基于无人机影像的滩涂入侵种互花米草植被信息提取与覆盖度研究

Research on Vegetation Extraction and Fractional Vegetation Cover of Spartina Alterniflora Using UAV Images

以福建三沙湾为试验区,以地面光谱和低空无人机获取的可见光影像与ADC多光谱影像为数据源对入侵种互花米草植被信息和覆盖度进行研究。构建了基于可见光波段的改进型土壤调整植被指数V-MSAVI用于可见光影像植被信息提取,以NDVI指数模型对ADC多光谱影像进行了植被覆盖度估算。结果表明,V-MSAVI指数具有较好的适用性;在互花米草覆盖度方面以40%~60%和60%~80%中高等级分布为主。精度检验表明,基于V-MSAVI植被指数提取得到的互花米草总体精度为89%,Kappa系数为0.77;植被覆盖度的估算值与真实值之间的均方根误差(RMSE)为0.06,决定系数R^2为0.92。

In this study,vegetation extraction and fractional vegetation cover of Spartina alterniflora（S.alterniflora）was studied in an experimental region of Sansha bay,a typical coastal wetland area in Fujian Province,China.A new vegetation index visible-band modified soil adjusted vegetation index（V-MSAVI）was constructed and the fractional vegetation cover was calculated subsequently based on the NDVI model.Results showed that,the S.alterniflora extraction results by V-MSAVI had a satisfactory precision.Most of the fractional vegetation covers of S.alterniflora were in medium-level coverage（40%-60%）and a highlevel coverage（60%-80%）.An accuracy analysis based on the visual interpretation indicated the overall extraction results accuracy of 0.89,and a kappa coefficient of 0.77.Root mean square error（RMSE）of fractional vegetation cover between the estimation value and the true value was 0.06,and the determination coefficient R-2 was 0.92.