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Statistics of TanDEM-X DSM, coherence and backscatter for the characterization of tropical forest structural configuration.

, , , , and . IGARSS, page 1805-1808. IEEE, (2015)

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Spatio-temporal wavelet statistics of SAR backscatter for the characterization of forest degradation in Cameroon., , and . IGARSS, page 2321-2323. IEEE, (2014)A New Drone Laser Scanning Benchmark Dataset for Characterization of Single-Tree and Forest Biophysical Properties., , , , , , , , , and 1 other author(s). IGARSS, page 728-730. IEEE, (2021)An Effective Method for InSAR Mapping of Tropical Forest Degradation in Hilly Areas., , , , , , , , and . Remote. Sens., 14 (3): 452 (2022)Comparing remote sensing-based forest biomass mapping approaches using new forest inventory plots in contrasting forests in northeastern and southwestern China., , , , , , , and . CoRR, (2024)Using Experimental Sites in Tropical Forests to Test the Ability of Optical Remote Sensing to Detect Forest Degradation at 0.3 - 30 M Resolutions., , , , , , and . IGARSS, page 677-680. IEEE, (2021)The Use of ALOS PALSAR for Supporting Sustainable Forest Use in Southern Africa: A Case Study in Malawi., , , and . IGARSS (2), page 206-209. IEEE, (2009)Fusing radar and optical remote sensing for biomass prediction in mountainous tropical forests., , , , , and . IGARSS, page 975-978. IEEE, (2013)Statistics of TanDEM-X DSM, coherence and backscatter for the characterization of tropical forest structural configuration., , , , and . IGARSS, page 1805-1808. IEEE, (2015)Improving Estimates and Change Detection of Forest Above-Ground Biomass Using Statistical Methods., , and . Remote. Sens., 14 (19): 4911 (2022)Multimodal deep learning for mapping forest dominant height by fusing GEDI with earth observation data., , , , , , , and . CoRR, (2023)