Application of Optical Remote Sensing in Harmful Algal Blooms in Lakes: A Review

Abstract

Harmful algal blooms (HABs) are a critical global issue, severely impacting aquatic ecosystems, public health, and economies. Optical remote sensing (ORS) has emerged as a prominent tool for HABs monitoring, providing operational capabilities for quantifying spatiotemporal dynamics through cost-effective observation platforms. This review systematically synthesizes recent advancements in ORS technologies, encompassing (1) novel sensor development, (2) advanced data analytics frameworks, and (3) the synergistic integration of multi-scale observation platforms (satellite–airborne–ground). The analysis critically evaluates (a) spectral signature identification methodologies and (b) persistent challenges including suboptimal spatiotemporal resolution, atmospheric correction uncertainties, and limited model generalizability across heterogeneous aquatic systems. Emerging technologies, including machine learning, spatial–temporal data fusion, and high-performance sensors, are explored as potential solutions to overcome these challenges.