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Andriolo U, Gonçalves G, Hidaka M, Gonçalves D, Gonçalves LM, Bessa F, Kako S. Marine litter weight estimation from UAV imagery: Three potential methodologies to advance macrolitter reports. Mar Pollut Bull 2024; 202:116405. [PMID: 38663345 DOI: 10.1016/j.marpolbul.2024.116405] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/05/2024] [Revised: 04/15/2024] [Accepted: 04/19/2024] [Indexed: 05/08/2024]
Abstract
In the context of marine litter monitoring, reporting the weight of beached litter can contribute to a better understanding of pollution sources and support clean-up activities. However, the litter scaling task requires considerable effort and specific equipment. This experimental study proposes and evaluates three methods to estimate beached litter weight from aerial images, employing different levels of litter categorization. The most promising approach (accuracy of 80 %) combined the outcomes of manual image screening with a generalized litter mean weight (14 g) derived from studies in the literature. Although the other two methods returned values of the same magnitude as the ground-truth, they were found less feasible for the aim. This study represents the first attempt to assess marine litter weight using remote sensing technology. Considering the exploratory nature of this study, further research is needed to enhance the reliability and robustness of the methods.
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Affiliation(s)
- Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290 Coimbra, Portugal.
| | - Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290 Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal.
| | - Mitsuko Hidaka
- Research Institute for Value-Added-Information Generation (VAiG), Japan Agency for Marine - Earth Science and Technology (JAMSTEC), Yokohama, Japan; Graduate School of Science and Engineering, Department of Engineering, Ocean Civil Engineering Program, Kagoshima University, Kagoshima, Japan.
| | - Diogo Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290 Coimbra, Portugal; University of Coimbra, Department of Civil Engineering, Coimbra, Portugal.
| | - Luisa Maria Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290 Coimbra, Portugal; School of Technology and Management, Polytechnic of Leiria, Nova IMS University Lisbon, Portugal.
| | - Filipa Bessa
- Centre for Functional Ecology - Science for People & the Planet (CFE), Associate Laboratory TERRA, Department of Life Sciences, University of Coimbra, Portugal.
| | - Shin'ichiro Kako
- Research Institute for Value-Added-Information Generation (VAiG), Japan Agency for Marine - Earth Science and Technology (JAMSTEC), Yokohama, Japan; Graduate School of Science and Engineering, Department of Engineering, Ocean Civil Engineering Program, Kagoshima University, Kagoshima, Japan.
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2
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Andriolo U, Topouzelis K, van Emmerik THM, Papakonstantinou A, Monteiro JG, Isobe A, Hidaka M, Kako S, Kataoka T, Gonçalves G. Drones for litter monitoring on coasts and rivers: suitable flight altitude and image resolution. Mar Pollut Bull 2023; 195:115521. [PMID: 37714078 DOI: 10.1016/j.marpolbul.2023.115521] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Revised: 08/29/2023] [Accepted: 09/05/2023] [Indexed: 09/17/2023]
Abstract
Multirotor drones can be efficiently used to monitor macro-litter in coastal and riverine environments. Litter on beaches, dunes and riverbanks, along with floating litter on coastal and river waters, can be spotted and mapped from aerial drone images. Items detection and classification are prone to image resolution, which is expressed in terms of Ground Sampling Distance (GSD). The GSD is determined by drone flight altitude and camera properties. This paper investigates what is a suitable GSD value for litter survey. Drone flight altitude and camera setup should be chosen to obtain a GSD between 0.5 cm/px and 1.25 cm/px. Within this range, the lowest GSD allows litter categorization and classification, whereas the highest value should be adopted for a coarser litter census. In the vision of drawing up a global protocol for drone-based litter surveys, this work sets the ground for homogenizing data collection and litter assessments.
