mean [ USGS LandDAAC uy_NDWI_SP NDWI_SP ]: NDWI por Seccional Policial data
USGS LandDAAC uy_NDWI_SP NDWI_SP NDWI por Seccional Policial from SOURCES: datos de MGAP SNIA prueba.
is
Independent Variables (Grids)
Other Info
- add_offset_err
- 0.0
- bufferwordsize
- 8
- calibrated_nt
- 5
- CE
- null
- CS
- null
- datatype
- doublearraytype
- maxncolor
- 254
- missing_value
- NaN
- pointwidth
- 0
- scale_factor_err
- 0.0
- SpatialReferenceSystemDims
- X
Y
- SpatialReferenceSystemWKT
- GEOGCS["WGS 84",DATUM["WGS_1984",SPHEROID["WGS 84",6378137,298.257223563,AUTHORITY["EPSG","7030"]],TOWGS84[0,0,0,0,0,0,0],AUTHORITY["EPSG","6326"]],PRIMEM["Greenwich",0,AUTHORITY["EPSG","8901"]],UNIT["degree",0.01745329251994328,AUTHORITY["EPSG","9122"]],AUTHORITY["EPSG","4326"]]
- units
- unitless
- valid_range
- 0
10000 - history
- USGS LandDAAC uy_NDWI_SP NDWI_SP
- Boxes with less than 0.0% dropped
Boxes with less than 0.0% dropped
mean [ USGS LandDAAC uy_NDWI_SP NDWI_SP ]- Averaged over depto_sec[0101, 1911] T[18 Feb 2000 - 4 Mar 2000, 2400 6 Apr 2025] minimum 0.0% data present
Last updated: Fri, 11 Apr 2025 08:25:46 GMT
Expires: Sat, 26 Apr 2025 00:00:00 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