Centre de documentation
scientifique

Rapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning / Xin Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 178 (August 2021) . - pp 36 - 50 Titre : Rapid and large-scale mapping of flood inundation via integrating spaceborne synthetic aperture radar imagery with unsupervised deep learning Type de document : Article/Communication Auteurs : Xin Jiang, Auteur ; Shijing Liang, Auteur ; Xinyue He, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 36 - 50 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] apprentissage non-dirigé [Termes IGN] apprentissage profond [Termes IGN] cartographie des risques [Termes IGN] chaîne de traitement [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] Fleuve bleu (Chine) [Termes IGN] Google Earth Engine [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] inondation [Termes IGN] modèle numérique de surface [Termes IGN] segmentation d'image [Termes IGN] superpixel [Termes IGN] surveillance hydrologique Résumé : (auteur) Synthetic aperture radar (SAR) has great potential for timely monitoring of flood information as it penetrates the clouds during flood events. Moreover, the proliferation of SAR satellites with high spatial and temporal resolution provides a tremendous opportunity to understand the flood risk and its quick response. However, traditional algorithms to extract flood inundation using SAR often require manual parameter tuning or data annotation, which presents a challenge for the rapid automated mapping of large and complex flooded scenarios. To address this issue, we proposed a segmentation algorithm for automatic flood mapping in near-real-time over vast areas and for all-weather conditions by integrating Sentinel-1 SAR imagery with an unsupervised machine learning approach named Felz-CNN. The algorithm consists of three phases: (i) super-pixel generation; (ii) convolutional neural network-based featurization; (iii) super-pixel aggregation. We evaluated the Felz-CNN algorithm by mapping flood inundation during the Yangtze River flood in 2020, covering a total study area of 1,140,300 km2. When validated on fine-resolution Planet satellite imagery, the algorithm accurately identified flood extent with producer and user accuracy of 93% and 94%, respectively. The results are indicative of the usefulness of our unsupervised approach for the application of flood mapping. Meanwhile, we overlapped the post-disaster inundation map with a 10-m resolution global land cover map (FROM-GLC10) to assess the damages to different land cover types. Of these types, cropland and residential settlements were most severely affected, with inundation areas of 9,430.36 km2 and 1,397.50 km2, respectively, results that are in agreement with statistics from relevant agencies. Compared with traditional supervised classification algorithms that require time-consuming data annotation, our unsupervised algorithm can be deployed directly to high-performance computing platforms such as Google Earth Engine and PIE-Engine to generate a large-spatial map of flood-affected areas within minutes, without time-consuming data downloading and processing. Importantly, this efficiency enables the fast and effective monitoring of flood conditions to aid in disaster governance and mitigation globally. Numéro de notice : A2021-560 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.05.019 Date de publication en ligne : 09/06/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.05.019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98118 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2021081	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2021083	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2021082	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Applying planetary mapping methods to submarine environments: onshore-offshore geomorphology of Christiana-Santorini-Kolumbo Volcanic Group, Greece / Alexandra E. Huff in Journal of maps, vol 17 n° 3 (July 2021)  

Public [article]  inJournal of maps > vol 17 n° 3 (July 2021) . - pp 111 - 121 Titre : Applying planetary mapping methods to submarine environments: onshore-offshore geomorphology of Christiana-Santorini-Kolumbo Volcanic Group, Greece Type de document : Article/Communication Auteurs : Alexandra E. Huff, Auteur ; Paraskevi Nomikou, Auteur ; Lisa A. Thompson, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 111 - 121 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique [Termes IGN] 1:100.000 [Termes IGN] carte bathymétrique [Termes IGN] carte géologique [Termes IGN] Grèce [Termes IGN] prévention des risques [Termes IGN] relief sous-marin [Termes IGN] surveillance géologique [Termes IGN] système d'information géographique [Termes IGN] volcan Résumé : (auteur) Geologic maps are foundational products for natural hazard assessments but developing them for submarine areas is challenging due to a lack of physical access to the study area. In response, submarine geomorphologic maps are used to provide geologic context and spatial information on landforms and related geo-hazards for risk management. These maps are generated from remotely sensed data, e.g. digital elevation models (DEMs), which introduce unique hurdles to submarine mapping. To address this issue, we produced a workflow for applying planetary geologic mapping methods to submarine data. Using this, we created an onshore-offshore geomorphologic map of the Christiana-Santorini-Kolumbo Volcanic Group, Greece. This product can be used to enhance hazard assessments on Santorini, which is a tourist hot-spot at high risk for volcanically- and seismically-induced hazards. We present this workflow as a tool for generating uniform geomorphologic map products that will aid natural hazard assessments of submarine environments. Numéro de notice : A2021-694 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2021.1880980 Date de publication en ligne : 02/03/2021 En ligne : https://doi.org/10.1080/17445647.2021.1880980 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98557 [article]

