Land Cover Classification of Subarctic Wetlands Using Multisource Remotely Sensed Data

Land Cover Classification of Subarctic Wetlands Using Multisource Remotely Sensed Data

This study aims to exploit multisource remotely sensed data to improve land cover classification of an area dominated by extensive wetlands with surface cover complexity strongly shaped by permafrost, fine-scale geomorphological and topographic characteristics. Accurate and precise mapping tools are...

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Bibliographic Details
Main Authors: Baoxin Hu, Glen Brown, Callie Stirling, Jianguo Wang
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Subjects:
Classification
Dempster-Shaffer (DS) theory
information fusion
multi-source remotely sensed data
prediction uncertainty
random forest
Online Access:https://ieeexplore.ieee.org/document/10418485/

Internet

https://ieeexplore.ieee.org/document/10418485/

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