Tools for Landscape Science: Theory, Models and Data
We review the different roles of theory, models and data in landscape science. The need for science at the landscape scale is argued. Landscape theory is considered as a repository of probabilistic patterns rather than as a collection of laws of nature. We present a typology of such patterns for five distinct landscape features: land cover, land use, patch properties, patch interactions and exogenous influences. We show how theory for these features can support landscape modelling, and we provide a checklist of questions for model developers. The limited availability of data on landscapes is discussed, and how that leads to uncertainties in theoretical patterns as well as models. We analyse how probability theory can be used to account for these uncertainties, strengthening the links between theory, models and data, and facilitating decision support.
KeywordsAgricultural landscapes Bayesian methods Data Ecosystem services Landscape theory Models Probability theory Uncertainties
I thank the organizers of the Landscape 2018 meeting in Berlin for their invitation to participate, and for the stimulating discussions about the future of landscape science.
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