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In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R dense time series ...
Owing to the high temporal resolution, GOES-R satellites offer capabilities to obtain images every 15 minutes enabling a near real-time monitoring of wildfires.
Aug 29, 2024 · In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R ...
36 different wildfires in North and South America under the coverage of GOES-R satellites are selected to assess the effectiveness of the GRU method. The ...
Sep 26, 2022 · In this research, a deep learning framework, based on Gated Recurrent Units (GRU), is proposed to detect wildfires at early stage using GOES-R ...
Abstract: Early detection of wildfires has been limited using the sun-synchronous orbit satellites due to their low temporal resolution and wildfires' fast ...
GOES-R Time Series for Early Detection of Wildfires with Deep GRU-Network Yu Zhao, Yifang Ban Remote Sensing Volume 14, issue 17, 1 September 2022. Resolve ...
NOAA's geostationary weather satellites GOES-R can acquire images every 15 minutes at 2km spatial resolution, and have been used for early fire detection.
The preliminary results show that proposed network can detect the wildfires earlier than the state-of-the- art fire product for 2020 wildfires in California and ...
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GOES-R Time Series for Early Detection of Wildfires with Deep GRU-Network Yu Zhao, Yifang Ban Remote Sensing Volume 14, issue 17, 1 September 2022. Resolve ...