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A convolutional neural network with mapping layers for hyperspectral image classification / Rui Li in IEEE Transactions on geoscience and remote sensing, vol 58 n° 5 (May 2020)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 58 n° 5 (May 2020) . - pp 3136 - 3147 Titre : A convolutional neural network with mapping layers for hyperspectral image classification Type de document : Article/Communication Auteurs : Rui Li, Auteur ; Zhibin Pan, Auteur ; Yang Wang, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 3136 - 3147 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] algèbre linéaire [Termes descripteurs IGN] analyse discriminante [Termes descripteurs IGN] analyse en composantes principales [Termes descripteurs IGN] analyse multidimensionnelle [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] couche thématique [Termes descripteurs IGN] dispersion [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] réduction Résumé : (auteur) In this article, we propose a convolutional neural network with mapping layers (MCNN) for hyperspectral image (HSI) classification. The proposed mapping layers map the input patch into a low-dimensional subspace by multilinear algebra. We use our mapping layers to reduce the spectral and spatial redundancies and maintain most energy of the input. The feature extracted by our mapping layers can also reduce the number of following convolutional layers for feature extraction. Our MCNN architecture avoids the declining accuracy with increasing layers phenomenon of deep learning models for HSI classification and also saves the training time for its effective mapping layers. Furthermore, we impose the 3-D convolutional kernel on the convolutional layer to extract the spectral–spatial features for HSI. We tested our MCNN on three data sets of Indian Pines, University of Pavia, and Salinas, and we achieved the classification accuracy of 98.3%, 99.5%, and 99.3%, respectively. Experimental results demonstrate that the proposed MCNN can significantly improve classification accuracy and save much time consumption. Numéro de notice : A2020-234 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2019.2948865 date de publication en ligne : 12/11/2019 En ligne : https://doi.org/10.1109/TGRS.2019.2948865 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94980 [article]

Dimension reduction methods applied to coastline extraction on hyperspectral imagery / Ozan Arslan in Geocarto international, vol 35 n° 4 ([15/03/2020])  

Public [article]  inGeocarto international > vol 35 n° 4 [15/03/2020] . - pp 376 - 390 Titre : Dimension reduction methods applied to coastline extraction on hyperspectral imagery Type de document : Article/Communication Auteurs : Ozan Arslan, Auteur ; özer Akyürek, Auteur ; Sinasi Kaya, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 376 - 390 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse en composantes principales [Termes descripteurs IGN] Bosphore [Termes descripteurs IGN] classification par réseau neuronal [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] détection de contours [Termes descripteurs IGN] extraction [Termes descripteurs IGN] image EO1-Hyperion [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] Istanbul (Turquie) [Termes descripteurs IGN] littoral [Termes descripteurs IGN] rapport signal sur bruit [Termes descripteurs IGN] réduction [Termes descripteurs IGN] télédétection [Termes descripteurs IGN] trait de côte Résumé : (auteur) In this study, dimensionality reduction (DR) methods on a hyperspectral dataset to explore the influence on the process of extraction of coastlines were examined and performance of different DR algorithms on the detection of coastline in Bosphorus, Istanbul was investigated. Among these methods, principal component (PC) analysis, maximum noise fraction and independent component (IC) analysis were used in the experiments with the aim of comparing. The study was carried out using these well-known DR techniques on a real hyperspectral image, an Hyperion data set with 161 bands, in the course of the experiments. Three different classifiers (i.e. ML, SVM and neural network) were used for the classification of dimensionally reduced and original images to detect coastline in the region. The DR results were evaluated quantitatively and visually in order to determine the reduced dimensions of the image subsets. Findings show that there is no significant influence of using DR methods on the dataset on the detection of coastline. Numéro de notice : A2020-099 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1520920 date de publication en ligne : 22/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1520920 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94690 [article]

Plant survival monitoring with UAVs and multispectral data in difficult access afforested areas / Maria Luz Gil-Docampo in Geocarto international, vol 35 n° 2 ([01/02/2020])  

