The need for more effective environmental monitoring of the open and coastal ocean has recently led to notable advances in satellite ocean color technology and algorithm research. Satellite ocean color sensors’ data are widely used for the detection, mapping and monitoring of phytoplankton blooms because earth observation provides a synoptic view of the ocean, both spatially and temporally. Algal blooms are indicators of marine ecosystem health; thus, their monitoring is a key component of effective management of coastal and oceanic resources. Since the late 1970s, a wide variety of operational ocean color satellite sensors and algorithms have been developed. The comprehensive review presented in this article captures the details of the progress and discusses the advantages and limitations of the algorithms used with the multi-spectral ocean color sensors CZCS, SeaWiFS, MODIS and MERIS. Present challenges include overcoming the severe limitation of these algorithms in coastal waters and refining detection limits in various oceanic and coastal environments. To understand the spatio-temporal patterns of algal blooms and their triggering factors, it is essential to consider the possible effects of environmental parameters, such as water temperature, turbidity, solar radiation and bathymetry. Hence, this review will also discuss the use of statistical techniques and additional datasets derived from ecosystem models or other satellite sensors to characterize further the factors triggering or limiting the development of algal blooms in coastal and open ocean waters

Science, resource management, and defense need algorithms capable of using airborne or satellite imagery to accurately map bathymetry, water quality, and substrate composition in optically shallow waters. Although a variety of inversion algorithms are available, there has been limited assessment of performance and no work has been published comparing their accuracy and efficiency. This paper compares the absolute and relative accuracies and computational efficiencies of one empirical and five radiative‐transfer‐based published approaches applied to coastal sites at Lee Stocking Island in the Bahamas and Moreton Bay in eastern Australia. These sites have published airborne hyperspectral data and field data. The assessment showed that (1) radiative‐transfer—based methods were more accurate than the empirical approach for bathymetric retrieval, and the accuracies and processing times were inversely related to the complexity of the models used; (2) all inversion methods provided moderately accurate retrievals of bathymetry, water column inherent optical properties, and benthic reflectance in waters less than 13 m deep with homogeneous to heterogeneous benthic/ substrate covers; (3) slightly higher accuracy retrievals were obtained from locally parameterized methods; and (4) no method compared here can be considered optimal for all situations. The results provide a guide to the conditions where each approach may be used (available image and field data and processing capability). A re‐analysis of these same or additional sites with satellite hyperspectral data with lower spatial and radiometric resolution, but higher temporal resolution would be instructive to establish guidelines for repeatable regional to global scale shallow water mapping approaches.

Freshwater ecosystems underpin global water and food security, yet are some of the most endangered ecosystems in the world because they are particularly vulnerable to land management change and climate variability. The US National Research Council's guidance to NASA regarding missions for the coming decade includes a polar orbiting, global mapping hyperspectral satellite remote sensing mission, the Hyperspectral Infrared Imager (HyspIRI), to make quantitative measurements of ecosystem change. Traditionally, freshwater ecosystems have been challenging to measure with satellite remote sensing because they are small and spatially complex, require high fidelity spectroradiometry, and are best described with biophysical variables derived from high spectral resolution data. In this study, we evaluate the contribution of a hyperspectral global mapping satellite mission to measuring freshwater ecosystems. We demonstrate the need for such a mission, and evaluate the suitability and gaps, through an examination of the measurement resolution issues impacting freshwater ecosystem measurements (spatial, temporal, spectral and radiometric). These are exemplified through three case studies that use remote sensing to characterize a component of freshwater ecosystems that drive primary productivity. The high radiometric quality proposed for the HyspIRI mission makes it uniquely well designed for measuring freshwater ecosystems accurately at moderate to high spatial resolutions. The spatial and spectral resolutions of the HyspIRI mission are well suited for the retrieval of multiple biophysical variables, such as phycocyanin and chlorophyll-a. The effective temporal resolution is suitable for characterizing growing season wetland phenology in temperate regions, but may not be appropriate for tracking algal bloom dynamics, or ecosystem responses to extreme events in monsoonal regions. Global mapping missions provide the systematic, repeated measurements necessary to measure the drivers of freshwater biodiversity change. Archival global mapping missions with open access and free data policies increase end user uptake globally. Overall, an archival, hyperspectral global mapping mission uniquely meets the measurement requirements of multiple end users for freshwater ecosystem science and management