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Variations of urban NO2 pollution during the COVID-19 outbreak and post-epidemic era in China: A synthesis of remote sensing and In situ measurements / Chunhui Zhao in Remote sensing, vol 14 n° 2 (January-2 2022)
[article]
Titre : Variations of urban NO2 pollution during the COVID-19 outbreak and post-epidemic era in China: A synthesis of remote sensing and In situ measurements Type de document : Article/Communication Auteurs : Chunhui Zhao, Auteur ; Chengzin Zhang, Auteur ; Jinan Lin, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 419 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] dioxyde d'azote
[Termes IGN] épidémie
[Termes IGN] image Sentinel-5P-TROPOMI
[Termes IGN] impact sur l'environnement
[Termes IGN] pollution atmosphérique
[Termes IGN] qualité de l'air
[Termes IGN] variation temporelleRésumé : (auteur) Since the COVID-19 outbreak in 2020, China’s air pollution has been significantly affected by control measures on industrial production and human activities. In this study, we analyzed the temporal variations of NO2 concentrations during the COVID-19 lockdown and post-epidemic era in 11 Chinese megacities by using satellite and ground-based remote sensing as well as in situ measurements. The average satellite tropospheric vertical column density (TVCD) of NO2 by TROPOMI decreased by 39.2–71.93% during the 15 days after Chinese New Year when the lockdown was at its most rigorous compared to that of 2019, while the in situ NO2 concentration measured by China National Environmental Monitoring Centre (CNEMC) decreased by 42.53–69.81% for these cities. Such differences between both measurements were further investigated by using ground-based multi-axis differential optical absorption spectroscopy (MAX-DOAS) remote sensing of NO2 vertical profiles. For instance, in Beijing, MAX-DOAS NO2 showed a decrease of 14.19% (versus 18.63% by in situ) at the ground surface, and 36.24% (versus 36.25% by satellite) for the total tropospheric column. Thus, vertical discrepancies of atmospheric NO2 can largely explain the differences between satellite and in situ NO2 variations. In the post-epidemic era of 2021, satellite NO2 TVCD and in situ NO2 concentrations decreased by 10.42–64.96% and 1.05–34.99% compared to 2019, respectively, possibly related to the reduction of the transportation industry. This study reveals the changes of China’s urban NO2 pollution in the post-epidemic era and indicates that COVID-19 had a profound impact on human social activities and industrial production. Numéro de notice : A2022-102 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs14020419 Date de publication en ligne : 17/01/2022 En ligne : https://doi.org/10.3390/rs14020419 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99567
in Remote sensing > vol 14 n° 2 (January-2 2022) . - n° 419[article]Above-ground biomass estimation in a Mediterranean sparse coppice oak forest using Sentinel-2 data / Fardin Moradi in Annals of forest research, vol 65 n° 1 (January - June 2022)
[article]
Titre : Above-ground biomass estimation in a Mediterranean sparse coppice oak forest using Sentinel-2 data Type de document : Article/Communication Auteurs : Fardin Moradi, Auteur ; Seyed Mohammad Moein Sadeghi, Auteur ; Hadi Beygi Heidarlou, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 165 - 182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] allométrie
[Termes IGN] biomasse aérienne
[Termes IGN] classification barycentrique
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par Perceptron multicouche
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] forêt méditerranéenne
[Termes IGN] image proche infrarouge
[Termes IGN] image Sentinel-MSI
[Termes IGN] indice de végétation
[Termes IGN] Iran
[Termes IGN] Quercus brantii
[Termes IGN] taillisRésumé : (auteur) Implementing a scheduled and reliable estimation of forest characteristics is important for the sustainable management of forests. This study aimed at evaluating the capability of Sentinel-2 satellite data to estimate above-ground biomass (AGB) in coppice forests of Persian oak (Quercus brantii var. persica) located in Western Iran. To estimate the AGB, field data collection was implemented in 80 square plots (40×40 m, area of 1600 m2). Two diameters of the crown were measured and used to calculate the AGB of each tree based on allometric equations. Then, the performance of satellite data in estimating the AGB was evaluated for the area of study using the field-based AGB (dependent variable) as well as the spectral band values, spectrally-derived vegetation indices (independent variables) and four machine learning (ML) algorithms: MultiLayer Perceptron Artificial Neural Network (MLPNN), k-Nearest Neighbor (kNN), Random Forest (RF), and Support Vector Regression (SVR). A five-fold cross-validation was used to verify the effectiveness of models. Examination of the Pearson’s correlation coefficient between AGB and the extracted values showed that IPVI and NDVI vegetation indices had the highest correlation with AGB (r = 0.897). The results indicated that the MLPNN algorithm was the best ML option (RMSE = 1.71 t ha-1; MAE = 1.37 t ha-1; relative RMSE = 24.75%; R2 = 0.87) in estimating the AGB, providing new insights on the capability of remotely sensed-based AGB modeling of sparse Mediterranean forest ecosystems in an area with limited number of field sample plots. Numéro de notice : A2022-876 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.15287/afr.2022.2390 Date de publication en ligne : 29/06/2022 En ligne : https://doi.org/10.15287/afr.2022.2390 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102180
