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scientifique

Framework for automatic coral reef extraction using Sentinel-2 image time series / Qizhi Zhang in Marine geodesy, vol 45 n° 3 (May 2022)  

Public [article]  inMarine geodesy > vol 45 n° 3 (May 2022) . - pp 195 - 231 Titre : Framework for automatic coral reef extraction using Sentinel-2 image time series Type de document : Article/Communication Auteurs : Qizhi Zhang, Auteur ; Jian Zhang, Auteur ; Liang Cheng, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 195 - 231 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Chine [Termes IGN] extraction de traits caractéristiques [Termes IGN] filtrage de points [Termes IGN] filtrage spatiotemporel [Termes IGN] image Sentinel-MSI [Termes IGN] mesure de similitude [Termes IGN] nébulosité [Termes IGN] récif corallien [Termes IGN] série temporelle Résumé : (auteur) Using supervised and unsupervised classification on a single image to extract coral reef extent results in missing data and wrong extraction results. To improve the accuracy of coral reef extraction, this study proposes a novel technical framework for automatic coral reef extraction based on an image filtering strategy and spatiotemporal similarity measurements of pixel-level Sentinel-2 image time series. This method was applied to the Anda Reef, Daxian Reef, and Nanhua Reef, China, using 1464 Sentinel-2 images obtained from 2015–2020. Sentinel-2 images were automatically selected considering space, time, cloud cover, and image entropy after atmospheric correction. With the binary classification measurement standard using the digitization coral reef results of the Sentinel-2 images as the true value, the time series established by the modified normalized difference water index demonstrated high robustness and accuracy. Analyzing the time series curves of the coral reef and deep water verified that the spatiotemporal similarity measurement of this framework can stably extract the boundaries of the coral reef. Numéro de notice : A2022-353 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1080/01490419.2022.2051648 Date de publication en ligne : 28/03/2022 En ligne : https://doi.org/10.1080/01490419.2022.2051648 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100550 [article]

Use of LiDAR for calculating solar irradiance on roofs and façades of buildings at city scale: Methodology, validation, and analysis / Liang Cheng in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 138 (April 2018) . - pp 12 - 29 Titre : Use of LiDAR for calculating solar irradiance on roofs and façades of buildings at city scale: Methodology, validation, and analysis Type de document : Article/Communication Auteurs : Liang Cheng, Auteur ; Hao Xu, Auteur ; Shuyi Li, Auteur ; Yanming Chen, Auteur ; Fangli Zhang, Auteur ; Manchun Li, Auteur Année de publication : 2018 Article en page(s) : pp 12 - 29 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] éclairement lumineux [Termes IGN] façade [Termes IGN] milieu urbain [Termes IGN] rayonnement solaire [Termes IGN] toit Résumé : (Auteur) As the rate of urbanization continues to accelerate, the utilization of solar energy in buildings plays an increasingly important role in sustainable urban development. For this purpose, we propose a LiDAR-based joint approach for calculating the solar irradiance incident on roofs and façades of buildings at city scale, which includes a methodology for calculating solar irradiance, the validation of the proposed method, and analysis of its application. The calculation of surface irradiance on buildings may then inform photovoltaic power generation simulations, architectural design, and urban energy planning. Application analyses of the proposed method in the experiment area found that: (1) Global and direct irradiations vary significantly by hour, day, month and season, both following the same trends; however, diffuse irradiance essentially remains unchanged over time. (2) Roof irradiation, but not façade irradiation, displays distinct time-dependent patterns. (3) Global and direct irradiations on roofs are highly correlated with roof aspect and slope, with high global and direct irradiations observed on roofs of aspect 100–250° and slopes of 0–60°, whereas diffuse irradiation on roofs is only affected by roof slope. (4) The façade of a building receives higher levels of global and direct irradiations if facing southeast, south, and southwest; however, diffuse irradiation remains constant regardless of façade orientation. Numéro de notice : A2018-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.024 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89568 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2018041	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2018043	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2018042	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery / Lei Ma in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 14 - 27 Titre : Training set size, scale, and features in Geographic Object-Based Image Analysis of very high resolution unmanned aerial vehicle imagery Type de document : Article/Communication Auteurs : Lei Ma, Auteur ; Liang Cheng, Auteur ; Manchung Li, Auteur ; Yongxue Liu, Auteur ; Xiaoxue Ma, Auteur Année de publication : 2015 Article en page(s) : pp 14 - 27 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] classification orientée objet [Termes IGN] drone [Termes IGN] échelle de prise de vue [Termes IGN] image à ultra haute résolution [Termes IGN] image aérienne [Termes IGN] image optique [Termes IGN] taille du jeu de données Résumé : (auteur) Unmanned Aerial Vehicle (UAV) has been used increasingly for natural resource applications in recent years due to their greater availability and the miniaturization of sensors. In addition, Geographic Object-Based Image Analysis (GEOBIA) has received more attention as a novel paradigm for remote sensing earth observation data. However, GEOBIA generates some new problems compared with pixel-based methods. In this study, we developed a strategy for the semi-automatic optimization of object-based classification, which involves an area-based accuracy assessment that analyzes the relationship between scale and the training set size. We found that the Overall Accuracy (OA) increased as the training set ratio (proportion of the segmented objects used for training) increased when the Segmentation Scale Parameter (SSP) was fixed. The OA increased more slowly as the training set ratio became larger and a similar rule was obtained according to the pixel-based image analysis. The OA decreased as the SSP increased when the training set ratio was fixed. Consequently, the SSP should not be too large during classification using a small training set ratio. By contrast, a large training set ratio is required if classification is performed using a high SSP. In addition, we suggest that the optimal SSP for each class has a high positive correlation with the mean area obtained by manual interpretation, which can be summarized by a linear correlation equation. We expect that these results will be applicable to UAV imagery classification to determine the optimal SSP for each class. Numéro de notice : A2015-692 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.12.026 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.12.026 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78323 [article]

