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Real-time monitoring and short-term forecasting of land surface phenology / M.A. White in Remote sensing of environment, vol 104 n° 1 (15/09/2006)
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Titre : Real-time monitoring and short-term forecasting of land surface phenology Type de document : Article/Communication Auteurs : M.A. White, Auteur ; Ramakrishna R. Nemani, Auteur Année de publication : 2006 Article en page(s) : pp 43 - 49 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse diachronique
[Termes IGN] phénologie
[Termes IGN] prédiction
[Termes IGN] prévision à court terme
[Termes IGN] seuillage d'image
[Termes IGN] surface du sol
[Termes IGN] surveillance écologique
[Termes IGN] temps réelRésumé : (Auteur) Land surface phenology is an important process for real-time monitoring and short-term forecasting in diverse land management, health, and hydrologic modeling applications. Yet current efforts to characterize phenological processes are limited by remote sensing challenges and lack of uncertainty estimates. Here, for a global distribution of phenologically and climatically similar phenoregions, we used the Advanced Very High Resolution Radiometer to develop a conceptually and computationally simple technique for real-time and forecast applications. Our overall approach was to analyze the phenological behavior of groups of pixels without recourse to smoothing or fitting. We used a 3-step initial process: (1) define a phenoregion specific normalized difference vegetation index threshold; (2) for all days from 1982–2003, calculate the percent of pixels above the threshold (PAT); (3) calculate daily 1982–2003 empirical distributions of PAT. For real-time monitoring, the current PAT may then be compared to the historical range of variability and visualized in relation to user-defined levels. Using similar concepts, we projected daily PAT up to one month in the future and compared predicted and actual dates at which a hypothetical PAT was reached. We found that the maximum lead-time of phenological forecasts could be analytically defined for user-specified uncertainty levels. The approach is adaptable to different remote sensing technologies and provides a foundation for ascribing a sequence of ground conditions (e.g. snowmelt, vegetative growth, pollen production, insect phenology) to remotely sensed land surface phenology observations. Copyright Elsevier Numéro de notice : A2006-393 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.04.014 En ligne : https://doi.org/10.1016/j.rse.2006.04.014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28117
in Remote sensing of environment > vol 104 n° 1 (15/09/2006) . - pp 43 - 49[article]Resolution dependent errors in remote sensing of cultivated areas / M. Ozdogan in Remote sensing of environment, vol 103 n° 2 (30/07/2006)
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Titre : Resolution dependent errors in remote sensing of cultivated areas Type de document : Article/Communication Auteurs : M. Ozdogan, Auteur ; Curtis E. Woodcock, Auteur Année de publication : 2006 Article en page(s) : pp 203 - 217 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse de sensibilité
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] Chine
[Termes IGN] cultures
[Termes IGN] distribution spatiale
[Termes IGN] erreur de classification
[Termes IGN] image Ikonos
[Termes IGN] limite de résolution géométrique
[Termes IGN] précision infrapixellaire
[Termes IGN] seuillage d'image
[Termes IGN] surface cultivée
[Termes IGN] variogrammeRésumé : (Auteur) Remote sensing has become a common and effective method for estimating the areal coverage of land cover classes. One class of particular interest is agriculture as area estimates of cultivated lands are important for purposes such as estimating yields or irrigation needs. The synoptic coverage of satellite imagery and the relative ease of automated analysis have led to widespread mapping of agriculture using remote sensing. The accuracy of area estimates derived from these maps is known to be related to the accuracy of the maps. However, even in the situation where the map is very accurate, errors in area estimates may occur. These errors result from the behavior of the distribution of subpixel proportions of cultivated areas, and how that behavior changes as a result of sensor spatial resolution and class definitions. The sensitivity of estimates of cultivated areas to sensor spatial resolution and to the choice of threshold used to define cultivated land is explored in six agriculturally distinct locations around the world. Using a beta model for the distribution of subpixel proportions that is parameterized using variograms, it is possible to model the distribution of subpixel proportions for any spatial resolution. When the spatial resolution is small with respect to the spatial structure of the landscape (as measured by the variogram range) use of any class definition threshold produces an estimate very close to the true area coverage. On the other hand, as the resolution becomes