Tropical forest biomass estimation based on the structure of the canopy is a burgeoning and crucial remote sensing capability for balancing terrestrial carbon budgets. This paper introduces a new approach to structural biomass estimation based on the Fourier transform of vertical profiles from lidar or interferometric SAR (InSAR). Airborne and field data were used from 28 tropical wet forest stands at La Selva Biological Station, Costa Rica, with average biomass of 229 Mg‐ha⁻¹. RMS scatters of remote sensing biomass estimates about field measurements were 58.3 Mg‐ha⁻¹, 21%, and 76.1 Mg‐ha⁻¹, 26%, for lidar and InSAR, respectively. Using mean forest height, the RMS scatter was 97 Mg‐ha⁻¹, ≈34% for both lidar and InSAR. The confidence that Fourier transforms are a significant improvement over height was >99% for lidar and ≈90% for InSAR. Lidar Fourier transforms determined the useful range of vertical wavelengths to be 14 m to 100 m.

Changes in tropical-forest structure and aboveground biomass (AGB) contribute directly to atmospheric changes in CO${}_2$ , which, in turn, bear on global climate. This paper demonstrates the capability of radar-interferometric phase-height time series at X-band (wavelength = 3 cm) to monitor changes in vertical structure and AGB, with sub-hectare and monthly spatial and temporal resolution, respectively. The phase-height observation is described, with a focus on how it is related to vegetation-density, radar-power vertical profiles, and mean canopy heights, which are, in turn, related to AGB. The study site covers $18\times 60$ km in the Tapajós National Forest in the Brazilian Amazon. Phase-heights over Tapajós were measured by DLR’s TanDEM-X radar interferometer 32 times in a 3.2 year period from 2011–2014. Fieldwork was done on 78 secondary and primary forest plots. In the absence of disturbance, rates of change of phase-height for the 78 plots were estimated by fitting the phase-heights to time with a linear model. Phase-height time series for the disturbed plots were fit to the logistic function to track jumps in phase-height. The epochs of clearing for the disturbed plots were identified with ≈1-month accuracy. The size of the phase-height change due to disturbance was estimated with ≈2-m accuracy. The monthly time resolution will facilitate REDD+ monitoring. Phase-height rates of change were shown to correlate with LiDAR RH90 height rates taken over a subset of the TanDEM-X data’s time span (2012–2013). The average rate of change of phase-height across all 78 plots was 0.5 m-yr ${}^{-1}$ with a standard deviation of 0.6 m-yr ${}^{-1}$ . For 42 secondary forest plots, the average rate of change of phase-height was 0.8 m-yr ${}^{-1}$ with a standard deviation of 0.6 m-yr ${}^{-1}$ . For 36 primary forest plots, the average phase-height rate was 0.1 m-yr ${}^{-1}$ with a standard deviation of 0.5 m-yr ${}^{-1}$ . A method for converting phase-height rates to AGB-rates of change was developed using previously measured phase-heights and field-estimated AGB. For all 78 plots, the average AGB-rate was 1.7 Mg-ha ${}^{-1}$ -yr ${}^{-1}$ with a standard deviation of 4.0 Mg-ha ${}^{-1}$ -yr ${}^{-1}$ . The secondary-plot average AGB-rate was 2.1 Mg-ha ${}^{-1}$ -yr ${}^{-1}$ , with a standard deviation of 2.4 Mg-ha ${}^{-1}$ -yr ${}^{-1}$ . For primary plots, the AGB average rate was 1.1 Mg-ha ${}^{-1}$ -yr ${}^{-1}$ with a standard deviation of 5.2 Mg-ha ${}^{-1}$ -yr ${}^{-1}$ . Given the standard deviations and the number of plots in each category, rates in secondary forests and all forests were significantly different from zero; rates in primary forests were consistent with zero. AGB-rates were compared to change models for Tapajós and to LiDAR-based change measurements in other tropical forests. Strategies for improving AGB dynamical monitoring with X-band interferometry are discussed.

This paper proposes the correlation of biomass with Fourier transforms of LiDAR and InSAR vegetation density measurements at vertical and horizontal Fourier spatial frequencies, as a means to estimate biomass. It further suggests that each Fourier frequency of leaf area density could be modeled as a harmonic oscillator, in which leaf area itself provides a restoring force to constrain it to some nominal value. Preferred Fourier frequencies for tropical forest stands at La Selva Biological Station, Costa Rica, with vertical wavelengths of 12 to 18 m and 5-7m are shown from LIDAR as an update to previous work. These two wavelengths are close to the average height and crown depth of forest stands measured. As an example of different kinds of modeling, it is suggested that biomass be considered a complex quantity with amplitude representing the usual biomass, and the phase representing some undetermined characteristic of the forest. Finally, since structure-based biomass estimation will presumably improve with signal penetration, a diffraction calculation of penetration through holes at L- and C-band shows that the diffractive component of penetration from C-band is greater than or equal to that at L-band, countering to some extent the lower penetration at C-band due to the frequency dependence of water's extinction.