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Decision fusion of deep learning and shallow learning for marine oil spill detection / Junfang Yang in Remote sensing, vol 14 n° 3 (February-1 2022)  

Public [article]  inRemote sensing > vol 14 n° 3 (February-1 2022) . - n° 666 Titre : Decision fusion of deep learning and shallow learning for marine oil spill detection Type de document : Article/Communication Auteurs : Junfang Yang, Auteur ; Yi Ma, Auteur ; Yabin Hu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 666 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] algorithme de fusion [Termes IGN] analyse multiéchelle [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] hydrocarbure [Termes IGN] image hyperspectrale [Termes IGN] marée noire [Termes IGN] milieu marin [Termes IGN] pollution des mers [Termes IGN] précision de la classification [Termes IGN] sous ensemble flou [Termes IGN] surveillance écologique [Termes IGN] transformation en ondelettes Résumé : (auteur) Marine oil spills are an emergency of great harm and have become a hot topic in marine environmental monitoring research. Optical remote sensing is an important means to monitor marine oil spills. Clouds, weather, and light control the amount of available data, which often limit feature characterization using a single classifier and therefore difficult to accurate monitoring of marine oil spills. In this paper, we develop a decision fusion algorithm to integrate deep learning methods and shallow learning methods based on multi-scale features for improving oil spill detection accuracy in the case of limited samples. Based on the multi-scale features after wavelet transform, two deep learning methods and two classical shallow learning algorithms are used to extract oil slick information from hyperspectral oil spill images. The decision fusion algorithm based on fuzzy membership degree is introduced to fuse multi-source oil spill information. The research shows that oil spill detection accuracy using the decision fusion algorithm is higher than that of the single detection algorithms. It is worth noting that oil spill detection accuracy is affected by different scale features. The decision fusion algorithm under the first-level scale features can further improve the accuracy of oil spill detection. The overall classification accuracy of the proposed method is 91.93%, which is 2.03%, 2.15%, 1.32%, and 0.43% higher than that of SVM, DBN, 1D-CNN, and MRF-CNN algorithms, respectively. Numéro de notice : A2022-125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14030666 Date de publication en ligne : 30/01/2022 En ligne : https://doi.org/10.3390/rs14030666 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99688 [article]

Un état de l’art sur l’imprécision spatiale et sa modélisation / Mattia Bunel in Cybergeo, European journal of geography, n° 2021 ([01/02/2021])  

Public [article]  inCybergeo, European journal of geography > n° 2021 [01/02/2021] . - n° 966 Titre : Un état de l’art sur l’imprécision spatiale et sa modélisation Titre original : A Review of Spatial Imprecision Modelisation Methods Type de document : Article/Communication Auteurs : Mattia Bunel , Auteur Année de publication : 2021 Projets : 1-Pas de projet / Article en page(s) : n° 966 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] données localisées [Termes IGN] imprécision géométrique [Termes IGN] incertitude géométrique [Termes IGN] modèle conceptuel de données localisées [Termes IGN] modèle d'incertitude [Termes IGN] sous ensemble flou Résumé : (auteur) L’objectif de cet article est de présenter et définir la notion d’imprécision spatiale, terme qualifiant toutes les situations où un objet spatial, quelle que soit sa nature, voit ses limites difficilement identifiables. Nous présentons cette notion ainsi que les concepts qui y sont apparentés, en prenant soin de clarifier un vocabulaire confus et des définitions contradictoires. Cet article recense également les différentes théories et leurs implémentations, permettant de modéliser l’imprécision spatiale. L’ensemble de ce programme s’appuiera sur un exemple filé, permettant d’expliciter concepts et modélisations. Numéro de notice : A2021-175 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.4000/cybergeo.36126 Date de publication en ligne : 11/02/2021 En ligne : https://doi.org/10.4000/cybergeo.36126 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97225 [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]

Acquisition of weak GPS signals using wavelet-based de-noising methods / Mohaddeseh Sharie in Survey review, vol 52 n° 375 (November 2020)  

Public [article]  inSurvey review > vol 52 n° 375 (November 2020) . - pp 497 - 513 Titre : Acquisition of weak GPS signals using wavelet-based de-noising methods Type de document : Article/Communication Auteurs : Mohaddeseh Sharie, Auteur ; Mohammad-Reza Mosavi, Auteur ; Narjes Rahemi, Auteur Année de publication : 2020 Article en page(s) : pp 497 - 513 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] atténuation du signal [Termes IGN] filtrage du bruit [Termes IGN] rapport signal sur bruit [Termes IGN] récepteur GPS [Termes IGN] seuillage [Termes IGN] signal GPS [Termes IGN] sous ensemble flou [Termes IGN] transformation en ondelettes Résumé : (auteur) Various factors cause GPS signals to be weakened in their path from satellites to receiver. This phenomenon leads to some problems in the normal stages of the positioning process, including acquisition stage. The wavelet transform is one of the tools that have been employed in several methods to improve receiver’s sensitivity in confronting weak GPS signals. Choosing an appropriate threshold plays a key role in the performance of this de-noising method. This study presents two methods for selecting an appropriate threshold. In the first method, the threshold is determined based on the statistical information extracted from the signal. On the other hand, the threshold in the second method is determined by type II fuzzy sets. The results show that employment of these two methods increases SNR gain as well as the range of acquirable SNR which makes signals acquisition with minimum post-correlation SNR of −6.5dB in a GPS receiver possible. Numéro de notice : A2020-687 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2019.1648718 Date de publication en ligne : 01/08/2020 En ligne : https://doi.org/10.1080/00396265.2019.1648718 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96220 [article]

