Beach carrying capacity assessment through image processing tools for coastal management. (October 2016)

• Record Type: Journal Article
• Authors: Huamantinco Cisneros, M. Andrea; Revollo Sarmiento, Natalia V.; Delrieux, Claudio A.; Piccolo, M. Cintia; Perillo, Gerardo M.E.
• Is Part Of: Ocean & coastal management. Volume 130(2016)
• Page Start: 138
• Page End: 147
• Publication Date: 2016-10
• Subjects: Image processing -- Coastal software -- Coastal management -- Feature extraction -- Beach Carrying Capacity -- Geographic Information Systems; Marine resources -- Management -- Periodicals; Coastal zone management -- Periodicals; Coastal ecology -- Periodicals; Ressources marines -- Périodiques; Littoral -- Aménagement -- Périodiques; Écologie littorale -- Périodiques; Coastal ecology; Coastal zone management; Marine resources -- Management; Periodicals; Electronic journals; 551.46
• DOI: 10.1016/j.ocecoaman.2016.06.010
• Languages: English
• ISSNs: 0964-5691

Abstract

Abstract: Coastal environments are spaces where people may develop varied economic and recreational activities, such as tourism, which usually damage beaches and other natural resources commonly placed in these settings. The aim of this paper is to present a methodology to estimate and evaluate the Beach Carrying Capacity (BCC) and the actual beach usage level in coastal cities, using on-site information and video processing to provide significant real-time data. To test our methodology, we chose the coastal city of Monte Hermoso, Argentina, as a pilot site because it is by far the prime choice for a large population during summer vacation in this country. Initially, to estimate BCC, cartographic information about facilities and beach zones was collected and combined with surveys requested to tourists, to better understand their habits and preferences. This allowed an accurate estimation of other beach capacities related to BCC. Secondly, beach video sequences were processed with an algorithm that identified, located and counted people on the beach with an adequate accuracy. The actual occupancy factor was computed and used to asses whether the BCC had been exceeded. Also, people were tracked and their preferred relaxing areas were registered (e.g, closer to seaside during the morning). Finally, all the information was stored and visualized using a Geographic Information System (GIS) which allows both to analyze the different information layers and to produce interactive thematic maps. In this way, the resulting methodology may help to identify zones under risk of deterioration and to define suitable places for the development of varied activities (specially those related to tourism). It may also serve as a dashboard for decision and policy making and contribute to coastal management planning as well. Highlights: We assess the Beach Carrying Capacity through video and image processing. On-site measurements and video processing information were used to provide real-time data. Processing video sequences allows recognizing, locating and counting people on the beach. Information obtained is visualized in a Geographic Information System. Each monitored zone under deterioration risk could be identified by the proposed methodology.