Design and development 3D RRR model for Turkish cadastral system using international standards / Mehmet Alkan in Survey review, Vol 53 n° 379 (July 2021)  

Public [article]  inSurvey review > Vol 53 n° 379 (July 2021) . - pp 312 - 324 Titre : Design and development 3D RRR model for Turkish cadastral system using international standards Type de document : Article/Communication Auteurs : Mehmet Alkan, Auteur ; Hicret Gürsoy Sürmeneli, Auteur ; Zeynel Abidin Polat, Auteur Année de publication : 2021 Article en page(s) : pp 312 - 324 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cadastre étranger [Termes IGN] base de données foncières [Termes IGN] cadastre 3D [Termes IGN] infrastructure nationale des données localisées [Termes IGN] INSPIRE [Termes IGN] norme ISO [Termes IGN] standard OGC [Termes IGN] Turquie Résumé : (auteur) The concepts of three-dimensional cadastre (3D) and property ownership led to increased interest in land use management and research towards the end of the 90s. Within the scope of these studies, international standards and definitions have been realised. In Turkey, there are some academic studies available. However, there are not many studies conducted on an institutional basis. Turkey cadastre carried out by the General Directorate of Land Registry, and Cadastre (GDLRC) are kept. In this context, a 3D RRR (Right, Restriction and Responsibility) for Turkey-based cadastral data model design and development is essential in terms of not constitute a base for the study. The fact that these studies are in the context of LADM and ISO standards and OGC is very important in terms of the fact that the cadastral system is related to international standards. Numéro de notice : A2021-521 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2020.1758386 Date de publication en ligne : 12/05/2020 En ligne : https://doi.org/10.1080/00396265.2020.1758386 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97954 [article]

Detecting high-temperature anomalies from Sentinel-2 MSI images / Yongxue Liu in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 177 (July 2021) . - pp 174 - 193 Titre : Detecting high-temperature anomalies from Sentinel-2 MSI images Type de document : Article/Communication Auteurs : Yongxue Liu, Auteur ; Zhi Weifeng, Auteur ; Bihua Xu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 174 - 193 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] anomalie thermique [Termes IGN] éruption volcanique [Termes IGN] image aérienne [Termes IGN] image Landsat-OLI [Termes IGN] image proche infrarouge [Termes IGN] image Sentinel-MSI [Termes IGN] image thermique [Termes IGN] incendie [Termes IGN] réflectance spectrale [Termes IGN] risque technologique [Termes IGN] série temporelle [Termes IGN] température au sol Résumé : (Auteur) High-temperature anomalies (HTAs) of the earth's surface, such as fires, volcanic activities, and industrial heat sources, have a profound impact on Earth's system. Sentinel-2 Multispectral Instrument (MSI) provides spatially-specific information for precisely measuring the location and extent of HTAs at a fine scale. However, detecting HTAs from MSI images remains challenging because the emitted radiance of an HTA in the short-wave infrared (SWIR) bands can be easily mixed with the reflected solar radiance background in the daytime; and an increasing number of atypical cases in MSI images need to be treated with the enhanced spatial resolution. A generic HTA detection approach that handles both anthropogenic and natural HTAs will broaden the scope of MSI applications. In this study, (i) we highlight two spectral characteristics of HTAs in the far-SWIR, near-SWIR, and NIR bands (i.e., (ρfar-SWIR - ρnear-SWIR)/ρNIR ≥ 0.45 and (ρfar-SWIR -ρnear-SWIR) ≥ ρnear-SWIR - ρNIR) that can effectively enhance HTAs from background geo-features, based on the reflectance spectra in airborne imaging spectrometer data. (ii) We propose a tri-spectral thermal anomaly index (TAI) that jointly uses the two high-temperature-sensitive SWIR bands and the high-temperature-insensitive NIR band to enhance HTAs, based on the above characteristics and a comprehensive sampling of different types of HTAs from 1,974 MSI images. (iii) We develop a TAI-based approach for MSI images to detect HTAs in general. The proposed approach was applied to detect different types of HTAs, including different biomass burnings, active volcanoes, and industrial HTAs, over a wide range of land-cover scenarios. Validations and comparisons demonstrate the proposed approach is reliable and performs better than the existing state-of-the-art HTA detection approaches. Evaluations on two types of small industrial HTAs, including operating kilns and enclosed landfill gas flares, show that the HTA detection probability of the TAI-based approach from time-series MSI images is ~ 84.91% and 88.23%, respectively. Further investigations show that the TAI-based approach also has good transferability in detecting HTAs from multispectral images acquired by Landsat-family satellites. Numéro de notice : A2021-372 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.05.008 Date de publication en ligne : 23/05/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.05.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97808 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2021071	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2021073	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2021072	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Digital camera calibration for cultural heritage documentation: the case study of a mass digitization project of religious monuments in Cyprus / Evagoras Evagorou in European journal of remote sensing, vol 54 sup 1 (2021)  

