In the realm of artificial intelligence, specifically utilizing methodologies such as machine learning and deep learning, a conspicuous display of substantial potential across various parameter estimation problems has been demonstrated. However, such AI techniques are often employed without the incorporation of domain-specific knowledge or expertise, raising concerns about the explainability and robustness of the implemented methodologies. In contrast, physical models (PMs) offer a significantly enhanced level of deterministic robustness. However, it is imperative to recognize that these models can exhibit performance limitations owing to their inherent simplicity and/or strictness. Moreover, the accuracy of their inversion process is c...
In this letter, the interferometric water cloud model (IWCM) is fit to 87 VV-polarized TanDEM-X acqu...
TanDEM-X provides a unique opportunity for environmental studies, being the first single-pass radar ...
Forest biomass (wood volume) is the most integrative forest structural parameter. Since no remote se...
Model-based (PM) forest height inversion from Polarimetric Interferometric Synthetic Aperture Radar ...
Recently, the German TanDEM-X mission provided valuable acquisitions for developing models for the s...
International audienceThe Random Volume over Ground (RVoG) model has been extensively applied to pol...
A model for aboveground biomass estimation from single-pass interferometric synthetic aperture radar...
This paper evaluates the potential of forest height estimation from a Dual-Pol InSAR observation vec...
This paper proposes an improved model-based forest height inversion method for airborne L-band dual-...
Knowledge of the global biomass distribution is essential in monitoring the carbon cycle budget and ...
In this paper, forest change detection and forest height estimation are studied using two-level mode...
The use of Interferometric Synthetic Aperture Radar (InSAR) data has great potential for monitoring ...
Forest height is of great significance in analyzing the carbon cycle on a global or a local scale an...
Forest density affects the inversion of forest height by influencing the penetration and attenuation...
This work makes an attempt to explain the origin, features and potential applications of the elevati...
In this letter, the interferometric water cloud model (IWCM) is fit to 87 VV-polarized TanDEM-X acqu...
TanDEM-X provides a unique opportunity for environmental studies, being the first single-pass radar ...
Forest biomass (wood volume) is the most integrative forest structural parameter. Since no remote se...
Model-based (PM) forest height inversion from Polarimetric Interferometric Synthetic Aperture Radar ...
Recently, the German TanDEM-X mission provided valuable acquisitions for developing models for the s...
International audienceThe Random Volume over Ground (RVoG) model has been extensively applied to pol...
A model for aboveground biomass estimation from single-pass interferometric synthetic aperture radar...
This paper evaluates the potential of forest height estimation from a Dual-Pol InSAR observation vec...
This paper proposes an improved model-based forest height inversion method for airborne L-band dual-...
Knowledge of the global biomass distribution is essential in monitoring the carbon cycle budget and ...
In this paper, forest change detection and forest height estimation are studied using two-level mode...
The use of Interferometric Synthetic Aperture Radar (InSAR) data has great potential for monitoring ...
Forest height is of great significance in analyzing the carbon cycle on a global or a local scale an...
Forest density affects the inversion of forest height by influencing the penetration and attenuation...
This work makes an attempt to explain the origin, features and potential applications of the elevati...
In this letter, the interferometric water cloud model (IWCM) is fit to 87 VV-polarized TanDEM-X acqu...
TanDEM-X provides a unique opportunity for environmental studies, being the first single-pass radar ...
Forest biomass (wood volume) is the most integrative forest structural parameter. Since no remote se...