An invasive goldenrod, Solidago altissima, is abundant in urban environment of Japan and a threat to native biodiversity. Aerial remote sensing approach would be useful for effective monitoring and management of the species. However, it is challenging for remote sensing technique to detect a specific single plant species with a small crown and population size in highly heterogeneous urban environments. This study investigated the ability to upscale the in-situ hyperspectral reflectance signature obtained at crown level for landscape scale detection. Field hyperspectral sensors were used to obtain the spectral signatures of Solidago altissima and its surrounding features at crown scale (5 cm × 5 cm, instantaneous field of view (IFOV)). By using the first derivative analysis, the hyperspectral indices namely SAFI (S. altissima flower index) was developed based on the sensitive and peak reflectance of full blooming flower. This index was subsequently applied to identify the blooming S. altissima at population scale (1 m × 1 m) and landscape scale (5 m × 5 m) using field hyperspectral sensor and satellite data respectively. The results at crown scale showed that SAFI was able to discriminate S. altissima from their surrounding features with average probability of 72%. At the population scale with (1 m plot), SAFI can discriminate plot with different S. altissima flower distribution starting from 45%dominance. At landscape scale, effective detection was found at SAFI value over 0.3 to 0.5. The sites which hadhigh SAFI values but no actual presence of S. altissima were often under intensive land management such as frequent mowing. We conclude that the detection of S. altissima distribution at landscape scale by direct upscaling crown scale hyperspectral signature was possible using high resolution satellite image with availability of green(~480 nm) and yellow (~600 nm) spectrum bands at fine resolution (~5 m). The detection, however, were influenced by the phenology state of the flowering stages, community size and adjacent plant that possesses similar carotenoid characteristics.

在日本的城市环境中，入侵的金毛rod，一枝黄花（Solidago altissima）丰富，对本地生物多样性构成了威胁。空中遥感方法将对物种的有效监测和管理很有用。但是，对于遥感技术来说，要在高度异类的城市环境中检测具有较小冠和种群大小的特定单一植物物种具有挑战性。本研究调查了在冠状水平上获得的用于景观尺度检测的原位高光谱反射信号特征的放大能力。现场高光谱传感器用于获得Solidago altissima的光谱特征及其周围特征为冠状刻度（5厘米×5厘米，瞬时视场（IFOV））。通过使用一阶导数分析，基于盛开花朵的敏感度和峰值反射率，开发了高光谱指数SAFI（S。altissima花卉指数）。该指数随后用于分别使用现场高光谱传感器和卫星数据在人口规模（1 m×1 m）和景观规模（5 m×5 m）上识别盛开的拟南芥。冠状尺度的结果表明，SAFI能够以72％的平均概率将altissima与周围特征区分开。在人口规模为（1 m地块）的情况下，SAFI可以区分具有不同链球菌的地块花的分布从占优势的45％开始。在景观尺度上，发现SAFI值超过0.3到0.5的有效检测。具有较高SAFI值但没有实际存在的altissima的地点通常受到密集的土地管理，例如频繁修剪。我们得出的结论是，可以使用高分辨率卫星图像以高分辨率（~~ 480 nm的绿色（〜480 nm）和黄色（〜600 nm）的波段）通过直接放大冠状标度高光谱特征来检测景观尺度上的S. altissima分布。 5 m）。然而，检测受到开花期的物候状态，群落大小和具有相似类胡萝卜素特征的邻近植物的影响。