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Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data / Tianyu Hu in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)
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Titre : Quantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data Type de document : Article/Communication Auteurs : Tianyu Hu, Auteur ; Dengjie Wei, Auteur ; Yanjun Su, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 203 - 214 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre urbain
[Termes IGN] canopée
[Termes IGN] Chine
[Termes IGN] couvert végétal
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image panoramique
[Termes IGN] semis de points
[Termes IGN] système de numérisation mobileRésumé : (auteur) Street trees are important components of an urban green space and understanding and measuring their ecological and cultural services is crucial for assessing the quality of streets and managing urban environments. Currently, most studies mainly focus on evaluating the ecological services of street trees by measuring the amount of greenness, but how to evaluate their aesthetic functions through quantitative measurements of street trees remain unclear. To address this problem, we propose a method to assess the aesthetic functions of street trees by quantifying the shape of greenness inspired by assessments of skyline aesthetics. Using a state-of-the-art mobile mapping system, we collected downtown-wide lidar data and panoramic images in Jinzhou City, Hebei Province, China. We developed a method for extracting the canopy line from the mobile lidar data, and then identified two basic elements, peaks and gaps, from street canopy lines and extracted six indexes (i.e., richness of peaks, evenness of peaks, frequency of peaks, total length of gaps, evenness of gaps and frequency of gaps) to describe the fluctuations and continuities of street canopy lines. We analyzed the abundance and spatial distribution of these indexes together with survey responses on the streets’ aesthetics and found that most of them were significantly correlated with human perception of streets. Compared to indexes of amount of greenness (e.g., green volume and green view index), these shape indexes have stronger influences on the physical aesthetic beauty of street trees. These findings suggest that a comprehensive assessment of the aesthetic function of street trees should consider both shape and amount of greenness. This study provides a new perspective for the assessment of urban green spaces and can assist future urban greening planning and urban landscape management. Numéro de notice : A2022-105 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2022.01.002 Date de publication en ligne : 15/01/2022 En ligne : https://doi.org/10.1016/j.isprsjprs.2022.01.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99602
in ISPRS Journal of photogrammetry and remote sensing > vol 184 (February 2022) . - pp 203 - 214[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2022021 SL Revue Centre de documentation Revues en salle Disponible 081-2022023 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2022022 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Recurrent origin–destination network for exploration of human periodic collective dynamics / Xiaojian Chen in Transactions in GIS, vol 26 n° 1 (February 2022)
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Titre : Recurrent origin–destination network for exploration of human periodic collective dynamics Type de document : Article/Communication Auteurs : Xiaojian Chen, Auteur ; Jiayi Xie, Auteur ; Changjiang Xiao, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 317 - 340 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données localisées dynamiques
[Termes IGN] flux
[Termes IGN] origine - destination
[Termes IGN] planification urbaine
[Termes IGN] réseau neuronal récurrent
[Termes IGN] série temporelle
[Termes IGN] taxi
[Termes IGN] Wuhan (Chine)Résumé : (auteur) While daily periodic movements of individuals have been widely studied, their collective dynamics are not understood. To capture periodic collective dynamics, this article represents individual daily movements as a time series of directed weighted origin–destination (OD) networks, and proposes an approach to identify a sub-network called the “recurrent OD network”, which contains frequent edges appearing in each day. Taxi trajectory data over a period of 6 months in Wuhan, China are used for the case study. Here, we extracted the recurrent OD networks for each 2-h period on a given day, and compared them with the corresponding “major OD network” defined by both frequent and infrequent edges. Results show that the recurrent OD networks coincidentally exhibit spatially localized community structures and distinctive patterns of inflow and outflow for each region within a day. Overall, both methodology and findings in this study might make significant contributions in a range of fields, such as urban planning, regional economic development, and infectious disease control. Numéro de notice : A2022-179 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12849 Date de publication en ligne : 05/10/2021 En ligne : https://doi.org/10.1111/tgis.12849 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99838
