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Complete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China / Kun Tan in ISPRS Journal of photogrammetry and remote sensing, vol 165 (July 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 165 (July 2020) . - pp 1 - 15 Titre : Complete and accurate data correction for seamless mosaicking of airborne hyperspectral images: A case study at a mining site in Inner Mongolia, China Type de document : Article/Communication Auteurs : Kun Tan, Auteur ; Chao Niu, Auteur ; Xiuping Jia, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 1 - 15 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] atténuation [Termes IGN] correction atmosphérique [Termes IGN] distorsion du signal [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] image hyperspectrale [Termes IGN] mine [Termes IGN] Mongolie intérieure (Chine) [Termes IGN] mosaïquage d'images [Termes IGN] radiance [Termes IGN] rayonnement infrarouge [Termes IGN] réflectance de surface [Termes IGN] Short Waves InfraRed [Termes IGN] spectroradiométrie [Termes IGN] surveillance écologique Résumé : (auteur) Airborne hyperspectral remote sensing is an important application in the ecological monitoring of the environment in mining areas, and accurate preprocessing of the original images is the key to quantitative information retrieval. The original image data need radiation correction to acquire surface reflectance data. Due to the impact of the field angle, incidental radiance, and the bidirectional reflectance distribution function (BRDF), there can be a brightness gradient between adjacent strips, which leads to radiance difference and obvious chromatic aberration of the mosaicked images. We propose a novel data correction method for seamless mosaicking of airborne hyperspectral images. Firstly, visible and near-infrared (VNIR) and shortwave infrared (SWIR) sensors are calibrated in the laboratory, and the radiation calibration model of the sensor is established by an integrating-sphere system. A correction function is then established by combining the BRDF effect and the radiation attenuation coefficients. We also normalize the exposure time, sun altitude angle, and sensor altitude angle according to the flight strip. The results showed that this method is able to eliminate the signal distortion, allowing the seamless mosaicking of 37 strip images which were taken in different date and conditions in the study area. After the atmospheric correction of the imagery was completed, the accuracy of the preprocessing results was evaluated by field-measured ASD spectroradiometer data. The coefficient of determination R2 of the results for the reflectance was greater than 0.9. The experiments show that the proposed method has a good performance in radiation accuracy, and can provide high-quality hyperspectral data for the follow-up application of the ecological monitoring of a mining area. Numéro de notice : A2020-465 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.04.022 Date de publication en ligne : 16/05/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.04.022 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95092 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2020071	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2020073	DEP-RECP	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2020072	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Change detection based on stacked generalization system with segmentation constraint / Kun Tan in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 11 (November 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 11 (November 2018) . - pp 733 - 741 Titre : Change detection based on stacked generalization system with segmentation constraint Type de document : Article/Communication Auteurs : Kun Tan, Auteur ; Yusha Zhang, Auteur ; Qian Du, Auteur ; Peijun Du, Auteur ; Xiao Jin, Auteur ; Jiayi Li, Auteur Année de publication : 2018 Article en page(s) : pp 733 - 741 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] détection de changement [Termes IGN] image Quickbird [Termes IGN] image ZiYuan-3 [Termes IGN] segmentation d'image Résumé : (Auteur) Change detection based on a multi-classifier ensemble system can take advantage of multiple classifiers to extract change information in remote sensing images. In this paper, an efficient heterogeneous ensemble algorithm, i.e., the stacked generalization (SG) combined with image segmentation, is proposed to construct a simple multi-classifier ensemble system that can offer better detection accuracy with lower computational cost. Due to the rich spatial information in high-spatial-resolution remote sensing images, structure texture (morphological) and statistical texture features are extracted to construct the input data to the ensemble system along with spectral features. In addition, constrained analysis on segmented objects integrates the smaller heterogeneity segmentation map and pixel-wise change map to generate the final change map. The experiments were carried out on two ZY-3 and a QuickBird dataset. The results show that the proposed algorithm can integrate the advantages of both pixel-wise ensemble and object-oriented methods, and effectively improve the accuracy and stability of change detection. Numéro de notice : A2018-485 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.11.733 Date de publication en ligne : 01/11/2018 En ligne : https://doi.org/10.14358/PERS.84.11.733 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91210 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2018111	RAB	Revue	Centre de documentation	En réserve L003	Disponible