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Uncertainty Modeling in Buffer Operations Applied to Connectivity Analysis
Author(s) -
De Genst William,
Canters Frank,
Gulinck Hubert
Publication year - 2001
Publication title -
transactions in gis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.721
H-Index - 63
eISSN - 1467-9671
pISSN - 1361-1682
DOI - 10.1111/1467-9671.00085
Subject(s) - biological dispersal , uncertainty analysis , propagation of uncertainty , monte carlo method , outcome (game theory) , sensitivity analysis , computer science , set (abstract data type) , multivariate statistics , econometrics , statistics , ecology , mathematics , simulation , algorithm , machine learning , biology , population , demography , mathematical economics , sociology , programming language
In this paper we will study the potential connectivity of red squirrels in a fragmented landscape, using a buffer operation that takes into account the difficulty of moving through the landscape. The outcome of such an analysis is greatly influenced by the various sources of uncertainty that are introduced in the model. Two main sources of uncertainty can be identified: source layer uncertainty and model uncertainty. In this paper the propagation of source layer uncertainty resulting from a multivariate statistical classification of remotely sensed data is studied using Monte Carlo simulation, taking the spatial structure of uncertainty into account. Model uncertainty results from the adoption of deterministic model parameters regarding the dispersal capacity and the landscape effect, and is examined using fuzzy set theory. Comparing the outcome of error sensitized models to the observed dispersal activity of squirrels, demonstrates how modeling of uncertainty can help to explain the dispersal activity of red squirrels.