Modelling environmental dynamics is critical to understanding and predicting the evolution of the environment in response to the large number of influences including urbanisation, climate change and deforestation. Simulation and modelling provide support for decision making in environmental management. This lesson introduces terminology and provides an overview of methodological modelling approaches which may be applied to environmental and complex dynamics.

In accordance with this, the guidebook illustrates various models applied to a large variety of themes: deforestation in tropical regions, fire risk, natural reforestation in European mountains, agriculture, biodiversity, urbanism, climate change and land management for decision support, etc. These case studies, provided by a large international spectrum of researchers and presented in a uniform structure, focus particularly on methods and model validation so that this guidebook is not only aimed at researchers and graduates but also at professionals.

As stated by the Merriam-Webster dictionary, a model is a system of postulates, data, and inferences presented as a mathematical description of an entity or state of affairs. Simply put, a model is a simplified representation of reality according to the specific vision of the modeller.

Spatially explicit models simulate an environmental system, reproducing the way its spatial patterns evolve, projecting the nature and likelihood of ecological and socioeconomic consequences from the system dynamics.

• A Discrete Map holds a finite array of integer values. Otherwise stated, a discrete map includes only those values that can only be counted in whole numbers or integers and are separate, which means the data cannot be broken down into a fraction or decimal representation.

• A Continuous Map is described as an unbroken set of observations that can be measured on a scale. It can take any numeric value, within a finite or infinite range of possible values. Statistically, range refers to the difference between the highest and lowest observations. The continuous data can be broken down into a fraction and decimal representation , i.e. it can be meaningfully subdivided into smaller parts according to the measurement precision.

Hence, discrete maps expect a certain number data of isolated values. On the other hand, continuous maps expect any value from a given range (without any breaks), and is related to a physical measurement.

• Vector Data is a representation of the world using points, lines, and polygons. These data are created by digitising the base data and they store information in X, Y coordinates. Vector models are useful for storing data that has discrete boundaries, such as country borders, land parcels, and streets.

• Raster Data stores information of features in cell-based manner. Satellite images, photogrammetry and scanned maps are all raster-based data. Raster models are used to store data, which varies continuously as in aerial photography, a satellite image or elevation values. A raster consists of a matrix of cells (or pixels) organised into rows and columns.

• Land Change Models provides scientific background for decision making
• Predict and project (What if we choose policy A or B?)
• Explain and learn (What are some potential unintended consequences of choosing policy A?)

A feedback loop in a dynamic system can be defined as a closed-loop or a circle of cause and effect in which “conditions” in one part of the system cause “results” elsewhere in the system, which in turn act on the original “conditions” to change them. There are two types of feedback loops that can occur. These are positive feedback loops (also called reinforcing feedback) and negative feedback loops (also called counteracting feedback).

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