# Tropical-Forest Structure and Biomass Dynamics from TanDEM-X Radar Interferometry

^{1}

Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA

^{2}

Canopy Remote Sensing Solutions, Florianópolis, SC 88032, Brazil

^{3}

US Forest Service, International Institute of Tropical Forestry, Rio Piedras 00926, Puerto Rico

^{4}

EMBRAPA, Agricultural Informatics, Campinas, SP 13083, Brazil

^{5}

Instituto Nacional de Pesquisas Espaciais, Sao Jose dos Campos, SP 12227, Brazil

^{6}

Amazon, Seattle, WA 98109, USA

^{7}

Departamento de Engenharia Agrícola, Universidade Federal de Sergipe, SE 49100, Brazil

^{*}

Author to whom correspondence should be addressed.

Received: 24 May 2017 / Revised: 24 June 2017 / Accepted: 15 July 2017 / Published: 31 July 2017

(This article belongs to the Special Issue Remote Sensing of Forest Disturbance)

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.