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Related Experiment Video

Updated: May 24, 2026

Use of Principal Components for Scaling Up Topographic Models to Map Soil Redistribution and Soil Organic Carbon

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Published on: October 16, 2018

A multi-scale modelling approach for analysing landscape service dynamics.

L Willemen¹, A Veldkamp, P H Verburg

¹Land Dynamics Group, Wageningen University, PO Box 47, 6700 AA Wageningen, The Netherlands. louise.willemen@jrc.ec.europa.eu

Journal of Environmental Management

|February 28, 2012

Summary

This summary is machine-generated.

This study models how changing societal needs and policies affect landscape services over time. It visualizes spatial and temporal dynamics, revealing trade-offs in landscape service supply for better environmental management.

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Area of Science:

Environmental Science
Spatial Planning
Ecosystem Services

Background:

Societal needs dynamically shape landscapes and the services they provide.
Understanding these shifts is crucial for effective environmental management and policy development.
Existing models often lack a comprehensive approach to spatial and temporal landscape service dynamics.

Purpose of the Study:

To develop and demonstrate a modelling approach for visualizing regional spatial and temporal dynamics of landscape service supply.
To integrate the multifunctional character of landscapes, multi-level interactions, and land management trade-offs into a unified framework.
To assess the impact of changing societal demand, driven by policy targets, on landscape service provision.

Main Methods:

Conceptualizing the system dynamics of landscape service supply, demand, and land management across different spatial levels.
Developing an operational model based on the conceptual framework.
Applying the model to simulate changes in landscape service supply in a rural Dutch region under regional policy scenarios.

Main Results:

The model successfully visualizes regional spatial and temporal dynamics in landscape service supply.
Demonstrated potential trade-offs in service supply emerging in a spatially explicit manner over time.
Highlighted the influence of regional policies on landscape service dynamics and their associated trade-offs.

Conclusions:

Modelling landscape service dynamics is relevant for environmental management and decision-making.
The developed approach effectively illustrates complex interactions between landscape change, societal demand, and policy.
Spatially explicit visualization of trade-offs aids in understanding and mitigating potential conflicts in land management.