Abstract
A variety of landscape properties have been modeled successfully using topographic indices such as topographic wetness index (TWI), defined as ln(a/tanβ), where a is the specific upslope area and β is the surface slope. In this study, 25 m spatial resolution from digital elevation models (DEM) data were used to investigate the scale-dependency of TWI values when converting DEMs to 50 and 100 m. To investigate the impact of different spatial resolution, the two lower resolution DEMs were interpolated to the original 25 m grid size. In addition, to compare different flow-direction algorithms, a second objective was to evaluate differences in spatial patterns. Thus the values of TWI were compared in two different ways: 1) distribution functions and their statistics; and 2) cell by cell comparison of DEMs with the same spatial resolution but different flow- directions. As in previous TWI studies, the computed specific upstream is smaller, on average, at higher resolution. TWI variation decreased with increasing grid size. A cell by cell comparison of the TWI values of the 50 and 100 m DEMs showed a low correlation with the TWI based on the 25 m DEM. The results showed significant differences between different flow-diretction algorithms computed for DEMs with 25, 50 and 100 m spatial resolution.
Highlights
Available digital elevation models (DEMs), together with corresponding tools for spatial analysis, have found extensive use in the development of research in many areas of the environmental sciences, including agriculture, hydrology, ecology, geography and branches of engineering using topographically-dependent variables
The results showed significant differences between different flow-diretction algorithms computed for DEMs with 25, 50 and 100 m spatial resolution
Higher spatial resolutions are obtained from photogrammetry and laser profiling, while coarser spatial resolutions are freely available through the Shuttle Radar Topographic Mission (SRTM) [11]
Summary
Available digital elevation models (DEMs), together with corresponding tools for spatial analysis, have found extensive use in the development of research in many areas of the environmental sciences, including agriculture, hydrology, ecology, geography and branches of engineering using topographically-dependent variables. Data are generated at different scales and spatial resolutions. The accuracy of data generated at different spatial resolutions depends exclusively on how closely a calculated measure lies to its true value: the reliability of the data is linked to its accuracy. In this context, the higher the spatial resolution of a DEM, the greater is the tendency to accuracy. When analyzing data from a DEM, a fundamental step is the evaluation of the precision of the derived data; the user must know how trustworthy his derived data is
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