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Evaluating metrics derived from Landsat 8 OLI imagery to map crop cover / Rei Sonobe in Geocarto international, vol 34 n° 8 ([15/06/2019])
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Titre : Evaluating metrics derived from Landsat 8 OLI imagery to map crop cover Type de document : Article/Communication Auteurs : Rei Sonobe, Auteur ; Yuki Yamaya, Auteur ; Hiroshi Tani, Auteur ; Xiufeng Wang, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 839 - 855 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification et arbre de régression
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] rayonnement lumineux
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] réflectance végétale
[Termes IGN] signature spectrale
[Termes IGN] surface cultivéeRésumé : (auteur) Developing techniques are required to generate agricultural land cover maps to monitor agricultural fields. Landsat 8 Operational Land Imager (OLI) offers reflectance data over the visible to shortwave-infrared range. OLI offers several advantages, such as adequate spatial and spectral resolution, and 16 day repeat coverage, furthermore, spectral indices derived from Landsat 8 OLI possess great potential for evaluating the status of vegetation. Additionally, classification algorithms are essential for generating accurate maps. Recently, multi-Grained Cascade Forest, which is also called deep forest, was proposed, and it was shown to give highly competitive performance for classification. However, the ability of this algorithm to generate crop maps with satellite data had not yet been evaluated. In this study, the reflectance at 7 bands and 57 spectral indices calculated from Landsat 8 OLI data were evaluated for its potential for crop type identification. Numéro de notice : A2019-514 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1425739 Date de publication en ligne : 19/01/2018 En ligne : https://doi.org/10.1080/10106049.2018.1425739 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93823
in Geocarto international > vol 34 n° 8 [15/06/2019] . - pp 839 - 855[article]Analyzing the recent dynamics of wildland fires in Quercus suber L. woodlands in Sardinia (Italy), Corsica (France) and Catalonia (Spain) / Michele Salis in European Journal of Forest Research, vol 138 n° 3 (June 2019)
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Titre : Analyzing the recent dynamics of wildland fires in Quercus suber L. woodlands in Sardinia (Italy), Corsica (France) and Catalonia (Spain) Type de document : Article/Communication Auteurs : Michele Salis, Auteur ; Bachisio Arca, Auteur ; Fermin Alcasena-Urdiroz, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 415 - 431 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] bassin méditerranéen
[Termes IGN] Catalogne (Espagne)
[Termes IGN] Corse
[Termes IGN] données socio-économiques
[Termes IGN] incendie de forêt
[Termes IGN] précipitation
[Termes IGN] Quercus suber
[Termes IGN] régression logistique
[Termes IGN] SardaigneRésumé : (Auteur) Wildland fires represent a major threat to Quercus suber L. ecosystems, which provide relevant socioeconomic and ecological services in the Mediterranean Basin. In this work, we analyzed recent wildland fire dynamics in cork oak woodlands along the fire-prone areas of Sardinia (Italy), Corsica (France) and Catalonia (Spain). We first characterized geographic extent and main characteristics of cork oak woodlands in these regions and analyzed how environmental (climate and elevation) and socioeconomic factors (population and land uses) vary in the areas covered by Quercus suber L. We then evaluated how wildfires affected cork oak stands and, by logistic regression analysis, to what extent wildfires in cork oak areas were related to the above set of environmental and anthropic explanatory variables. Results revealed specific variations across study areas in cork oak characteristics as well as in environmental and social factors. We highlighted the spatial and temporal patterns of wildfires on cork oak woodlands, in terms of extent, seasonality, frequency and main driving factors. In the period 2003–2015, the percentage of cork oak woodlands burned ranged from 3.42% in Corsica to 11.30% in Sardinia. A few large and severe wildfires accounted for most of the area burned in cork oak woodlands. The most significant predictive variable that explained the spatial variation in wildland fire ignitions inside or nearby cork oaks was summer precipitation, while the weight of other factors varied depending on the region. This study provides evidence on recent fire dynamics in cork oak woodlands and gives valuable information and insights for the implementation of forest management and planning strategies in the Mediterranean area. Numéro de notice : A2019-243 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10342-019-01179-1 Date de publication en ligne : 20/02/2019 En ligne : https://doi.org/10.1007/s10342-019-01179-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92746
in European Journal of Forest Research > vol 138 n° 3 (June 2019) . - pp 415 - 431[article]Buildings in GI: How to deal with building models in the GIS domain / Laura Knoth in Transactions in GIS, vol 23 n° 3 (June 2019)
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Titre : Buildings in GI: How to deal with building models in the GIS domain Type de document : Article/Communication Auteurs : Laura Knoth, Auteur ; Manfred Mittlböck, Auteur ; Bernhard Vockner, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 435 - 449 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] échange de données informatisé