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Affiliation(s)
- Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal.
| | | | - Tim H M van Emmerik
- Hydrology and Environmental Hydraulics Group, Wageningen University, Wageningen, the Netherlands.
| | | | - João Gama Monteiro
- MARE - Marine and Environmental Sciences Centre/ARNET - Aquatic Research Network, Agência Regional para o Desenvolvimento da Investigação Tecnologia e Inovação (ARDITI), Funchal, Madeira, Portugal; Faculty of Life Sciences, Universidade da Madeira, Funchal, Madeira, Portugal.
| | - Atsuhiko Isobe
- Research Institute for Applied Mechanics, Kyushu University, Kasuga, Japan.
| | - Mitsuko Hidaka
- Research Institute for Value-Added-Information Generation (VAiG), Japan Agency for Marine - Earth Science and Technology (JAMSTEC), Yokohama, Japan; Graduate School of Science and Engineering, Department of Engineering, Ocean Civil Engineering Program, Kagoshima University, Kagoshima, Japan.
| | - Shin'ichiro Kako
- Graduate School of Science and Engineering, Department of Engineering, Ocean Civil Engineering Program, Kagoshima University, Kagoshima, Japan.
| | - Tomoya Kataoka
- Department of Civil and Environmental Engineering, Graduate School of Science and Engineering, Ehime University, Matsuyama, Japan.
| | - Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal.
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3
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Andriolo U, Gonçalves G. The octopus pot on the North Atlantic Iberian coast: A plague of plastic on beaches and dunes. Mar Pollut Bull 2023; 192:115099. [PMID: 37267867 DOI: 10.1016/j.marpolbul.2023.115099] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/06/2023] [Revised: 05/22/2023] [Accepted: 05/23/2023] [Indexed: 06/04/2023]
Abstract
This baseline focuses on the octopus pot, a litter item found on the North Atlantic Iberian coast. Octopus pots are deployed from vessels in ropes, with several hundred units, and placed on the seabed, to capture mostly Octopus Vulgaris. The loss of gears due to extreme seas state, bad weather and/or fishing-related unforeseen circumstances, cause the octopus pots contaminating beaches and dunes, where they are transported by sea current, waves and wind actions. This work i) gives an overview of the use of octopus pot on fisheries, ii) analyses the spatial distribution of this item on the coast, and iii) discusses the potential measures for tackling the octopus pot plague on the North Atlantic Iberian coast. Overall, it is urgent to promote conducive policies and strategies for a sustainable waste management of octopus pots, based on Reduce, Reuse and Recycle hierarchical framework.
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Affiliation(s)
- Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290 Coimbra, Portugal.
| | - Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290 Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal.
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4
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Andriolo U, Gonçalves G. Impacts of a massive beach music festival on a coastal ecosystem - A showcase in Portugal. Sci Total Environ 2023; 861:160733. [PMID: 36481146 DOI: 10.1016/j.scitotenv.2022.160733] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Revised: 11/29/2022] [Accepted: 12/02/2022] [Indexed: 06/17/2023]
Abstract
Beach music festivals are numerous and popular worldwide. The concerns about the environmental sustainability of these events have been increasing among scientists, coastal managers and local communities. Nevertheless, the negative effects of beach music festivals on the coastal environment have been poorly studied. This work identified, analysed and discussed the eco-geomorphological impacts of a massive beach music festival held on a Portuguese beach-dune system over three days in July 2022. Drone-based orthophotos and pictures collected in the field were analysed to evaluate the impact of pre- and post-festival works, which turned the beach into a construction site over about twenty days. Digital Surface Model (DSM) analysis showed that beach configuration was approximately restored to the pre-festival configuration after the event. In contrast, the comparison of Normalized Difference Vegetation Index (NDVI) maps revealed that 18,500 m2 of embryonic dune vegetation, which represented 35 % of the existing plant community, was removed by works on the beach and by trampling of festival attendees. To authors' knowledge, this is the first work that evaluates the eco-geomorphological impact of a massive beach music festival on the delicate coastal ecosystem. Overall, it contributes in raising awareness for making these events more respectful of the coastal environment.
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Affiliation(s)
- Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal.
| | - Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal.
