Restoration Status Summary

Restoration Status Summary (RSS) computes patch-based connectivity indices for a binary raster map. RSS characterises the spatial structure of the foreground by analysing the size distribution of individual patches, providing a set of indices that quantify landscape connectivity and restoration potential. Further details about Restoration Status Summary analysis are available in the RSS product sheet.

Note

RSS produces a statistics report only; it does not write a classified output map. All results are returned in the dictionary and, optionally, the .txt report. rss() computes its statistics as part of the main run; there is no separate standalone *_stats() function for this tool.

Functions

pyguidos.rss(in_tiff, outdir=None, stat_files=True, verb=False)

Performs Restoration Status Summary (RSS) analysis on a binary or multi-class raster. Computes patch-based habitat network indices including Equivalent Connected Area (ECA), Coherence (COH) and Restoration Potential (REST_POT) from the patch size distribution.

Parameters:

• in_tiff (str or Path) – Path to input GeoTIFF (0=NoData, 1=Background, 2=Foreground; optionally 3/4 for special background classes).

• outdir (str or Path, optional) – Output directory. If None (default), outputs are written to the input file’s directory.

• stat_files (bool, optional) – If True, writes a .txt report file.

• verb (bool, optional) – If True, prints progress messages.

Returns:

dict – A dictionary containing three main sections:

• "output paths" (dict or None):

  • "path txt" (str) – Absolute path to the statistics report (RSS writes no GeoTIFF).

• "input stats" (dict):

  • "foreground pxl" (int) – Count of foreground pixels.

  • "background pxl" (int) – Count of background pixels.

  • "missing pxl" (int) – Count of NoData pixels.

  • "backgr3 pxl" (int) – Count of special background class 3 pixels.

  • "backgr4 pxl" (int) – Count of special background class 4 pixels.

• "output stats" (dict):

  • "total patches" (int) – Total number of discrete foreground patches.

  • "average patch size" (float) – Mean patch size in pixels.

  • "median patch size" (float) – Median patch size in pixels.

  • "largest patch size" (int) – Size of the largest single patch in pixels.

  • "CNOA" (int) – Critical New Object Area.

  • "ECA" (int) – Equivalent Connected Area.

  • "RAC" (float) – Reference Area Coverage (%).

  • "COH" (float) – Coherence index (%).

  • "REST_POT" (float) – Restoration Potential index (%), equal to 100 - COH.

Outputs:

The function writes the following output file with stat_files=True:

• <input_filename>_rss.txt: Statistics report with all connectivity indices

Example

Standard execution of the RSS analysis with default parameters using the Forest/Non-Forest GeoTIFF file of Corsica stored on pyguidos/data folder:

>>> import pyguidos as pg
>>> forest_map = pg.DATA_DIR / "CLC2018_corsica_FNF.tif"
>>> rss_result = pg.rss(in_tiff=forest_map, outdir="output/",
... stat_files=True, verb=False)
>>> rss_result['output stats']['COH']
8.123809429358433
>>> rss_result['output stats']['median patch size']
        726.4178743961353
>>> rss_result['output paths']['path txt']
'output/CLC2018_corsica_FNF_rss.txt'

Connectivity Indices

RSS computes the following patch-based connectivity indices:

RSS connectivity indices.

Full Name	Code	Unit	Description
Critical New Object Area	CNOA	pixels	Minimum area of a new patch that would increase connectivity
Equivalent Connected Area	ECA	pixels	Area of a single patch providing the same connectivity as observed
Reference Area Coverage	RAC	%	Percentage of foreground relative to total foreground and background
Coherence	COH	%	Percentage of foreground pixels effectively connected
Restoration Potential	REST_POT	%	Percentage of foreground pixels that could improve connectivity (100 - COH)

In addition to these indices, RSS reports basic patch size statistics: total number of foreground patches, and the average, median and largest patch size (in pixels).