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Geomorphic analysis of Xiadian buried fault zone in Eastern Beijing plain based on SPOT image and unmanned aerial vehicle (UAV) data / Yanping Wang in Geomatics, Natural Hazards and Risk, vol 12 n° 1 (2021)  

Public [article]  inGeomatics, Natural Hazards and Risk > vol 12 n° 1 (2021) . - pp 261 - 278 Titre : Geomorphic analysis of Xiadian buried fault zone in Eastern Beijing plain based on SPOT image and unmanned aerial vehicle (UAV) data Type de document : Article/Communication Auteurs : Yanping Wang, Auteur ; Pinliang Dong, Auteur ; Yueqin Zhu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 261 - 278 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] auscultation topographique [Termes descripteurs IGN] déformation de la croute terrestre [Termes descripteurs IGN] données de terrain [Termes descripteurs IGN] effondrement de terrain [Termes descripteurs IGN] faille géologique [Termes descripteurs IGN] géomorphologie locale [Termes descripteurs IGN] image captée par drone [Termes descripteurs IGN] image SPOT 5 [Termes descripteurs IGN] MNS SRTM [Termes descripteurs IGN] modèle numérique de surface [Termes descripteurs IGN] Pékin (Chine) [Termes descripteurs IGN] réseau de drainage [Termes descripteurs IGN] zone à risque Résumé : (auteur) This study presents geomorphic analysis of Xiadian buried fault in eastern Beijing plain (China), based on the analysis of a Satellite Pour l’Observation de la Terre (SPOT-5) image, a high-resolution digital elevation model (DEM) derived from an unmanned aerial vehicle (UAV) system, SRTM DEM and field investigation. Interpretations of the SPOT-5 image show that the pits always distribute between fault scarp segments or shallow grooves. The geomorphic features near the fault show echelon arrangements caused by dextral strike-slip activities of the fault. Based on this, the characteristics of stress field in this area have been clearly inferred. At centimeter-level accuracy, UAV-derived DEM profiles can clearly show micro tectonic landforms such as fault scarps, shallow grooves, steep slopes, and pits. Combined with previous research and field measurements, the evolution rates in length and height of the fault scarps are analysed. Furthermore, the deflection analysis of the drainage system also shows the characteristics of the continuous strike slip activity of the Xiadian fault. The study can provide valuable insight into geomorphic analysis of buried and semi-buried active faults in plain areas with increasingly frequent human activities. Numéro de notice : A2021-108 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/19475705.2020.1870168 date de publication en ligne : 19/01/2021 En ligne : https://doi.org/10.1080/19475705.2020.1870168 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96905 [article]

A worldwide 3D GCP database inherited from 20 years of massive multi-satellite observations / Laure Chandelier in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2 (August 2020)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > V-2 (August 2020) . - pp 15 - 23 Titre : A worldwide 3D GCP database inherited from 20 years of massive multi-satellite observations Type de document : Article/Communication Auteurs : Laure Chandelier , Auteur ; Laurent Coeurdevey, Auteur ; Sébastien Bosch, Auteur ; Pascal Favé, Auteur ; Roland Gachet, Auteur ; Alain Orsoni, Auteur ; Thomas Tilak , Auteur ; Alexis Barot, Auteur Année de publication : 2020 Projets : 1-Pas de projet / Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 15 - 23 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] base de données d'images [Termes descripteurs IGN] compensation par bloc [Termes descripteurs IGN] données localisées de référence [Termes descripteurs IGN] formatage [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image multi sources [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] image SPOT 6 [Termes descripteurs IGN] image SPOT 7 [Termes descripteurs IGN] image SPOT-HRS [Termes descripteurs IGN] informatique en nuage [Termes descripteurs IGN] Institut national de l'information géographique et forestière (France) [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] spatiotriangulation Résumé : (auteur) High location accuracy is a major requirement for satellite image users. Target performance is usually achieved thanks to either specific on-board satellite equipment or an auxiliary registration reference dataset. Both methods may be expensive and with certain limitations in terms of performance. The Institut national de l’information géographique et forestière (IGN) and Airbus Defence and Space (ADS) have worked together for almost 20 years, to build reference data for improving image location using multi-satellite observations. The first geometric foundation created has mainly used SPOT 5 High Resolution Stereoscopic (HRS) imagery, ancillary Ground Control Points (GCP) and Very High Resolution (VHR) imagery, providing a homogenous location accuracy of 10m CE90 almost all over the world in 2010. Space Reference Points (SRP) is a new worldwide 3D GCP database, built from a plethoric SPOT 6/7 multi-view archive, largely automatically processed, with cloud-based technologies. SRP aims at providing a systematic and reliable solution for image location (Unmanned Aerial Vehicle, VHR satellite imagery, High Altitudes Pseudo-Satellite…) and similar topics thanks to a high-density point distribution with a 3m CE90 accuracy. This paper describes the principle of SRP generation and presents the first validation results. A SPOT 6/7 smart image selection is performed to keep only relevant images for SRP purpose. The location of these SPOT 6/7 images is refined thanks to a spatiotriangulation on the worldwide geometric foundation, itself improved where needed. Points making up the future SRP database are afterward extracted thanks to classical feature detection algorithms and with respect to the expected density. Different filtering methods are applied to keep the best candidates. The last step of the processing chain is the formatting of the data to the delivery format, including metadata. An example of validation of SRP concept and specification on two tests sites (Spain and China) is then given. As a conclusion, the on-going production is shortly presented. Numéro de notice : A2020-474 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-15-2020 date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-15-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95613 [article]

