Integrating Remote Sensing Data and CNN-LSTM-Attention Techniques for Improved Forest Stock Volume Estimation: A Comprehensive Analysis of Baishanzu Forest Park, China

Integrating Remote Sensing Data and CNN-LSTM-Attention Techniques for Improved Forest Stock Volume Estimation: A Comprehensive Analysis of Baishanzu Forest Park, China

Forest stock volume is the main factor to evaluate forest carbon sink level. At present, the combination of multi-source remote sensing and non-parametric models has been widely used in FSV estimation. However, the biodiversity of natural forests is complex, and the response of the spatial informati...

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Bibliographic Details
Main Authors: Bo Wang, Yao Chen, Zhijun Yan, Weiwei Liu
Format: Article
Language:English
Published: MDPI AG 2024-01-01
Series:Remote Sensing
Subjects:
forest stock volume
remote sensing (RS)
Pearson correlation analysis
convolutional neural network (CNN)
LSTM
attention mechanism
Online Access:https://www.mdpi.com/2072-4292/16/2/324

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https://www.mdpi.com/2072-4292/16/2/324

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