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A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping / Wei Chen in Geocarto international, vol 32 n° 4 (April 2017)
[article]
Titre : A GIS-based comparative study of Dempster-Shafer, logistic regression and artificial neural network models for landslide susceptibility mapping Type de document : Article/Communication Auteurs : Wei Chen, Auteur ; Hamid Reza Pourghasemi, Auteur ; Zhou Zhao, Auteur Année de publication : 2017 Article en page(s) : pp 367 - 385 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] aléa
[Termes IGN] analyse comparative
[Termes IGN] ArcGIS
[Termes IGN] cartographie des risques
[Termes IGN] Chine
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] classification par réseau neuronal
[Termes IGN] effondrement de terrain
[Termes IGN] régression logistique
[Termes IGN] risque naturel
[Termes IGN] vulnérabilitéRésumé : (Auteur) The main aim of present study is to compare three GIS-based models, namely Dempster–Shafer (DS), logistic regression (LR) and artificial neural network (ANN) models for landslide susceptibility mapping in the Shangzhou District of Shangluo City, Shaanxi Province, China. At First, landslide locations were identified by aerial photographs and supported by field surveys, and a total of 145 landslide locations were mapped in the study area. Subsequently, the landslide inventory was randomly divided into two parts (70/30) using Hawths Tools in ArcGIS 10.0 for training and validation purposes, respectively. In the present study, 14 landslide conditioning factors such as altitude, slope angle, slope aspect, topographic wetness index, sediment transport index, stream power index, plan curvature, profile curvature, lithology, rainfall, distance to rivers, distance to roads, distance to faults and normalized different vegetation index were used to detect the most susceptible areas. In the next step, landslide susceptible areas were mapped using the DS, LR and ANN models based on landslide conditioning factors. Finally, the accuracies of the landslide susceptibility maps produced from the three models were verified using the area under the curve (AUC). The validation results showed that the landslide susceptibility map generated by the ANN model has the highest training accuracy (73.19%), followed by the LR model (71.37%), and the DS model (66.42%). Similarly, the AUC plot for prediction accuracy presents that ANN model has the highest accuracy (69.62%), followed by the LR model (68.94%), and the DS model (61.39%). According to the validation results of the AUC curves, the map produced by these models exhibits the satisfactory properties. Numéro de notice : A2017-271 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1140824 Date de publication en ligne : 22/03/2016 En ligne : http://doi.org/10.1080/10106049.2016.1140824 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85297
in Geocarto international > vol 32 n° 4 (April 2017) . - pp 367 - 385[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2017041 RAB Revue Centre de documentation En réserve L003 Disponible Generating a hazard map of dynamic objects using lidar mobile mapping / Alexander Schlichting in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 12 (December 2016)
[article]
Titre : Generating a hazard map of dynamic objects using lidar mobile mapping Type de document : Article/Communication Auteurs : Alexander Schlichting, Auteur ; Claus Brenner, Auteur Année de publication : 2016 Article en page(s) : pp 967 - 972 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] aléa
[Termes IGN] cartographie cadastrale
[Termes IGN] cartographie des risques
[Termes IGN] détection de piéton
[Termes IGN] processus
[Termes IGN] semis de points
[Termes IGN] système de numérisation mobile
[Termes IGN] véhicule sans piloteRésumé : (auteur) One of the hardest problems for future self-driving cars is to predict hazardous situations involving pedestrians and cyclists. Human drivers solve this problem typically by having a deeper understanding of the scene. The technical equivalent of this is to provide a hazard map, which serves as a prior for self-driving cars, enabling them to adjust driving speed and processing thresholds.
In this paper, we present a method to derive such a hazard map using lidar mobile mapping. Pedestrians and cyclists are obtained from a sequence of point clouds by segmentation and classification. Their locations are then accumulated in a grid map, which serves as a "heat map" for possible hazardous situations. To demonstrate our approach, we generated a map using lidar mobile mapping, obtained by twelve measurement campaigns in Hanover (Germany). Our results show different outcomes for the city center, residential areas, busy roads, and road junctions.Numéro de notice : A2016-985 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.12.967 En ligne : https://doi.org/10.14358/PERS.82.12.967 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83701
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 12 (December 2016) . - pp 967 - 972[article]Local-scale flood mapping on vegetated floodplains from radiometrically calibrated airborne LiDAR data / Radosław Malinowski in ISPRS Journal of photogrammetry and remote sensing, vol 119 (September 2016)
[article]
Titre : Local-scale flood mapping on vegetated floodplains from radiometrically calibrated airborne LiDAR data Type de document : Article/Communication Auteurs : Radosław Malinowski, Auteur ; Bernhard Höfle, Auteur ; Kristina Koenig, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 267 - 279 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] capteur aérien
[Termes IGN] cartographie des risques
[Termes IGN] classification
[Termes IGN] classification bayesienne
[Termes IGN] classification par arbre de décision
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] couvert végétal
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] étalonnage radiométrique
[Termes IGN] forme d'onde pleine
[Termes IGN] inondation
[Termes IGN] lidar à retour d'onde complète
