Geophys Database

Aggregated description of the geospatial databases supported by GenPhysX.

General notes

• Please refer to the individual pages of the geospatial databases to learn about their specifications.
• If your target grid is of higher spatial resolution than any of the source geospatial database, you must specify 'celldim =2' when running GenPhysX otherwise some of the target grid points will be empty.
• Ayrton Zadra documented examples of problems with current databases, screenshots included. Specifically:
  • "Ghost" mountain in USGS BC area
  • CDED topography missing near the coast of some areas
  • Discrepancies between vegetation databases
  • Border impact of SRTM and USGS topography
• Consistency among databases is not guaranteed.
• The geospatial databases are located on hawa:/data/shared_1_b0/armn/

Topography

Here's the Digital elevation models available in GenPhysX. Derived parameters are:

• Orography (LH, Y7, Y8, Y9, Z0 and ZP)
• Slope (SLA)
• Aspect (FSA)

Name	Resolution	Coverage	Pros	Cons
GTOPO30 (aka "USGS")	~ 900m	Global	Used by various operational models No gaps	Low resolution Some glitches at high latitudes Missing small islands Some known errors (e.g. "ghost" mountain in BC) Bad choice for Z0 of grids under 10Km resolution
USNAVY	~ 18.5 Km	Global	Used by Genesis	Low resolution
GMTED2010 (GMTED30)(GMTED15)(GMTED75)	~1km, ~500m, ~250m	-56<lat<+84 Only product MEAN30 has Antarctica and Groenland	Available at 3 spatial resolutions	Tested by few users Missing Antarctica and Groenland for all products except MEAN of GMTED30 Original data all have a square area with 0 as value in lake Superior, this has been repaired by replacing 0 with value=height of lake.
SRTM-DEM	~ 30m for v3.0 (90m for SRTMv4)	-60<lat<+60	High resolution	High latitudes missing Tested by few users
ASTER GDEM	~ 30m	-83<lat<+83	Very high resolution	“Experimental” or “research grade” product Tested by few users
CDED250	~ 90m	Canada	High resolution	Tested by few users See limitations
CDED50	~ 20m	Canada	Very high resolution	Tested by few users See limitations
CDEM	~ 20m	Canada	Very high resolution	Tested by few users See limitations

Warnings and notes

(this is in French since directly copied from a previous source) Voici quelques éléments important à prendre en compte lors du traitement de DEMs haute résolution avec GenPhysX :

• Lorsque la région d'intérêt (i.e. le fichier standard) couvre une partie du Canada et des États-Unis : lorsque les données DNEC1 et SRTM-DEM sont utilisés pour l'orographie d'un même fichier standard, le phénomène suivant se produit pour les valeurs de pentes; puisque la pente dépend fortement de la résolution spatiale des données sources et qu'il y a une différence de résolution spatiale importante (un facteur 4) entre DNEC1 et SRTM-DEM, les valeurs de pentes ont des plages de valeur différentes d'une part et d'autre de la frontière et ne peuvent conséquemment être comparées. Les nombreux échanges avec Jocelyn Mailhot semblent indiquer que ce phénomène ne constitue pas un problème pour les modèles météo puisque les valeurs de pente et d'aspect ne sont considérés que localement et jamais globalement.
• Les valeurs d'Aspect (orientation de la pente) lorsque la pente est nulle : il a été convenu que lorsque les pentes sont nulles, par exemple sur les surfaces d'eau, la moyenne d'aspect par cadran sera nulle pour tous les cadrans.
• Les données DNEC1 dans les régions plates : les données DNEC1 d'origine sont arrondies à l'entier le plus près. Cette réalité devient problématique lors du calcul de la pente et de l'aspect pour les régions avec peu de dénivellations, par exemple dans les prairies canadiennes. On observe aisément l'effet d'escalier sur les résultats de pente et d'aspect sur le fichier standard à plus basse résolution. Une solution envisagée mais qui n'a pas été mise en oeuvre est de passer un filtre passe-bas 3x3 sur les données DNEC1 pour les régions plates, cela réduirait l'effet indésirable mais réduit la qualité des données d'origine.

Land-Water Mask (MG)

This correspond to the 'fractional land coverage area' and the 'MG' field. At the moment, it is not possible to combine land-water mask databases. See page Land-Water Mask for more information.

Name	Resolution	Coverage	Pros	Cons
MCD12Q1	~ 500m	Global	Used by various operational models Best available resolution for Global coverage	Tested by few users
USGS	~ 900m	Global	Used by various operational models	Low resolution The following errors are found in RPN-FST version only (in use), original Geotiff version is error free (not in use) Various islands missing Corrupted data for Hawai islands Crete island eaten away by missing values not enough water buffer surrounding land, missing values too near or next to land. Coastal land ratios are wrong and too high in many cases. Therefore, this version is not recommended for use on its own. Currently. The Raster version of USGS will be accessible as "USGS_R"
USNAVY	~ 18.5km	Global	Used by Genesis to complete USGS (RPN-FST version)	Low resolution Contains several errors (fake islands near Columbia, Somalia and Antarctica)
GLC2000	~ 1km	Global		No distinction between ocean and inland-lake Tested by few users
GlobCover	~ 300m	lat>-65.0	Medium resolution Good representation of lakes	Antarctica missing No distinction between ocean, inland-lake and nodata THUS UNUSABLE FOR MG IN ITS PRESENT STATE Tested by few users
CCI_LC	~ 300m	Global	Medium resolution coverage over Antarctica	Lake, sea-water and no-data are all the same value (210) No distinction between ocean, inland-lake Tested by few users
CanVec	~ 20m	Canada	Very high resolution Vector data	Tested by few users
AAFC (2015)	30m	Canada (partial)	High resolution	Areas may have 'nodata' value because of cloud coverage Tested by few users Missing data in Northern part of most provinces, where there are no crops.

