sim_patterns {apcf} R Documentation

## Simulated Patterns (sample data)

### Description

The simulated patterns were created for testing the Adapted Pair Correlation Function presented in Nuske et al. (2009).

### Usage

sim_area

sim_pat_clust

sim_pat_rand

sim_pat_reg


### Format

A set of WKBs of class wk_wkb containing the study area and three simulated patterns.

 Dataset name Description sim_area study area sim_pat_reg simulated regular pattern sim_pat_rand simulated random pattern sim_pat_clust simulated clustered pattern

The study area is a square of 100 m x 100 m. A set of n = 100 objects were created and latter placed according to the designated spatial distribution. The size distribution and shapes of the objects are inspired by measurements of canopy gaps. The areas of the objects range from 1.6 m2 to 57.7 m2 with an arithmetic mean of 9.7 m2 and a median of 5.5 m2. The total area of all objects is 969.7 m2, meaning 9.7% of the study area is covered by objects.

For the sim_pat_reg dataset, the objects were arranged in a strict regular manner. A centric systematic grid was constructed, and the objects of the set were then randomly rotated and randomly placed by locating the centroids of the objects exactly on the matching randomly numbered grid points, resulting in a regular arrangement of objects with a constant distance of the centroids of 10 m.

For the sim_pat_rand dataset with randomly distributed objects, we generated a realisation of the Binomial process with intensity 0.01 m^-2, meaning one point per 100 m2. The objects were again randomly rotated and numbered and objects put on matching points with their centroid as close to the point as possible without overlapping other objects.

The sim_pat_clust dataset represents a clustered configuration. Again, we first created a point pattern with 100 points and then put the randomly numbered objects on the points. The point pattern was a realisation of Matern’s cluster process with w = 0.0006 m^-2 or 6 cluster centres per ha, a dispersion radius of R = 10 m and on average y = 16.6 points per cluster.

We used the R-package spatstat (Baddeley et al. 2015) for simulating the Binomial process and Matern’s cluster process.

### Source

Nuske et al. 2009

### References

Baddeley A., Rubak E. and Turner, R. (2015): Spatial Point Patterns: Methodology and Applications with R. Chapman and Hall/CRC, London. https://doi.org/10.1201/b19708

Nuske, R.S., Sprauer, S. and Saborowski, J. (2009): Adapting the pair-correlation function for analysing the spatial distribution of canopy gaps. Forest Ecology and Management, 259(1): 107–116. https://doi.org/10.1016/j.foreco.2009.09.050

### Examples

ds <- pat2dists(area=sim_area, pattern=sim_pat_reg, max_dist=25, n_sim=3)



[Package apcf version 0.3.1 Index]