Abstract
Digital Elevation Models (DEMs) contribute to geomorphological and hydrological applications. DEMs can be derived using different remote sensing-based datasets, such as Interferometric Synthetic Aperture Radar (InSAR) (e.g., Advanced Land Observing Satellite (ALOS) Phased Array type L-band SAR (PALSAR) and Shuttle Radar Topography Mission (SRTM) DEMs). In addition, there is also the Digital Surface Model (DSM) derived from optical tri-stereo ALOS Panchromatic Remote-sensing Instrument for Stereo Mapping (PRISM) imagery. In this study, we evaluated satellite-based DEMs, SRTM (Global) GL1 DEM V003 28.5 m, ALOS DSM 28.5 m, and PALSAR DEMs 12.5 m and 28.5 m, and their derived channel networks/orders. We carried out these assessments using Light Detection and Ranging (LiDAR) Digital Surface Models (DSMs) and Digital Terrain Models (DTMs) and their derived channel networks and Strahler orders as reference datasets at comparable spatial resolutions. We introduced a pixel-based method for the quantitative horizontal evaluation of the channel networks and Strahler orders derived from global DEMs utilizing confusion matrices at different flow accumulation area thresholds (ATs) and pixel buffer tolerance values (PBTVs) in both ±X and ±Y directions. A new Python toolbox for ArcGIS was developed to automate the introduced method. A set of evaluation metrics—(i) producer accuracy (PA), (ii) user accuracy (UA), (iii) F-score (F), and (iv) Cohen’s kappa index (KI)—were computed to evaluate the accuracy of the horizontal matching between channel networks/orders extracted from global DEMs and those derived from LiDAR DTMs and DSMs. PALSAR DEM 12.5 m ranked first among the other global DEMs with the lowest root mean square error (RMSE) and mean difference (MD) values of 4.57 m and 0.78 m, respectively, when compared to the LiDAR DTM 12.5 m. The ALOS DSM 28.5 m had the highest vertical accuracy with the lowest recorded RMSE and MD values of 4.01 m and −0.29 m, respectively, when compared to the LiDAR DSM 28.5 m. PALSAR DEM 12.5 m and ALOS DSM 28.5 m-derived channel networks/orders yielded the highest horizontal accuracy when compared to those delineated from LiDAR DTM 12.5 m and LiDAR DSM 28.5 m, respectively. The number of unmatched channels decreased when the PBTV increased from 0 to 3 pixels using different ATs.
Highlights
Current advances in remote sensing techniques are essential in producing high-quality Digital Elevation Models (DEMs)
We assessed the vertical accuracies of the global DEMs (SRTM DEM V003 28.5 m, Advanced Land Observing Satellite (ALOS) Digital Surface Model (DSM) 28.5 m, and Phased Array type L-band Synthetic Aperture Radar (SAR) (PALSAR) DEMs 12.5 m and 28.5 m) by computing the per-pixel difference with the Light Detection and Ranging (LiDAR) Digital Terrain Models (DTMs)/DSMs at similar spatial details
Negative elevation differences were dominant in the comparison between Shuttle Radar Topography Mission (SRTM) DEM 28.5 m and ALOS DSM 28.5 m against LiDAR DTM 28.5 m and DSM 28.5 m, respectively
Summary
Current advances in remote sensing techniques are essential in producing high-quality Digital Elevation Models (DEMs). Because of the general availability of different optical and microwave satellite data-based DEMs, many authors have extensively used these elevation datasets for a wide range of applications, for various hydrological and geomorphological models. The outcomes of these models depend mainly on the accuracy and quality of the utilized DEMs [1,2,3,4,5,6]. A DEM is an umbrella term for any electronically accessible elevation datasets, such as Digital Terrain Models (DTMs) and Digital Surface Models (DSMs) It includes elevation measures of the Earth’s terrain, in addition to natural- and human-based objects above a certain vertical datum [7]. The elevation datasets required to create a DEM can be collected using various ground- and satellite-based techniques, including conventional topographic surveys [10], digitizing and interpolation of contours [11], kinematic global navigation satellite system surveys [12], stereo-photogrammetry [13], Synthetic Aperture Radar (SAR) interferometry [14], airborne laser scanning [15], and fusion of data from different sources [16]
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