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A combination of convolutional and graph neural networks for regularized road surface extraction / Jingjing Yan in IEEE Transactions on geoscience and remote sensing, vol 60 n° 2 (February 2022)
[article]
Titre : A combination of convolutional and graph neural networks for regularized road surface extraction Type de document : Article/Communication Auteurs : Jingjing Yan, Auteur ; Shunping Ji, Auteur ; Yao Wei, Auteur Année de publication : 2022 Article en page(s) : n° 4409113 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Bavière (Allemagne)
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection de contours
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] extraction du réseau routier
[Termes IGN] image aérienne
[Termes IGN] jeu de données
[Termes IGN] optimisation (mathématiques)
[Termes IGN] régression
[Termes IGN] réseau neuronal de graphes
[Termes IGN] Wuhan (Chine)Résumé : (auteur) Road surface extraction from high-resolution remote sensing images has many engineering applications; however, extracting regularized and smooth road surface maps that reach the human delineation level is a very challenging task, and substantial and time-consuming manual work is usually unavoidable. In this article, to solve this problem, we propose a novel regularized road surface extraction framework by introducing a graph neural network (GNN) for processing the road graph that is preconstructed from the easily accessible road centerlines. The proposed framework formulates the road surface extraction problem as two-sided width inference of the road graph and consists of a convolutional neural network (CNN)-based feature extractor and a GNN model for vertex attribute adjustment. The CNN extracts the high-level abstract features of each vertex in the graph as the input of the GNN and also the road boundary features that allow us to distinguish roads from the background. The GNN propagates and aggregates the features of the vertices in the graph to achieve global optimization of the regression of the regularized widths of the vertices. At the same time, a biased centerline map can also be corrected based on the width prediction result. To the best of the authors’ knowledge, this is the first study to have introduced a GNN to regularized human-level road surface extraction. The proposed method was evaluated on four diverse datasets, and the results show that the proposed method comprehensively outperforms the recent CNN-based segmentation methods and other regularization methods in the intersection over union (IoU) and smoothness score, and a visual check shows that a majority of the prediction results of the proposed method approach the human delineation level. Numéro de notice : A2022-297 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2022.3151688 Date de publication en ligne : 15/02/2022 En ligne : https://doi.org/10.1109/TGRS.2022.3151688 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100355
in IEEE Transactions on geoscience and remote sensing > vol 60 n° 2 (February 2022) . - n° 4409113[article]Spatiotemporal fusion modelling using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria / Maninder Singh Dhillon in Remote sensing, vol 14 n° 3 (February-1 2022)
[article]
Titre : Spatiotemporal fusion modelling using STARFM: Examples of Landsat 8 and Sentinel-2 NDVI in Bavaria Type de document : Article/Communication Auteurs : Maninder Singh Dhillon, Auteur ; Thorsten Dahms, Auteur ; Carina Kübert-Flock, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 677 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Bavière (Allemagne)
[Termes IGN] carte d'occupation du sol
[Termes IGN] fusion de données
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] réflectance
[Termes IGN] surveillance de la végétation
[Termes IGN] utilisation du solRésumé : (auteur) The increasing availability and variety of global satellite products provide a new level of data with different spatial, temporal, and spectral resolutions; however, identifying the most suited resolution for a specific application consumes increasingly more time and computation effort. The region’s cloud coverage additionally influences the choice of the best trade-off between spatial and temporal resolution, and different pixel sizes of remote sensing (RS) data may hinder the accurate monitoring of different land cover (LC) classes such as agriculture, forest, grassland, water, urban, and natural-seminatural. To investigate the importance of RS data for these LC classes, the present study fuses NDVIs of two high spatial resolution data (high pair) (Landsat (30 m, 16 days; L) and Sentinel-2 (10 m, 5–6 days; S), with four low spatial resolution data (low pair) (MOD13Q1 (250 m, 16 days), MCD43A4 (500 m, one day), MOD09GQ (250 m, one-day), and MOD09Q1 (250 m, eight day)) using the spatial and temporal adaptive reflectance fusion model (STARFM), which fills regions’ cloud or shadow gaps without losing spatial information. These eight synthetic NDVI STARFM products (2: high pair multiply 4: low pair) offer a spatial resolution of 10 or 30 m and temporal resolution of 1, 8, or 16 days for the entire state of Bavaria (Germany) in 2019. Due to their higher revisit frequency and more cloud and shadow-free scenes (S = 13, L = 9), Sentinel-2 (overall R2 = 0.71, and RMSE = 0.11) synthetic NDVI products provide more accurate results than Landsat (overall R2 = 0.61, and RMSE = 