基于无人机光学遥感的森林生物量估算研究

Forest Biomass Estimation Based on UAV Optical Remote Sensing

森林生物量(Forest biomass)是研究地球生态环境和气候变化的关键影响因子,在碳循环研究中起着决定性的作用,准确且直接地估算目标样地内森林生物量具有重大意义。为探索东北林业大学城市林业示范基地单木尺度上的生物量研究方法,获取目标样地内单一树种的生物量估算模型,得到目标树种的地上生物量。该研究利用无人机获取东北林业大学城市林业示范基地内建模样地和验证样地内的樟子松遥感影像;对无人机获取的遥感影像进行预处理,并获取建模样地(plot1)和验证样地(plot2)内所有目标样木的胸径;对影像进行分割并提取树冠信息。运用eCognition软件对无人机获取到的遥感影像进行信息提取,并进行自动的分割和分类从而提取单木树冠;将信息导入ArcGIS软件,统计出所有樟子松的树冠面积,估算样地内樟子松的生物量。结合实测胸径数据,对建模样地内的樟子松数据进行拟合,拟合出树冠面积-胸径的最优模型,并借助胸径-生物量的经验模型,得出樟子松地上生物量。研究表明运用无人机遥感技术和拟合出的最优模型可以有效估算目标样地内樟子松的地上生物量,其中,plot1的总生物量为6 315 kg;plot2的总生物量为5 802 kg。

Forest biomass is an important influencing factor in the study of global environmental and climate change, and plays an important role in the study of the carbon cycle. It is important to estimate forest biomass in a region quickly and accurately. In order to explore the biomass research method at the single-wood scale in the urban forestry demonstration base of Northeast Forestry University(NEFU), the biomass estimation model of the same tree species in the target sample site was obtained, and the above-ground biomass of the target tree species was obtained. In this paper, the Unmanned Aerial Vehicle(UAV) was used to acquire remote sensing images of Pinus sylvestris var. mongolica in the modeling and validation sample plots in the urban forestry demonstration base of NEFU. The UAV remote sensing images were pre-processed and the diameter at breast height(DBH) of all Pinus sylvestris var. mongolica in the modeling and validation plots(Plot1 and Plot2) was measured. The images were segmented and crown information was extracted. The eCognition software was used to extract the information from the remote sensing images and to automatically segment and classify the single tree crowns. The information was imported into ArcGIS software and the crown area of all the Pinus sylvestris var. mongolica was counted. The above-ground biomass of Pinus sylvestris var. mongolica in the sample plots was estimated. Combined with the measured DBH data, the model was fitted to the Pinus sylvestris var. mongolica data in the sample plots, and an optimal model of crown area-DBH was fitted. With the help of the empirical model of DBH-biomass, the above-ground biomass of Pinus sylvestris var. mongolica was derived. The results showed that the above-ground biomass of Pinus sylvestris var. mongolica in the target sample plots can be effectively estimated by using UAV remote sensing technology and the fitted optimal model. The total biomass of the modeling plot1 was 6 315 kg and the validation plot2 was 5 802 kg.