Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data

Berninger, Anna; Lohberger, Sandra; Zhang, Devin und Siegert, Florian (2019): Canopy Height and Above-Ground Biomass Retrieval in Tropical Forests Using Multi-Pass X- and C-Band Pol-InSAR Data. In: Remote Sensing, Bd. 11, Nr. 18, 2105

Abstract

Indonesia's landscape is strongly characterized by degradation and deforestation, which results in carbon release. This makes Indonesia one of the largest carbon sources worldwide. The study at hand, investigates monitoring of canopy height and above-ground biomass (AGB) from space in Indonesian tropical forests. Using data from 2015, the canopy height and AGB were modelled in Kalimantan based on quad-pol Pol-InSAR data from RADARSAT-2 (RS-2) and dual-pol Pol-InSAR data from TerraSAR-X (TS-X). Novel algorithms utilizing the Random Volume over Ground (RVoG) interferometric model and the Random Motion over Ground (RMoG) interferometric model were tested to obtain a more accurate and robust forest parameter estimation during dry weather conditions. As a reference for modelling canopy height and AGB, extensive field inventory as well as LiDAR and drone data collected in Kalimantan were used. The RMoG model-based height inversion algorithm led to more accurate results for canopy height than the RVoG model. Using RS-2 imagery, the independent validation displayed a coefficient of determination (R-2) of 0.63 and a slight overestimation for the modelled canopy height. The modelled canopy height from TS-X data achieved an R-2 of up to 0.66 and resulted in underestimated modelled canopy height. The resulting AGB estimation based on the modelled canopy height resulted in an R-2 of 0.83 for RS-2 data and 0.84 for TS-X data. The results of the different tested images varied since the acquisition parameters and the weather conditions changed during acquisitions. It can be concluded, that not all RS-2 and TS-X data is suitable for modelling canopy height from coherence. The parameters that most affect the canopy height model were identified as the baselines (temporal and perpendicular), HoA (height of ambiguity), incident angle and moist weather conditions, as well as the wavelength. Ascending and descending flight directions did not display influence. Globally available high-resolution information about canopy height and AGB is important for carbon accounting. The present study showed that Pol-InSAR data from TS-X and RS-2 could be used together with field inventories and high-resolution data such as drone or LiDAR data to support the carbon accounting in the context of REDD+ (Reducing Emissions from Deforestation and Forest Degradation) projects.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Biologie
• Themengebiete: 500 Naturwissenschaften und Mathematik > 570 Biowissenschaften; Biologie
• Sprache: Englisch