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Multiscale geographically and temporally weighted regression with a unilateral temporal weighting scheme and its application in the analysis of spatiotemporal characteristics of house prices in Beijing / Zhi Zhang in International journal of geographical information science IJGIS, vol 35 n° 11 (November 2021)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 35 n° 11 (November 2021) . - pp 2262 - 2286 Titre : Multiscale geographically and temporally weighted regression with a unilateral temporal weighting scheme and its application in the analysis of spatiotemporal characteristics of house prices in Beijing Type de document : Article/Communication Auteurs : Zhi Zhang, Auteur ; Jing Li, Auteur ; Fung, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2262 - 2286 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse spatio-temporelle [Termes IGN] coût [Termes IGN] hétérogénéité spatiale [Termes IGN] logement [Termes IGN] marché foncier [Termes IGN] Pékin (Chine) [Termes IGN] régression géographiquement pondérée Résumé : (auteur) Geographically and temporally weighted regression (GTWR) has been demonstrated as an effective tool for exploring spatiotemporal data under spatial and temporal heterogeneity. Exploiting the advantages of the two most popular GTWR methods, we propose an alternative GTWR with a good balance between complexity and interpretability via a unilateral temporal weighting scheme called unilateral GTWR (UGTWR). When compared to the other two popular GTWR methods, the simulation experiment shows that UGTWR has comparable estimation accuracy and model fit, but it is more efficient. Furthermore, we propose its multiscale extension, coined multiscale UGTWR (MUGTWR), to characterize the spatiotemporal dynamic regression relationships at multiple scales. The proposed MUGTWR was applied to the analysis of house prices in the period of 2014–2018 in Beijing as a case study. Our analysis reveals that MUGTWR can effectively capture different levels of spatiotemporal heterogeneity in selected factors affecting house prices at different scales. Therefore, this study is useful for the formulation of housing policy in which the spatiotemporal dynamics of house prices with respect to specific factors can be considered. Numéro de notice : A2021-758 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.1080/13658816.2021.1912348 Date de publication en ligne : 12/05/2021 En ligne : https://doi.org/10.1080/13658816.2021.1912348 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98773 [article]

A novel unsupervised change detection method from remotely sensed imagery based on an improved thresholding algorithm / Sara Khanbani in Applied geomatics, vol 13 n° 1 (May 2021)  

Public [article]  inApplied geomatics > vol 13 n° 1 (May 2021) . - pp 89 - 105 Titre : A novel unsupervised change detection method from remotely sensed imagery based on an improved thresholding algorithm Type de document : Article/Communication Auteurs : Sara Khanbani, Auteur ; Ali Mohammadzadeh, Auteur ; Milad Janalipour, Auteur Année de publication : 2021 Article en page(s) : pp 89 - 105 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Alaska (Etats-Unis) [Termes IGN] algorithme génétique [Termes IGN] changement temporel [Termes IGN] classification floue [Termes IGN] classification non dirigée [Termes IGN] classification par nuées dynamiques [Termes IGN] coût [Termes IGN] détection de changement [Termes IGN] seuillage Résumé : (auteur) Change Detection (CD) problem from remotely sensed images is a popular topic among researchers. Because of the diversity in the problem of change detection and the complexity of the study areas it cannot be claimed that there is an appropriate and prevalent algorithm which is more effective for different types of the case study. As a fundamental investigation, it is critical to recognize the weaknesses of the state of artworks in change detection. Also, those examined weaknesses have to be improved aptly to develop a new strong method. This paper presents a thresholding algorithm improved by the Genetic Algorithm (GA) in CD problems, which focuses on minimizing a novel cost function. The suggested cost function can be adopted for local and global change variations in difference images without any prior assumptions. The presented algorithm was tested on two data sets (i.e., Alaska region and Uremia Lake) to validate its effectiveness. Experimental results demonstrated that the proposed algorithm in this work has improved the accuracy of change detection (changed pixel accuracy term) in the Alaska region about 8%–12% and also in Uremia Lake approximately between 8%–13% in comparison with other conventional methods including Fuzzy C- Means (FCM), Otsu thresholding, K-Means, and K-Medoid. Numéro de notice : A2021-237 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00323-6 Date de publication en ligne : 22/06/2020 En ligne : https://doi.org/10.1007/s12518-020-00323-6 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97246 [article]

