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Detection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM / Jiehua Cai in Engineering Geology, vol 305 (August 2022)  

Public [article]  inEngineering Geology > vol 305 (August 2022) . - n° 106730 Titre : Detection and characterization of slow-moving landslides in the 2017 Jiuzhaigou earthquake area by combining satellite SAR observations and airborne Lidar DSM Type de document : Article/Communication Auteurs : Jiehua Cai, Auteur ; Lu Zhang, Auteur ; Jie Dong, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 106730 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] cartographie des risques [Termes IGN] déformation de surface [Termes IGN] données lidar [Termes IGN] données multisources [Termes IGN] effondrement de terrain [Termes IGN] géomorphologie [Termes IGN] image ALOS-PALSAR [Termes IGN] image optique [Termes IGN] image Sentinel-SAR [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] MNS lidar [Termes IGN] MNS SRTM [Termes IGN] séisme [Termes IGN] Setchouan (Chine) [Termes IGN] surveillance géologique Résumé : (auteur) On 8th August 2017, a catastrophic Ms. 7.0 earthquake with a focal depth of 20 km struck the Jiuzhaigou County in Sichuan Province, China. It exerted a strong influence on the slope stability within the surrounding areas and triggered numerous secondary geohazards including rockfalls and other co-seismic landslides, which incurred drastic surface changes, and thus can be easily identified from cloud-free high-resolution optical imagery. Most of such landslides became stabilized shortly after the earthquake while others moving very slowly for years. In contrast, some slopes were destabilized without significant surface change into slow-moving landslides, which may pose long-term potential threats to people's life and property. Therefore, it is crucial to accurately identify these slow-moving landslides and regularly monitor their post-seismic activity. In this study, we employed the synthetic aperture radar interferometry (InSAR) techniques to detect and monitor slow-moving landslides after the earthquake in the Jiuzhaigou area, and analyzed the impacts of the earthquake on these landslides through integration of multi-source data (InSAR, Lidar, optical image, and field survey). As a result, 16 slow-moving landslides were detected by InSAR in the Jiuzhaigou area, including several historical landslides. The results of time-series InSAR analyses enabled identification of three kinds of landslide evolution modes affected by the earthquake, i.e. acceleration of deformation of pre-existing landslides, reactivation of dormant landslide, and remobilization of earthquake-triggered landslide. Each mode is supported by detailed analyses of multi-source data. The results demonstrated that satellite InSAR combined with high-resolution Lidar and optical data can provide a cost-effective approach of post-earthquake geohazards detection and monitoring. Numéro de notice : A2022-469 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.enggeo.2022.106730 Date de publication en ligne : 28/05/2022 En ligne : https://doi.org/10.1016/j.enggeo.2022.106730 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100811 [article]

Developing a data-fusing method for mapping fine-scale urban three-dimensional building structure / Xinxin Wu in Sustainable Cities and Society, vol 80 (May 2022)  

Public [article]  inSustainable Cities and Society > vol 80 (May 2022) . - n° 103716 Titre : Developing a data-fusing method for mapping fine-scale urban three-dimensional building structure Type de document : Article/Communication Auteurs : Xinxin Wu, Auteur ; Jinpei Ou, Auteur ; Youyue Wen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103716 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] apprentissage automatique [Termes IGN] cartographie urbaine [Termes IGN] données localisées 3D [Termes IGN] données multisources [Termes IGN] fusion de données [Termes IGN] hauteur du bâti [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle de régression [Termes IGN] morphologie urbaine [Termes IGN] Shenzhen [Termes IGN] ville durable [Termes IGN] ville intelligente Résumé : (auteur) Understanding urban morphology is essential for various urban management studies and local environmental issues and guiding sustainable city development. Existing studies mainly focus on analyzing urban morphology from the horizontal aspect, while the urban vertical structure has rarely been discussed due to the scarcity of reliable and fine-scale urban three-dimensional (3-D) building data. This study develops an effective data-fusing methodology to estimate the heights of individual buildings at a city scale. We examined a machine-learning regression model by collecting public materials, including multi-source remote sensing-(RS)-based products, building-derived features, and relevant data to verify its performance in building height estimation. By applying the model in Shenzhen City, a dense city in the Guangdong-Hong Kong-Macao Greater Bay Area, results demonstrated that integrating rich multi-source explanatory variables could achieve high-accuracy building height retrieval. Using multiple building morphological metrics derived by building height data as proxy measures, the urban 3-D form patterns were further analyzed to understand current heterogeneous urban morphological structures. The proposed methodology can be conveniently applied to worldwide cities for urban 3-D morphology retrieval. Also, the available building height information is useful for planners to design morphological control for cities and thus contributes to sustainable and smart city development. Numéro de notice : A2022-268 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.scs.2022.103716 Date de publication en ligne : 12/02/2022 En ligne : https://doi.org/10.1016/j.scs.2022.103716 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100279 [article]

Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework / Evgeny Noi in International journal of geographical information science IJGIS, vol 36 n° 3 (March 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 3 (March 2022) . - pp 585 - 616 Titre : Assessing COVID-induced changes in spatiotemporal structure of mobility in the United States in 2020: a multi-source analytical framework Type de document : Article/Communication Auteurs : Evgeny Noi, Auteur ; Alexander Rudolph, Auteur ; Somayeh Dodge, Auteur Année de publication : 2022 Article en page(s) : pp 585 - 616 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] autocorrélation spatiale [Termes IGN] comportement [Termes IGN] données multisources [Termes IGN] données spatiotemporelles [Termes IGN] épidémie [Termes IGN] Etats-Unis [Termes IGN] hétérogénéité spatiale [Termes IGN] maladie virale [Termes IGN] mobilité [Termes IGN] mobilité territoriale Résumé : (auteur) The COVID-19 pandemic resulted in profound changes in mobility patterns and altered travel behaviors locally and globally. As a result, movement metrics have widely been used by researchers and policy makers as indicators to study, model, and mitigate the impacts of the COVID-19 pandemic. However, the veracity and variability of these mobility metrics have not been studied. This paper provides a systematic review of mobility and social distancing metrics available to researchers during the pandemic in 2020 in the United States. Twenty-six indices across nine different sources are analyzed and assessed with respect to their spatial and temporal coverage as well as sample representativeness at the county-level. Finally global and local indicators of spatial association are computed to explore spatial and temporal heterogeneity in mobility patterns. The structure of underlying changes in mobility and social distancing is examined in different US counties and across different data sets. We argue that a single measure might not describe all aspects of mobility perfectly. Numéro de notice : A2022-207 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2005796 Date de publication en ligne : 21/12/2021 En ligne : https://doi.org/10.1080/13658816.2021.2005796 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100023 [article]

Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3 / Nima Pahlevan in Remote sensing of environment, vol 270 (March 2022)  

