensing images at exactly the same coordinates. We then used comparison technique to auto-validate the detection of changes. The technique is based on a window-to-window comparison of the coastal zones. Three highly affected regions were identified. The Bin El-Ouidiane (in the southeast) and Rass Errmal (in the north) regions underwent deposition during the study period, whereas the region of Rass El Kastil (in the north) underwent high erosion.
KW - Canny edge detector
KW - Coastal line change
KW - Djerba
KW - Landsat TM
KW - SURF
UR - http://www.scopus.com/inward/record.url?scp=84867136834&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84867136834&partnerID=8YFLogxK
U2 - 10.1109/Geoinformatics.2012.6270334
DO - 10.1109/Geoinformatics.2012.6270334
M3 - Conference contribution
AN - SCOPUS:84867136834
SN - 9781467311045
T3 - Proceedings - 2012 20th International Conference on Geoinformatics, Geoinformatics 2012
BT - Proceedings - 2012 20th International Conference on Geoinformatics, Geoinformatics 2012
T2 - 2012 20th International Conference on Geoinformatics, Geoinformatics 2012
Y2 - 15 June 2012 through 17 June 2012
ER -