Centre dedocumentation
scientifique

Combined InSAR and terrestrial structural monitoring of bridges / Sivasakthy Selvakumaran in IEEE Transactions on geoscience and remote sensing, vol 58 n° 10 (October 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 10 (October 2020) . - pp 7141 - 7153 Titre : Combined InSAR and terrestrial structural monitoring of bridges Type de document : Article/Communication Auteurs : Sivasakthy Selvakumaran, Auteur ; Cristian Rossi, Auteur ; Andrea Marinoni, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 7141 - 7153 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] coin réflecteur [Termes descripteurs IGN] données multisources [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] incertitude des données [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] Londres [Termes descripteurs IGN] pont [Termes descripteurs IGN] surveillance d'ouvrage [Termes descripteurs IGN] tachéomètre électronique Résumé : (auteur) This article examines advances in interferometric synthetic aperture radar (InSAR) satellite measurement technologies to understand their relevance, utilization, and limitations for bridge monitoring. Waterloo Bridge is presented as a case study to explore how InSAR data sets can be combined with traditional measurement techniques including sensors installed on the bridge and automated total stations. A novel approach to InSAR bridge monitoring was adopted by the installation of physical reflectors at key points of structural interest on the bridge, in order to supplement the bridge’s own reflection characteristics and ensure that the InSAR measurements could be directly compared and combined with in situ measurements. The interpretation and integration of InSAR data sets with civil infrastructure data are more than a trivial task, and a discussion of uncertainty of measurement data is presented. Finally, a strategy for combining and interpreting varied data from multiple sources to provide useful insights into each of these methods is presented, outlining the practical applications of this data analysis to support wider monitoring strategies. Numéro de notice : A2020-588 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2979961 date de publication en ligne : 01/04/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2979961 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95916 [article]

Evaluating the accuracy of ALS-based removal estimates against actual logging data / Ville Vähä-Konka in Annals of Forest Science [en ligne], vol 77 n° 3 (September 2020)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 77 n° 3 (September 2020) . - 11 p. Titre : Evaluating the accuracy of ALS-based removal estimates against actual logging data Type de document : Article/Communication Auteurs : Ville Vähä-Konka, Auteur ; Matti Maltamo, Auteur ; Timo Pukkala, Auteur ; Kalle Kärhä, Auteur Année de publication : 2020 Article en page(s) : 11 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] éclaircie (sylviculture) [Termes descripteurs IGN] fiabilité des données [Termes descripteurs IGN] Finlande [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] inventaire forestier étranger (données) [Termes descripteurs IGN] récolte de bois [Termes descripteurs IGN] télédétection par lidar [Termes descripteurs IGN] télémètre laser aéroporté [Termes descripteurs IGN] volume en bois Résumé : (auteur) Key message: We examined the accuracy of the stand attribute data based on airborne laser scanning (ALS) provided by the Finnish Forest Centre. The precision of forest inventory data was compared for the first time with operative logging data measured by the harvester. Context: Airborne laser scanning (ALS) is increasingly used together with models to predict the stand attributes of boreal forests. The information is updated by growth models. Information produced by remote sensing, model prediction, and growth simulation needs field verification. The data collected by harvesters on logging sites provide a means to evaluate and verify the accuracy of the ALS-based data. Aims: This study investigated the accuracy of ALS-based forest inventory data provided by the Finnish Forest Centre at the stand level, using harvester data as the reference. Special interest was on timber assortment volumes where the quality reductions of sawlog are model predictions in ALS-based data and true realized reductions in the logging data. Methods: We examined the accuracy of total volume and timber assortment volumes by comparing ALS-based data and operative logging data measured by a harvester. This was done both for clear cuttings and thinning sites. Accuracy of the identification of the dominant tree species of the stand was examined using the Kappa coefficient. Results: In clear-felling sites, the total harvest removals based on ALS and model prediction had a RMSE% of 26.0%. In thinning, the corresponding difference in the total harvested removal was 42.4%. Compared to logged volume, ALS-based prediction overestimated sawlog removals in clear cuttings and underestimated pulpwood removals. Conclusion: The study provided valuable information on the accuracy of ALS-based stand attribute data. Our results showed that ALS-based data need better methods to predict the technical quality of harvested trees, to avoid systematic overestimates of sawlog volume. We also found that the ALS-based estimates do not accurately predict the volume of trees removed in actual thinnings. Numéro de notice : A2020-592 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-00985-7 date de publication en ligne : 27/08/2020 En ligne : https://doi.org/10.1007/s13595-020-00985-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95927 [article]

