Evaluating Lidar Point Densities for Effective Estimation of Aboveground Biomass
| Dublin Core | PKP Metadata Items | Metadata for this Document | |
| 1. | Title | Title of document | Evaluating Lidar Point Densities for Effective Estimation of Aboveground Biomass |
| 2. | Creator | Author's name, affiliation, country | Zhuoting Wu; US Geological Survey, Western Geographic Science Center, United States |
| 2. | Creator | Author's name, affiliation, country | Dennis Dye; US Geological Survey, Western Geographic Science Center, United States |
| 2. | Creator | Author's name, affiliation, country | Jason Stoker; National Geospatial Program, US Geological Survey, United States |
| 2. | Creator | Author's name, affiliation, country | John Vogel; US Geological Survey, Western Geographic Science Center, United States |
| 2. | Creator | Author's name, affiliation, country | Miguel Velasco; US Geological Survey, Western Geographic Science Center, United States |
| 2. | Creator | Author's name, affiliation, country | Barry Middleton; US Geological Survey, Western Geographic Science Center, United States |
| 2. | Creator | Author's name, affiliation, country | (doi: 10.23953/cloud.ijarsg.40) |
| 3. | Subject | Discipline(s) | Ecology; Geography |
| 3. | Subject | Keyword(s) | 3DEP; Aboveground Biomass; Essential Climate Variable (ECV); Landsat; Lidar; Point Density; Quality Level |
| 3. | Subject | Subject classification | Remote sensing |
| 4. | Description | Abstract |
The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone. |
| 5. | Publisher | Organizing agency, location | |
| 6. | Contributor | Sponsor(s) | US Geological Survey |
| 7. | Date | (YYYY-MM-DD) | 2016-02-09 |
| 8. | Type | Status & genre | Peer-reviewed Article |
| 8. | Type | Type | |
| 9. | Format | File format | |
| 10. | Identifier | Uniform Resource Identifier | http://technical.cloud-journals.com/index.php/IJARSG/article/view/Tech-559 |
| 11. | Source | Journal/conference title; vol., no. (year) | International Journal of Advanced Remote Sensing and GIS; Volume 5 (Year 2016) |
| 12. | Language | English=en | en |
| 14. | Coverage | Geo-spatial location, chronological period, research sample (gender, age, etc.) | |
| 15. | Rights | Copyright and permissions |
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