How to Measure Distance on a Digital Terrain Surface and Why it Matters in Geographical Analysis
Bibliographic Data
| ID | 21321826 |
|---|---|
| Authors | Yi Qiang (0000-0002-6872-8837, Department of Geography and Environment University of Hawaii at Manoa Honolulu HI USA, corresponding author), Barbara Buttenfield (0000-0001-5961-5809, University of Colorado Boulder), Barbara P Buttenfield (Department of Geography University of Colorado at Boulder Boulder CO USA), Maxwell B Joseph (0000-0002-7745-9990, Earth Lab University of Colorado at Boulder Boulder CO USA) |
| Year | 2021 |
| Volume | 53 |
| Issue | 3 |
| Pages | 588-622 |
| Publication date | 2021-07-01 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Geographical Analysis (JOURNAL) |
| Journal identifiers | ISSN: 0016-7363 • E-ISSN: 1538-4632 |
| Publisher | Wiley (PUBLISHER • GB) |
| DOI | 10.1111/gean.12255 |
| OpenAlex | W3049212148 |
| Language | EN |
| References cited | 20 |
Distance is the most fundamental metric in spatial analysis and modeling. Planar distance and geodesic distance are the common distance measurements in current geographic information systems and geospatial analytic tools. However, there is little understanding about how to measure distance in a digital terrain surface and the uncertainty of the measurement. To fill this gap, this study applies a Monte‐Carlo simulation to evaluate seven surface‐adjustment methods for distance measurement in digital terrain model. Using parallel computing techniques and a memory optimization method, the processing time for the distances calculation of 6,000 simulated transects has been reduced to a manageable level. The accuracy and computational efficiency of the surface‐adjustment methods were systematically compared in six study areas with various terrain types and in digital elevation models in different resolutions. Major findings of this study indicate a trade‐off between measurement accuracy and computational efficiency: calculations at finer resolution DEMs improve measurement accuracy but increase processing times. Among the methods compared, the weighted average demonstrates highest accuracy and second fastest processing time. Additionally, the choice of surface adjustment method has a greater impact on the accuracy of distance measurements in rougher terrain
Algorithm · Cartography · Computer vision · Data mining · Digital elevation model · Distance transform · Geodesic · Geography · Geometry · Geospatial analysis · Measure (data warehouse) · Metric (unit) · Monte Carlo method · Remote sensing · Statistics · Surface (topology) · Terrain · Computer Science · Engineering · Hydrology and Watershed Management Studies · Mathematics · Soil and Water Nutrient Dynamics · Soil erosion and sediment transport
| Citation velocity | historical |
|---|---|
| Highly cited | No |