in Transactions in GIS > vol 26 n° 1 (February 2022) . - pp 317 - 340[article]Relationships between species richness and ecosystem services in Amazonian forests strongly influenced by biogeographical strata and forest types / Gijs Steur in Scientific reports, vol 12 (2022)
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Titre : Relationships between species richness and ecosystem services in Amazonian forests strongly influenced by biogeographical strata and forest types Type de document : Article/Communication Auteurs : Gijs Steur, Auteur ; Hans Ter Steege, Auteur ; René W. Verburg, Auteur ; Daniel Sabatier, Auteur ; Jean-François Molino, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 5960 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Amazonie
[Termes IGN] forêt tropicale
[Termes IGN] produit forestier non ligneux
[Termes IGN] puits de carbone
[Termes IGN] richesse floristique
[Termes IGN] service écosystémique
[Termes IGN] strate végétale
[Termes IGN] volume en bois
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Despite increasing attention for relationships between species richness and ecosystem services, for tropical forests such relationships are still under discussion. Contradicting relationships have been reported concerning carbon stock, while little is known about relationships concerning timber stock and the abundance of non-timber forest product producing plant species (NTFP abundance). Using 151 1-ha plots, we related tree and arborescent palm species richness to carbon stock, timber stock and NTFP abundance across the Guiana Shield, and using 283 1-ha plots, to carbon stock across all of Amazonia. We analysed how environmental heterogeneity influenced these relationships, assessing differences across and within multiple forest types, biogeographic regions and subregions. Species richness showed significant relationships with all three ecosystem services, but relationships differed between forest types and among biogeographical strata. We found that species richness was positively associated to carbon stock in all biogeographical strata. This association became obscured by variation across biogeographical regions at the scale of Amazonia, resembling a Simpson’s paradox. By contrast, species richness was weakly or not significantly related to timber stock and NTFP abundance, suggesting that species richness is not a good predictor for these ecosystem services. Our findings illustrate the importance of environmental stratification in analysing biodiversity-ecosystem services relationships. Numéro de notice : A2022-308 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1038/s41598-022-09786-6 Date de publication en ligne : 08/04/2022 En ligne : http://dx.doi.org/10.1038/s41598-022-09786-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100403
in Scientific reports > vol 12 (2022) . - n° 5960[article]Siamese Adversarial Network for image classification of heavy mineral grains / Huizhen Hao in Computers & geosciences, vol 159 (February 2022)
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Titre : Siamese Adversarial Network for image classification of heavy mineral grains Type de document : Article/Communication Auteurs : Huizhen Hao, Auteur ; Zhiwei Jiang, Auteur ; Shiping Ge, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 105016 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage profond
[Termes IGN] classification barycentrique
[Termes IGN] classification et arbre de régression
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] microscope électronique
[Termes IGN] minéral
[Termes IGN] polarisation croisée
[Termes IGN] réseau antagoniste génératif
[Termes IGN] réseau neuronal siamois
[Termes IGN] séparateur à vaste margeRésumé : (auteur) The identification of heavy mineral grains based on microscopic images can significantly reduce the time and economic cost of the identification. There are several deep learning models to realize end-to-end identification of mineral image recently. However, due to the variety and complexity of mineral images, the existing models are difficult to accurately recognize heavy mineral grains in microscopic images. Here we propose the Siamese Adversarial Network (SAN) for image classification of the heavy mineral grains, which is the first time to focus on addressing the domain difference of heavy mineral images from different basins. In more details, we design a Siamese feature encoder to extract features of both the plane-polarized and cross-polarized images as internal representation of heavy mineral grains. The features are reconstructed to discard domain-related information by adversarial training the heavy mineral classifier and domain discriminator. The identification performance of the models under the three mixed domain experiments is consistently higher than the performance under the same domain settings respectively which shows that the model we proposed achieves a great generalization ability on unseen domains. Numéro de notice : A2022-174 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.105016 Date de publication en ligne : 03/12/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.105016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99810
