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Quantifying spatial heterogeneity at the landscape scale using variogram models / S. Garrigues in Remote sensing of environment, vol 103 n° 1 (15 July 2006)
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Titre : Quantifying spatial heterogeneity at the landscape scale using variogram models Type de document : Article/Communication Auteurs : S. Garrigues, Auteur ; Denis Allard, Auteur ; F. Baret, Auteur ; M. Weiss, Auteur Année de publication : 2006 Article en page(s) : pp 81 - 96 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] couvert végétal
[Termes IGN] erreur systématique
[Termes IGN] hétérogénéité spatiale
[Termes IGN] image à basse résolution
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] pixel
[Termes IGN] utilisation du sol
[Termes IGN] variogrammeRésumé : (Auteur) The monitoring of earth surface dynamic processes at a global scale requires high temporal frequency remote sensing observations which are provided up to now by moderate spatial resolution sensors. However, the spatial heterogeneity within the moderate spatial resolution pixel biases non-linear estimation processes of land surface variables from remote sensing data. To limit its influence on the description of land surface processes, corrections based on the quantification of the intra-pixel heterogeneity may be applied to non-linear estimation processes. A complementary strategy is to define the proper pixel size to capture the spatial variability of the data and minimize the intra-pixel variability.
This work provides a methodology to characterize and quantify the spatial heterogeneity of landscape vegetation cover from the modeling of the variogram of high spatial resolution NDVI data. NDVI variograms for 18 landscapes extracted from the VALERI database show that the land use is the main factor of spatial variability as quantified by the variogram sill. Crop sites are more heterogeneous than natural vegetation and forest sites at the landscape level. The integral range summarizes all structural parameters of the variogram into a single characteristic area. Its square root quantifies the mean length scale (i.e. spatial scale) of the data, which varies between 216 and 1060 m over the 18 landscapes considered. The integral range is also used as a yardstick to judge if the size of an image is large enough to measure properly the length scales of the data with the variogram. We propose that it must be smaller than 5% of the image surface. The theoretical dispersion variance, computed from the variogram model, quantifies the spatial heterogeneity within a moderate resolution pixel. It increases rapidly with pixel size until this size is larger than the mean length scale of the data. Finally based on the analysis of 18 landscapes, the sufficient pixel size to capture the major part of the spatial variability of the vegetation cover at the landscape scale is estimated to be less than 100 m. Since for all the heterogeneous landscapes the loss of NDVI spatial variability was small at this spatial resolution, the bias generated by the intra-pixel spatial heterogeneity on non-linear estimation processes will be reduced. Copyright ElsevierNuméro de notice : A2006-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2006.03.013 En ligne : https://doi.org/10.1016/j.rse.2006.03.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28010
in Remote sensing of environment > vol 103 n° 1 (15 July 2006) . - pp 81 - 96[article]Incorporating domain knowledge and spatial relationships into land cover classifications: a rule-based approach / A.E. Daniels in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)
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Titre : Incorporating domain knowledge and spatial relationships into land cover classifications: a rule-based approach Type de document : Article/Communication Auteurs : A.E. Daniels, Auteur Année de publication : 2006 Article en page(s) : pp 2949 - 2975 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] carte d'occupation du sol
[Termes IGN] classe d'objets
[Termes IGN] classification à base de connaissances
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] données auxiliaires
[Termes IGN] feuillu
[Termes IGN] forêt tropicale
[Termes IGN] interprétation automatique
[Termes IGN] occupation du sol
[Termes IGN] précision de la classificationRésumé : (Auteur) For some tropical regions, remote sensing of land cover yields unacceptable results, particularly as the number of land cover classes increases. This research explores the utility of incorporating domain knowledge and multiple algorithms into land cover classifications via a rule-based algorithm for a series of satellite images. The proposed technique integrates the fundamental, knowledge-based interpretation elements of remote sensing without sacrificing the ease and consistency of automated, algorithm-based processing. Compared with results from a traditional maximum likelihood algorithm, classification accuracy was improved substantially for each of the six land cover classes and all three years in the image series. Use of domain knowledge proved effective in accurately classifying problematic tropical land covers, such as tropical deciduous forest and seasonal wetlands. Results also suggest that ancillary data may be most useful in the classification of historic images, where the greatest improvement was observed relative to results from maximum likelihood. The cost of incorporating contextual knowledge and extensive spatial data sets may be justified, since results from the proposed technique suggest a considerable improvement in accuracy may be achieved. Copyright Taylor & Francis Numéro de notice : A2006-310 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600567753 En ligne : https://doi.org/10.1080/01431160600567753 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28034
