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

发布时间：2018-03-21 18:33

  本文选题：互花米草　切入点：植被信息提取　出处：《遥感技术与应用》2017年04期 　论文类型：期刊论文

【摘要】：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。
[Abstract]:Taking Sansha Bay, Fujian Province, as the experimental area, The vegetation information and coverage of invasive Spartina alterniflora were studied based on visible light images and ADC multispectral images obtained from ground spectrum and low altitude UAV. An improved soil adjustment plant based on visible light was constructed. The index V-MSAVI is used to extract vegetation information from visible light image. The vegetation coverage of ADC multispectral images was estimated by using NDVI index model. The results showed that V-MSAVI index had good applicability, and the coverage of Spartina alterniflora was mainly distributed in 400.60% and 80% of the total coverage of Spartina alterniflora. The total precision of Spartina alterniflora extracted from V-MSAVI vegetation index was 0.77, the root mean square error (RMSE) between the estimated value of vegetation coverage and the real value was 0.06, and the determining coefficient Rn2 was 0.92. the total precision of Spartina alterniflora was 0.77, the root mean square error (RMSE) between the estimated value of vegetation coverage and the real value was 0.06.
【作者单位】： 国家海洋局第三海洋研究所;
【基金】：福建省自然科学基金项目(2015J05085) 国家海洋局第三海洋研究所基本科研业务费项目(HE150805-14(B)) 促进海峡两岸科技合作联合基金(U1405234)
【分类号】：S45;TP751
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本文编号：1645055