Geoinformatics for Applied Coastal and Marine Management

Bartlett, Darius; Celliers, Louis

doi:10.1201/9781315181523-2

Cited by 4 publications

(10 citation statements)

References 10 publications

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“…23 It is the most important consideration for site selection. 13,24 Decision makers are naturally going to want to site their MRE farm where the resource is most plentiful. 25 Furthermore, TE calculations are not possible without some characterisation of the resource, which ultimately leads to the calculation of Annual Energy Production (AEP) -regarded as having the most significant impact on project feasibility analysis in offshore energy projects.…”

Section: Resource Assessmentmentioning

confidence: 99%

“…They can be physical, social, environmental, commercial or even martial in nature. 13 Examples include distance from market, geology, bathymetry, seabed slope and stability, seabed character, protected areas, shipping lanes, subsea cables, energy storage, grid connection requirements, extreme met-ocean conditions and visual impact. 3,[46][47][48][49] Resource focused GIS tools Some GIS tools focus on little other than the renewable energy resource itself.…”

Section: Gis: Approaches and Considerationsmentioning

confidence: 99%

“…Geographic Information Systems (GIS) has played a hugely influential role in the area of energy exploration in recent decades, particularly in the oil and gas industry, 11 but increasingly for renewable energy applications with the growing demand for clean energy. 12–14 It is the ability of a GIS to handle, process and analyse huge amounts of geospatial data that distinguish it from other information systems. Such functionality allows GIS to be used for integration of geospatial data with other data, such as Techno Economic (TE) data, in order to perform advanced spatial analyses.…”

Section: Introductionmentioning

confidence: 99%

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A review of geographic information system (GIS) and techno economic (TE) software tools for renewable energy and methodology to develop a coupled GIS-TE software tool for marine renewable energy (MRE)

O’Connell

Murphy

McAuliffe

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part M:

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Accurate and up-to-date Geographic Information System (GIS) and Techno Economic (TE) tools are pertinent to helping to develop the renewable energy sector. This paper reviews the state of the art in existing GIS and TE tools for renewable energy and proposes a methodology to develop a coupled GIS-TE software tool that is geared specifically to Marine Renewable Energy (MRE) applications and bespoke to Irish and Western UK waters. Methods for approaching GIS and TE analysis within existing tools for renewable energy are presented and compared. Many existing tools of this nature have some interesting functionalities, but most are unsuitable for MRE; are limited by a lack of information on both the technology and the site; and focus solely either on GIS or TE aspects of analysis. Additionally, almost all of those with a TE focus are not open access. The proposed tool aims to incorporate increased resolution and site relevance of resource data; the most up-to-date geospatial data for site selection; and will provide site specific TE indicators and recommendations for contemporary MRE devices. The result will be the development an open-access GIS-TE software tool for MRE.

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Section: Resource Assessmentmentioning

confidence: 99%

Section: Gis: Approaches and Considerationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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A review of geographic information system (GIS) and techno economic (TE) software tools for renewable energy and methodology to develop a coupled GIS-TE software tool for marine renewable energy (MRE)

O’Connell

Murphy

McAuliffe

et al. 2023

Proceedings of the Institution of Mechanical Engineers, Part M:

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“…Each site was chosen as representing seabed sediment waves occurring at different spatial scales. Site A, Cork Harbour, is a macrotidal harbour, with a maximum tidal range of 4.2 m. It is the second largest estuary in Ireland and one of the largest natural harbours in the world [40,41]. A strong tidal current driven by the channelised high tidal range in the harbour induces bedload sediment transport and produces migratory mega-scale bedforms such as sediment waves (Figure 1A(ii)).…”

Section: Study Sitesmentioning

confidence: 99%

A Scalable, Supervised Classification of Seabed Sediment Waves Using an Object-Based Image Analysis Approach

Summers

Wheeler

2021

Remote Sensing

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National mapping programs (e.g., INFOMAR and MAREANO) and global efforts (Seabed 2030) acquire large volumes of multibeam echosounder data to map large areas of the seafloor. Developing an objective, automated and repeatable approach to extract meaningful information from such vast quantities of data is now essential. Many automated or semi-automated approaches have been defined to achieve this goal. However, such efforts have resulted in classification schemes that are isolated or bespoke, and therefore it is necessary to form a standardised classification method. Sediment wave fields are the ideal platform for this as they maintain consistent morphologies across various spatial scales and influence the distribution of biological assemblages. Here, we apply an object-based image analysis (OBIA) workflow to multibeam bathymetry to compare the accuracy of four classifiers (two multilayer perceptrons, support vector machine, and voting ensemble) in identifying seabed sediment waves across three separate study sites. The classifiers are trained on high-spatial-resolution (0.5 m) multibeam bathymetric data from Cork Harbour, Ireland and are then applied to lower-spatial-resolution EMODnet data (25 m) from the Hemptons Turbot Bank SAC and offshore of County Wexford, Ireland. A stratified 10-fold cross-validation was enacted to assess overfitting to the sample data. Samples were taken from the lower-resolution sites and examined separately to determine the efficacy of classification. Results showed that the voting ensemble classifier achieved the most consistent accuracy scores across the high-resolution and low-resolution sites. This is the first object-based image analysis classification of bathymetric data able to cope with significant disparity in spatial resolution. Applications for this approach include benthic current speed assessments, a geomorphological classification framework for benthic biota, and a baseline for monitoring of marine protected areas.

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“…Since much of these information and data is likely to have spatial components, GIS can contribute significantly to coastal management in a number of ways: it can handle much larger databases, and integrate and synthesize data from a much wider range of relevant criteria than might be achieved through manual methods. GIS encourages the development and use of standards for coastal data definition, collection and storage, which promotes compatibility of data and processing techniques between projects and between departments, as well as ensuring consistency of approach at any one site over time (Bartlett & Celliers, 2016).…”

Section: Geographical Information System (Gis) In Coastal Managementmentioning

confidence: 99%

Special Issue 3 : 2017

Malaysia¹

2017

PMJ

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All rights reserved.No part of this publication may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, or otherwise without the prior permission of the publisher.The views expressed in this publication are those of the author(s) and do not necessarily represent the views of MIP.This journal is a refereed journal. All articles were reviewed by two or three unanimous referees identified by the Institute (MIP).

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Geoinformatics for Applied Coastal and Marine Management

Cited by 4 publications

References 10 publications

A review of geographic information system (GIS) and techno economic (TE) software tools for renewable energy and methodology to develop a coupled GIS-TE software tool for marine renewable energy (MRE)

A review of geographic information system (GIS) and techno economic (TE) software tools for renewable energy and methodology to develop a coupled GIS-TE software tool for marine renewable energy (MRE)

A Scalable, Supervised Classification of Seabed Sediment Waves Using an Object-Based Image Analysis Approach

Special Issue 3 : 2017

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