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Tree model based eco-climatic vegetation classification and fuzzy mapping in diverse tropical deciduous ecosystems using multi-season NDVI / J. Krishnaswamy in International Journal of Remote Sensing IJRS, vol 25 n° 6 (March 2004)
[article]
Titre : Tree model based eco-climatic vegetation classification and fuzzy mapping in diverse tropical deciduous ecosystems using multi-season NDVI Type de document : Article/Communication Auteurs : J. Krishnaswamy, Auteur ; M.C. Kiran, Auteur ; K.N. Ganeshaiah, Auteur Année de publication : 2004 Article en page(s) : pp 1185 - 1205 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] arbre (mathématique)
[Termes IGN] classification
[Termes IGN] classification dirigée
[Termes IGN] écosystème
[Termes IGN] Kappa de Cohen
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] végétationRésumé : (Auteur) Many vegetation classification strategies in tropical ecosystems involving conventional image processing of original satellite imagery bands require considerable prior site knowledge, statistical assumptions, and are difficult, expensive and inconsistent. In this paper we show that the intra-annual variation and rates of change in NDVI for different parts of a large forest area in combination with rules derived from a tree model can be used for detailed vegetation mapping. We used three-date NDVI data for the Biligiri Rangaswamy Temple Wildlife Sanctuary in Karnataka, southern India comprising mean NDVI, coefficient of variation (CV) and two NDVI change vectors corresponding to intraseasonal NDVI differences. A rule-based classification using a tree model was developed at two levels. The overall kappa statistic is 0.61 at level 1 classification. indicating a strong correspondence with the raster version of the available vector reference map based on ground data, even though the two maps are not strictly comparable. Several limitations of the available reference map have been highlighted by the new technique, especially the absence of ecotones. At level two the tree model map has provided detailed classification of dry deciduous forests and new classes not available in the reference map. The method in combination with reference data also provides a framework for fuzzy classification. This technique offers a relatively simple cost-effective alternative to existing classification strategies, especially for areas with diverse evergreen and deciduous vegetation elements. Numéro de notice : A2004-088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000149989 En ligne : https://doi.org/10.1080/0143116031000149989 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26615
in International Journal of Remote Sensing IJRS > vol 25 n° 6 (March 2004) . - pp 1185 - 1205[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04061 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Hyperion, Ikonos, ALI, and ETM+ sensors in the study of African rainforests / Prasad S. Thenkabail in Remote sensing of environment, vol 90 n° 1 (15/03/2004)
[article]
Titre : Hyperion, Ikonos, ALI, and ETM+ sensors in the study of African rainforests Type de document : Article/Communication Auteurs : Prasad S. Thenkabail, Auteur ; E.A. Enclona, Auteur ; M.S. Ashton, Auteur ; C. Legg, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 23 - 43 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse comparative
[Termes IGN] Cameroun
[Termes IGN] carbone
[Termes IGN] carte de la végétation
[Termes IGN] classification
[Termes IGN] Congo (bassin)
[Termes IGN] forêt équatoriale
[Termes IGN] image EO1-ALI
[Termes IGN] image EO1-Hyperion
[Termes IGN] image Ikonos
[Termes IGN] image Landsat-ETM+
[Termes IGN] indice de végétation
[Termes IGN] masse végétale
[Termes IGN] occupation du solRésumé : (Auteur) The goal of this research was to compare narrowband hyperspectral Hyperion data with broadband hyperspatial IKONOS data and anced multispectral Advanced Land Imager (ALI) and Landsat-7 Enhanced Thematic Mapper Plus (ETM+) data through modeling and classifying complex rainforest vegetation. For this purpose, Hyperion, ALI, IKONOS, and ETM+ data were acquired for southern Cameroon, a region considered to be a representative area for tropical moist evergreen and semideciduous forests. Field data, collected in near-real time to coincide with satellite sensor overpass, were used to (1) quantify and model the biomass of tree, shrub, and weed species; and (2) characterize forest land use/land cover (LULC) classes. The study established that even the most advanced broadband sensors (i.e., ETM+, IKONOS, and ALI) had serious limitations in modeling biomass and in classifying forest LULC classes. The broadband models explained only 13-60% of the variability in biomass across primary forests, secondary forests, and fallows. The overall accuracies were between 42% and 51% for classifying nine complex rainforest LULC classes using the broadband data of these sensors. Within individual vegetation types (e.g., primary or secondary forest), the overall accuracies increased slightly, but followed a similar trend. Among the broadband sensors, ALI sensor performed better than the IKONOS and ETM+ sensors. When compared to the three broadband sensors, Hyperion narrowband data produced (1) models that explained 36-83% more of the variability in rainforest biomass, and (2) LULC classifications with 45-52% higher overall accuracies. Twenty-three Hyperion narrowbands that were most sensitive in modeling forest biomass and in classifying forest LULC classes were identified and discussed. Numéro de notice : A2004-127 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2003.11.018 En ligne : https://doi.org/10.1016/j.rse.2003.11.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26654