[Termes IGN] interopérabilité
[Termes IGN] modélisation 3D du bâti BIM
[Termes IGN] modélisation du bâti
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Digital building information is important during a building's lifecycle, it is needed from first design until demolition. The two domains that mainly contribute are AEC (architecture, engineering, and construction) during design, construction, and operation, and GIS as a supporting discipline for analysis and further integration of the building's environment. However, there is a challenge in information exchange between the two domains, resulting in the remodeling of digital building information in GIS. In this article, we identify three major data sources from the AEC domain and show transformation processes to enable the integration of such models into the geographical environment in the form of one transition model. Furthermore, we show that this model can either be used directly or exported in the form of de facto standards that allow for further analysis. Numéro de notice : A2019-254 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12541 Date de publication en ligne : 05/06/2019 En ligne : https://doi.org/10.1111/tgis.12541 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93012
in Transactions in GIS > vol 23 n° 3 (June 2019) . - pp 435 - 449[article]Exploitation of deep learning in the automatic detection of cracks on paved roads / Won Mo Jung in Geomatica, vol 73 n° 2 (June 2019)
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Titre : Exploitation of deep learning in the automatic detection of cracks on paved roads Type de document : Article/Communication Auteurs : Won Mo Jung, Auteur ; Faizaan Naveed, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 29 - 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] autoroute
[Termes IGN] chaussée
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] détection d'objet
[Termes IGN] Ontario (Canada)Mots-clés libres : fissure Résumé : (auteur) With the advance of deep learning networks, their applications in the assessment of pavement conditions are gaining more attention. A convolutional neural network (CNN) is the most commonly used network in image classification. In terms of pavement assessment, most existing CNNs are designed to only distinguish between cracks and non-cracks. Few networks classify cracks in different levels of severity. Information on the severity of pavement cracks is critical for pavement repair services. In this study, the state-of-the-art CNN used in the detection of pavement cracks was improved to localize the cracks and identify their distress levels based on three categories (low, medium, and high). In addition, a fully convolutional network (FCN) was, for the first time, utilized in the detection of pavement cracks. These designed architectures were validated using the data acquired on four highways in Ontario, Canada, and compared with the ground truth that was provided by the Ministry of Transportation of Ontario (MTO). The results showed that with the improved CNN, the prediction precision on a series of test image patches were 72.9%, 73.9%, and 73.1% for cracks with the severity levels of low, medium, and high, respectively. The precision for the FCN was tested on whole pavement images, resulting in 62.8%, 63.3%, and 66.4%, respectively, for cracks with the severity levels of low, medium, and high. It is worth mentioning that the ground truth contained some uncertainties, which partially contributed to the relatively low precision. Numéro de notice : A2019-657 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1139/geomat-2019-0008 En ligne : https://doi.org/10.1139/geomat-2019-0008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98324
in Geomatica > vol 73 n° 2 (June 2019) . - pp 29 - 44[article]Helmert-VCE-aided fast-WTLS approach for global ionospheric VTEC modelling using data from GNSS, satellite altimetry and radio occultation / Andong Hu in Journal of geodesy, vol 93 n°6 (June 2019)
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Titre : Helmert-VCE-aided fast-WTLS approach for global ionospheric VTEC modelling using data from GNSS, satellite altimetry and radio occultation Type de document : Article/Communication Auteurs : Andong Hu, Auteur ; Zishen Li, Auteur ; Brett Anthony Carter, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 877 - 888 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] carte ionosphérique mondiale
[Termes IGN] données altimétriques
[Termes IGN] données GNSS
[Termes IGN] méthode des moindres carrés
[Termes IGN] modèle ionosphérique
[Termes IGN] occultation du signal
[Termes IGN] pondération
[Termes IGN] retard ionosphèrique
[Termes IGN] teneur verticale totale en électrons
