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Integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images / Yijie Tang in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 130 - 150 Titre : Integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images Type de document : Article/Communication Auteurs : Yijie Tang, Auteur ; Qunming Wang, Auteur ; Xiaohua Tong, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 130 - 150 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] données spatiotemporelles [Termes IGN] fusion d'images [Termes IGN] image multibande [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-OLCI [Termes IGN] pouvoir de résolution géométrique [Termes IGN] réduction d'échelle [Termes IGN] réflectance Résumé : (auteur) Sentinel-3 is a newly launched satellite implemented by the European Space Agency (ESA) for global observation. The Ocean and Land Colour Imager (OLCI) sensor onboard Sentinel-3 provides 21 band images with a fine spectral resolution and is of great value for ocean, land and atmospheric monitoring. The two platforms (Sentinel-3A and -3B) can provide OLCI images at an almost daily temporal resolution. The coarse spatial resolution of the 21 band OLCI images (i.e., 300 m), however, limits greatly their utility for local, precise monitoring. Sentinel-2, another satellite provided by ESA, carries the Multispectral Imager (MSI) sensor which can supply much finer spatial resolution (e.g., 10 m and 20 m) images. This paper introduces a new fusion framework integrating spatio-temporal-spectral information for downscaling Sentinel-3 OLCI images, which has two parts. Based on bands with similar wavelengths (i.e., bands 2, 3, 4 and 8a for Sentinel-2 and bands Oa4, Oa6, Oa8 and Oa17 for Sentinel-3), the four Sentinel-3 bands are first downscaled to the spatial resolution of Sentinel-2 images by applying spatio-temporal fusion to Sentinel-2 MSI and Sentinel-3 OLCI images. Then, to take full advantage of all 21 available OLCI bands of the Sentinel-3 images, the extended image pair-based spatio-spectral fusion (EIPSSF) method is proposed in this paper to downscale the other 17 bands. EIPSSF is performed based on the new concept of the extended image pair (EIP) and by exploiting existing spatio-temporal fusion approaches. The framework consisting of spatio-temporal and spatio-spectral fusion is entirely general, which provides a practical solution for comprehensive downscaling of Sentinel-3 OLCI images for fine spatial, temporal and spectral resolution monitoring. Numéro de notice : A2021-654 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.08.012 Date de publication en ligne : 24/08/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.08.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98384 [article]

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A review of assessment methods for cellular automata models of land-use change and urban growth / Xiaohua Tong in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 5 (May 2020) . - pp 866 - 898 Titre : A review of assessment methods for cellular automata models of land-use change and urban growth Type de document : Article/Communication Auteurs : Xiaohua Tong, Auteur ; Yongjiu Feng, Auteur Année de publication : 2020 Article en page(s) : pp 866 - 898 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de sensibilité [Termes IGN] analyse du paysage [Termes IGN] automate cellulaire [Termes IGN] changement d'occupation du sol [Termes IGN] croissance urbaine [Termes IGN] dynamique de la végétation [Termes IGN] dynamique spatiale [Termes IGN] Kappa de Cohen [Termes IGN] matrice [Termes IGN] modèle de simulation [Termes IGN] population urbaine [Termes IGN] propagation d'erreur Résumé : (auteur) Cellular automata (CA) models are in growing use for land-use change simulation and future scenario prediction. It is necessary to conduct model assessment that reports the quality of simulation results and how well the models reproduce reliable spatial patterns. Here, we review 347 CA articles published during 1999–2018 identified by a Scholar Google search using ‘cellular automata’, ‘land’ and ‘urban’ as keywords. Our review demonstrates that, during the past two decades, 89% of the publications include model assessment related to dataset, procedure and result using more than ten different methods. Among all methods, cell-by-cell comparison and landscape analysis were most frequently applied in the CA model assessment; specifically, overall accuracy and standard Kappa coefficient respectively rank first and second among all metrics. The end-state assessment is often criticized by modelers because it cannot adequately reflect the modeling ability of CA models. We provide five suggestions to the method selection, aiming to offer a background framework for future method choices as well as urging to focus on the assessment of input data and error propagation, procedure, quantitative and spatial change, and the impact of driving factors. Numéro de notice : A2020-809 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1684499 Date de publication en ligne : 05/11/2019 En ligne : https://doi.org/10.1080/13658816.2019.1684499 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94880 [article]

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A novel fire index-based burned area change detection approach using Landsat-8 OLI data / Sicong Liu in European journal of remote sensing, vol 53 n° 1 (2020)  

Public [article]  inEuropean journal of remote sensing > vol 53 n° 1 (2020) . - pp 104 - 112 Titre : A novel fire index-based burned area change detection approach using Landsat-8 OLI data Type de document : Article/Communication Auteurs : Sicong Liu, Auteur ; Yongjie Zheng, Auteur ; Michele Dalponte, Auteur ; Xiaohua Tong, Auteur Année de publication : 2020 Article en page(s) : pp 104 - 112 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] brûlis [Termes IGN] détection de changement [Termes IGN] image Landsat-OLI [Termes IGN] image multibande [Termes IGN] image multitemporelle [Termes IGN] incendie de forêt [Termes IGN] seuillage d'image [Termes IGN] signature spectrale Résumé : (auteur) Change detection from multi-temporal remote sensing images is an effective way to identify the burned areas after forest fires. However, the complex image scenario and the similar spectral signatures in multispectral bands may lead to many false positive errors, which make it difficult to exact the burned areas accurately. In this paper, a novel-burned area change detection approach is proposed. It is designed based on a new Normalized Burn Ratio-SWIR (NBRSWIR) index and an automatic thresholding algorithm. The effectiveness of the proposed approach is validated on three Landsat-8 data sets presenting various fire disaster events worldwide. Compared to eight index-based detection methods that developed in the literature, the proposed approach has the best performance in terms of class separability (2.49, 1.74 and 2.06) and accuracy (98.93%, 98.57% and 99.51%) in detecting the burned areas. Simultaneously, it can also better suppress the complex irrelevant changes in the background. Numéro de notice : A2020-167 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/22797254.2020.1738900 Date de publication en ligne : 16/03/2020 En ligne : https://doi.org/10.1080/22797254.2020.1738900 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94836 [article]

