scholarly journals UASea: A Data Acquisition Toolbox for Improving Marine Habitat Mapping

Drones ◽  
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.

scholarly journals UAS DATA ACQUISITION PROTOCOL FOR MARINE HABITAT MAPPING: AN ACCURACY ASSESSMENT STUDY

2020 ◽  
Vol XLIII-B3-2020 ◽  
pp. 1321-1326
Author(s):  
M. Doukari ◽  
K. Topouzelis
Keyword(s):  
High Resolution ◽  
Data Acquisition ◽  
Marine Environment ◽  
Environmental Conditions ◽  
Accuracy Assessment ◽  
Habitat Mapping ◽  
Marine Habitat ◽  
Acquisition Protocol ◽  
Marine Habitats ◽  
Marine Habitat Mapping

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.

scholarly journals Comparison of True-Color and Multispectral Unmanned Aerial Systems Imagery for Marine Habitat Mapping Using Object-Based Image Analysis

2020 ◽  
Vol 12 (3) ◽  
pp. 554 ◽  
Author(s):  
Apostolos Papakonstantinou ◽  
Chrysa Stamati ◽  
Konstantinos Topouzelis
Keyword(s):  
Habitat Mapping ◽  
Unmanned Aerial Systems ◽  
Marine Habitat ◽  
Object Based Image Analysis ◽  
In Situ Data ◽  
Object Based ◽  
Marine Habitat Mapping ◽  
True Color ◽  
Aerial Systems

The use of unmanned aerial systems (UAS) over the past years has exploded due to their agility and ability to image an area with high-end products. UAS are a low-cost method for close remote sensing, giving scientists high-resolution data with limited deployment time, accessing even the most inaccessible areas. This study aims to produce marine habitat mapping by comparing the results produced from true-color RGB (tc-RGB) and multispectral high-resolution orthomosaics derived from UAS geodata using object-based image analysis (OBIA). The aerial data was acquired using two different types of sensors—one true-color RGB and one multispectral—both attached to a UAS, capturing images simultaneously. Additionally, divers’ underwater images and echo sounder measurements were collected as in situ data. The produced orthomosaics were processed using three scenarios by applying different classifiers for the marine habitat classification. In the first and second scenario, the k-nearest neighbor (k-NN) and fuzzy rules were applied as classifiers, respectively. In the third scenario, fuzzy rules were applied in the echo sounder data to create samples for the classification process, and then the k-NN algorithm was used as the classifier. The in situ data collected were used as reference and training data. Additionally, these data were used for the calculation of the overall accuracy of the OBIA process in all scenarios. The classification results of the three scenarios were compared. Using tc-RGB instead of multispectral data provides better accuracy in detecting and classifying marine habitats when applying the k-NN as the classifier. In this case, the overall accuracy was 79%, and the Kappa index of agreement (KIA) was equal to 0.71, which illustrates the effectiveness of the proposed approach. The results showed that sub-decimeter resolution UAS data revealed the sub-bottom complexity to a large extent in relatively shallow areas as they provide accurate information that permits the habitat mapping in extreme detail. The produced habitat datasets are ideal as reference data for studying complex coastal environments using satellite imagery.

scholarly journals A Protocol for Aerial Survey in Coastal Areas Using UAS

2019 ◽  
Vol 11 (16) ◽  
pp. 1913 ◽  
Author(s):  
Michaela Doukari ◽  
Marios Batsaris ◽  
Apostolos Papakonstantinou ◽  
Konstantinos Topouzelis
Keyword(s):  
Data Acquisition ◽  
Case Studies ◽  
Marine Environment ◽  
Aerial Survey ◽  
Coastal Areas ◽  
Weather Data ◽  
Accurate Information ◽  
Unmanned Aerial Systems ◽  
Optimal Conditions ◽  
Marine Applications

Aerial surveys in coastal areas using Unmanned Aerial Vehicles (UAVs) present many limitations. However, the need for detailed and accurate information in a marine environment has made UAVs very popular. The aim of this paper is to present a protocol which summarizes the parameters that affect the reliability of the data acquisition process over the marine environment using Unmanned Aerial Systems (UAS). The proposed 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 prevailing in the study area during a UAV mission and affect the quality of marine data. Furthermore, a UAS toolbox, which combines forecast weather data values with predefined thresholds and calculates the optimal flight window times in a day, was developed. The UAS toolbox was tested in two case studies with data acquisition over a coastal study area. The first UAS survey was operated under optimal conditions while the second was realized under non-optimal conditions. The acquired images and the produced orthophoto maps from both surveys present significant differences in quality. Moreover, a comparison between the classified maps of the case studies showed the underestimation of some habitats in the area at the non-optimal survey day. The UAS toolbox is expected to contribute to proper flight planning in marine applications. The UAS protocol can provide valuable information for mapping, monitoring, and management of the coastal and marine environment, which can be used globally in research and a variety of marine applications.

Epibenthic marine habitat mapping in a tropical bay: Todos os Santos Bay, Eastern Brazil

2020 ◽  
pp. 219-230
Author(s):  
Renato Guimarães de Oliveira ◽  
José Maria Landim Dominguez ◽  
Ivan Cardoso Lemos ◽  
Carla Maria Menegola da Silva
Keyword(s):  
Habitat Mapping ◽  
Marine Habitat ◽  
Eastern Brazil ◽  
Marine Habitat Mapping ◽  
Tropical Bay

Testing the utility of abiotic surrogates for marine habitat mapping at scales relevant to management

2004 ◽  
Vol 119 (3) ◽  
pp. 351-362 ◽  
Author(s):  
Tim Stevens ◽  
Rod M. Connolly
Keyword(s):  
Habitat Mapping ◽  
Marine Habitat ◽  
Marine Habitat Mapping

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

2018 ◽  
Vol 168 ◽  
pp. 39-47 ◽  
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

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

2018 ◽  
Vol 76 (1) ◽  
pp. 10-22 ◽  
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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