Marine litter predictive mapping
This pilot project develops a shoreline map to define coastal areas with different likelihood of accumulating beach litter.
A novel GIS-based tool for predicting coastal litter accumulation and optimising coastal cleanup actions
Effective site selection is a key component of maximising debris removal
during coastal cleanup actions. We tested a GIS-based predictive model
to identify marine litter hotspots in Lofoten, Norway based on shoreline
gradient and shape. Litter density was recorded at 27 randomly selected
locations with 5 transects sampled in each. Shoreline gradient was a
limiting factor to litter accumulation when >35%. The curvature of
the coastline correlated differently with litter density at different
spatial scales. The greatest litter concentrations were in small coves
located on larger headlands. A parsimonious model scoring sites on a
scale of 1–5 based on shoreline slope and shape had the highest
validation success. Sites unlikely to have high litter concentrations
were successfully identified and could be avoided. The accuracy of
hotspot identifications was more variable, and presumably more
parameters influencing litter deposition, such as shoreline aspect
relative to prevailing winds, should be incorporated.
Status: Completed
Type: Staff Publications
Year of publication: 2018
Publisher: Marine Pollution Bulletin
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