Detection of aeolian transport in coastal images

Abstract

A B S T R A C TOptical remote sensing provides a low cost method of documenting surface conditions over extended periods of time. Its utility in resolving large scale aeolian transport events is examined in this paper. To this end, over 1800 images taken over a three month period by a stationary camera in a coastal setting are classified as containing/ not containing aeolian transport using both a manual and automated approach. In both cases transport is inferred by the identification of aeolian streamers within a given image. With regards to the manual approach, images were visually examined by three users. There was good agreement between the different users with 77.8% of transport identifications being unanimous. Comparison of the user results with measured transport highlights that observations of transport in images coincide with increased particle counts. The particle counts indicate that transport is dominated by a series of discernible transport events. Transport is observed in images throughout the duration of these events. Manually processing the images is a laborious process. A method is presented which allows for the automated detection of images containing transport. The method utilises 2D-DFTs to exploit the linear appearance of streamers in images. Relative to the manual classifications which serve as ground truth, the method performs well in identifying images containing transport with values of precision, recall and F1 score ⩾ 0.85. address: i.a.williams@utwente.nl (I.A. Williams). Aeolian Research 35 (2018) 47-57 1875-9637/

Estimating Annual Onshore Aeolian Sand Supply from the Intertidal Beach Using an Aggregated-Scale Transport Formula

“…Hage et al [31] determined this threshold wind velocity as 8 m/s by using data from the same wind station (IJmuiden) and Argus images from Egmond Beach for the period October 2011 and March 2012. A similar value is proposed by Williams et al [32] for the occurrence of transport in the Sand Motor [51]. If U Threshold = 8 m/s is assumed, the observed occurrence of onshore transport rise to 52% of the cases in which the mean wind speed is equal or above of the new threshold (8 m/s).…”

“…Originally, video imagery systems, such as Argus, were developed to study the morphology and the hydrodynamics of the nearshore zone. However during the last years video imagery systems have been used not only for hydrodynamics studies [27][28][29], but also to analyse the aeolian activity at the coast [5,[30][31][32]. In this study, Argus images ( Figure 2) were utilized to visually determine when aeolian sand transport occurred, on a basis of 8 h per day, between 8:00 and 16:00 h.…”

Long-term video monitoring of aeolian activity on a narrow beach

“…The original purpose of Argus was to study nearshore phenomena (Holman and Stanley, 2007), but it has been used here to study the intertidal and upper (dry) beach, offering potential for further development in the field of coastal aeolian research. Other aeolian studies based on video monitoring include Delgado-Fernandez and Davidson-Arnott (2011), Montreuil et al (2018), and Williams et al (2018). Chapter 2 particularly focussed on sand strips, but video monitoring does not have to be limited to these bedforms.…”

“…This was done by combining the imagery with data from in situ measurements. Williams et al (2018) also combined coastal imagery with in-situ data. Here, they used Argus images taken at the Sand Motor, the Netherlands, to automatically find and classify aeolian streamers.…”

“…Video monitoring has been used to observe sand strips, protodunes, and streamers (Delgado-Fernandez, 2010; Guimarães et al, 2016;Williams et al, 2018;Montreuil et al, 2018). Delgado-Fernandez (2010) observed that the moments with the strongest wind were not necessary the moments with the highest visual signs of transport and volumes of transported sand; out of the 9 days with strong winds, only one day resulted in high transport rates and strong visual transport signs.…”