NAME
r.forestfrag - Computes the forest fragmentation index (Riitters et al. 2000)
KEYWORDS
raster,
landscape structure analysis,
forest,
fragmentation index,
Riitters
SYNOPSIS
r.forestfrag
r.forestfrag --help
r.forestfrag [-rtsa] input=name output=name [size=number] [pf=name] [pff=name] [window=integer] [--overwrite] [--help] [--verbose] [--quiet] [--ui]
Flags:
- -r
- Set computational region to input raster map
- -t
- Keep Pf and Pff maps
- -s
- Run r.report on output map
- -a
- Trim the output map to avoid border effects
- --overwrite
- Allow output files to overwrite existing files
- --help
- Print usage summary
- --verbose
- Verbose module output
- --quiet
- Quiet module output
- --ui
- Force launching GUI dialog
Parameters:
- input=name [required]
- Name of forest raster map (where forest=1, non-forest=0)
- output=name [required]
- Name for output raster map
- size=number
- Moving window size (odd number)
- Options: 3-
- Default: 3
- pf=name
- Name for output Pf (forest area density) raster map
- Proportion of area which is forested (amount of forest)
- pff=name
- Name for output Pff (forest connectivity) raster map
- Conditional probability that neighboring cell is forest
- window=integer
- This option is deprecated, use the option size instead
- Options: 3-
r.forestfrag Computes the forest fragmentation following
the methodology proposed by Riitters et al. (2000). See
this article for a
detailed explanation.
It follows a "sliding window" algorithm with overlapping windows.
The amount of forest and its occurrence as adjacent forest pixels
within fixed-area "moving-windows" surrounding each forest pixel is
measured. The window size is user-defined. The result is stored at
the location of the center pixel. Thus, a pixel value in the derived
map refers to "between-pixel" fragmentation around the corresponding
forest location.
As input it requires a binary map with (1) forest and (0)
non-forest. Obviously, one can replace forest any other land cover
type. If one wants to exclude the influence of a specific land cover
type, e.g., water bodies, it should be classified as no-data (NA) in
the input map. See e.g.,
blog post.
Let Pf be the proportion of pixels in the window that
are forested. Define Pff (strictly) as the proportion of
all adjacent (cardinal directions only) pixel pairs that include at
least one forest pixel, for which both pixels are forested. Pff
thus (roughly) estimates the conditional probability that,
given a pixel of forest, its neighbor is also forest. The
classification model then identifies six fragmentation categories as:
interior: Pf = 1.0
patch: Pf < 0.4
transitional: 0.4 ≤ Pf < 0.6
edge: Pf ≥ 0.6 and Pf - Pff < 0
perforated: Pf ≥ 0.6 and Pf - Pff > 0
undetermined: Pf ≥ 0.6 and Pf = Pff
- The moving window size is user-defined (default=3)
and must be an odd number. If an even number is given, the function
will stop with an error message.
- No-data cells are ignored. This means that statistics at the
raster edges are based on fewer cells (smaller) moving windows. If this
is a problem, the user can choose to have the output raster trimmed
with a number of raster cells equal to 1/2 * the size of the moving
window.
- The function respects the region. However, the user has the option
to set the region to match the input layer.
In the North Carolina sample Location, set the computational region
to match the land classification raster map:
g.region raster=landclass96
Then mark all cells which are forest as 1 and everything else as zero:
r.mapcalc "forest = if(landclass96 == 5, 1, 0)"
Use the new forest presence raster map to compute the forest
fragmentation index with window size 7:
r.forestfrag input=forest output=fragmentation window=7
Two forest fragmentation indices with window size 7 (left) and
11 (right) show how increasing window size increases the amount of
edges.
r.mapcalc,
r.li
The addon is based on the
r.forestfrag.sh script, with as extra options user-defined
moving window size, option to trim the region (by default it
respects the region) and a better handling of no-data cells.
Riitters, K., J. Wickham, R. O'Neill, B. Jones,
and E. Smith. 2000. Global-scale patterns of forest fragmentation.
Conservation Ecology 4(2): 3. [online] URL:
https://www.consecol.org/vol4/iss2/art3/
Emmanuel Sambale (original shell version)
Stefan Sylla (original shell version)
Paulo van Breugel (Python version, user-defined moving window size)
Vaclav Petras (major code clean up)
SOURCE CODE
Available at:
r.forestfrag source code
(history)
Latest change: Thursday Feb 03 09:32:35 2022 in commit: f17c792f5de56c64ecfbe63ec315307872cf9d5c
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