Reducing multipath effect of low-cost GNSS receivers for monitoring by considering temporal correlations / Li Zhang in Journal of applied geodesy, vol 14 n° 2 (April 2020)  

Public [article]  inJournal of applied geodesy > vol 14 n° 2 (April 2020) . - pp 167 – 175 Titre : Reducing multipath effect of low-cost GNSS receivers for monitoring by considering temporal correlations Type de document : Article/Communication Auteurs : Li Zhang, Auteur ; Volker Schwieger, Auteur Année de publication : 2020 Article en page(s) : pp 167 – 175 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] atténuation du signal [Termes IGN] corrélation temporelle [Termes IGN] coût [Termes IGN] itération [Termes IGN] ligne de base [Termes IGN] oscillation [Termes IGN] phase [Termes IGN] plan de masse [Termes IGN] qualité des données [Termes IGN] récepteur GNSS [Termes IGN] récepteur monofréquence [Termes IGN] réflecteur [Termes IGN] source d'erreur [Termes IGN] trajet multiple Résumé : (auteur) The investigations on low-cost single frequency GNSS receivers at the Institute of Engineering Geodesy (IIGS) show that u-blox GNSS receivers combined with low-cost antennas and self-constructed L1-optimized choke rings can reach an accuracy which almost meets the requirements of geodetic applications (see Zhang and Schwieger [25]). However, the quality (accuracy and reliability) of low-cost GNSS receiver data should still be improved, particularly in environments with obstructions. The multipath effects are a major error source for the short baselines. The ground plate or the choke ring ground plane can reduce the multipath signals from the horizontal reflector (e. g. ground). However, the shieldings cannot reduce the multipath signals from the vertical reflectors (e. g. walls). Because multipath effects are spatially and temporally correlated, an algorithm is developed for reducing the multipath effect by considering the spatial correlations of the adjoined stations (see Zhang and Schwieger [24]). In this paper, an algorithm based on the temporal correlations will be introduced. The developed algorithm is based on the periodic behavior of the estimated coordinates and not on carrier phase raw data, which is easy to use. Because, for the users, coordinates are more accessible than the raw data. The multipath effect can cause periodic oscillations but the periods change over time. Besides this, the multipath effect’s influence on the coordinates is a mixture of different multipath signals from different satellites and different reflectors. These two properties will be used to reduce the multipath effect. The algorithm runs in two steps and iteratively. Test measurements were carried out in a multipath intensive environment; the accuracies of the measurements are improved by about 50 % and the results can be delivered in near-real-time (in ca. 30 minutes), therefore the algorithm is suitable for structural health monitoring applications. Numéro de notice : A2020-217 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2019-0059 Date de publication en ligne : 27/03/2020 En ligne : https://doi.org/10.1515/jag-2019-0059 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94910 [article]

Wavelet-adaptive neural subtractive clustering fuzzy inference system to enhance low-cost and high-speed INS/GPS navigation system / Elahe S. Abdolkarimi in GPS solutions, vol 24 n° 2 (April 2020)  

Public [article]  inGPS solutions > vol 24 n° 2 (April 2020) Titre : Wavelet-adaptive neural subtractive clustering fuzzy inference system to enhance low-cost and high-speed INS/GPS navigation system Type de document : Article/Communication Auteurs : Elahe S. Abdolkarimi, Auteur ; Mohammad-Reza Mosavi, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] centrale inertielle [Termes IGN] coût [Termes IGN] filtre de Kalman [Termes IGN] GPS-INS [Termes IGN] imprécision des données [Termes IGN] incertitude des données [Termes IGN] Inférence floue [Termes IGN] précision du positionnement [Termes IGN] rapport signal sur bruit [Termes IGN] transformation en ondelettes [Termes IGN] vitesse de déplacement Résumé : (auteur) The combined navigation system consisting of Global Positioning System (GPS) and Inertial Navigation System in a complementary mode assures an accurate, reliable, and continuous positioning capability in the navigation system. Because of problems such as dealing with a low-cost MEMS-based inertial sensors having a high level of uncertainty and imprecision, stochastic noise, a high-speed vehicle, high noisy real data, and long-term GPS signal outage during the real-time flight test, the advantage is taken for some approaches in different steps: (1) utilizing discrete wavelet transform technique to enhance the signal-to-noise ratio in raw and noisy inertial sensor signals and attenuate high-frequency noise as a preprocessing phase to prepare more accurate data for the proposed model and (2) employing adaptive neural subtractive clustering fuzzy inference system (ANSCFIS) which combines and extracts the best feature of adaptive neuro-fuzzy inference system (ANFIS), and the subtractive clustering algorithm with fewer rules than the ANFIS method, aiming to improve a more efficient, accurate, and especially a faster method which enhances the prediction accuracy and speeds up the positioning system. The achieved accuracies for the proposed model are discussed and compared with the extended Kalman filter (EKF), ANFIS, and ANSCFIS which are implemented and tested experimentally using a high-speed vehicle in three GPS blockages. The proposed model shows considerable improvements in high-speed navigation using low-cost MEMS-based inertial sensors in case of long-term GPS blockage. Numéro de notice : A2020-084 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-020-0951-y Date de publication en ligne : 11/01/2020 En ligne : https://doi.org/10.1007/s10291-020-0951-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94654 [article]