0.13). Likewise, for the agriculture class, synthetic products obtained using Sentinel-2 resulted in higher accuracy than Landsat except for L-MOD13Q1 (R2 = 0.62, RMSE = 0.11), resulting in similar accuracy preciseness as S-MOD13Q1 (R2 = 0.68, RMSE = 0.13). Similarly, comparing L-MOD13Q1 (R2 = 0.60, RMSE = 0.05) and S-MOD13Q1 (R2 = 0.52, RMSE = 0.09) for the forest class, the former resulted in higher accuracy and precision than the latter. Conclusively, both L-MOD13Q1 and S-MOD13Q1 are suitable for agricultural and forest monitoring; however, the spatial resolution of 30 m and low storage capacity makes L-MOD13Q1 more prominent and faster than that of S-MOD13Q1 with the 10-m spatial resolution. Numéro de notice : A2022-124 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14030677 Date de publication en ligne : 31/01/2022 En ligne : https://doi.org/10.3390/rs14030677 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99687
in Remote sensing > vol 14 n° 3 (February-1 2022) . - n° 677[article]Geospatial assessment of urban ecosystem disservices: An example of poisonous urban trees in Berlin, Germany / Peer von Döhren in Urban Forestry & Urban Greening, vol 67 (January 2022)
[article]
Titre : Geospatial assessment of urban ecosystem disservices: An example of poisonous urban trees in Berlin, Germany Type de document : Article/Communication Auteurs : Peer von Döhren, Auteur ; Dagmar Haase, Auteur Année de publication : 2022 Article en page(s) : n° 127440 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] arbre urbain
[Termes IGN] Berlin
[Termes IGN] santé
[Termes IGN] service écosystémiqueMots-clés libres : allergie poison terrain de jeu Résumé : (auteur) Urban trees play an important role in green infrastructure planning for the ecosystem services they provide. These services include carbon sequestration, the provision of clean air through oxygen production and filtering of airborne pollutants, and the offsetting of the urban heat island effect by providing shade and cooling. In addition to the well-studied positive effects of urban trees, under specific conditions, there are some unwanted side effects that need to be considered. Such negative side effects, such as allergies caused by tree pollen, traffic hazards from falling trees or tree parts or damage from roots or branches in resource supply or waste disposal infrastructures, are termed ecosystem disservices. An ecosystem disservice that is not very often illuminated in the urban context is the presence of poisonous urban trees. This paper provides a spatially explicit view of the distribution of poisonous urban trees in the city of Berlin, relating the spatial distribution of the hazard from this urban ecosystem disservice with the conditions under which it can have the most damaging effect by considering nearby playgrounds and areas with a high population density of children under 5 years old, the most vulnerable group within the urban population. Numéro de notice : A2022-317 Affiliation des auteurs : non IGN Thématique : FORET/URBANISME Nature : Article DOI : 10.1016/j.ufug.2021.127440 En ligne : https://doi.org/10.1016/j.ufug.2021.127440 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100422
in Urban Forestry & Urban Greening > vol 67 (January 2022) . - n° 127440[article]Jahresbericht 2021 des Bundesamtes für Kartographie und Geodäsie / Bundesamt für Kartographie und Geodäsie (2022)
Titre : Jahresbericht 2021 des Bundesamtes für Kartographie und Geodäsie Titre original : Annual report 2021 Federal Agency for Cartography and Geodesy Type de document : Rapport Auteurs : Bundesamt für Kartographie und Geodäsie, Auteur Editeur : Francfort sur le Main : Bundesamt für Kartographie und Geodäsie Année de publication : 2022 Importance : 22 p. Format : 21 x 30 cm Langues : Allemand (ger) Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie
[Termes IGN] activité cartographique
[Termes IGN] activité géodésique
[Termes IGN] Allemagne
[Termes IGN] base de données localisées
[Termes IGN] géomatique
[Termes IGN] système de référence localNote de contenu : 1 Looking back: This was BKG´s year 2021
2 From the coast to the Alps: GNSS measurement campaign
3 The weather in space
4 Observing sea level in North Sea and Baltic Sea
5 The digital twin: all of Germany in 3D
6 Satellite data and images for federal institutionsNuméro de notice : 17744 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Rapport d'activité DOI : sans En ligne : https://sg.geodatenzentrum.de/web_public/gdz/schriften/BKG-Jahresbericht-2021.pd [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103113 Documents numériques
en open access
rapport 2021 - pdf éditeurAdobe Acrobat PDF Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany / Omar Seleem in Geomatics, Natural Hazards and Risk, vol 13 (2022)
[article]
Titre : Towards urban flood susceptibility mapping using data-driven models in Berlin, Germany Type de document : Article/Communication Auteurs : Omar Seleem, Auteur ; Georgy Ayzel, Auteur Année de publication : 2022 Article en page(s) : pp 1640 - 1662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Berlin
[Termes IGN] cartographie des risques
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] inondation
[Termes IGN] pouvoir de résolution géométrique
