Mapping Spartina alterniflora Biomass Using LiDAR and Hyperspectral Data

Jing Wang,Zhengjun Liu,Fangfang Li,Haiying Yu

doi:10.3390/rs9060589

Abstract

Large-scale coastal reclamation has caused significant changes in Spartina alterniflora (S. alterniflora) distribution in coastal regions of China. However, few studies have focused on estimation of the wetland vegetation biomass, especially of S. alterniflora, in coastal regions using LiDAR and hyperspectral data. In this study, the applicability of LiDAR and hypersectral data for estimating S. alterniflora biomass and mapping its distribution in coastal regions of China was explored to attempt problems of wetland vegetation biomass estimation caused by different vegetation types and different canopy height. Results showed that the highest correlation coefficient with S. alterniflora biomass was vegetation canopy height (0.817), followed by Normalized Difference Vegetation Index (NDVI) (0.635), Atmospherically Resistant Vegetation Index (ARVI) (0.631), Visible Atmospherically Resistant Index (VARI) (0.599), and Ratio Vegetation Index (RVI) (0.520). A multivariate linear estimation model of S. alterniflora biomass using a variable backward elimination method was developed with R squared coefficient of 0.902 and the residual predictive deviation (RPD) of 2.62. The model accuracy of S. alterniflora biomass was higher than that of wetland vegetation for mixed vegetation types because it improved the estimation accuracy caused by differences in spectral features and canopy heights of different kinds of wetland vegetation. The result indicated that estimated S. alterniflora biomass was in agreement with the field survey result. Owing to its basis in the fusion of LiDAR data and hyperspectral data, the proposed method provides an advantage for S. alterniflora mapping. The integration of high spatial resolution hyperspectral imagery and LiDAR data derived canopy height had significantly improved the accuracy of mapping S. alterniflora biomass.

Highlights

Spartina alterniflora (S. alterniflora) is a perennial deciduous grass which is found in intertidal wetlands, especially estuarine salt marshes
GNDVI, DVI, RDVI, EVI, TVI, GEMI, Visible Atmospherically Resistant Index (VARI), Atmospherically Resistant Vegetation Index (ARVI), and vegetation canopy height) was performed biomass content was significantly correlated with the following parameters: the reflectance at a (Table 1)
The results further demonstrated the importance of vegetation canopy variables, such as vegetation height, as a major factor affecting the S. alterniflora biomass distribution

Summary

Introduction

Spartina alterniflora (S. alterniflora) is a perennial deciduous grass which is found in intertidal wetlands, especially estuarine salt marshes. Some biologists and geographers have conducted various researches on ecological characteristics of S. alterniflora and its impacts on environment [1,2,3,4,5,6,7]. Some evidence has been reported that S. alterniflora could compete with native plants, threaten native ecosystems and coastal aquaculture, and cause declines in local biodiversity [2,3,4]. In China, S. alterniflora is widely distributed along the eastern coastal region of China from Tianjin to Beihai, with a concentration in Jiangsu Province. Large-scale coastal reclamation has resulted in significant changes in distribution of S. alterniflora in Dafeng coastal zone of Jiangsu. The formation, expansion, and distribution of the plant in Jiangsu coastal zone has been

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Conclusion