Learning and adapting robust features for satellite image segmentation on heterogeneous data sets / Sina Ghassemi in IEEE Transactions on geoscience and remote sensing, vol 57 n° 9 (September 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 9 (September 2019) . - pp 6517 - 6529 Titre : Learning and adapting robust features for satellite image segmentation on heterogeneous data sets Type de document : Article/Communication Auteurs : Sina Ghassemi, Auteur ; Attilio Friandrotti, Auteur ; Gianluca Francini, Auteur ; Enrico Magli, Auteur Année de publication : 2019 Article en page(s) : pp 6517 - 6529 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] chaîne de traitement [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] coût [Termes IGN] données hétérogènes [Termes IGN] image binaire [Termes IGN] image satellite [Termes IGN] méthode robuste [Termes IGN] réseau neuronal convolutif [Termes IGN] segmentation d'image [Termes IGN] seuillage binaire [Termes IGN] test de performance Résumé : (auteur) This paper addresses the problem of training a deep neural network for satellite image segmentation so that it can be deployed over images whose statistics differ from those used for training. For example, in postdisaster damage assessment, the tight time constraints make it impractical to train a network from scratch for each image to be segmented. We propose a convolutional encoder–decoder network able to learn visual representations of increasing semantic level as its depth increases, allowing it to generalize over a wider range of satellite images. Then, we propose two additional methods to improve the network performance over each specific image to be segmented. First, we observe that updating the batch normalization layers’ statistics over the target image improves the network performance without human intervention. Second, we show that refining a trained network over a few samples of the image boosts the network performance with minimal human intervention. We evaluate our architecture over three data sets of satellite images, showing the state-of-the-art performance in binary segmentation of previously unseen images and competitive performance with respect to more complex techniques in a multiclass segmentation task. Numéro de notice : A2019-341 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2906689 Date de publication en ligne : 17/04/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2906689 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93379 [article]

Spatial mining of migration patterns from web demographics / T. Edwin Chow in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)  

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Structural health monitoring using a GPS sensor network / Nicolas Manzini (2018)  

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The use of low-cost, single-frequency GNSS receivers in mapping surveys / M. Tsakiri in Survey review, vol 50 n° 358 (January 2018)  

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Economics of mapping using small manned and unmanned aerial vehicles / Orrin H. Thomas in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 8 (August 2017)  

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The cost(s) of geospatial open data / Peter A. Johnson in Transactions in GIS, vol 21 n° 3 (June 2017)  

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Assessing the ecosystem service flood protection of a riparian forest by applying a cascade approach / Nina-Christin Barth in Ecosystem Services, vol 21 Part A (October 2016)  

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Mobilités à la loupe / Françoise de Blomac in DécryptaGéo le mag, n° 179 (septembre 2016)

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Open access: at what cost ? / Rebecca Pool in Research information, n° 85 (August - September 2016) 

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Belastungen der deutschen Forstwirtschaft aus der Schutz- und Erholungsfunktion des Waldes / Markus Dög in Landbauforschung, vol 66 n° 2 (06-2016) 

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Estimations dendrométriques pour l’aménagement forestier à l’aide de LiDAR aéroporté : premier démonstrateur en forêts littorales dunaires / Alain Munoz in Rendez-vous techniques, n° 50 (Hiver 2016) 

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