Remote sensing approaches for land use/land cover change in coastal areas and oceanic islands: an open science-based systematic review

Abstract

In the current climate change context, detecting and monitoring relevant land use/land cover (LULC) changes in insular and coastal areas is critical as soon as they occur. This research consists of a systematic literature review of 167 open-access articles from January 2010 to June 2022, based on several parameters, namely year of publication, journals, geographic location of the study area, time range of the studies, data source, data type, sensors, remote sensing-based approach, data processing algorithms, accuracy assessment approach, and spatial resolution, using the Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) declaration as a guideline. The results revealed that the years 2020 and 2021 showed the highest number of studies published, namely 33 for each year (20%). The continent with the most case studies was Asia (48%), with China being the most productive country in this field (23%). The most analyzed time range was superior to 20 years (37% of the studies). Satellite imagery was the most applied data source (77%), followed by relevant historical data (e.g., land cover maps). The multispectral data was used in 77% of the studies, and the Landsat Mission represents three of five of the most used sensors. Normalized Difference Vegetation Index was the most applied remote sensing-based approach (10%), and the Maximum Likelihood Classifier Algorithm was the most widely used data processing algorithm (10%). The Overall Accuracy is the most applied accuracy assessment approach used in 85 papers (51%). Many articles used a 30-meter spatial resolution (69%), and higher resolutions completed the top 5 approaches. This study contributes to perceiving the main current approaches for monitoring LULC changes in insular and coastal environments to identify research gaps for future developments.