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            "title": "Explorer les relations sensibles à la biodiversité : quelle est l’influence des chants d’oiseaux sur le rapport des citoyens à l’espace urbain ? Une étude des perceptions sonores des espaces végétalisés des habitats collectifs au sein de la métropole de Lyon",
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                    "firstName": "Olivier",
                    "lastName": "Maquaire"
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            "abstractNote": "Cette étude vise à cartographier la répartition mondiale des falaises et côtes rocheuses par détection semi-automatique basée sur des données satellitaires et un critère, la pente topographique. Les estimations de leur linéaire varient, oscillant entre 52 % (Young et Carilli, 2019), et 80 % (Emery et Kuhn, 1982). La méthodologie repose sur l’utilisation du MNT CoastalDEM et des données OpenStreetMap pour le trait de côte. Le seuil de pente de 10° est adopté pour identifier les falaises et les côtes rocheuses à des fins comparatives aux études internationales. La validation par photo-interprétation et la comparaison avec les bases de données EMODnet montrent une bonne précision de nos résultats (88 %) mais une sensibilité plus faible (50 %), indiquant que certaines côtes rocheuses de faible pente (fausse falaise et côte à dénudation, dont le façonnement est continental) ne sont pas toujours détectées. Les erreurs sont particulièrement marquées pour les roches cohérentes et les littoraux d’altitude inférieure à 10 m. Notre analyse révèle que les falaises et côtes rocheuses représenteraient 27 % du linéaire côtier mondial (31 % avec les côtes arctiques). Ce résultat brut est cohérent avec les travaux de Young et Carilli (2019) qui estime ce linéaire total entre 23 % (75 % de probabilité de confiance) et 52 % (50 % de probabilité de confiance) du linéaire côtier mondial. Cependant, en ajoutant les données chiffrées bibliographiques des côtes arctiques à notre estimation issue de CoastalDEM permettant une évaluation entre l’équateur et 60° de latitude nord et 56° sud, nos valeurs s’approchent de 31 %. De plus, si, comme nous le proposons, nous ajoutons les linéaires côtiers correspondant à des côtes rocheuses à faible pente mal déterminées par notre méthodologie (fausse falaise et côte à dénudation, dont le façonnement est continental), et pourtant considérées dans toutes les autres études, nous arriverions à un total de 53 %, soit très proche de la valeur proposée par Young et Carilli (2019), mais obtenue avec des données différentes.",
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            "title": "Enhancing Geotourism in Southeastern Morocco through Machine Learning-Based Geomorphosite Identification",
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            "abstractNote": "Mapping optimal areas for finding geomorphosites in large areas is a complex task influenced by various factors. To address this challenge, the present study assesses the effectiveness of three widely used machine learning classifiers in identifying and mapping potential areas for geomorphosite, a crucial factor for attracting and enhancing geotourism in Ziz, southeast Morocco. Initially, a comprehensive inventory of 120 geomorphosites was conducted in the study area. At each site, precise measurements of three topographical parameters were taken. Following this, three machine learning algorithms, namely Random Forest, Multi-Layer Perceptron, and M5 Prime, were utilized to create predictive models. Regarding the model performance, the Multi-Layer Perceptron model achieved the highest performance with an area under the curve of 0.91, followed by the M5 Prime model with 0.77. These models identified highly favorable areas, which accounted for approximately 60% and 42% of the study area according to Multi-Layer Perceptron and M5 Prime, respectively. These areas were predominantly located in the western region, characterized by mountainous terrain with relatively shorter slope lengths and altitudes ranging between 2500 m and 3500 m. This research serves as a valuable roadmap for decision-makers, offering guidance on how to improve the likelihood of discovering geomorphosites while minimizing costs and reducing the time required for exploration.",
            "publicationTitle": "Geoheritage",
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            "date": "2025-02-14",
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            "pages": "34",
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                    "tag": "Geodiversity",
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                {
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            "title": "Reflections on the Use of k-Nearest-Neighbours Bespoke Neighbourhoods in Urban Studies",
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                    "firstName": "Jan",
                    "lastName": "Amcoff"
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            "abstractNote": "During the first decades of the 21st century, bespoke neighbourhoods have often replaced predefined areas in urban studies. This development has been enabled by the improved availability of detailed data, as well as methodological innovations (e.g. the construction of bespoke neighbourhoods based on k-nearest neighbours, or knn). This paper argues that, while knn-based bespoke neighbourhoods facilitate more nuanced results in several respects, they do not provide all the advantages claimed by their advocates; as have been pointed out, they also present new problems. A literature review of the arguments for knn, illustrated by concrete examples of how k = 400 neighbourhoods fit the varying physical urban environments, leads to the conclusion that, despite explicit claims to the contrary, the modifiable areal unit problem (MAUP) still remains, and certainly various physical aspects of urban space, are largely ignored. Finally, this article discusses various possible ways to include aspects currently missing.",
            "publicationTitle": "Tijdschrift voor Economische en Sociale Geografie",
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            "date": "2025",
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            "DOI": "10.1111/tesg.70001",
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                {
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            "creatorSummary": "Agyemang and Sahana",
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            "title": "Modelling Urbanisation in Cities in the Global South: A Review of Progress and Framework for the Future",
            "creators": [
                {
                    "creatorType": "author",
                    "firstName": "Felix S. K.",
                    "lastName": "Agyemang"
                },
                {
                    "creatorType": "author",
                    "firstName": "Mehebub",
                    "lastName": "Sahana"
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            ],
            "abstractNote": "Over the past several decades, urbanisation has been a key feature of cities in the Global South, and many scholars have used urban expansion models as tools to not only study this phenomenon, but to also predict likely evolution of cities in the region. Yet, there is limited knowledge of how urbanisation in the Global South has been modelled. In this study, we examine how urbanisation has been modelled in cities in the Global South, highlighting progress made and identifying key emerging issues for future research. Based on a review of 149 articles, we find an increasing preference for hybrid models that combine simple modelling approaches with more complex deep learning approaches. However, the advantages of hybrid approaches over stand-alone models in terms of prediction power has not been strongly established in the literature. We also find that most of the applications do not directly account for the social processes that generate the urban expansion patterns we observe in the region. As a result, the validation of most models has been limited to the ‘where’ (locations) and ‘when’ (time) and not the ‘who’ (socio-economic characteristics of occupants of location at a given point in time). The application of the models is highly localised as most studies do not model more than one city. This review could serve as a foundation for improving how urbanisation is modelled in the Global South.",
            "publicationTitle": "Geography Compass",
            "publisher": "",
            "place": "",
            "date": "2025",
            "volume": "19",
            "issue": "2",
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            "pages": "e70019",
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            "DOI": "10.1111/gec3.70019",
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            "ISSN": "1749-8198",
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            "shortTitle": "Modelling Urbanisation in Cities in the Global South",
            "language": "en",
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            "rights": "© 2025 The Author(s). Geography Compass published by John Wiley & Sons Ltd.",
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