Grid analysis¶

Tanım¶

<put algorithm description here>

Parametreler¶

Cost Grid [raster]

<put parameter description here>

Direction of max cost [raster]

<put parameter description here>

Destination Points [raster]

<put parameter description here>

k factor [number]

<put parameter description here>

Default: 1

Threshold for different route [number]

<put parameter description here>

Default: 0

Çıkışlar¶

Accumulated Cost [raster]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:accumulatedcostanisotropic', cost, direction, points, k, threshold, acccost)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Cost Grid [raster]

<put parameter description here>

Destination Points [raster]

<put parameter description here>

Threshold for different route [number]

<put parameter description here>

Default: 0.0

Çıkışlar¶

Accumulated Cost [raster]

<put output description here>

Closest Point [raster]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:accumulatedcostisotropic', cost, points, threshold, acccost, closestpt)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Input Grid [raster]

<put parameter description here>

Max. Number of Classes [number]

<put parameter description here>

Default: 5

Çıkışlar¶

Result [table]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:aggregationindex', input, maxnumclass, result)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Input Grids [multipleinput: rasters]

<put parameter description here>

Pairwise Comparisons Table [table]

<put parameter description here>

Çıkışlar¶

Output Grid [raster]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:analyticalhierarchyprocess', grids, table, output)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Input Grid 1 [raster]

<put parameter description here>

Input Grid 2 [raster]

<put parameter description here>

Max. Number of Classes [number]

<put parameter description here>

Default: 5

Çıkışlar¶

Cross-Classification Grid [raster]

<put output description here>

Cross-Tabulation Table [table]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:crossclassificationandtabulation', input, input2, maxnumclass, resultgrid, resulttable)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Classification [raster]

<put parameter description here>

Class Identifier [number]

<put parameter description here>

Default: 1

Neighborhood Min [number]

<put parameter description here>

Default: 1

Neighborhood Max [number]

<put parameter description here>

Default: 1

Level Aggregation [selection]

<put parameter description here>

Options:

• 0 — [0] average
• 1 — [1] multiplicative

Default: 0

Add Border [boolean]

<put parameter description here>

Default: True

Connectivity Weighting [number]

<put parameter description here>

Default: 1.1

Minimum Density [Percent] [number]

<put parameter description here>

Default: 10

Minimum Density for Interior Forest [Percent] [number]

<put parameter description here>

Default: 99

Search Distance Increment [number]

<put parameter description here>

Default: 0.0

Density from Neighbourhood [boolean]

<put parameter description here>

Default: True

Çıkışlar¶

Density [Percent] [raster]

<put output description here>

Connectivity [Percent] [raster]

<put output description here>

Fragmentation [raster]

<put output description here>

Summary [table]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:fragmentationalternative', classes, class, neighborhood_min, neighborhood_max, aggregation, border, weight, density_min, density_int, level_grow, density_mean, density, connectivity, fragmentation, fragstats)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Density [Percent] [raster]

<put parameter description here>

Connectivity [Percent] [raster]

<put parameter description here>

Add Border [boolean]

<put parameter description here>

Default: True

Connectivity Weighting [number]

<put parameter description here>

Default: 0

Minimum Density [Percent] [number]

<put parameter description here>

Default: 10

Minimum Density for Interior Forest [Percent] [number]

<put parameter description here>

Default: 99

Çıkışlar¶

Fragmentation [raster]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:fragmentationclassesfromdensityandconnectivity', density, connectivity, border, weight, density_min, density_int, fragmentation)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Classification [raster]

<put parameter description here>

Class Identifier [number]

<put parameter description here>

Default: 1

Neighborhood Min [number]

<put parameter description here>

Default: 1

Neighborhood Max [number]

<put parameter description here>

Default: 3

Level Aggregation [selection]

<put parameter description here>

Options:

• 0 — [0] average
• 1 — [1] multiplicative

Default: 0

Add Border [boolean]

<put parameter description here>

Default: True

Connectivity Weighting [number]

<put parameter description here>

Default: 1.1

Minimum Density [Percent] [number]

<put parameter description here>

Default: 10

Minimum Density for Interior Forest [Percent] [number]

<put parameter description here>

Default: 99

Neighborhood Type [selection]

<put parameter description here>

Options:

• 0 — [0] square
• 1 — [1] circle

Default: 0

Include diagonal neighbour relations [boolean]

<put parameter description here>

Default: True

Çıkışlar¶

Density [Percent] [raster]

<put output description here>

Connectivity [Percent] [raster]

<put output description here>

Fragmentation [raster]

<put output description here>

Summary [table]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:fragmentationstandard', classes, class, neighborhood_min, neighborhood_max, aggregation, border, weight, density_min, density_int, circular, diagonal, density, connectivity, fragmentation, fragstats)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Grids [multipleinput: rasters]

<put parameter description here>

Method [selection]

<put parameter description here>

Options:

• 0 — [0] Maximum
• 1 — [1] Minimum

Default: 0

Çıkışlar¶

Result [raster]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:layerofextremevalue', grids, criteria, result)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Source Point(s) [vector: point]

<put parameter description here>

Accumulated cost [raster]

<put parameter description here>

Values [multipleinput: rasters]

Optional.

<put parameter description here>

Çıkışlar¶

Profile (points) [vector]

<put output description here>

Profile (lines) [vector]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:leastcostpaths', source, dem, values, points, line)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Input Grids [multipleinput: rasters]

<put parameter description here>

Weights [fixedtable]

<put parameter description here>

Çıkışlar¶

Output Grid [raster]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:orderedweightedaveraging', grids, weights, output)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Input Grid [raster]

<put parameter description here>

Size of Analysis Window [selection]

<put parameter description here>

Options:

• 0 — [0] 3 X 3
• 1 — [1] 5 X 5
• 2 — [2] 7 X 7

Default: 0

Max. Number of Classes [number]

<put parameter description here>

Default: 0

Çıkışlar¶

Relative Richness [raster]

<put output description here>

Diversity [raster]

<put output description here>

Dominance [raster]

<put output description here>

Fragmentation [raster]

<put output description here>

Number of Different Classes [raster]

<put output description here>

Center Versus Neighbours [raster]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:patternanalysis', input, winsize, maxnumclass, relative, diversity, dominance, fragmentation, ndc, cvn)

Ayrıca bakınız¶

Tanım¶

<put algorithm description here>

Parametreler¶

Sand [raster]

Optional.

<put parameter description here>

Silt [raster]

Optional.

<put parameter description here>

Clay [raster]

Optional.

<put parameter description here>

Çıkışlar¶

Soil Texture [raster]

<put output description here>

Sum [raster]

<put output description here>

Konsol kullanımı¶

processing.runalg('saga:soiltextureclassification', sand, silt, clay, texture, sum)

Ayrıca bakınız¶