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Linear feature detection using multi-resolution wavelet filters / S.P. Kozaitis in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 6 (June 2005)
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Titre : Linear feature detection using multi-resolution wavelet filters Type de document : Article/Communication Auteurs : S.P. Kozaitis, Auteur ; R.H. Cofer, Auteur Année de publication : 2005 Article en page(s) : pp 689 - 697 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse multiéchelle
[Termes IGN] analyse multirésolution
[Termes IGN] détection automatique
[Termes IGN] filtre numérique
[Termes IGN] géométrie différentielle
[Termes IGN] image aérienne
[Termes IGN] route
[Termes IGN] transformation en ondelettesRésumé : (Auteur) We detected road pixels in aerial imagery using a multiresolution, wavelet-based approach. Our method involved the description of a differential geometry approach for road seed pixel detection in terms of wavelet transforms. Using this approach allowed us to extend the differential geometry approach to incorporate multiple scales. We found that using multiple scales significantly reduced the number of potential false positives. Our approach seemed to work well with a computer-assisted approach where the "seed" or potential pixels of interest should have a high confidence level of being correct. We found that our approach led to an effective method for detecting roads in aerial imagery. Our method is general, and in principle could be applied to other filtering techniques besides the one used here. Numéro de notice : A2005-218 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.71.6.689 En ligne : https://doi.org/10.14358/PERS.71.6.689 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27355
in Photogrammetric Engineering & Remote Sensing, PERS > vol 71 n° 6 (June 2005) . - pp 689 - 697[article]Ground-penetrating radar measurement of crop and surface water content dynamics / G. Serbin in Remote sensing of environment, vol 96 n° 1 (15/05/2005)
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Titre : Ground-penetrating radar measurement of crop and surface water content dynamics Type de document : Article/Communication Auteurs : G. Serbin, Auteur ; D. Or, Auteur Année de publication : 2005 Article en page(s) : pp 119 - 134 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] diffusion du rayonnement
[Termes IGN] humidité du sol
[Termes IGN] masse végétale
[Termes IGN] propriété diélectrique
[Termes IGN] radar pénétrant GPR
[Termes IGN] réflectance de surface
[Termes IGN] réflectance du sol
[Termes IGN] sous-bois
[Termes IGN] temps de propagation
[Termes IGN] teneur en eau de la végétationRésumé : (Auteur) Ground-penetrating radar (GPR) with a suspended 1 GHz horn antenna was deployed for measurement of soil water contents and crop canopy properties over bare and electrically terminating surfaces. Surface reflection (SR) and signal propagation times (PT) were used to independently determine dielectric permittivity and water content of soil and canopy. Measured surface reflection coefficients progressively decreased with increasing canopy biomass according to Beer-Lambert type relationships. In contrast, PT measurements remained unaffected by canopy, and hence provided an accurate account of soil water content dynamics. Immediately after canopy removal, SR-based soil water content measurements were in close agreement with PT values. Canopy dielectric properties were inferred from canopy water contents (ec-CWC) and canopy propagation times (ec-CPT). Distinct canopy reflections were correlated with key canopy biophysical parameters. The study demonstrates the usefulness of a horn antenna GPR for characterization of vegetation canopy scattering, and for subcanopy water content measurements within a well-defined footprint, thereby offering a potential for calibration and verification of radar data collected from air- and spacebome platforms. Numéro de notice : A2005-212 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2005.01.018 En ligne : https://doi.org/10.1016/j.rse.2005.01.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27349
in Remote sensing of environment > vol 96 n° 1 (15/05/2005) . - pp 119 - 134[article]Separating surface emissivity and temperature using two-channel spectral indices and emissivity composites and comparison with a vegetation fraction method / P. Dash in Remote sensing of environment, vol 96 n° 1 (15/05/2005)
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Titre : Separating surface emissivity and temperature using two-channel spectral indices and emissivity composites and comparison with a vegetation fraction method Type de document : Article/Communication Auteurs : P. Dash, Auteur ; F. Göttsche, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1 - 17 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] correction atmosphérique
[Termes IGN] données de terrain
[Termes IGN] données météorologiques
[Termes IGN] éclairement énergétique
[Termes IGN] emissivité
[Termes IGN] erreur
[Termes IGN] image NOAA-AVHRR
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] radiance
[Termes IGN] rayonnement infrarouge thermique
