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- B11A-04: Tracking Recovery: Temporally-Matched 3D Gaussian Splatting of Ecosystems after Prescribed Burns
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NOLA CC
Author(s):Generic 'disconnected' Message
Daniel Neamati, Stanford University (First Author, Presenting Author)
Grace Gao, Stanford University
Fire management involves reducing the risk of large wildfires or making it easier to fight a future wildfire by prescribing an ecosystem treatment, such as manual plant trimming or carefully controlled burns. However, many questions remain concerning how the ecosystem recovers after the treatment, which can vary significantly across small scales. Current management teams are missing tools to understand the treated area in 3D over time. We develop tools by combining knowledge in multiple engineering and science disciplines to facilitate improved fire management. Using handheld tablets and drone platforms, we take images of the treated area every month and turn the image collections into high-resolution 3D models. Our approach to joining these models in time allows the management team to quantitatively connect 3D insights at each data collection trip. We collaborate with a local biological preserve where fire management treatments were recently conducted. Across just tens of meters and a few seasons, we captured differences in the ecosystem recovery that can impact decisions on follow-up treatments. Our core approach of 3D models connected in time to understand ecosystem change has broad applicability across fire management. Especially near residential areas, these models could assist in future firefighting operations.
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