School of Forestry, Northeast Forestry University, Harbin, China.
Key Laboratory of Sustainable Forest Ecosystem Management-Ministry of Education, School of Forestry, Northeast Forestry University, Harbin, China.
Environ Monit Assess. 2020 Oct 29;192(11):734. doi: 10.1007/s10661-020-08694-4.
Forest age is an important stand description factor and plays an important role in the carbon cycle of forest ecosystems. However, forest age data are typically lacking or are difficult to acquire at large spatial scale. Thus, it is important to develop a method of spatial forest age mapping. In this study, a method of forest age estimation based on multiple-resource remote sensing data was developed. Forest age was estimated by using average tree height estimated from the ICESat/GLAS and MODIS BRDF products. The results showed that forest age was significantly related to average tree height with a correlation coefficient of 0.752. Then, the average tree height was inversed using a waveform parameter extracted from ICESat/GLAS and was extended to continuous space with the help of the MODIS BRDF product. Thus, forest age mapping was realized. Lastly, the structure of forest age in the study area was evaluated. The results indicated that this method can be used to estimate forest age at the local scale and at large scale and can facilitate understandings of the real forest age structure features of a research area.
森林年龄是一个重要的林分描述因子，在森林生态系统的碳循环中起着重要作用。然而，森林年龄数据通常缺乏或难以在大空间尺度上获取。因此，开发一种空间森林年龄制图的方法是很重要的。在本研究中，开发了一种基于多源遥感数据的森林年龄估算方法。利用 ICESat/GLAS 和 MODIS BRDF 产品估算的平均树高来估算森林年龄。结果表明，森林年龄与平均树高显著相关，相关系数为 0.752。然后，利用从 ICESat/GLAS 中提取的波形参数反演平均树高，并借助 MODIS BRDF 产品将其扩展到连续空间。因此，实现了森林年龄制图。最后，评估了研究区的森林年龄结构。结果表明，该方法可用于局部和大尺度估算森林年龄，有助于了解研究区真实的森林年龄结构特征。
