遥感技术能够大面积覆盖和动态监测森林冠层叶片特征,森林乔木层地上生物量(AGB)与叶生物量之间存在良好的统计关系,根据遥感数据提取森林有效叶面积指数(LAIe)以估算叶生物量、进而估算AGB是可行的。然而,利用遥感数据提取森林LAIe时会受到林下植被等背景信息的影响。因此,论文以我国东北大兴安岭林区为研究区,利用中分辨率成像光谱仪(MODIS)数据和四尺度模型定量研究森林背景反射率对冠层LAIe和乔木层AGB遥感估算的影响。结果表明:背景反射率对森林LAIe遥感反演和 AGB估算影响显著,利用遥感数据提取的背景反射率对背景影响订正后,反演的LAIe与基于高分辨率专题制图仪(TM)影像反演出的LAIe之间的相关性明显提高,决定系数(R²)由0.32(n=25,p<0.10)增大到0.48(n=25,p<0.01),遥感估算的AGB与利用森林一类清查数据估算的AGB之间R²由0.52(n=10,p<0.05)上升到0.86(n=10,p<0.01),LAIe和AGB高估现象得到明显纠正。

Remote sensing technology is of great importance to estimating large-scale forest canopy leaf characteristics dynamically,and there is a good statistical relationship between forest aboveground biomass (AGB) and leaf biomass.It is feasible to estimate leaf biomass and then AGB based on canopy effective leaf area index (LAIe) estimated from remotely sensed data.However,the forest background information,such as understory vegetation,has a negative influence on LAIe and AGB retrieval by this way.Therefore,this paper focused on exploring the impacts of forest background reflectance on LAIe and AGB inversion in the Great Khingan forest area using moderate resolution imaging spectroradiometer (MODIS) data and a four scale model.The results showed that both LAIe and AGB were sensitive to the forest background reflectance.The determinate coefficient (R²) between MODIS-and Landsat thematic mapper (TM)-based LAIe increased from 0.32 (n=25,p<0.1) to 0.48 (n=25,p<0.01) when eliminating the influence of background reflectance on LAI inversion.Also,the AGB estimates were more related to the national forest inventory (NFI)-based AGB after considering the effects of forest background (R²=0.86,n=10,p<0.01).Forest LAI and AGB overestimation could be put right in this research.