Automatic extraction of large-scale aquaculture encroachment areas using Canny Edge Otsu algorithm in Google earth engine – the case study of Kolleru Lake, South India
Kolli, Meena Kumari, Opp, Christian, Karthe, Daniel and Pradhan, Biswajeet, (2022). Automatic extraction of large-scale aquaculture encroachment areas using Canny Edge Otsu algorithm in Google earth engine – the case study of Kolleru Lake, South India. Geocarto International, 1-17
Document type:
Article
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Sub-type Journal article Author Kolli, Meena Kumari
Opp, Christian
Karthe, Daniel
Pradhan, BiswajeetTitle Automatic extraction of large-scale aquaculture encroachment areas using Canny Edge Otsu algorithm in Google earth engine – the case study of Kolleru Lake, South India Appearing in Geocarto International Publication Date 2022-03-10 Place of Publication London Publisher Taylor & Francis Start page 1 End page 17 Language eng Abstract The aquaculture expansion has made significant contributions toglobal food security, socio-economic development and, if imple-mented sustainably, can help preserve stable coastal environ-ments. This study explicitly details the rapid expansion of large-scale aquaculture growth across the Kolleru and Upputeru regionsof South India. We developed a novel classification method forautomated extraction of aquaculture ponds in the Kolleru zoneusing the Canny Edge-Otsu algorithm to segment and extract theponds applied to SAR-VV images in Google Earth Engine. Thisapproach enables the area estimation of dense aquaculture pondsare essential for monitoring and management purposes. Theresults indicated that this method could effectively map the aqua-culture ponds and the overall accuracy achieved in 2020 for theKolleru and Upputeru areas by 90.6% and 95.7%, respectively. Theaquaculture maps of this study can help government organiza-tions, resource managers, stakeholders, and decision-makersunderstand the dynamics and plan sustainable measures inthis area. Keyword Google Earth Engine
CannyEdge-Otsu threshold
Sentinel-1
remote sensing
image segmentationCopyright Holder Informa UK Limited Copyright Year 2022 Copyright type All rights reserved DOI 10.3390/resources11100093 -
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