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Department of Computer Science and Technology

Friday, 6 October, 2023 - 13:00 to 14:00
Amelia Holcomb
FW 11, William Gates Building. Zoom link:

Forest disturbance, defined as partial reduction in forest cover that does not result in conversion to non-forested land, has surpassed deforestation by area in the Brazilian Amazon. In addition to causing direct carbon emissions, disturbance also diminishes ecosystem integrity by harming forest structure, even when canopy cover remains. Recent advances using LandSat and Sentinel-1 have improved detection of disturbances at fine spatiotemporal resolution but are so far unable to quantify the changes in forest structure and biomass associated with a detected disturbance. The Global Ecosystem Dynamics Investigation (GEDI), a novel spaceborne LiDAR system, has captured billions of 25-meter diameter footprints measuring forest height, plant area, and understory structure since it began collecting data in 2019. Though there is no guaranteed repeat cycle, GEDI often measures the same location several times; some of these coincident footprints happen to fall before and after a detected disturbance. In this work, we develop a general-purpose open-source pipeline for identifying these locations and use it to find over 7,100 coincident footprint pairs with intermediate disturbance events across the Amazon basin. We also identify a control set of over 34,000 coincident footprint pairs from disturbed areas but without intermediate disturbance events. Analysis of this continent-scale dataset demonstrates that GEDI can detect canopy and biomass losses in non-stand-replacing disturbances as small as 0.09 ha. GEDI’s unique three-dimensional view of forest structure allows us to identify varied effects of different disturbance types, including areas where the upper canopy retains its height, but the understory suffers substantial losses. Finally, we model the relationship between LandSat and Sentinel-1 disturbance detection parameters and GEDI-measured percent biomass loss. This is the first step towards a pan-tropical, spatially explicit estimate of carbon losses and structural changes due to forest disturbance. Amelia Holcomb is a second-year PhD student in Computer Science and Plant Sciences. Her PhD brings together these two fields to develop novel remote sensing techniques for measuring biomass and structural changes following tropical forest disturbance and regrowth.

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Energy and Environment Group

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