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5
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Gonçalves G, Andriolo U, Gonçalves LMS, Sobral P, Bessa F. Beach litter survey by drones: Mini-review and discussion of a potential standardization. Environ Pollut 2022; 315:120370. [PMID: 36216177 DOI: 10.1016/j.envpol.2022.120370] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/21/2022] [Revised: 09/23/2022] [Accepted: 10/03/2022] [Indexed: 06/16/2023]
Abstract
The abundance of beach litter has been increasing globally during the last decades, and it is an issue of global concern. A new survey strategy, based on uncrewed aerial vehicles (UAV, aka drones), has been recently adopted to improve the monitoring of beach macro-litter items abundance and distribution. This work identified and analysed the 15 studies that used drone for beach litter surveys on an operational basis. The analysis of technical parameters for drone flight deployment revealed that flight altitude varied between 5 and 40 m. The analysis of final assessments showed that, through manual and/or automated items detection on images, most of studies provided litter bulk characteristics (type, material and size), along with litter distribution maps. The potential standardization of drone-based litter survey would allow a comparison among surveys, however it seems difficult to propose a standard set of flight parameters, given the wide variety of coastal environments, the different devices available, and the diverse objectives of drone-based litter surveys. On the other hand, in our view, a set of common outcomes can be proposed, based on the grid mapping process, which can be easily generated following the procedure indicated in the paper. This work sets the ground for the development of a standardized protocol for drone litter data collection, analysis and assessments. This would allow the provision of broad scale comparative studies to support coastal management at both national and international scales.
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Affiliation(s)
- Gil Gonçalves
- University of Coimbra, Department of Mathematics, Coimbra, Portugal; INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290, Coimbra, Portugal.
| | - Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290, Coimbra, Portugal.
| | - Luísa M S Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290, Coimbra, Portugal; School of Technology and Management, Polytechnic of Leiria, Nova IMS University Lisbon, Portugal.
| | - Paula Sobral
- MARE- Marine and Environmental Sciences Centre, NOVA School of Science and Technology, NOVA University Lisbon, Portugal.
| | - Filipa Bessa
- University of Coimbra, MARE - Marine and Environmental Sciences Centre, ARNET - Aquatic Research Network, Department of Life Sciences, Calçada Martim de Freitas, 3000-456, Coimbra, Portugal.
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6
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Gonçalves G, Andriolo U. Operational use of multispectral images for macro-litter mapping and categorization by Unmanned Aerial Vehicle. Mar Pollut Bull 2022; 176:113431. [PMID: 35158175 DOI: 10.1016/j.marpolbul.2022.113431] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2021] [Revised: 02/01/2022] [Accepted: 02/03/2022] [Indexed: 06/14/2023]
Abstract
The use of Unmanned Aerial Systems (UAS, aka drones) has shown to be feasible to perform marine litter surveys. We operationally tested the use of multispectral images (5 bands) to classify litter type and material on a beach-dune system. For litter categorization by their multispectral characteristics, the Spectral Angle Mapping (SAM) technique was adopted. The SAM-based categorization of litter agreed with the visual classification, thus multispectral images can be used to fasten and/or making more robust the manual RGB image screening. Fully automated detection returned an F-score of 0.64, and a reasonable categorization of litter. Overall, the image-based litter density maps were in line with the manual detection. Assessments were promising given the complexity of the study area, where different dunes plants and partially-buried items challenged the UAS-based litter detection. The method can be easily implemented for both floating and beached litter, to advance litter survey in the environment.
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Affiliation(s)
- Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290 Coimbra, Portugal; University of Coimbra, Department of Mathematics, Apartado 3008 EC Santa Cruz, 3001 - 501 Coimbra, Portugal
| | - Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030 - 290 Coimbra, Portugal.
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Andriolo U, Gonçalves G. Is coastal erosion a source of marine litter pollution? Evidence of coastal dunes being a reservoir of plastics. Mar Pollut Bull 2022; 174:113307. [PMID: 35090292 DOI: 10.1016/j.marpolbul.2021.113307] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/23/2021] [Revised: 12/14/2021] [Accepted: 12/28/2021] [Indexed: 05/27/2023]
Abstract
This baseline reports scientific evidence of marine litter items embedded in the dune volume at two study sites on the North Atlantic Portuguese coast. We described how stranded litter participate in the sand dune growth/erosion processes on a natural beach-dune system. From the storm-eroded foredunes on the urbanized beach, we documented exhumed plastics with age up to 38 years. Whether litter burial was due to beach-dune morphodynamic processes, or to irresponsible and/or illegal dumping in the past, this work emphasises the need of improving buried litter census and monitoring on coastal dunes. Coastal erosion processes may further exhume litter buried in dune volumes and on other coastal environments over short- and long-term, re-exposing items into the marine environment. Thus, coastal erosion can be accounted as a secondary diffuse source of littering pollution, beside the multiple sources already identified in the environment.