[Termes IGN] vulnérabilitéRésumé : (auteur) Identifying urban pluvial flood-prone areas is necessary but the application of two-dimensional hydrodynamic models is limited to small areas. Data-driven models have been showing their ability to map flood susceptibility but their application in urban pluvial flooding is still rare. A flood inventory (4333 flooded locations) and 11 factors which potentially indicate an increased hazard for pluvial flooding were used to implement convolutional neural network (CNN), artificial neural network (ANN), random forest (RF) and support vector machine (SVM) to: (1) Map flood susceptibility in Berlin at 30, 10, 5, and 2 m spatial resolutions. (2) Evaluate the trained models' transferability in space. (3) Estimate the most useful factors for flood susceptibility mapping. The models' performance was validated using the Kappa, and the area under the receiver operating characteristic curve (AUC). The results indicated that all models perform very well (minimum AUC = 0.87 for the testing dataset). The RF models outperformed all other models at all spatial resolutions and the RF model at 2 m spatial resolution was superior for the present flood inventory and predictor variables. The majority of the models had a moderate performance for predictions outside the training area based on Kappa evaluation (minimum AUC = 0.8). Aspect and altitude were the most influencing factors on the image-based and point-based models respectively. Data-driven models can be a reliable tool for urban pluvial flood susceptibility mapping wherever a reliable flood inventory is available. Numéro de notice : A2022-457 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/19475705.2022.2097131 Date de publication en ligne : 12/07/2022 En ligne : https://doi.org/10.1080/19475705.2022.2097131 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101257
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 1640 - 1662[article]Vegetation changes in the understory of nitrogen-sensitive temperate forests over the past 70 years / Marina Roth in Forest ecology and management, vol 503 (January-1 2022)PermalinkThe efficiency of retention measures in continuous-cover forestry for conserving epiphytic cryptogams: A case study on Abies alba / Stefan Kaufmann in Forest ecology and management, vol 502 (December-15 2021)PermalinkEarly detection of spruce vitality loss with hyperspectral data: Results of an experimental study in Bavaria, Germany / Kathrin Einzmann in Remote sensing of environment, vol 266 (December 2021)PermalinkGenetic diversity of seeds from four German Douglas fir (Pseudotsuga menziesii) seed orchards / Birte Pakull in European Journal of Forest Research, vol 140 n° 6 (December 2021)PermalinkShining light on danger / Anonyme in GEO: Geoconnexion international, Vol 20 n° 5 (Autumn 2021)PermalinkForest inventory-based assessments of the invasion risk of Pseudotsuga menziesii (Mirb.) Franco and Quercus rubra L. in Germany / A. Bindewald in European Journal of Forest Research, vol 140 n° 4 (August 2021)PermalinkA hierarchical deep learning framework for the consistent classification of land use objects in geospatial databases / Chun Yang in ISPRS Journal of photogrammetry and remote sensing, vol 177 (July 2021)Permalink3D reconstruction of bridges from airborne laser scanning data and cadastral footprints / Steffen Goebbels in Journal of Geovisualization and Spatial Analysis, vol 5 n° 1 (June 2021)PermalinkThe social drift of trees. Consequence for growth trend detection, stand dynamics, and silviculture / Hans Pretzsch in European Journal of Forest Research, vol 140 n° 3 (June 2021)PermalinkWeak relationships of continuous forest management intensity and remotely sensed stand structural complexity in temperate mountain forests / Thomas Asbeck in European Journal of Forest Research, vol 140 n° 3 (June 2021)PermalinkDevelopment of German-Ukrainian cooperations for education and research in photogrammetry and laser scanning / Thomas Luhmann in Geo-spatial Information Science, vol 24 n° 1 (March 2021)PermalinkEuropean beech leads to more bioactive humus forms but stronger mineral soil acidification as Norway spruce and Scots pine – Results of a repeated site assessment after 63 and 82 years of forest conversion in Central Germany / Florian Achilles in Forest ecology and management, vol 483 ([01/03/2021])PermalinkGridded population mapping for Germany based on building density, height and type from Earth Observation data using census disaggregation and bottom-up estimates / Franz Schug in Plos one, vol 16 n° 3 (March 2021)PermalinkModelling potential density of natural regeneration of European oak species (Quercus robur L., Quercus petraea (Matt.) Liebl.) depending on the distance to the potential seed source: Methodological approach for modelling dispersal from inventory data at forest enterprise level / Maximilian Axer in Forest ecology and management, vol 482 ([15/02/2021])PermalinkDevelopment and analysis of land-use/land-cover spatio-temporal metrics in urban environments: Exploring urban growth patterns and linkages to socio-economic factors / Marta Sapena Moll (2021)PermalinkFrom point clouds to high-fidelity models - advanced methods for image-based 3D reconstruction / Audrey Richard (2021)PermalinkInvestigation of Sentinel-1 time series for sensitivity to fern vegetation in an European temperate forest / Marlin Mueller (2021)PermalinkJahresbericht 2020 des Bundesamtes für Kartographie und Geodäsie / Bundesamt für Kartographie und Geodäsie (2021)PermalinkPermalinkQualification des données LiDAR GEDI pour le suivi de l’impact climatique sur la forêt de Südharz / Iris Jeuffrard (2021)Permalink