Recent applications of point process methods in forestry statistics

By Dietrich Stoyan, Antti Penttinen. 2000

515 citations recorded by the source corpus.

Subfields: Applied Mathematics, Environmental Engineering, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/7e9e38560ba4c63adb442d412901a0cfbf3e14bc

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In Applied Mathematics

In Environmental Engineering

In Nature and Landscape Conservation

Citations in the corpus

Ecological information from spatial patterns of plants: insights from point process theory (2009, background): “The potential of these correlation functions based on marks has yet to be taken up in ecology; the only case we are aware of is an example of the mark correlation function in forest ecology (Stoyan & Penttinen 2000).”
A comparison of methods for the statistical analysis of spatial point patterns in plant ecology (2006, background): “Point processes While it is not the purpose of this review to provide technical definitions (for these see Cressie 1993; Stoyan et al. 1995; Diggle 2003), it is important to define the terms of relevance.”
Heterogeneity influences spatial patterns and demographics in forest stands (2008, background): “Although homogeneity and CSR are different concepts, significant deviation of a pattern from a homogeneous Poisson process (CSR) at scales r > 10 m beyond direct tree–tree interaction (Stoyan & Penttinen 2000) is usually interpreted as environmental heterogeneity.”
Understanding the dynamics of an undisturbed tropical rain forest from the spatial pattern of trees (2009, methodology): “The idea then is to produce realistic virtual forests for simulation-based studies (Stoyan & Penttinen 2000; Goreaud et al .”
Ripley's K Function (2006, background): “Applications include spatial patterns of trees [29, 20, 10], herbaceous plants [28], bird nests [11], and disease cases [7].”
Evaluating structural indices by reversing forest structural analysis (2006, methodology): “pair-, mark correlation functions and mark connection functions (Stoyan and Penttinen, 2000; Pommerening, 2002).”
Comparison of point pattern analysis methods for classifying the spatial distributions of spruce-fir stands in the north-east USA (2007, background): “The corresponding second function naturally similar to a density function is called the pair correlation function ( Stoyan and Penttinen, 2000 ).”
Tree spatial patterns and stand attributes in temperate forests: The importance of plot size, sampling design, and null model (2018, methodology): “In the natural environment, trees are not uniformly distributed, but form a complex mosaic with patches of different age, size, species, which reflect past endogenous and exogenous processes, and influence future ones (Watt, 1947; Dale, 1999; Stoyan and Penttinen, 2000).”
Spatial distributions of tree species in a subtropical forest of China (2009, methodology): “These include using Ripley’s K function (Ripley 1977) and the pair correlation g function (Stoyan and Stoyan 1994, Stoyan and Penttinen 2000).”
Funnel libraries for real-time robust feedback motion planning (2016, unknown): “For instance, it is known that the locations of trees in a forest are modeled well by spatial Poisson processes (Stoyan and Penttinen, 2000).”
Logistic regression for spatial Gibbs point processes (2014, background): “Spatial Gibbs and Markov point processes are important classes of models for spatial depen- 25 dence in point patterns (van Lieshout, 2000) with a broad range of applications (e.g. Harkness & Isham, 1983; Stoyan & Penttinen, 2000; Mattfeldt et al., 2007; Funwi-Gabga & Mateu, 2012).”
Land use impact on Vitellaria paradoxa C.F. Gaerten. stand structure and distribution patterns: a comparison of Biosphere Reserve of Pendjari in Atacora district in Benin (2008, background): “Additionally it is more intuitive than an accumulative measure (Stoyan and Penttinen 2000) because it has a direct interpretation as normalized neighborhood density function.”
Scale-dependent competition at the stand level assessed from crown areas (2008, background): “In northern forests, such interaction patterns of trees are usually correlated up to a maximal radius of 10 m (Stoyan and Penttinen, 2000) and 6– 7 m have been observed as finite range of competitive tree interaction in middle European forests (Parrott and Lange, 2004; Schlather et al., 2004).”
Rings, circles, and null-models for point pattern analysis in ecology (2004, background): “…pair correlation function g(r), which arises if the circles of Ripley’s K-function are replaced by rings (Ripley 1981, Stoyan and Stoyan 1994, Stoyan and Penttinen 2000, Dale et al. 2002), gives the expected number of points at distance r from an arbitrary point, divided by the intensity l…”