root mean sq [ 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.
Independent Variables (Grids)
- Time (time)
- grid: /T (days since 2003-01-01) ordered [ (18 Feb 2000 - 4 Mar 2000) (5-20 Mar 2000) (21 Mar 2000 - 5 Apr 2000) ... (22 Mar 2025 - 6 Apr 2025)] N= 578 pts :grid
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
root mean sq [ USGS LandDAAC uy_NDWI_SP NDWI_SP ]- Averaged over depto_sec[0101, 1911] 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 T
- Differentiate along T
- Take differences along T
Average over
T
|
RMS (root mean square with mean *not* removed) over
T
|
RMSA (root mean square with mean removed) over
T
|
Maximum over
T
|
Minimum over
T
|
Detrend (best-fit-line) over
T
|
Note on units