[Termes IGN] saison
[Termes IGN] simulation de surface
[Termes IGN] température au sol
[Termes IGN] thermal infrared multispectral scannerRésumé : (Auteur) The temperature-independent thermal infrared spectral indices (TISI) method is employed for the separation of land surface temperature (LST) and emissivity from surface radiances (atmospherically corrected satellite data). The daytime reflected solar irradiance and the surface emission at ~3.8 um have comparable magnitudes. Using surface radiances and a combination of day-night 2-channel TISI ratios, the ~3.8 um reflectivity is derived. For implementing the TISI method, coefficients for NOAA 9-16 AVHRR channels are obtained. A numerical analysis with simulated surface radiances shows that for most surface types (showing nearly Lambertian behavior) the achievable accuracy is ~0.005 for emissivity (AVHRR channel-5) and ~1.5 K for LST. Data from the European Centre for Medium-Range Weather Forecasts (ECMWF) is used for calculation of atmospheric attenuation. Comparisons are made over a part of central Europe on two différent dates (seasons). Clouds pose a major problem to surface observations; hence, monthly emissivity composites are derived. Additionally, using TISI-based monthly composites of emissivities, a normalized difference vegetation index (NDVI)-based method is tuned to the particular study area and the results are intercompared. Once the coefficients are known, the NDVI method is easily implemented but holds well only for vegetated areas. The error of the NDVI-based emissivities (with respect to the TISI results) ranges between -0.038 and 0.032, but for vegetated areas the peak of the error-histogram is at ~0.002. The algorithm for retrieving emissivity via TISI was validated with synthetic data. Due to the different spatial scales of satellite and surface measurements and the lack of homogeneous areas, which are representative for low-resolution pixels and ground measurements, ground-validation is a daunting task. However, for operational products ground-truth validation is necessary. Therefore, also an approach to identify suitable validation sites for meteorological satellite products in Europe is described. Numéro de notice : A2005-209 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2004.12.023 En ligne : https://doi.org/10.1016/j.rse.2004.12.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27346
in Remote sensing of environment > vol 96 n° 1 (15/05/2005) . - pp 1 - 17[article]Combining spectral and spatial information into hidden Markov models for unsupervised image classification / B. Tso in International Journal of Remote Sensing IJRS, vol 26 n° 10 (May 2005)
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Titre : Combining spectral and spatial information into hidden Markov models for unsupervised image classification Type de document : Article/Communication Auteurs : B. Tso, Auteur ; C. Olsen, Auteur Année de publication : 2005 Article en page(s) : pp 2113 - 2133 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification barycentrique
[Termes IGN] classification contextuelle
[Termes IGN] classification non dirigée
[Termes IGN] données localisées 2D
[Termes IGN] image multi sources
[Termes IGN] modèle de Markov
[Termes IGN] optimisation (mathématiques)
[Termes IGN] précision de la classification
[Termes IGN] qualité des donnéesRésumé : (Auteur) Unsupervised classification methodology applied to remote sensing image processing can provide benefits in automatically converting the raw image data into useful information so long as higher classification accuracy is achieved. The traditional k-means clustering scheme using spectral data alone does not perform well in general as far as accuracy is concerned. This is partly due to the failure to take the spatial inter-pixels dependencies (i.e. the context) into account, resulting in a 'busy' visual appearance to the output imagery. To address this, the hidden Markov models (HMM) are introduced in this study as a fundamental framework to incorporate both the spectral and contextual information in analysis. This helps generate more patch-like output imagery and produces higher classification accuracy in an unsupervised scheme. The newly developed unsupervised classification approach is based on observation-sequence and observation-density adjustments, which have been proposed for incorporating 2D spatial information into the linear HMM. For the observation-sequence adjustment methods, there are a total of five neighbourhood systems being proposed. Two neighbourhood systems were incorporated into the observation-density methods for study. The classification accuracy is then evaluated by means of confusion matrices made by randomly chosen test samples. The classification obtained by k-means clustering and the HMM with commonly seen strip-like and Hilbert-Peano sequence fitting methods were also measured. Experimental results showed that the proposed approaches for combining both the spectral and spatial information into HMM unsupervised classification mechanism present improvements in both classification accuracy and visual qualities. Numéro de notice : A2005-259 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331337844 En ligne : https://doi.org/10.1080/01431160512331337844 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27395
