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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. Quantifying aboveground herbaceous biomass in grassy ecosystems: a comparison of field and high‐resolution UAV‐LiDAR approaches

   https://doi.org/10.1002/rse2.70023  

   Coverdale, Tyler C; Boucher, Peter B; Singh, Jenia; Davies, Andrew B (August 2025, Remote Sensing in Ecology and Conservation)

   Abstract Grassy ecosystems cover >25% of the world's land surface area. The abundance of herbaceous vegetation in these systems directly impacts a variety of ecological processes, including carbon sequestration, regulation of water and nutrient cycling, and support of grazing wildlife and livestock. Efforts to quantify herbaceous biomass, however, are often limited by a trade‐off between accuracy and spatial scale. Here, we describe a method for using Light Detection and Ranging (LiDAR) to estimate continuous aboveground biomass (AGB) at sub‐meter resolutions over large (10–10 000 ha) spatial scales. Across two African savanna ecosystems, we compared field‐ and LiDAR‐derived structural metrics—including measures of vegetation height and volume—with destructively harvested AGB by aligning our geospatial data with the location of harvested quadrats. Using this combination of approaches, we develop scaling equations to estimate spatially continuous herbaceous AGB over large areas. We demonstrate the utility of this method using a long‐term, large herbivore exclosure experiment as a case study and comprehensively compare common field‐ and LiDAR‐derived metrics for estimating herbaceous AGB. Our results indicate that UAV‐borne LiDAR provides comparable accuracy to standard field methods but over considerably larger areas. Nearly every measure of vegetation structure we quantified using LiDAR provided estimates of AGB that were comparable in accuracy (R² > 0.6) to the suite of common field methods we evaluated. However, marked differences between our two sites indicate that, for applications where accurate estimation of absolute biomass is a priority, site‐specific parameterization with destructive harvesting is necessary regardless of methodology. With the increasing availability of high‐resolution remote sensing data globally, our results indicate that many measures of herbaceous vegetation structure can be used to accurately compare AGB, even in the absence of complementary field data. 

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