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A comparison of vector and raster GIS methods for calculating landscape metrics used in environmental assessments / T.G. Wade in Photogrammetric Engineering & Remote Sensing, PERS, vol 69 n° 12 (December 2003)
[article]
Titre : A comparison of vector and raster GIS methods for calculating landscape metrics used in environmental assessments Type de document : Article/Communication Auteurs : T.G. Wade, Auteur ; J.D. Wickham, Auteur ; M.S. Nash, Auteur ; A.C. Neale, Auteur ; K. Riitters, Auteur ; K.B. Jones, Auteur Année de publication : 2003 Article en page(s) : pp 1399 - 1405 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de groupement
[Termes IGN] données maillées
[Termes IGN] données vectorielles
[Termes IGN] environnement
[Termes IGN] estimation statistique
[Termes IGN] ligne de partage des eaux
[Termes IGN] paysage
[Termes IGN] système d'information géographiqueRésumé : (Auteur)GIS-based measurements that combine native raster and native vector data are commonly used in environmental assessments. Most of these measurements can be calculated using either raster or vector data formats and processing methods. Raster processes are more commonly used because they can be significantly faster computationally than vector, but error is introduced in converting vector data to raster. This conversion error has been widely studied and quantified, but the impact on environmental assessment results has not been investigated. We examined four Gis-based measurements commonly used in environmental assessments for approximately 1000 watersheds in the state of Maryland and Washington, D.C. Each metric was calculated using vector and raster methods, and estimated values were compared using a paired t-test, Spearman rank correlation, and cluster analyses. Paired t-tests were used to determine the statistical significance of quantitative differences between methods, and Spearman rank correlation and cluster analyses were used to evaluate the impact of the differences on environmental assessments. Paired t-test results indicated significant quantitative differences between methods for three of the four metrics. However, Spearman ranks and cluster analyses indicated that the quantitative differences would not affect environmental assessment results. Spearman rank correlations between vector and raster values were greater than 0.98 for all comparisons. Cluster analyses resulted in identical assignment for 88 percent to over 98 percent of watersheds analyzed among vector and various raster methods. Numéro de notice : A2003-359 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.69.12.1399 En ligne : https://doi.org/10.14358/PERS.69.12.1399 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26439
in Photogrammetric Engineering & Remote Sensing, PERS > vol 69 n° 12 (December 2003) . - pp 1399 - 1405[article]Principal-components-based display strategy for spectral imagery / J.S. Tyo in IEEE Transactions on geoscience and remote sensing, vol 41 n° 3 (March 2003)
[article]
Titre : Principal-components-based display strategy for spectral imagery Type de document : Article/Communication Auteurs : J.S. Tyo, Auteur ; A. Konsolakis, Auteur ; D.I. Diersen, Auteur ; R.C. Olsen, Auteur Année de publication : 2003 Article en page(s) : pp 708 - 718 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] analyse en composantes principales
[Termes IGN] classification dirigée
[Termes IGN] image en pseudo-couleur
[Termes IGN] image hyperspectrale
[Termes IGN] image multidimensionnelle
[Termes IGN] image spectrale
[Termes IGN] teinteRésumé : (Auteur) A new pseudocolor mapping strategy for use with spectral imagery is presented. This strategy is based on a principal components analysis of spectral data, and it capitalizes on the similarities between three-color human vision and high-dimensional hyperspectral datasets. The mapping is closely related to three-dimensional versions of scatter plots that are commonly used in remote sensing to visualize the data cloud. The transformation results in final images where the color assigned to each pixel is solely determined by the position within the data cloud. Materials with similar spectral characteristics are presented in similar hues, and basic classification and clustering decisions can be made by the observer. Final images tend to have large regions of desaturated pixels that make the image more readily interpretable. The data cloud is shown here to be conical in nature, and materials with common spectral signatures radiate from the origin of the cone, which is not (in general) at the origin of the spectral data. A supervised method for locating the origin of the cone based on identification of clusters in the data is presented, and the effects of proper origin orientation are illustrated. Numéro de notice : A2003-120 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2003.808879 En ligne : https://doi.org/10.1109/TGRS.2003.808879 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22416
