High-resolution information of the marine environment is very important for the protection and the management of marine species. In recent years, the ability of the unmanned aerial systems (UAS) to acquire remotely, high-resolution imagery has made them very popular in the marine remote sensing field. Observations in the marine environment are very challenging in many ways as they are affected by weather and oceanographic conditions that interact with each other. The UAS aerial surveys deal with many limitations affecting the quality and reliability of the acquired data, directly dependent on the environmental conditions prevailing in the survey area. For example, high wind speed affects the sea surface state and the safety of a UAS survey, resulting in unsatisfying observations of the marine environment.
This study presents the validation of a UAS toolbox designed to calculate the optimal flight times on a day for UAS surveys. The ruleset of the toolbox is based on a theoretical UAS data acquisition protocol which summarizes all the parameters that affect the quality and reliability of the UAS acquired data in the marine environment. For the validation of the toolbox, flights were conducted in different conditions, according to the toolbox predictions, while underwater targets were placed and compared as to their characteristics in different conditions. The aerial images of each flight were processed for the creation of high-resolution orthophoto-maps that showed significant differences between the optimal flight times and the non-optimal flights. The present work emphasizes the importance of the environmental conditions during an aerial survey and evidence that data quality is superior during the toolbox suggested flight times.
The collection of detailed and accurate information about marine habitats and flora species is crucial for mapping, monitoring and management of marine and coastal environments. Remote sensing is widely used to collect information at marine environments, while in recent years the potential use of UAS for mapping is examined. The aim of this paper is the creation of a prediction model for the optimal flight windows of UAS, using the programming language R. The methodology examines several limitations of UAS data acquisition over coastal areas, related to environmental conditions, mainly due to weather and sea state. A theoretical protocol that summarizes the parameters that affect the quality of aerial data acquisition, was created. These parameters are related to the weather conditions (wind, temperature, clouds etc.) and oceanographic phenomena (waves, turbidity, sun glint etc.), prevailing in the study area during the UAV flight. The protocol for the collection of accurate and reliable geospatial information in coastal and marine areas using UAS will be a useful mapping tool for the coastal zone mapping. The produced prediction model will act as a versatile computation approach to different input variables and therefore can be used widely. The input variables of this model refer to weather conditions prevailing in the area of interest and measurements of oceanographic parameters. The result of the prediction model is the optimal flight windows for the collection of accurate and qualitative marine information, in a region of interest.
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