Day 4

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Paper title UASea: a toolbox for acquiring accurate marine data using UAS
Authors
  1. Michaela Doukari University of the Aegean Speaker
  2. Konstantinos Topouzelis University of the Aegean
Form of presentation Poster
Topics
  • C4. HAPs/UAVs
    • C4.01 Innovative UAV applications
Abstract text Unmanned Aerial Systems (UASs) deal with many limitations in acquiring reliable data in the marine environment, mostly because of the prevalent environmental conditions during a UAS survey. These limitations refer to parameters like weather conditions (e.g., wind speed, cloud coverage), sea-state conditions (e.g., wavy sea-surface, sunglint presence), and water column parameters (e.g., turbidity). Parameters like them affect the quality of the acquired data and the accuracy and reliability of the retrieved information.
In this study, we present a toolbox that overcomes the UAS limitations in the coastal environment and calculates the optimal survey times to acquire marine information. The UASea toolbox (https://uav.marine.aegean.gr/) identifies the optimal flight times in a given day for an efficient UAS survey and the acquisition of reliable aerial imagery in the coastal environment. It gives hourly positive or negative suggestions about the optimal or non-optimal UAS acquisition times to conduct UAS surveys in coastal areas. The suggestions are derived using weather forecast data of weather variables and adaptive thresholds in a ruleset. The parameters that have been proven to affect the quality of UAS imagery and flight safety have been used as variables in the ruleset. The proposed thresholds are used to exclude inconsistent and outlier values that may affect the quality of the acquired images and the safety of the survey. Considering the above, the ruleset is designed in such a way that outlines the optimal weather conditions, suitable for reliable and accurate data acquisition as well as for efficient short-range flight scheduling.
UASea toolbox has been developed as an interactive web application accessible through the internet from modern web browsers. It is designed using HTML and CSS scripts while JavaScript augments the user experience and user interactivity through mouse events (scroll, pan, click, etc.). To identify the optimal flight times for marine mapping applications, the UASea toolbox uses short-range forecast data. In this context, we use a) Dark Sky (DS) API (Dark Sky by Apple, https://darksky.net/) for two days of forecast data on an hourly basis and b) Open Weather Map (OWM) API (Open Weather Map, https://openweathermap.org/) five days forecast with three-hour step. Users may navigate to a map element by zooming in/out and panning to the desired location and selecting the study area by clicking the map. A leaflet marker triggers an ‘Adjust Parameters’ panel that consists of an HTML form in which users can adjust the parameters and their thresholds and select one of the available weather forecast data providers. After the adjustment, a decision panel becomes available at the bottom of the screen. At the top of the decision panel, there is a date menu that is used to address the range of the available forecast data, while on the bottom of the decision panel the results of the UASea toolbox are presented in tabular format. In the ‘Decisions’ row, the green color indicates optimal weather conditions, while the red color stands for non-optimal weather conditions.
The performance of the UASea toolbox has been tested and validated in different coastal areas and environmental conditions, through image quality estimates and classification accuracy assessment analysis. The quality and accuracy assessment validated the suggested acquisition times of the UASea, resulting in significant differences between the data acquired in optimal and non-optimal conditions in each site. The results showed that most of the positive toolbox suggestions (optimal acquisition times) match the images with the higher quality. The validation of the toolbox proved that UAS surveys on the suggested optimal acquisition times result in high-quality images. In addition, the results confirmed that a more accurate image classification can be achieved during optimal flight conditions.
UASea is a user-friendly and promising toolbox that can be used globally for efficient mapping, monitoring, and management of the coastal environment, by researchers, engineers, environmentalists, NGOs for efficient mapping, monitoring, and management of the coastal environment, for ecological and environmental purposes, exploiting the existing capability of UAS in marine remote sensing.