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Temporal change in the landscape erosion pattern in the Yellow River basin / W. Siyuan in International journal of geographical information science IJGIS, vol 21 n° 9-10 (october 2007)
[article]
Titre : Temporal change in the landscape erosion pattern in the Yellow River basin Type de document : Article/Communication Auteurs : W. Siyuan, Auteur ; L. Jingshi, Auteur ; Y. Cunjian, Auteur Année de publication : 2007 Article en page(s) : pp 1077 - 1092 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] agriculture
[Termes IGN] bassin hydrographique
[Termes IGN] Chine
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] érosion hydrique
[Termes IGN] Fleuve jaune (Chine)
[Termes IGN] gestion durable
[Termes IGN] image Landsat-TM
[Termes IGN] impact sur l'environnement
[Termes IGN] urbanisation
[Termes IGN] utilisation du solRésumé : (Auteur) Using Landsat TM data from 1995 and 2000, changes in the landscape erosion pattern of the Yellow River Basin, China were analysed. The aim was to improve our understanding of soil-erosion change so that sustainable land use could be established. First, a soil-erosion intensity index model was developed to study soil-erosion intensity change in the study area. Over the 5 years, the areas of weak erosion, moderate erosion, severe erosion, and very severe erosion all increased. The area of weak erosion increased dramatically by 7.94*105 ha, and areas of slight erosion and acute erosion decreased by 1.93*106 ha and 4.50*104 ha, respectively. The results show that while the intensity of soil erosion has gradually been decreasing as a whole, in some regions the soil erosion is becoming more severe. Based on landscape indices, the pattern of changes in soil erosion over the past 5 years was analysed. The changes in landscape pattern of soil erosion resulted from human activities. Analysis showed that human impact increases fragmentation, having three major effects on landscape pattern, reduction in patch area, variations in patch shape, and changes in spatial pattern. In the study area, population growth, farming, governmental policy and forest degradation are the major factors causing soil erosion change over a 5-year period. Copyright Taylor & Francis Numéro de notice : A2007-557 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/13658810701228645 En ligne : https://doi.org/10.1080/13658810701228645 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28920
in International journal of geographical information science IJGIS > vol 21 n° 9-10 (october 2007) . - pp 1077 - 1092[article]Exemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 079-07061 RAB Revue Centre de documentation En réserve L003 Disponible 079-07062 RAB Revue Centre de documentation En réserve L003 Disponible Estimation of vegetation parameter for modelling soil erosion using linear spectral mixture analysis of Landsat ETM data / A.M. DE Asis in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 4 (September 2007)
[article]
Titre : Estimation of vegetation parameter for modelling soil erosion using linear spectral mixture analysis of Landsat ETM data Type de document : Article/Communication Auteurs : A.M. DE Asis, Auteur ; K. Omasa, Auteur Année de publication : 2007 Article en page(s) : pp 309 - 324 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] classification pixellaire
[Termes IGN] couvert végétal
[Termes IGN] données de terrain
[Termes IGN] érosion
[Termes IGN] estimation statistique
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Quickbird
[Termes IGN] modèle physique
[Termes IGN] modèle RUSLERésumé : (Auteur) Soil conservation planning often requires estimates of soil erosion at a catchment or regional scale. Predictive models such as Universal Soil Loss Equation (USLE) and its subsequent Revised Universal Soil Loss Equation (RUSLE) are useful tools to generate the quantitative estimates necessary for designing sound conservation measures. However, large-scale soil erosion model-factor parameterization and quantification is difficult due to the costs, labor and time involved. Among the soil erosion parameters, the vegetative cover or C factor has been one of the most difficult to estimate over broad geographic areas. The C factor represents the effects of vegetation canopy and ground covers in reducing soil loss. Traditional methods for the extraction of vegetation information from remote sensing data such as classification techniques and vegetation indices were found to be inaccurate. Thus, this study presents a new approach based on Spectral Mixture Analysis (SMA) of Landsat ETM data to map the C factor for use in the modeling of soil erosion. A desirable feature of SMA is that it estimates the fractional abundance of ground cover and bare soils simultaneously, which is appropriate for soil erosion analysis. Hence, we estimated the C factor by utilizing the results of SMA on a pixel-by-pixel basis. We specifically used a linear SMA (LSMA) model and performed a minimum noise fraction (MNF) transformation and pixel purity index (PPI) on Landsat ETM image to derive the proportion of ground cover (vegetation and non-photosynthetic materials) and bare soil within a pixel. The end-members were selected based on the purest pixels found using PPI with reference to very high-resolution QuickBird image and actual field data. Results showed that the C factor value estimated using LSMA correlated strongly with the values measured in the field. The correlation coefficient (r) obtained was 0.94. A comparative analysis between NDVI- and LSMA-derived C factors also proved that the latter produced a more detailed spatial variability, as well as generated more accurate erosion estimates when used as input to RUSLE model. The QuickBird image coupled with field data was used in the validation of results. Copyright ISPRS Numéro de notice : A2007-430 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2007.05.013 En ligne : https://doi.org/10.1016/j.isprsjprs.2007.05.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28793