in Remote sensing of environment > vol 90 n° 1 (15/03/2004) . - pp 23 - 43[article]Accuracy analysis of remote sensing change detection by rule-based rationality evaluation with post-classification comparison / H. Liu in International Journal of Remote Sensing IJRS, vol 25 n° 5 (March 2004)
[article]
Titre : Accuracy analysis of remote sensing change detection by rule-based rationality evaluation with post-classification comparison Type de document : Article/Communication Auteurs : H. Liu, Auteur ; Q. Zhou, Auteur Année de publication : 2004 Article en page(s) : pp 1037 - 1050 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] classification
[Termes IGN] détection de changement
[Termes IGN] estimation de précision
[Termes IGN] image multitemporelle
[Termes IGN] Kappa de Cohen
[Termes IGN] zone urbaineRésumé : (Auteur) Accuracy assessment for remote sensing classification is commonly based on using an error matrix, or confusion table, which needs reference, or 'ground truthing', data to support. When undertaking change detection using numerous multi-temporal images, it is often difficult to make the accuracy assessment by the 'traditional' method, which typically requires simultaneous collection of reference data. In this study, we propose a new approach by arguing change rationality with post-classification comparison. Multitemporal Landsat TM images were classified for land use in an urban fringe area of Beijing, China and the post-classification comparison of these classified images shows change trajectories through the time series. These change trajectories were then analysed by assessing their rationality against a set of logical rules to separate cases of 'real land use change' and possible classification errors. The analvsis results show that the overall accuracy for land use change in the urban fringe area was 86%, with a fuzziness of 7%. Although it is argued that the uncertainty, still exists on classification accuracy assessed by this method. It nevertheless provides an alternative approach for more reasonable assessment when ideal simultaneous 'ground truthing' is not available. Numéro de notice : A2004-081 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/0143116031000150004 En ligne : https://doi.org/10.1080/0143116031000150004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26609
in International Journal of Remote Sensing IJRS > vol 25 n° 5 (March 2004) . - pp 1037 - 1050[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 080-04051 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Areas of fuzzy geographical entities / Cidália Costa Fonte in International journal of geographical information science IJGIS, vol 18 n° 2 (march 2004)
[article]
Titre : Areas of fuzzy geographical entities Type de document : Article/Communication Auteurs : Cidália Costa Fonte, Auteur ; W. Weldon, Auteur Année de publication : 2004 Article en page(s) : pp 127 - 150 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] classification floue
[Termes IGN] objet flou
[Termes IGN] opérateur spatial
[Termes IGN] requête (informatique)
[Termes IGN] sous ensemble flou
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Fuzzy Geographical Entities (FGEs) refer in this paper to geographical entities with fuzzy spatial extent. The use of FGEs in geographical information systems requires the existence of operators capable of processing them. In this paper, our contribution to that field focuses on the computation of areas. Two methods are considered, one crisp due to Rosenfeld (1984), which has limited applicability, and the other fuzzy, which is a new approach. The new fuzzy area operator gives more information about the possible values of the area and enables the fuzziness in the spatial extent of the entity to be propagated to the area. Crisp and fuzzy areas have different meanings, and the use of one or the other depends not only on the purpose of the computation but also on the semantics of the membership functions. When the FGEs are represented by normal fuzzy sets, the fuzzy area operator generates fuzzy numbers, and therefore arithmetic operations can be performed with them using fuzzy arithmetic. However, we show that care must be taken with the use of the fuzzy arithmetic operators because, in some situations, the usual operators should not be applied. Properties of the Rosenfeld and fuzzy area operators are analysed, establishing a parallel with properties of the areas of crisp sets. Numéro de notice : A2004-039 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article DOI : 10.1080/13658810310001620933 En ligne : https://doi.org/10.1080/13658810310001620933 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26567
