Coastal landscape classification using convolutional neural network and remote sensing data in Vietnam

• Published in: Journal of environmental management Vol. 335; p. 117537
• Main Authors: Giang, Tuan Linh, Bui, Quang Thanh, Nguyen, Thi Dieu Linh, Dang, Van Bao, Truong, Quang Hai, Phan, Trong Trinh, Nguyen, Hieu, Ngo, Van Liem, Tran, Van Truong, Yasir, Muhammad, Dang, Kinh Bac
• Format: Journal Article
• Language: English
• Published: England Elsevier Ltd 01.06.2023
• Subjects: Artificial intelligence; Coast; Environment; Environmental Monitoring - methods; Landsat; Machine learning; Neural Networks, Computer; Optical satellite imagery; Remote Sensing Technology; Vietnam; Vietnam; Coast; Optical satellite imagery; Artificial intelligence; Machine learning; Landsat
• ISSN: 0301-4797; 1095-8630
• DOI: 10.1016/j.jenvman.2023.117537

The length of global coastline is about 356 thousand kilometers with various dynamic natural and anthropogenic. Although the number of studies on coastal landscape categorization has been increasing, it is still difficult to distinguish precisely them because the used methods commonly are traditional qualitative ones. With the leverage of remote sensing data and GIS tools, it helps categorize and identify a variety of features on land and water based on multi-source data. The aim of study is using different natural – social profile data obtained from ALOS, NOAA, and multi-temporal Landsat satellite images as input data of the convolutional-neural-network (CvNet) models for coastal landscape classification. Studies used 900 cut-line samples which represent coastal landscapes in Vietnam for training and optimizing CvNet models. As a result, nine coastal landscapes were identified including: deltas, alluvial, mature and young sand dunes, cliff, lagoon, tectonic, karst, and transitional landscapes. Three CvNet models using three different optimizer types classified the landscapes of other 1150 cut-lines in Vietnam with the accuracies about 98% and low loss function value. Excepting dalmatian, karst and delta coastal landscapes, five others distribute heterogeneous along the coasts in Vietnam. Therefore, the evaluation of additional natural components is necessary and CvNet model have ability to update new landscape types in variety of tropical nation as a step toward coastal landscape classification at both national and global scales. A coastal landscape classification system in Vietnam based on artificial intelligent models, remote sensing, GIS data. [Display omitted] •A Convolutional Neural Network to classify coastal landscapes was developed.•Different indices based on ALOS, NOAA, and Landsat data were used to classify coastal landscapes.•Five natural and anthropogenic factors were selected to identify a coastal landscape.•Nine coastal landscapes were identified in coastlines of Vietnam.•Coastal landscapes in Vietnam were separated into twenty regions with nine types.