Information In Support Of Management Research Articles

Living up to the Hype of Hyperspectral Aquatic Remote Sensing: Science, Resources and Outlook

Intensifying pressure on global aquatic resources and services due to population growth and climate change is inspiring new surveying technologies to provide science-based information in support of management and policy strategies. One area of rapid development is hyperspectral remote sensing: imaging across the full spectrum of visible and infrared light. Hyperspectral imagery contains more environmentally meaningful information than panchromatic or multispectral imagery and is poised to provide new applications relevant to society, including assessments of aquatic biodiversity, habitats, water quality, and natural and anthropogenic hazards. To aid in these advances, we provide resources relevant to hyperspectral remote sensing in terms of providing the latest reviews, databases, and software available for practitioners in the field. We highlight recent advances in sensor design, modes of deployment, and image analysis techniques that are becoming more widely available to environmental researchers and resource managers alike. Systems recently deployed on space- and airborne platforms are presented, as well as future missions and advances in unoccupied aerial systems (UAS) and autonomous in-water survey methods. These systems will greatly enhance the ability to collect interdisciplinary observations on-demand and in previously inaccessible environments. Looking forward, advances in sensor miniaturization are discussed alongside the incorporation of citizen science, moving toward open and FAIR (findable, accessible, interoperable, and reusable) data. Advances in machine learning and cloud computing allow for exploitation of the full electromagnetic spectrum, and better bridging across the larger scientific community that also includes biogeochemical modelers and climate scientists. These advances will place sophisticated remote sensing capabilities into the hands of individual users and provide on-demand imagery tailored to research and management requirements, as well as provide critical input to marine and climate forecasting systems. The next decade of hyperspectral aquatic remote sensing is on the cusp of revolutionizing the way we assess and monitor aquatic environments and detect changes relevant to global communities.

Development of an Ocean Forecasting System off the West Coast of the United States: Sea Level Applications

In the context of continuing development and implementation of global and regional ocean observing systems, we describe here the need and essential ingredients for a coastal ocean forecasting system focused on sea level and associated inundation issues and applications. Such a system must consist of the following key components: 1) satellite and in situ observations, 2) atmospheric forcing, 3) ocean circulation and tide modeling, 4) data assimilation for initialization, 5) forecast error estimation, and 6) data and model management. We describe these components, their continuing development and integrated implementation and application as part of a prototype coastal ocean forecast system for the U.S. West Coast. The multiscale nested modeling approach utilized here has demonstrated that sea level simulation can be improved by increasing the spatial resolution of observations. This and other regional ocean forecast systems are complementary and necessary elements of the emerging Global Ocean Observing System (GOOS) needed to predict changes in sea level. Building on the increasing maturity of ocean observing and forecasting capabilities, there are a number of significant challenges that require immediate attention, planning and development. These include: 1) further development of models, data assimilation algorithms and information management system, 2) adaptive sampling to reduce uncertainty in ocean forecasting, 3) Observing System Simulation Experiments (OSSE) to optimize observing system design, 4) bridging the land-sea boundary, and 5) moving from measurements to information in support of management and decision-making.