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

Flavio Marzialetti,Alicia Teresa Rosario Acosta,Ludovico Frate,Walter De Simone,Maria Laura Carranza,Anna Rita Frattaroli

doi:10.3390/rs13173361

Flavio Marzialetti, Alicia Teresa Rosario Acosta + Show 4 more

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https://doi.org/10.3390/rs13173361

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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.

Highlights

Invasive alien plants (IAPs) are non–native species introduced by humans into a natural system outside of their native range and have become a global conservation concern, representing one of the major threats to biodiversity and demanding costly monitoring and control programs [1–4]
In order to improve the spectral resolution of the RGB images we considered Hue, Intensity and Saturation metrics (HIS) [64–66] using the i.rgb.his tool implemented in GRASS GIS 7.8 [67]
Only in the flowering period the polygons of A. saligna identified as evinced by the increase of K, True Skill Statistics (TSS), PRC and SNS values com identified as evinced by the increase of K, TSS, PRC and SNS values compared by preflowering period

Summary

Introduction

Invasive alien plants (IAPs) are non–native species introduced by humans into a natural system outside of their native range and have become a global conservation concern, representing one of the major threats to biodiversity and demanding costly monitoring and control programs [1–4]. In this context, the European Commission promulgated the Regulation on invasive alien species (the (EU 1143/2014 IAS Regulation) providing a normative frame to prevent, minimize and mitigate the negative impacts of IAS introduction and spread on biodiversity and related ecosystem services. According to the IAS Regulation, Member States are committed to implement specific actions of monitoring and surveillance aimed at detecting invasive species into non-native regions. The Regulation provides a list of IAS (both animals and plants) that must be carefully monitored through a dedicated surveillance system and subjected to management actions aimed at eradicating, containing or controlling their populations [16]

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