Characterising forest spatial structure through inhomogeneous second order characteristics

DOI10.1007/s00477-008-0224-8zbMath1411.62335OpenAlexW2058245445MaRDI QIDQ1741086

Xianqiang Yang

Publication date: 3 May 2019

Published in: Stochastic Environmental Research and Risk Assessment (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00477-008-0224-8

zbMATH Keywords

Ripley's \(K\) functionforest structurenon-stationary point processesinhomogeneous pair correlation functionreplicated forest data

Mathematics Subject Classification ID

Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Point processes (e.g., Poisson, Cox, Hawkes processes) (60G55)

Uses Software

• bootstrap

Cites Work

• An information-fusion method to identify pattern of spatial heterogeneity for improving the accuracy of estimation
• Analysis of forest thinning strategies through the development of space-time growth-interaction simulation models
• The second-order analysis of stationary point processes
• Log Gaussian Cox Processes
• Non‐ and semi‐parametric estimation of interaction in inhomogeneous point patterns
• Rainfall modelling using Poisson-cluster processes: a review of developments
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