基于无人机与卫星遥感的草原地上生物量反演研究

草原生物量是评价草原生态系统功能的重要参数.为了快速、准确、有效地估算草原地上生物量,以呼伦贝尔草原为研究区,基于无人机多光谱影像和卫星遥感(Sentinel-2)影像,选择GNDVI、LCI、NDRE、NDVI、OSAVI、EVI等6个植被指数,结合实测地上生物量数据,建立植被指数回归模型,并采用留一法交叉验证进行精...

Research of Grassland Aboveground Biomass Inversion based on UAV and Satellite Remoting Sensing

Grassland biomass is an important parameter to evaluate the grassland ecosystem function. To estimate the grassland aboveground biomass rapidly， accurately and effectively， six vegetation indices （GNDVI， LCI， NDRE， NDVI， OSAVI and EVI） were selected and calculated based on UAV multi-spectral images and satellite remote sensing （Sentinel-2） images， combined with the ground measured biomass data. The vegetation index regression model was established， and the precision was verified by the left one method. The results showed that the accuracy of LCI-biomass regression model （RRMSE = 18%， the measured and predicted R² = 0.70） and NDRE-biomass model （RRMSE = 18%， the measured and predicted R² = 0.71） based on UAV multi-spectral images was higher than that of other vegetation -biomass models. The biomass-vegetation index models based on UAV multi-spectral images （RRMSE lower than 22%） have better simulation accuracy than Sentinel-2 biomass-vegetation index models （RRMSE higher than 25%）， which can more accurately retrieve the aboveground biomass of Hulunbuir grassland. The results can provide scientific methods and basis for accurate retrieval of grassland biomass.