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Validation of Island 3D-mapping based on UAV spatial point cloud optimization: a case study in Dongluo Island of China / Jian Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 3 (March 2023)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 3 (March 2023) . - pp 173 - 182 Titre : Validation of Island 3D-mapping based on UAV spatial point cloud optimization: a case study in Dongluo Island of China Type de document : Article/Communication Auteurs : Jian Wu, Auteur ; Shifeng Fu, Auteur ; Peng Chen, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 173 - 182 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] cartographie 3D [Termes IGN] Chine [Termes IGN] île [Termes IGN] image captée par drone [Termes IGN] modélisation 3D [Termes IGN] semis de points [Termes IGN] télédétection aérienne Résumé : (Auteur) The unmanned aerial vehicle (UAV) remote sensing is of small volume, low cost, fine timeliness, and high spatial resolution, and has the special advantage on island surveying. Focus on the inaccurate elevation of non-ground point cloud without lidar device, this study explored a methodology for island three-dimensional (3D) mapping and modelling based on spatial point clouds optimization with a K-Nearest Neighbors Adaptive Inverse Distance Weighted (K-AIDW) interpolation algorithm. By classifying the UAV point clouds into ground, vegatetation, and structure, the K-AIDW algorithm was applied to optimize the elevations of non-ground point clouds (vegetation and structure) to recalculate Z values. The aerophotogrammetry result was generated based on the optimized spatial point clouds. Finally, the 3D model of Dongluo Island was reconstructed and rendered in Metashape. The accuracy evaluation result shows that the max-errors of ground control points (–0.0154 in X, 0.0305 in Y, and 0.0133 in Z) and the checkpoints (–0.091 in X, –0.176 in Y, and 0.338 in Z) can meet the error-tolerance requirements of the corresponding terrain on the 1:500 scale set by the national standard of GB/T 23236-2009 in China. It is found that the K-AIDW algorithm displayed the best Z accuracy (root-mean-square error of 0.2538) compared with IDW (0.3668) and no-optimized (1.6012), proving it is an effective methodology for improving 3D-modelling accuracy of island. Numéro de notice : A2023-172 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.22-00109R2 Date de publication en ligne : 01/03/2023 En ligne : https://doi.org/10.14358/PERS.22-00109R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102923 [article]

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Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability / Benjamin T. Gutierrez in Earth and space science, vol 9 n° 11 (November 2022)  

Public [article]  inEarth and space science > vol 9 n° 11 (November 2022) . - 24 p. Titre : Integrating Bayesian networks to forecast sea-level rise impacts on barrier island characteristics and habitat availability Type de document : Article/Communication Auteurs : Benjamin T. Gutierrez, Auteur ; Sarah Zeigler, Auteur ; Erika Lentz, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : 24 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de sensibilité [Termes IGN] changement climatique [Termes IGN] géomorphologie [Termes IGN] habitat animal [Termes IGN] île [Termes IGN] modèle de simulation [Termes IGN] montée du niveau de la mer [Termes IGN] New York (Etats-Unis ; ville) [Termes IGN] planification côtière [Termes IGN] réseau bayesien [Termes IGN] submersion marine [Termes IGN] surveillance du littoral [Termes IGN] trait de côte Résumé : (auteur) Evaluation of sea-level rise (SLR) impacts on coastal landforms and habitats is a persistent need for informing coastal planning and management, including policy decisions, particularly those that balance human interests and habitat protection throughout the coastal zone. Bayesian networks (BNs) are used to model barrier island change under different SLR scenarios that are relevant to management and policy decisions. BNs utilized here include a shoreline change model and two models of barrier island biogeomorphological evolution at different scales (50 and 5 m). These BNs were then linked to another BN to predict habitat availability for piping plovers (Charadrius melodus), a threatened shorebird reliant on beach habitats. We evaluated the performance of the two linked geomorphology BNs and further examined error rates by generating hindcasts of barrier island geomorphology and habitat availability for 2014 conditions. Geomorphology hindcasts revealed that model error declined with a greater number of known inputs, with error rates reaching 55% when multiple outputs were hindcast simultaneously. We also found that, although error in predictions of piping plover nest presence/absence increased when outputs from the geomorphology BNs were used as inputs in the piping plover habitat BN, the maximum error rate for piping plover habitat suitability in the fully-linked BNs was only 30%. Our findings suggest this approach may be useful for guiding scenario-based evaluations where known inputs can be used to constrain variables that produce higher uncertainty for morphological predictions. Overall, the approach demonstrates a way to assimilate data and model structures with uncertainty to produce forecasts to inform coastal planning and management. Numéro de notice : A2022-883 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1029/2022EA002286 Date de publication en ligne : 14/10/2022 En ligne : https://doi.org/10.1029/2022EA002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102024 [article]

