publications 👨🏻‍🔬

2026

1. Com. orale

   

   De Marioupol à Gaza : Google Maps et la mémoire des lieux meurtris par la guerre

   Romain Mejean

   octobre 2026

   Communication orale aux journées d’étude « Géonumérisation du Monde : Infrastructures, pratiques et enjeux politiques », MSH Bordeaux, France, 6–8 octobre 2026.

   Abs

   À partir des cas de Marioupol et de Gaza, cette communication montrera comment Google Maps, principal dispositif géonumérique utilisé par le grand public, devient une archive involontaire des lieux détruits par la guerre. Les territoires en guerre connaissent en effet une rupture brutale de leur vie géonumérique : les pratiques ordinaires de contribution à la plateforme disparaissent en même temps que les infrastructures, les sociabilités, voire les populations elles-mêmes. Dès lors, les traces laissées avant les conflits — avis, photographies ou commentaires associés aux points d’intérêt géolocalisés — acquièrent une fonction mémorielle et politique. À Gaza, les contributions publiées avant octobre 2023 sur les commerces, cafés ou boulangeries témoignent aujourd’hui d’une identité culturelle et culinaire menacée d’effacement. À Marioupol, les dernières traces laissées avant l’occupation russe deviennent les fragments d’une « vie d’avant », où apparaissent encore des centaines d’enfants ukrainiens photographiés dans les lieux de loisirs ou les équipements sportifs, alors même qu’une partie d’entre eux a depuis été déplacée vers la Russie dans le cadre de politiques de russification. La mise au jour de cette mémoire géonumérique soulève plusieurs enjeux éthiques et démocratiques, dans la mesure où celle-ci demeure entièrement dépendante des infrastructures privées de Google, capables de supprimer, hiérarchiser ou invisibiliser ces données sans contrôle collectif. Il s’agira ainsi d’interroger les logiques capitalistes et hégémoniques de la géonumérisation contemporaine, mais également les possibilités de réappropriation des données géonumériques à travers des alternatives telles qu’OpenStreetMap, Panoramax ou la démarche des géocommuns portée par l’IGN. La maîtrise des données géonumériques constitue désormais un enjeu de souveraineté, mais aussi de mémoire et de pouvoir sur le récit du monde, particulièrement sensible dans les lieux détruits par la guerre.

2023

1. Thèse

   

   Modélisations rétrospectives des dynamiques de déforestation de l’Amazonie équatorienne : vers une hybridation des approches pattern et process

   Romain Mejean

   Université Toulouse 2 - Jean Jaurès , novembre 2023

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2021

1. Com. orale

   

   Landscape generation for a Land Use and Land Cover Change Agent-Based Model, with GAMA platform

   Romain Mejean, Kevin Chapuis, Mehdi Saqalli, 2 autres auteurs

   juin 2021

   Communication orale présentée aux 1st GAMA Days 2021, conférence en ligne organisée à Toulouse, France.

   Abs HTML PDF

   Land change models have emerged over the past few decades to explore the causes and consequences of land use and land cover changes (LUCC) and to better forecast them in order to guide public policies. Agent-based models of LUCC (LUCC-ABMs) allows formalizing the interactions between society and environment through the modelling of heterogeneous stakeholders involved in land change and their individual decision-making process regarding to the land use, which has an impact on regional land cover. We introduce a LUCC-ABM of deforestation dynamics in Northern Ecuadorian Amazon, built with GAMA platform. The purpose of the model is to reproduce LUCC patterns due to human activities over eight years as they appeared between two land cover maps. To this end, we have developed a workflow based on i) a strong input of both qualitative and quantitative data at initialization step by a landscape generator based on census and survey data ii) livelihood strategies to typologize land use behaviours. Our model workflow can be described as following: after the data processing, we generate a spatially and socially structured population with a synthetic population generation library (GENSTAR) on the basis of census, cadastral and land cover data. Then, we assign a livelihood strategy to each household through a multi-criteria evaluation according to qualitative and spatial criteria from field surveys. Next, once again with GENSTAR, we generate an agricultural landscape for the entire study area by specifying a patchwork of farming activities in each plot assigned to these agents according to their livelihood strategy, on the basis of field survey data in a sparse remote sensing data context. Lastly, we calibrate parameters related to agent decision-making processes in order to better reproduce environmental dynamics. In addition to a contribution on the integration of data in LUCC-ABMs, this work aims to investigate the connection between pattern-based and process-based modelling of LUCC.