in International journal of geographical information science IJGIS > vol 18 n° 2 (march 2004) . - pp 127 - 150[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-04021 RAB Revue Centre de documentation En réserve L003 Disponible A double continuous approach to visualization and analysis of categorial maps / T. Hengl in International journal of geographical information science IJGIS, vol 18 n° 2 (march 2004)
[article]
Titre : A double continuous approach to visualization and analysis of categorial maps Type de document : Article/Communication Auteurs : T. Hengl, Auteur ; D.J.J. Walvoort, Auteur ; et al., Auteur Année de publication : 2004 Article en page(s) : pp 183 - 202 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse factorielle
[Termes IGN] carte thématique
[Termes IGN] classification barycentrique
[Termes IGN] classification floue
[Termes IGN] cohérence des couleurs
[Termes IGN] pixel
[Termes IGN] système d'information géographique
[Termes IGN] taxinomie
[Termes IGN] traitement d'image
[Termes IGN] transformation intensité-teinte-saturation
[Termes IGN] visualisation cartographiqueRésumé : (Auteur) A method to visualize multiple membership maps, called 'Colour mixture' (CM) is described and compared with alternative techniques: defuzzification and Pixel mixture. Six landform parameters were used to derive the landform classes using supervised fuzzy k-means classification. The continuous categorical map is derived by GIS calculations with colours, where colour values are considered to represent the taxonomic space spanned by the attribute variables. Coordinates of the nine class centres (landform facets) were first transformed from multivariate to two-dimensional attribute space using factor analysis, and then projected on the Hue Saturation Intensity (HSI) colourwheel. The taxonomic value was coded with the Hue and confusion with Saturation. To improve visual impression, saturation was replaced with whiteness. Classes that were closer in attribute space were merged into similar generic colours. The CM technique limits the derived mixed-colour map to seven generic hues independently of the total number of classes, which provides a basis for automated generalization. The confusion index derived from the mixed-colour map was used to derive primary boundaries and to locate areas of higher taxonomic confusion. Numéro de notice : A2004-042 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810310001620924 En ligne : https://doi.org/10.1080/13658810310001620924 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=26570
in International journal of geographical information science IJGIS > vol 18 n° 2 (march 2004) . - pp 183 - 202[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-04021 RAB Revue Centre de documentation En réserve L003 Disponible Evaluation comparative en cartographie forestière de l'analyse de texture et de la transformée en paquets d'ondelettes par le moyen d'un classifieur / A. Hammouch in Photo interprétation, vol 40 n° 1 (Mars 2004)PermalinkUsing maximum likelihood (ML) and maximum a prior probability (MAP) in iterative self-organizing data (Isodata) / Hassan A. Karimi in Geocarto international, vol 19 n° 1 (March - May 2004)PermalinkEstimation of land surface temperature-vegetation abundance relationship for urban heat island studies / Q. Wenger in Remote sensing of environment, vol 89 n° 4 (29/02/2004)PermalinkCarbon mass fluxes of forests in Belgium determined with low resolution optical sensors / F. Veroustraete in International Journal of Remote Sensing IJRS, vol 25 n° 4 (February 2004)PermalinkImproving tropical forest mapping using multi-date Landsat TM data and pre-classification image smoothing / C. Tottrup in International Journal of Remote Sensing IJRS, vol 25 n° 4 (February 2004)PermalinkDelineation of forest/nonforest land use classes using nearest neighbor methods / R. Haapanen in Remote sensing of environment, vol 89 n° 3 (15/02/2004)PermalinkApproaches to fractional land cover and continuous field mapping: a comparative assessment over the BOREAS [BOReal Ecosystem Atmosphere Study] study region / R. Fernandes in Remote sensing of environment, vol 89 n° 2 (30/01/2004)PermalinkRemote sensing in BOREAS [BOReal Ecosystem Atmosphere Study]: Lessons learned / John A. Gamon in Remote sensing of environment, vol 89 n° 2 (30/01/2004)PermalinkMapping rice field anopheline breeding habitats in Mali, West Africa, using Landsat ETM+ sensor data / M.A. Diuk-Wasser in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)PermalinkUnsupervised classification of hyperspectral data: an ICA mixture model based approach / Chintan A. Shah in International Journal of Remote Sensing IJRS, vol 25 n° 2 (January 2004)Permalink