A knowledge-based, validated classifier for the identification of aliphatic and aromatic plastics by WorldView-3 satellite data

Zhou, Shengjun; Kuester, Theres; Bochow, Mathias; Bohn, Niklas; Brell, Maximilian; Kaufmann, Hermann

doi:10.1016/j.rse.2021.112598

“…For plastic debris detection methods over water that use the increased brightness of a pixel containing floating matter to separate pixels of interest [26], this may not be a problem. However, for detecting plastic debris against terrestrial backgrounds where absorption features are used [45], this poses a challenge for accurately quantifying sub-pixel plastic cover. For future endeavours attempting to quantify the volume of debris within a pixel, these variations in absorption magnitude may produce under-estimations of debris.…”

Section: Discussionmentioning

confidence: 99%

“…Given that the data were collected on a beachfront in proximity to the ocean, this is likely due to increased moisture in the sand. Zhou et al [45] recently developed a knowledge-based classifier for plastic debris using Worldview-3 imagery. This classifier made use of the spectral features at 1660 nm, 1730 nm, 2165 and 2205 nm.…”

Section: Discussionmentioning

confidence: 99%

Quantifying Marine Plastic Debris in a Beach Environment Using Spectral Analysis

Guffogg

¹

,

Blades

²

,

Soto‐Berelov

³

et al. 2021

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Marine plastic debris (MPD) is a globally relevant environmental challenge, with an estimated 8 million tons of synthetic debris entering the marine environment each year. Plastic has been found in all parts of the marine environment, including the surface layers of the ocean, within the water column, in coastal waters, on the benthic layer and on beaches. While research on detecting MPD using remote sensing is increasing, most of it focuses on detecting floating debris in open waters, rather than detecting MPD on beaches. However, beaches present challenges that are unique from other parts of the marine environment. In order to better understand the spectral properties of beached MPD, we present the SWIR reflectance of weathered MPD and virgin plastics over a sandy substrate. We conducted spectral feature analysis on the different plastic groups to better understand the impact that polymers have on our ability to detect synthetic debris at sub-pixel surface covers that occur on beaches. Our results show that the minimum surface cover required to detect MPD on a sandy surface varies between 2–8% for different polymer types. Furthermore, plastic composition affects the magnitude of spectral absorption. This suggests that variation in both surface cover and polymer type will inform the efficacy of beach litter detection methods.

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“…Several papers have focused on detecting the greenhouses themselves, e.g. [35][36][37], while this paper also focuses on the plastic waste between the greenhouses and in abandoned areas.…”

Section: Almería Greenhouses Spainmentioning

confidence: 99%

Detection of Waste Plastics in the Environment: Application of Copernicus Earth Observation data

Lavender¹

2022

Preprint

0

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The detection of waste plastics in the marine and terrestrial environment using satellite Earth Observation data offers the possibility of large-scale mapping, and reducing on-the-ground manual investigation. In addition, costs are kept to a minimum by utilizing free-to-access Copernicus data. A Machine Learning based classifier was developed to run on Sentinel-1 and -2 data. In support of the training and validation, a dataset was created with terrestrial and aquatic cases by manually digitizing varying landcover classes alongside plastics under the sub-categories of greenhouses, plastic, tyres and waste sites. The trained classifier, including an Artificial Neural Network and post-processing decision tree, was verified using five locations encompassing these different forms of plastic. Although exact matchups are challenging to digitize, the performance has generated high accuracy statistics, and the resulting land cover classifications have been used to map the occurrence of plastic waste in aquatic and terrestrial environments.

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“…Polyethylene is preferred because of its affordability, flexibility, and ease of manufacturing [33], with the plastics being transparent or translucent with vegetation below. Several papers have focused on detecting the greenhouses themselves, e.g., [34][35][36], while this paper also focuses on the plastic waste between the greenhouses and in abandoned areas.…”

Section: Almería Greenhouses Spainmentioning

confidence: 99%

Detection of Waste Plastics in the Environment: Application of Copernicus Earth Observation data

Lavender¹

2022

Preprint

0

View full text Add to dashboard Cite

The detection of waste plastics in the marine and terrestrial environment using satellite Earth Observation data offers the possibility of large-scale mapping, and reducing on-the-ground manual investigation. In addition, costs are kept to a minimum by utilizing free-to-access Copernicus data. A Machine Learning based classifier was developed to run on Sentinel-1 and -2 data. In support of the training and validation, a dataset was created with terrestrial and aquatic cases by manually digitizing varying landcover classes alongside plastics under the sub-categories of greenhouses, plastic, tyres and waste sites. The trained classifier, including an Artificial Neural Network and post-processing decision tree, was verified using five locations encompassing these different forms of plastic. Although exact matchups are challenging to digitize, the performance has generated high accuracy statistics, and the resulting land cover classifications have been used to map the occurrence of plastic waste in aquatic and terrestrial environments.

show abstract

A knowledge-based, validated classifier for the identification of aliphatic and aromatic plastics by WorldView-3 satellite data

Cited by 20 publications

References 65 publications

Quantifying Marine Plastic Debris in a Beach Environment Using Spectral Analysis

Quantifying Marine Plastic Debris in a Beach Environment Using Spectral Analysis

Detection of Waste Plastics in the Environment: Application of Copernicus Earth Observation data

Detection of Waste Plastics in the Environment: Application of Copernicus Earth Observation data

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