PLoS ONE (Jan 2014)

Alien plant monitoring with ultralight airborne imaging spectroscopy.

  • María Calviño-Cancela,
  • Roi Méndez-Rial,
  • Javier Reguera-Salgado,
  • Julio Martín-Herrero

DOI
https://doi.org/10.1371/journal.pone.0102381
Journal volume & issue
Vol. 9, no. 7
p. e102381

Abstract

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Effective management of invasive plants requires a precise determination of their distribution. Remote sensing techniques constitute a promising alternative to field surveys and hyperspectral sensors (also known as imaging spectrometers, with a large number of spectral bands and high spectral resolution) are especially suitable when very similar categories are to be distinguished (e.g. plant species). A main priority in the development of this technology is to lower its cost and simplify its use, so that its demonstrated aptitude for many environmental applications can be truly realized. With this aim, we have developed a system for hyperspectral imaging (200 spectral bands in the 380-1000 nm range and circa 3 nm spectral resolution) operated on board ultralight aircraft (namely a gyrocopter), which allows a drastic reduction of the running costs and operational complexity of image acquisition, and also increases the spatial resolution of the images (circa 5-8 pixels/m(2) at circa 65 km/h and 300 m height). The detection system proved useful for the species tested (Acacia melanoxylon, Oxalis pes-caprae, and Carpobrotus aff. edulis and acinaciformis), with user's and producer's accuracy always exceeding 90%. The detection accuracy reported corresponds to patches down to 0.125 m(2) (50% of pixels 0.5 × 0.5 m in size), a very small size for many plant species, making it very effective for initial stages of invasive plant spread. In addition, its low operating costs, similar to those of a 4WD ground vehicle, facilitate frequent image acquisition. Acquired images constitute a permanent record of the status of the study area, with great amount of information that can be analyzed in the future for other purposes, thus greatly facilitating the monitoring of natural areas at detailed spatial and temporal scales for improved management.