A new stochastic simulation algorithm for image-based classification : Feature-space indicator simulation / Qing Wang in ISPRS Journal of photogrammetry and remote sensing, vol 152 (June 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 152 (June 2019) . - pp 145 - 165 Titre : A new stochastic simulation algorithm for image-based classification : Feature-space indicator simulation Type de document : Article/Communication Auteurs : Qing Wang, Auteur ; Hua Sun, Auteur ; Ruopu Li, Auteur ; Guangxing Wang, Auteur Année de publication : 2019 Article en page(s) : pp 145 - 165 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] forêt [Termes descripteurs IGN] géostatistique [Termes descripteurs IGN] image Landsat-OLI [Termes descripteurs IGN] image SPOT 5 [Termes descripteurs IGN] Mongolie intérieure (Chine) [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] utilisation du sol [Termes descripteurs IGN] variogramme Résumé : (Auteur) Traditional parametric methods for classification of land use and land cover (LULC) types using remote sensing imagery assume a global distribution model and fail to consider local variation of categorical variables. Differently, non-parametric methods do not make any statistical assumptions but are typically sensitive to the sample sizes of training sample data that usually require a high cost to collect in the field. Geostatistical classifiers, such as indicator kriging and simulation, are local variability-based methods that exhibit great potential for image-based classification of LULC types. However, variogram models required are highly sensitive to the spatial configuration of training samples as well as sample size given a study area. Moreover, when a large number of spectral variables are considered into kriging systems, modeling the variograms and cross-variograms would be problematic. To circumvent these issues, this study extended the geostatistical methods from a 2-dimensional geographic space to a m-dimensional image feature space to derive feature-space indicator variograms (FSIVs). Moreover, a novel stochastic simulation classification algorithm, Feature-Space Indicator Simulation (FSIS), was proposed and examined for classification of LULC types in Duolun County located in Inner Mongolia and in Huang-Feng-Qiao (HFQ) forest farm, Hunan of China. In Duolun, six LULC types were involved and in HFQ a complicated forest landscape consisting of nine forest types plus water, built-up area, and agricultural/bare soil, was classified. The classification results of FSIS were compared with another feature-space geostatistical classifier – feature-space indicator kriging (FSIK), a traditional parametric method – maximum likelihood (ML), a widely used nonparametric method – support vector machine (SVM), and a recently popular method – random forest (RF). The results showed that compared with ML, SVM and RF, in both study areas FSIS statistically significantly increased the accuracy of the classifications by 10.0–29.9% for percentage correct and 19.0–47.6% for Kappa statistic. Compared with FSIK, FSIS also improved the classification accuracy but the accuracy increases were relatively smaller with the percentages correct of 3.5% and 7.6% and the Kappa values of 4.6% and 8.6% for Duolun and HFQ, respectively. Moreover, FSIS led to the spatial uncertainties of the classification estimates as the quality measure of the estimates. In addition, the results also demonstrated that FSIVs were sensitive to the within-class heterogeneity but not very much to the size of training samples. Overall, FSIS exhibited the greater potential to improve the classification accuracy of LULC and forest types using remote sensing image. Numéro de notice : A2019-457 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.04.011 date de publication en ligne : 25/04/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.04.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92871 [article]

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Object-based crop classification using multi-temporal SPOT-5 imagery and textural features with a Random Forest classifier / Huanxue Zhang in Geocarto international, vol 33 n° 10 (October 2018)  

Public [article]  inGeocarto international > vol 33 n° 10 (October 2018) . - pp 1017 - 1035 Titre : Object-based crop classification using multi-temporal SPOT-5 imagery and textural features with a Random Forest classifier Type de document : Article/Communication Auteurs : Huanxue Zhang, Auteur ; Qiangzi Li, Auteur ; Jiangui Liu, Auteur ; Taifeng Dong, Auteur ; Heather McNairn, Auteur Année de publication : 2018 Article en page(s) : pp 1017 - 1035 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] bande spectrale [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] corrélation par régions de niveaux de gris [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] image SPOT 5 [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] limite de terrain [Termes descripteurs IGN] Ontario (Canada) [Termes descripteurs IGN] réflectance spectrale [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] surface cultivée [Termes descripteurs IGN] surveillance agricole [Termes descripteurs IGN] texture [Termes descripteurs IGN] variogramme Résumé : (auteur) In this study, an object-based image analysis (OBIA) approach was developed to classify field crops using multi-temporal SPOT-5 images with a random forest (RF) classifier. A wide range of features, including the spectral reflectance, vegetation indices (VIs), textural features based on the grey-level co-occurrence matrix (GLCM) and textural features based on geostatistical semivariogram (GST) were extracted for classification, and their performance was evaluated with the RF variable importance measures. Results showed that the best segmentation quality was achieved using the SPOT image acquired in September, with a scale parameter of 40. The spectral reflectance and the GST had a stronger contribution to crop classification than the VIs and GLCM textures. A subset of 60 features was selected using the RF-based feature selection (FS) method, and in this subset, the near-infrared reflectance and the image acquired in August (jointing and heading stages) were found to be the best for crop classification. Numéro de notice : A2019-049 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1333533 date de publication en ligne : 23/06/2017 En ligne : https://doi.org/10.1080/10106049.2017.1333533 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92063 [article]

