Spectrometric analyses in comparison to the physiological condition of heavy metal stressed floodplain vegetation in a standardised experiment

Abstract

Floodplain ecosystems are affected by flood dynamics, nutrient supply as well as anthropogenic activities.Heavy metal pollution poses a serious environmental challenge. Pollution transfer from the soil to vegetation is still present at the central location of Elbe River, Germany. The goal of this study was to assess and separate the current heavy metal contamination of the floodplain ecosystem, using spectrometric field and laboratory measurements. A standardized pot experiment with floodplain vegetation in differently contaminated soils provided the basis for the measurements. The dominant plant types of the floodplains are: Urtica dioica, Phalaris arundinacea and Alopecurus pratensis, these were also chemically analysed. Various vegetation indices and methods were used to estimate the red edge position, to normalise the spectral curve of the vegetation and to investigate the potential of different methods for separating plant stress in floodplain vegetation. The main task was to compare spectral bands during phenological phases to find a method to detect heavy metal stress in plants. A multi-level algorithm for the curve parameterisation was developed. Chemo-analytical and ecophysiological parameters of plants were considered in the results and correlated with spectral data. The results of this study show the influence of heavy metals on the spectral characteristics of the focal plants. The developed method (depth CR1730) showed significant relationship between the plants and the contamination.

Evaluating Metal Effects on the Reflectance Spectra of Plant Leaves during Different Seasons in Post-Mining Areas, China

“…(2) VIs: VIs are a linear or nonlinear combination of values of two or more bands. Two types of two-band VIs were calculated, including RE-NDVI and PRI, which were confirmed for detection of the metal stress through vegetation reflectance in the literature [17,22,50].…”

Spectroscopic estimation of leaf water content in commercial vineyards using continuum removal and partial least squares regression

“…Similarly, Santos and Kaye (2009), Wang et al (2009) and Zhang et al (2012 found that spectrum regions that included 1400 nm (Z3) and 1900 nm (Z4) were most correlated with leaf composition variables. These same bands correspond to the first overtone excitation of O H for H 2 O and O H and the H O H deformation combination, whereas other bands correspond to water content but also with cellulose and other organic components (Shenk et al, 2001); Götze et al (2010) also demonstrated that the 1750 nm region is related to lignin leaf content (dry matter) but not with water. Gaulton et al (2013) found that the Z1 region -mainly related to dry matter content and leaf structure -had the weakest relationship with EWT.…”

“…970 nm, 1200 nm, 1450 nm, 1950 nm) ( Table 2). The transformed values were also used to calculate two derived indices for each spectral interval: maximum band depth (MBD) and the area over the minimum or band area (BA) (Götze et al, 2010).…”

Detecting heavy metal pollution of floodplain vegetation in a pot experiment using reflectance spectroscopy

“…Well-studied indices indicate changes in chlorophyll content (Ren et al 2008), plant status (Liu et al 2011), leaf internal structure (Bandaru et al 2010) and leaf chemistry (Götze et al 2010). Few studies employing the spectral analysis of heavy metal-affected plants have been conducted for floodplain ecosystems (Clevers et al 2004, Götze et al 2010.…”

“…Well-studied indices indicate changes in chlorophyll content (Ren et al 2008), plant status (Liu et al 2011), leaf internal structure (Bandaru et al 2010) and leaf chemistry (Götze et al 2010). Few studies employing the spectral analysis of heavy metal-affected plants have been conducted for floodplain ecosystems (Clevers et al 2004, Götze et al 2010. It was pointed Downloaded by [Library Services City University London] at 01:22 01 July 2016 out by several researchers (overview shown in Rathod et al 2013) that most of these vegetation indices cannot differentiate the changes due to metal accumulation from other stresses, since loss of chlorophyll is a general symptom of many physiological stresses in plants.…”