OSMWatchman: Learning how to detect vandalized contributions in OSM using a Random Forest classifier / Quy Thy Truong in ISPRS International journal of geo-information, vol 9 n° 9 (September 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 9 (September 2020) . - n° 504 Titre : OSMWatchman: Learning how to detect vandalized contributions in OSM using a Random Forest classifier Type de document : Article/Communication Auteurs : Quy Thy Truong , Auteur ; Guillaume Touya , Auteur ; Cyril de Runz, Auteur Année de publication : 2020 Projets : 1-Pas de projet / Article en page(s) : n° 504 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes descripteurs IGN] cartographie collaborative [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] qualité des données Résumé : (auteur) Though Volunteered Geographic Information (VGI) has the advantage of providing free open spatial data, it is prone to vandalism, which may heavily decrease the quality of these data. Therefore, detecting vandalism in VGI may constitute a first way of assessing the data in order to improve their quality. This article explores the ability of supervised machine learning approaches to detect vandalism in OpenStreetMap (OSM) in an automated way. For this purpose, our work includes the construction of a corpus of vandalism data, given that no OSM vandalism corpus is available so far. Then, we investigate the ability of random forest methods to detect vandalism on the created corpus. Experimental results show that random forest classifiers perform well in detecting vandalism in the same geographical regions that were used for training the model and has more issues with vandalism detection in “unfamiliar regions”. Numéro de notice : A2020-507 Affiliation des auteurs : UMR LaSTIG+Ext Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9090504 date de publication en ligne : 22/08/2020 En ligne : https://doi.org/10.3390/ijgi9090504 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95682 [article]

A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery / Bo Yang in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 9 (September 2020) . - pp 1740 - 1764 Titre : A spatio-temporal method for crime prediction using historical crime data and transitional zones identified from nightlight imagery Type de document : Article/Communication Auteurs : Bo Yang, Auteur ; Lin Liu, Auteur ; Minxuan Lan, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1740 - 1764 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] criminalité [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] géostatistique [Termes descripteurs IGN] historique des données [Termes descripteurs IGN] image VIIRS [Termes descripteurs IGN] krigeage [Termes descripteurs IGN] modèle dynamique [Termes descripteurs IGN] nuit [Termes descripteurs IGN] Ohio (Etats-Unis) [Termes descripteurs IGN] prédiction [Termes descripteurs IGN] prévention des risques [Termes descripteurs IGN] prise de vue nocturne [Termes descripteurs IGN] test statistique [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Accurate crime prediction can help allocate police resources for crime reduction and prevention. There are two popular approaches to predict criminal activities: one is based on historical crime, and the other is based on environmental variables correlated with criminal patterns. Previous research on geo-statistical modeling mainly considered one type of data in space-time domain, and few sought to blend multi-source data. In this research, we proposed a spatio-temporal Cokriging algorithm to integrate historical crime data and urban transitional zones for more accurate crime prediction. Time-series historical crime data were used as the primary variable, while urban transitional zones identified from the VIIRS nightlight imagery were used as the secondary co-variable. The algorithm has been applied to predict weekly-based street crime and hotspots in Cincinnati, Ohio. Statistical tests and Predictive Accuracy Index (PAI) and Predictive Efficiency Index (PEI) tests were used to validate predictions in comparison with those of the control group without using the co-variable. The validation results demonstrate that the proposed algorithm with historical crime data and urban transitional zones increased the correlation coefficient by 5.4% for weekdays and by 12.3% for weekends in statistical tests, and gained higher hit rates measured by PAI/PEI in the hotspots test. Numéro de notice : A2020-475 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1737701 date de publication en ligne : 13/03/2020 En ligne : https://doi.org/10.1080/13658816.2020.1737701 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95622 [article]

Vegetation unit assignments: phytosociology experts and classification programs show similar performance but low convergence / Lise Maciejewski in Applied Vegetation Science, vol inconnu (2020)  

