2018
DOI: 10.1016/j.aeolia.2017.08.006
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UAV-imaging to model growth response of marram grass to sand burial: Implications for coastal dune development

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Cited by 43 publications
(30 citation statements)
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“…In this experiment we used only a RGB sensor so vegetation metrics (e.g., normalised difference vegetation index (NDVI)) could not be determined. However, we suggest that including infra-red based vegetation index data such as NDVI could be used to further enhance the M3C2-PM analysis by separating vegetation from bare sand areas to improve identification of the more dynamic parts of the dune environment, as has been shown by Reference [36].…”
Section: Kap Surveysmentioning
confidence: 94%
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“…In this experiment we used only a RGB sensor so vegetation metrics (e.g., normalised difference vegetation index (NDVI)) could not be determined. However, we suggest that including infra-red based vegetation index data such as NDVI could be used to further enhance the M3C2-PM analysis by separating vegetation from bare sand areas to improve identification of the more dynamic parts of the dune environment, as has been shown by Reference [36].…”
Section: Kap Surveysmentioning
confidence: 94%
“…SfM-MVS has been used to study geomorphological features such as glacially sculpted ridges [17], estimate biomass in tropical forest environments [31] and create digital surface models of coastal dune environments [32]. Fine spatial resolution data (typically sub-centimetre) have been used to quantify the heterogeneity of seagrass meadows [33], conduct coastal vulnerability assessments [34], map mangroves [35] and quantify changes in vegetation within dune ecosystems [36,37]. Although these prior experiments have demonstrated the opportunities for this new approach to be adopted widely in coastal environments, drone operations specifically are not without their risks in these settings.…”
Section: Introductionmentioning
confidence: 99%
“…The latter condition is not disputed, as the reinforcing feedback between the 5 growth response of marram grass and burial by wind-blown sand is well documented (Huiskes, 1979;Disraeli, 1984;Maun and Lapierre, 1984;Van der Putten et al, 1988;Hesp, 1991;Maun, 1998) and recognized to be fundamental to coastal dune development in temperate regions around the world (e.g., Baas and Nield, 2010;Durán and Moore, 2013;Keijsers et al, 2016;Nolet et al, 2017). The positive feedback mechanism is thought to originate from a trait that all beach grasses of the genus Ammophila possess, namely potentially unlimited horizontal and vertical growth through its rhizomes (Gemmell et al, 1953;10 Ranwell, 1972).…”
Section: Boundary Conditions Indicating Favorable Accommodation Spacementioning
confidence: 99%
“…The capacity to trap sand, as noted before, is enhanced by the growth response of marram grass to trapping, which introduces the positive feedback mechanism driving coastal dune development (Gemmell 20 et al, 1953;Ranwell, 1972). Using very high-resolution data, Nolet et al (2017) showed that marram grass on foredunes along the Zandmotor thrives best under a sand trapping rate of approximately 0.3 meter of sand per growing season and that marram grass can withstand sand burial up to 1 meter of sand. However, while this demonstrates how positive plant-sand feedback steers dune development, it must be noted that the physical size of a developing dune also controls its morphology.…”
Section: Boundary Conditions Indicating Favorable Accommodation Spacementioning
confidence: 99%
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