Public [article]  inRemote sensing of environment > vol 270 (March 2022) . - n° 112860 Titre : Simultaneous retrieval of selected optical water quality indicators from Landsat-8, Sentinel-2, and Sentinel-3 Type de document : Article/Communication Auteurs : Nima Pahlevan, Auteur ; Brandon Smith, Auteur ; Krista Alikas, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 112860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] appariement d'images [Termes IGN] apprentissage automatique [Termes IGN] chlorophylle [Termes IGN] classification par maximum de vraisemblance [Termes IGN] classification par Perceptron multicouche [Termes IGN] correction atmosphérique [Termes IGN] données multisources [Termes IGN] eaux côtières [Termes IGN] image Landsat-OLI [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-OLCI [Termes IGN] matière organique [Termes IGN] Oregon (Etats-Unis) [Termes IGN] qualité des eaux Résumé : (auteur) Constructing multi-source satellite-derived water quality (WQ) products in inland and nearshore coastal waters from the past, present, and future missions is a long-standing challenge. Despite inherent differences in sensors’ spectral capability, spatial sampling, and radiometric performance, research efforts focused on formulating, implementing, and validating universal WQ algorithms continue to evolve. This research extends a recently developed machine-learning (ML) model, i.e., Mixture Density Networks (MDNs) (Pahlevan et al., 2020; Smith et al., 2021), to the inverse problem of simultaneously retrieving WQ indicators, including chlorophyll-a (Chla), Total Suspended Solids (TSS), and the absorption by Colored Dissolved Organic Matter at 440 nm (acdom(440)), across a wide array of aquatic ecosystems. We use a database of in situ measurements to train and optimize MDN models developed for the relevant spectral measurements (400–800 nm) of the Operational Land Imager (OLI), MultiSpectral Instrument (MSI), and Ocean and Land Color Instrument (OLCI) aboard the Landsat-8, Sentinel-2, and Sentinel-3 missions, respectively. Our two performance assessment approaches, namely hold-out and leave-one-out, suggest significant, albeit varying degrees of improvements with respect to second-best algorithms, depending on the sensor and WQ indicator (e.g., 68%, 75%, 117% improvements based on the hold-out method for Chla, TSS, and acdom(440), respectively from MSI-like spectra). Using these two assessment methods, we provide theoretical upper and lower bounds on model performance when evaluating similar and/or out-of-sample datasets. To evaluate multi-mission product consistency across broad spatial scales, map products are demonstrated for three near-concurrent OLI, MSI, and OLCI acquisitions. Overall, estimated TSS and acdom(440) from these three missions are consistent within the uncertainty of the model, but Chla maps from MSI and OLCI achieve greater accuracy than those from OLI. By applying two different atmospheric correction processors to OLI and MSI images, we also conduct matchup analyses to quantify the sensitivity of the MDN model and best-practice algorithms to uncertainties in reflectance products. Our model is less or equally sensitive to these uncertainties compared to other algorithms. Recognizing their uncertainties, MDN models can be applied as a global algorithm to enable harmonized retrievals of Chla, TSS, and acdom(440) in various aquatic ecosystems from multi-source satellite imagery. Local and/or regional ML models tuned with an apt data distribution (e.g., a subset of our dataset) should nevertheless be expected to outperform our global model. Numéro de notice : A2022-126 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112860 Date de publication en ligne : 04/01/2022 En ligne : https://doi.org/10.1016/j.rse.2021.112860 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99705 [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)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 1 (January 2022) . - pp 31 - 54 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 [article]

A 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)  

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Multi-view urban scene classification with a complementary-information learning model / Wanxuan Geng in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)  

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A deep multi-modal learning method and a new RGB-depth data set for building roof extraction / Mehdi Khoshboresh Masouleh in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)  

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Mapping essential urban land use categories with open big data: Results for five metropolitan areas in the United States of America / Bin Chen in ISPRS Journal of photogrammetry and remote sensing, vol 178 (August 2021)  

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Surface modelling of forest aboveground biomass based on remote sensing and forest inventory data / Xiaofang Sun in Geocarto international, vol 36 n° 14 ([01/08/2021])  

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Multi-modal learning in photogrammetry and remote sensing / Michael Ying Yang in ISPRS Journal of photogrammetry and remote sensing, vol 176 (June 2021)  

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Anti-cross validation technique for constructing and boosting random subspace neural network ensembles for hyperspectral image classification / Laxmi Narayana Eeti in Geocarto international, vol 36 n° 6 ([01/04/2021])  

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Automated registration of SfM‐MVS multitemporal datasets using terrestrial and oblique aerial images / Luigi Parente in Photogrammetric record, vol 36 n° 173 (March 2021)  

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A points of interest matching method using a multivariate weighting function with gradient descent optimization / Zhou Yang in Transactions in GIS, Vol 25 n° 1 (February 2021)  

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Estimation et cartographie d’attributs forestiers haute résolution : Le potentiel des approches multisource / Cédric Vega (2021) 

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