Developing 5 m resolution canopy height and digital terrain models from WorldView and ArcticDEM data

• Published in: Remote sensing of environment 2018-12, Vol.218, p.174-188
• Main Authors: Meddens, Arjan J.H., Vierling, Lee A., Eitel, Jan U.H., Jennewein, Jyoti S., White, Joanne C., Wulder, Michael A.
• Format: Article
• Language: English
• Subjects: Airborne laser scanning; Airborne lasers; Altitude; ArcticDEM; Calibration; Canopies; Canopy height; Digital elevation model; Digital imaging; Digital surface model; Digital terrain model; Domains; Earth; Environmental science; High resolution; Lidar; Photogrammetry; Polar environments; Remote sensing; Root-mean-square errors; Satellite data; Satellites; Scanners; Spatial analysis; Spatial data; Spatial discrimination; Spatial resolution; Terrain; Terrain models; Vegetation; Vegetation height
• ISSN: 0034-4257; 1879-0704
• DOI: 10.1016/j.rse.2018.09.010

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 2.6 m 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. [Display omitted] •The ArcticDEM is a high-resolution digital surface model for northern latitudes.•The ArcticDEM generally follows the highest local surface, vegetation or terrain.•We developed methods that accurately quantify canopy height.•We used the canopy height to remove vegetation elevations from t