Country-wide retrieval of forest structure from optical and SAR satellite imagery with deep ensembles

Author:

Becker Alexander,Russo Stefania,Puliti Stefano,Lang NicoORCID,Schindler KonradORCID,Wegner Jan Dirk

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Computer Science Applications,Engineering (miscellaneous),Atomic and Molecular Physics, and Optics

Reference101 articles.

1. A simple approach to forest structure classification using airborne laser scanning that can be adopted across bioregions;Adnan;Forest Ecol. Manag.,2019

2. Determining maximum entropy in 3D remote sensing height distributions and using it to improve aboveground biomass modelling via stratification;Adnan;Remote Sens. Environ.,2021

3. Alves de Almeida, D.R., Stark, S.C., Silva, C.A., Hamamura, C., Valbuena, R., 2020. URL: https://rdocumentation.org/packages/leafR/versions/0.3.

4. Decision-Making under uncertainty for the deployment of future hyperconnected networks: A survey;Alzate-Mejía;Sensors,2021

5. Ashukha, A., Lyzhov, A., Molchanov, D., Vetrov, D., 2020. Pitfalls of In-Domain Uncertainty Estimation and Ensembling in Deep Learning. In: International Conference on Learning Representations.

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