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Affiliation(s)
- Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal.
| | - Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal; University of Coimbra, Department of Mathematics, Apartado 3008, EC Santa Cruz, 3001 - 501 Coimbra, Portugal.
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8
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Andriolo U, Gonçalves G, Rangel-Buitrago N, Paterni M, Bessa F, Gonçalves LMS, Sobral P, Bini M, Duarte D, Fontán-Bouzas Á, Gonçalves D, Kataoka T, Luppichini M, Pinto L, Topouzelis K, Vélez-Mendoza A, Merlino S. Drones for litter mapping: An inter-operator concordance test in marking beached items on aerial images. Mar Pollut Bull 2021; 169:112542. [PMID: 34052588 DOI: 10.1016/j.marpolbul.2021.112542] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/27/2021] [Revised: 05/13/2021] [Accepted: 05/19/2021] [Indexed: 06/12/2023]
Abstract
Unmanned aerial systems (UAS, aka drones) are being used to map macro-litter on the environment. Sixteen qualified researchers (operators), with different expertise and nationalities, were invited to identify, mark and categorize the litter items (manual image screening, MS) on three UAS images collected at two beaches. The coefficient of concordance (W) among operators varied between 0.5 and 0.7, depending on the litter parameter (type, material and colour) considered. Highest agreement was obtained for the type of items marked on the highest resolution image, among experts in litter surveys (W = 0.86), and within territorial subgroups (W = 0.85). Therefore, for a detailed categorization of litter on the environment, the MS should be performed by experienced and local operators, familiar with the most common type of litter present in the target area. This work provides insights for future operational improvements and optimizations of UAS-based images analysis to survey environmental pollution.
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Affiliation(s)
- Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal.
| | - Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal.
| | - Nelson Rangel-Buitrago
- Programa de Física, Facultad de Ciencias Básicas, Universidad del Atlántico, Barranquilla, Atlántico, Colombia; Programa de Biología, Facultad de Ciencias Básicas, Universidad del Atlántico, Barranquilla, Atlántico, Colombia.
| | - Marco Paterni
- CNR-National Research Council, Institute of Clinical Physiology, Italy.
| | - Filipa Bessa
- University of Coimbra, MARE - Marine and Environmental Sciences Center, Department of Life Sciences, Calçada Martim de Freitas, 3000-456 Coimbra, Portugal.
| | - Luisa M S Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal; School of Technology and Management, Polytechnic of Leiria, Nova IMS University Lisbon, Portugal.
| | - Paula Sobral
- MARE- Marine and Environmental Sciences Centre, NOVA School of Science and Technology, NOVA University Lisbon, Portugal.
| | - Monica Bini
- Department of Earth Sciences, University of Pisa, Via S. Maria, 53, 56126 Pisa, Italy; Istituto Nazionale di Geofisica e Vulcanologia (INGV), Sez. Pisa, via Cesare Battisti 53, Pisa 56125, Italy.
| | - Diogo Duarte
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal.
| | - Ángela Fontán-Bouzas
- Centro de Investigación Mariña, University of Vigo, GEOMA, Campus de Santiago, 36310 Vigo, Spain; Physics Department & CESAM, Universidade de Aveiro, Campus de Santiago, 3810-193 Aveiro, Portugal.
| | - Diogo Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Polo 2, 3030-290 Coimbra, Portugal; Department of Civil Engineering, University of Coimbra, Rua Luís Reis Santos - Pólo II, 3030-788 Coimbra, Portugal.
| | - Tomoya Kataoka
- Department of Civil & Environmental Engineering, Ehime University, 3 Bunkyo-cho, Matsuyama 790-8577, Japan.
| | - Marco Luppichini
- Department of Earth Sciences, University of Pisa, Via S. Maria, 53, 56126 Pisa, Italy; Department of Earth Sciences, University of Florence, Via La Pira 4, 50121 Florence, Italy.
| | - Luis Pinto
- University of Coimbra, CMUC, Department of Mathematics, Coimbra, Portugal.
| | | | - Anubis Vélez-Mendoza
- Programa de Biología, Facultad de Ciencias Básicas, Universidad del Atlántico, Barranquilla, Atlántico, Colombia.
| | - Silvia Merlino
- CNR-National Research Council, Institute of Marine Science ISMAR-CNR, 19032 Lerici, SP, Italy.
