ISPRS International journal of geo-information / International society for photogrammetry and remote sensing (1980 -) . vol 9 n° 3Paru le : 01/03/2020 |
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Ajouter le résultat dans votre panierRecent sea level change in the black sea from satellite altimetry and tide gauge observations / Nevin Betül Avsar in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : Recent sea level change in the black sea from satellite altimetry and tide gauge observations Type de document : Article/Communication Auteurs : Nevin Betül Avsar, Auteur ; H.S. Kutoglu, Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] altimétrie
[Termes IGN] déformation verticale de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] données marégraphiques
[Termes IGN] données satellitaires
[Termes IGN] données topographiques
[Termes IGN] érosion côtière
[Termes IGN] marégraphe
[Termes IGN] montée du niveau de la mer
[Termes IGN] Noire, mer
[Termes IGN] série temporelle
[Termes IGN] surcharge hydrologique
[Termes IGN] variation saisonnière
[Vedettes matières IGN] AltimétrieRésumé : (auteur) Global mean sea level has been rising at an increasing rate, especially since the early 19th century in response to ocean thermal expansion and ice sheet melting. The possible consequences of sea level rise pose a significant threat to coastal cities, inhabitants, infrastructure, wetlands, ecosystems, and beaches. Sea level changes are not geographically uniform. This study focuses on present-day sea level changes in the Black Sea using satellite altimetry and tide gauge data. The multi-mission gridded satellite altimetry data from January 1993 to May 2017 indicated a mean rate of sea level rise of 2.5 ± 0.5 mm/year over the entire Black Sea. However, when considering the dominant cycles of the Black Sea level time series, an apparent (significant) variation was seen until 2014, and the rise in the mean sea level has been estimated at about 3.2 ± 0.6 mm/year. Coastal sea level, which was assessed using the available data from 12 tide gauge stations, has generally risen (except for the Bourgas Station). For instance, from the western coast to the southern coast of the Black Sea, in Constantza, Sevastopol, Tuapse, Batumi, Trabzon, Amasra, Sile, and Igneada, the relative rise was 3.02, 1.56, 2.92, 3.52, 2.33, 3.43, 5.03, and 6.94 mm/year, respectively, for varying periods over 1922–2014. The highest and lowest rises in the mean level of the Black Sea were in Poti (7.01 mm/year) and in Varna (1.53 mm/year), respectively. Measurements from six Global Navigation Satellite System (GNSS) stations, which are very close to the tide gauges, also suggest that there were significant vertical land movements at some tide gauge locations. This study confirmed that according to the obtained average annual phase value of sea level observations, seasonal sea level variations in the Black Sea reach their maximum annual amplitude in May–June. Numéro de notice : A2020-254 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030185 Date de publication en ligne : 20/03/2020 En ligne : https://doi.org/10.3390/ijgi9030185 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95008
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 18 p.[article]Uber movement data: a proxy for average one-way commuting times by car / Yeran Sun in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : Uber movement data: a proxy for average one-way commuting times by car Type de document : Article/Communication Auteurs : Yeran Sun, Auteur ; Yinming Ren, Auteur ; Xuan Sun, Auteur Année de publication : 2020 Article en page(s) : 16 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Boston (Massachusetts)
[Termes IGN] distribution spatiale
[Termes IGN] durée de trajet
[Termes IGN] flux
[Termes IGN] migration pendulaire
[Termes IGN] objet mobile
[Termes IGN] origine - destination
[Termes IGN] planification urbaine
[Termes IGN] taxi
[Termes IGN] trace GPSRésumé : (auteur) Recently, Uber released datasets named Uber Movement to the public in support of urban planning and transportation planning. To prevent user privacy issues, Uber aggregates car GPS traces into small areas. After aggregating car GPS traces into small areas, Uber releases free data products that indicate the average travel times of Uber cars between two small areas. The average travel times of Uber cars in the morning peak time periods on weekdays could be used as a proxy for average one-way car-based commuting times. In this study, to demonstrate usefulness of Uber Movement data, we use Uber Movement data as a proxy for commuting time data by which commuters’ average one-way commuting time across Greater Boston can be figured out. We propose a new approach to estimate the average car-based commuting times through combining commuting times from Uber Movement data and commuting flows from travel survey data. To further demonstrate the applicability of the commuting times estimated by Uber movement data, this study further measures the spatial accessibility of jobs by car by aggregating place-to-place commuting times to census tracts. The empirical results further uncover that 1) commuters’ average one-way commuting time is around 20 min across Greater Boston; 2) more than 75% of car-based commuters are likely to have a one-way commuting time of less than 30 min; 3) less than 1% of car-based commuters are likely to have a one-way commuting time of more than 60 min; and 4) the areas suffering a lower level of spatial accessibility of jobs by car are likely to be evenly distributed across Greater Boston. Numéro de notice : A2020-255 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030184 Date de publication en ligne : 24/03/2020 En ligne : https://doi.org/10.3390/ijgi9030184 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95010
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 16 p.[article]Classification and segmentation of mining area objects in large-scale spares Lidar point cloud using a novel rotated density network / Yueguan Yan in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : Classification and segmentation of mining area objects in large-scale spares Lidar point cloud using a novel rotated density network Type de document : Article/Communication Auteurs : Yueguan Yan, Auteur ; Haixu Yan, Auteur ; Junting Guo, Auteur ; Huayang Dai, Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] apprentissage profond
