# Unmanned Aerial Vehicle Based Wireless Sensor Network for Marine-Coastal Environment Monitoring
## 1 Introduction  
Ecological monitoring is an area of great interest for remote sensing, mainly due to the increased concern for the preservation of the environment, as well as the impact of climate change and human activity. Diverse implementations have been widely used in fields such as forest monitoring [1; 2], wildlife preservation [3; 4] and agriculture monitoring [5; 6]. Another field in which remote sensing has played a key role in recent years is the marine environment. It is probably one of the most important areas in ecology, as changes in this environment directly impact the biodiversity and atmospheric conditions, as well as any fishing-related activities [7; 8; 9]. Moreover, it is also one of the harshest settings to monitor for any type of deployment, as it requires waterproof robust technology to endure the high levels of humidity and salinity, wave collisions, and extreme weather conditions [10]. The way in which marine environments have been monitored has changed little in the past few decades, with the majority of implementations being based on satellite imagery, underwater devices with various sensors, and buoy developments. The latter are by far the most commonly used, being mostly applied to ambient variable measurement, either as stationary or drifting devices, each with its own specific purpose. These devices can measure several variables simultaneously and monitor areas for long periods of time. Currently, there are at least 1354 stations and 1421 drifter buoys deployed globally, according to data from theNational Data Buoy Center [11] and The Global Drifter Program [12] correspondingly. Yet one of the main drawbacks of using buoys is the process for data extraction. The most commons methods are long-range communications, close-range wireless transmissions, or dry-land data collection. Long-range transmissions require either a previously established infrastructure, such as a ground base station, or satellite connectivity. When using a ground station, the buoys must be fixed to a given position, or several stations must be established for drifting buoys. Additionally, these types of wireless communications tend to have a range limited to less than 100 m per ground station, thus the high usage of satellite communications. In the case of short-range communications and dry-land data collection, an aquatic vessel is required to reach the buoys and either extract the data or the buoy itself. All the previously mentioned methods are hardly sustainable due to expenses associated with monthly fees, maintenance, or person-hours. Currently, one of the most novel approaches for monitoring marine environments is the use of Unmanned Aerial Vehicles (UAV). These devices can cover areas several km wide, given their long-range communications, enabling the possibility of monitoring hard to reach areas with relative ease, as well as acquiring similar data than that of satellite imagery. In this last area, its contributions highly benefit from the possibility of extracting data at a higher resolution than satellites, but in contrast they may only cover smaller areas of analysis [13]. Additionally, as they are airborne devices, UAVs do not face the same challenges as marine monitoring deployments. Implementations using these types of devices have been used for wildlife [14; 15; 16; 17], environmental [18; 19], and hazardous marine monitoring [20]. Usually the data type acquired by a UAV in a marine implementation are those that can be collected using infrared, multispectral, or conventional cameras, yet environmental data are, for the most part, unattainable. Moreover, given their short life span of tens of minutes and the need for user interactions, monitoring for extended periods of time is difficult to achieve, as it would require several landings and battery replacements. To overcome the limitations of UAV and buoy based implementations, the use of a hybrid Wireless Sensor Network (WSN), which uses both technologies, is proposed in this article.