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How does Lidar data support forest ecosystem rewetting: comparison between official airborne lidar with high-resolution UAS Lidar
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Autores
Orientador(es)
Resumo(s)
Nowadays many efforts are being made to mitigate the impacts of climate change in
our society and in natural environments, such as the recuperation of ecosystems
impacted by human activities. Rewetting is an ecological restoration process that aims
to recover water supplies in dried wetting areas, recovering biodiversity and reducing
CO2 emissions. Precise information from the current water channels is required for
rewetting to create hydrologic models and analyze the effects of closing the channels
on water runoff. Remote Sensing using LiDAR (Light Detection and Ranging)
technology can efficiently collect information from water channels and create precise
DTM (Digital Terrain Model) to support hydrologic modelling. Airborne LiDAR has
been used for many decades but now with the advancement of UAS (Unmanned Aerial
System) technology new potentialities are appearing for monitoring and data
acquisition, improving the spatial and temporal resolution. However, it is necessary to
evaluate if this new technology can substitute the official aerial surveys. The objective
of this thesis is to evaluate the potential differences between official Airborne LiDAR
and high-resolution LiDAR using UAS to support forest ecosystem rewetting,
comparing the extraction of water drainages and hydrological models. Results show
small differences between these two datasets, probably created by the temporal
difference between them or the increased spatial resolution, revealing more details with
UAS that were not detected in the Airborne flight. This study concludes that UAS can
collect high-quality data comparable to traditional aerial surveys, enabling more
accessible and cost-effective data collection for ecosystem restoration and monitoring.
Descrição
Dissertation submitted in partial fulfilment of the requirements for the Degree of Master of Science in Geospatial Technologies
Palavras-chave
UAS LiDAR Rewetting Digital Terrain Models