in IEEE Transactions on geoscience and remote sensing > vol 41 n° 3 (March 2003) . - pp 708 - 718[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-03031 RAB Revue Centre de documentation En réserve L003 Disponible Landscape dynamics of the spread of sudden oak death / M. Kelly in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 10 (October 2002)
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Titre : Landscape dynamics of the spread of sudden oak death Type de document : Article/Communication Auteurs : M. Kelly, Auteur ; Ross K. Meentemeyer, Auteur Année de publication : 2002 Article en page(s) : pp 1001 - 1009 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse de groupement
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification non dirigée
[Termes IGN] distribution spatiale
[Termes IGN] dynamique spatiale
[Termes IGN] Fagus (genre)
[Termes IGN] forêt
[Termes IGN] image ADAR
[Termes IGN] image multibande
[Termes IGN] indice d'humidité
[Termes IGN] maladie phytosanitaire
[Termes IGN] modélisation spatiale
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] simulation dynamiqueRésumé : (Auteur) Sudden Oak Death is caused by a newly discovered virulent pathogen (Phytophthora ramorum) that is killing thousands of native oak trees in California. We present a landscape-scale study on the spatio-temporal dynamics of oak mortality. Second-order spatial point-pattern analysis techniques (Ripley's K) were applied to the distribution of dead tree crowns (derived from high-resolution imagery) in Marin County, California to determine the existence and scale of mortality clustering in two years (2000 and 2001). Both years showed clustering patterns between 100 and 300 m. A classification tree model was developed to predict spatial patterns of risk for oak mortality based on several landscapescale variables. Proximity to forest edge was the most important explanatory factor, followed by topographic moisture index, proximity to trails, abundance of Umbellularia californica, and potential summer solar radiation. This research demonstrates the utility of integrating remotely sensed imagery analysis with geographic information systems and spatial modeling for understanding the dynamics of exotic species invasions. Numéro de notice : A2002-233 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/october/2002_oct_1001- [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22147
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 10 (October 2002) . - pp 1001 - 1009[article]Large-area land-cover mapping through scene-based classification compositing / B. Guindon in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 6 (June 2002)
[article]
Titre : Large-area land-cover mapping through scene-based classification compositing Type de document : Article/Communication Auteurs : B. Guindon, Auteur ; C.M. Edmonds, Auteur Année de publication : 2002 Article en page(s) : pp 589 - 596 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de groupement
[Termes IGN] bassin hydrographique
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification non dirigée
[Termes IGN] image Landsat-MSS
[Termes IGN] image Landsat-TM
[Termes IGN] modèle stéréoscopique
[Termes IGN] recouvrement d'imagesRésumé : (Auteur) Over the past decade, a number of initiatives have been undertaken to create definitive national and global data sets consisting of precision corrected Landsat Multispectral Scanner (Mss) and Thematic Mapper (TM) scenes. One important application of these data is the derivation of large area ]andcover products spanning multiple satellite scenes. A popular approach to land-cover mapping on this scale involves merging constituent scenes into image mosaics prior to image clustering and cluster labeling, thereby eliminating redundant geographic coverage arising from overlapping imaging swaths of adjacent orbital tracks. In this paper, arguments are presented to support the view that areas of overlapping coverage contain important information that can be used to assess and improve classification performance. A methodology is presented for the creation of large area land-cover products through the compositing of independently classified scenes. Statistical analyses of classification consistency between scenes in overlapping regions are employed both to identify mislabeled clusters and to provide a measure of classification confidence for each scene at the cluster level. During classification compositing, confidence measures are used to rationalize conflicting classifications in overlap regions and to create a relative confidence layer, sampled at the pixel level, which characterizes the spatial variation in classification quality over the final product. The procedure is illustrated with results from a synoptic mapping project of the Great Lakes watershed that involved the classification and compositing of 46 Landsat Mss scenes. Numéro de notice : A2002-132 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/june/2002_jun_589-596. [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=22047