in Computers & geosciences > vol 159 (February 2022) . - n° 105016[article]SNN_flow: a shared nearest-neighbor-based clustering method for inhomogeneous origin-destination flows / Qiliang Liu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)
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Titre : SNN_flow: a shared nearest-neighbor-based clustering method for inhomogeneous origin-destination flows Type de document : Article/Communication Auteurs : Qiliang Liu, Auteur ; Jie Yang, Auteur ; Min Deng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 253 - 279 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse de groupement
[Termes IGN] classification ascendante hiérarchique
[Termes IGN] classification barycentrique
[Termes IGN] flux
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] mobilité urbaine
[Termes IGN] noeud
[Termes IGN] origine - destination
[Termes IGN] Pékin (Chine)
[Termes IGN] réseau routier
[Termes IGN] taxi
[Termes IGN] trajet (mobilité)Résumé : (auteur) Identifying clusters from individual origin–destination (OD) flows is vital for investigating spatial interactions and flow mapping. However, detecting arbitrarily-shaped and non-uniform flow clusters from network-constrained OD flows continues to be a challenge. This study proposes a shared nearest-neighbor-based clustering method (SNN_flow) for inhomogeneous OD flows constrained by a road network. To reveal clusters of varying shapes and densities, a normalized density for each OD flow is defined based on the concept of shared nearest-neighbor, and flow clusters are constructed using the density-connectivity mechanism. To handle large amounts of disaggregated OD flows, an efficient method for searching the network-constrained k-nearest flows is developed based on a local road node distance matrix. The parameters of SNN_flow are statistically determined: the density threshold is modeled as a significance level of a significance test, and the number of nearest neighbors is estimated based on the variance of the kth nearest distance. SNN_flow is compared with three state-of-the-art methods using taxicab trip data in Beijing. The results show that SNN_flow outperforms existing methods in identifying flow clusters with irregular shapes and inhomogeneous distributions. The clusters identified by SNN_flow can reveal human mobility patterns in Beijing. Numéro de notice : A2022-163 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1899184 Date de publication en ligne : 16/03/2021 En ligne : https://doi.org/10.1080/13658816.2021.1899184 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99786
in International journal of geographical information science IJGIS > vol 36 n° 2 (February 2022) . - pp 253 - 279[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)
PermalinkSurvival time and mortality rate of regeneration in the deep shade of a primeval beech forest / R. Petrovska in European Journal of Forest Research, vol 141 n° 1 (February 2022)
PermalinkSynergistic use of particle swarm optimization, artificial neural network, and extreme gradient boosting algorithms for urban LULC mapping from WorldView-3 images / Alireza Hamedianfar in Geocarto international, vol 37 n° 3 ([01/02/2022])
PermalinkThree-Dimensional point cloud analysis for building seismic damage information / Fan Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 2 (February 2022)
PermalinkTree mortality caused by Diplodia shoot blight on Pinus sylvestris and other mediterranean pines / Maria Caballol in Forest ecology and management, vol 505 (February-1 2022)
PermalinkUsing vertices of a triangular irregular network to calculate slope and aspect / Guanghui Hu in International journal of geographical information science IJGIS, vol 36 n° 2 (February 2022)
Permalink3D modeling of urban area based on oblique UAS images - An end-to-end pipeline / Valeria-Ersilia Oniga in Remote sensing, vol 14 n° 2 (January-2 2022)
PermalinkAutomatic extraction of damaged houses by earthquake based on improved YOLOv5: A case study in Yangbi / Yafei Jing in Remote sensing, vol 14 n° 2 (January-2 2022)
PermalinkCo-seismic ionospheric disturbances following the 2016 West Sumatra and 2018 Palu earthquakes from GPS and GLONASS measurements / Mokhamad Nur Cahyadi in Remote sensing, vol 14 n° 2 (January-2 2022)
PermalinkCombined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation / Narissara Nuthammachot in Geocarto international, vol 37 n° 2 ([15/01/2022])
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