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Decision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping / Jiadi Yin in Remote sensing, vol 13 n° 8 (April-2 2021)
[article]
Titre : Decision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping Type de document : Article/Communication Auteurs : Jiadi Yin, Auteur ; Ping Fu, Auteur ; Nicholas A.S. Hamm, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 1579 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte d'utilisation du sol
[Termes IGN] cartographie urbaine
[Termes IGN] Chine
[Termes IGN] données massives
[Termes IGN] image Sentinel-MSI
[Termes IGN] intégration de données
[Termes IGN] OpenStreetMap
[Termes IGN] point d'intérêt
[Termes IGN] zone urbaineRésumé : (auteur) Information about urban land use is important for urban planning and sustainable development. The emergence of geospatial big data (GBD), increased the availability of remotely sensed (RS) data and the development of new methods for data integration to provide new opportunities for mapping types of urban land use. However, the modes of RS and GBD integration are diverse due to the differences in data, study areas, classifiers, etc. In this context, this study aims to summarize the main methods of data integration and evaluate them via a case study of urban land use mapping in Hangzhou, China. We first categorized the RS and GBD integration methods into decision-level integration (DI) and feature-level integration (FI) and analyzed their main differences by reviewing the existing literature. The two methods were then applied for mapping urban land use types in Hangzhou city, based on urban parcels derived from the OpenStreetMap (OSM) road network, 10 m Sentinel-2A images, and points of interest (POI). The corresponding classification results were validated quantitatively and qualitatively using the same testing dataset. Finally, we illustrated the advantages and disadvantages of both approaches via bibliographic evidence and quantitative analysis. The results showed that: (1) The visual comparison indicates a generally better performance of DI-based classification than FI-based classification; (2) DI-based urban land use mapping is easy to implement, while FI-based land use mapping enables the mixture of features; (3) DI-based and FI-based methods can be used together to improve urban land use mapping, as they have different performances when classifying different types of land use. This study provides an improved understanding of urban land use mapping in terms of the RS and GBD integration strategy. Numéro de notice : A2021-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13081579 Date de publication en ligne : 19/04/2021 En ligne : https://doi.org/10.3390/rs13081579 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97634
in Remote sensing > vol 13 n° 8 (April-2 2021) . - n° 1579[article]1996–2017 GPS position time series, velocities and quality measures for the CORS Network / Jarir Saleh in Journal of applied geodesy, vol 15 n° 2 (April 2021)
[article]
Titre : 1996–2017 GPS position time series, velocities and quality measures for the CORS Network Type de document : Article/Communication Auteurs : Jarir Saleh, Auteur ; Sungpil Yoon, Auteur ; Kevin Choi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 105 - 115 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] Continuously Operating Reference Station network
[Termes IGN] données GPS
[Termes IGN] données localisées des bénévoles
[Termes IGN] Etats-Unis
[Termes IGN] positionnement par GPS
[Termes IGN] qualité des données
[Termes IGN] série temporelle
[Termes IGN] station de référenceRésumé : (Auteur) The CORS network is a volunteer-based network of Global Positioning System reference stations located mainly in the US and its territories. We discuss the most recent comprehensive reprocessing of all GPS data collected via this network since 1996. Daily data for GPS weeks 834 through 1933 were reprocessed leading to epoch 2010.0 coordinates and velocities of 3049 stations aligned to IGS14. The updated realization of the US National Spatial Reference System derived in this work has been in use since late 2019. As a validation of the results, the derived velocity field is compared to several other solutions and to three regional geophysical and geodetic velocity models. These comparisons uncovered unstable stations which move differently than the regional kinematics around them. Once these are ignored, we estimate the horizontal and vertical stability of this updated realization to be better than ∼0.3 and ∼0.6 mm/year, respectively. We use the position residuals and estimated uncertainties from this reprocessing to derive long-term stability measures for all active stations serving longer than 3 years. These measures exposed ∼60 CORS with the poorest long-term stability, which have been consequently excluded from serving as mapping control. Numéro de notice : A2021-320 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2020-0041 Date de publication en ligne : 15/01/2021 En ligne : https://doi.org/10.1515/jag-2020-0041 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97476
