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Quantifying coherence between TDM90, SRTM90 and ASTER90 / Umut Gunes Sefercik in Geocarto international, Vol 36 n° 15 ([10/08/2021])  

Public [article]  inGeocarto international > Vol 36 n° 15 [10/08/2021] . - pp 1752 -1767 Titre : Quantifying coherence between TDM90, SRTM90 and ASTER90 Type de document : Article/Communication Auteurs : Umut Gunes Sefercik, Auteur Année de publication : 2021 Article en page(s) : pp 1752 -1767 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse comparative [Termes IGN] cohérence des données [Termes IGN] contour [Termes IGN] données topographiques [Termes IGN] MNS ASTER [Termes IGN] MNS SRTM [Termes IGN] MNS TerraSAR & TanDEM-X [Termes IGN] pente [Termes IGN] Turquie Résumé : (auteur) German Aerospace Centre released TanDEM-X 90 m (TDM90) global digital elevation model (GDEM) as freely available in October, 2018 and declared that it describes all Earth’s landmasses pole to pole with 1 m absolute height accuracy which could not been achieved by previous space-borne GDEMs. In this study, the coherence level of TDM90 with SRTM90 and ASTER90 were comprehensively analysed by visual and statistical comparison approaches in two study areas including different topographic characteristics. In visual approaches, colour-scaled coherence maps, contour maps, aspects depending on ascending and descending flying orbits and outlier illustrations were generated and interpreted. In statistical approaches, horizontal and vertical absolute and relative geolocation disparities and frequency distributions of height differences were presented. The results demonstrated that the terrain slope has a great impact on the coherence levels between TDM90 and compared GDEMs. Overall, TDM90 is more coherent with SRTM90 against ASTER90 except clear dissimilarity problems in strip border lines. Numéro de notice : A2021-591 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1659425 date de publication en ligne : 02/09/2019 En ligne : https://doi.org/10.1080/10106049.2019.1659425 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98211 [article]

Indoor mapping and modeling by parsing floor plan images / Yijie Wu in International journal of geographical information science IJGIS, vol 35 n° 6 (June 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 6 (June 2021) . - pp 1205 - 1231 Titre : Indoor mapping and modeling by parsing floor plan images Type de document : Article/Communication Auteurs : Yijie Wu, Auteur ; Jianga Shang, Auteur ; Pan Chen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1205 - 1231 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] carte d'intérieur [Termes IGN] chevauchement [Termes IGN] CityGML [Termes IGN] construction [Termes IGN] format Industry foudation classes IFC [Termes IGN] intégrité topologique [Termes IGN] mur [Termes IGN] optimisation spatiale [Termes IGN] positionnement en intérieur [Termes IGN] vectorisation Résumé : (auteur) A large proportion of indoor spatial data is generated by parsing floor plans. However, a mature and automatic solution for generating high-quality building elements (e.g., walls and doors) and space partitions (e.g., rooms) is still lacking. In this study, we present a two-stage approach to indoor mapping and modeling (IMM) from floor plan images. The first stage vectorizes the building elements on the floor plan images and the second stage repairs the topological inconsistencies between the building elements, separates indoor spaces, and generates indoor maps and models. To reduce the shape complexity of indoor boundary elements, i.e., walls and openings, we harness the regularity of the boundary elements and extract them as rectangles in the first stage. Furthermore, to resolve the overlaps and gaps of the vectorized results, we propose an optimization model that adjusts the rectangle vertex coordinates to conform to the topological constraints. Experiments demonstrate that our approach achieves a considerable improvement in room detection without conforming to Manhattan World Assumption. Our approach also outputs instance-separate walls with consistent topology, which enables direct modeling into Industry Foundation Classes (IFC) or City Geography Markup Language (CityGML). Numéro de notice : A2021-385 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1781130 date de publication en ligne : 08/07/2020 En ligne : https://doi.org/10.1080/13658816.2020.1781130 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97642 [article]

Vegetation unit assignments: phytosociology experts and classification programs show similar performance but low convergence / Lise Maciejewski in Applied Vegetation Science, vol 23 n° 4 (October 2020)  

Public [article]  inApplied Vegetation Science > vol 23 n° 4 (October 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 IGN] classification automatique [Termes IGN] cohérence des données [Termes IGN] convergence [Termes IGN] écosystème forestier [Termes IGN] phytosociologie [Termes 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 (2012-2019) 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]