[Termes IGN] lit majeurRésumé : (Auteur) Knowledge about the magnitude of localised flooding of riverine areas is crucial for appropriate land management and administration at regional and local levels. However, detection and delineation of localised flooding with remote sensing techniques are often hampered on floodplains by the presence of herbaceous vegetation. To address this problem, this study presents the application of full-waveform airborne laser scanning (ALS) data for detection of floodwater extent. In general, water surfaces are characterised by low values of backscattered energy due to water absorption of the infrared laser shots, but the exact strength of the recorded laser pulse depends on the area covered by the targets located within a laser pulse footprint area. To account for this we analysed the physical quantity of radiometrically calibrated ALS data, the backscattering coefficient, in relation to water and vegetation coverage within a single laser footprint. The results showed that the backscatter was negatively correlated to water coverage, and that of the three distinguished classes of water coverage (low, medium, and high) only the class with the largest extent of water cover (>70%) had relatively distinct characteristics that can be used for classification of water surfaces. Following the laser footprint analysis, three classifiers, namely AdaBoost with Decision Tree, Naïve Bayes and Random Forest, were utilised to classify laser points into flooded and non-flooded classes and to derive the map of flooding extent. The performance of the classifiers is highly dependent on the set of laser points features used. Best performance was achieved by combining radiometric and geometric laser point features. The accuracy of flooding maps based solely on radiometric features resulted in overall accuracies of up to 70% and was limited due to the overlap of the backscattering coefficient values between water and other land cover classes. Our point-based classification methods assure a high mapping accuracy (∼89%) and demonstrate the potential of using full-waveform ALS data to detect water surfaces on floodplain areas with limited water surface exposition through the vegetation canopy. Numéro de notice : A2016-785 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.06.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.06.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82499
in ISPRS Journal of photogrammetry and remote sensing > vol 119 (September 2016) . - pp 267 - 279[article]Satellite image collection modeling for large area hazard emergency response / Shufan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 118 (August 2016)
[article]
Titre : Satellite image collection modeling for large area hazard emergency response Type de document : Article/Communication Auteurs : Shufan Liu, Auteur ; Michael E. Hodgson, Auteur Année de publication : 2016 Article en page(s) : pp 13 – 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] cartographie d'urgence
[Termes IGN] image satellite
[Termes IGN] planification
[Termes IGN] risque naturel
[Termes IGN] traitement d'imageRésumé : (auteur) Timely collection of critical hazard information is the key to intelligent and effective hazard emergency response decisions. Satellite remote sensing imagery provides an effective way to collect critical information. Natural hazards, however, often have large impact areas – larger than a single satellite scene. Additionally, the hazard impact area may be discontinuous, particularly in flooding or tornado hazard events. In this paper, a spatial optimization model is proposed to solve the large area satellite image acquisition planning problem in the context of hazard emergency response. In the model, a large hazard impact area is represented as multiple polygons and image collection priorities for different portion of impact area are addressed. The optimization problem is solved with an exact algorithm. Application results demonstrate that the proposed method can address the satellite image acquisition planning problem. A spatial decision support system supporting the optimization model was developed. Several examples of image acquisition problems are used to demonstrate the complexity of the problem and derive optimized solutions. Numéro de notice : A2016-588 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.04.007 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.04.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81733
in ISPRS Journal of photogrammetry and remote sensing > vol 118 (August 2016) . - pp 13 – 21[article]Measurement of surface changes in a scaled-down landslide model using high-speed stereo image sequences / Tiantian Feng in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 7 (juillet 2016)
[article]
Titre : Measurement of surface changes in a scaled-down landslide model using high-speed stereo image sequences Type de document : Article/Communication Auteurs : Tiantian Feng, Auteur ; Huan Mi, Auteur ; Marco Scaioni, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 547 - 557 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] cartographie d'urgence
[Termes IGN] Chine
[Termes IGN] détection de changement
[Termes IGN] effondrement de terrain
[Termes IGN] gestion prévisionnelle
[Termes IGN] modèle de simulation
[Termes IGN] modèle stéréoscopique
[Termes IGN] photogrammétrie métrologique
[Termes IGN] séquence d'images
[Termes IGN] surveillance géologique
[Termes IGN] vitesseRésumé : (Auteur) Construction of scaled-down landslide models is an important means for landslide study. The objective of this study is to develop an innovative non-contact photogrammetric system to meet the challenge for monitoring the fast surface deformation of a laboratory-simulated landslide, which can detect pre-failure events and the final failure, provide sectional and overall surface deformation patterns, and generate speed maps during the rapid slope failure. We proposed an event detector based on altered surface features in the slower SLRC (single-lensreflex camera) image sequence to detect pre-failure events, while a combined analysis tool used the surface velocity fields and deformation areas based on fast HSCS (high-speed stereocamera system) stereo image sequences to reveal fast-changing landslide behavior during the short final failure. The introduced surface change detector uses the percentage of sliding block areas, percentage of changed features, and average speeds. It successfully detected four pre-failure local collapse events and the final slope failure; the extent of surface changes reached its maximum to accumulate energy 1.5 seconds before the failure when the average speed of changed features achieved its peak of 0.8 m/s. The developed system achieved a position accuracy of 3.8 mm and a speed accuracy of 0.11 m/s. The analysis result demonstrated a time period of 66 minutes before the failure which is confirmed by significant signals from both imaging and contact sensors and is important for landslide early warning. A field implementation scheme in western China will be designed and realized in the near future. Numéro de notice : A2016-516 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.7.547 En ligne : http://dx.doi.org/10.14358/PERS.82.7.547 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81587
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