A Hybrid Mangrove Identification Method by Combining the Time-Frequency Threshold of the Mangrove Index With a Random Forest Binary Classifier
Mangroves are in coastal zones where mass-energy exchange is most active. Their functions in high productivity, strong carbon sequestration capacity, and rich ecosystem services are crucial for achieving the sustainable development goals. Although various classification methods have been extensively...
Saved in:
Main Authors: | Zhuokai Jian, Bin Ai, Jiali Zeng, Yuchao Sun |
---|---|
Format: | Article |
Language: | English |
Published: |
IEEE
2025-01-01
|
Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
Subjects: | |
Online Access: | https://ieeexplore.ieee.org/document/10750253/ |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Rhizophora mangle, Red Mangrove
by: Natalia Medina Irizarry, et al.
Published: (2023-02-01) -
The Change Detection of Mangrove Forests Using Deep Learning with Medium-Resolution Satellite Imagery: A Case Study of Wunbaik Mangrove Forest in Myanmar
by: Kyaw Soe Win, et al.
Published: (2024-10-01) -
The phenology and water level time-series mangrove index for improved mangrove monitoring
by: Ke Huang, et al.
Published: (2024-11-01) -
Avicennia germinans, Black Mangrove
by: Michael G. Andreu, et al.
Published: (2013-04-01) -
Conservation behaviors of local communities towards mangrove forests in Iran
by: Moslem Savari, et al.
Published: (2024-12-01)