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)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 6 (June 2020) Titre : ALERT: adversarial learning with expert regularization using Tikhonov operator for missing band reconstruction Type de document : Article/Communication Auteurs : Litu Rout, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage automatique [Termes IGN] apprentissage dirigé [Termes IGN] bande spectrale [Termes IGN] cohérence géométrique [Termes IGN] correction d'image [Termes IGN] dégradation d'image [Termes IGN] pollution acoustique [Termes IGN] qualité d'image [Termes IGN] reconstruction [Termes IGN] régularisation de Tychonoff Résumé : (auteur) The Earth observation using remote sensing is one of the most important technologies to assimilate key attributes about the Earth’s surface. To achieve tangible consequence, the internal building blocks of such a complex system must operate flawlessly. However, due to a dynamically changing environment, degradation in sensor electronics, and extreme weather condition remotely sensed images often miss essential information. As the sensors operate over several years in space the likelihood of sensor degradation persists. This results in commonly observed issues, such as stripe noise, missing partial data, and missing band. Various ground-based solutions have been developed to address these technological bottlenecks individually. In this article, we devise a method, which we call ALERT, to tackle missing band reconstruction. The proposed method reconstructs the missing band with the sole supervision of spectral and spatial priors. We compare the proposed framework with state-of-the-art methods and show compelling improvement both qualitatively and quantitatively. We provide both theoretical and empirical evidence of better performance by regularized adversarial learning as compared to complete supervision. Furthermore, we propose a new residual-dense-block (RDB) module to preserve geometric fidelity and assist in efficient gradient flow. We show that ALERT captures essential features such that the spatial and spectral characteristics of the reconstructed band remains preserved. To critically analyze the generalization we test the performance on two different satellite data sets: Resourcesat-2A and WorldView-2. As per our extensive experimentation, the proposed method achieves 20.72%, 13.81%, 1.05%, 15.91%, and 2.94% improvement in the root mean square error (RMSE), SAM, SSIM, PSNR, and SRE, respectively, over the state-of-the-art model. Numéro de notice : A2020-285 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2963818 date de publication en ligne : 16/01/2020 En ligne : https://doi.org/10.1109/TGRS.2019.2963818 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95108 [article]

A probabilistic framework for improving reverse geocoding output / Zhengcong Yin in Transactions in GIS, Vol 24 n° 3 (June 2020)  

Public [article]  inTransactions in GIS > Vol 24 n° 3 (June 2020) . - pp 656 - 680 Titre : A probabilistic framework for improving reverse geocoding output Type de document : Article/Communication Auteurs : Zhengcong Yin, Auteur ; Daniel W. Goldberg, Auteur ; Tracy A. Hammond, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 656 - 680 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] coordonnées GPS [Termes IGN] géocodage inverse [Termes IGN] géolocalisation [Termes IGN] intégrité topologique [Termes IGN] modèle stochastique Résumé : (auteur) Reverse geocoding, which transforms machine‐readable GPS coordinates into human‐readable location information, is widely used in a variety of location‐based services and analysis. The output quality of reverse geocoding is critical because it can greatly impact these services provided to end‐users. We argue that the output of reverse geocoding should be spatially close to and topologically correct with respect to the input coordinates, contain multiple suggestions ranked by a uniform standard, and incorporate GPS uncertainties. However, existing reverse geocoding systems often fail to fulfill these aims. To further improve the reverse geocoding process, we propose a probabilistic framework that includes: (1) a new workflow that can adapt all existing address models and unitizes distance and topology relations among retrieved reference data for candidate selections; (2) an advanced scoring mechanism that quantifies characteristics of the entire workflow and orders candidates according to their likelihood of being the best candidate; and (3) a novel algorithm that derives statistical surfaces for input GPS uncertainties and propagates such uncertainties into final output lists. The efficiency of the proposed approaches is demonstrated through comparisons to the four commercial reverse geocoding systems and through human judgments. We envision that more advanced reverse geocoding output ranking algorithms specific to different application scenarios can be built upon this work. Numéro de notice : A2020-444 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12623 date de publication en ligne : 08/05/2020 En ligne : https://doi.org/10.1111/tgis.12623 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95507 [article]

Extending Processing Toolbox for assessing the logical consistency of OpenStreetMap data / Sukhjit Singh Sehra in Transactions in GIS, Vol 24 n° 1 (February 2020)  

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Visual analysis of inconsistencies in hydraulic simulation data / Octave Perrin (2020)  

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Consistency and analysis of ionospheric observables obtained from three precise point positioning models / Yan Xiang in Journal of geodesy, vol 93 n° 8 (August 2019)  

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On the detectability of mis-modeled biases in the network-derived positioning corrections and their user impact / Amir Khodabandeh in GPS solutions, vol 23 n° 3 (July 2019)  

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A topographically preserved road‐network tile model and optimal routing method for virtual globes / Quanhua Dong in Transactions in GIS, vol 23 n° 2 (April 2019)  

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Complete 3D scene parsing from an RGBD image / Chuhang Zou in International journal of computer vision, vol 127 n° 2 (February 2019)  

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Data linking by indirect spatial referencing systems, [report of] EuroSDR - EuroGeographics seminar, September 5th - 6th, 2018 - Paris, France / Bénédicte Bucher (2019)  

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Joint analysis of SAR and optical satellite images time series for grassland event detection / Anatol Garioud (2019)

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Potential of Sentinel-1 data for monitoring temperate mixed forest phenology / Pierre-Louis Frison in Remote sensing, vol 10 n° 12 (December 2018)  

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Road safety evaluation through automatic extraction of road horizontal alignments from Mobile LiDAR System and inductive reasoning based on a decision tree / José Antonio Martin-Jimenez in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

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