.

Imagery classification

Change detection

설명

<put algorithm description here>

Parameters

Initial State [raster]
<put parameter description here>
Look-up Table [table]

Optional.

<put parameter description here>

Value [tablefield: any]
<put parameter description here>
Value (Maximum) [tablefield: any]
<put parameter description here>
Name [tablefield: any]
<put parameter description here>
Final State [raster]
<put parameter description here>
Look-up Table [table]

Optional.

<put parameter description here>

Value [tablefield: any]
<put parameter description here>
Value (Maximum) [tablefield: any]
<put parameter description here>
Name [tablefield: any]
<put parameter description here>
Report Unchanged Classes [boolean]

<put parameter description here>

Default: True

Output as... [selection]

<put parameter description here>

Options:

  • 0 — [0] cells
  • 1 — [1] percent
  • 2 — [2] area

Default: 0

Outputs

Changes [raster]
<put output description here>
Changes [table]
<put output description here>

Console usage

processing.runalg('saga:changedetection', initial, ini_lut, ini_lut_min, ini_lut_max, ini_lut_nam, final, fin_lut, fin_lut_min, fin_lut_max, fin_lut_nam, nochange, output, change, changes)

See also

Cluster analysis for grids

설명

<put algorithm description here>

Parameters

Grids [multipleinput: rasters]
<put parameter description here>
Method [selection]

<put parameter description here>

Options:

  • 0 — [0] Iterative Minimum Distance (Forgy 1965)
  • 1 — [1] Hill-Climbing (Rubin 1967)
  • 2 — [2] Combined Minimum Distance / Hillclimbing

Default: 0

Clusters [number]

<put parameter description here>

Default: 5

Normalise [boolean]

<put parameter description here>

Default: True

Old Version [boolean]

<put parameter description here>

Default: True

Outputs

Clusters [raster]
<put output description here>
Statistics [table]
<put output description here>

Console usage

processing.runalg('saga:clusteranalysisforgrids', grids, method, ncluster, normalise, oldversion, cluster, statistics)

See also

Supervised classification

설명

<put algorithm description here>

Parameters

Grids [multipleinput: rasters]
<put parameter description here>
Training Areas [vector: polygon]
<put parameter description here>
Class Identifier [tablefield: any]
<put parameter description here>
Method [selection]

<put parameter description here>

Options:

  • 0 — [0] Binary Encoding
  • 1 — [1] Parallelepiped
  • 2 — [2] Minimum Distance
  • 3 — [3] Mahalanobis Distance
  • 4 — [4] Maximum Likelihood
  • 5 — [5] Spectral Angle Mapping
  • 6 — [6] Winner Takes All

Default: 0

Normalise [boolean]

<put parameter description here>

Default: True

Distance Threshold [number]

<put parameter description here>

Default: 0.0

Probability Threshold (Percent) [number]

<put parameter description here>

Default: 0.0

Probability Reference [selection]

<put parameter description here>

Options:

  • 0 — [0] absolute
  • 1 — [1] relative

Default: 0

Spectral Angle Threshold (Degree) [number]

<put parameter description here>

Default: 0.0

Outputs

Class Information [table]
<put output description here>
Classification [raster]
<put output description here>
Quality [raster]
<put output description here>

Console usage

processing.runalg('saga:supervisedclassification', grids, roi, roi_id, method, normalise, threshold_dist, threshold_prob, relative_prob, threshold_angle, class_info, classes, quality)

See also