in Annals of forest research > vol 65 n° 1 (January - June 2022) . - pp 165 - 182[article]An assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 / Darius Phiri in Geomatics, Natural Hazards and Risk, vol 13 (2022)
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Titre : An assessment of forest loss and its drivers in protected areas on the Copperbelt province of Zambia: 1972–2016 Type de document : Article/Communication Auteurs : Darius Phiri, Auteur ; Collins Chanda, Auteur ; Vincent R. Nyirenda, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 148 - 166 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] aire protégée
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse diachronique
[Termes IGN] carte d'occupation du sol
[Termes IGN] carte thématique
[Termes IGN] classification par arbre de décision
[Termes IGN] couvert forestier
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] gestion forestière durable
[Termes IGN] protection de la biodiversité
[Termes IGN] ZambieRésumé : (auteur) In sub-Saharan Africa, protected areas provide a platform for conserving biodiversity. However, these areas are facing massive pressure due to deforestation, and information on forest dynamics and factors driving the changes in protected areas is generally lacking. This study has two objectives: (1) to assess forest cover changes that have occurred between 1972 and 2016 in Copperbelt Province’s protected areas, and (2) understand the drivers of forest cover changes. The study used thematic land cover maps for six selected years, which were classified using an object-based image analysis (OBIA) approach. We also applied a Classification Tree (CT) approach to assess the drivers of forest cover changes using R statistical software. The findings showed that forest cover in protected areas has been characterised by massive deforestation due to various factors. Between 1972 and 2016, primary and secondary forests showed a decrease of 2,226.43 km2 (11.06%) and an increase of 1,082.93 km2 (4.05%), respectively. The major factors driving forest changes include the levels of precipitation, human population density, elevation, distance from roads, towns and rivers. This study presents consistent information for long-term forest monitoring in protected areas, and informs decision-makers on the levels of deforestation and their drivers for effective forest management. Numéro de notice : A2022-092 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article DOI : 10.1080/19475705.2021.2017021 Date de publication en ligne : 21/12/2021 En ligne : https://doi.org/10.1080/19475705.2021.2017021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99515
in Geomatics, Natural Hazards and Risk > vol 13 (2022) . - pp 148 - 166[article]Attributing pedestrian networks with semantic information based on multi-source spatial data / Xue Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)
[article]
Titre : Attributing pedestrian networks with semantic information based on multi-source spatial data Type de document : Article/Communication Auteurs : Xue Yang, Auteur ; Kathleen Stewart, Auteur ; Mengyuan Fang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 31 - 54 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] données localisées des bénévoles
[Termes IGN] données multisources
[Termes IGN] extraction de données
[Termes IGN] itinéraire piétionnier
[Termes IGN] navigation pédestre
[Termes IGN] ondelette
[Termes IGN] réseau routier
[Termes IGN] segmentation sémantique
[Termes IGN] utilisation du sol
[Termes IGN] Wuhan (Chine)Résumé : (auteur) The lack of associating pedestrian networks, i.e. the paths and roads used for non-vehicular travel, with information about semantic attribution is a major weakness for many applications, especially those supporting accurate pedestrian routing. Researchers have developed various algorithms to generate pedestrian walkways based on datasets, including high-resolution images, existing map databases, and GPS data; however, the semantic attribution of pedestrian walkways is often ignored. The objective of our study is to automatically extract semantic information including incline values and the different categories of pedestrian paths from multi-source spatial data, such as crowdsourced GPS tracking data, land use data, and motor vehicle road (MVR) networks. Incline values for each pedestrian path were derived from tracking data through elevation filtering using wavelet theory and a similarity-based map-matching method. To automatically categorize pedestrian paths into five classes including sidewalk, crosswalk, entrance walkway, indoor path, and greenway, we developed a hierarchical strategy of spatial analysis using land use data and MVR networks. The effectiveness of our proposed method is demonstrated using real datasets including GPS tracking data collected by volunteers, land use data acquired from OpenStreetMap, and MVR network data downloaded from Gaode Map. Numéro de notice : A2022-083 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.1902530 En ligne : https://doi.org/10.1080/13658816.2021.1902530 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99480
in International journal of geographical information science IJGIS > vol 36 n° 1 (January 2022) . - pp 31 - 54[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022011 SL Revue Centre de documentation Revues en salle Disponible Automatic identification of addresses: A systematic literature review / Paula Cruz in ISPRS International journal of geo-information, vol 11 n° 1 (January 2022)