Spectral–spatial classification of hyperspectral data via morphological component analysis-based image separation / Zhaohui Xue in IEEE Transactions on geoscience and remote sensing, vol 53 n° 1 (January 2015)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 53 n° 1 (January 2015) . - pp 70 - 84 Titre : Spectral–spatial classification of hyperspectral data via morphological component analysis-based image separation Type de document : Article/Communication Auteurs : Zhaohui Xue, Auteur ; Jun Li, Auteur ; Liang Cheng, Auteur ; Peijun Du, Auteur Année de publication : 2015 Article en page(s) : pp 70 - 84 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse en composantes indépendantes [Termes IGN] classification spectrale [Termes IGN] image hyperspectrale Résumé : (Auteur) This paper presents a new spectral-spatial classification method for hyperspectral images via morphological component analysis-based image separation rationale in sparse representation. The method consists of three main steps. First, the high-dimensional spectral domain of hyperspectral images is reduced into a low-dimensional feature domain by using minimum noise fraction (MNF). Second, the proposed separation method is acted on each features to generate the morphological components (MCs), i.e., the content and texture components. To this end, the dictionaries for these two components are built by using local curvelet and Gabor wavelet transforms within the randomly chosen image partitions. Then, sparse coding of one of the MCs and update of the associated dictionary are sequentially performed with the other one fixed. To better direct the separation process, an undecimated Haar wavelet with soft threshold is performed for the content component to make it smooth. This process is repeated until some stopping criterion is met. Finally, a support vector machine is adopted to obtain the classification maps based on the MCs. The experimental results with hyperspectral images collected by the National Aeronautics and Space Administration Jet Propulsion Laboratory's Airborne Visible/Infrared Imaging Spectrometer and the Reflective Optics Spectrographic Imaging System indicate that the proposed scheme provides better performance when compared with other widely used methods. Numéro de notice : A2015-029 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2318332 En ligne : https://doi.org/10.1109/TGRS.2014.2318332 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75110 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2015011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Automatic registration of coastal remotely sensed imagery by affine invariant feature matching with shoreline constraint / Liang Cheng in Marine geodesy, vol 37 n° 1 (March - May 2014)  

Public [article]  inMarine geodesy > vol 37 n° 1 (March - May 2014) . - pp 32 - 46 Titre : Automatic registration of coastal remotely sensed imagery by affine invariant feature matching with shoreline constraint Type de document : Article/Communication Auteurs : Liang Cheng, Auteur ; Lihua Tong, Auteur ; Yongxue Liu, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 32 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] appariement d'images [Termes IGN] couple stéréoscopique [Termes IGN] littoral [Termes IGN] Ransac (algorithme) [Termes IGN] télédétection spatiale [Termes IGN] trait de côte Résumé : (Auteur) A new approach based on Affine Invariant Feature Matching (AIFM) with a filtering technique is proposed for automatic registration of remotely sensed image in coastal areas. The novelty of this approach is an automatic filtering technique using RANdom SAmple Consensus (RANSAC) with shoreline constraint for AIFM to remove all wrong matches and simultaneously keep as many correct matches as possible. To implement it, a progressive threshold strategy (from small value to large value) is presented to determine an appropriate RANSAC threshold, in which the progressive process is guided by shoreline constraint. The proposed approach (with filtering) is compared with standard AIFM (without filtering) using two typical image pairs in coastal areas. The experimental results indicate that the proposed approach can always provide much better matching results than standard AIFM. Numéro de notice : A2015-162 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/01490419.2013.868382 Date de publication en ligne : 02/08/2013 En ligne : https://doi.org/10.1080/01490419.2013.868382 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75849 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
230-2014011	RAB	Revue	Centre de documentation	En réserve L003	Disponible

3D building model reconstruction from multi-view aerial imagery and Lidar data / Liang Cheng in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 2 (February 2011)  

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