<put algorithm description here>
Cost Grid
[raster]Direction of max cost
[raster]Destination Points
[raster]k factor
[number]<put parameter description here>
Default: 1
Threshold for different route
[number]<put parameter description here>
Default: 0
Accumulated Cost
[raster]processing.runalg('saga:accumulatedcostanisotropic', cost, direction, points, k, threshold, acccost)
<put algorithm description here>
Cost Grid
[raster]Destination Points
[raster]Threshold for different route
[number]<put parameter description here>
Default: 0.0
Accumulated Cost
[raster]Closest Point
[raster]processing.runalg('saga:accumulatedcostisotropic', cost, points, threshold, acccost, closestpt)
<put algorithm description here>
Input Grid
[raster]Max. Number of Classes
[number]<put parameter description here>
Default: 5
Result
[table]processing.runalg('saga:aggregationindex', input, maxnumclass, result)
<put algorithm description here>
Input Grids
[multipleinput: rasters]Pairwise Comparisons Table
[table]Output Grid
[raster]processing.runalg('saga:analyticalhierarchyprocess', grids, table, output)
<put algorithm description here>
Input Grid 1
[raster]Input Grid 2
[raster]Max. Number of Classes
[number]<put parameter description here>
Default: 5
Cross-Classification Grid
[raster]Cross-Tabulation Table
[table]processing.runalg('saga:crossclassificationandtabulation', input, input2, maxnumclass, resultgrid, resulttable)
<put algorithm description here>
Classification
[raster]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:
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
Density [Percent]
[raster]Connectivity [Percent]
[raster]Fragmentation
[raster]Summary
[table]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)
<put algorithm description here>
Density [Percent]
[raster]Connectivity [Percent]
[raster]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
Fragmentation
[raster]processing.runalg('saga:fragmentationclassesfromdensityandconnectivity', density, connectivity, border, weight, density_min, density_int, fragmentation)
<put algorithm description here>
Classification
[raster]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:
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:
Default: 0
Include diagonal neighbour relations
[boolean]<put parameter description here>
Default: True
Density [Percent]
[raster]Connectivity [Percent]
[raster]Fragmentation
[raster]Summary
[table]processing.runalg('saga:fragmentationstandard', classes, class, neighborhood_min, neighborhood_max, aggregation, border, weight, density_min, density_int, circular, diagonal, density, connectivity, fragmentation, fragstats)
<put algorithm description here>
Grids
[multipleinput: rasters]Method
[selection]<put parameter description here>
Options:
Default: 0
Result
[raster]processing.runalg('saga:layerofextremevalue', grids, criteria, result)
<put algorithm description here>
Source Point(s)
[vector: point]Accumulated cost
[raster]Values
[multipleinput: rasters]Optional.
<put parameter description here>
Profile (points)
[vector]Profile (lines)
[vector]processing.runalg('saga:leastcostpaths', source, dem, values, points, line)
<put algorithm description here>
Input Grids
[multipleinput: rasters]Weights
[fixedtable]Output Grid
[raster]processing.runalg('saga:orderedweightedaveraging', grids, weights, output)
<put algorithm description here>
Input Grid
[raster]Size of Analysis Window
[selection]<put parameter description here>
Options:
Default: 0
Max. Number of Classes
[number]<put parameter description here>
Default: 0
Relative Richness
[raster]Diversity
[raster]Dominance
[raster]Fragmentation
[raster]Number of Different Classes
[raster]Center Versus Neighbours
[raster]processing.runalg('saga:patternanalysis', input, winsize, maxnumclass, relative, diversity, dominance, fragmentation, ndc, cvn)
<put algorithm description here>
Sand
[raster]Optional.
<put parameter description here>
Silt
[raster]Optional.
<put parameter description here>
Clay
[raster]Optional.
<put parameter description here>
Soil Texture
[raster]Sum
[raster]processing.runalg('saga:soiltextureclassification', sand, silt, clay, texture, sum)