in International Journal of Remote Sensing IJRS > vol 27 n°12-13-14 (July 2006) . - pp 2949 - 2975[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-06071 RAB Revue Centre de documentation En réserve L003 Disponible A new method to determine near surface air temperature from satellite observations / Ranjit Singh in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)
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Titre : A new method to determine near surface air temperature from satellite observations Type de document : Article/Communication Auteurs : Ranjit Singh, Auteur ; C.M. Kishtawal, Auteur Année de publication : 2006 Article en page(s) : pp 2831 - 2846 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] algorithme génétique
[Termes IGN] image DMSP-SSM/I
[Termes IGN] image NOAA-AVHRR
[Termes IGN] température au sol
[Termes IGN] température de surface de la mer
[Termes IGN] température en altitude
[Termes IGN] vapeur d'eauRésumé : (Auteur) We present a new method to determine the near surface air temperature (Ta) from satellite observations. The satellite observed parameters of total precipitable water (W), atmospheric boundary layer (~500 m) water vapour (Wb), and sea surface temperature (SST) are used to derive Ta. A genetic algorithm (GA) is used to find the optimum relation between the input (W, Wb, SST) and output (Ta) parameters. The input data consist of 6 years (1988–1993) of insTanTaneous as well as monthly averages of W, Wb from the Special Sensor Microwave Imager (SSM/I), and SST data from the Advanced Very High Resolution Radiometer (AVHRR). Ta observations based on Comprehensive Ocean Atmospheric Data Set (COADS) are used to develop and evaluate the new methodology. The global mean root mean square (rms) error for instantaneous Ta estimates is 1.4°C and for monthly averages it decreases to 0.74°C. Slightly higher discrepancies between Ta derived from the new method and in situ data are found over the western boundary currents (such as the Kuroshio and Gulf Stream) during wintertime. These regions are characterized by continental cold air outbreak and seasonal current systems, particularly during wintertime. During these conditions weak coupling between SST and Ta may be one of the reasons for large error over these regions. Our method improves upon the air temperature estimates of earlier studies. Copyright Taylor & Francis Numéro de notice : A2006-307 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160500195234 En ligne : https://doi.org/10.1080/01431160500195234 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28031
in International Journal of Remote Sensing IJRS > vol 27 n°12-13-14 (July 2006) . - pp 2831 - 2846[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-06071 RAB Revue Centre de documentation En réserve L003 Disponible Scale sets image analysis / Laurent Guigues in International journal of computer vision, vol 68 n°3 (July 2006)
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Titre : Scale sets image analysis Type de document : Article/Communication Auteurs : Laurent Guigues , Auteur ; Jean-Pierre Cocquerez, Auteur ; Hervé Le Men
, Auteur
Année de publication : 2006 Article en page(s) : pp 289 - 317 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] géométrie de l'image
[Termes IGN] méthode de réduction d'énergie
[Termes IGN] partitionnement
[Termes IGN] programmation dynamique
[Termes IGN] représentation multiple
[Termes IGN] segmentation d'imageRésumé : (auteur) This paper introduces a multi-scale theory of piecewise image modelling, called the scale-sets theory, and which can be regarded as a region-oriented scale-space theory. The first part of the paper studies the general structure of a geometrically unbiased region-oriented multi-scale image description and introduces the scale-sets representation, a representation which allows to handle such a description exactly. The second part of the paper deals with the way scale-sets image analyses can be built according to an energy minimization principle. We consider a rather general formulation of the partitioning problem which involves minimizing a two-term-based energy, of the form λC + D, where D is a goodness-of-fit term and C is a regularization term. We describe the way such energies arise from basic principles of approximate modelling and we relate them to operational rate/distorsion problems involved in lossy compression problems. We then show that an important subset of these energies constitutes a class of multi-scale energies in that the minimal cut of a hierarchy gets coarser and coarser as parameter λ increases. This allows us to devise a fast dynamic-programming procedure to find the complete scale-sets representation of this family of minimal cuts. Considering then the construction of the hierarchy from which the minimal cuts are extracted, we end up with an exact and parameter-free algorithm to build scale-sets image descriptions whose sections constitute a monotone sequence of upward global minima of a multi-scale energy, which is called the “scale climbing” algorithm. This algorithm can be viewed as a continuation method along the scale dimension or as a minimum pursuit along the operational rate/distorsion curve. Furthermore, the solution verifies a linear scale invariance property which allows to completely postpone the tuning of the scale parameter to a subsequent stage. For computational reasons, the scale climbing algorithm is approximated by a pair-wise region merging scheme: however the principal properties of the solutions are kept. Some results obtained with Mumford-Shah’s piece-wise constant model and a variant are provided and different applications of the proposed multi-scale analyses are finally sketched. Numéro de notice : A2006-660 Affiliation des auteurs : MATIS+Ext (1993-2011) Thématique : IMAGERIE Nature : Article DOI : 10.1007/s11263-005-6299-0 Date de publication en ligne : 01/04/2006 En ligne : http://doi.org/10.1007/s11263-005-6299-0 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86514
