An overview of land system modelling

Duration: 31 mins 24 secs

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Description:	Rounsevell, M Wednesday 9th September 2020 - 09:30 to 10:00


Created:	2020-09-10 13:59
Collection:	Mathematical and statistical challenges in landscape decision making
Publisher:	Isaac Newton Institute
Copyright:	Rounsevell, M
Language:	eng (English)


Abstract:	Land system modelling is primarily focused on the question: how do land managers make decisions about the use of land resources. There is a long history of land system modelling stretching back to classical economists in the early 19th Century. Early concepts focused strongly on economic (land rent) models to explain land use distributions, but these began to also include the notion of relative location (e.g. distance to markets) in determining land use patterns. Much of the initial thinking from this time is still relevant today and shapes, to some extent, current thinking about how to model the decision-making processes of land users. However, as land use models evolved through time, non-economic aspects began to take on increasing importance. Processes such as access to information and the spatial diffusion of knowledge through space and time were shown to be critical in understanding landscape decisions. This has led to an evolution in land system modelling towards a focus on agency and social interaction in addition to economic aspects. Methods such as Agent-Based Modelling (ABM) are now able to accommodate a range of human behaviours that underpin decision making and the social interaction processes that foster knowledge exchange through cooperation or competition. In this talk I provide an overview of the evolution of land system modelling exploring the advantages and disadvantages of the many extant approaches. I also explore the considerable progress that is still needed to develop land system models further, e.g. better representing human decision-making processes, better testing against data, coupling land system models with other components of the broader environment, and endogenizing the policy making process within models.

Abstract:

Land system modelling is primarily focused on the question: how do land managers make decisions about the use of land resources. There is a long history of land system modelling stretching back to classical economists in the early 19th Century. Early concepts focused strongly on economic (land rent) models to explain land use distributions, but these began to also include the notion of relative location (e.g. distance to markets) in determining land use patterns. Much of the initial thinking from this time is still relevant today and shapes, to some extent, current thinking about how to model the decision-making processes of land users. However, as land use models evolved through time, non-economic aspects began to take on increasing importance. Processes such as access to information and the spatial diffusion of knowledge through space and time were shown to be critical in understanding landscape decisions. This has led to an evolution in land system modelling towards a focus on agency and social interaction in addition to economic aspects. Methods such as Agent-Based Modelling (ABM) are now able to accommodate a range of human behaviours that underpin decision making and the social interaction processes that foster knowledge exchange through cooperation or competition. In this talk I provide an overview of the evolution of land system modelling exploring the advantages and disadvantages of the many extant approaches. I also explore the considerable progress that is still needed to develop land system models further, e.g. better representing human decision-making processes, better testing against data, coupling land system models with other components of the broader environment, and endogenizing the policy making process within models.

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