Public [article]  inGeocarto international > vol 35 n° 2 [01/02/2020] . - pp 128 - 140 Titre : Plant survival monitoring with UAVs and multispectral data in difficult access afforested areas Type de document : Article/Communication Auteurs : Maria Luz Gil-Docampo, Auteur ; Juan Ortiz-Sanz, Auteur ; S. Martínez-Rodríguez, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 128 - 140 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] aire protégée [Termes descripteurs IGN] analyse de survie [Termes descripteurs IGN] analyse en composantes principales [Termes descripteurs IGN] climat aride [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image proche infrarouge [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] mortalité [Termes descripteurs IGN] reboisement [Termes descripteurs IGN] ressources en eau [Termes descripteurs IGN] surveillance de la végétation [Termes descripteurs IGN] télédétection aérienne Résumé : (Auteur) Water supply devices enable afforestation in dry climates and on poor lands with generally high success rates. Previous survival analyses have been based on the direct observation of each individual plant in the field, which entails considerable effort and costs. This study provides a low-cost method to discriminate between live and dead plants in afforestation that can efficiently replace traditional field inspections through the use of unmanned aerial vehicles (UAVs) equipped with RGB and NIR sensors. The method combines the use of a conventional camera with an identical camera modified to record the NIR channel. Survival analysis was performed with digital image processing techniques based on calculated indices associated with plant vigour and PCA-based decorrelation. The method yielded results with high global accuracy rates (∼96.2%) with a minimum percentage of doubtful plants, even in young plantations (seedlings Numéro de notice : A2020-035 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1508312 date de publication en ligne : 02/10/2018 En ligne : https://doi.org/10.1080/10106049.2018.1508312 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94517 [article]

Individual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data / Sitinor Atikah Nordin in Geocarto international, vol 34 n° 11 ([15/08/2019])  

Public [article]  inGeocarto international > vol 34 n° 11 [15/08/2019] . - pp 1218 - 1236 Titre : Individual tree crown segmentation in tropical peat swamp forest using airborne hyperspectral data Type de document : Article/Communication Auteurs : Sitinor Atikah Nordin, Auteur ; Zulkiflee Abd Latif, Auteur ; Hamdan Omar, Auteur Année de publication : 2019 Article en page(s) : pp 1218 - 1236 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] analyse en composantes principales [Termes descripteurs IGN] analyse multibande [Termes descripteurs IGN] Asie du sud-est [Termes descripteurs IGN] bande rouge [Termes descripteurs IGN] canopée [Termes descripteurs IGN] capteur hyperspectral [Termes descripteurs IGN] carte forestière [Termes descripteurs IGN] forêt tropicale [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image proche infrarouge [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] niveau de gris (image) [Termes descripteurs IGN] réflectance végétale [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] teneur en chlorophylle des feuilles [Termes descripteurs IGN] tourbière Résumé : (Auteur) Individual tree crown segmentation is important step for deriving various information for fine-scale analysis of ecological process. However, only several studies have applied tree crown segmentation in tropical forest ecosystems, especially in mixed peat swamp forests. In this study, hyperspectral data were used to detect changes in the biochemical and biophysical characteristics, which are important factors for tree crown segmentation. Principal Component Analysis method was performed to investigate its influence on crown segmentation. Visually Selected PCs, 160 PCs and 160 Spectral Bands image were used and two segmentation techniques; Watershed Transformation and Region Growing segmentation were applied on those images. The highest accuracy was achieved for the crown segmentation is using Region Growing segmentation, based on 1:1 measurement, D value and RMSE value. The results obtained from 160 PCs image using region growing algorithm shows better accuracy with D value of 0.2 (80% accuracy, 20% error) and RMSE of 9.9 m2. Numéro de notice : A2019-463 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1475511 date de publication en ligne : 24/05/2018 En ligne : https://doi.org/10.1080/10106049.2018.1475511 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93605 [article]

