Articles | Volume 18, issue 22
https://doi.org/10.5194/bg-18-6077-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/bg-18-6077-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
25 Nov 2021
Research article |
| 25 Nov 2021
| 25 Nov 2021
Unveiling spatial and temporal heterogeneity of a tropical forest canopy using high-resolution NIRv, FCVI, and NIRvrad from UAS observations
Remote Sensing Division, Naval Research Laboratory, 4555 Overlook
Ave. SW, Washington, DC 20375, USA
Stephanie Pau
Department of Geography, Florida State University, 113 Collegiate
Loop, Tallahassee, FL 32306, USA
Matteo Detto
Smithsonian Tropical Research Institute, Apartado 0843–03092,
Balboa, Ancón, Panama
Department of Ecology and Evolutionary Biology, Princeton University,
Princeton, NJ 08544, USA
Eben N. Broadbent
Spatial Ecology and Conservation Lab, School of Forest, Fisheries, and
Geomatics Sciences, University of Florida, Gainesville, FL 32608, USA
Stephanie A. Bohlman
Smithsonian Tropical Research Institute, Apartado 0843–03092,
Balboa, Ancón, Panama
School of Forest, Fisheries, and Geomatics Sciences, University of
Florida, Gainesville, FL 32608, USA
Christopher J. Still
Department of Forest Ecosystems and Society, Oregon State University,
Corvallis, OR 97331, USA
Angelica M. Almeyda Zambrano
Spatial Ecology and Conservation Lab, Center for Latin American
Studies, University of Florida, Gainesville, FL 32608, USA
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Methane is an important greenhouse gas, yet we lack knowledge about its global emissions and drivers. We present FLUXNET-CH4, a new global collection of methane measurements and a critical resource for the research community. We use FLUXNET-CH4 data to quantify the seasonality of methane emissions from freshwater wetlands, finding that methane seasonality varies strongly with latitude. Our new database and analysis will improve wetland model accuracy and inform greenhouse gas budgets.
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Short summary
Remote sensing measurements of forest structure promise to improve monitoring of tropical forest health. We investigated drone-based vegetation measurements' abilities to capture different structural and functional elements of a tropical forest. We found that emerging vegetation indices captured greater variability than traditional indices and one new index trends with daily change in carbon flux. These new tools can help improve understanding of tropical forest structure and function.
Remote sensing measurements of forest structure promise to improve monitoring of tropical forest...
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