[Termes IGN] varianceRésumé : (auteur) Vertical total electron content (VTEC) global ionospheric maps (GIM) are commonly used to correct the ionospheric delay of global navigation satellite system (GNSS) signals for single-frequency positioning and other ionospheric studies. The measurements observed by inhomogeneously distributed ground reference stations are the only data used to generate the GIMs. Thus the accuracy of the GIMs over ocean and polar regions is relatively poor due to the lack of measurements over these regions. In this study, space-borne VTECs obtained from ocean-altimetry and GNSS radio occultation measurements are incorporated into the modelling process. Since the three types of VTEC data have different qualities, the weight for each type of data is determined using the Helmert-variance component estimation (Helmert-VCE) method. In addition, unlike the traditional weighted least squares (WLS) estimation method in which the design matrix of observation equations is fixed, in this study, the design matrix, especially those elements in design matrix that are derived from the coordinates of either tangent point or ionospheric pierce point, are considered to be inaccurate. Thus they are adjusted together with the unknown coefficient parameters of the fitting model using the fast-weighted total least squares (fast-WTLS) technique. The proposed approach, named Helmert-WTLS, was tested using the data in the period of day of year (DOY) 217–224, 2016 and validated using GIMs produced by the research team for ionosphere and precise positioning based on BDS/GNSS (GIPP) at the Academy of Opto-Electronics, Chinese Academy of Sciences (CAS). Comparison results showed that the GIMs (with a 2 h temporal resolution) generated using the new approach can improve the determination of ionospheric TEC by 0.28 TEC units (TECU) over those from the Helmert-VCE-aided WLS approach (w.r.t CAS references, respectively) and by 1.61 TECU better than those from WLS, in terms of the mean of all root-mean-squares errors of all 2 h time slots in the 8-day testing period. In addition, in comparison with out-of-sample Jason-3 observations, results from the proposed method also outperformed Helmert-VCE-aided WLS, CAS and CODE models by 1.5, 2.4 and 2.4 TECU, respectively. Numéro de notice : A2019-352 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1210-7 Date de publication en ligne : 14/11/2018 En ligne : https://doi.org/10.1007/s00190-018-1210-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93398
in Journal of geodesy > vol 93 n°6 (June 2019) . - pp 877 - 888[article]Long-term soil moisture content estimation using satellite and climate data in agricultural area of Mongolia / Enkhjargal Natsagdorj in Geocarto international, vol 34 n° 7 ([01/06/2019])
PermalinkObject-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment / Eduarda M.O. Silveira in International journal of applied Earth observation and geoinformation, vol 78 (June 2019)
PermalinkThe cause of the 2011 Hawthorne (Nevada) earthquake swarm constrained by seismic and InSAR methods / Xianjie Zha in Journal of geodesy, vol 93 n°6 (June 2019)
PermalinkThe conservation status assessment of Natura 2000 forest habitats in Europe: capabilities, potentials and challenges of national forest inventories data / Iciar A. Alberdi in Annals of Forest Science, vol 76 n° 2 (June 2019)
PermalinkTree and stand level estimations of Abies alba Mill. aboveground biomass / Andrzej M. Jagodzinski in Annals of Forest Science, vol 76 n° 2 (June 2019)
PermalinkBayesian calibration of a carbon balance model PREBAS using data from permanent growth experiments and national forest inventory / Francesco Minunno in Forest ecology and management, vol 440 (15 May 2019)
PermalinkAbility of GPS PPP in 2D deformation analysis with respect to GPS network solution / C. Aydin in Survey review, vol 51 n° 366 (May 2019)
PermalinkAn artificial bee colony-based algorithm to automatically create colour schemes for geovisualizations / Mingguang Wu in Cartographic journal (the), Vol 56 n° 2 (May 2019)
PermalinkAn improved robust Kalman filtering strategy for GNSS kinematic positioning considering small cycle slips / Wanke Liu in Advances in space research, vol 63 n° 9 (1 May 2019)
PermalinkAssessing the latest performance of Galileo-only PPP and the contribution of Galileo to Multi-GNSS PPP / Fengyu Xiu in Advances in space research, vol 63 n° 9 (1 May 2019)
PermalinkAutomatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network / Jianfeng Huang in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
PermalinkDetecting and characterizing downed dead wood using terrestrial laser scanning / Tuomas Yrttimaa in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
PermalinkEstimating architecture-based metabolic scaling exponents of tropical trees using terrestrial LiDAR and 3D modelling / Alvaro Lau in Forest ecology and management, vol 439 (1 May 2019)
PermalinkEstimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
PermalinkExamining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change / Hao Wu in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)
PermalinkExploring semantic elements for urban scene recognition: Deep integration of high-resolution imagery and OpenStreetMap (OSM) / Wenzhi Zhao in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
PermalinkModel-based investigation on the effects of spatial evenness, and size selection in thinning of Picea abies stands / Peter Fransson in Scandinavian journal of forest research, vol 34 n° 3 (May 2019)
PermalinkA model for phased evacuations for disasters with spatio-temporal randomness / Menghui Li in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)
PermalinkMulti-temporal image change mining based on evidential conflict reasoning / Fatma Haouas in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
PermalinkPairwise coarse registration of point clouds in urban scenes using voxel-based 4-planes congruent sets / Yusheng Xu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
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