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Titre : Automatic identification of addresses: A systematic literature review Type de document : Article/Communication Auteurs : Paula Cruz, Auteur ; Leonardo Vanneschi, Auteur ; Marco Painho, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 11 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] appariement d'adresses
[Termes IGN] apprentissage automatique
[Termes IGN] apprentissage profond
[Termes IGN] base de données d'adresses
[Termes IGN] géocodage par adresse postale
[Termes IGN] Geoparsing
[Termes IGN] service fondé sur la positionRésumé : (auteur) Address matching continues to play a central role at various levels, through geocoding and data integration from different sources, with a view to promote activities such as urban planning, location-based services, and the construction of databases like those used in census operations. However, the task of address matching continues to face several challenges, such as non-standard or incomplete address records or addresses written in more complex languages. In order to better understand how current limitations can be overcome, this paper conducted a systematic literature review focused on automated approaches to address matching and their evolution across time. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed, resulting in a final set of 41 papers published between 2002 and 2021, the great majority of which are after 2017, with Chinese authors leading the way. The main findings revealed a consistent move from more traditional approaches to deep learning methods based on semantics, encoder-decoder architectures, and attention mechanisms, as well as the very recent adoption of hybrid approaches making an increased use of spatial constraints and entities. The adoption of evolutionary-based approaches and privacy preserving methods stand as some of the research gaps to address in future studies. Numéro de notice : A2022-088 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi11010011 Date de publication en ligne : 29/12/2021 En ligne : https://doi.org/10.3390/ijgi11010011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99497
in ISPRS International journal of geo-information > vol 11 n° 1 (January 2022) . - n° 11[article]Beech and hornbeam dominate oak 20 years after the creation of storm-induced gaps / Lucie Dietz in Forest ecology and management, vol 503 (January-1 2022)PermalinkClassification of mediterranean shrub species from UAV point clouds / Juan Pedro Carbonell-Rivera in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkCombining a class-weighted algorithm and machine learning models in landslide susceptibility mapping: A case study of Wanzhou section of the Three Gorges Reservoir, China / Huijuan Zhang in Computers & geosciences, vol 158 (January 2022)PermalinkA comparison of linear-mode and single-photon airborne LiDAR in species-specific forest inventories / Janne Raty in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkA comprehensive assessment of four-satellite QZSS constellation: navigation signals, broadcast ephemeris, availability, SPP, interoperability with GPS, and ISB against GPS / Xuanping Li in Survey review, vol 54 n° 382 (January 2022)PermalinkA constraint-based approach for identifying the urban–rural fringe of polycentric cities using multi-sourced data / Jing Yang in International journal of geographical information science IJGIS, vol 36 n° 1 (January 2022)PermalinkCultivating historical heritage area vitality using urban morphology approach based on big data and machine learning / Jiayu Wu in Computers, Environment and Urban Systems, vol 91 (January 2022)PermalinkCultural Heritage and Climate Change: New challenges and perspectives for research / Christopher Ballard (2022)PermalinkDeep image translation with an affinity-based change prior for unsupervised multimodal change detection / Luigi Tommaso Luppino in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkDetection and biomass estimation of phaeocystis globosa blooms off Southern China from UAV-based hyperspectral measurements / Xue Li in IEEE Transactions on geoscience and remote sensing, vol 60 n° 1 (January 2022)PermalinkDetection of windthrown tree stems on UAV-orthomosaics using U-Net convolutional networks / Stefan Reder in Remote sensing, vol 14 n° 1 (January-1 2022)PermalinkEffective triplet mining improves training of multi-scale pooled CNN for image retrieval / Federico Vaccaro in Machine Vision and Applications, vol 33 n° 1 (January 2022)PermalinkEstimating aboveground biomass in dense Hyrcanian forests by the use of Sentinel-2 data / Fardin Moradi in Forests, vol 13 n° 1 (January 2022)PermalinkEstimation of Lesser Antilles vertical velocity fields using a GNSS-PPP software comparison / Pierre Sakic-Kieffer (2022)PermalinkExplorer les processus de mobilité passée : raisonnement ontologique fondé sur la connaissance des pratiques socioculturelles et des vestiges archéologiques / Laure Nuninger in Revue internationale de géomatique, vol 31 n° 1-2 (janvier - juin 2022)PermalinkFlood susceptibility mapping using meta-heuristic algorithms / Alireza Arabameri in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkPermalinkForest fire susceptibility assessment using Google Earth engine in Gangwon-do, Republic of Korea / Yong Piao in Geomatics, Natural Hazards and Risk, vol 13 (2022)PermalinkPermalinkPermalink