From small-scale forest structure to Amazon-wide carbon estimates
Improving estimates of forest biomass based on remote sensing data is important to assess global carbon cycling. Here the authors develop an approach to use forest gap models to simulate lidar waveforms and compare the outputs with ICESAT-1 GLAS profiles, showing improved estimates across the Amazon...
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| Autores principales: | , , , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Nature Portfolio
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/16f0714eaaf44808ade6f451a84b3018 |
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| Sumario: | Improving estimates of forest biomass based on remote sensing data is important to assess global carbon cycling. Here the authors develop an approach to use forest gap models to simulate lidar waveforms and compare the outputs with ICESAT-1 GLAS profiles, showing improved estimates across the Amazon basin. |
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