coarse in relation to the variogram range, the subpixel proportions are no longer concentrated at the extremes of the distribution and the difference between the estimated and the true area has greater sensitivity to the selected threshold used to define classes. Thus, for the cases examined here, both the resolution and the class definition threshold have a strong influence on area estimates. The spatial resolutions where errors can be large depend on landscape spatial structure, which can be quantified using variograms. The net effect is that for the same spatial resolution, some places will exhibit much larger errors in area estimates than others. For the site in the Anhui province of China, where agricultural fields are very small (0.07 ha on the average), area estimates are highly sensitive to class definition thresholds even at the relatively fine resolution of 45 m. Conversely, in California (USA) spatial resolutions as coarse as 500 m can be used to reliably estimate cultivated areas. Results also suggest that the proportion of the total area that is cultivated significantly influences the accuracy of area estimates. When the area proportion is low, the class definition threshold must also be low to achieve an accurate area estimate. Conversely, in areas dominated by agriculture, a very stringent class definition of cultivated lands is required for accurate area estimates. While explored in the context of estimation of cultivated areas, the findings presented here are generic to the problem of area estimation using remote sensing. Copyright Elsevier Numéro de notice : A2006-321 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.04.004 En ligne : https://doi.org/10.1016/j.rse.2006.04.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28045
in Remote sensing of environment > vol 103 n° 2 (30/07/2006) . - pp 203 - 217[article]Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage / H. Othman in IEEE Transactions on geoscience and remote sensing, vol 44 n° 2 (February 2006)
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Titre : Noise reduction of hyperspectral imagery using hybrid spatial-spectral derivative-domain wavelet shrinkage Type de document : Article/Communication Auteurs : H. Othman, Auteur ; S.E. Qian, Auteur Année de publication : 2006 Article en page(s) : pp 397 - 408 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification hypercube
[Termes IGN] filtrage du bruit
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] ondelette
[Termes IGN] seuillage d'imageRésumé : (Auteur) In this paper, a new noise reduction algorithm is introduced and applied to the problem of denoising hyperspectral imagery. This algorithm resorts to the spectral derivative domain, where the noise level is elevated, and benefits from the dissimilarity of the signal regularity in the spatial and the spectral dimensions of hyperspectral images. The performance of the new algorithm is tested on two different hyperspectral datacubes : an Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) datacube that is acquired in a vegetation-dominated site and a simulated AVIRIS datacube that simulates a geological site. The new algorithm provides signal-to-noise-ratio improvement up to 84.44% and 98.35% in the first and the second datacubes, respectively. Numéro de notice : A2006-125 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2005.860982 En ligne : https://doi.org/10.1109/TGRS.2005.860982 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27852
in IEEE Transactions on geoscience and remote sensing > vol 44 n° 2 (February 2006) . - pp 397 - 408[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-06021 RAB Revue Centre de documentation En réserve L003 Disponible Integrated shadow removal based on photogrammetry and image analysis / Y. Li in International Journal of Remote Sensing IJRS, vol 26 n° 18 (September 2005)
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Titre : Integrated shadow removal based on photogrammetry and image analysis Type de document : Article/Communication Auteurs : Y. Li, Auteur ; P. Gong, Auteur ; T. Sasagawa, Auteur Année de publication : 2005 Article en page(s) : pp 3911 - 3929 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] ADS40
[Termes IGN] détection automatique
[Termes IGN] image à haute résolution
[Termes IGN] image aérienne
[Termes IGN] image RVB
[Termes IGN] lancer de rayons
[Termes IGN] milieu urbain
[Termes IGN] modèle numérique de surface
[Termes IGN] ombre
[Termes IGN] rayonnement solaire
[Termes IGN] segmentation d'image
[Termes IGN] seuillage d'image