Public [article]  inApplied Vegetation Science > vol inconnu (2020) Titre : Vegetation unit assignments: phytosociology experts and classification programs show similar performance but low convergence Type de document : Article/Communication Auteurs : Lise Maciejewski, Auteur ; Paulina E. Pinto, Auteur ; Stéphanie Wurpillot , Auteur ; Jacques Drapier , Auteur ; Serge Cadet, Auteur ; Serge Muller (1953-....), Auteur ; Pierre Agou, Auteur ; Benoit Renaux, Auteur ; Jean-Claude Gégout, Auteur Année de publication : 2020 Projets : 1-Pas de projet / Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] classification automatique [Termes descripteurs IGN] cohérence des données [Termes descripteurs IGN] convergence [Termes descripteurs IGN] écosystème forestier [Termes descripteurs IGN] phytosociologie [Termes descripteurs IGN] unité phytosociologique [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) Aims : Assigning vegetation plots to vegetation units is a key step in biodiversity management projects. Nevertheless, the process of plot assignment to types is usually non‐standardized, and assignment consistency remains poorly explored. To date, the efficiency of automatic classification programs has been assessed by comparing them with a unique expert judgment. Therefore, we investigated the consistency of five phytosociology expert judgments, and the consistency of these judgements with those of automatic classification programs. Location : Mainland France. Methods : We used 273 vegetation plots distributed across France and covering the diversity of the temperate and mountainous forest ecosystems of Western Europe. We asked a representative panel of five French organizations with recognized expertise in phytosociology to assign each plot to vegetation units. We provided a phytosociological classification including 228 associations, 43 alliances and eight classes. The assignments were compared among experts using an agreement ratio. We then compared the assignments suggested by three automatic classification programs with the expert judgments. Results : We observed small differences among the agreement ratios of the expert organizations; a given expert organization agreed with another one on association assignment one time in four on average, and one time in two on alliance assignment. The agreement ratios of the automatic classification programs were globally lower, but close to expert judgments. Conclusions : The results support the current trend toward unifying the existing classifications and specifying the assignment rules by creating guiding tools, which will decrease inter‐observer variation. As compared to a pool of phytosociology experts, programs perform similarly to individual experts in vegetation unit assignment, especially at the alliance level. Although programs still need to be improved, these results pave the way for the creation of habitat time series crucial for the monitoring and conservation of biodiversity. Numéro de notice : A2020-461 Affiliation des auteurs : IGN+Ext Thématique : BIODIVERSITE/FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/avsc.12516 date de publication en ligne : 12/07/2020 En ligne : https://doi.org/10.1111/avsc.12516 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95579 [article]

Volunteered geographic information research in the first decade: a narrative review of selected journal articles in GIScience / Yingwei Yan in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)  

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A regression model of spatial accuracy prediction for Openstreetmap buildings / Ibrahim Maidaneh Abdi in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-4 (August 2020)  

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Exploration of OpenStreetMap missing built-up areas using twitter hierarchical clustering and deep learning in Mozambique / Hao Li in ISPRS Journal of photogrammetry and remote sensing, vol 166 (August 2020)  

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Evaluations of the significant wave height products of HY-2B satellite radar altimeters / Yongjun Jia in Marine geodesy, Vol 43 n° 4 (July 2020)  

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Integration of spatialization and individualization: the future of epidemic modelling for communicable diseases / Meifang Li in Annals of GIS, vol 26 n° 3 (July 2020)  

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Investigating the quality of reverse geocoding services using text similarity techniques and logistic regression analysis / Batuhan Kilic in Cartography and Geographic Information Science, Vol 47 n° 4 (July 2020)  

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Mutualiser la donnée pour une information utile / Jean-Marie Séïté in Géomètre, n° 2182 (juillet - août 2020)

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ALERT: adversarial learning with expert regularization using Tikhonov operator for missing band reconstruction / Litu Rout in IEEE Transactions on geoscience and remote sensing, vol 58 n° 6 (June 2020)  

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Hétérogénéité des distances : quel impact sur la qualité des relevés lidar aériens et terrestres ? / Laurent Polidori in XYZ, n° 163 (juin 2020)

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Improved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

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