in Journal of applied geodesy > vol 15 n° 2 (April 2021) . - pp 105 - 115[article]An iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects / Linyuan Li in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)
[article]
Titre : An iterative-mode scan design of terrestrial laser scanning in forests for minimizing occlusion effects Type de document : Article/Communication Auteurs : Linyuan Li, Auteur ; Xihan Mu, Auteur ; Maxime Soma, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 3547 - 3566 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] détection de partie cachée
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] itération
[Termes IGN] semis de pointsRésumé : (auteur) Occlusion effect, an inherent problem of terrestrial laser scanning (TLS) measurements, limits the potential of TLS data in tree attribute estimation. Multiple scans seek to mitigate this effect to provide enhanced scan completeness. However, the numbers and locations of the scans (i.e., the scan design) are usually determined via a subjective assessment of the tree density, spatial patterns of trees, and attributes to be derived. These could cause suboptimal scan completeness and limit tree attribute estimation. This study proposed an iterative-mode scan design to minimize the occlusion effect. First, we introduced a PoTo index based on visibility analysis to evaluate how many trees can be scanned from a location and to select effective candidates for the optimal TLS location. Second, we introduced a cumulative degree of ring closure (CDRC) to quantify the scan completeness for each candidate and determine the optimal TLS location. The TLS data sets of virtual forests with field-measured and synthetic plot parameter settings were simulated according to iterative- and regular-mode designs by using a Heidelberg light detection and ranging (LiDAR) Operations Simulator (HELIOS). The results demonstrated that an iterative-mode design can improve the scan completeness of trees compared to the regular-mode design. The tree attribute (diameter at breast height (DBH), tree height, stem curve, and crown volume) estimates of the iterative-mode design were less erroneous than those of the regular-mode design (e.g., the root-mean-square error (RMSE) could decrease the stem curve estimation by 38% and the crown volume estimation by 15%). This study suggests that the iterative-mode design can obtain an improved quality of the TLS data, especially for dense stands. Numéro de notice : A2021-288 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3018643 Date de publication en ligne : 10/09/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3018643 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97397
in IEEE Transactions on geoscience and remote sensing > vol 59 n° 4 (April 2021) . - pp 3547 - 3566[article]Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours / Amir Hossein Safaie in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)
[article]
Titre : Automated street tree inventory using mobile LiDAR point clouds based on Hough transform and active contours Type de document : Article/Communication Auteurs : Amir Hossein Safaie, Auteur ; Heidar Rastiveis, Auteur ; Alireza Shams, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 19 - 34 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre remarquable
[Termes IGN] arbre urbain
[Termes IGN] détection d'arbres
[Termes IGN] détection de contours
[Termes IGN] diagramme de Voronoï
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] sécurité routière
[Termes IGN] semis de points
[Termes IGN] transformation de HoughRésumé : (auteur) Trees are important road-side objects, and their geometric information plays an essential role in road studies and safety analyses. This paper proposes an efficient method for the automated creation of a road-side tree inventory using Mobile Terrestrial Lidar System (MTLS) point clouds. In the proposed method ground points are filtered through preprocessing to reduce processing time. Next, tree trunks are detected by performing a Hough Transform (HT) algorithm on several generated raster images from the point clouds. By initiating an approximate area of a tree’s foliage through a Voronoi Tessellation (VT) algorithm, the accurate boundary of the foliage is identified by applying Active Contour (AC) models. By extracting the points within this foliage boundary the geometric characteristics of each tree are obtained. This method was evaluated with two sample point clouds from different MTLS systems, and the algorithm correctly extracted all of the trees from both datasets. Additionally, comparing the calculated parameters with manually observed measures, the accuracy of the obtained geometric parameters were promising. Numéro de notice : A2021-206 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.01.026 Date de publication en ligne : 14/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.01.026 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97183
in ISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 19 - 34[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021041 SL Revue Centre de documentation Revues en salle Disponible 081-2021043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Automatic atmospheric correction for shortwave hyperspectral remote sensing data using a time-dependent deep neural network / Jian Sun in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)
[article]
Titre : Automatic atmospheric correction for shortwave hyperspectral remote sensing data using a time-dependent deep neural network Type de document : Article/Communication Auteurs : Jian Sun, Auteur ; Fangcao Xu, Auteur ; Guido Cervone, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 117 - 131 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] correction atmosphérique
[Termes IGN] détection de cible
[Termes IGN] image hyperspectrale
[Termes IGN] modèle de transfert radiatif
[Termes IGN] rayonnement solaire
[Termes IGN] réflectivitéRésumé : (auteur) Atmospheric correction is an essential step in hyperspectral imaging and target detection from spectrometer remote sensing data. State-of-the-art atmospheric correction approaches either require extensive filed experiments or prior knowledge of atmospheric characteristics to improve the predicted accuracy, which are computational expensive and unsuitable for real time application. To take full advantages of remote sensing observation in quickly and reliably acquiring data for a large area, an automatic and efficient processing tool is required for atmospheric correction. In this paper, we propose a time-dependent neural network for automatic atmospheric correction and target detection using multi-scan hyperspectral data under different elevation angles. In addition to the total radiance, the collection day and time are also incorporated to improve the time-dependency of the network and represent the seasonal and diurnal characteristics of atmosphere and solar radiation. Results show that the proposed network has the capacity to accurately provide atmospheric characteristics and estimate precise reflectivity spectra with 95,72% averaged accuracy for different materials, including vegetation, sea ice, and ocean. Additional experiments are designed to investigate the network’s temporal dependency and performance on missing data. The error analysis confirms that our proposed network is capable of estimating atmospheric characteristics under both seasonally and diurnally varying environments and handling the influence of missing data. Both the predicted results and error analysis are promising and demonstrate that our network has the ability of providing accurate atmospheric correction and target detection in real time. Numéro de notice : A2021-208 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.02.007 Date de publication en ligne : 24/02/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.02.007 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97186
in ISPRS Journal of photogrammetry and remote sensing > vol 174 (April 2021) . - pp 117 - 131[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021041 SL Revue Centre de documentation Revues en salle Disponible 081-2021043 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021042 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt A BiLSTM-CNN model for predicting users’ next locations based on geotagged social media / Yi Bao in International journal of geographical information science IJGIS, vol 35 n° 4 (April 2021)PermalinkChemical interaction between Quercus pubescens and its companion species is not emphasized under drought stress / H. Hashoum in European Journal of Forest Research, vol 140 n° 2 (April 2021)PermalinkA CNN approach to simultaneously count plants and detect plantation-rows from UAV imagery / Lucas Prado Osco in ISPRS Journal of photogrammetry and remote sensing, vol 174 (April 2021)PermalinkDetecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network / Nantheera Anantrasirichai in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkEvolution of the beaches in the regional Park of Salinas and Arenales of San Pedro del Pinatar (Southeast of Spain) (1899–2019) / Daniel Ibarra-Marinas in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)PermalinkGraph convolutional networks by architecture search for PolSAR image classification / Hongying Liu in Remote sensing, vol 13 n° 7 (April-1 2021)PermalinkMulti-GNSS real-time precise clock estimation considering the correction of inter-satellite code biases / Liang Chen in GPS solutions, vol 25 n° 2 (April 2021)PermalinkA novel class-specific object-based method for urban change detection using high-resolution remote sensing imagery / Ting Bai in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 4 (April 2021)PermalinkRotation-invariant feature learning in VHR optical remote sensing images via nested siamese structure with double center loss / Ruoqiao Jiang in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)PermalinkScene classification of remotely sensed images via densely connected convolutional neural networks and an ensemble classifier / Qimin Cheng in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 4 (April 2021)Permalink