# Detecting Symptoms and Dispersal of Pine Tortoise Scale Pest in an Urban Forest by Remote Sensing
## 4 Discussion  
We reported on the detection (by hyperspectral remote sensing) of defoliation in a stone pine urban forest caused by an invasive pest and the modeling of its dispersion due to wind in a study site in Central Italy. Four years after the first reports of _T. parvicornis_' arrival in Europe and Italy [19] in 2014, the pest was detected 150 km further north, in the Castelporziano Presidential Estate, close to Rome. As occurred for the other outbreaks in Italy, PTS reached high levels of population density in a short time thanks to several phenological and ecological factors. Among such factors are the intrinsic high reproduction rate and adaptability to the warm Mediterranean climate that allows several generations per year, as well as the difficulty in implementing sustainable control strategies in an urban environment and the absence of efficient natural enemies [22]. The wind represents one of the drivers for the natural dispersal of wingless insects and very weak fliers whose movement frequently occurs downwind [30]. Airborne dispersal of the first-nymphal instars (crawlers) has been reported in several species of scale insects, and it has been suggested that specific morphological characters allow them to drift longer on air currents. In addition, crawlers of some species display behaviors that seem to be adapted for take-off in wind streams: they accumulate at the tips of leaves, where they are more exposed to air currents, and orient themselves downwind, increasing frictional drag and enhancing removal by air currents [57]. Nymphs of the scale _Parthenolecantium corni_ (Bouche) were found in the prevailing wind sector and were mostly collected on the trap side exposed downwind within and among vineyard plots [58]. Concerning PTS, no information on its wind dispersal mode is currently available. Most of the pine forests affected by PTS in Castelporziano have been replaced by natural understory deciduous vegetation, which grew intensively thanks to the increased solar radiation penetrating the damaged canopy. The shift from forest canopy to understory vegetation is mirrored by a considerable decrease in mean near-infrared (NIR) reflectance and its shift from a steady inter-annual phenology to a seasonal cycle recorded by both multispectral and hyperspectral satellite sensors. This is in open contrast to the phenology of the reflectance in the photosynthetically active region of the spectrum (visible red), which did not record any symptoms of canopy dieback due to PTS. Thus, the magnitude and seasonal phenology of NIR may be a strong signal of forest canopy dieback. On the other hand, a strong consensus has grown on using vegetation indexes (VIs) for assessing canopy structure, photosynthesis, and LAI [59], which are favored by the convenient interpretation provided by an adimensional indicator that overrides the complexities behind the measurement of radiance and its conversion to reflectance specific to each sensor [60]. VIs usually combine visible and NIR channels, and each VI is suitable for specific uses and is affected by some limiting factors [61], so the choice of a specific VI should be made with caution. A set of recent papers [62; 63] mentions that reflectance at NIR wavelengths can be directly used as a proxy for photosynthetic activity assessment. Our results highlight that the red channel carries little or no useful information over the direct usage of the NIR channel for the detection of forest dieback while not being affected by the idiosyncrasies of VIs, such as saturation at high reflectance values or sensitivity to atmospheric effects [64]. This method shows promise for rapidly detecting the onset of pest outbreaks in coniferous forests, providing an alternative to approaches based on VIs often employed in similar studies [65, 66].