Three-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation / Massimiliano Alvioli in Geomatics, Natural Hazards and Risk, vol 13 (2022)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 2712 - 2736 Titre : Three-dimensional simulations of rockfalls in Ischia, Southern Italy, and preliminary susceptibility zonation Type de document : Article/Communication Auteurs : Massimiliano Alvioli, Auteur ; Ada De Mateo, Auteur ; Raffaele Castaldo, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2712 - 2736 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] cartographie des risques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] éboulement [Termes IGN] île [Termes IGN] Italie [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique de terrain [Termes IGN] pente [Termes IGN] risque naturel [Termes IGN] roche [Termes IGN] séisme [Termes IGN] semis de points [Termes IGN] surveillance géologique [Termes IGN] vulnérabilité Résumé : (auteur) Ischia Island is a volcano-tectonic horst in the Phlegrean Volcanic District, Italy. We investigated rockfalls in Ischia using STONE, a three-dimensional model for simulating trajectories for given detachment locations of blocks. We propose methodological advances regarding the use of high-resolution LiDAR elevation data, the localization of possible detachments sources, and the inclusion of scenario-based seismic shaking as a trigger for rockfalls. We demonstrated that raw LiDAR data are useful to distinguish areas covered by tall vegetation, allowing realistic simulation of trajectories. We found that the areas most susceptibile to rockfalls are located along the N, N-W and S-W steep flanks of Mt. Epomeo, the S and S-W coast, and the sides of some steep exposed hydrographic channels located in the southern sector of the island. A novel procedure for dynamic activation of sources depending on ground shaking, in the event of an earthquake, helped inferring a seismically-triggered source map and the corresponding rockfall trajectories, for a scenario with 475 y return time. Thus, we obtained preliminary rockfall suceptibility in Ischia both in a “static” (trigger-independent) scenario, and in a seismic shaking triggering scenario. They must not be considered a risk map, but a starting point for a detailed field analysis. Numéro de notice : A2022-874 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : https://doi.org/10.1080/19475705.2022.2131472 Date de publication en ligne : 09/10/2022 En ligne : https://doi.org/10.1080/19475705.2022.2131472 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102172 [article]

Geomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) / Marcello Buccolini in Journal of maps, vol 16 n° 3 ([01/12/2020])  

Public [article]  inJournal of maps > vol 16 n° 3 [01/12/2020] . - pp 10 - 18 Titre : Geomorphological analysis of the San Domino Island (Tremiti Islands, Southern Adriatic Sea). Results from the 2019 Geomorphological Field Camp of the MSc in Geological Science and Technology (University of Chieti-Pescara) Type de document : Article/Communication Auteurs : Marcello Buccolini, Auteur ; Cristiano Carabella, Auteur ; Giorgio Paglia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 10 - 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] 1:5.000 [Termes IGN] analyse des risques [Termes IGN] archipel [Termes IGN] cartographie géologique [Termes IGN] données de terrain [Termes IGN] géologie locale [Termes IGN] géomorphologie locale [Termes IGN] Italie [Termes IGN] morphométrie Résumé : (auteur) The 2019 Geomorphological Field Camp at San Domino Island (Tremiti Islands, Southern Adriatic Sea) is the result of geological and geomorphological field work activities carried out by a group of students attending the Geomorphological field mapping course of the Master’s Degree in Geological Science and Technology (University of Chieti-Pescara). The main map (1:5000 scale) was obtained through an integrated approach that incorporates morphometric analysis, geological and geomorphological field mapping, and geomorphological profiles drawing. Activities were carried out by all students, divided into six working groups of three to four persons each. The field camp and field work activities made it possible to produce a detailed thematic map, as a scientific tool to depict the San Domino Island landscape, and to outline some geomorphological issues in terms of possible constraints to landscape evolution, geomorphological processes distribution, and natural hazard assessment. Numéro de notice : A2020-816 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/17445647.2020.1831979 Date de publication en ligne : 16/11/2020 En ligne : https://doi.org/10.1080/17445647.2020.1831979 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96982 [article]