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Synergetic efficiency of Lidar and WorldView-2 for 3D urban cartography in Northeast Mexico / Fabiola D. Yepez-Rincon in Geocarto international, vol 34 n° 2 ([01/02/2019])  

Public [article]  inGeocarto international > vol 34 n° 2 [01/02/2019] . - pp 164 - 178 Titre : Synergetic efficiency of Lidar and WorldView-2 for 3D urban cartography in Northeast Mexico Type de document : Article/Communication Auteurs : Fabiola D. Yepez-Rincon, Auteur ; Diego Fabian Lozano Garcia, Auteur Année de publication : 2019 Article en page(s) : pp 164 - 178 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] analyse en composantes principales [Termes descripteurs IGN] bande infrarouge [Termes descripteurs IGN] carte d'occupation du sol [Termes descripteurs IGN] cartographie urbaine [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] détection de changement [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image Worldview [Termes descripteurs IGN] Mexico (Mexique) [Termes descripteurs IGN] pansharpening (fusion d'images) [Termes descripteurs IGN] zone urbaine Résumé : (auteur) Three-dimensional urban cartography is needed for city changes’ assessment. The variety of studies using 3D calculations of urban elements grows each year. Building and vegetation volumes are necessary to assess and understand spatio-temporal urban changeable environments. However, there are technical questions as to which method can improve 3D urban cartographic accuracy. The innovative part of this current study is the creation of a six-band hybrid obtained from LIDAR and WorldView2 synergy. Two different enhancement algorithms demonstrated the most important spectral features for the urban development and vegetation classes. Results indicated an improvement in accuracy by up to 21.3%, according to the Kappa coefficient. Both infra-red band and intensity band were the most significant, according to the principal components analysis. The synergy delimited classes and polygons, as well as the direct display of information regarding heights of elements and improving the extraction of roads, buildings and vegetation classes. Numéro de notice : A2019-220 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1377774 date de publication en ligne : 21/09/2017 En ligne : https://doi.org/10.1080/10106049.2017.1377774 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92738 [article]

Application of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak, Kerman, south of Iran / Morteza Safari in Geocarto international, vol 33 n° 11 (November 2018)  

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On the spatial distribution of buildings for map generalization / Zhiwei Wei in Cartography and Geographic Information Science, Vol 45 n° 6 (November 2018)  

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Influences of environmental loading corrections on the nonlinear variations and velocity uncertainties for the reprocessed global positioning system height time series of the crustal movement observation network of China / Peng Yuan in Remote sensing, vol 10 n° 6 (June 2018)    

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Long-term prediction of polar motion using a combined SSA and ARMA model / Y. Shen in Journal of geodesy, vol 92 n° 3 (March 2018)  

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Sensitivity analysis of pansharpening in hyperspectral change detection / Seyd Teymoor Seydi in Applied geomatics, vol 10 n° 1 (March 2018)  

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Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar / Melissa Fedrigo in ISPRS Journal of photogrammetry and remote sensing, vol 136 (February 2018)  

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Utilisation de QGIS en télédétection, Ch. 2. Apports du MNT topo-bathymétrique pour l'évolution bio-géomorphologique des marais d'Ichkeul (Tunisie) / Zeineb Kassouk (2018)

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Application of the PCA/EOF method for the analysis and modelling of temporal variations of geoid heights over Poland / Walyeldeen Godah in Acta geodaetica et geophysica, vol 52 n° 4 (December 2017)  

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On the estimation of physical height changes using GRACE satellite mission data – A case study of Central Europe / Walyeldeen Godah in Geodesy and cartography, vol 66 n° 2 (December 2017)  

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Fusion of hyperspectral and LiDAR data using sparse and low-rank component analysis / Behnood Rasti in IEEE Transactions on geoscience and remote sensing, vol 55 n° 11 (November 2017)  

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