Processing Kernel for remote sensing data
|
program to compare two raster image files
Usage: pkdiff -i input -ref reference
Options: [-ln layer] [-b band] [-cm] [-lr attribute] [-c name -r value]* [-nodata value]* [-m mask] [-msknodata value]*
Advanced options: [-o output] [-f OGR format] [-lc attribute] [-bnd value [-hom] [-circ]] [-ct colortable] [-co NAME=VALUE]*
The utility pkdiff compares two datasets. The reference can either be a raster or a vector, but the input must be a raster dataset. In case the reference is a raster dataset, a pixel by pixel comparison is performed. With no further options, the utility reports if the rasters are identical or different. If required, an output raster dataset can be written with a qualitative information per pixel: 0 (input=reference), 1 (input>reference) or 2 (input<reference). If, however, the reference is a vector dataset, it must consist of point features. Polygon features are automatically converted to the centroid points before analyzing.
A typical use of the utility is to assess the accuracy of an input raster land cover map, based on a reference vector dataset. The reference dataset must contain an attribute (label) for each class. A confusion matrix is produced if the option -cm|–confusion is set. Here too, an output dataset can be written, which will be a vector dataset in this case. It contains the reference feature points with the extracted data value of the raster input dataset as a new attribute.
-short
or --long
options (both --long=value
and --long value
are supported)-h
shows basic options only, long option --help
shows all options short | long | type | default | description |
---|---|---|---|---|
i | input | std::string | Input raster dataset. | |
ref | reference | std::string | Reference (raster or vector) dataset | |
ln | ln | std::string | Layer name(s) in sample. Leave empty to select all (for vector reference datasets only) | |
b | band | short | 0 | Input (reference) raster band. Optionally, you can define different bands for input and reference bands respectively: -b 1 -b 0. |
rmse | rmse | bool | false | Report root mean squared error |
reg | reg | bool | false | Report linear regression (Input = c0+c1*Reference) |
cm | confusion | bool | false | Create confusion matrix (to std out) |
lr | lref | std::string | label | Attribute name of the reference label (for vector reference datasets only) |
c | class | std::string | List of class names. | |
r | reclass | short | List of class values (use same order as in classname option). | |
nodata | nodata | short | No data value(s) in input or reference dataset are ignored | |
m | mask | std::string | Use the first band of the specified file as a validity mask. Nodata values can be set with the option msknodata. | |
msknodata | msknodata | double | 0 | Mask value(s) where image is invalid. Use negative value for valid data (example: use -t -1: if only -1 is valid value) |
o | output | std::string | Output dataset (optional) | |
f | f | std::string | SQLite | OGR format for output vector (for vector reference datasets only) |
lc | lclass | std::string | class | Attribute name of the classified label (for vector reference datasets only) |
bnd | boundary | short | 1 | Boundary for selecting the sample (for vector reference datasets only) |
hom | homogeneous | bool | false | Only take regions with homogeneous boundary into account (for reference datasets only) |
circ | circular | bool | false | Use circular boundary (for vector reference datasets only) |
ct | ct | std::string | Color table in ASCII format having 5 columns: id R G B ALFA (0: transparent, 255: solid). | |
co | co | std::string | Creation option for output file. Multiple options can be specified. | |
commission | short | 2 | Value for commission errors: input label < reference label |
Some examples how to use pkdiff can be found here