remote sensing

TanDEM-X elevation model data for canopy height and aboveground biomass retrieval in a tropical peat swamp forest

Michael Schlund a*, Felicitas von Poncet b, Steffen Kuntz  b, Hans-Dieter Viktor Boehm c, Dirk H. Hoekman d and Christiane Schmullius a

a Department of Earth Observation, Friedrich-Schiller-University Jena, Jena, Germany; b Airbus Defence and Space, Immenstaad, Germany; c Kalteng Consultants, Hoehenkirchen, Germany; d Department of Environmental Sciences, Wageningen University, Wageningen, The Netherlands

INTERNATIONAL JOURNAL OF REMOTE SENSING, 2016, VOL. 37, NO. 21, 5021–5044

/userfiles/htmleditor//TanDEM X elevation model data for canopy height and aboveground biomass retrieval in a tropical peat swamp forest.pdf

ABSTRACT

It was demonstrated in the past that radar data is useful to estimate aboveground biomass due to their interferometric capability.

Therefore, the potential of a globally available TanDEM-X digital elevation model (DEM) was investigated for aboveground

biomass estimation via canopy height models (CHMs) in a tropical peat swamp forest. However, CHMs based on X-band interferometers

usually require external terrain models. High accurate terrain models are not available on global scale. Therefore, an approach

exclusively based on TanDEM-X and the decrease of accuracy compared to an approach utilizing a high accurate terrain model

is assessed. In addition, the potential of X-band interferometric heights in tropical forests needs to be evaluated. Therefore, two

CHMs were derived from an intermediate TanDEM-X DEM (iDEM; as a precursor for WorldDEMTM) alone and in combination with

lidar measurements used as terrain model. The analysis showed high accuracies (root mean square error [RMSE] = 5 m) for CHMs

based on iDEM and reliable estimation of aboveground biomass.

The iDEM CHM, exclusively based on TanDEM-X, achieved a poor R2 of 0.2, nonetheless resulted in a cross-validated RMSE of 54

t ha−1 (16%). The low R2 suggested that the X-band height alone was not sufficient to estimate an accurate CHM, and thus the need

for external terrain models was confirmed. A CHM retrieved from the difference of iDEM and an accurate lidar terrain model

achieved a considerably higher correlation with aboveground biomass (R2 = 0.68) and low cross-validated RMSE of 24.5 t ha−1

(7.5%). This was higher or comparable to other aboveground biomass estimations in tropical peat swamp forests. The potential

of X-band interferometric heights for CHM and biomass estimation was thus confirmed in tropical forest in addition to existing knowledge

in boreal forests.

1. Introduction

It is a prerequisite to estimate the aboveground biomass and its change over time to

implement programmes, such as reducing emissions from deforestation and degradation

(REDD+), where the reduction of carbon emission from deforestation and degradation

and the enhancement of carbon stocks are incentivized. This could support climate

change mitigation (Van der Werf et al. 2009; Gibbs et al. 2007; Olander et al. 2008).

Tropical peat swamp forests and their soils play a significant role in the global carbon

cycle because their carbon emissions equal one-fourth of total emissions from tropical

forests despite their relatively small extent compared to the overall tropical forests (Page

et al. 2002; Page, Rieley, and Banks 2011; Van der Werf et al. 2009; Lawson et al. 2015).

Estimating forest canopy height and subsequently biomass is considered high potential

for large scale biomass estimations (Chavez et al. 2005; Koch 2010; Lefsky et al. 2002;

Saatchi et al. 2011; Asner et al. 2009). A frequently used method is to produce a digital

surface model (DSM) and by subtracting a digital terrain model (DTM) deriving a canopy

height model (CHM). The CHM represents the vegetation height as well as the canopy

surface, whereas the canopy surface represents the crown topography, which can be

used, e.g. for single tree detection (Koch, Heyder, and Weinacker 2006). The vegetation

height is frequently used to estimate the biomass in combination with field measured

data, whereas the capability of airborne as well as space borne lidar was demonstrated

(Boehm, Liesenberg, and Limin 2013; St-Onge, Hu, and Vega 2008; Dandois and Ellis

2013; Simard et al. 2011; Lefsky et al. 2005; Rosette, North, and Suárez 2008; Drake et al.

2002).

The Geoscience Laser Altimeter System (GLAS) on board of the ice, cloud, and land

elevation satellite (ICESat) was a space borne lidar, which was used to extract vegetation

height profiles from the laser signal estimating forest height accurately (Lefsky et al.

2005; Rosette, North, and Suárez 2008; Simard et al. 2011). ICESat acquired data not

continuously but on ca. 65 m diameter footprints with a distance of 170 m along track

and in the order of kilometres across track (Abdalati et al. 2010; Simard et al. 2011).

Consequently, spatial sampling schemes are required for this space borne system to

achieve continuous mapping results (Simard et al. 2011). The estimated canopy height

from ICESat GLAS was further utilized with external data to estimate aboveground

biomass on pan-tropical scale (Baccini et al. 2008; Saatchi et al. 2011). Today, lidar

campaigns are mostly airborne, especially after the failure and retirement of ICESat

GLAS, and thus lidar campaigns are cost-intensive compared to space borne systems

(Köhl et al. 2011; Koch 2010). Subsequently, aboveground biomass estimations via

airborne lidar sensors are applicable mainly for small spatial coverage or should be

integrated in sampling schemes for large area applications (Asner et al. 2009).