Abstract
Insular ecosystems are natural laboratories in which evolution processes may be isolated and examined before being connected and expanded to the more complicated patterns displayed by more extensive systems. Similarly, islands can provide insights into effective land/costal management techniques. In the current climate change context, and with most of these territories being highly vulnerable to natural hazards (e.g., landslides, volcanic eruptions, earthquakes, etc.), it is critical to detect and monitor relevant land surface, and land use/land cover (LULC) changes as soon as they occur, to identify and address their drivers and triggers through effective land/coastal planning and management policies. This research aims to evaluate the current state-of-the-art in remote sensing-based multi-sensor land surface and LULC change detection in terms data availability/complementarity, methodological approaches, data processing strategies, and parameters. A systematic literature review was undertaken using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses declaration (PRISMA) as a guideline to reach this goal. A search was run by applying nine combinations of relevant keywords and Boolean operators to the title, abstract, and keywords of pre-selected works. Review papers, conference papers, publications authored in languages other than English and  those that were not open access were not included. The search period was between January 2010 and June 2022 (the last access was done on 30 June 2022). As a result, a database including  167 journal articles from the Web of Science was created. The main results revealed an increasing number of published papers using remote sensing to map and quantify LULC change areas. Multispectral data were the most relevant source for identifying and analyzing surface changes (e.g., Landsat mission). The results revealed also that the highest number of studies was published in 2020 and 2021. The continent with more case studies was Asia, with China being the more productive country in this field. Most articles (26%) analyzed in this study were published in the Remote Sensing journal (MDPI). Moreover, this analysis showed that the combination of different parameters studied in this paper, namely the data source, data type, sensors, approaches, algorithms, software, platforms, spatial resolution and temporal resolution, might foster new opportunities for improved remote sensing-based LULC monitoring in oceanic islands and coastal areas.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.