Fuzzy modelling of growth potential in forest development simulation / Damjan Strnad in Ecological Informatics, vol 48 (November 2018)  

Public [article]  inEcological Informatics > vol 48 (November 2018) . - pp 80 - 88 Titre : Fuzzy modelling of growth potential in forest development simulation Type de document : Article/Communication Auteurs : Damjan Strnad, Auteur ; Štefan Kohek, Auteur ; Simon Kolmanič, Auteur Année de publication : 2018 Article en page(s) : pp 80 - 88 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation [Termes IGN] analyse de sensibilité [Termes IGN] biodiversité [Termes IGN] composition floristique [Termes IGN] croissance des arbres [Termes IGN] écosystème forestier [Termes IGN] modèle de croissance végétale [Termes IGN] modèle de simulation [Termes IGN] Slovénie [Termes IGN] sous ensemble flou [Termes IGN] surveillance écologique Résumé : (Auteur) In the paper, we introduce a new fuzzy-based model for calculation of plant growth potential in the context of forest development simulation, which is an important tool for prediction and monitoring of forest biodiversity. When modelling a forest ecosystem, one needs to account for a significant amount of ambiguity in the specification of plant requirements and environmental conditions, whose overlap determines the competitive potential of co-occurring species. The proposed fuzzy model addresses the imprecision and uncertainty about proper interpretation of numerically estimated growth conditions with respect to linguistically specified plant requirements. Individual requirement levels are represented as fuzzy sets to which estimated growth conditions are mapped, while plant needs are modelled as fuzzy numbers with adjustable tolerance radii. The growth potential with respect to a particular resource is then calculated as a membership of condition mean in a fuzzy set of plant demand. We validate the model operation within the ForestMAS simulator on real data obtained from six decades of observations registered at a forest fire recovery site in northern Slovenia. We show that the enhanced expressiveness about the tolerance of tree species to deviations of growth conditions allows the fuzzy model to improve the accuracy of forest composition prediction with respect to the crisp model. Sensitivity analysis also shows that, in many cases, the fuzzy model increases simulation robustness with respect to vaguely defined plant needs and estimated site conditions. Numéro de notice : A2019-229 Affiliation des auteurs : non IGN Thématique : FORET/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.ecoinf.2018.08.002 Date de publication en ligne : 11/08/2018 En ligne : https://doi.org/10.1016/j.ecoinf.2018.08.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92744 [article]

µ-shapes: Delineating urban neighborhoods using volunteered geographic information / Matt Aadland in Journal of Spatial Information Science (JoSIS), n° 12 (March 2016)  

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Reconstruct street network from imprecise excavation data using fuzzy Hough transforms / Cyril de Runz in Geoinformatica, vol 18 n° 2 (April 2014)  

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A method for extracting burned areas from Landsat TM/ETM+ images by soft aggregation of multiple Spectral Indices and a region growing algorithm / D. Stroppiana in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)  

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Accuracy 2010 : Proceedings of the Ninth international symposium on spatial accuracy assessment in natural resources and environmental sciences, Leicester, UK, 20 - 23 juillet 2010 / Nicholas J. Tate (2010)  

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Relative positions in words: a system that builds descriptions around Allen relations / P. Matsakis in International journal of geographical information science IJGIS, vol 24 n°1-2 (january 2010)  

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Representing geographical objects with scale-induced indeterminate boundaries: a neural network-based data model / José L. Silvan-Cardenas in International journal of geographical information science IJGIS, vol 23 n°3-4 (march - april 2009)  

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Location approximation for local search services using natural language hints / S. Schockaert in International journal of geographical information science IJGIS, vol 22 n° 3 (march 2008)  

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Multispectral image classification: a supervised neural computation approach based on rough-fuzzy membership function and weak fuzzy similarity relation / A. Agrawal in International Journal of Remote Sensing IJRS, vol 28 n°19-20 (October 2007)  

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Higher order vagueness in geographical information: empirical geographical population of type N fuzzy sets / P. Fischer in Geoinformatica, vol 11 n° 3 (September - November 2007)  

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A system of types and operators for handling vague spatial objects / A. Dilo in International journal of geographical information science IJGIS, vol 21 n° 3-4 (march - april 2007)  

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