Data:Geomorpho90m

From CSDMS
Revision as of 14:12, 12 June 2020 by WikiSysop (talk | contribs) (Created page with "{{Data description |One-line data description=A global dataset comprising of different geomorphometric features derived from the MERIT-Digital Elevation Model (DEM) - the best...")
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)

Geomorpho90m dataset information page



Short Description

Geomorphological forms of South Dakota

Statement: A global dataset comprising of different geomorphometric features derived from the MERIT-Digital Elevation Model (DEM) - the best global, high-resolution DEM available.

Abstract: The fully-standardised 26 geomorphometric variables consist of layers that describe the (i) rate of change across the elevation gradient, using first and second derivatives, (ii) ruggedness, and (iii) geomorphological forms. The Geomorpho90m variables are available at 3 (~90 m) and 7.5 arc-second (~250 m) resolutions under the WGS84 geodetic datum, and 100 m spatial resolution under the Equi7 projection. They are useful for modelling applications in fields such as geomorphology, geology, hydrology, ecology and biogeography.

Data format

Data type: Land Cover
Data origin: Measured
Data format: GeoTIFF
Other format:
Data resolution: In 100m, 3 arc-seconds, and 7.5 arc-seconds
Datum: WGS84

Data Coverage

Spatial data coverage: Global
Temporal data coverage: Time snap shot
Time period covered: 02/11/2000 - 04/01/2011

Availability

Download data: https://portal.opentopography.org/dataSearch?search=Geomorpho90m
Data source: https://portal.opentopography.org/dataspace/dataset?opentopoID=OTDS.012020.4326.1

References

  • Amatulli, G., McInerney, D., Sethi, T. et al. Geomorpho90m, empirical evaluation and accuracy assessment of global high-resolution geomorphometric layers. Sci Data 7, 162 (2020). https://doi.org/10.1038/s41597-020-0479-6
  • Amatulli, G., McInerney, D., Sethi, T., Strobl, P., Domisch, S. (2020). Geomorpho90m - Global High-Resolution Geomorphometry Layers. Distributed by OpenTopography. https://doi.org/10.5069/G91R6NPX. Accessed: 2020-06-12