Department of Earth Systems Analysis, Faculty of Geo-information Science and Earth Observation, University of Twente, Enschede, The Netherlands.
Int J Phytoremediation. 2013;15(5):405-26. doi: 10.1080/15226514.2012.702805.
Assessment of soil contamination and its long-term monitoring are necessary to evaluate the effectiveness of phytoremediation systems. Spectral sensing-based monitoring methods promise obvious benefits compared to field-based methods: lower cost, faster data acquisition and better spatio-temporal monitoring. This paper reviews the theoretical basis whereby proximal spectral sensing of soil and vegetation could be used to monitor phytoremediation of metal-contaminated soils, and the eventual upscaling to imaging sensing. Both laboratory and field spectroscopy have been applied to sense heavy metals in soils indirectly via their intercorrelations with soil constituents, and also through metal-induced vegetation stress. In soil, most predictions are based on intercorrelations of metals with spectrally-active soil constituents viz., Fe-oxides, organic carbon, and clays. Spectral variations in metal-stressed plants is particularly associated with changes in chlorophyll, other pigments, and cell structure, all of which can be investigated by vegetation indices and red edge position shifts. Key shortcomings in obtaining satisfactory calibration for monitoring the metals in soils or metal-related plant stress include: reduced prediction accuracy compared to chemical methods, complexity of spectra, no unique spectral features associated with metal-related plant stresses, and transfer of calibrations from laboratory to field to regional scale. Nonetheless, spectral sensing promises to be a time saving, non-destructive and cost-effective option for long-term monitoring especially over large phytoremediation areas, and it is well-suited to phytoremediation networks where monitoring is an integral part.
评估土壤污染及其长期监测对于评估植物修复系统的有效性是必要的。基于光谱感应的监测方法与基于现场的方法相比具有明显的优势：成本更低、数据采集更快、时空监测更好。本文综述了利用近地表光谱感应土壤和植被来监测受金属污染土壤的植物修复的理论基础，以及最终扩展到成像感应。实验室和现场光谱学都已应用于通过它们与土壤成分的相互关系间接感应土壤中的重金属，以及通过金属诱导的植被胁迫来感应重金属。在土壤中，大多数预测都是基于金属与光谱活性土壤成分（如铁氧化物、有机碳和粘土）之间的相互关系。受金属胁迫的植物的光谱变化特别与叶绿素、其他色素和细胞结构的变化有关，这些都可以通过植被指数和红边位置偏移来研究。在获得对土壤中金属或与金属相关的植物胁迫进行监测的令人满意的校准方面存在一些关键缺陷，包括：与化学方法相比，预测精度降低，光谱复杂性，与金属相关的植物胁迫没有独特的光谱特征，以及从实验室到野外到区域尺度的校准转移。尽管如此，光谱感应有望成为一种节省时间、非破坏性和具有成本效益的长期监测选择，特别是在大型植物修复区域，并且非常适合作为监测的一部分的植物修复网络。
