Fires Hotspot Forecasting in Indonesia Using Long Short-Term Memory Algorithm and MODIS Datasets
Vegetation fires are most common in South and Southeast Asian countries, including Indonesia. In addition to anthropogenic causes, climate change in the form of droughts is the biggest driver of fires in Indonesia. In particular, the peatlands in Indonesia are highly vulnerable to droughts with recu...
Saved in:
Main Authors: | Kadir, E.A., Kung, H.T., Nasution, A.H., Daud, H., AlMansour, A.A., Othman, M., Rosa, L. |
---|---|
Format: | Book |
Published: |
Springer International Publishing
2023
|
Online Access: | http://scholars.utp.edu.my/id/eprint/37659/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85171518501&doi=10.1007%2f978-3-031-29916-2_35&partnerID=40&md5=23de4c2c760340a7871fa0bd35bb776d |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Fires Hotspot Forecasting in Indonesia Using Long Short-Term Memory Algorithm and MODIS Datasets
by: Kadir, E.A., et al.
Published: (2023) -
Fires Hotspot Forecasting in Indonesia Using Long Short-Term Memory Algorithm and MODIS Datasets
by: Kadir, Evizal Abdul, et al.
Published: (2023) -
Modelling of wireless sensor networks for detection land and forest fire hotspot
by: Kadir, E.A., et al.
Published: (2019) -
Modelling of wireless sensor networks for detection land and forest fire hotspot
by: Kadir, E.A., et al.
Published: (2019) -
Short term residential load forecasting using long short-term memory recurrent neural network
by: Muneer, A., et al.
Published: (2022)