Recently, the German TanDEM-X mission provided valuable acquisitions for developing models for the single-pass single-pol X-band forest height inversion. In this paper, the assessment of the two machine learning approaches to estimate forest height from the interferometric coherence are investigated and compared to the state-of-art physical models over Gabon. The contribution of this work is toward the analysis of two approaches: Approach 1 is an implementation of a conventional ML approach. Approach 2 is the first attempt to integrate model-based knowledge in the ML approach and use a single input variable
In this work we provide basic building blocks for semi-empirical models to be applied mainly for for...
In this paper, forest change detection and forest height estimation are studied using two-level mode...
Forest height is an important variable for modeling terrestrial carbon storage and global carbon cyc...
Model-based (PM) forest height inversion from Polarimetric Interferometric Synthetic Aperture Radar ...
In the realm of artificial intelligence, specifically utilizing methodologies such as machine learni...
Model-based forest height inversion from Pol-InSAR data relies on the realistic parameterization of ...
In this study we compare semi-empirical interferometric coherence models, proposed in [1], for tree ...
Recent TanDEM-X experiments have shown that forest height can be estimated with the single polarizat...
This paper evaluates the potential of forest height estimation from a Dual-Pol InSAR observation vec...
Allometric relations that link forest above ground biomass to top forest (i.e. canopy) height are of...
International audienceThe Random Volume over Ground (RVoG) model has been extensively applied to pol...
In this study, four models describing the interferometric coherence of the forest vegetation layer a...
This paper proposes an improved model-based forest height inversion method for airborne L-band dual-...
In this study, four models describing the interferometric coherence of the forest vegetation layer a...
The use of Interferometric Synthetic Aperture Radar (InSAR) data has great potential for monitoring ...
In this work we provide basic building blocks for semi-empirical models to be applied mainly for for...
In this paper, forest change detection and forest height estimation are studied using two-level mode...
Forest height is an important variable for modeling terrestrial carbon storage and global carbon cyc...
Model-based (PM) forest height inversion from Polarimetric Interferometric Synthetic Aperture Radar ...
In the realm of artificial intelligence, specifically utilizing methodologies such as machine learni...
Model-based forest height inversion from Pol-InSAR data relies on the realistic parameterization of ...
In this study we compare semi-empirical interferometric coherence models, proposed in [1], for tree ...
Recent TanDEM-X experiments have shown that forest height can be estimated with the single polarizat...
This paper evaluates the potential of forest height estimation from a Dual-Pol InSAR observation vec...
Allometric relations that link forest above ground biomass to top forest (i.e. canopy) height are of...
International audienceThe Random Volume over Ground (RVoG) model has been extensively applied to pol...
In this study, four models describing the interferometric coherence of the forest vegetation layer a...
This paper proposes an improved model-based forest height inversion method for airborne L-band dual-...
In this study, four models describing the interferometric coherence of the forest vegetation layer a...
The use of Interferometric Synthetic Aperture Radar (InSAR) data has great potential for monitoring ...
In this work we provide basic building blocks for semi-empirical models to be applied mainly for for...
In this paper, forest change detection and forest height estimation are studied using two-level mode...
Forest height is an important variable for modeling terrestrial carbon storage and global carbon cyc...