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May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications

Harvard Dataverse (Africa Rice Center, Bioversity International, CCAFS, CIAT, IFPRI, IRRI and WorldFish)

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Title May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications
 
Identifier https://doi.org/10.7910/DVN/7CBBAT
 
Creator Cooley, Savannah
Pinto, Naiara
White, Bella
Fricker, Andrew
 
Publisher Harvard Dataverse
 
Description Here, we provide an overview of the use of light detection and ranging (lidar) for tropical ecosystem applications, with a particular focus on the Global Ecosystem Dynamics Investigation (GEDI). We summarize how data from GEDI measures vegetation vertical structure and give a step-by-step description of how to obtain spatially-subset GEDI Level 2A data from the NASA EarthData Search web portal. We then provide an example of how to characterize the structure of various vegetation classes in Ucayali, Peru. These vegetation classes include: (1) old-growth lowland forest, (2) young lowland vegetation regrowth (‘Purma’)”, (3) secondary lowland forest, (4) mature oil palm plantations, and (5) cacao plantations (monocrop and agroforestry). We interpret the structural height metrics from GEDI among each of these vegetation classes, identifying edge effects as a possible influence on our results. To address this issue, we conducted a final analysis of the data with an area of 35m diameter footprint (25m of the original diameter area of the beam, and 10m as a conservative additional buffer) and excluded any observations that did not completely overlap with each land cover polygon. When we removed edge effects, no observations remained in the cacao data set and fewer observations remained in the forest stage data set. Nonetheless, the overall structural patterns shown in the relative heights of each forest stage remained very similar. We recommend that future projects utilizing spaceborne lidar for tropical ecosystems consider adopting the techniques and best practices we describe here, including refined noise filtering and explicit consideration of edge effects.
 
Subject Agricultural Sciences
Earth and Environmental Sciences
cocoa
land degradation
land use mapping
agroforestry systems
forest structure
tropical ecosystems
lidar
GEDI
Ucayali
Peru
Land Cover, Land Use Change & Ecosystems
S08 Ecosystem Services Modeling in the Amazon's Forest-Agricultural Interface
 
Date 2022-05-01
 
Contributor Castaño, Silvia-Elena
 
Type Quantitative Data
Environmental Data
Capacity Building
Geographic Data
Active remote sensing