Name
Abstract | ||
|---|---|---|
We developed new vegetation indices utilizing terrestrial laser scanning (TLS) to quantify the three-dimensional spatial configuration of plant communities. These indices leverage the novelty of TLS data and rely on the spatially biased arrangement of a TLS point cloud. We calculated these indices from TLS data acquired within an existing long term manipulation of forest structure in Central Oregon, USA, and used these data to test for differences in vegetation structure. Results provided quantitative evidence of a significant difference in vegetation density due to thinning and burning, and a marginally significant difference in vegetation patchiness due to grazing. A comparison to traditional field sampling highlighted the novelty of the TLS based method. By creating a linkage between traditional field sampling and landscape ecology, these indices enable field investigations of fine-scale spatial patterns. Applications include experimental assessment, long-term monitoring, and habitat characterization. |
Year | DOI | Venue |
|---|---|---|
2014 | 10.3390/s141120304 | SENSORS |
Keywords | Field | DocType |
density,patchiness,forest,remote sensing,grazing,fire | Plant community,Vegetation,Landscape ecology,Thinning,Remote sensing,Sampling (statistics),Engineering,Point cloud,Spatial ecology,Environmental monitoring | Journal |
Volume | Issue | ISSN |
14 | 11 | 1424-8220 |
Citations | PageRank | References |
3 | 0.46 | 4 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jeffrey J Richardson | 1 | 3 | 0.80 |
| L Monika Moskal | 2 | 140 | 20.24 |
| Bakker, J.-D. | 3 | 4 | 0.84 |