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Predicting tree diameter distributions from airborne laser scanning, SPOT 5 satellite, and field sample data in the perm region, Russia / Jussi Peuhkurinen in Forests, vol 9 n° 10 (October 2018)  

Public [article]  inForests > vol 9 n° 10 (October 2018) Titre : Predicting tree diameter distributions from airborne laser scanning, SPOT 5 satellite, and field sample data in the perm region, Russia Type de document : Article/Communication Auteurs : Jussi Peuhkurinen, Auteur ; Timo Tokola, Auteur ; Kseniia Plevak, Auteur ; Sanna Sirparanta, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Abies sibirica [Termes descripteurs IGN] alnus incana [Termes descripteurs IGN] Betula pendula [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] diamètre des arbres [Termes descripteurs IGN] données de terrain [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image SPOT 5 [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] Picea abies [Termes descripteurs IGN] Pinus sibirica [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] placette d'échantillonnage [Termes descripteurs IGN] Populus tremula [Termes descripteurs IGN] Russie [Termes descripteurs IGN] Salix caprea [Termes descripteurs IGN] tilia cordata [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) A tree list is a list of trees in the area of interest containing, for example, the species, diameter, height, and stem volume of each tree. Tree lists can be used to derive various characteristics of the growing stock, and are therefore versatile and informative sources of data for several forest management purposes. Especially in heterogonous and unmanaged forest structures with multiple species, tree list estimates imputed from local reference field data can provide an alternative to mean value estimates of growing stock (e.g., basal area, total stem volume, mean tree diameter, mean tree height, and number of trees). In this study, reference field plots, airborne laser scanning (ALS) data, and SPOT 5 satellite (Satellite Pour l’Observation de la Terre) imagery were used for tree list imputation applying the k most similar neighbors (k-MSN) estimation method in the West Ural taiga region of the Russian Federation for diameter distribution estimation. In k-MSN, weighted average of k field reference plots with highest similarity between field reference plot and target (forest grid cell, or field plot) based on ALS and SPOT 5 features were used to predict the mean values of growing stock and tree lists for the target object simultaneously. Diameter distributions were then constructed from the predicted tree lists. The prediction of mean values and diameter distributions was tested in 18 independent validation plots of 0.25–0.5 ha in size, whose species specific diameter distributions were measured in the field and grouped into three functional groups (Pines, Spruce/Fir, Broadleaf Group), each containing several species. In terms of root mean squared error relative to mean of validation plots, the accuracy of estimation was 0.14 and 0.17 for basal area and total stem volume, respectively. Reynolds error index values and visual inspection showed encouraging results in evaluating the goodness-of-fit statistics of the estimated diameter distributions. Although estimation accuracy was worse for functional group mean values and diameter distributions, the results indicate that it is possible to predict diameter distributions in forests of the test area with the tested methodology and materials. Numéro de notice : A2018-476 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f9100639 date de publication en ligne : 13/10/2018 En ligne : https://doi.org/10.3390/f9100639 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91176 [article]

Assessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja, Nigeria / Christopher Ifechukwude Chima in Geocarto international, vol 33 n° 9 (September 2018)  

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Stand-volume estimation from multi-source data for coppiced and high forest Eucalyptus spp. silvicultural systems in KwaZulu-Natal, South Africa / Timothy Dube in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)  

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A Stepwise-Then-Orthogonal Regression (STOR) with quality control for optimizing the RFM of high-resolution satellite imagery / Chang Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 9 (September 2017)  

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Monitoring mangrove biomass change in Vietnam using SPOT images and an object-based approach combined with machine learning algorithms / Lien T.H. Pham in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)  

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Distinctive order based self-similarity descriptor for multi-sensor remote sensing image matching / Amin Sedaghat in ISPRS Journal of photogrammetry and remote sensing, vol 108 (October 2015)  

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Cartographie du châtaignier en Alsace par imagerie satellite multi-date / Colette Meyer in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)

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Improving the spatial resolution of landsat TM/ETM+ through fusion with SPOT5 images via learning-based super-resolution / Huihui Song in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)  

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Etude de l'évolution de l'utilisation du sol dans le district Sunsari (plaine du Népal) depuis les années 1950 / Mathilde Dumont-Aublin (2015) 

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Etude expérimentale en cartographie de la végétation par télédétection / Vanessa Sellin in Cybergeo, European journal of geography, n° 2015 ([01/01/2015])  

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Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery / Mustafa Neamah Jebur in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)  

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