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Increasing territorial planning activities through viewshed analysis / Gheorghe-Gavrilă Hognogi in Geocarto international, vol 37 n° 2 ([06/01/2022])  

Public [article]  inGeocarto international > vol 37 n° 2 [06/01/2022] . - pp 627 - 637 Titre : Increasing territorial planning activities through viewshed analysis Type de document : Article/Communication Auteurs : Gheorghe-Gavrilă Hognogi, Auteur ; Ana-Maria Pop, Auteur ; Simona Mălăescu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 627 - 637 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] aménagement du territoire [Termes IGN] analyse géovisuelle [Termes IGN] Carpates [Termes IGN] carte topographique [Termes IGN] logique floue [Termes IGN] point de visibilité [Termes IGN] Roumanie [Termes IGN] vision [Vedettes matières IGN] Géovisualisation Résumé : (auteur) Visibility analyses are employed in various fields, from landscape to archeology or territorial planning. Two case studies, of different elevation, from Romania were selected to be considered for setting up some observation points as lookout points. Fuzzy viewshed analysis was performed to evaluate the degree of visibility of certain landscape components and was also used as a tool for territorial planning. The main results of the research were some particular viewshed analysis area according to the dominant visibility directions. This methodology may be useful to local authorities, which are the only responsible bodies for authorizing, creating and setting up lookout points in a given space or for organizing certain planning activities. Numéro de notice : A2022-051 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2020.1730450 Date de publication en ligne : 27/02/2020 En ligne : https://doi.org/10.1080/10106049.2020.1730450 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99444 [article]

Un désordre complexe à modéliser / Laurent Polidori in Géomètre, n° 2197 (décembre 2021)

Public [article]  inGéomètre > n° 2197 (décembre 2021) . - pp 30 - 37 Titre : Un désordre complexe à modéliser Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2021 Article en page(s) : pp 30 - 37 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Mathématique [Termes IGN] approximation [Termes IGN] corrélation [Termes IGN] données topographiques [Termes IGN] estimation de position [Termes IGN] géométrie fractale [Termes IGN] géostatistique [Termes IGN] logique floue [Termes IGN] milieu naturel [Termes IGN] modélisation environnementale [Termes IGN] qualité du modèle Résumé : (Auteur) L’histoire est riche sur le rôle de la mesure dans la compréhension des phénomènes naturels, comme pour le cas des objets ou phénomènes rebelles à la modélisation. Mais comment mesurer des structures géologiques irrégulières, des arbres, des espèces, des épidémies, etc.? Pour diverses raisons, il est difficile de mesurer les objets naturels en termes de grandeurs géométriques, de la longueur d’un fleuve au volume d’un arbre et de son feuillage. Ces difficultés conduisent parfois à des simplifications dans l’acquisition et l’exploitation de la donnée, la précision recherchée n’étant généralement pas importante. D’où parfois un recours aux relations allométriques lorsque l’objet n’est pas directement mesurable voire inaccessible (biomasse d’un arbre à partir de son diamètre, poids d’un fœtus en cours de grossesse à partir d’une dimension sur l’échographie...). En outre, avec les débuts de l’informatique dans les années 1970, est apparu un outillage mathématique adapté à la complexité du monde réel (géostatistique, géométrie fractale, logique floue...). L’important étant de toujours avoir conscience des limites de la mesure sur les éléments naturels. Numéro de notice : A2021-892 Affiliation des auteurs : non IGN Thématique : IMAGERIE/MATHEMATIQUE/POSITIONNEMENT Nature : Article nature-HAL : ArtSansCL DOI : sans Date de publication en ligne : 01/12/2021 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99249 [article]

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Incorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment / Ali Azareh in Geocarto international, vol 36 n° 20 ([10/11/2021])  

