Surveyance of the marine environment for beached plastic debris using a novel, hyperspectral shortwave infrared camera on an uncrewed aerial vehicle (UAV)
type: CreativeWork
description: Plastic waste has been rapidly accumulating in the natural environment for decades since the commercial introduction of plastic in the 1950s as a disposable material. Millions of tonnes of durable, persistent plastic waste now contaminate global ecosystems, including rivers, urban beaches, remote islands, the deep sea, soils, mountains, and very small pieces (microplastics) have even been detected in the air. Such pervasive plastic debris is a deadly and common threat to wildlife due to ingestion and entanglement. Large debris are particularly problematic not only because of these direct consequences, but because they break down into smaller pieces in the environment. These smaller pieces are more easily ingested by a greater diversity of species and are more difficult to remediate. It is therefore sensible to focus prevention, remediation, and monitoring efforts on large, more easily observable debris. In the past five years, monitoring efforts have increasingly included the investigation of automated plastic detection via remote sensing technologies and techniques. This approach has the potential to reduce observer bias (associated with manual, visual surveys), and realise regular and widespread plastic pollution monitoring, with the ultimate goal of achieving environmentally relevant reductions in plastic production and pollution. This thesis contributes to these aims by i) investigating the performance of novel remote sensing methods for plastic detection, ii) developing and implementing a new plastic detection algorithm, and iii) evaluating for the first time, the impact of operational and environmental variables on these specific plastic detection methods. A large proportion of plastic litter detection investigations have implemented inexpensive and common digital cameras that operate in the visible light spectrum. This approach is often limited in capability/reliability by inherent ambiguity, resulting from two-dimensional imagery of materials of unverifiable…
abstract: Plastic waste has been rapidly accumulating in the natural environment for decades since the commercial introduction of plastic in the 1950s as a disposable material. Millions of tonnes of durable, persistent plastic waste now contaminate global ecosystems, including rivers, urban beaches, remote islands, the deep sea, soils, mountains, and very small pieces (microplastics) have even been detected in the air. Such pervasive plastic debris is a deadly and common threat to wildlife due to ingestion and entanglement. Large debris are particularly problematic not only because of these direct consequences, but because they break down into smaller pieces in the environment. These smaller pieces are more easily ingested by a greater diversity of species and are more difficult to remediate. It is therefore sensible to focus prevention, remediation, and monitoring efforts on large, more easily observable debris. In the past five years, monitoring efforts have increasingly included the investigation of automated plastic detection via remote sensing technologies and techniques. This approach has the potential to reduce observer bias (associated with manual, visual surveys), and realise regular and widespread plastic pollution monitoring, with the ultimate goal of achieving environmentally relevant reductions in plastic production and pollution. This thesis contributes to these aims by i) investigating the performance of novel remote sensing methods for plastic detection, ii) developing and implementing a new plastic detection algorithm, and iii) evaluating for the first time, the impact of operational and environmental variables on these specific plastic detection methods. A large proportion of plastic litter detection investigations have implemented inexpensive and common digital cameras that operate in the visible light spectrum. This approach is often limited in capability/reliability by inherent ambiguity, resulting from two-dimensional imagery of materials of unverifiable…
author: Cocking, Jennifer Laura
language: eng
date published: 2023-5-9
date modified: 2026-07-24T05:12:10Z
provider: University of the Highlands and Islands
publisher: Networked Digital Library of Theses and Dissertations
type: WebPage
source organization: University of the Highlands and Islands