Shoreline change mapping using crowd-sourced smartphone images

Harley, Mitchell D.; Kinsela, Michael A.; Sánchez-García, Elena; Vos, Kilian

doi:10.1016/j.coastaleng.2019.04.003

Cited by 115 publications

(100 citation statements)

References 42 publications

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“…A variety of data sources are available to observe the variation of the coastline. Potential data sources for coastline investigation include historical photographs, coastal maps and charts, aerial photography, beach surveys, in situ geographic positioning system shorelines, and a range of digital elevation or image data derived from remote sensing platforms (Boak & Turner, 2005;Holman & Haller, 2013;Harley et al, 2019). High and very high resolution satellite images and the related feature extraction techniques have proven to be particularly suitable for these applications (Teodoro, 2016).…”

Section: Introductionmentioning

confidence: 99%

Using Optical Satellite and Aerial Imagery for Automatic Coastline Mapping

Costantino¹,

Pepe²,

Dardanelli³

et al. 2020

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The continuous availability and rapid accessibility to multispectral data from satellite platforms within the Copernicus Programme represents a great opportunity for users in different fields of applications as: agriculture, observation of coastal zones, monitoring land cover change. The aim of this paper is to identify a suitable method to map coastline using Sentinel-2 optical satellite image. The method provides the use of two indexes developed in remote sensing field for water environment: NDWI (Normalized difference water index) and MNDWI (Modified Normalized difference water index). Starting from the construction of maps of these indexes and, identifying appropriate threshold values, it has been possible to extrapolate the coastline. The coastlines derived from the use of the NDWI and MNDWI index were compared with a coastline obtained from the photointerpretation of a very high resolution orthophoto obtained through photogrammetric techniques. The results show that it is possible to map the coastline automatically and quickly with an intrinsic accuracy close to the geometric resolution bands of Sentinel-2 satellite images.

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Section: Introductionmentioning

confidence: 99%

Using Optical Satellite and Aerial Imagery for Automatic Coastline Mapping

Costantino¹,

Pepe²,

Dardanelli³

et al. 2020

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“…It is worth mentioning that, since the ratio L Hs /24 can be used to approximate the local water depth at breaking, the possibility of using such relation for a rough estimation of beach profile under breaking conditions from Timex images could also be explored. As final suggestion, further work may investigate the potential of the method being applied to snapshots [52], to UAS images (e.g., [53][54][55]) and/or to surfcam images [14,56,57] for a quasi-real time estimation of breaking wave height.…”

Section: Methods 2: Hs Bv24mentioning

confidence: 99%

Breaking Wave Height Estimation from Timex Images: Two Methods for Coastal Video Monitoring Systems

2020

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The breaking wave height is a crucial parameter for coastal studies but direct measurements constitute a difficult task due to logistical and technical constraints. This paper presents two new practical methods for estimating the breaking wave height from digital images collected by shore-based video monitoring systems. Both methods use time-exposure (Timex) images and exploit the cross-shore length ( L H s ) of the typical time-averaged signature of breaking wave foam. The first method ( H s b , v ) combines L H s and a series of video-derived parameters with the beach profile elevation to obtain the breaking wave height through an empirical formulation. The second method ( H s b , v 24 ) is based on the empirical finding that L H s can be associated with the local water depth at breaking, thus it can be used to estimate the breaking wave height without the requirement of local bathymetry. Both methods were applied and verified against field data collected at the Portuguese Atlantic coast over two days using video acquired by an online-streaming surfcam. Furthermore, H s b , v 24 was applied on coastal images acquired at four additional field sites during distinct hydrodynamic conditions, and the results were compared to a series of different wave sources. Achievements suggest that H s b , v method represents a good alternative to numerical hydrodynamic modeling when local bathymetry is available. In fact, the differences against modeled breaking wave height, ranging from 1 to 3 m at the case study, returned a root-mean-square-error of 0.2 m. The H s b , v 24 method, when applied on video data collected at five sites, assessed a normalized root-mean-square-error of 18% on average, for dataset of about 900 records and breaking wave height ranging between 0.1 and 3.8 m. These differences demonstrate the potential of H s b , v 24 in estimating breaking wave height merely using Timex images, with the main advantage of not requiring the beach profile. Both methods can be easily implemented as cost-effective tools for hydrodynamic applications in the operational coastal video systems worldwide. In addition, the methods have the potential to be coupled to the numerous other Timex applications for morphodynamic studies.

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“…Following the outcomes reported by Bracs et al [91] whereby repurposed surfcams were shown to provide reasonable accuracy in shoreline detection provided suitable rectification and calibration was included, Harley et al [93] have recently reported on the novel application of smartphones to obtain routine monitoring images of beaches. These crowd-sourced photos are supplied by the community back to researchers and managers via the digital media platforms Instagram, Twitter and Facebook.…”

Section: Coastsnapmentioning

confidence: 98%

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

2018

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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.

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Shoreline change mapping using crowd-sourced smartphone images

Cited by 115 publications

References 42 publications

Using Optical Satellite and Aerial Imagery for Automatic Coastline Mapping

Using Optical Satellite and Aerial Imagery for Automatic Coastline Mapping

Breaking Wave Height Estimation from Timex Images: Two Methods for Coastal Video Monitoring Systems

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

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