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1. UAV LiDAR Survey for Archaeological Documentation in Chiapas, Mexico

   https://doi.org/10.3390/rs13234731  

   Schroder, Whittaker; Murtha, Timothy; Golden, Charles; Scherer, Andrew K.; Broadbent, Eben N.; Almeyda Zambrano, Angélica M.; Herndon, Kelsey; Griffin, Robert (December 2021, Remote Sensing)

   Airborne laser scanning has proven useful for rapid and extensive documentation of historic cultural landscapes after years of applications mapping natural landscapes and the built environment. The recent integration of unoccupied aerial vehicles (UAVs) with LiDAR systems is potentially transformative and offers complementary data for mapping targeted areas with high precision and systematic study of coupled natural and human systems. We report the results of data capture, analysis, and processing of UAV LiDAR data collected in the Maya Lowlands of Chiapas, Mexico in 2019 for a comparative landscape study. Six areas of archaeological settlement and long-term land-use reflecting a diversity of environments, land cover, and archaeological features were studied. These missions were characterized by areas that were variably forested, rugged, or flat, and included pre-Hispanic settlements and agrarian landscapes. Our study confirms that UAV LiDAR systems have great potential for broader application in high-precision archaeological mapping applications. We also conclude that these studies offer an important opportunity for multi-disciplinary collaboration. UAV LiDAR offers high-precision information that is not only useful for mapping archaeological features, but also provides critical information about long-term land use and landscape change in the context of archaeological resources. 

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2. Distinguishing forest types in restored tropical landscapes with UAV-borne LIDAR

   https://doi.org/10.1016/j.rse.2023.113533  

   Scheeres, Janneke; de Jong, Johan; Brede, Benjamin; Brancalion, Pedro H.S.; Broadbent, Eben Noth; Zambrano, Angelica Maria; Gorgens, Eric Bastos; Silva, Carlos Alberto; Valbuena, Ruben; Molin, Paulo; et al (May 2023, Remote Sensing of Environment)
3. Monitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion

   https://doi.org/10.1016/j.rse.2021.112582  

   Almeida, Danilo Roberti; Broadbent, Eben North; Ferreira, Matheus Pinheiro; Meli, Paula; Zambrano, Angelica Maria; Gorgens, Eric Bastos; Resende, Angelica Faria; de Almeida, Catherine Torres; do Amaral, Cibele Hummel; Corte, Ana Paula; et al (October 2021, Remote Sensing of Environment)
4. Estimating mussel mound distribution and geometric properties in coastal salt marshes by using UAV-Lidar point clouds

   https://doi.org/10.1016/j.scitotenv.2023.163707  

   Pinton, Daniele; Canestrelli, Alberto; Williams, Sydney; Angelini, Christine; Wilkinson, Benjamin (July 2023, Science of The Total Environment)
5. Forest fire, thinning, and flood in wildland-urban interface: UAV and lidar-based estimate of natural disaster impacts

   https://doi.org/10.1007/s10980-024-01811-5  

   Sankey, Temuulen Ts; Tango, Lauren; Tatum, Julia; Sankey, Joel B (March 2024, Landscape Ecology)

   Abstract ContextWildland-urban interface (WUI) areas are facing increased forest fire risks and extreme precipitation events due to climate change, which can lead to post-fire flood events. The city of Flagstaff in northern Arizona, USA experienced WUI forest thinning, fire, and record rainfall events, which collectively contributed to large floods and damages to the urban neighborhoods and city infrastructure. ObjectivesWe demonstrate multi-temporal, high resolution image applications from an unoccupied aerial vehicle (UAV) and terrestrial lidar in estimating landscape disturbance impacts within the WUI. Changes in forest vegetation and bare ground cover in WUIs are particularly challenging to estimate with coarse-resolution satellite images due to fine-scale landscape processes and changes that often result in mixed pixels. MethodsUsing Sentinel-2 satellite images, we document forest fire impacts and burn severity. Using 2016 and 2021 UAV multispectral images and Structure-from-Motion data, we estimate post-thinning changes in forest canopy cover, patch sizes, canopy height distribution, and bare ground cover. Using repeat lidar data within a smaller area of the watershed, we quantify geomorphic effects in the WUI associated with the fire and subsequent flooding. ResultsWe document that thinning significantly reduced forest canopy cover, patch size, tree density, and mean canopy height resulting in substantially reduced active crown fire risks in the future. However, the thinning equipment ignited a forest fire, which burned the WUI at varying severity at the top of the watershed that drains into the city. Moderate-high severity burns occurred within 3 km of downtown Flagstaff threatening the WUI neighborhoods and the city. The upstream burned area then experienced 100-year and 200–500-year rainfall events, which resulted in large runoff-driven floods and sedimentation in the city. ConclusionWe demonstrate that UAV high resolution images and photogrammetry combined with terrestrial lidar data provide detailed and accurate estimates of forest thinning and post-fire flood impacts, which could not be estimated from coarser-resolution satellite images. Communities around the world may need to prepare their WUIs for catastrophic fires and increase capacity to manage sediment-laden stormwater since both fires and extreme weather events are projected to increase. 

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