Abstract

Profile radar allows direct characterization of the vertical forest structure. Short-wavelength, such as Ku or X band, microwave data provide opportunities to detect the foliage. In order to exploit the potential of radar technology in forestry applications, a helicopter-borne Ku-band profile radar system, named Tomoradar, has been developed by the Finnish Geospatial Research Institute. However, how to use the profile radar waveforms to assess forest canopy parameters remains a challenge. In this study, we proposed a method by matching Tomoradar waveforms with simulated ones to estimate forest canopy leaf area index (LAI). Simulations were conducted by linking an individual tree-based forest gap model ZELIG and a three-dimension (3D) profile radar simulation model RAPID2. The ZELIG model simulated the parameters of potential local forest succession scene, and the RAPID2 model utilized the parameters to generate 3D virtual scenes and simulate waveforms based on Tomoradar configuration. The direct comparison of simulated and collected waveforms from Tomoradar could be carried out, which enabled the derivation of possible canopy LAI distribution corresponding to the Tomoradar waveform. A 600-m stripe of Tomoradar data (HH polarization) collected in the boreal forest at Evo in Finland was used as a test, which was divided into 60 plots with an interval of 10 m along the trajectory. The average waveform of each plot was employed to estimate the canopy LAI. Good results have been found in the waveform matching and the uncertainty of canopy LAI estimation. There were 95% of the plots with the mean relative overlapping rate (RO) above 0.7. The coefficients of variation of canopy LAI estimates were less than 0.20 in 80% of the plots. Compared to lidar-derived canopy effective LAI estimation, the coefficient of determination was 0.46, and the root mean square error (RMSE) was 1.81. This study established a bridge between the Ku band profile radar waveform and the forest canopy LAI by linking the RAPID2 and ZELIG model, presenting the uncertainty of forest canopy LAI estimation using Tomoradar. It is worth noting that since the difference of backscattering contribution is caused by both canopy structure and tree species, similar waveforms may correspond to different canopy LAI, inducing the uncertainty of canopy LAI estimation, which should be noticed in forest parameters estimation with empirical methods.

Highlights

  • Leaf area index (LAI), defined as half the total leaf area per unit of the horizontal ground surface area [1], is an essential indicator for forest ecosystem assessment and management

  • This study demonstrated an approach for estimating the canopy LAI using Ku-band profile radar waveforms with the waveform matching method based on linking the 3D

  • We proposed a method of linking the 3D radiative transfer model RAPID2 and forest gap model ZELIG to estimate canopy LAI using profile radar waveform, which is analogously used in large-footprint waveform lidar [25,39,42]

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Summary

Introduction

Leaf area index (LAI), defined as half the total leaf area per unit of the horizontal ground surface area [1], is an essential indicator for forest ecosystem assessment and management. Forest LAI reflects the growth status of the forest. It is closely related to the photosynthesis, respiration, and transpiration of the forest [2]. LAI has been used as an input of ecological models and climate models as well [3,4,5]. 2021, 13, 297 plays a major role in forestry and ecology research. Remote sensing is generally utilized to retrieve forest LAI in large areas [2,6]

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