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9
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Andriolo U, Gonçalves G, Sobral P, Bessa F. Spatial and size distribution of macro-litter on coastal dunes from drone images: A case study on the Atlantic coast. Mar Pollut Bull 2021; 169:112490. [PMID: 34022556 DOI: 10.1016/j.marpolbul.2021.112490] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/15/2020] [Revised: 05/03/2021] [Accepted: 05/12/2021] [Indexed: 06/12/2023]
Abstract
This work analyses the cross-shore (80 m) and long-shore (200 m) spatial and size distribution of macro-litter on coastal dunes, employing a mapping framework based on an Unmanned Aerial System (UAS, aka drone) and a GIS mobile application. Over the cross-shore, plastic percentage increased from 60% to 90% landwards. The largest items (processed wood) were found on the embryo dune. Plastic bottles and paper napkins were trapped by the foredune grass, while the largest fishing-related items were intercepted by the low scrub plant community on the backdune. Over the long-shore, plastic percentage and items size increased from the urbanized area towards the natural dunes. This work assessed the abundance of marine litter on coastal dune sectors, underlining the role of distinct vegetation types in trapping items of different size. The mapping framework can promote further marine litter monitoring programs and support specific strategies for protecting the dune ecosystems.
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Affiliation(s)
- Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal.
| | - Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal.
| | - Paula Sobral
- MARE - Marine and Environmental Sciences Centre, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Campus da Caparica, 2829-516 Caparica, Portugal.
| | - Filipa Bessa
- MARE - Marine and Environmental Sciences Centre, C/o Department of Life Sciences, Faculty of Sciences and Technology, University of Coimbra, Coimbra, Portugal.
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10
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Pinto L, Andriolo U, Gonçalves G. Detecting stranded macro-litter categories on drone orthophoto by a multi-class Neural Network. Mar Pollut Bull 2021; 169:112594. [PMID: 34118575 DOI: 10.1016/j.marpolbul.2021.112594] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/18/2020] [Revised: 05/19/2021] [Accepted: 05/31/2021] [Indexed: 06/12/2023]
Abstract
The use of Unmanned Aerial Systems (UAS, aka drones) images for mapping macro-litter in the environment have been exponentially increasing in the recent years. In this work, we developed a multi-class Neural Network (NN) to automatically identify stranded plastic litter categories on an UAS-derived orthophoto. The best results were assessed for items that did not have substantial intra-class colour variability, such as octopus pots and fishing ropes (F-score = 61%, on average). Instead, performance was poor (37%) for plastic bottles and fragments, due to their changing intra-class colours. On average, the performance improved 24% when the binary detection (litter/non-litter, F-Score = 73%) was considered, however this approach did not discriminate the litter categories. This work gives a new perspective for the automated litter detection on drone images, suggesting that colour-based approach can be used to improve the categorization of stranded litter on UAS orthophoto.
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Affiliation(s)
- Luis Pinto
- University of Coimbra, CMUC, Department of Mathematics, Coimbra, Portugal.
| | - Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal.
| | - Gil Gonçalves
- INESC Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal.
