root mean sq mean [ SoilGrids GYGA_Results_ll Aggregated_over30cm coarse_frag_cont ] : Coarse fragments content data
root mean sq Coarse fragments content: Coarse fragments content (v\%) of the whole earth, aggregated over the top 30 cm.
is
Independent Variables (Grids)
Other Info
- bufferwordsize
- 8
- CE
- null
- CS
- null
- datatype
- doublearraytype
- missing_value
- NaN
- SpatialReferenceSystemDims
- X
Y
- SpatialReferenceSystemWKT
- GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]]
- units
- percent
- standard units*
- 0.01
- history
- root mean sq mean [ SoilGrids GYGA_Results_ll Aggregated_over30cm coarse_frag_cont ]
- Averaged over X[23.2145W, 56.9045E] minimum 0.0% data present
Averaged over Y[35.0045S, 38.0045N] minimum 0.0% data present
Last updated: Tue, 15 Aug 2017 15:51:28 GMT
Filters
Here are some filters that are useful for manipulating data. There
are actually many more available, but they have to be entered
manually. See
Ingrid
Function Documentation for more information.
- Monthly Climatology calculates
a monthly climatology by averaging over all years.
- anomalies calculates the difference
between the (above) monthly climatology and the original data.
- Integrate along
- Differentiate along
- Take differences along
Average over
RMS (root mean square with mean *not* removed) over
RMSA (root mean square with mean removed) over
Maximum over
Minimum over
Detrend (best-fit-line) over
Note on units