Description
The SOC (Soil Organic Carbon) pool is a large carbon reservoir that is closely linked to climatic drivers. In complex terrain, quantifying SOC storage is challenging due to high spatial variability. Generally, point data is distributed by developing quantitative relationships between SOC and spatially-distributed, variables like elevation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) can be used to predict below-ground carbon stocks. With this research, we evaluated SOC variability in complex terrain and attempt to improve upon SOC models by incorporating hyperspectral and LiDAR datasets.
Date made available | 28 Mar 2017 |
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Keywords
- SOC
- RCEW
- soil carbon
- Reynolds Creek