Satellite remote sensing is transforming coastal science from a “data-poor” field into a “data-rich” field. Sandy beaches are dynamic landscapes that change in response to long-term pressures, short-term pulses, and anthropogenic interventions. Until recently, the rate and breadth of beach change have outpaced our ability to monitor those changes, due to the spatiotemporal limitations of our observational capacity. Over the past several decades, only a handful of beaches worldwide have been regularly monitored with accurate yet expensive in situ surveys. The long-term coastal-change data of these few well-monitored beaches have led to in-depth understanding of many site-specific coastal processes. However, because the best-monitored beaches are not representative of all beaches, much remains unknown about the processes and fate of the other >99% of unmonitored beaches worldwide. The fleet of Earth-observing satellites has enabled multiscale monitoring of beaches, for the very first time, by providing imagery with global coverage and up to daily frequency. The long-standing and ever-expanding archive of satellite imagery will enable coastal scientists to investigate coastal change at sites vulnerable to future sea-level rise, that is, (almost) everywhere. In the past decade, our capability to observe coastal change from space has grown substantially with computing and algorithmic power. Yet, further advances are needed in automating monitoring using machine learning, deep learning, and computer vision to fully leverage this massive treasure trove of data. Extensive monitoring and investigation of the causes and effects of coastal change at the requisite spatiotemporal scales will provide coastal managers with additional, valuable information to evaluate problems and solutions, addressing the potential for widespread beach loss due to accelerated sea-level rise, development, and reduced sediment supply. Monitoring from Earth-observing satellites is currently the only means of providing seamless data with high spatiotemporal resolution at the global scale of the impending impacts of climate change on coastal systems.

Structure from motion (SFM) has become an integral technique in coastal change assessment; the U.S. Geological Survey (USGS) used Agisoft Metashape Professional Edition photogrammetry software to develop a workflow that processes coastline aerial imagery collected in response to storms since Hurricane Florence in 2018. This report details step-by-step instructions to create three-dimensional (3D) spatial products from both singular and repeated collections of shoreline aerial imagery. The products can be used for real-time hazard guidance and future forecasting and recovery endeavors.

Sediment rating curves, which are fitted relationships between river discharge (Q) and suspended‐sediment concentration (C), are commonly used to assess patterns and trends in river water quality. In many of these studies, it is assumed that rating curves have a power‐law form (i.e.C = aQ^b, whereaandbare fitted parameters). Two fundamental questions about the utility of these techniques are assessed in this paper: (i) how well to the parameters,aandb, characterize trends in the data, and (ii) are trends in rating curves diagnostic of changes to river water or sediment discharge? As noted in previous research, the offset parameter,a, is not an independent variable for most rivers but rather strongly dependent onbandQ. Here, it is shown thatais a poor metric for trends in the vertical offset of a rating curve, and a new parameter,â, as determined by the discharge‐normalized power function [C = â(Q/Q_GM)^b], whereQ_GMis the geometric mean of theQ‐values sampled, provides a better characterization of trends. However, these techniques must be applied carefully, because curvature in the relationship between log(Q) and log(C), which exists for many rivers, can produce false trends inâandb. Also, it is shown that trends inâandbare not uniquely diagnostic of river water or sediment supply conditions. For example, an increase inâcan be caused by an increase in sediment supply, a decrease in water supply or a combination of these conditions. Large changes in water and sediment supplies can occur without any change in the parameters,âandb. Thus, trend analyses using sediment rating curves must include additional assessments of the time‐dependent rates and trends of river water, sediment concentrations and sediment discharge. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.Hydrological Processespublished by John Wiley & Sons Ltd.

Coastal erosion outpaces land generation along many of the world’s deltas and a significant percentage of shorelines, and human-caused alterations to coastal sediment budgets can be important drivers of this erosion. For sediment-starved and erosion-prone coasts, large-scale enhancement of sediment supply may be an important, but poorly understood, management option. Here we provide new topographic measurements that show patterns and trends of beach accretion following the restoration of sediment supply from a massive dam removal project. River sediment was initially deposited in intertidal-to-subtidal deltaic lobes, and this sediment was reworked by ocean waves into subaerial river mouth bars over time scales of several months. These river mouth bars welded to the shoreline and then initiated waves of sediment accretion along adjacent upcoast and downcoast beaches. Although the downcoast shoreline has a high wave-angle setting, the sedimentation waves straightened the downcoast shoreline rather than forming self-organized quasi-periodic instabilities, which suggests that simple coastal evolution theory did not hold under these conditions. Combined with other mega-nourishment projects, these findings provide new understanding of littoral responses to the restoration of sediment supplies.

Warrick, J.A.; Ritchie, A.C.; Adelman, G.; Adelman, K., and Limber, P.W., 2017. New techniques to measure cliff change from historical oblique aerial photographs and Structure-from-Motion photogrammetry. Oblique aerial photograph surveys are commonly used to document coastal landscapes. Here it is shown that adequate overlap may exist in these photographic records to develop topographic models with Structure-from-Motion (SfM) photogrammetric techniques. Using photographs of Fort Funston, California, from the California Coastal Records Project, imagery were combined with ground control points in a four-dimensional analysis that produced topographic point clouds of the study area's cliffs for 5 years spanning 2002 to 2010. Uncertainty was assessed by comparing point clouds with airborne LIDAR data, and these uncertainties were related to the number and spatial distribution of ground control points used in the SfM analyses. With six or more ground control points, the root mean squared errors between...