基于无人机影像可见光植被指数的若尔盖草地地上生物量估算研究

地上生物量是衡量草地长势及生态系统服务功能的重要参数,对于草地生态系统碳收支、资源可持续开发等研究具有重要意义。研究基于若尔盖高原典型样带的无人机可见光影像和地面实测样本,建立生物量与多种可见光植被指数的指数回归模型,对比不同植被指数模型的生物量估算精度的差异。结果表明:可见光植被指数能够有效区分草地和其他覆盖类型,生物量与植被指数具有较好的相关关系。但基于不同波段建立的植被指数对生物量的估算精度存在差异,其中利用红、绿波段建立的植被指数NGRDI模型对生物量具有最高的模拟精度(R~2=0.856)和预测精度(验证样本ABE=94g/m~2,RMSE=124g/m~2)。研究获取了高空间分辨率的草地地上生物量,相关成果可为若尔盖高原碳收支、卫星遥感产品真实性检验、生态模型、资源可持续利用等研究提供方法与数据支撑。

Estimating Aboveground Biomass of Grassland in Zoige by Visible Vegetation Index Derived from Unmanned Aerial Vehicle Image

Aboveground biomass is an essential parameter for estimating the growth trend and ecosystem services of grassland.It is important to correctly evaluate biomass for grassland ecosystem carbon budget and sustainable development of resources.In this study,the field measurements and synchronous observations from UAV were combined to estimate the aboveground biomass of grassland.Based on the “valley\|peak\|valley” morphological features of green vegetation in the visible band reflectance,multiple types of vegetation indices were constructed.Then,the regression models between the fresh weight of grassland and vegetation indices were established.Accuracy analysis showed that visible vegetation indices had the potential to distinguish grassland from others and the correlation between biomass of grassland and vegetation indices was strong.The highest estimation accurate model was provided by NGRDI which derived from red and blue band,and the RMSE and R² were 124 g/m² and 0.856,respectively.The prediction accuracy of the regression model with the same band combination was stable,regardless of the fitting methods Among the different regression models.The results of this study was anticipated to support the research of carbon budget and validation of remote sensing products researches in Zoige.