Data for: Distinguishing On-Year and Off-Year Improves Remote Sensing Estimation Accuracy of Aboveground Biomass in Moso Bamboo Forests.

<p dir="ltr">This study proposes a biomass estimation method that integrates Moso bamboo's on-year/off-year growth cycle characteristics by combining Sentinel-2 remote sensing data with machine learning technology. The research first achieved high-precision identification of bam...

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Bibliographic Details
Main Author:	haixin ma (22398007) (author)
Published:	2025
Subjects:	Agroforestry Forestry management and environment Forestry sciences not elsewhere classified Computational modelling and simulation in earth sciences Earth and space science informatics Geoscience data visualisation Moso bamboo forests RemoteSensing Aboveground Biomass Decline Machine Learning - Data processing PLSR method CNN analysis
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Data for: Distinguishing On-Year and Off-Year Improves Remote Sensing Estimation Accuracy of Aboveground Biomass in Moso Bamboo Forests.

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