森林地上生物量遥感估算研究综述
郝晴, 黄昌

A review of forest aboveground biomass estimation based on remote sensing data
HAO Qing, HUANG Chang
表3 使用光学遥感、合成孔径雷达(SAR)和激光雷达(LiDAR)估算生物量对比
Table 3 Biomass estimation comparison using optical remote sensing, synthetic aperture radar (SAR) and light detection and ranging (LiDAR)
遥感类型
Sensor type
优势
Advantage
不足
Disadvantage
光学遥感
Optical remote sensing
光谱信息丰富, 易得多种时空分辨率影像, 可用于不同尺度的生物量估算研究。数据提取方法较简便, 结果可视化程度较高
Spectral information is abundant, and various spatial and temporal resolution images are easily available, which can be used for biomass estimation research at different scales. The data extraction methods are relatively straightforward, and the results can be visualized to a high degree
光学传感器易受天气影响, 遥感信号难以到达植被冠层之下, 不能有效反映森林的垂直结构信息, 且受植被密度影响而易导致光饱和现象
Optical sensors are susceptible to weather conditions, and remote sensing signals struggle to penetrate beneath the vegetation canopy, thus failing to effectively capture vertical structural information of forests. Additionally, optical sensors are prone to saturation effects due to variations in vegetation density
SAR 能与树叶、树干和树冠发生作用, 成像受云雨影响小, 可快速获取大区域、全覆盖的影像, 对生物量敏感
SAR can interact with leaves, tree trunks, and canopies, with minimal impact from clouds and rain. It can rapidly acquire large-area, full-coverage images and is highly sensitive to biomass measurements
SAR影像来源相对较少, 数据处理较为复杂, 受地形和土壤条件影响较大, 后向散射系数估算存在饱和性
SAR images have relatively limited data sources and require more complex data processing. They are significantly influenced by terrain and soil conditions. Estimating the backscattering coefficient in SAR images can be subject to saturation effects
LiDAR LiDAR数据的空间分辨率较高, 不仅能够获取森林的垂直结构信息, 而且还克服了信号饱和的局限性
LiDAR data possesses a high spatial resolution, enabling the acquisition of vertical structural information of forests. Moreover, LiDAR data overcomes the limitations of signal saturation
成本较高, 缺乏历史数据, 具体模型方法受研究区域限制; 机载LiDAR在大尺度空间上采样不连续, 无法达到无缝覆盖, 波形受林下地形和树木空间结构影响较大
LiDAR technology is associated with higher costs and lacks historical data. The specific models and methods may be limited by the research area. Airborne LiDAR suffers from discontinuous sampling at large spatial scales, making it challenging to achieve seamless coverage. The LiDAR waveform is greatly affected by the understory terrain and spatial structure of trees