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pktools
2.6.4
Processing Kernel for geospatial data
|
produce kalman filtered raster time series
-short
or --long
options (both --long=value
and --long value
are supported)-h
shows basic options only, long option --help
shows all optionsshort | long | type | default | description |
---|---|---|---|---|
dir | direction | std::string | forward | direction to run model (forward|backward|smooth) |
mod | model | std::string | model input datasets, e.g., MODIS (use: -mod model1 -mod model2 etc. | |
obs | observation | std::string | observation input datasets, e.g., landsat (use: -obs obs1 -obs obs2 etc. | |
tmod | tmodel | int | time sequence of model input. Sequence must have exact same length as model input. Leave empty to have default sequence 0,1,2,etc. | |
tobs | tobservation | int | time sequence of observation input. Sequence must have exact same length as observation input) | |
a_srs | a_srs | std::string | Override the projection for the output file (leave blank to copy from input file, use epsg:3035 to use European projection and force to European grid | |
ofw | outputfw | std::string | Output raster dataset for forward model | |
obw | outputbw | std::string | Output raster dataset for backward model | |
ofb | outputfb | std::string | Output raster dataset for smooth model | |
modnodata | modnodata | double | 0 | invalid value for model input |
obsnodata | obsnodata | double | 0 | invalid value for observation input |
obsmin | obsmin | double | Minimum value for observation data | |
obsmax | obsmax | double | Maximum value for observation data | |
eps | eps | double | 1e-05 | epsilon for non zero division |
um | uncertmodel | double | 2 | Multiply this value with std dev of first model image to obtain uncertainty of model |
uo | uncertobs | double | 0 | Uncertainty of valid observations |
unodata | uncertnodata | double | 10000 | Uncertainty in case of no-data values in observation |
q | q | double | 1 | Process noise: expresses instability (variance) of proportions of fine res pixels within a moderate resolution pixel |
down | down | int | Downsampling factor for reading model data to calculate regression | |
co | co | std::string | Creation option for output file. Multiple options can be specified. | |
v | verbose | short | 0 | verbose mode when positive |
produce kalman filtered raster time series
-short
or --long
options (both --long=value
and --long value
are supported)-h
shows basic options only, long option --help
shows all optionsshort | long | type | default | description |
---|---|---|---|---|
dir | direction | std::string | forward | direction to run model (forward|backward|smooth) |
mod | model | std::string | model input datasets, e.g., MODIS (use: -mod model1 -mod model2 etc. | |
obs | observation | std::string | observation input datasets, e.g., landsat (use: -obs obs1 -obs obs2 etc. | |
tmod | tmodel | int | time sequence of model input. Sequence must have exact same length as model input. Leave empty to have default sequence 0,1,2,etc. | |
tobs | tobservation | int | time sequence of observation input. Sequence must have exact same length as observation input) | |
a_srs | a_srs | std::string | Override the projection for the output file (leave blank to copy from input file, use epsg:3035 to use European projection and force to European grid | |
ofw | outputfw | std::string | Output raster dataset for forward model | |
obw | outputbw | std::string | Output raster dataset for backward model | |
ofb | outputfb | std::string | Output raster dataset for smooth model | |
modnodata | modnodata | double | 0 | invalid value for model input |
obsnodata | obsnodata | double | 0 | invalid value for observation input |
modoffset | modoffset | double | offset used to read model input dataset (value=offset+scale*readValue | |
modscale | modscale | double | scale used to read model input dataset (value=offset+scale*readValue | |
obsoffset | obsoffset | double | offset used to read observation input dataset (value=offset+scale*readValue | |
obsscale | obsscale | double | scale used to read observation input dataset (value=offset+scale*readValue | |
eps | eps | double | 1e-05 | epsilon for non zero division |
um | uncertmodel | double | 2 | Multiply this value with std dev of first model image to obtain uncertainty of model |
uo | uncertobs | double | 0 | Uncertainty of valid observations |
w | weight | double | Set observation uncertainty as weighted difference between observation and model (use -w 0 to use a constant observation uncertainty, use -w value >> 1 to penalize low observation values with respect to model, use -w value << 0 to penalize a high observation values with respect to model | |
dobs | deltaobs | double | Lower and upper thresholds for relative pixel differences (in percentage): (observation-model)/model. For instance to force the observation within a +/- 10 % interval, use: -dobs -10 -dobs 10 (equivalent to -dobs 10). Leave empty to always update on observation | |
unodata | uncertnodata | double | 10000 | Uncertainty in case of no-data values in observation |
rt | regtime | double | 1 | Set optional regression for sensor difference (model - observation). |
rs | regsensor | double | 1 | Set optional regression for sensor difference (model - observation). |
down | down | int | Downsampling factor for reading model data to calculate regression | |
th | threshold | float | 0 | threshold for selecting samples (randomly). Provide probability in percentage (>0) or absolute (<0). |
win | window | unsigned short | 0 | window size for calculating regression (use 0 for global) |
co | co | std::string | Creation option for output file. Multiple options can be specified. | |
v | verbose | short | 0 | verbose mode when positive |