[Termes IGN] système d'information géographiqueRésumé : (Auteur) This paper presents a methodology to automatically detect and remove the shadows in high-resolution urban aerial images for urban GIS applications. The image is generated by ADS40, which is a multiple line scanner. The system includes shadow simulation, ray tracing, integrated shadow detection. and shadow removal. The geodetic shadow is simulated from a digital surface model (DSM) and the sun attitude. Using an ADS40 camera model and collinearity equations, the corresponding scan line of the shadow is obtained. Ray tracing is used to determine the visibility of the shadow in the image. A building boundary driven height field ray tracing method is proposed to boost the tracing efficiency. Shadow segmentation is taken from the RGB image at the base of the traced image shadows. The segmentation threshold is derived from the histogram of the traced image shadow area. Shadow removal includes the shadow region and companion region labelling, the histogram processing, and intensity mapping. Some experiment results are presented to show the effectiveness of the methods. Numéro de notice : A2005-428 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500159347 En ligne : https://doi.org/10.1080/01431160500159347 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27564
in International Journal of Remote Sensing IJRS > vol 26 n° 18 (September 2005) . - pp 3911 - 3929[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05181 RAB Revue Centre de documentation En réserve L003 Exclu du prêt De-shadowing of satellite/airborne imagery / R. Richter in International Journal of Remote Sensing IJRS, vol 26 n° 15 (August 2005)
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Titre : De-shadowing of satellite/airborne imagery Type de document : Article/Communication Auteurs : R. Richter, Auteur ; A. Muller, Auteur Année de publication : 2005 Article en page(s) : pp 3137 - 3148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] bande visible
[Termes IGN] correction des ombres
[Termes IGN] filtre numérique
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image multibande
[Termes IGN] image spatiale
[Termes IGN] matrice de covariance
[Termes IGN] rayonnement proche infrarouge
[Termes IGN] seuillage d'imageRésumé : (Auteur) A de-shadowing technique is presented for multispectral and hyperspectral imagery over land acquired by satellite/airborne sensors. The method requires a channel in the visible and at least one spectral band in the near-infrared (0.8-1um) region, but performs much better if bands in the short-wave infrared region (around 1.6 and 2.2 um) are available as well. The algorithm consists of these major components: (i) calculation of the covariance matrix and zero-reflectance matched filter vector, (ii) derivation of the unsealed and scaled shadow function, (iii) histogram thresholding of the unscaled shadow function to define the core shadow areas, (iv) region growing to include the surroundings of the core shadow areas for a smooth shadowlclear transition, and (v) de-shadowing of the pixels in the final shadow mask. The critical parameters of the method are discussed. Example images from different climates and landscapes are presented to demonstrate the successful performance of the shadow removal process over land surfaces. Numéro de notice : A2005-323 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500114664 En ligne : https://doi.org/10.1080/01431160500114664 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27459
in International Journal of Remote Sensing IJRS > vol 26 n° 15 (August 2005) . - pp 3137 - 3148[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05151 RAB Revue Centre de documentation En réserve L003 Exclu du prêt An unsupervised approach based on the generalized Gaussian model to automatic change detection in multitemporal SAR images / Y. Bazi in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)
PermalinkReal-time speed limit sign recognition based on locally adaptive thresholding and depth-first-search / J. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 4 (April 2005)
PermalinkRemote sensing image thresholding methods for determining landslide activity / P.L. Rosin in International Journal of Remote Sensing IJRS, vol 26 n° 6 (March 2005)
PermalinkAutomatic detection of earthquake-damaged buildings using DEMs created from pre- and post-earthquake stereo aerial photographs / M. Turker in International Journal of Remote Sensing IJRS, vol 26 n° 4 (February 2005)
PermalinkAutomated quality control for orthoimages and DEMs / J.K. Höhle in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 1 (January 2005)
PermalinkRoad extraction using SVM and image segmentation / M. Song in Photogrammetric Engineering & Remote Sensing, PERS, vol 70 n° 12 (December 2004)
PermalinkComparison of different speckle-reduction techniques in SAR images using wavelet transform / A. Vidal-Pantaleoni in International Journal of Remote Sensing IJRS, vol 25 n° 22 (November 2004)
PermalinkCouplage de données optiques et radar pour la caractérisation de paysages urbains amazoniens : application à l'île de Cayenne / Jean-François Faure in Revue internationale de géomatique, vol 14 n° 3 - 4 (septembre 2004 – février 2005)
PermalinkMonitoring surface soil moisture in post-harvest rice areas using C-band radar imagery in NorthEast Thailand / S. Kaojarern in Geocarto international, vol 19 n° 3 (September - November 2004)
PermalinkNighttime polar cloud detection with MODIS / Y. Liu in Remote sensing of environment, vol 92 n° 2 (15/08/2004)
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