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Forest structure dependency analysis of L-band SAR backscatter
Yongjie Ji1, Jimao Huang1, Yilin Ju2
1Southwest Forestry University, School of Geography and Ecotourism, Kunming, Yunnan, China.
Peerj
|October 16, 2020
Summary
L-band Synthetic Aperture Radar (SAR) backscatter is sensitive to forest structure, with canopy density being the most influential factor for above-ground biomass (AGB) estimation. Forest species also impact these relationships.
Area of Science:
- Remote Sensing
- Forestry Science
- Geophysics
Background:
- Forest structure significantly influences forest biomass estimation using Synthetic Aperture Radar (SAR) backscatter.
- Long-wavelength SAR sensors, particularly L-band, offer deep penetration capabilities for reliable forest biomass inversion.
- Understanding the interplay between forest structure and SAR backscatter is crucial for improving biomass estimation accuracy.
Purpose of the Study:
- To investigate the sensitivity of L-band SAR backscatter to forest structural parameters (canopy density, tree height, diameter at breast height) at the sub-compartment level.
- To analyze how forest species influence the relationship between forest structure and L-band SAR backscatter.
- To determine the most influential forest structural parameter for L-band SAR backscatter.
Main Methods:
- Analysis of L-band SAR backscatter data from 6037 forest sub-compartments.
- Utilized correlation coefficients (R, R², Maximal Information Coefficient) to assess relationships between SAR backscatter and forest structural parameters.
- Focused on the HV polarization channel for its higher sensitivity to forest structure.
Main Results:
- Canopy density demonstrated a stronger influence on L-band backscatter than mean tree height and diameter at breast height (DBH).
- High correlation (R > 0.7) was observed between canopy density and L-band backscatter throughout the forest growth cycle.
- Sensitivity of L-band backscatter to tree height was dependent on canopy density, with higher sensitivity observed at densities above 0.4.
- DBH sensitivity was most pronounced at a canopy density of 0.6.
- Forest species significantly affected the relationships between SAR backscatter and all structural parameters.
Conclusions:
- Canopy density is the primary driver of L-band SAR backscatter variations in forests, impacting above-ground biomass estimation.
- The sensitivity of L-band SAR backscatter to forest structure is modulated by canopy density and varies with tree species.
- Accurate forest biomass inversion requires considering forest structure, particularly canopy density, and accounting for species-specific responses.
