Canadian Forest Service Publications
Developing 5 m resolution canopy height and digital terrain models from WorldView and ArcticDEM data. 2018. Meddens, A., Vierling, L.A., Eitel, J.U., Jennewein, J.S., White, J.C., Wulder, M.A. Remote Sensing of Environment 218, pp.174–188.
Year: 2018
Issued by: Pacific Forestry Centre
Catalog ID: 39459
Language: English
Availability: PDF (request by e-mail)
Available from the Journal's Web site. †
DOI: 10.1016/j.rse.2018.09.010
† This site may require a fee
Abstract
Digital terrain models (DTMs) and vegetation canopy height models (CHMs) are used in a wide range of earth and environmental sciences. An increasing number of CHM products are available from active, passive, and photogrammetric remotely sensed data; however, high-resolution (≤5 m), wall-to-wall CHMs for the arctic and northern boreal domains that are suitable for detailed spatial analysis are lacking. Recently, a 5-m spatial resolution pan-arctic digital surface model – the ArcticDEM – was created using automated stereopair analysis of high-resolution satellite data. The ArcticDEM is unprecedented in extent and spatial resolution, yet the product generally follows the uppermost surface elevation (i.e., representing a digital surface model, DSM) without regard to whether the surface is comprised of vegetation or bare-earth terrain. To address this limitation, we developed and tested an approach to map vegetation canopy height at a 5-m spatial resolution (hereafter called the local ArcticCHM), and then subtracted these estimated canopy heights from the ArcticDEM in order to create a 5-m resolution DTM (local ArcticDTM). We selected three pilot study areas (total 58 km2) across a north-south gradient in Alaska, representing a range of vegetation types and topographic conditions. We estimated and mapped canopy height using randomForest and imputation modeling approaches, with the ArcticDEM and high spatial resolution multispectral satellite data (WorldView-2) used as predictors. Airborne laser scanning (ALS) data was used for model calibration and independent validation. Canopy height was reliably predicted across the three study areas, with the best models ranging from root mean square errors (RMSE) 2.2 to 2.6m and R2 ranging from 0.59 to 0.76 relative to ALS-based CHM reference data. Similarly, the RMSE between the new local ArcticDTM product and ALS-based DTM reference data was 45–68% less than similar comparisons with the ArcticDEM. Our results offer a means to extend these local ArcticDTM and CHM products to establish high resolution products elsewhere in Alaska of high value for a wide range of earth and environmental sciences research investigations.
Plain Language Summary
Digital terrain models (DTMs) and vegetation canopy height models (CHMs) are used in a wide range of earth and environmental sciences. Currently available canopy height maps for the arctic and boreal domains have a relatively coarse spatial resolution (500-1000 m), making them unsuitable for detailed spatial analysis. Recently, a 5-m spatial resolution pan-arctic digital surface model – the ArcticDEM – was created using automated stereopair analysis of high resolution satellite data. The ArcticDEM is unprecedented in extent and spatial resolution, yet as a feature of the data used and methods applied, the product generally follows the uppermost surface elevation (i.e., representing a digital surface model, DSM) without regard to whether the surface is comprised of vegetation or bare terrain. To address this limitation, we developed and tested an approach to map vegetation canopy height at a 5-m spatial resolution (hereafter called the local ArcticCHM), and then subtracted these estimated canopy heights from the ArcticDEM in order to create a 5-m resolution digital terrain model (local ArcticDTM).