in International Journal of Remote Sensing IJRS > vol 26 n° 10 (May 2005) . - pp 2113 - 2133[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05101 RAB Revue Centre de documentation En réserve L003 Disponible A quantitative comparison of methods for classifying burned areas with LISS-3 imagery / R.M. Roman-Cuesta in International Journal of Remote Sensing IJRS, vol 26 n° 9 (May 2005)
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Titre : A quantitative comparison of methods for classifying burned areas with LISS-3 imagery Type de document : Article/Communication Auteurs : R.M. Roman-Cuesta, Auteur ; J. Retana, Auteur ; et al., Auteur Année de publication : 2005 Article en page(s) : pp 1979 - 2003 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] analyse multibande
[Termes IGN] classificateur paramétrique
[Termes IGN] classification dirigée
[Termes IGN] image IRS-LISS
[Termes IGN] impact sur l'environnement
[Termes IGN] incendie de forêt
[Termes IGN] surveillance écologiqueRésumé : (Auteur) Environmental agencies frequently require tools for quick assessments of areas affected by large fires. Remote sensing techniques have been reported as efficient tools to evaluate the effects of fire. However, there exist few quantitative comparisons about the performance of the diverse methods. This study quantitatively evaluated the accuracy of five different techniques, a field survey and four satellite-based techniques, in order to quickly classify a large forest fire that occurred in 1998 in Solsonès (north-east Spain) by means of an IRS LISS-3 image. Three pure classes were determined: burned area, unburned vegetation, and bare soil; along with a non-pure class that we called mixed area. These selected techniques were included into a tree classifier to investigate their partial contribution to the final classification. The most accurate methods when focusing on pure classes were those directly related to the spectral characteristics of the pixel: Reflectance Data and Spectral Unmixing (82% of overall accuracy), versus the poorer performances of Vegetation Indices (70%), Textural measures (72%) and the field survey (68.6%). Since no image processing technique was applied to the Raw Reflectance Data, it can be considered the most cost-effective method, and the tree classifier reinforces its importance. The results of this study reveal that time consuming and expensive methods are not necessarily the most accurate, especially when potentially easily distinguishable classes are involved. Numéro de notice : A2005-258 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160512331299315 En ligne : https://doi.org/10.1080/01431160512331299315 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27394
in International Journal of Remote Sensing IJRS > vol 26 n° 9 (May 2005) . - pp 1979 - 2003[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-05091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Radial basis function neural networks classification using very high spatial resolution satellite imagery: an application to the habitat area of Lake Kerkini (Greece) / Iphigenia Keramitsoglou in International Journal of Remote Sensing IJRS, vol 26 n° 9 (May 2005)
PermalinkCalculating NDVI for NOAA/AVHRR data after atmospheric correction for extensive images using 6S code: a case study in the Marsabit district Kenya / K. Tachiiri in ISPRS Journal of photogrammetry and remote sensing, vol 59 n° 3 (May 2005)
PermalinkImplementation of an equal-area gridding method for global-scale image archiving / J.C. Seong in Photogrammetric Engineering & Remote Sensing, PERS, vol 71 n° 5 (May 2005)
PermalinkMicrowave land emissivity calculations using AMSU measurements / Fatima Karbou in IEEE Transactions on geoscience and remote sensing, vol 43 n° 5 (May 2005)
PermalinkMIRAS reference radiometer: a fully polarimetric noise injection radiometer / A. Colliander in IEEE Transactions on geoscience and remote sensing, vol 43 n° 5 (May 2005)
PermalinkNOAA operational hydrological products derived from the Advanced Microwave Sounding Unit / R.R. Ferraro in IEEE Transactions on geoscience and remote sensing, vol 43 n° 5 (May 2005)
PermalinkRepresenting and reducing error in natural-resource classification using model combination / Zhi Huang in International journal of geographical information science IJGIS, vol 19 n° 5 (may 2005)
PermalinkThe emissivity of foam-covered water surface at L-band: theoretical modelling and experimental results from the frog 2003 field experiment / A. Camps in IEEE Transactions on geoscience and remote sensing, vol 43 n° 5 (May 2005)
PermalinkVexcel ultracam D in operation: survey workflow with aerial digital camera / F. Hagman in GIM international, vol 19 n° 5 (May 2005)
PermalinkApplication of an automated cloud-tracking algorithm on satellite imagery for tracking and monitoring small mesoscale convective cloud systems / H. Feidas in International Journal of Remote Sensing IJRS, vol 26 n° 8 (April 2005)
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