Keywords
complexity, land cover change, land use change, land systems
Start Date
1-7-2012 12:00 AM
Abstract
Improved understanding of land-use/land-cover change will be essential to help identify and follow more sustainable development pathways in a resource constrained world. While land-use/land-cover change models have advanced to address different domains, questions, processes, themes, scales and levels of complexity, they continue to have several inherent limitations. The limitations stem mainly from conceptualisation of landscapes as “scanned paper maps” that represent land use/cover as simple, non-overlapping categorical objects and include: 1) confounding of cover and use, 2) inability to depict more than one cover/use, 3) simplification of highly complex systems, 4) one process for many different types of change, and 5) substantial data pre-processing that hampers model development. To help overcome those limitations, we present a conceptual modelling approach that characterises landscape as “land systems” consisting of interacting components. Each component is depicted and operates at its own appropriate scale, subject to considerations of interest, data availability, or usually both. An important aspect is the atomisation of data into fundamental components or “elements.” For example, an atomised land cover map results in a separate dataset for each land cover element. A common database stores all data atoms for possible re-use. Advantages include 1) scalability in space, time, and complexity, 2) extensibility such that data can be easily updated, replaced, added, or deleted, 3) depiction of multiple cover/uses/functions, and 4) fidelity between scale of process and scale of modelling. Disadvantages include 1) more substantial data requirements, 2) increased complexity of data storage and handling, and 3) lack of knowledge about many complex processes. We very briefly overview a conceptual framework of the land systems approach to the study of landscape change and its potential effects on ecosystem services.
Land Systems Modelling: An Atomistic Approach to Improve Handling of Complexity in Land-use and Land-cover Change Modelling
Improved understanding of land-use/land-cover change will be essential to help identify and follow more sustainable development pathways in a resource constrained world. While land-use/land-cover change models have advanced to address different domains, questions, processes, themes, scales and levels of complexity, they continue to have several inherent limitations. The limitations stem mainly from conceptualisation of landscapes as “scanned paper maps” that represent land use/cover as simple, non-overlapping categorical objects and include: 1) confounding of cover and use, 2) inability to depict more than one cover/use, 3) simplification of highly complex systems, 4) one process for many different types of change, and 5) substantial data pre-processing that hampers model development. To help overcome those limitations, we present a conceptual modelling approach that characterises landscape as “land systems” consisting of interacting components. Each component is depicted and operates at its own appropriate scale, subject to considerations of interest, data availability, or usually both. An important aspect is the atomisation of data into fundamental components or “elements.” For example, an atomised land cover map results in a separate dataset for each land cover element. A common database stores all data atoms for possible re-use. Advantages include 1) scalability in space, time, and complexity, 2) extensibility such that data can be easily updated, replaced, added, or deleted, 3) depiction of multiple cover/uses/functions, and 4) fidelity between scale of process and scale of modelling. Disadvantages include 1) more substantial data requirements, 2) increased complexity of data storage and handling, and 3) lack of knowledge about many complex processes. We very briefly overview a conceptual framework of the land systems approach to the study of landscape change and its potential effects on ecosystem services.
