Ye Zilin, Long Jiangping, Zhang Tingchen, Lin Bingbing, Lin Hui
Research Center of Forestry Remote Sensing & Information Engineering, Central South University of Forestry and Technology, Changsha 410004, China.
Key Laboratory of Forestry Remote Sensing Based Big Data & Ecological Security for Hunan Province, Changsha 410004, China.
Plants (Basel). 2024 Sep 7;13(17):2511. doi: 10.3390/plants13172511.
Optical remote sensing can effectively capture 2-dimensional (2D) forest information, such as woodland area and percentage forest cover. However, accurately estimating forest vertical-structure relevant parameters such as height using optical images remains challenging, which leads to low accuracy of estimating forest stocks like biomass and carbon stocks. Thus, accurately obtaining vertical structure information of forests has become a significant bottleneck in the application of optical remote sensing to forestry. Microwave remote sensing such as synthetic aperture radar (SAR) and polarimetric SAR provides the capability to penetrate forest canopies with the L-band signal, and is particularly adept at capturing the vertical structure information of forests, which is an alternative ideal remote-sensing data source to overcome the aforementioned limitation. This paper utilizes the Citexs data analysis platform, along with the CNKI and PubMed databases, to investigate the advancements of applying L-band SAR technology to forest canopy penetration and structure-parameter estimation, and provides a comprehensive review based on 58 relevant articles from 1978 to 2024 in the PubMed database. The metrics, including annual publication numbers, countries/regions from which the publications come, institutions, and first authors, with the visualization of results, were utilized to identify development trends. The paper summarizes the state of the art and effectiveness of L-band SAR in addressing the estimation of forest height, moisture, and forest stocks, and also examines the penetration depth of the L-band in forests and highlights key influencing factors. This review identifies existing limitations and suggests research directions in the future and the potential of using L-band SAR technology for forest parameter estimation.
光学遥感能够有效地获取二维（2D）森林信息，如林地面积和森林覆盖百分比。然而，利用光学图像精确估计森林垂直结构相关参数（如高度）仍然具有挑战性，这导致在估计生物量和碳储量等森林蓄积量时准确性较低。因此，准确获取森林垂直结构信息已成为光学遥感在林业应用中的一个重大瓶颈。合成孔径雷达（SAR）和极化SAR等微波遥感能够利用L波段信号穿透森林冠层，尤其擅长捕捉森林的垂直结构信息，是克服上述限制的一种理想的替代遥感数据源。本文利用Citexs数据分析平台以及中国知网和PubMed数据库，研究L波段SAR技术在森林冠层穿透和结构参数估计方面的进展，并基于PubMed数据库中1978年至2024年的58篇相关文章进行了全面综述。利用包括年度发表数量、发表文章的国家/地区、机构和第一作者等指标，并对结果进行可视化，以确定发展趋势。本文总结了L波段SAR在估计森林高度、湿度和森林蓄积量方面的现状和有效性，还研究了L波段在森林中的穿透深度，并突出了关键影响因素。本综述指出了现有局限性，并提出了未来的研究方向以及利用L波段SAR技术进行森林参数估计的潜力。
