Analysing Pine Disease Spread Using Random Point Process by Remote Sensing of a Forest Stand

Autor: Rostyslav Kosarevych, Izabela Jonek-Kowalska, Bohdan Rusyn, Anatoliy Sachenko, Oleksiy Lutsyk
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: Remote Sensing, Vol 15, Iss 16, p 3941 (2023)
Druh dokumentu: article
ISSN: 2072-4292
DOI: 10.3390/rs15163941
Popis: The application of a process model to investigate pine tree infestation caused by bark beetles is discussed. The analysis of this disease was carried out using spatial and spatio−temporal models of random point patterns. Spatial point patterns were constructed for remote sensing images of pine trees damaged by the apical bark beetle. The method of random point processes was used for their analysis. A number of known models of point pattern processes with pairwise interaction were fitted to actual data. The best model to describe the real data was chosen using the Akaike information index. The residual K−function was used to check the fit of the model to the real data. According to values of the Akaike information criterion and the residual K−function, two models were found to correspond best to the investigated data. These are the generalized Geyer model of the point process of saturation and the pair interaction process with the piecewise constant potential of a pair of points. For the first time, a spatio−temporal model of the contagious process was used for analysis of tree damage.
Databáze: Directory of Open Access Journals
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