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A hydrological sensor web ontology based on the SSN ontology: A case study for a flood / Chao Wang in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 1 (January 2018) Titre : A hydrological sensor web ontology based on the SSN ontology: A case study for a flood Type de document : Article/Communication Auteurs : Chao Wang, Auteur ; Nengcheng Chen, Auteur ; Wei Wang, Auteur ; Zeqiang Chen, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] classe d'objets [Termes IGN] données spatiotemporelles [Termes IGN] hydrographie [Termes IGN] modèle d'ontologie [Termes IGN] ontologie [Termes IGN] raisonnement sémantique [Termes IGN] réseau de capteurs Résumé : (Auteur) Accompanying the continuous development of sensor network technology, sensors worldwide are constantly producing observation data. However, the sensors and their data from different observation platforms are sometimes difficult to use collaboratively in response to natural disasters such as floods for the lack of semantics. In this paper, a hydrological sensor web ontology based on SSN ontology is proposed to describe the heterogeneous hydrological sensor web resources by importing the time and space ontology, instantiating the hydrological classes, and establishing reasoning rules. This work has been validated by semantic querying and knowledge acquiring experiments. The results demonstrate the feasibility and effectiveness of the proposed ontology and its potential to grow into a more comprehensive ontology for hydrological monitoring collaboratively. In addition, this method of ontology modeling is generally applicable to other applications and domains. Numéro de notice : A2018-039 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7010002 En ligne : https://doi.org/10.3390/ijgi7010002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89261 [article]

Exploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 1 (January 2018) Titre : Exploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region Type de document : Article/Communication Auteurs : Tao Zhou, Auteur ; Meifang Zhao, Auteur ; Chuanliang Sun, Auteur ; Jianjun Pan, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte d'occupation du sol [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image GF-1 [Termes IGN] image Sentinel-SAR [Termes IGN] Kiangsou (Chine) [Termes IGN] surface imperméable [Termes IGN] variation saisonnière [Termes IGN] zone urbaine Résumé : (Auteur) The objective of this research was to investigate the impact of seasonality on urban land-cover mapping and to explore better classification accuracy by using multi-season Sentinel-1A and GF-1 wide field view (WFV) images, and the combinations of both types of images in subtropical monsoon-climate regions in Southeast China. We obtained multi-season Sentinel-1A and GF-1 WFV images, as well as the combinations of both data, by using a support vector machine (SVM) and a random forest (RF) classifier. The backscatter intensity, texture, and interference-coherence images were extracted from Sentinel-1A images, and different combinations of these Sentinel-1A-derived images were used to evaluate their ability to map urban land cover. The results showed that the performance of winter images was better than that of any other season, while the summer images performed the worst. Higher classification accuracy was achieved by using multi-season images, and satisfactory classification results were obtained when using Sentinel-1A images from only three seasons. The best classification result was achieved using a combination of all Sentinel-1A data from all four seasons and GF-1 WFV data from winter, with an overall accuracy of up to 96.02% and a kappa coefficient reaching 0.9502. The performance of textures was slightly better than that of the backscatter-intensity images. Although the coherence data performed the worst, it was still able to distinguish urban impervious surfaces well. In addition, the overall classification accuracy of RF was better than that of SVM. Numéro de notice : A2018-040 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7010003 En ligne : https://doi.org/10.3390/ijgi7010003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89262 [article]

Cartographic redundancy in reducing change blindness in detecting extreme values in spatio-temporal maps / Paweł Cybulski in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 1 (January 2018) Titre : Cartographic redundancy in reducing change blindness in detecting extreme values in spatio-temporal maps Type de document : Article/Communication Auteurs : Paweł Cybulski, Auteur ; Beata Medyńska-Gulij, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cécité au changement [Termes IGN] données spatiotemporelles [Termes IGN] redondance de données [Termes IGN] test de performance [Termes IGN] vision [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) The article investigates the possibility of using cartographic redundancy to reduce the change blindness effect on spatio-temporal maps. Unlike in the case of previous research, the authors take a look at various methods of cartographic presentation and modify the visual variables in order to see how those modifications affect the user’s perception of changes on spatio-temporal maps. The study described in the following article was the first attempt at minimizing the change blindness phenomenon by manipulating graphical parameters of cartographic visualization and using various quantitative mapping methods. Research shows that cartographic redundancy is not enough to completely resolve the problem of change blindness; however, it might help reduce it. Numéro de notice : A2018-041 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7010008 En ligne : https://doi.org/10.3390/ijgi7010008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89263 [article]

Multilevel visualization of travelogue trajectory data / Yongsai Ma in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 1 (January 2018) Titre : Multilevel visualization of travelogue trajectory data Type de document : Article/Communication Auteurs : Yongsai Ma, Auteur ; Yang Wang, Auteur ; Guangluan Xu, Auteur ; Xianqing Tai, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] récit [Termes IGN] trajet (mobilité) [Termes IGN] visualisation de données [Vedettes matières IGN] Géovisualisation Résumé : (Auteur) User-generated travelogues can generate much geographic data, containing abundant semantic and geographic information that reflects people’s movement patterns. The tourist movement patterns in travelogues can help others when planning trips, or understanding how people travel within certain regions. The trajectory data in travelogues might include tourist attractions, restaurants and other locations. In addition, all travelogues generate a trajectory, which has a large volume. The variety and volume of trajectory data make it very hard to directly find patterns contained within them. Moreover, existing work about movement patterns has only explored the simple semantic information, without considering using visualization to find hidden information. We propose a multilevel visual analytical method to help find movement patterns in travelogues. The data characteristic of a single travelogue are different from multiple travelogues. When exploring a single travelogue, the individual movement patterns comprise our main concern, like semantic information. While looking at many travelogues, we focus more on the patterns of population movement. In addition, when choosing the levels for multilevel aggregation, we apply an adaptive method. By combining the multilevel visualization in a single travelogue and multiple travelogues, we can better explore the movement patterns in travelogues. Numéro de notice : A2018-042 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7010012 En ligne : https://doi.org/10.3390/ijgi7010012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89265 [article]