Combining GF-2 and RapidEye satellite data for mapping mangrove species using ensemble machine-learning methods / Liheng Peng in International Journal of Remote Sensing IJRS, vol 41 n° 3 (15 - 22 janvier 2020)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 41 n° 3 (15 - 22 janvier 2020) . - pp 813 - 838 Titre : Combining GF-2 and RapidEye satellite data for mapping mangrove species using ensemble machine-learning methods Type de document : Article/Communication Auteurs : Liheng Peng, Auteur ; Kai Liu, Auteur ; Jingjing Cao, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 813 - 838 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] apprentissage automatique [Termes IGN] boosting adapté [Termes IGN] Chine, mer de [Termes IGN] classification et arbre de régression [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] écosystème [Termes IGN] extraction de la végétation [Termes IGN] île [Termes IGN] image Gaofen [Termes IGN] image RapidEye [Termes IGN] image satellite [Termes IGN] mangrove [Termes IGN] modèle numérique de surface [Termes IGN] précision de la classification [Termes IGN] Rotation Forest classification Résumé : (auteur) Mangrove forests are important constitutions for sustainable development of coastal ecosystems, and they are often mapped and monitored with remote sensing approaches. Satellite images allow detailed studies of the distribution and composition of mangrove forests, and therefore facilitate the management and conservation of the ecosystems. The combination of multiple types of satellite images with different spatial and spectral resolutions is helpful in mangrove forests extraction and mangrove species discrimination as it reduces sampling workload and increases classification accuracies. In this study, the 1.0-m-resolution Gaofen-2 (GF-2) and the 5.0-m-resolution RapidEye-4 (RE-4) satellite images, acquired in February 2017 and November 2016 respectively, were used with ensemble machine-learning and object-oriented methods for mangroves mapping at both the community and species levels of the Qi’ao Island, Zhuhai, China. First, the mangroves on the island were segmented from the GF-2 image on a large scale, and then they were extracted combining with their digital elevation model (DEM) data. Second, the GF-2 image was further processed on a fine scale, in which object-oriented features from both the GF-2 and RE-4 images were extracted for each mangrove species. Third, it is followed by the mangrove species classification process which involves three ensemble machine-learning methods: the adaptive boosting (AdaBoost), the random forest (RF) and the rotation forest (RoF). These three methods employed a classification and regression tree (CART) as the base classifier. The results show that the overall accuracy (OA) of mangrove area extraction on the Qi’ao Island with the auxiliary data, DEM, achieves 98.76% (Kappa coefficient (κ) = 0.9289). The features extracted by the GF-2 and RE-4 images were shown to be beneficial for mangrove species discrimination. A maximum improvement in the OA of approximately 8% and a κκ of approximately 0.10 were achieved when employing RoF (OA = 92.01%, κ = 0.9016). Ensemble-learning methods can significantly improve the classification accuracy of CART, and the use of a bagging scheme (RF and RoF) is shown as a better way to map mangrove species than adaptive boosting (AdaBoost). In addition, RoF performed well in mangrove species classification but it was not as robust as the RF, whose average OA and κκ were 80.59% and 0.7608, respectively, while the RoF’s were 77.45% and 0.7214, respectively, in the 10-fold cross-validation. Numéro de notice : A2020-212 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01431161.2019.1648907 Date de publication en ligne : 30/07/2019 En ligne : https://doi.org/10.1080/01431161.2019.1648907 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94897 [article]

Télédétection des habitats insulaires ligériens par drone : Retour d’expérience sur les îles de Mareau-aux-Prés (Loiret) / Hilaire Martin in Revue forestière française, vol 71 n° 6 (2019)  

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Quand le Mont Saint-Michel redevient île / Alice Schwab in SIGmag, n° 6 (octobre 2015)

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Traitement de données Thematic Mapper pour la cartographie multi temporelle du plateau sous-marin autour des îles Kerkennah (Tunisie) / Rim Katlane in Photo interprétation, European journal of applied remote sensing, vol 50 n° 3 - 4 (septembre 2014)

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Tour du Monde des terres françaises oubliées / Bruno Fuligni (2014)

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Modélisation de l'accessibilité territoriale pour l'aide à la gestion de crise tsunami (Mayotte, France) / Frédéric Leone in Annales de géographie, n° 693 (septembre - octobre 2013)  

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Why the artificial shapes for the smaller islands on the portolan charts (1330-1600) help to clarify their navigational use / Tony Campbell in Cartes & Géomatique, n° 216 (juin 2013)  

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Plis et replis de la carte : formes artistiques de la cartographie / David Renaud in Cartes & Géomatique, n° 213 (septembre 2012)  

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Encyclopédie des tours du monde / C. Nau (2012)

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Crossing natural and data set boundaries : coastal terrain modelling in the South-West Finnish Archipelago / A. Stock in International journal of geographical information science IJGIS, vol 24 n° 9 (september 2010)  

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Inventorying management status and plant species richness in seminatural grasslands using high spatial resolution imagery / K. Hall in Applied Vegetation Science, vol 13 n° 2 (April 2010)  

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