Land-cover (LC) products, especially at the regional and global scales, comprise essential data for a wide range of environmental studies affecting biodiversity, climate, and human health. This review builds on previous compartmentalized efforts by summarizing 23 global and 41 regional LC products. Characteristics related to spatial resolution, overall accuracy, time of data acquisition, sensor used, classification scheme and method, support for LC change detection, download location, and key corresponding references are provided. Operational limitations and uncertainties are discussed, mostly as a result of different original modelling outcomes. Upcoming products are presented and future prospects towards increasing usability of different LC products are offered. Despite the common realization of product usage by non-experts, the remote-sensing community has not fully addressed the challenge. Algorithmic development for the effective representation of inherent product limitations to facilitate proper usage by non-experts is necessary. Further emphasis should be placed on international coordination and harmonization initiatives for compatible LC product generation. We expect the applicability of current and future LC products to increase, especially as our environmental understanding increases through multi-temporal studies.

Algae serves as a food source for a wide range of aquatic species; however, a high concentration of inorganic nutrients under favorable conditions can result in the development of harmful algal blooms (HABs). Many studies have addressed HAB detection and monitoring; however, no global scale meta-analysis has specifically explored remote sensing-based HAB monitoring. Therefore, this manuscript elucidates and visualizes spatiotemporal trends in HAB detection and monitoring using remote sensing methods and discusses future insights through a meta-analysis of 420 journal articles. The results indicate an increase in the quantity of published articles which have facilitated the analysis of sensors, software, and HAB proxy estimation methods. The comparison across multiple studies highlighted the need for a standardized reporting method for HAB proxy estimation. Research gaps include: (1) atmospheric correction methods, particularly for turbid waters, (2) the use of analytical-based models, (3) the application of machine learning algorithms, (4) the generation of harmonized virtual constellation and data fusion for increased spatial and temporal resolutions, and (5) the use of cloud-computing platforms for large scale HAB detection and monitoring. The planned hyperspectral satellites will aid in filling these gaps to some extent. Overall, this review provides a snapshot of spatiotemporal trends in HAB monitoring to assist in decision making for future studies.