## 1 Introduction  
Reed beds provide important structural elements of lake ecosystems. Along a horizontal gradient that runs from the lake towards the bank, reed stocks are classified into three different ecological zones that occur either in water, transition, or in land zones [1]. The water reed at the expansion front of a reed stock is considered the most sensitive zone of a reed bed [2]. According to their definition, land reed beds are located in areas above water level, comprising an onshore/shoreward stock of multiple species, and usually growing in meadows [2]. Aquatic reed beds grow in locations that were flooded throughout the year. Lakewards stocks are pure stands of _Phragmites australis_, and are characterized by their low stem density (stems/m\({}^{2}\)) and longer sparse fertility [2]. Stocks of this macrophyte act as a buffer between land and water. They provide a key habitat for several endangered species [1], they physically protect banks from erosion, and they provide a food resource for various arthropods,birds, and mammals [3]. Aquatic reed beds are threatened, mainly due to mechanical, hydrological, anthropogenic, biological, and climatic causes [3; 4; 5; 6; 7; 8; 9]. Global warming influences, such as an increase in water temperature, extreme drought, and heavy rain events could additionally affect the growth and status of aquatic reed populations of freshwater lakes [10; 11]. Changes in the abundance and density of reed beds can be quantified through the implementation of field measurements and remote sensing methodologies. Although on-site evaluations deliver highly accurate results, they are associated with high personnel, time, and financial expenses, as well as ecological disturbance of protected habitats [12]. Visual interpretation of multispectral aerial imagery has been the standard method to bypass this problem [7; 13; 14; 15]. In the same way, analysis of satellite imagery has also been implemented [16; 17; 18; 19]. These methodologies have contributed to the global monitoring of reed beds in wetlands and large lakes, where tens of hectares are covered by this type of vegetation. In the monitoring of small lakes with a limited presence of aquatic reed beds, spatial resolutions provided by satellite constellations are still too coarse for identifying stocks that are sparsely distributed or only comprise single reed individuals. This difficulty poses a serious limitation to monitoring spatial occurrence. The accurate identification of aquatic reed beds by analysis of optical imagery is affected by sun illumination, plant phenology, and spatial resolution. The position of the leaves' and the stems' incidence angle towards the sun causes differences in the spectral response and therefore, causes variances in the extent of quantification of sparse aquatic reed beds [7]. The imagery of official surveys is recorded normally for updating cadaster data and topographic maps, and not usually in the growth season (i.e., August to mid-September) when aquatic reed beds have their peak growth and maximum vitality. Accurate assessment is additionally hindered by shades, light reflection on the water surface, or vegetation reflectance. Although spatial resolution is sufficient for other purposes, sparse aquatic reeds cannot be identified in imagery with spatial resolutions lower than 20 cm per pixel [20; 21]. Technological advancements in remote sensing science offer new possibilities in the characterisation of reed beds based on 3D data analysis. Very high spatial resolution multispectral imagery recorded with unmanned aerial vehicles and close range aerial photogrammetry have already supported the accurate mapping of land and aquatic reed beds [22]. In the same way, the biomass of wetland _Phragmites australis_[23], of wetland vegetation mapping [24; 25; 26], and characterisation of the land reed bed habitat quality [27] have all been achieved by applying Light Detection and Ranging (LiDAR) technologies alone or in combination with other data types (e.g., hyperspectral data).