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THEME 4 : Observation and modelling of change

Theme 4 – Observation and modelling of change

The theme Observation and modelling of change responds to a double objective: first of all, using Prodig’s areas of methodological expertise (GIS, remote sensing, cartography, modelling) to monitor technological developments and update methods for the collection, processing and representation of geographic data; secondly, creating synergies with the analyses of territorial shifts and evolutions to develop new observation and modelling methods, in order to analyse change according to varying (...)

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Theme 4.1 Observation

Before we collect data, in order to describe and qualify spatial configurations and their evolutions, we need to consider relevant variables and indicators, both quantitative and qualitative, as well as their selection, representativeness and sampling (Janelle, 2004 ). Data collection itself requires context-relevant protocols, either by using established ones or by developing new observation and measurement methods. Prodig will engage in methodological research (deployment, improvement and (...)

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Theme 4.2 Modelling

Modelling is a synthetic and simplified representation of a complex reality, aimed at describing and analysing a geographic object’s functioning and evolution (geographic objects are seen as socio-environmental systems). By describing the various types of evolutions and creating typologies through simulation, we can highlight the specificities of each object’s spatial, territorial, economic and social context. Modelling is applied to data, or to information that can be integrated into (...)

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Theme 4.3 Reflecting on our methodological practices

Theme 4 also includes a reflection on our research process and its associated methods and position. Prior to asking any questions on the research objects themselves, we should question the integration of geographic information systems, databases and other geographic representation models (theme-specific maps and atlases, geographic images, multi-agent models, etc.). What types of representation are the most appropriate? How can we organize the data and analyses we collect? What (...)

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