Comparison of aboveground biomass estimation from InSAR and LiDAR canopy height models in tropical forests

M. Schlund*, Stefan Erasmi, Klaus Scipal

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

8 Citations (Scopus)


The potential of interferometric synthetic aperture radar (InSAR) heights from TanDEM-X for vegetation canopy height and aboveground biomass (AGB) estimation has long been recognized. Penetration of X-band into the canopy affects these estimations. Thus, the canopy height and AGB retrieval from InSAR are typically biased and cannot be compared directly to estimates from other data sources. The objective of this letter was to apply a penetration depth model to compensate for height biases in TanDEM-X InSAR heights. The resulting canopy height estimates are subsequently converted to AGB estimates using regression models. The uncorrected InSAR heights of the forest canopy are biased due to the penetration of the signal into the canopy and differ substantially to light detection and ranging (LiDAR) canopy height estimates. The application of the penetration depth compensation results in unbiased forest canopy height estimates and AGB regression models that are comparable between InSAR and LiDAR. These results indicate that TanDEM-X InSAR and LiDAR technologies can be used to estimate AGB in complex tropical forests suggesting a synergistic use of these fundamentally different observation concepts.

Original languageEnglish
Article number8764606
Pages (from-to)367-371
Number of pages5
JournalIEEE geoscience and remote sensing letters
Issue number3
Publication statusPublished - Mar 2020
Externally publishedYes


  • Aboveground biomass (AGB)
  • forestry
  • interferometric synthetic aperture radar (InSAR)
  • light detection and ranging (LiDAR)
  • TanDEM-X
  • ITC-CV
  • n/a OA procedure


Dive into the research topics of 'Comparison of aboveground biomass estimation from InSAR and LiDAR canopy height models in tropical forests'. Together they form a unique fingerprint.

Cite this