0000000000017535
AUTHOR
Aila Särkkä
showing 3 related works from this author
Plant colonization of a bare peat surface: population changes and spatial patterns
1992
. Changes in size and spatial arrangement of plant populations established on an initially bare peat surface were described over a period of 5 yr by following plant individuals on a 1-cm grid in an area of 10 m x 25 m. The spatial pattern of populations and association between species was analyzed statistically. The study site was very slowly colonized by 14 perennial plant species. The early successional stage was dominated by Carex rostrata, with a clumped spatial distribution, and the homogeneously distributed Eriophorum vaginatum and Pinus sylvestris. Both the growth in size of populations and changes in their spatial distribution were interpreted as a result of species dispersal abilit…
What we look at in paintings: A comparison between experienced and inexperienced art viewers
2016
How do people look at art? Are there any differences between how experienced and inexperienced art viewers look at a painting? We approach these questions by analyzing and modeling eye movement data from a cognitive art research experiment, where the eye movements of twenty test subjects, ten experienced and ten inexperienced art viewers, were recorded while they were looking at paintings. Eye movements consist of stops of the gaze as well as jumps between the stops. Hence, the observed gaze stop locations can be thought as a spatial point pattern, which can be modeled by a spatio-temporal point process. We introduce some statistical tools to analyze the spatio-temporal eye movement data, a…
Hierarchical log Gaussian Cox process for regeneration in uneven-aged forests
2021
We propose a hierarchical log Gaussian Cox process (LGCP) for point patterns, where a set of points x affects another set of points y but not vice versa. We use the model to investigate the effect of large trees to the locations of seedlings. In the model, every point in x has a parametric influence kernel or signal, which together form an influence field. Conditionally on the parameters, the influence field acts as a spatial covariate in the intensity of the model, and the intensity itself is a non-linear function of the parameters. Points outside the observation window may affect the influence field inside the window. We propose an edge correction to account for this missing data. The par…