Application of PROSPECT for estimating total petroleum hydrocarbons in contaminated soils from leaf optical properties

Abstract

Recent advances in hyperspectral spectroscopy suggest making use of leaf optical properties for monitoring soil contamination in oil production regions by detecting pigment alterations induced by Total Petroleum Hydrocarbons (TPH). However, this provides no quantitative information about the level of contamination. To achieve this, we propose an approach based on the inversion of the PROSPECT model. 1620 leaves from five species were collected on a site contaminated by 16 to 77 g.kg-1 of TPH over a 14-month period. Their spectral signature was measured and used in PROSPECT model inversions to retrieve leaf biochemistry. The model performed well for simulating the spectral signatures (RMSE < 2%) and for estimating leaf pigment contents (RMSE ≤ 2.95 µg.cm-2 for chlorophylls). Four out of the five species exhibited alterations in pigment contents when exposed to TPH. A strong correlation was established between leaf chlorophyll content and soil TPH concentrations (R 2 ≥ 0.74) for three of them, allowing accurate predictions of TPH (RMSE = 3.20 g.kg-1 and RPD = 5.17). The accuracy of predictions varied by season and improved after the growing period. This study demonstrates the capacity of PROSPECT to estimate oil contamination and opens up promising perspectives for larger-scale applications.

Toward Quantifying Oil Contamination in Vegetated Areas Using Very High Spatial and Spectral Resolution Imagery

“…where R sim and R meas denote the simulated and measured reflectance in the [λ min :λ max ] spectral range, respectively. In previous work, the LCC of R. fruticosus estimated using PROSPECT inversion was consistent with laboratory analyses and strongly linked to TPH concentrations [43]. This method was developed in the field and performed well for predicting the contamination level (i.e., TPH concentration) at leaf scale.…”

“…2019, 11, 2241 4 of 19 (≤3.15 g/kg −1 ). More information about the mud pits, including soil properties, can be found in our previous studies [28,34,43]. In addition, one large (~20 × 20 m) and five smaller control sites colonized by R. fruticosus were identified in the same region and used for the calibration and validation of the detection method, respectively, Figure 1d-f. No TPH were detected in soil analyses for any of the control sites.…”

“…The study focused on this species, as it is generally well-established in temperate industrial areas. Bramble served for developing the methods of oil detection and quantification under controlled and field conditions [28,34,43] and was suitable for application to hyperspectral imagery.…”

“…For example, Arellano et al [41] inverted the PROSPECT model [42] to detect changes in leaf chlorophyll content (LCC) resulting from an oil spill under tropical region. The same model was recently used for quantifying TPH in mud pit soils from leaf reflectance measurements performed in the field [43]. As suggested, its coupling with the SAIL canopy model [44] (forming the PROSAIL model [45]) might be of great interest for quantifying oil contamination in vegetated areas, from hyperspectral images.…”

“…In the continuity of the abovementioned studies [28,43], this work aims to detect and quantify oil contamination (i.e., soil TPH content) in vegetated areas using airborne hyperspectral images with very high spatial and spectral resolutions. To achieve this, a method of detection previously developed under Remote Sens.…”