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Exploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region / Tao Zhou in ISPRS International journal of geo-information, vol 7 n° 1 (January 2018)  

Public [article]  inISPRS International journal of geo-information > vol 7 n° 1 (January 2018) Titre : Exploring the impact of seasonality on urban land-cover mapping using multi-season sentinel-1A and GF-1 WFV images in a subtropical monsoon-climate region Type de document : Article/Communication Auteurs : Tao Zhou, Auteur ; Meifang Zhao, Auteur ; Chuanliang Sun, Auteur ; Jianjun Pan, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte d'occupation du sol [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image GF-1 [Termes IGN] image Sentinel-SAR [Termes IGN] Kiangsou (Chine) [Termes IGN] surface imperméable [Termes IGN] variation saisonnière [Termes IGN] zone urbaine Résumé : (Auteur) The objective of this research was to investigate the impact of seasonality on urban land-cover mapping and to explore better classification accuracy by using multi-season Sentinel-1A and GF-1 wide field view (WFV) images, and the combinations of both types of images in subtropical monsoon-climate regions in Southeast China. We obtained multi-season Sentinel-1A and GF-1 WFV images, as well as the combinations of both data, by using a support vector machine (SVM) and a random forest (RF) classifier. The backscatter intensity, texture, and interference-coherence images were extracted from Sentinel-1A images, and different combinations of these Sentinel-1A-derived images were used to evaluate their ability to map urban land cover. The results showed that the performance of winter images was better than that of any other season, while the summer images performed the worst. Higher classification accuracy was achieved by using multi-season images, and satisfactory classification results were obtained when using Sentinel-1A images from only three seasons. The best classification result was achieved using a combination of all Sentinel-1A data from all four seasons and GF-1 WFV data from winter, with an overall accuracy of up to 96.02% and a kappa coefficient reaching 0.9502. The performance of textures was slightly better than that of the backscatter-intensity images. Although the coherence data performed the worst, it was still able to distinguish urban impervious surfaces well. In addition, the overall classification accuracy of RF was better than that of SVM. Numéro de notice : A2018-040 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi7010003 En ligne : https://doi.org/10.3390/ijgi7010003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89262 [article]

Combined calibration method based on rational function model for the Chinese GF-1 wide-field-of-view imagery / Taoyang Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 4 (April 2016)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 4 (April 2016) . - pp 291 - 298 Titre : Combined calibration method based on rational function model for the Chinese GF-1 wide-field-of-view imagery Type de document : Article/Communication Auteurs : Taoyang Wang, Auteur ; Guo Zhang, Auteur ; Yonghua Jiang, Auteur Année de publication : 2016 Article en page(s) : pp 291 - 298 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] champ visuel [Termes IGN] échantillonnage d'image [Termes IGN] étalonnage de capteur (imagerie) [Termes IGN] image GF-1 [Termes IGN] modèle par fonctions rationnelles [Termes IGN] orientation interne Résumé : (auteur) The internal geometric distortion of charge-coupled-device (CCD) chips degrades the internal geometric accuracy of satellite images. Even if a large number of ground control points (GCPs) are used for geometric correction, the satellite images cannot always be used for direct mapping. Because of the current lack of core parameters for building a rigorous geometric model, this paper proposes a combined interior-orientation calibration method based on the rational function model (RFM) for multiple GF-1 wide-field-of-view (WFV) images of the same general scene. A polynomial model of look angles in the image space is chosen to compensate for the systemic error of CCD chips. After calibration for sensors 1 to 4, the orientation accuracy is improved to 0.4 pixels. Moreover, the residual error figures show no obvious trend. Other GF-1 WFV images are calibrated using the obtained interior-orientation parameters, and the improvement in their orientation accuracy is demonstrated to validate the effectiveness of the proposed method. Numéro de notice : A2016-181 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.82.4.291 En ligne : https://doi.org/10.14358/PERS.82.4.291 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80524 [article]