Shoreline variability from days to decades: Results of long‐term video imaging

Pianca, Cássia; Holman, Robert A.; Siegle, Eduardo

doi:10.1002/2014jc010329

Cited by 88 publications

(72 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The coastlines detected by multi-temporal satellite imagery have been well verified by a number of studies using topographic, nautical, water level surveys, and near-ground photography [18,19]. Remote sensing video systems are another tool for coastline change detection used by some researchers [20][21][22][23]. Airborne Lidar is suggested for improved detection and monitoring of coastlines [24][25][26][27].…”

Section: Introductionmentioning

confidence: 94%

Developing Superfine Water Index (SWI) for Global Water Cover Mapping Using MODIS Data

et al. 2015

View full text Add to dashboard Cite

Abstract:Monitoring of water cover and shorelines at a global scale is essential for better understanding climate change consequences and modern human disturbances. The level and turbidity of the surface water, and the background objects in which they interact with, vary significantly at a global scale. The existing water indices applicable to detection and extraction of water cover at local and regional scales cannot work efficiently everywhere in the globe. In this research, a new water index called Superfine Water Index (SWI) was developed for robust detection and discrimination of the surface water at a global scale using MODIS based multispectral data. The SWI was designed in such a way that it provides high contrast between the water and non-water areas. Achieving high contrast is vital for discriminating the surface water mixed with a variety of objects. The sensitivity analysis of the SWI demonstrated its high sensitivity to the surface water compared to the existing water indices. One single-layered global mosaic of a 90-percentile SWI image was used as a master image for global water cover mapping by reducing the large volume of MODIS data available between 2012 and 2014 globally. The random walker algorithm was applied in the SWI image with the support of reference training data for the extraction and mapping of water cover. This research produced an up-to-date global water cover map of the year 2013. OPEN ACCESSRemote Sens. 2015, 7 13808The performance of a new map was evaluated with a number of case studies and compared with existing maps. The supremacy of the SWI over the existing water indices, and high performance of the SWI based water map confirmed the reliability of the new water mapping methodology developed. We expect that this methodology can contribute to seasonal and annual change analysis of the global water cover as well.

show abstract

Section: Introductionmentioning

confidence: 94%

Developing Superfine Water Index (SWI) for Global Water Cover Mapping Using MODIS Data

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Video remote sensing data provides a unique source of long-term, sustained monitoring of the coastline, in which shoreline behavior can be explored in relation to a range of forcing conditions [3,31,33]. Utilizing approximately six years of weekly image-derived shoreline data from the permanent Argus station at Narrabeen-Collaroy, Davidson et al [31] developed and tested a new equilibrium-based shoreline model for wave-dominated coastlines.…”

Section: Shoreline Modelingmentioning

confidence: 99%

“…It complements a handful of other coastal monitoring programs around the world in which comprehensive datasets have been collected near-continuously using in-situ methods spanning several decades. Some notable examples of current long-term coastal monitoring programs worldwide include efforts by Rijkswaterstaat in the Netherlands (JarKus, http://kml.deltares.nl/kml/rijkswaterstaat/jarkus/), the United States Geological Survey on the US West Coast (e.g., [2]), the United States Army Corps of Engineers on the US East Coast (e.g., [3], see http://www.frf.usace.army.mil/) and the Hazaki Oceanographical Research Station in Japan (e.g., [4]). The international coastal research community has been using these long-term observations for more than four decades to significantly expand knowledge of nearshore processes, waves and beaches.…”

Section: Introductionmentioning

confidence: 99%

Remote Sensing Is Changing Our View of the Coast: Insights from 40 Years of Monitoring at Narrabeen-Collaroy, Australia

2018

View full text Add to dashboard Cite

Narrabeen-Collaroy Beach, located on the Northern Beaches of Sydney along the Pacific coast of southeast Australia, is one of the longest continuously monitored beaches in the world. This paper provides an overview of the evolution and international scientific impact of this long-term beach monitoring program, from its humble beginnings over 40 years ago using the rod and tape measure Emery field survey method; to today, where the application of remote sensing data collection including drones, satellites and crowd-sourced smartphone images, are now core aspects of this continuing and much expanded monitoring effort. Commenced in 1976, surveying at this beach for the first 30 years focused on in-situ methods, whereby the growing database of monthly beach profile surveys informed the coastal science community about fundamental processes such as beach state evolution and the role of cross-shore and alongshore sediment transport in embayment morphodynamics. In the mid-2000s, continuous (hourly) video-based monitoring was the first application of routine remote sensing at the site, providing much greater spatial and temporal resolution over the traditional monthly surveys. This implementation of video as the first of a now rapidly expanding range of remote sensing tools and techniques also facilitated much wider access by the international research community to the continuing data collection program at Narrabeen-Collaroy. In the past decade the video-based data streams have formed the basis of deeper understanding into storm to multi-year response of the shoreline to changing wave conditions and also contributed to progress in the understanding of estuary entrance dynamics. More recently, 'opportunistic' remote sensing platforms such as surf cameras and smartphones have also been used for image-based shoreline data collection. Commencing in 2011, a significant new focus for the Narrabeen-Collaroy monitoring program shifted to include airborne lidar (and later Unmanned Aerial Vehicles (UAVs)), in an enhanced effort to quantify the morphological impacts of individual storm events, understand key drivers of erosion, and the placing of these observations within their broader regional context. A fixed continuous scanning lidar installed in 2014 again improved the spatial and temporal resolution of the remote-sensed data collection, providing new insight into swash dynamics and the often-overlooked processes of post-storm beach recovery. The use of satellite data that is now readily available to all coastal researchers via Google Earth Engine continues to expand the routine data collection program and provide key insight into multi-decadal shoreline variability. As new and expanding remote sensing technologies continue to emerge, a key lesson from the long-term monitoring at Narrabeen-Collaroy is the importance of a regular re-evaluation of what data is most needed to progress the science.

show abstract

“…Long-term observational data sets of beach profile variability and underlying trends that have been measured regularly and uninterrupted for several decades are very rare (Barnard et al, 2012(Barnard et al, , 2015Kuriyama et al, 2012;Splinter et al, 2014;Pianca et al, 2015;Turner et al, 2016). Only a few sites around the world have sustained routine decadal-scale monitoring of the coastline, with notable examples that include the US Army Corps of Engineers Field Research Facility in the United States (http://www.frf.usace.army.mil), the Hazaki Oceanographical Research Station in Japan (http://www.pari.go.jp/unit/ edosy/en/main-facility/2.html), and Narrabeen-Collaroy Beach in Australia (http://www.narrabeen.wrl.unsw.edu.au).…”

Section: Purpose Of Activitymentioning

confidence: 99%

Assessing Cross-Shore and Alongshore Variation in Beach Morphology Due to Wave Climate: Storms to Decades

Gallop¹,

Harley

Brander

et al. 2017

Oceanog.

View full text Add to dashboard Cite

Shoreline variability from days to decades: Results of long‐term video imaging

Cited by 88 publications

References 27 publications

Developing Superfine Water Index (SWI) for Global Water Cover Mapping Using MODIS Data

Developing Superfine Water Index (SWI) for Global Water Cover Mapping Using MODIS Data

Remote Sensing Is Changing Our View of the Coast: Insights from 40 Years of Monitoring at Narrabeen-Collaroy, Australia

Assessing Cross-Shore and Alongshore Variation in Beach Morphology Due to Wave Climate: Storms to Decades

Contact Info

Product

Resources

About