An error analysis of marine habitat mapping methods and prioritised work packages required to reduce errors and improve consistency

Abstract. Marine habitat mapping is essential for updating existing information, preserving, and protecting the marine environment. Unmanned Aerial Systems (UAS) are an important tool for monitoring and mapping coastal and marine environment because of their ability to provide very high-resolution aerial imagery.Environmental conditions have a critical role in marine mapping using UAS. This is due to the limitations of UAS surveys in coastal areas, i.e. the environmental conditions prevailing in the area. The limitations of weather and oceanographic conditions affecting the quality of marine data led to the creation of a UAS protocol for the acquisition of reliable marine information. The produced UAS Data Acquisition Protocol consists of three main categories: (i) Morphology of the study area, (ii) Environmental conditions, (iii) Flight parameters. These categories include the parameters that must be considered for marine habitat mapping.The aim of the present study is the accuracy assessment of the UAS protocol for marine habitat mapping through experimental flights. For the accuracy assessment of the UAS protocol, flights on different dates and environmental conditions were conducted, over a study area. The flight altitude was the same for all the missions, so the results were comparable. The high-resolution orthophoto maps derived from each date of the experiment were classified. The classification maps show several differences in the shape and size of the marine habitats which are directly dependent on the conditions that the habitats were mapped. A change detection comparison was conducted in pairs to examine the exact changes between the classified maps.The results emphasize the importance of the environmental conditions prevailing in an area during the mapping of marine habitats. The present study proves that the optimal flight conditions that are proposed of the UAS Data Acquisition protocol, respond to the real-world conditions and are important to be considered for an accurate and reliable mapping of the marine environment.

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Improving marine habitat mapping using high-resolution acoustic data; a predictive habitat map for the Firth of Lorn, Scotland

Continental Shelf Research ◽

10.1016/j.csr.2018.09.005 ◽

2018 ◽

Vol 168 ◽

pp. 39-47 ◽

Cited By ~ 8

Author(s):

Karen Boswarva ◽

Alyssa Butters ◽

Clive J. Fox ◽

John A. Howe ◽

Bhavani Narayanaswamy

Keyword(s):

High Resolution ◽

Habitat Mapping ◽

Marine Habitat ◽

Acoustic Data ◽

Marine Habitat Mapping

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Performance of Different Classifiers for Marine Habitat Mapping using Side Scan Sonar and Object-Based Image Analysis

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/540/1/012087 ◽

2020 ◽

Vol 540 ◽

pp. 012087

Author(s):

Raihanah Rusmadi ◽

Rozaimi Che Hasan

Keyword(s):

Image Analysis ◽

Habitat Mapping ◽

Marine Habitat ◽

Side Scan Sonar ◽

Object Based Image Analysis ◽

Object Based ◽

Marine Habitat Mapping

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A review of the influence of marine habitat classification schemes on mapping studies: inherent assumptions, influence on end products, and suggestions for future developments

ICES Journal of Marine Science ◽

10.1093/icesjms/fsy161 ◽

2018 ◽

Vol 76 (1) ◽

pp. 10-22 ◽

Cited By ~ 10

Author(s):

James Asa Strong ◽

Annika Clements ◽

Helen Lillis ◽

Ibon Galparsoro ◽

Tim Bildstein ◽

...

Keyword(s):

Habitat Mapping ◽

Marine Habitat ◽

Classification Schemes ◽

Habitat Classification ◽

Thematic Resolution ◽

Superficial Similarity ◽

Marine Habitat Mapping ◽

Working Practices ◽

Mapping Techniques ◽

Resolution Structure

Abstract The production of marine habitat maps typically relies on the use of habitat classification schemes (HCSs). The choice of which HCS to use for a mapping study is often related to familiarity, established practice, and national desires. Despite a superficial similarity, HCSs differ greatly across six key properties, namely, purpose, environmental and ecological scope, spatial scale, thematic resolution, structure, and compatibility with mapping techniques. These properties impart specific strengths and weaknesses for each HCS, which are subsequently transferred to the habitat maps applying these schemes. This review has examined seven HCSs (that are commonly used and widely adopted for national and international mapping programmes), over the six properties, to understand their influence on marine habitat mapping. In addition, variation in how mappers interpret and apply HCSs introduces additional uncertainties and biases into the final maps. Recommendations are provided for improving HCSs for marine habitat mapping as well as for enhancing the working practices of mappers using habitat classification. It is hoped that implementation of these recommendations will lead to greater certainty and usage within mapping studies and more consistency between studies and adjoining maps.

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Marine habitat mapping of the Milford Haven Waterway, Wales, UK: Comparison of facies mapping and EUNIS classification for monitoring sediment habitats in an industrialized estuary

Journal of Sea Research ◽

10.1016/j.seares.2014.09.012 ◽

2015 ◽

Vol 100 ◽

pp. 99-119 ◽

Cited By ~ 5

Author(s):

Drew A. Carey ◽

Melanie Hayn ◽

Joseph D. Germano ◽

David I. Little ◽

Blaise Bullimore

Keyword(s):

Habitat Mapping ◽

Marine Habitat ◽

Marine Habitat Mapping

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UASea: A Data Acquisition Toolbox for Improving Marine Habitat Mapping

Drones ◽

10.3390/drones5030073 ◽

2021 ◽

Vol 5 (3) ◽

pp. 73

Author(s):

Michaela Doukari ◽

Marios Batsaris ◽

Konstantinos Topouzelis

Keyword(s):

Image Quality ◽

Data Acquisition ◽

Marine Environment ◽

Weather Forecast ◽

Habitat Mapping ◽

Unmanned Aerial Systems ◽

Marine Habitat ◽

Marine Habitat Mapping ◽

Highly Correlated ◽

Marine Applications

Unmanned aerial systems (UAS) are widely used in the acquisition of high-resolution information in the marine environment. Although the potential applications of UAS in marine habitat mapping are constantly increasing, many limitations need to be overcome—most of which are related to the prevalent environmental conditions—to reach efficient UAS surveys. The knowledge of the UAS limitations in marine data acquisition and the examination of the optimal flight conditions led to the development of the UASea toolbox. This study presents the UASea, a data acquisition toolbox that is developed for efficient UAS surveys in the marine environment. The UASea uses weather forecast data (i.e., wind speed, cloud cover, precipitation probability, etc.) and adaptive thresholds in a ruleset that calculates the optimal flight times in a day for the acquisition of reliable marine imagery using UAS in a given day. The toolbox provides hourly positive and negative suggestions, based on optimal or non-optimal survey conditions in a day, calculated according to the ruleset calculations. We acquired UAS images in optimal and non-optimal conditions and estimated their quality using an image quality equation. The image quality estimates are based on the criteria of sunglint presence, sea surface texture, water turbidity, and image naturalness. The overall image quality estimates were highly correlated with the suggestions of the toolbox, with a correlation coefficient of −0.84. The validation showed that 40% of the toolbox suggestions were a positive match to the images with higher quality. Therefore, we propose the optimal flight times to acquire reliable and accurate UAS imagery in the coastal environment through the UASea. The UASea contributes to proper flight planning and efficient UAS surveys by providing valuable information for mapping, monitoring, and management of the marine environment, which can be used globally in research and marine applications.

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