May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications
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 descriptio...
| Autores principales: | , , , |
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| Formato: | Conjunto de datos |
| Lenguaje: | Inglés |
| Publicado: |
2022
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/130764 |
| _version_ | 1855513876302397440 |
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| author | Cooley, Savannah Pinto, Naiara White, Bella Fricker, Andrew |
| author_browse | Cooley, Savannah Fricker, Andrew Pinto, Naiara White, Bella |
| author_facet | Cooley, Savannah Pinto, Naiara White, Bella Fricker, Andrew |
| author_sort | Cooley, Savannah |
| collection | Repository of Agricultural Research Outputs (CGSpace) |
| 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. |
| format | Conjunto de datos |
| id | CGSpace130764 |
| institution | CGIAR Consortium |
| language | Inglés |
| publishDate | 2022 |
| publishDateRange | 2022 |
| publishDateSort | 2022 |
| record_format | dspace |
| spelling | CGSpace1307642024-04-25T06:00:15Z May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications Cooley, Savannah Pinto, Naiara White, Bella Fricker, Andrew land degradation land use mapping agroforestry systems peru 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. 2022-08 2023-06-20T13:09:18Z 2023-06-20T13:09:18Z Dataset https://hdl.handle.net/10568/130764 en Open Access Cooley, Savannah;Pinto, Naiara;White, Bella;Fricker, Andrew, 2022, "May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications", 10.7910/DVN/7CBBAT, Harvard Dataverse, V1, |
| spellingShingle | land degradation land use mapping agroforestry systems peru Cooley, Savannah Pinto, Naiara White, Bella Fricker, Andrew May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications |
| title | May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications |
| title_full | May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications |
| title_fullStr | May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications |
| title_full_unstemmed | May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications |
| title_short | May the forest be with you: leveraging GEDI’s spaceborne lidar data for tropical ecosystem applications |
| title_sort | may the forest be with you leveraging gedi s spaceborne lidar data for tropical ecosystem applications |
| topic | land degradation land use mapping agroforestry systems peru |
| url | https://hdl.handle.net/10568/130764 |
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