[Termes IGN] classification barycentrique
[Termes IGN] classification orientée objet
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] densité des points
[Termes IGN] données lidar
[Termes IGN] objet 3D
[Termes IGN] reconnaissance d'objets
[Termes IGN] semis de points clairsemésRésumé : (auteur) The classification and segmentation of large-scale, sparse, LiDAR point cloud with deep learning are widely used in engineering survey and geoscience. The loose structure and the non-uniform point density are the two major constraints to utilize the sparse point cloud. This paper proposes a lightweight auxiliary network, called the rotated density-based network (RD-Net), and a novel point cloud preprocessing method, Grid Trajectory Box (GT-Box), to solve these problems. The combination of RD-Net and PointNet was used to achieve high-precision 3D classification and segmentation of the sparse point cloud. It emphasizes the importance of the density feature of LiDAR points for 3D object recognition of sparse point cloud. Furthermore, RD-Net plus PointCNN, PointNet, PointCNN, and RD-Net were introduced as comparisons. Public datasets were used to evaluate the performance of the proposed method. The results showed that the RD-Net could significantly improve the performance of sparse point cloud recognition for the coordinate-based network and could improve the classification accuracy to 94% and the segmentation per-accuracy to 70%. Additionally, the results concluded that point-density information has an independent spatial–local correlation and plays an essential role in the process of sparse point cloud recognition. Numéro de notice : A2020-256 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 0.3390/ijgi9030182 Date de publication en ligne : 24/03/2020 En ligne : https://doi.org/10.3390/ijgi9030182 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95012
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 19 p.[article]A proposal for modeling indoor–outdoor spaces through indoorGML, open location code and OpenStreetMap / Ruben Cantarero Navarro in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : A proposal for modeling indoor–outdoor spaces through indoorGML, open location code and OpenStreetMap Type de document : Article/Communication Auteurs : Ruben Cantarero Navarro, Auteur ; Ana Rubio Ruiz, Auteur ; Javier Dorado Chaparro, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 21 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] CityGML
[Termes IGN] données hétérogènes
[Termes IGN] format Industry foudation classes IFC
[Termes IGN] indoorGML
[Termes IGN] internet des objets
[Termes IGN] modélisation 3D
[Termes IGN] OpenStreetMap
[Termes IGN] positionnement en intérieur
[Termes IGN] représentation spatiale
[Termes IGN] ville intelligente
[Termes IGN] WiFiRésumé : (auteur) Traditionally, the standards of spatial modeling are oriented to represent the quantitative information of space. However, in recent years an increasingly common challenge is appearing: flexibly and appropriately integrating quantitative information that goes beyond the purely geometric. This problem has been aggravated due to the success of new paradigms such as the Internet of Things. This adds an additional challenge to the representation of this information due to the need to represent characteristic information of the space from different points of view in a model, such as WiFi coverage, dangerous surroundings, etc. While this problem has already been addressed in indoor spaces with the IndoorGML standard, it remains to be solved in outdoor and indoor–outdoor spaces. We propose to take the advantages proposed in IndoorGML, such as cellular space or multi-layered space model representation, to outdoor spaces in order to create indoor–outdoor models that enable the integration of heterogeneous information that represents different aspects of space. We also propose an approach that gives more flexibility in spatial representation through the integration of standards such as OpenLocationCode for the division of space. Further, we suggest a procedure to enrich the resulting model through the information available in OpenStreetMap. Numéro de notice : A2020-257 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030169 Date de publication en ligne : 12/03/2020 En ligne : https://doi.org/10.3390/ijgi9030169 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95013
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 21 p.[article]Development and application of an intelligent modeling method for ancient wooden architecture / Yonghui Jiang in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : Development and application of an intelligent modeling method for ancient wooden architecture Type de document : Article/Communication Auteurs : Yonghui Jiang, Auteur ; Aiqun Li, Auteur ; Linlin Xie, Auteur Année de publication : 2020 Article en page(s) : 19 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Architecture
[Termes IGN] architecture orientée modèle
[Termes IGN] Chine
[Termes IGN] conservation du patrimoine
[Termes IGN] histoire
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] monument historique
[Termes IGN] patrimoine culturel
[Termes IGN] patrimoine immobilier
[Termes IGN] reconstruction 3D du bâtiRésumé : (auteur) Building-information-modeling for cultural heritage (HBIM), which is established using surveying data, can be used to conserve architectural heritage. The development of an HBIM model for ancient wooden architecture (AWA) structures requires interdisciplinary integration. A parametric model for the main components that intelligently integrates the historical knowledge, as well as an intelligent modeling method for these components, are two critical issues required to bridge the existing gap and improve the application of HBIM. Taking an AWA structure constructed during the Liao and Song Dynasties as an example, the parametric model for the typical components, with emphasis on commonality and characteristics, were first proposed. Subsequently, an intelligent automated modeling method was developed and programmed using Dynamo, which can intelligently identify the component type and determine the invisible dimensions. A complicated dou-gong was successfully established with surveying data using the proposed method within five minutes, thereby validating the reliability and efficiency of this method. Furthermore, the proposed method was used to establish the HBIM model of Yingxian Wood Pagoda, which is the oldest and tallest AWA structure in China with a height of 65.88 m. The research findings will provide an essential reference for the conservation of wooden architectural heritage structures. Numéro de notice : A2020-258 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030167 En ligne : https://doi.org/10.3390/ijgi9030167 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95015