Public [article]  inEuropean journal of remote sensing > vol 54 sup 1 (2021) . - pp 6 - 17 Titre : Digital camera calibration for cultural heritage documentation: the case study of a mass digitization project of religious monuments in Cyprus Type de document : Article/Communication Auteurs : Evagoras Evagorou, Auteur ; Christodoulos Mettas, Auteur ; Athos Agapiou, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 6 - 17 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] Agisoft Photoscan [Termes IGN] auto-étalonnage [Termes IGN] Chypre [Termes IGN] distorsion d'image [Termes IGN] données massives [Termes IGN] édifice religieux [Termes IGN] étalonnage d'instrument [Termes IGN] patrimoine culturel [Termes IGN] point d'appui [Termes IGN] texture d'image [Termes IGN] vision par ordinateur [Termes IGN] visualisation 3D Résumé : (auteur) The paper summarizes the methodology followed, to evaluate the accuracy of different digitization methods of ecclesiastical monuments in 3D computer vision form and stresses the importance of photographic equipment calibration. In this study, a set of images were taken using the CANON EOS M5 digital camera, while the internal calibration parameters – horizontal and vertical focal length (fx, fy), principal point coordinates (x0, y0), radial distortion coefficients (K1, K2, K3), tangential distortion coefficients (P1, P2) and the affinity and the shear terms (b1, b2) were estimated. These parameters were calculated using different software applications and then analyzed. For the calibration procedure, 3D texture models were built with the Agisoft commercial software based on: (a) the aforementioned calibration parameters and (b) the self-calibration process. The overall accuracy (Root Mean Square – RMS) between these models, by comparing known geo-referenced ground-control-points (GCP) is presented through the Cloud Compare software. The results indicate that the internal calibration parameters of the digital camera used for documentation purposes are essential and should be systematically implemented for documentation purposes. Numéro de notice : A2021-816 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Atlas DOI : 10.1080/22797254.2020.1810131 Date de publication en ligne : 02/09/2020 En ligne : https://doi.org/10.1080/22797254.2020.1810131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98902 [article]

Dynamique contrastée de la compaction d’un ferralsol après une défriche mécanisée alternative en Guyane française / Xavier Guerrini in Bois et forêts des tropiques, n° 348 ([01/07/2021])  

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Feux de forêts et technologies spatiales / Laurent Polidori in Géomètre, n° 2193 (juillet-août 2021)

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Flood depth mapping in street photos with image processing and deep neural networks / Bahareh Alizadeh Kharazi in Computers, Environment and Urban Systems, vol 88 (July 2021)  

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Identifying home locations in human mobility data: an open-source R package for comparison and reproducibility / Qingqing Chen in International journal of geographical information science IJGIS, vol 35 n° 7 (July 2021)  

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Layout graph model for semantic façade reconstruction using laser point clouds / Hongchao Fan in Geo-spatial Information Science, vol 24 n° 3 (July 2021)  

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Machine learning for inference: using gradient boosting decision tree to assess non-linear effects of bus rapid transit on house prices / Linchuan Yang in Annals of GIS, vol 27 n° 3 (July 2021)  

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Multi-scale coal fire detection based on an improved active contour model from Landsat-8 satellite and UAV images / Yanyan Gao in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)  

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SemiCDNet: A semisupervised convolutional neural network for change detection in high resolution remote-sensing images / Daifeng Peng in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)  

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The spread of the Mercator projection in Western European and United States cartography / Michele Abee in Cartographica, vol 56 n° 2 (Summer 2021)  

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Using machine learning to map Western Australian landscapes for mineral exploration / Thomas Albrecht in ISPRS International journal of geo-information, vol 10 n° 7 (July 2021)  

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