Drone-Based Identification and Monitoring of Two Invasive Alien Plant Species in Open Sand Grasslands by Six RGB Vegetation Indices

Abstract

Today, invasive alien species cause serious trouble for biodiversity and ecosystem services, which are essential for human survival. In order to effectively manage invasive species, it is important to know their current distribution and the dynamics of their spread. Unmanned aerial vehicle (UAV) monitoring is one of the best tools for gathering this information from large areas. Vegetation indices for multispectral camera images are often used for this, but RGB colour-based vegetation indices can provide a simpler and less expensive solution. The goal was to examine whether six RGB indices are suitable for identifying invasive plant species in the QGIS environment on UAV images. To examine this, we determined the shoot area and number of common milkweed (Asclepias syriaca) and the inflorescence area and number of blanket flowers (Gaillardia pulchella) as two typical invasive species in open sandy grasslands. According to the results, the cover area of common milkweed was best identified with the TGI and SSI indices. The producers’ accuracy was 76.38% (TGI) and 67.02% (SSI), while the user’s accuracy was 75.42% (TGI) and 75.12% (SSI), respectively. For the cover area of blanket flower, the IF index proved to be the most suitable index. In spite of this, it gave a low producer’s accuracy of 43.74% and user’s accuracy of 51.4%. The used methods were not suitable for the determination of milkweed shoot and the blanket flower inflorescence number, due to significant overestimation. With the methods presented here, the data of large populations of invasive species can be processed in a simple, fast, and cost-effective manner, which can ensure the precise planning of treatments for nature conservation practitioners.

Plant phenotyping relevance

UAV RGB画像と6種の植生指数を用いて、侵入植物のシュート面積・花序面積・個体数を抽出し、適合性と精度を評価している。単なる分布把握ではなく、植物形質の画像計測法の検証・適用が中心である。

Code and data availability

The paper reports UAV RGB-image phenotyping of Asclepias syriaca and Gaillardia pulchella with supplementary tables (S1–S5) and figures, but the Data Availability Statement says 'Not applicable.' No author code, dataset, or image deposit is disclosed. The supplementary materials URL (https://www.mdpi.com/article/10.339

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