Public [article]  inGeocarto international > vol 36 n° 20 [10/11/2021] . - pp 2345 - 2365 Titre : Incorporating multi-criteria decision-making and fuzzy-value functions for flood susceptibility assessment Type de document : Article/Communication Auteurs : Ali Azareh, Auteur ; Elham Rafiei Sardooi, Auteur ; Bahram Choubin, Auteur ; Saeed Barkhori, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2345 - 2365 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse des risques [Termes IGN] analyse multicritère [Termes IGN] bassin hydrographique [Termes IGN] cartographie des risques [Termes IGN] classification floue [Termes IGN] crue [Termes IGN] gestion des risques [Termes IGN] inondation [Termes IGN] Iran [Termes IGN] logique floue [Termes IGN] risque naturel [Termes IGN] zone à risque Résumé : (auteur) Floods are among the most frequently occurring natural disasters and the costliest in terms of human life and ecosystem disturbance. Identifying areas susceptible to flooding is important for developing appropriate watershed management policies. As such, the goal of the present study was to develop an integrated framework for flood susceptibility assessment in data-scarce regions, using data from the Haraz watershed in Iran. Flood-influencing indices best suited to the identification of areas particularly prone to flooding were selected. The decision-making trial and evaluation laboratory (DEMATEL) approach was used to investigate the interdependence among criteria and to develop a network structure representative of the problem. The relative importance of different flood-influencing factors was determined using the analytical network process (ANP). A flood susceptibility map was produced using weights obtained through the ANP and fuzzy-value function (FVF) and validated using 72 available flood locations where flooding occurred between 2006 and 2018. After validating the results, fuzzy theory served to better delineate the flood susceptibility scores among the region’s sub-watersheds. Incorporating the DEMATEL-ANP approach with FVF yielded an accuracy of 89.1%, as was assessed through the area under the curve (AUC) of a receiver operating characteristics (ROC) curve. The results indicated that the strongest flood-influencing (occurrence/nonoccurrence) factors were elevation, land use, soil texture, and frequency of heavy rainstorms. The fuzzy theory showed sub-watershed C1 to be highly susceptible to flooding, and thus, most in need of flood management. Numéro de notice : A2021-833 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1695958 Date de publication en ligne : 28/11/2019 En ligne : https://doi.org/10.1080/10106049.2019.1695958 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99006 [article]

Exploring fuzzy local spatial information algorithms for remote sensing image classification / Anjali Madhu in Remote sensing, vol 13 n° 20 (October-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 20 (October-2 2021) . - n° 4163 Titre : Exploring fuzzy local spatial information algorithms for remote sensing image classification Type de document : Article/Communication Auteurs : Anjali Madhu, Auteur ; Anil Kumar, Auteur ; Peng Jia, Auteur Année de publication : 2021 Article en page(s) : n° 4163 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de groupement [Termes IGN] approche pixel [Termes IGN] classification dirigée [Termes IGN] classification floue [Termes IGN] distance euclidienne [Termes IGN] erreur moyenne quadratique [Termes IGN] Inde [Termes IGN] matrice d'erreur [Termes IGN] occupation du sol [Termes IGN] théorie des possibilités Résumé : (auteur) Fuzzy c-means (FCM) and possibilistic c-means (PCM) are two commonly used fuzzy clustering algorithms for extracting land use land cover (LULC) information from satellite images. However, these algorithms use only spectral or grey-level information of pixels for clustering and ignore their spatial correlation. Different variants of the FCM algorithm have emerged recently that utilize local spatial information in addition to spectral information for clustering. Such algorithms are seen to generate clustering outputs that are more enhanced than the classical spectral-based FCM algorithm. Nonetheless, the scope of integrating spatial contextual information with the conventional PCM algorithm, which has several advantages over the FCM algorithm for supervised classification, has not been explored much. This study proposed integrating local spatial information with the PCM algorithm using simpler but proven approaches from available FCM-based local spatial information algorithms. The three new PCM-based local spatial information algorithms: Possibilistic c-means with spatial constraints (PCM-S), possibilistic local information c-means (PLICM), and adaptive possibilistic local information c-means (ADPLICM) algorithms, were developed corresponding to the available fuzzy c-means with spatial constraints (FCM-S), fuzzy local information c-means (FLICM), and adaptive fuzzy local information c-means (ADFLICM) algorithms. Experiments were conducted to analyze and compare the FCM and PCM classifier variants for supervised LULC classifications in soft (fuzzy) mode. The quantitative assessment of the soft classification results from fuzzy error matrix (FERM) and root mean square error (RMSE) suggested that the new PCM-based local spatial information classifiers produced higher accuracies than the PCM, FCM, or its local spatial variants, in the presence of untrained classes and noise. The promising results from PCM-based local spatial information classifiers suggest that the PCM algorithm, which is known to be naturally robust to noise, when integrated with local spatial information, has the potential to result in more efficient classifiers capable of better handling ambiguities caused by spectral confusions in landscapes. Numéro de notice : A2021-806 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs13204163 Date de publication en ligne : 18/10/2021 En ligne : https://doi.org/10.3390/rs13204163 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98864 [article]

