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Automatic detection of thin oil films on water surfaces in ultraviolet imagery / Ming Xie in Photogrammetric record, vol 38 n° 181 (March 2023)  

Public [article]  inPhotogrammetric record > vol 38 n° 181 (March 2023) . - pp 47 - 62 Titre : Automatic detection of thin oil films on water surfaces in ultraviolet imagery Type de document : Article/Communication Auteurs : Ming Xie, Auteur ; Xiurui Zhang, Auteur ; Ying Li, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 47 - 62 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] détection automatique [Termes IGN] filtre optique [Termes IGN] hydrocarbure [Termes IGN] image AVIRIS [Termes IGN] marée noire [Termes IGN] niveau de gris (image) [Termes IGN] rayonnement ultraviolet [Termes IGN] segmentation d'image [Termes IGN] seuillage binaire [Termes IGN] surface de la mer Résumé : (auteur) Among the various remote sensing technologies that have been applied to monitor oil spills on the sea surface, passive ultraviolet (UV) imaging is a controversial one that has raised some disputes in the community of oil spill remote sensing. As a result, the research and applications of oil spill detection using passive UV imaging have not been as developed as other methods. In order to clarify some existing questions on oil spill detection using passive UV remote sensing technology, this paper discusses the needs of thin oil film detection, examines the feasibility of thin oil film detection using passive UV imaging through field experiments under controlled conditions and validates it with the UV imagery derived from the airborne visible/infrared imaging spectrometer (AVIRIS) observation of the Deepwater Horizon oil spill. Two types of fully automatic models are designed to extract the thin oil films on the water surface: (1) a binary classification model based on an adaptive threshold; (2) an unsupervised image segmentation model based on image clustering and greyscale histogram analysis. The two models are tested on the UV imagery obtained through both field experiments and AVIRIS observations. The results indicate that the binary classification model can extract the thin oil films with reasonable accuracy under stable imaging conditions, while the unsupervised image clustering model can robustly detect the thin oil films at the cost of higher computational complexity. These results infer that passive UV imaging is an effective way to detect thin oil films and could be applied to provide early warning at the beginning stage of oil spills and reduce further damage. It may also be applied as a supplementary method for oil spill detection to achieve comprehensive oil spill monitoring. Numéro de notice : A2023-163 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/phor.12439 Date de publication en ligne : 09/02/2023 En ligne : https://doi.org/10.1111/phor.12439 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102866 [article]

A novel nonlinear hyperspectral unmixing approach for images of oil spills at sea / Ying Li in International Journal of Remote Sensing IJRS, vol 41 n° 12 (20 - 30 March 2020)  

Public [article]  inInternational Journal of Remote Sensing IJRS > vol 41 n° 12 (20 - 30 March 2020) . - pp 4684 - 4701 Titre : A novel nonlinear hyperspectral unmixing approach for images of oil spills at sea Type de document : Article/Communication Auteurs : Ying Li, Auteur ; Huimin Lu, Auteur ; Zhenduo Zhang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 4684 - 4701 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse des mélanges spectraux [Termes IGN] équation polynomiale [Termes IGN] hydrocarbure [Termes IGN] image hyperspectrale [Termes IGN] marée noire [Termes IGN] modèle non linéaire [Termes IGN] pollution des mers [Termes IGN] trigonométrie Résumé : (auteur) Hyperspectral remote sensing is currently being used to detect and monitor marine oil spills that cause damage to the environment. However, nonlinear interactions of oil and water make it difficult to extract their fractional abundances from the spectral response. Improving the modelling of nonlinear hyperspectral mixtures, which is required for a thorough and reliable characterization of the materials in an image, remains a challenging yet fundamental task. This study proposes a new model that combines polynomial and trigonometric systems to understand the nonlinear effects of oil and water spectral response. Although the model is nonlinear, unmixing is performed by solving a linear problem, thus allowing fast computation. Compared to classic polynomial models, the details of nonlinear interactions are better expressed and quantified, and the reconstruction accuracy and endmember abundance estimation are improved for both synthetic and real datasets. Both the polynomial and trigonometric parts of the model play important roles in characterizing nonlinearities, with statistically linear dependence areas covering more than 90% and 30%, respectively, in oil spill images sampled after the Deepwater Horizon explosion. Analysis of the experimental results suggests that the proposed model provides an efficient and accurate unmixing method that can be used to help design oil spill response plans. Numéro de notice : A2020-452 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2020.1723179 Date de publication en ligne : 27/02/2020 En ligne : https://doi.org/10.1080/01431161.2020.1723179 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95540 [article]

Assessing tree dendrometrics in young regenerating plantations using terrestrial laser scanning / Ying Li in Annals of Forest Science, vol 71 n° 4 (June 2014)  

Public [article]  inAnnals of Forest Science > vol 71 n° 4 (June 2014) . - pp 453 - 462 Titre : Assessing tree dendrometrics in young regenerating plantations using terrestrial laser scanning Type de document : Article/Communication Auteurs : Ying Li, Auteur ; Carsten Hess, Auteur ; Henrik Von Wehrden, Auteur ; Werner Härdtle, Auteur ; Goddert Von Oheimb, Auteur Année de publication : 2014 Article en page(s) : pp 453 - 462 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] arbre (flore) [Termes IGN] Chine [Termes IGN] données dendrométriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] hauteur des arbres [Termes IGN] plantation forestière [Termes IGN] taillis [Termes IGN] télémétrie laser terrestre Résumé : (Auteur) Context : Terrestrial laser scanning (TLS) provides a valuable tool for the retrieval of detailed individual-tree structural parameters, but has never previously been applied to young stands under field conditions. Aims: The aim was to explore the performance of TLS in a young tree plantation located in a heterogeneous environment in subtropical China. Methods: We investigated 438 young trees for congruence between direct field and TLS measurements of total tree height, stem diameter at ground height, and length and height of the longest branch using correlation tests. We applied generalized linear models to examine whether congruence was affected by the observed structural parameter or extrinsic factors (e.g., potential occlusion, point cloud quality). Results: TLS made it possible to detect trees higher than 40cm. The TLS-retrieved data were highly congruent with the data obtained from direct measurements. The poor descriptions of stems and branches of some individuals of small-sized and leaf-on tree species were due to occlusion by ground vegetation and leaf-on branches. Observed structural parameter and extrinsic factors did not explain the variance between the two approaches. Conclusion: TLS proved to be a promising tool for high-resolution, non-destructive analyses of tree dendrometrics in young regenerating plantations. Numéro de notice : A2014-284 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1007/s13595-014-0358-4 Date de publication en ligne : 29/01/2014 En ligne : https://doi.org/10.1007/s13595-014-0358-4 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33187 [article]

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