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Discussion: Alaska Wildfire Prediction Using Satellite Imagery (GSoC 2026) #68
Hi everyone,
I’m Eshaan Saha, a B.Tech student with a strong interest in machine learning, computer vision, and climate-focused AI applications.
I’m particularly interested in the "Alaska Wildfire Prediction Using Satellite Imagery" project. I have prior experience working with spatiotemporal data through an EEG signal analysis project during my internship at IIT Jodhpur, as well as a computer vision project involving UAV-based fruit ripeness detection using YOLOv8 with GPS mapping.
I’m currently exploring approaches for wildfire prediction using multi-temporal satellite imagery combined with environmental data (e.g., temperature, humidity, wind). I’m considering a CNN + LSTM/ConvLSTM-based architecture for spatio-temporal modeling.
I would love to get your thoughts on:
- Preferred datasets (MODIS, VIIRS, Sentinel?)
- Whether temporal prediction is expected beyond detection
- Any existing baselines or prior work in this repo
Looking forward to contributing and learning from the community!
Thanks!
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Replies: 1 comment
Hi,
Please reach out to the project's specific GitHub page.
As the deadline is fast-approaching (just a couple of hours more), I recommend submitting the proposals. We will review and get back to you by mid-April if we have questions or comments.