EGU25-17103, updated on 15 Mar 2025
https://doi.org/10.5194/egusphere-egu25-17103
EGU General Assembly 2025
© Author(s) 2025. This work is distributed under the Creative Commons Attribution 4.0 License.
A new remote sensing index for multi-type forest anomalies detection based on Sentinel-2 imagery
- Beijing Normal University, Faculty of Geographical Science, China (ldl2395380880@163.com)
How to cite: Liang, D. and Cao, B.: A new remote sensing index for multi-type forest anomalies detection based on Sentinel-2 imagery, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17103, https://doi.org/10.5194/egusphere-egu25-17103, 2025.