Integrating disparate lidar data at the national scale to assess the relationships between height above ground, land cover and ecoregions
Photogrammetric Engineering and Remote Sensing
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Abstract
With the acquisition of lidar data for over 30 percent of the US, it is now possible to assess the three-dimensional distribution of features at the national scale. This paper integrates over 350 billion lidar points from 28 disparate datasets into a national-scale database and evaluates if height above ground is an important variable in the context of other nationalscale layers, such as the US Geological Survey National Land Cover Database and the US Environmental Protection Agency ecoregions maps. While the results were not homoscedastic and the available data did not allow for a complete height census in any of the classes, it does appear that where lidar data were used, there were detectable differences in heights among many of these national classification schemes. This study supports the hypothesis that there were real, detectable differences in heights in certain national-scale classification schemes, despite height not being a variable used in any of the classification routines.
| Publication type | Article |
|---|---|
| Publication Subtype | Journal Article |
| Title | Integrating disparate lidar data at the national scale to assess the relationships between height above ground, land cover and ecoregions |
| Series title | Photogrammetric Engineering and Remote Sensing |
| DOI | 10.14358/PERS.80.1.59 |
| Volume | 80 |
| Issue | 1 |
| Year Published | 2013 |
| Language | English |
| Publisher | American Society for Photogrammetry and Remote Sensing |
| Contributing office(s) | Earth Resources Observation and Science (EROS) Center |
| Description | 12 p. |
| Larger Work Type | Article |
| Larger Work Subtype | Journal Article |
| Larger Work Title | Photogrammetric Engineering and Remote Sensing |
| First page | 59 |
| Last page | 70 |
| Google Analytic Metrics | Metrics page |