Forest Height Estimation From Tandem-X Images With Semi-Empirical Coherence Models

IGARSS 2018 - 2018 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM(2018)

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摘要
In this study we compare semi-empirical interferometric coherence models, proposed in ill, for tree height estimation from TanDEM-X coherence scenes. The models are derived from Random Volume over Ground model, by applying simplifications and introducing empirical parameters at different complexity levels so that the models can be adapted to available ancillary data. Several different TandDEM-X interferometric scenes from Estonia are used to test the model performance in various conditions. All the results are compared with highly accurate canopy height models measured using airborne laser scanning. We demonstrate that models which are very simple to invert, produce accurate tree height estimates when the conditions are most favorable. Best results can be seen for winter images for frozen and dry snow conditions. Simple parametric sinc model can produce accurate tree height maps over large areas with pixel-wise deviation only few meters.
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关键词
forest height estimation,TanDEM-X images,semiempirical coherence models,semiempirical interferometric coherence models,tree height estimation,TanDEM-X coherence scenes,Random Volume,Ground model,available ancillary data,highly accurate canopy height models,empirical parameters,complexity levels,tree height maps,TandDEM-X interferometric scenes,frozen and dry snow conditions,pixel-wise deviation
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