Unmanned Aerial Vehicle (UAV)-Based Mapping of Acacia saligna Invasion in the Mediterranean Coast

Abstract

Remote Sensing (RS) is a useful tool for detecting and mapping Invasive Alien Plants (IAPs). IAPs mapping on dynamic and heterogeneous landscapes, using satellite RS data, is not always feasible. Unmanned aerial vehicles (UAV) with ultra-high spatial resolution data represent a promising tool for IAPs detection and mapping. This work develops an operational workflow for detecting and mapping Acacia saligna invasion along Mediterranean coastal dunes. In particular, it explores and tests the potential of RGB (Red, Green, Blue) and multispectral (Green, Red, Red Edge, Near Infra—Red) UAV images collected in pre-flowering and flowering phenological stages for detecting and mapping A. saligna. After ortho—mosaics generation, we derived from RGB images the DSM (Digital Surface Model) and HIS (Hue, Intensity, Saturation) variables, and we calculated the NDVI (Normalized Difference Vegetation Index). For classifying images of the two phenological stages we built a set of raster stacks which include different combination of variables. For image classification, we used the Geographic Object-Based Image Analysis techniques (GEOBIA) in combination with Random Forest (RF) classifier. All classifications derived from RS information (collected on pre-flowering and flowering stages and using different combinations of variables) produced A. saligna maps with acceptable accuracy values, with higher performances on classification derived from flowering period images, especially using DSM + HIS combination. The adopted approach resulted an efficient method for mapping and early detection of IAPs, also in complex environments offering a sound support to the prioritization of conservation and management actions claimed by the EU IAS Regulation 1143/2014.

Mapping Areas Invaded by Pinus sp. from Geographic Object-Based Image Analysis (GEOBIA) Applied on RPAS (Drone) Color Images

“…High-resolution satellite imagery, frequently expensive, can be useful for monitoring critical large areas. As a result, aerophotogrammetric surveys that offer sub-metric spatial resolutions may represent even better alternatives for this kind of monitoring, as demonstrated by Müllerová et al [15] and confirmed by other studies [13,14], especially with the popularization of unmanned aircraft, formally referred to as a remotely piloted aircraft systems (RPASs) [16].…”

“…Given this scenario, in regard to the control of exotic plant species within CUs, Marzialetti et al [13] pointed out that the use of remote sensing can contribute to locating, detecting, measuring, or even specifically identifying these species, and remote sensing can be used both in planning and in monitoring efforts, especially in areas that are difficult and risky to access [14].…”

Remote Sensing in Studies of the Growing Season: A Bibliometric Analysis

“…It should be noted that the reference to climatic conditions is difficult in many cases due to their high variability in the analyzed area. Europe, where the studies were carried out in a warm and dry climate [54,192,205], high mountain conditions (Swiss Alps- [170]), warm maritime climate (e.g., Ireland), or temperate climate (e.g., Germany) is one example. Similarly, in China, studies of the growing season were conducted in Tibet [353] and in loess uplands [259].…”

“…Plant analyses are mainly focused on the chlorophyll content [25] or substances contained in plants [91] and, consequently, the condition of plants [24,27]. Research on the growth and development of vegetation can be carried out in both strictly controlled laboratory conditions [29,79,92,93] and using satellite techniques [42,44,46,[49][50][51]56,59,61,62,[64][65][66]68,71,[75][76][77][78]80,88, or other means of transporting remote sensing devices (UAV, airships, airplanes) [43,47,54,55,65,84,[108][109][110]118,[140][141][142][143][144][145][146][147][148]…”

“…For many years, measurements were based on traditional sources of information (i.e., direct phenological observations combined with meteorological data). The dynamic development of technology in recent decades has allowed for the use of remote sensing data, mainly properly processed satellite data with different temporal and spatial resolutions [10,14,23,26,28,[30][31][32][33][34][35][40][41][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56][58][59][60][61][62][63][64][65][66][67][68][69][70][71][72]94,95,[134][135][136][137]…”