SoilTPHConcentrationEstimationUsingVegetationIndicesinanOilPollutedAreaofEasternChina

Zhu LH,Zhao XC,Lai LM,Wang JJ,Jiang LH,Ding JZ,Liu NX,Yu YJ,Li JS,Xiao NW,Zheng YR,Rimmington GM

Abtract:

Assessingoilpollutionusingtraditional field-based methods over large areas is difficult and expensive. Remote sensing technologies with good spatial and temporal coverage might provideanalternative for monitoringoilpollution by recording the spectral signalsofplants growinginpollutedsoils. Total petroleum hydrocarbon concentrationsofsoils and the hyperspectral canopy reflectance were measuredinwetlands dominated by reeds (Phragmites australis) aroundoilwells that have been producingoilfor approximately 10 yearsinthe Yellow River Delta,easternChinato evaluate the potentialofvegetationindicesand red edge parameters to estimatesoiloilpollution. The detrimental effectofoilpollution on reed communities was confirmed by the evidence that the aboveground biomass decreased from 1076.5 g m(-2) to 5.3 g m(-2) with increasing total petroleum hydrocarbon concentrations ranging from 9.45 mg kg(-1) to 652 mg kg(-1). The modified chlorophyll absorption ratio index (MCARI) best estimatedsoilTPHconcentrationamong 20vegetationindices. The linear model involving MCARI had the highest coefficientofdetermination (R-2 = 0.73) and accuracyofprediction (RMSE = 104.2 mg kg(-1)). For othervegetationindicesand red edge parameters, the R-2 and RMSE values ranged from 0.64 to 0.71 and from 120.2 mg kg(-1) to 106.8 mg kg(-1) respectively. The traditional broadband normalized differencevegetationindex (NDVI), oneofthe broadband multispectralvegetationindices(BMVIs), produced a prediction (R-2 = 0.70 and RMSE = 110.1 mg kg(-1)) similar to thatofMCARI. These results corroborated the potentialofremote sensing for assessingsoiloilpollutioninlarge areas. Traditional BMVIs are stillofgreat valueinmonitoringsoiloilpollution when hyperspectral data are unavailable.

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