Extracting knowledge from legacy maps to delineate eco-geographical regions / Lin Yang in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 250 - 272 Titre : Extracting knowledge from legacy maps to delineate eco-geographical regions Type de document : Article/Communication Auteurs : Lin Yang, Auteur ; Xinming Li, Auteur ; Qinye Yang, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 250 - 272 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] carte ancienne [Termes IGN] carte climatique [Termes IGN] cartographie écologique [Termes IGN] Chine [Termes IGN] délimitation [Termes IGN] données cartographiques [Termes IGN] écorégion [Termes IGN] extraction de données [Termes IGN] logique floue [Termes IGN] sous ensemble flou [Termes IGN] zone tampon Résumé : (auteur) Legacy ecoregion maps contain knowledge on relationships between eco-region units and their environmental factors. This study proposes a method to extract knowledge from legacy area-class maps to formulate a set of fuzzy membership functions useful for regionalization. We develop a buffer zone approach to reduce the uncertainty of boundaries between eco-region units on area-class maps. We generate buffer zones with a Euclidean distance perpendicular to the boundaries, then the original eco-region units without buffer zones serve as the basic units to generate the probability density functions (PDF) of environmental variables. Then, we transform the PDFs to fuzzy membership functions for class-zones on the map. We demonstrate the proposed method with a climatic zone map of China. The results showed that the buffer zone approach effectively reduced the uncertainties of boundaries. A buffer distance of 10–15 km was recommended in this study. The climatic zone map generated based on the extracted fuzzy membership functions showed a higher spatial stratification heterogeneity (compared to the original map). Based on the fuzzy membership functions with climate data of 1961–2015, we also prepared an updated climatic zone map. This study demonstrates the prospects of using fuzzy membership functions to delineate area classes for regionalization purpose. Numéro de notice : A2021-025 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1806284 Date de publication en ligne : 17/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1806284 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96692 [article]

Intelligent sensors for positioning, tracking, monitoring, navigation and smart sensing in smart cities / Li Tiancheng (2021)  

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Mining the semantic Web for OWL axioms / Thu Huong Nguyen (2021)  

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Modélisation et raisonnement spatial flou pour l’aide à la localisation de victimes en montagne / Mattia Bunel (2021)  

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A LiDAR aiding ambiguity resolution method using fuzzy one-to-many feature matching / Chuang Qian in Journal of geodesy, vol 94 n° 10 (October 2020)  

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Prediction of traffic accidents hot spots using fuzzy logic and GIS / Aslam Al-Omari in Applied geomatics, vol 12 n° 2 (June 2020)  

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Estimation of metabolic flows of urban environment based on fuzzy expert knowledge / Igor Patrakeyev in Geodesy and cartography, vol 46 n° 1 (January 2020)  

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Fuzzy logic / Constantin Volosencu (2020)  

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Introduction to data science and machine learning / Keshav Sud (2020)  

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Recent trends in artificial neural networks / Ali Sadollah (2020)  

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Saliency-guided deep neural networks for SAR image change detection / Jie Geng in IEEE Transactions on geoscience and remote sensing, Vol 57 n° 10 (October 2019)  

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