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Case Study: Forest Canopy

Writer's picture: Fiona BoothFiona Booth




The Global Canopy Atlas (GCA) is a forthcoming global database of airborne and drone-based laser scanning (ALS/ DLS) acquisitions over forested ecosystems.


It is curated specifically for ecological and climate-related research. It is particularly useful for examining forest structure and carbon reserves, comprehending the fundamental dynamics (such as tree mortality, carbon fluctuations), and verifying satellite data.


To ensure global comparability, any dataset that is included in the GCA has gone through the same standardised and maximally robust pipeline (Fischer et al. 2024[1]). The pipeline was written in R and uses LAStools software.


Three flowcharts were created which describe manual steps to ensure that datasets meet minimum quality requirements and automated steps to derive analysis-ready products. The flowchart shown here describes a sequential set of steps to check raw scan data and the accompanying metadata, which typically includes flightlogs, flightlines, coordinate reference systems and scan quality reports.


Key checks include whether laser scans are properly geo-referenced and whether the acquisition period is known. The latter is important to separate vegetation changes across years from vegetation changes across seasons, such as leaf fall in winter (boreal and temperate forests) or dry seasons (subtropical and tropical forests). 


The three process maps will help new users adopt the pipeline; emphasise quality requirements for laser scanning in global ecology and climate change research; and assist in future workflow development and software transitions.

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