Logo Lanfrica
  • Accueil
  • Atlas
  • Analyses
  • Documentation
  • Sign in

© 2026 Lanfrica. Tous droits réservés. Tous les droits d'auteur des ressources affichées sur le site Web Lanfrica appartiennent aux détenteurs de droits d'auteur d'origine, sauf indication contraire explicite.

Forest Height Estimation by Means of TanDEM-X InSAR and Waveform Lidar Data

Domaine:

geospatialenvironment and energy

Type de record:

paper
Créateur:
GulCazParPap
Éditeur:
ETH
Hôte:avatar
Model-based forest height inversion from Pol-InSAR data relies on the realistic parameterization of the underlying (vertical) radar reflectivity function. In the context of interferometric TanDEM-X measurements – especially in the global single pol DEM mode – this is not possible due to the limited dimensionality of the observation space. In order to overcome this, the use of lidar waveforms to directly approximate the TanDEM-X reflectivity is proposed. This allows the forest height estimation from a single, single polarimetric, bistatic TanDEM-X acquisition. In order to extend the proposed lidar-supported inversion schema to areas only partially covered or sampled by (waveform) lidar measurements, the use of a “mean” (vertical) reflectivity profile is further proposed. This “mean” reflectivity profile is defined by means of the eigenfunctions of the available set of lidar waveforms. Both approaches are demonstrated and validated using TanDEM-X and airborne waveform lidar data acquired in the framework of the AfriSAR 2016 campaign over the Lopé National Park, in Gabon. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14 ISSN:1939-1404 ISSN:2151-1535

Visit

doi.orghdl.handle.net

Tags

Forest height estimationSAR interferometryTanDEM-Xvertical radar reflectivitywaveform lidar

Licenses

Creative Commons Attribution 4.0 Internationalhttps://creativecommons.org/licenses/by/4.0/legalcodeinfo:eu-repo/semantics/openAccess

Similaires

Country-Scale Mapping Of Forest Parameters Using Deep Learning And Tandem-X Insar DataImproving Forest Height-To-Biomass Allometry With Structure Information: A Tandem-X StudyMapping Tree Height in Burkina Faso Parklands with TanDEM-XEarthquake-induced landslide monitoring and survey by means of InSARCharacterizing tree species diversity in the tropics using full-waveform lidar dataModelling Canopy Height of Forest-Savannah Mosaics in Togo Using ICESat-2 and GEDI Spaceborne LiDAR and Multisource Satellite Data

Country-Scale Mapping Of Forest Parameters Using Deep Learning And Tandem-X Insar Data

International audience Highly accurate estimates of canopy height (CH) and above grou

Improving Forest Height-To-Biomass Allometry With Structure Information: A Tandem-X Study

Allometric relations that link forest above ground biomass to top forest (i.e., canopy) height are o

Mapping Tree Height in Burkina Faso Parklands with TanDEM-X

Mapping of tree height is of great importance for management, planning, and research related to agro

Earthquake-induced landslide monitoring and survey by means of InSAR

International audience Abstract. This study uses interferometric synthetic aperture r

Characterizing tree species diversity in the tropics using full-waveform lidar data

Tree species diversity is of paramount value to maintain forest health and to ensure that forests ar

Modelling Canopy Height of Forest-Savannah Mosaics in Togo Using ICESat-2 and GEDI Spaceborne LiDAR and Multisource Satellite Data

Quantifying forest carbon storage to better manage climate change and its effects requires accurate