文献类型：期刊文献

中文题名：基于无人机影像VDVI指数的植被覆盖度估算--以陕西神木防护林工程研究区为例

英文题名：Estimation of Vegetation Coverage Based on VDVI Index of UAV Visible Image——Using the Shelterbelt Research Area as An Example

作者：凌成星[1,2] 刘华[1,2] 纪平[1] 胡鸿[3] 王晓慧[1,2] 侯瑞霞[1]

第一作者：凌成星

机构：[1]中国林业科学研究院资源信息研究所,北京100091;[2]国家林业和草原局林业遥感与信息技术重点实验室,北京100091;[3]国家林业和草原局调查规划设计院,北京100714

年份：2021

卷号：37

期号：2

起止页码：57-66

中文期刊名：森林工程

外文期刊名：Forest Engineering

收录：CSTPCD;;北大核心:【北大核心2020】；

基金：国家重点研发计划课题(2017YFC0506502)。

语种：中文

中文关键词：无人机;CCD传感器;植被覆盖度;植被指数

外文关键词：UAV;CCD sensor;vegetation coverage;vegetation index

分类号：S812

摘要：为快速准确获取防护林工程区植被覆盖度特征,掌握植被生长和生态环境评价重要指标,利用无人机高时间频率获取、高空间分辨率的特点,在陕西神木的三北工程樟子松防护林研究区进行实验,构建无人机可见光RGB波段差异性植被指数(VDVI)和HSV变换植被指数(HSVVI),并与同区域GF-1卫星NDVI指数进行相关性分析,建立无人机研究区的植被覆盖度估算模型,快速计算出植被覆盖度结果。研究表明,VDVI指数与NDVI指数具有更高的相关性,非常适用于像元二分模型的植被覆盖度估算模型建立,通过地面调查的植被覆盖度实测值与模型估算值精度验证,决定系数R 2为0.8556,植被覆盖度估算精度达到81.35%,在研究区域得到较为理想的估算结果。由此也证明采用无人机影像可见光数据构建VDVI指数像元二分模型进行植被覆盖度估算是有效和准确的,可以为快速获取植被覆盖度特征服务。
In order to quickly and accurately obtain the characteristics of vegetation coverage in the shelterbelt project area and master the important indicators of vegetation growth and ecological environment evaluation,experiments were carried out in the research area of Pinus sylvestris var.mongolica shelterbelt in Shenmu,Shanxi Province by using the characteristics of high time frequency acquisition and high spatial resolution of UAV.Different Vegetation Index(VDVI)and HSV Transform Vegetation Index(HSVVI)in RGB band of UAV visible light were constructed,and correlation analysis was conducted with the NDVI index of GF-1 satellite in the same region.Vegetation coverage estimation model was established in the UAV study area,and the results of vegetation coverage were quickly calculated.The results showed that VDVI index and NDVI index had a higher correlation,which was very suitable for the establishment of vegetation coverage estimation model of pixel binary model.Through the accuracy verification of the measured FVC value and the model estimation value,the determination coefficient R 2 was 0.8556,and the estimation accuracy of FVC was 81.35%,which was an ideal estimation result in the study area.It was also proved that the VDVI index pixel binary model based on visible light data of UAV images was effective and accurate for vegetation coverage estimation,which could serve for the rapid acquisition of vegetation coverage characteristics.