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 19 p.[article]A novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety / Mayra Salcedo-Gonzalez in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : A novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety Type de document : Article/Communication Auteurs : Mayra Salcedo-Gonzalez, Auteur ; Julio Suarez-Paez, Auteur ; Manuel Esteve, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] cartographie des risques
[Termes IGN] Colombie
[Termes IGN] criminalité
[Termes IGN] données spatiotemporelles
[Termes IGN] géoréférencement
[Termes IGN] géovisualisation
[Termes IGN] gestion des ressources humaines
[Termes IGN] gestion urbaine
[Termes IGN] logiciel libre
[Termes IGN] protection civile
[Termes IGN] risque social
[Termes IGN] système d'information urbain
[Termes IGN] système de contrôle
[Termes IGN] ville intelligenteRésumé : (auteur) This article shows a novel geo-visualization method of dynamic spatiotemporal data that allows mobility and concentration of criminal activity to be study. The method was developed using, only and significantly, real data of Santiago de Cali (Colombia), collected by the Colombian National Police (PONAL). This method constitutes a tool that allows criminal influx to be analyzed by concentration, zone, time slot and date. In addition to the field experience of police commanders, it allows patterns of criminal activity to be detected, thereby enabling a better distribution and management of police resources allocated to crime deterrence, prevention and control. Additionally, it may be applied to the concepts of safe city and smart city of the PONAL within the architecture of Command and Control System (C2S) of Command and Control Centers for Public Safety. Furthermore, it contributes to a better situational awareness and improves the future projection, agility, efficiency and decision-making processes of police officers, which are all essential for fulfillment of police missions against crime. Finally, this was developed using an open source software, it can be adapted to any other city, be used with real-time data and be implemented, if necessary, with the geographic software of any other C2S. Numéro de notice : A2020-259 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi9030160 Date de publication en ligne : 10/03/2020 En ligne : https://doi.org/10.3390/ijgi9030160 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95016
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 17 p.[article]Integration of remote sensing and GIS to extract plantation rows from a drone-based image point cloud digital surface model / Nadeem Fareed in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : Integration of remote sensing and GIS to extract plantation rows from a drone-based image point cloud digital surface model Type de document : Article/Communication Auteurs : Nadeem Fareed, Auteur ; Khushbakht Rehman, Auteur Année de publication : 2020 Article en page(s) : 26 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] agriculture de précision
[Termes IGN] données GNSS
[Termes IGN] données lidar
[Termes IGN] extraction automatique
[Termes IGN] extraction de la végétation
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] image à très haute résolution
[Termes IGN] image captée par drone
[Termes IGN] image RVB
[Termes IGN] modèle dynamique
[Termes IGN] modèle numérique de surface
[Termes IGN] semis de points
[Termes IGN] structure-from-motion
[Termes IGN] système d'information géographique
[Termes IGN] télédétectionRésumé : (auteur) Automated feature extraction from drone-based image point clouds (DIPC) is of paramount importance in precision agriculture (PA). PA is blessed with mechanized row seedlings to attain maximum yield and best management practices. Therefore, automated plantation rows extraction is essential in crop harvesting, pest management, and plant grow-rate predictions. Most of the existing research is consists on red, green, and blue (RGB) image-based solutions to extract plantation rows with the minimal background noise of test study sites. DIPC-based DSM row extraction solutions have not been tested frequently. In this research work, an automated method is designed to extract plantation row from DIPC-based DSM. The chosen plantation compartments have three different levels of background noise in UAVs images, therefore, methodology was tested under different background noises. The extraction results were quantified in terms of completeness, correctness, quality, and F1-score values. The case study revealed the potential of DIPC-based solution to extraction the plantation rows with an F1-score value of 0.94 for a plantation compartment with minimal background noises, 0.91 value for a highly noised compartment, and 0.85 for a compartment where DIPC was compromised. The evaluation suggests that DSM-based solutions are robust as compared to RGB image-based solutions to extract plantation-rows. Additionally, DSM-based solutions can be further extended to assess the plantation rows surface deformation caused by humans and machines and state-of-the-art is redefined. Numéro de notice : A2020-260 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030151 Date de publication en ligne : 06/03/2020 En ligne : https://doi.org/10.3390/ijgi9030151 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95020
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 26 p.[article]