in International journal of computer vision > vol 68 n°3 (July 2006) . - pp 289 - 317[article]A technique for generating natural colour images from false colour composite images / S.K. Patra in International Journal of Remote Sensing IJRS, vol 27 n°12-13-14 (July 2006)
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Titre : A technique for generating natural colour images from false colour composite images Type de document : Article/Communication Auteurs : S.K. Patra, Auteur ; M. Shekher, Auteur ; et al., Auteur Année de publication : 2006 Article en page(s) : pp 2977 - 2989 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bande spectrale
[Termes IGN] couleur (variable spectrale)
[Termes IGN] couleur à l'écran
[Termes IGN] image en couleur composée
[Termes IGN] point d'appui
[Termes IGN] superposition d'imagesRésumé : (Auteur) Colour is widely used in remote sensing work. In many instances, the use of colour conveys additional information both visually and scientifically. Remote sensing satellites view the earth in different spectral bands, viz. near infrared (NIR), red, green, and blue bands, in a conventional multispectral imaging system. In the absence of a blue channel, colour images can be generated using near infrared, red, and green bands in what is known as a false colour composite (FCC) and does not look natural, like the image we see with the naked eye. For a trained interpreter, this does not pose any problems. However, when the intended use is a fly-through of a draped terrain, visual interpretation, or a display, meant for the non-remote sensing professional, this becomes a handicap. To overcome this, there is a requirement to generate natural colour composites (NCC) from the given false colour composite, which demands the simulation of a blue band to be combined with green and red bands. This paper describes a unique method of generating a blue band to form natural colour images from a given false colour image set. We use a spectral transformation method to establish a relationship between the false colour and true colour image pairs provided by a sensor with all the four bands, which has a broader spectral coverage. A transformation function is fitted by selecting radiometric control points along the line of geometric registration to find a set of coefficients to be used for simulating a blue band. This blue band, along with the green and red bands, provides a near true colour or ‘natural colour’ on the display. In this paper, we present a set of adjustable radiometric transformation coefficients to accommodate variation in spatial and dynamic range offered by sensors to generate natural colour. These coefficients seem to work on a large number of images of different seasons, provided similar spectral bands and terrain are used. The proposed ‘natural colour generator’ can be used in changing false colour images to natural colour images with the aim of ‘what you get is what you would have seen’. Copyright Taylor & Francis Numéro de notice : A2006-311 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431160600554322 En ligne : https://doi.org/10.1080/01431160600554322 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28035
in International Journal of Remote Sensing IJRS > vol 27 n°12-13-14 (July 2006) . - pp 2977 - 2989[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-06071 RAB Revue Centre de documentation En réserve L003 Disponible Urban land-use classification using variogram-based analysis with an aerial photograph / S.S. Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 72 n° 7 (July 2006)
PermalinkEnhancing a sequence of facial images combining multiple undersampled and compressed images / G. Scarmana in Photogrammetric record, vol 21 n° 114 (June - August 2006)
PermalinkHigh-resolution change estimation of soil moisture using L-band radiometer and Radar observations made during the SMEX02 experiments / U. Narayan in IEEE Transactions on geoscience and remote sensing, vol 44 n° 6 (June 2006)
PermalinkPerformance metrics: how and when / S.A. Israel in Geocarto international, vol 21 n° 2 (June - August 2006)
PermalinkPermalink3D simulation of soft-objects / D.Y. Shen in International journal of geographical information science IJGIS, vol 20 n° 3 (march 2006)
PermalinkDetecting roads in stabilized video with the spatio-temporal structure tensor / R. Plessl in Geoinformatica, vol 10 n° 1 (March - May 2006)
PermalinkSegmentation multi-échelles d'images et applications / Laurent Guigues in Bulletin d'information scientifique et technique de l'IGN, n° 75 (mars 2006)
PermalinkA new approach to the nearest-neighbour method to discover cluster features in overlaid spatial point processes / Tao Pei in International journal of geographical information science IJGIS, vol 20 n° 2 (february 2006)
PermalinkParcel-based classification / J. Wijnant in GEO: Geoconnexion international, vol 5 n° 2 (february 2006)
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