2020

1. Publication

   

   Improving Business-as-Usual Scenarios in Land Change Modelling by Extending the Calibration Period and Integrating Demographic Data

   Romain Mejean, Martin Paegelow, Mehdi Saqalli, 1 autre auteur

   In Geospatial Technologies for Local and Regional Development , 2020

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   Land use and land cover change (LUCC) models are increasingly being used to anticipate the future of territories, particularly through the prospective scenario method. In the case of so-called trend or Business-as-Usual (BAU) scenarios, the aim is to observe the current dynamics and to extend them into the future. However , as they are implemented as baseline simulation in most current software packages , BAU scenarios are calibrated from a training period built from only two dates. We argue that this limits the quantitative estimation of future change intensity, and we illustrate it from a simple model of deforestation in Northern Ecuadorian Amazon using the Land Change Modeler (LCM) software package. This paper proposes a contribution to improve BAU scenarios calibration by mainly two enhancements: taking into account a longer calibration period for estimating change quantities and the integration of thematic data in change probabilities matrices. We thus demonstrate the need to exceed the linear construction of BAU scenarios as well as the need to integrate thematic and particularly socio-demographic data into the estimation of future quantities of change. The spatial aspects of our quantitative adjustments are discussed and tend to show that improvements in the quantitative aspects should not be dissociated from an improvement in the spatial allocation of changes, which may lead to a decrease in the predictive accuracy of the simulations.

2. Résumé publié

   

   Building an Agent-Based Model to simulate changes between two land cover maps: an init optimization?

   Romain Mejean, Kevin Chapuis, Doryan Kaced, 2 autres auteurs

   In International Environmental Modelling and Software Society (iEMSs) Conference 2020 , 2020

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   Spatial agent-based models (ABMs) are increasingly used to study land use and land cover changes (LUCC). This process-based approach allows formalizing the interactions between society and environment through the modelling of human decision-making processes regarding to the land use and its impact on regional land cover. Data-driven ABMs, which have emerged over the past decade, imply the integration of data for getting models more realistic, in a descriptive approach (KIDS). Most of the data are integrated at the initialization step, where agents of the simulation are created and their attributes values (including location) are initialized. We argue that this step is crucial, particularly because of the well-known phenomena of path dependence and dependence over initial conditions but also for getting a more comprehensive simulation model i.e. more realistic initial conditions of agents and landscape, a necessity for testing the model facing known empirical data using calibration. Thus, we introduce a LUCC-ABM of deforestation dynamics in Northern Ecuadorian Amazon for which initialization has been optimized. Our model workflow can be described as follow: first, we generate a spatially and socially structured population with a synthetic population generation library (GENSTAR) on the basis of census, cadastral and land cover data. Then, we generate an agricultural landscape by specifying a patchwork of farming activities in each cadastral parcel assigned to these agents according to their livelihood strategy, on the basis of field survey data in a sparse remote sensing data context. Lastly, we calibrate parameters related to agent decision-making processes in order to reproduce LUCC patterns due to human activities over eight years in Northern Ecuadorian Amazon as they appeared on land cover maps.

3. Com. orale

   

   Génération de population synthétique et land use modelling : questionnements et application en Amazonie équatorienne

   Romain Mejean, Kevin Chapuis, et Mehdi Saqalli

   février 2020

   Communication orale présentée aux Journées Génération de Population Synthétique, UMR IDEES, Rouen, France, février 2020.

2019

1. Publication

   

   PASHAMAMA: An Agricultural Process-Driven Agent-Based Model of the Ecuadorian Amazon

   Doryan Kaced, Romain Mejean, Aurélien Richa, 2 autres auteurs

   In Multi-Agent-Based Simulation XIX , 2019

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   This article presents the PASHAMAMA model that aims at studying the situation in the northern part of the Amazonian region of Ecuador in which the intensive oil extraction has induced a high rise of population, pollution, agricultural work and deforestation. It simulates these dynamics impacts on both environment and population by examining exposure and demography over time thanks to a retro-prospective and spatially explicit agent-based approach. Based on a previous work that has introduced roads, immigration and pollution (induced by the oil industry) dynamics, we focus here on the agricultural and the oil salaried work sides of the model. Unlike many models that are highly focused on the use of quantitative data, we choose a process-based approach and rest on qualitative data extracted from interviews with the local population: farmers are not represented by highly cognitive agents, but only attempt to fulfill their local objectives by fulfilling sequentially their constraints (e.g. eating before earning money). We also introduce a new evaluation method based on satellite pictures that compares simulated to “real” data on a thematic division of the environment.

2018

1. Com. orale

   Contaminations et conflits environnementaux contrastés en Amazonie équatorienne : une approche par la cartographie participative

   Romain Mejean, Clément De Meyer, Doryan Kaced, 1 autre auteur

   2018

   Communication orale présentée au colloque CESS 2018 : Contaminants, environnement, société et santé : de l’évaluation des risques à leur gestion, Toulouse, France.
2. Com. orale

   Algunos resultados de las cartografías con actores (CADA) realizadas en el territorio del Oriente

   Mehdi Saqalli, Romain Mejean, et Clément De Meyer

   avril 2018

   Communication orale présentée lors de la Restitución Programa MONOIL, Universidad Estatal Amazónica, Puyo, Équateur, 28 avril 2018.