Abstract
An airborne Ku-band frequency-modulated continuous waveform (FM-CW) profiling radar, Tomoradar, records the backscatter signal from the canopy surface and the underlying ground in the southern boreal forest zone of Finland. The recorded waveforms are transformed into canopy height profiles (CHP) with a similar methodology utilized in large-footprint light detection and ranging (LiDAR). The point cloud data simultaneously collected by a Velodyne® VLP-16 LiDAR on-board the same platform represent the frequency of discrete returns, which are also applied to the extraction of the CHP by calculating the gap probability and incremental distribution. To thoroughly explore the relationships of the CHP derived from Tomoradar waveforms and LiDAR data we utilized the effective waveforms of one-stripe field measurements and comparison them with four indicators, including the correlation coefficient, the root-mean-square error (RMSE) of the difference, and the coefficient of determination and the RMSE of residuals of linear regression. By setting the Tomoradar footprint as 20 degrees to contain over 95% of the transmitting energy of the main lobe, the results show that 88.17% of the CHPs derived from Tomoradar waveforms correlated well with those from the LiDAR data; 98% of the RMSEs of the difference ranged between 0.002 and 0.01; 79.89% of the coefficients of determination were larger than 0.5; and 98.89% of the RMSEs of the residuals ranged from 0.001 to 0.01. Based on the investigations, we discovered that the locations of the greatest CHP derived from the Tomoradar were obviously deeper than those from the LiDAR, which indicated that the Tomoradar microwave signal had a stronger penetration capability than the LiDAR signal. Meanwhile, there are smaller differences (the average RMSEs of differences is only 0.0042 when the total canopy closure is less than 0.5) and better linear regression results in an area with a relatively open canopy than with a denser canopy.
Highlights
Forest covers approximate 30% of the global land area, which plays a significant role in the natural circulation of carbon and the mitigation of climate change [1]
To describe the differences of the canopy height profile (CHP) extracted from Tomoradar waveforms (FT) and light detection and ranging (LiDAR) data (FL), a correlation coefficient (R2) and a root-mean-square error (RMSE) of the differences were computed by the following expressions: R2 =
It can be perceived that the tendency of the CHP extracted from Tomoradar waveforms are nearly similar as those from the LiDAR data, as Figure 6a,b presents
Summary
Forest covers approximate 30% of the global land area, which plays a significant role in the natural circulation of carbon and the mitigation of climate change [1]. Passive optical remote sensing systems mainly collect the reflected sunlight from the exterior canopy surface and are almost unable to acquire the information inside the canopy due to topographical occlusion, the limitation of the employed spectral range, and poor illustration conditions. They can hardly capture the vertical forest structure directly and exclusively obtain the limited characterization of the canopy structure, such as tree crown and leaf area index (LAI) [6,7,8].
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