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11
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Andriolo U, Gonçalves G, Sobral P, Fontán-Bouzas Á, Bessa F. Beach-dune morphodynamics and marine macro-litter abundance: An integrated approach with Unmanned Aerial System. Sci Total Environ 2020; 749:141474. [PMID: 32846347 DOI: 10.1016/j.scitotenv.2020.141474] [Citation(s) in RCA: 31] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/26/2020] [Revised: 07/30/2020] [Accepted: 08/02/2020] [Indexed: 06/11/2023]
Abstract
This work shows an integrated approach for coastal environmental monitoring, which aimed to understand the relation between beach-dune morphodynamics, marine litter abundance and environmental forcing. Three unmanned aerial system (UAS) flights were deployed on a beach-dune system at the Atlantic Portuguese coast to assess two main goals: (i) quantifying the morphological changes that occurred among flights, with focus on dune erosion, and (ii) mapping the changes of marine macro-litter abundance on the shore. Two most vulnerable-to-erosion sectors of the beach were identified. In the northern sector, the groin affected the downdrift shoreline, with dune erosion of about 1 m. In the central part of the beach, the dunes recessed about 4 m during the winter, being more exposed to environmental forcing due to the absence of dune vegetation. Marine litter occupation area on the beach decreased from 25% to 20% over the winter, with octopus pots (13%) and fragments (69%) being the most abundant items on average. Litter distribution varied in relation to swash elevation, wind speed and direction. With low swash elevation, the wind played a predominant role in moving the stranded items northwards, whereas high swash elevation concentrated the items at the dune foot. This study emphasizes the potential of UAS in allowing an integrated approach for coastal erosion monitoring and marine litter mapping, and set the ground for marine litter dynamic modelling on the shore.
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Affiliation(s)
- Umberto Andriolo
- INESC-Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal.
| | - Gil Gonçalves
- INESC-Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal; University of Coimbra, Department of Mathematics, Coimbra, Portugal.
| | - Paula Sobral
- MARE - Marine and Environmental Sciences Centre, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Campus da Caparica, 2829-516 Caparica, Portugal.
| | - Ángela Fontán-Bouzas
- Centro de Investigación Mariña, University of Vigo, GEOMA, Campus de Vigo, As Lagoas, Marcosende, 36310 Vigo, Spain; Physics Department & Centre of Environmental and Marine Studies, University of Aveiro, Portugal.
| | - Filipa Bessa
- University of Coimbra, MARE - Marine and Environmental Sciences Centre, Department of Life Sciences, 3000-456 Coimbra, Portugal.
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12
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Andriolo U, Gonçalves G, Bessa F, Sobral P. Mapping marine litter on coastal dunes with unmanned aerial systems: A showcase on the Atlantic Coast. Sci Total Environ 2020; 736:139632. [PMID: 32485384 DOI: 10.1016/j.scitotenv.2020.139632] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2020] [Revised: 05/19/2020] [Accepted: 05/20/2020] [Indexed: 06/11/2023]
Abstract
Marine litter pollution on coastal dunes has received limited scientific attention when compared with sandy shores. This paper proposes a new framework based on the combined use of Unmanned Aerial Systems (UAS) and a mobile application to map and quantify marine macro-litter (>2.5 cm) accumulation on coastal dunes. The first application on a dune area of 200 m × 80 m at the north-east Atlantic Portuguese coast is shown. Nine different marine litter categories were found, with styrofoam fragments (23% of the total amount) and plastic bottles (20%) being the most abundant items. Plastic was the most common material (76%). The highest number of items (272) was found on the backdune, mostly related with fishing activities (octopus pots and Styrofoam fragments). In contrast, the highest density (0.031 items/m2) was found on the foredune, with the most abundant items associated with human recreational activities (for example, plastic bottles, bags, papers and napkins). Three major marine litter hotspots (~0.1 items/m2) were identified in correspondence of dune blowouts. The recognition of the primary marine litter pathways highlighted the main role that wind and overwash events play on dune contamination, and suggests that the dune ridge restoration can act as a mitigation measure for preventing marine litter accumulation on the backdune. This study shows how UAS offer the possibility of a detailed non-intrusive survey, and gives a new impulse to coastal dune litter monitoring, where the long residence time of marine debris may threaten the bio-ecological equilibrium of these ecosystems.
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Affiliation(s)
- Umberto Andriolo
- INESC-Coimbra, Department of Electrical and Computer Engineering, 3030-290 Coimbra, Portugal.
| | - Gil Gonçalves
- INESC-Coimbra, Department of Electrical and Computer Engineering, 3030-290 Coimbra, Portugal; University of Coimbra, Department of Mathematics, 3001-501 Coimbra, Portugal.
| | - Filipa Bessa
- University of Coimbra, MARE - Marine and Environmental Sciences Centre, Department of Life Sciences, 3000-456 Coimbra. Portugal.
| | - Paula Sobral
- MARE - Marine and Environmental Sciences Centre, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Campus da Caparica, 2829-516 Caparica, Portugal.
