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A fast volume-gradient-based band selection method for hyperspectral image / X. Geng in IEEE Transactions on geoscience and remote sensing, vol 52 n° 11 tome 1 (November 2014)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 52 n° 11 tome 1 (November 2014) . - pp 7111 - 7119 Titre : A fast volume-gradient-based band selection method for hyperspectral image Type de document : Article/Communication Auteurs : X. Geng, Auteur ; Kang Sun, Auteur ; L. Ji, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 7111 - 7119 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] bande spectrale [Termes IGN] gradient [Termes IGN] image hyperspectrale [Termes IGN] volume (grandeur) Résumé : (Auteur) In this paper, a subtle relationship is found between the volume of a subsimplex and the volume gradient of a simplex with respect to hyperspectral images. By using this relationship, we propose an efficient band selection method, namely, the volume-gradient-based band selection (VGBS) method. The VGBS method is an unsupervised method, which tries to remove the most redundant band successively. Interestingly, the VGBS method can find the most redundant band based only on the gradient of volume instead of calculating the volumes of all subsimplexes. Experiments on simulated and real hyperspectral data verify the efficiency of the proposed method. Numéro de notice : A2014-544 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2014.2307880 En ligne : https://doi.org/10.1109/TGRS.2014.2307880 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74162 [article]

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Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices / L. Ji in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 20 - 47 Titre : Geostatistical estimation of signal-to-noise ratios for spectral vegetation indices Type de document : Article/Communication Auteurs : L. Ji, Auteur ; Li Zhang, Auteur ; Jennifer Rover, Auteur Année de publication : 2014 Article en page(s) : pp 20 - 47 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal [Termes IGN] bruit (théorie du signal) [Termes IGN] estimation statistique [Termes IGN] géostatistique [Termes IGN] indice de végétation Résumé : (Auteur) In the past 40 years, many spectral vegetation indices have been developed to quantify vegetation biophysical parameters. An ideal vegetation index should contain the maximum level of signal related to specific biophysical characteristics and the minimum level of noise such as background soil influences and atmospheric effects. However, accurate quantification of signal and noise in a vegetation index remains a challenge, because it requires a large number of field measurements or laboratory experiments. In this study, we applied a geostatistical method to estimate signal-to-noise ratio (S/N) for spectral vegetation indices. Based on the sample semivariogram of vegetation index images, we used the standardized noise to quantify the noise component of vegetation indices. In a case study in the grasslands and shrublands of the western United States, we demonstrated the geostatistical method for evaluating S/N for a series of soil-adjusted vegetation indices derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. The soil-adjusted vegetation indices were found to have higher S/N values than the traditional normalized difference vegetation index (NDVI) and simple ratio (SR) in the sparsely vegetated areas. This study shows that the proposed geostatistical analysis can constitute an efficient technique for estimating signal and noise components in vegetation indices. Numéro de notice : A2014-382 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.06.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.06.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73809 [article]

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Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data / K. Gallo in Remote sensing of environment, vol 99 n° 3 (30/11/2005)  

Public [article]  inRemote sensing of environment > vol 99 n° 3 (30/11/2005) . - pp 221 - 231 Titre : Multi-platform comparisons of MODIS and AVHRR normalized difference vegetation index data Type de document : Article/Communication Auteurs : K. Gallo, Auteur ; L. Ji, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 221 - 231 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse comparative [Termes IGN] capteur (télédétection) [Termes IGN] image NOAA-AVHRR [Termes IGN] image Terra-MODIS [Termes IGN] Normalized Difference Vegetation Index Résumé : (Auteur) The relationship between AVHRR-derived normalized difference vegetation index (NDVI) values and those of future sensors is critical to continued long-term monitoring of land surface properties. The follow-on operational sensor to the AVHRR, the Visible/Infrared Imager/ Radiometer Suite (VIIRS), will be very similar to the NASA Earth Observing System's Moderate Resolution Imaging Spectroradiometer (MODIS) sensor. NDVI data derived from visible and near-infrared data acquired by the MODIS (Terra and Aqua platforms) and AVHRR (NOAA-16 andNOAA-17) sensors were compared over the same time periods and a variety of land cover classes within the conterminous United States. The results indicate that the 16-day composite NDVI values are quite similar over the composite intervals of 2002 and 2003, and linear relationships exist between the NDVI values from the various sensors. The composite AVHRR NDVI data included water and cloud masks and adjustments for water vapor as did the MODIS NDVI data. When analyzed over a variety of land cover types and composite intervals, the AVHRR derived NDVI data were associated with 89% or more of the variation in the MODIS NDVI values. The results suggest that it may be possible to successfully reprocess historical AVHRR data sets to provide continuity of NDVI products through future sensor systems. Numéro de notice : A2005-458 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.08.014 En ligne : https://doi.org/10.1016/j.rse.2005.08.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27594 [article]