Component Forest Above Ground Biomass Estimation Using Lidar and Sardata

Zeng, Peng; Shi, Jianmin; Huang, Jimao; Zhang, Yongxin; Zhang, Wangfei

doi:10.1109/igarss46834.2022.9883852

Cited by 1 publication

(1 citation statement)

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“…Optical remote sensing, the most widely used type, is susceptible to weather influences and prone to the "saturation" phenomenon in high-biomass areas [10]. Conversely, SAR remote sensing overcomes weather-related limitations, providing insights into the forest canopy level and vertical structure, making it a promising data source for biomass inversion [12]. However, SAR's effectiveness varies with different wavelengths, each having its own saturation points [10].…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Research Status of the Remote Sensing-Mediated Monitoring of Forest Biomass: A Bibliometric Analysis of WOS

Shi,

Wang,

Zhang

et al. 2024

Forests

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Forests serve as the largest carbon reservoir in terrestrial ecosystems, playing a crucial role in mitigating global warming and achieving the goal of “carbon neutrality”. Forest biomass is intrinsically related to carbon sinks and sources in forest ecosystems, and thus, the accurate monitoring of forest biomass is of great significance in ensuring ecological security and maintaining the global carbon balance. Significantly, remote sensing is not only able to estimate forest biomass at a large spatial scale but does so quickly, accurately, and without loss. Moreover, it can obtain forest biomass in areas inaccessible to human beings, which have become the main data source for forest biomass estimation at present. For this reason, this study analyzes the current research status, research hotspots, and future research trends in the field of remote sensing monitoring of forest biomass based on 1678 forest biomass remote sensing monitoring results from 1985 to 2023 obtained from the Web of Science Core Collection database. The results showed that the following: (1) The number of publications showed an exponential upward trend from 1985 to 2023, with an average annual growth rate of 2.64%. The top ten journals contributed to 53.76% of the total number of publications and 52.89% of the total number of citations in the field. (2) In particular, Remote Sensing of Environment has maintained a leading position in the field for an extended period, boasting the highest impact factor. Additionally, the author Saatchi S. stands out with the highest total number of citations for articles. (3) Keyword clustering analysis revealed that the main research topics in the remote sensing monitoring of forest biomass can be categorized into the following: optical remote sensing, LiDAR remote sensing, SAR remote sensing, and carbon stock. The explosion of keywords in the last six years indicates that an increasing number of researchers are focusing on carbon, airborne LiDAR data, biomass mapping, and constructing optimal biomass models.

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Section: Introductionmentioning

confidence: 99%