in ISPRS Journal of photogrammetry and remote sensing > vol 62 n° 4 (September 2007) . - pp 309 - 324[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-07061 SL Revue Centre de documentation Revues en salle Disponible Assessing alternatives for modelling the spatial distribution of multiple land-cover classes at sub-pixel scales / Y. Makido in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 8 (August 2007)
[article]
Titre : Assessing alternatives for modelling the spatial distribution of multiple land-cover classes at sub-pixel scales Type de document : Article/Communication Auteurs : Y. Makido, Auteur ; A. Shortridge, Auteur ; P. Messina, Auteur Année de publication : 2007 Article en page(s) : pp 935 - 943 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse infrapixellaire
[Termes IGN] autocorrélation spatiale
[Termes IGN] distribution spatiale
[Termes IGN] image Landsat-ETM+Résumé : (Auteur) We introduce and evaluate three methods for modeling the spatial distribution of multiple land-cover classes at subpixel scales: (a) sequential categorical swapping, (b) simultaneous categorical swapping, and (c) simulated annealing. Method 1, a modification of a binary pixel-swapping algorithm, allocates each class in turn to maximize internal spatial autocorrelation. Method 2 simultaneously examines all pairs of cell-class combinations within a pixel to determine the most appropriate pairs of sub-pixels to swap. Method 3 employs simulated annealing to swap cells. While convergence is relatively slow, Method 3 offers increased flexibility. Each method is applied to a classified Landsat-7 ETM dataset that has been resampled to a spatial resolution of 210 m, and evaluated for accuracy performance and computational efficiency. Numéro de notice : A2007-371 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.73.8.935 En ligne : http://dx.doi.org/10.14358/PERS.73.8.935 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28734
in Photogrammetric Engineering & Remote Sensing, PERS > vol 73 n° 8 (August 2007) . - pp 935 - 943[article]Multitemporel fuzzy classification model based on class transition possibilities / G.L.A. Mota in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)
[article]
Titre : Multitemporel fuzzy classification model based on class transition possibilities Type de document : Article/Communication Auteurs : G.L.A. Mota, Auteur ; R. Feitosa, Auteur ; H.L.C. Coutinho, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 186 - 200 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme génétique
[Termes IGN] Brésil
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification floue
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] modélisation spatialeRésumé : (Auteur) This paper proposes a new method to model temporal knowledge and to combine it with spectral and spatial knowledge within an integrated fuzzy automatic image classification framework for land-use land-cover map update applications. The classification model explores not only the object features, but also information about its class at a previous date. The method expresses temporal class dependencies by means of a transition diagram, assigning a possibility value to each class transition. A Genetic Algorithm (GA) carries out the class transition possibilities estimation. Temporal and spectral/spatial classification results are combined by means of fuzzy aggregation. The improvement achieved by the use of multitemporal knowledge rather than a pure monotemporal approach was assessed in a real application using LANDSAT images from Midwest Brazil. The experiments showed that the use of temporal knowledge markedly improved the classification performance, in comparison to a conventional single-time classification. A further observation was that multitemporal knowledge may subsume the knowledge related to steady spatial attributes whose values do not significantly change over time. Copyright ISPRS Numéro de notice : A2007-368 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2007.04.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2007.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28731
in ISPRS Journal of photogrammetry and remote sensing > vol 62 n° 3 (August 2007) . - pp 186 - 200[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-07051 SL Revue Centre de documentation Revues en salle Disponible Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping / Robert Lucas in ISPRS Journal of photogrammetry and remote sensing, vol 62 n° 3 (August 2007)
[article]
Titre : Rule-based classification of multi-temporal satellite imagery for habitat and agricultural land cover mapping Type de document : Article/Communication Auteurs : Robert Lucas, Auteur ; A. Rowlands, Auteur ; A. Brown, Auteur ; et al., Auteur Année de publication : 2007 Article en page(s) : pp 165 - 185 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification floue
[Termes IGN] eCognition
[Termes IGN] habitat (urbanisme)
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] indice de végétation
[Termes IGN] intelligence artificielle
[Termes IGN] logique floue
[Termes IGN] Pays de Galles
[Termes IGN] segmentation d'image