A new cellular automata framework of urban growth modeling by incorporating statistical and heuristic methods / Yongjiu Feng in International journal of geographical information science IJGIS, vol 34 n° 1 (January 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 1 (January 2020) . - pp 74 - 97 Titre : A new cellular automata framework of urban growth modeling by incorporating statistical and heuristic methods Type de document : Article/Communication Auteurs : Yongjiu Feng, Auteur ; Xiaohua Tong, Auteur Année de publication : 2020 Article en page(s) : pp 74 - 97 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de données [Termes IGN] automate cellulaire [Termes IGN] croissance urbaine [Termes IGN] données spatiotemporelles [Termes IGN] dynamique spatiale [Termes IGN] méthode heuristique [Termes IGN] modèle de Markov [Termes IGN] modèle de simulation [Termes IGN] Shanghai (Chine) [Termes IGN] utilisation du sol Résumé : (auteur) We develop a new geographical cellular automata (CA) modeling framework, named UrbanCA, through reconstructing the essential CA structure and incorporating nonspatial, spatial, and heuristic approaches. The new UrbanCA is featured by 1) the improvement of the CA modeling framework by reformulating relationships among CA components, 2) the development of two scaling parameters to adjust the effects of transition probability and neighborhood, 3) the incorporation of a variety of statistical and heuristic methods to construct transition rules, and 4) the inclusion of urban planning regulations and spatial heterogeneities to project future urban scenarios. To illustrate the effectiveness of UrbanCA, we calibrate a CA model using artificial bee colony (ABC) to simulate the past urban patterns and predict future scenarios in Shanghai of China. The results show that UrbanCA under different scaling parameters is comparable to CA-Markov (as a reference model) concerning the accuracy of the end-state and change simulations, and is better than CA-Markov regarding the driving factor’s ability to explain the modeling outcomes. UrbanCA provides more choices compared to existing CA software packages, and the models are readily calibrated elsewhere to simulate the dynamic urban growth and assess the resulting natural and socioeconomic impacts. Numéro de notice : A2020-008 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1648813 Date de publication en ligne : 02/08/2019 En ligne : https://doi.org/10.1080/13658816.2019.1648813 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94388 [article]

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LRAGE : learning latent relationships with adaptive graph embedding for aerial scene classification / Yuebin Wang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 2 (February 2018)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 56 n° 2 (February 2018) . - pp 621 - 634 Titre : LRAGE : learning latent relationships with adaptive graph embedding for aerial scene classification Type de document : Article/Communication Auteurs : Yuebin Wang, Auteur ; Liqiang Zhang, Auteur ; Xiaohua Tong, Auteur ; Feiping Nie, Auteur ; Haiyang Huang, Auteur ; Jie Mei, Auteur Année de publication : 2018 Article en page(s) : pp 621 - 634 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage automatique [Termes IGN] classification semi-dirigée [Termes IGN] graphe [Termes IGN] image aérienne [Termes IGN] programmation par contraintes [Termes IGN] régression linéaire [Termes IGN] scène Résumé : (Auteur) The performance of scene classification relies heavily on the spatial and structural features that are extracted from high spatial resolution remote-sensing images. Existing approaches, however, are limited in adequately exploiting latent relationships between scene images. Aiming to decrease the distances between intraclass images and increase the distances between interclass images, we propose a latent relationship learning framework that integrates an adaptive graph with the constraints of the feature space and label propagation for high-resolution aerial image classification. To describe the latent relationships among scene images in the framework, we construct an adaptive graph that is embedded into the constrained joint space for features and labels. To remove redundant information and improve the computational efficiency, subspace learning is introduced to assist in the latent relationship learning. To address out-of-sample data, linear regression is adopted to project the semisupervised classification results onto a linear classifier. Learning efficiency is improved by minimizing the objective function via the linearized alternating direction method with an adaptive penalty. We test our method on three widely used aerial scene image data sets. The experimental results demonstrate the superior performance of our method over the state-of-the-art algorithms in aerial scene image classification. Numéro de notice : A2018-189 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2752217 Date de publication en ligne : 24/10/2017 En ligne : https://doi.org/10.1109/TGRS.2017.2752217 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89854 [article]

Discriminative-dictionary-learning-based multilevel point-cluster features for ALS point-cloud classification / Zhenxin Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 12 (December 2016)  

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A multilevel point-cluster-based discriminative feature for ALS point cloud classification / Zhenxin Zhang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)  

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Attraction-repulsion model-based subpixel mapping of multi-/hyperspectral imagery / Xiaohua Tong in IEEE Transactions on geoscience and remote sensing, vol 51 n° 5 Tome 1 (May 2013)  

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Use of shadows for detection of earthquake-induced collapsed buildings in high-resolution satellite imagery / Xiaohua Tong in ISPRS Journal of photogrammetry and remote sensing, vol 79 (May 2013)  

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