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Gonçalves G, Andriolo U, Pinto L, Duarte D. Mapping marine litter with Unmanned Aerial Systems: A showcase comparison among manual image screening and machine learning techniques. Mar Pollut Bull 2020; 155:111158. [PMID: 32310099 DOI: 10.1016/j.marpolbul.2020.111158] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 04/06/2020] [Accepted: 04/06/2020] [Indexed: 06/11/2023]
Abstract
Recent works have shown the feasibility of Unmanned Aerial Systems (UAS) for monitoring marine pollution. We provide a comparison among techniques to detect and map marine litter objects on an UAS-derived orthophoto of a sandy beach-dune system. Manual image screening technique allowed a detailed description of marine litter categories. Random forest classifier returned the best-automated detection rate (F-score 70%), while convolutional neural network performed slightly worse (F-score 60%) due to a higher number of false positive detections. We show that automatic methods allow faster and more frequent surveys, while still providing a reliable density map of the marine litter load. Image manual screening should be preferred when the characterization of marine litter type and material is required. Our analysis suggests that the use of UAS-derived orthophoto is appropriate to obtain a detailed geolocation of marine litter items, requires much less human effort and allows a wider area coverage.
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Affiliation(s)
- Gil Gonçalves
- University of Coimbra, Department of Mathematics, Faculty of Sciences and Technology, Coimbra, Portugal; INESC Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal.
| | - Umberto Andriolo
- INESC Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal.
| | - Luís Pinto
- University of Coimbra, CMUC, Department of Mathematics, Faculty of Sciences and Technology, Coimbra, Portugal.
| | - Diogo Duarte
- INESC Coimbra, Department of Electrical and Computer Engineering, Coimbra, Portugal.
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Gonçalves G, Andriolo U, Pinto L, Bessa F. Mapping marine litter using UAS on a beach-dune system: a multidisciplinary approach. Sci Total Environ 2020; 706:135742. [PMID: 31791786 DOI: 10.1016/j.scitotenv.2019.135742] [Citation(s) in RCA: 55] [Impact Index Per Article: 13.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/30/2019] [Revised: 11/22/2019] [Accepted: 11/23/2019] [Indexed: 06/10/2023]
Abstract
The amount of marine litter, mainly composed by plastic materials, has become a global environmental issue in coastal environments. Traditional monitoring programs are based on in-situ visual census, which require human effort and are time-demanding. Therefore, it is crucial to implement innovative mapping strategies to improve the environmental monitoring of marine litter on the coast. This work presents a procedure for an automated Unmanned Aerial System (UAS)-based marine litter mapping on a beach-dune system. A multidisciplinary framework, which comprises photogrammetry, geomorphology, machine learning and hydrodynamic modelling, was developed to process a block of UAS images. The work shows how each of these scientific methodologies can be complementary to improve and making more efficient the mapping of marine litter items with UAS on coastal environment. The very high-resolution orthophoto produced from UAS images was automatically screened by random forest machine learning method, in order to characterize the marine litter load on beach and dune areas, distinctively. The marine litter objects were identified with a F-test score of 75% when compared to manual procedure. The location of major marine litter loads within the monitored area was found related to beach slope and water level dynamics on the beach profiles, suggesting that UAS flight deployment and post-processing for beach litter mapping can be optimized based on these environmental parameters. The described UAS-based marine litter detection framework is intended to support scientists, engineers and decision makers aiming at monitoring marine and coastal pollution, with the additional aim of optimizing and automating beach clean-up operations.
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Affiliation(s)
- Gil Gonçalves
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), University of Coimbra, Coimbra, Portugal; Department of Mathematics, University of Coimbra, Coimbra, Portugal.
| | - Umberto Andriolo
- Institute for Systems Engineering and Computers at Coimbra (INESC Coimbra), University of Coimbra, Coimbra, Portugal.
| | - Luís Pinto
- CMUC, Department of Mathematics, University of Coimbra, Coimbra, Portugal.
| | - Filipa Bessa
- MARE - Marine and Environmental Sciences Centre, Department of Life Sciences, Faculty of Science and Technology, University of Coimbra, Coimbra, Portugal
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