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 6 (June 2002) . - pp 589 - 596[article]A synergic automatic clustering technique (syneract) for multispectral image analysis / K.Y. Huang in Photogrammetric Engineering & Remote Sensing, PERS, vol 68 n° 1 (January 2002)
[article]
Titre : A synergic automatic clustering technique (syneract) for multispectral image analysis Type de document : Article/Communication Auteurs : K.Y. Huang, Auteur Année de publication : 2002 Article en page(s) : pp 33 - 40 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image numérique
[Termes IGN] analyse de groupement
[Termes IGN] classification dirigée
[Termes IGN] classification ISODATA
[Termes IGN] classification non dirigée
[Termes IGN] image multibandeRésumé : (Auteur) The Iterative Self-Organizing Data Analysis Technique (ISODATA) has been widely used in unsupervised and supervised classification. However, ISODATA suffers from several limitations. The user often spends much analyst time on specifying input parameters by trial and error, particularly initial cluster centers. Of more importance, an inapropriate choice of initial clusters may cause poor classification results. ISODATA is computationally intensive because of its iterative process . This study aimed to develop a synergistic automatic clustering technique (SYNERACT) that combined the hierachical descending and ISODATA clustering procedures to avoid those limitations. The two methods were compared using multispectral digitized video images. An inappropriate choice of initial seeds for SODATA was shown to reduce accuracies significantly. In contrast, SYNERACT was capable of determining the suitable locations for the initial clusters automatically from the data, therby avoiding those limitations. Owing to this capability, SYNERACT was not so heavily dependent on the iterative process as was ISODATA, and thus was much faster than ISODATA. SYNERACT also matched ISODATA in accuracy. Accordingly, SYNERACT could serve as an alternative to ISODATA for multispectral image analysis. Numéro de notice : A2002-008 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans En ligne : https://www.asprs.org/wp-content/uploads/pers/2002journal/january/2002_jan_33-40 [...] Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=21925
in Photogrammetric Engineering & Remote Sensing, PERS > vol 68 n° 1 (January 2002) . - pp 33 - 40[article]Detection of urban structures in SAR images by robust fuzzy clustering algorithms: the example of street tracking / F. Dell'acqua in IEEE Transactions on geoscience and remote sensing, vol 39 n° 10 (October 2001)PermalinkClustering to improve matched filter detection of weak gas plumes in hyperspectral thermal imagery / C.C. Funk in IEEE Transactions on geoscience and remote sensing, vol 39 n° 7 (July 2001)PermalinkGraph-based representations in pattern recognition, GbR'99 / Walter G. Kropatsch (1999)PermalinkSegmentierung und Interpretation digitaler Bilder mit Markoff-Zufallsfeldern / J. Klonowski (1999)PermalinkSDH 98 Proceedings, 8th international symposium on spatial data handling, Vancouver, July 11 - 15, 1998 / Thomas K. Poiker (1998)PermalinkNo fuzzy creep! A clustering algorithm for controlling arbitrary node movement / Francis Harvey (07/04/1997)PermalinkPermalinkKlassifizierung von multispektralen Bildern unter Verwendung der Clusterformen im Merkmalsraum / M. Zahn (1996)PermalinkMeasurement, characterization and classification for automated line feature generalization / Corinne Plazanet (1995)PermalinkCluster analysis of pine crown foliage patterns aid identification of mountain pine beetle current-attack / P.A. Murtha in Photogrammetric Engineering & Remote Sensing, PERS, vol 55 n° 1 (january 1989)PermalinkUsing cluster analysis to improve the selection of training statistics in classifying remotely sensed data / E. Chuvieco in Photogrammetric Engineering & Remote Sensing, PERS, vol 54 n° 9 (september 1988)PermalinkAdaptive clustering algorithm / Lawrence O'Malley in IBM Journal research and development, vol 29 n° 1 (01/01/1985)Permalink