[Termes IGN] série temporelleRésumé : (Auteur) The aim is to evaluate the use of time-series of Landsat sensor data acquired over an annual cycle for mapping semi-natural habitats and agricultural land cover. The location is Berwyn Mountains, North Wales, United Kingdom. The methods are Using eCognition Expert, segmentation of the Landsat sensor data was undertaken for actively managed agricultural land based on Integrated Administration and Control System (IACS) land parcel boundaries, whilst a per-pixel level segmentation was undertaken for all remaining areas. Numerical decision rules based on fuzzy logic that coupled knowledge of ecology and the information content of single and multi-date remotely sensed data and derived products (e.g., vegetation indices) were developed to discriminate vegetation types based primarily on inferred differences in phenology, structure, wetness and productivity. The results : The rule-based classification gave a good representation of the distribution of habitats and agricultural land. The more extensive, contiguous and homogeneous habitats could be mapped with accuracies exceeding 80%, although accuracies were lower for more complex environments (e.g., upland mosaics) or those with broad definition (e.g., semi-improved grasslands). The application of a rule-based classification to temporal imagery acquired over selected periods within an annual cycle provides a viable approach for mapping and monitoring of habitats and agricultural land in the United Kingdom that could be employed operationally. Copyright ISPRS Numéro de notice : A2007-367 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2007.03.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2007.03.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=28730
in ISPRS Journal of photogrammetry and remote sensing > vol 62 n° 3 (August 2007) . - pp 165 - 185[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-07051 SL Revue Centre de documentation Revues en salle Disponible Spatio-temporal urban landscape change analysis using the Markov chain model and a modified genetic algorithm / J. Tang in International Journal of Remote Sensing IJRS, vol 28 n°15-16 (August 2007)PermalinkSpectral properties and reflectance curves of the revealed volcanic rocks in Syria using radiometric measurements / M. Rukieh in International Journal of Remote Sensing IJRS, vol 28 n°15-16 (August 2007)PermalinkApports de la télédétection à l'étude de la déformation des chainons de Metlaoui (Tunisie Centro-méridionale) / Maged Jabbour in Photo interprétation, vol 43 n° 2 (Juin 2007)PermalinkÉvaluation comparative des images Ikonos pour la cartographie de l'occupation du sol à différentes échelles : cas d'étude au Liban / C. Abdallah in Photo interprétation, vol 43 n° 2 (Juin 2007)PermalinkIntegrated use of SRM, Landsat ETM+ data and 3D perspective views to identify the tectonic geomorphology of Dehradun valley, India / A.K. Singh in International Journal of Remote Sensing IJRS, vol 28 n°11-12 (June 2007)PermalinkMapping of salt-affected soils using TM images / P. Garcia Rodriguez in International Journal of Remote Sensing IJRS, vol 28 n°11-12 (June 2007)PermalinkModelling and mapping potential hooded warbler (Wilsonia citrina) habitat using remotely sensed imagery / J. Pasher in Remote sensing of environment, vol 107 n° 3 (12 April 2007)PermalinkA comparison of four common atmospheric correction methods / A.S. Mahiny in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)PermalinkImproving land-cover classification using recognition threshold neural networks / M.J. Aitkenhead in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 4 (April 2007)PermalinkSpace analysis and the detection of the changes for the follow-up of the components sand-vegetation in the area of Mecheria, Algeria / I. Haddouch in Revue Française de Photogrammétrie et de Télédétection, n° 185 (Mars 2007)PermalinkClassification of biodiversity in Doi Inthanon national parc / H. Draux (2007)PermalinkWoody vegetation increase in Alpine areas: a proposal for a classification and validation scheme / M. Maggi in International Journal of Remote Sensing IJRS, vol 28 n° 1-2 (January 2007)PermalinkApport des données Spot et Landsat au suivi des inondations dans l'estuaire du fleuve Sénégal / A.M. Dia in Photo interprétation, vol 42 n° 4 (Décembre 2006)PermalinkApports de l'imagerie spatiale à la résolution des structures géologiques en zone équatoriale: exemples du Précambrien au Kivu (Congo oriental) / M. Villeneuve in Photo interprétation, vol 42 n° 4 (Décembre 2006)PermalinkComparison and integration of radar and optical data for land use / cover mapping / Nathaniel D. Herold in Geocarto international, vol 21 n° 4 (December 2006 - February 2007)PermalinkDelineating lakes and enclosed islands in satellite imagery by geodesic active contour model / C. Shen in International Journal of Remote Sensing IJRS, vol 27 n°23-24 (December 2006)PermalinkIntegration of GPS and remote sensing into GIS: a case study of rectifying satellite imagery using uncorrected coordinates in different scenes / J. Gao in Geocarto international, vol 21 n° 4 (December 2006 - February 2007)PermalinkLineament analysis through remote sensing as a contribution to the identification of caves in western Lebanon / A. Shaban in Photo interprétation, vol 42 n° 4 (Décembre 2006)PermalinkPeut-on mesurer les effets du CRIGE PACA ? / Françoise de Blomac in SIG la lettre, n° 82 (décembre 2006)PermalinkAssessment of EOS aqua AMSR-E artic sea ice concentrations using Landsat-7 and airborne microwave imagery / D.J. Cavalieri in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 1 (November 2006)Permalink