Land Use Land Cover (VG)

All classes must be remapped to the 26-classes RPN VG classification via a look-up table (LUT). Information from original datasets is severely degraded in the process.

Name	Resolution	Coverage	Pros	Cons
MCD12Q1	~ 500m	Global	Used by various operational models Best available resolution for Global coverage	Medium resolution
USGS USGS_R	~ 900m	Global	Used by various operational models	Low resolution Same comments as USGS mask, the RPN FST format version contains many errors The Raster version of USGS will be accessible as "USGS_R"
CCRN	~ 100km	Global	Used by Genesis as filler for USGS	Low resolution
GlobCover	~ 300m	lat > -65	Medium resolution	Antarctica missing Lake, sea-water and no-data are all the same value (210) Correspondence table questioned Tested by few users Where lands are seen as very bright or white in color (Quarry, Sands) could be reported as Glaciers (44.685N, 79.495W)
CCI_LC	~ 300m	Global	Medium resolution coverage over Antarctica Where lands are seen as very bright or white in color (Quarry, Sands) are reported correctly as bare areas (200)	Lake, sea-water and no-data are all the same value (210) Correspondence table questioned Tested by few users
GLC2000	~ 1km	Global	Global	Tested by few users
CCRS	~ 250m	Canada	Medium resolution	See details here Lake, sea-water and no-data are all the same value (37) Correspondence table provisory Tested by few users
EOSD	25m	Canada (partial)	High resolution	Correspondence table provisory Strong classification for forested areas, weaker for other cover types. Areas may have 'nodata' value because of cloud coverage Tested by few users Missing data in south of Alberta, Saskatchewan, Manitoba and Ontario, and on the northern regions of Canada. No urban areas, all seen as bare soil
CORINE	~ 250m	Europe	Medium resolution	Missing Yugoslavia, Switzerland and Norway Tested by few users
LCC2000-V	~ 30m	Canada	High resolution Combines data from AAFC, CFS (EOSD) and CCRS	Tested by few users Long processing time
AAFC (2015)	30m	Canada (partial)	High resolution	Correspondence table provisory Strong classification for crops areas. Areas may have 'nodata' value because of cloud coverage Tested by few users Missing data in Northern part of most provinces, where there are no crops.
NALCMS (2010)	250m, 30m	North America	Medium resolution Very High resolution	Correspondence table provisory Updated 2010 data on land cover changes Data available for North America only

Comparisons of Land Use Land Cover Datasets

• NALCMS vs. CCI_LC

Vegetation Canopy Height

Values on land only are to be considered, all values on water must be ignored
All values on urban areas should be ignored (0.01 m !!!)

Name	Resolution	Coverage	Pros	Cons
GLAS	~ 900m, 30 arc sec	Global	Modification was made to replace all 0 on water by NoData=255	NoData not defined No distinction between 0 on land and 0 on water

Soil

Name	Resolution	Coverage	Pros	Cons
USDA	~ 1km	USA	Used by various operational models 5 layers (originally 11 layers but regrouped as 5)	USA only
AGRC	~ 10km	Canada	Used by many operational models	Canada only One layer only Rather noisy Low resolution
FAO	~ 1 degree	Global	Used by various operational models No gaps	One layer only Low resolution
HWSD	30 arc sec (1km at equator)	Global	Two layers (top and sub)	Untested
JPL	~ 112 arc sec (3.5Km at equator)	Global	No gaps	One layer only Untested
CANSIS	~ 1km	North America, part of Russia and Greenland	3 layers (10,25,375 cm) Used by CRCM III (Canadian Regional Climate Model) contains also depth to bedrock data.	North America only
BNU	~ 1km	Global	8 layers (.045,.091, 0.166, 0.289, 0.493, 0.829, 1.383, 2.296 m) contains also soil Hydraulic parameters and more. Most recent and detailed soil data	Untested
Gridded SLC	~ 90m	Canada only	6 layers ( 0-5cm, 5-15cm, 15-30cm, 30-60cm, 60-100cm, 100-200cm ) Most recent and detailed soil data over Canada	Untested
GSRS	30 arcsec (1km)	Global 60S to 90N	Contains only Thickness of Soil to bedrock	Untested

Warnings and notes

• See the problems related to the masking of US Department of Agriculture soil types

Hydrology

Name	Resolution	Coverage	Pros	Cons
NHN	0.0000001 degree	Canada
NHD	0.0000001 degree	USA

Geoid Height

Name	Resolution	Coverage	Pros	Cons
EGM96	1/4 degree	Global
EGM2008	1/24 degree	Global

See also

• GenPhysX's documentation
• GenPhysX's geospatial databases prospection
• Geospatial databases at the CMC