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A moving weighted harmonic analysis method for reconstructing high-quality SPOT VEGETATION NDVI time-series data / Gang Yang in IEEE Transactions on geoscience and remote sensing, vol 53 n° 11 (November 2015)
[article]
Titre : A moving weighted harmonic analysis method for reconstructing high-quality SPOT VEGETATION NDVI time-series data Type de document : Article/Communication Auteurs : Gang Yang, Auteur ; Huanfeng Shen, Auteur ; Liangpei Zhang, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 6008 - 6021 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] analyse harmonique
[Termes IGN] Chine
[Termes IGN] filtrage numérique d'image
[Termes IGN] image SPOT-Végétation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] occupation du sol
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétationRésumé : (Auteur) Global or regional environmental change is of wide concern. Extensive studies have indicated that long-term vegetation cover change is one of the most important factors reflecting environmental change, and normalized difference vegetation index (NDVI) time-series data sets have been widely used in vegetation dynamic change monitoring. However, the significant residual effects and noise levels impede the application of NDVI time-series data in environmental change research. This study develops a novel and robust filter method, i.e., the moving weighted harmonic analysis (MWHA) method, which incorporates a moving support domain to assign the weights for all the points, making the determination of the frequency number much easier. Additionally, a four-step process flow is designed to make the data approach the upper NDVI envelope, so that the actual change in the vegetation can be detected. A total of 487 test pixels selected from SPOT VEGETATION 10-day MVC NDVI time-series data from January 1999 to December 2001 were used to illustrate the effectiveness of the new method by comparing the MWHA results with the results of another four existing methods. Finally, the long-term SPOT VEGETATION 10-day maximum-value compositing (MVC) NDVI time series for China from April 1998 to May 2014 was reconstructed by the use of the proposed method, and a test region in China was utilized to validate the effectiveness of the proposed MWHA method. All the results indicate that the reconstructed high-quality NDVI time series fits the actual growth profile of the vegetation and is suitable for use in further remote sensing applications. Numéro de notice : A2015-771 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2431315 Date de publication en ligne : 02/06/2015 En ligne : https://doi.org/10.1109/TGRS.2015.2431315 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78827
in IEEE Transactions on geoscience and remote sensing > vol 53 n° 11 (November 2015) . - pp 6008 - 6021[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2015111 SL Revue Centre de documentation Revues en salle Disponible Extraction des zones cohérentes par l’analyse spatio-temporelle d’images de télédétection / Thomas Guyet in Revue internationale de géomatique, vol 25 n° 4 (octobre - décembre 2015)
[article]
Titre : Extraction des zones cohérentes par l’analyse spatio-temporelle d’images de télédétection Type de document : Article/Communication Auteurs : Thomas Guyet, Auteur ; Simon Malinowski, Auteur ; Mohand Cherif Benyounès, Auteur Année de publication : 2015 Article en page(s) : pp 473 - 494 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse spatio-temporelle
[Termes IGN] caractérisation
[Termes IGN] cohérence des données
[Termes IGN] écologie
[Termes IGN] extraction de données
[Termes IGN] fusion de données
[Termes IGN] image Aqua-MODIS
[Termes IGN] image Terra-MODIS
[Termes IGN] partition d'image
[Termes IGN] Sénégal
[Termes IGN] série temporelle
[Termes IGN] surface cultivéeRésumé : (auteur) Cet article présente une méthode de segmentation de séries temporelles d’images satellite (SITS) en zones cohérentes, c’est-à-dire en des régions géographiques ayant des comportements temporels homogènes. L’objectif de cette méthode est, d’une part, d’extraire des caractéristiques spatio-temporelles d’une région observée et, d’autre part, d’obtenir cette caractérisation de manière efficace en temps de calcul pour traiter de grandes masses de données. Cette méthode est appliquée à la caractérisation des régions agro-écologiques du Sénégal par l’analyse des images MODIS sur un an (23 dates). Numéro de notice : A2015-923 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3166/RIG.25.473-494 Date de publication en ligne : 24/02/2016 En ligne : https://doi.org/10.3166/RIG.25.473-494 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=79725
in Revue internationale de géomatique > vol 25 n° 4 (octobre - décembre 2015) . - pp 473 - 494[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 047-2015041 RAB Revue Centre de documentation En réserve L003 Disponible Estimation of precipitation fields from 1-minute rain gauge time series – comparison of spatial and spatio-temporal interpolation methods / D. Fitzner in International journal of geographical information science IJGIS, vol 29 n° 9 (September 2015)
[article]
Titre : Estimation of precipitation fields from 1-minute rain gauge time series – comparison of spatial and spatio-temporal interpolation methods Type de document : Article/Communication Auteurs : D. Fitzner, Auteur ; Monika Sester, Auteur Année de publication : 2015 Article en page(s) : pp 1668 - 1693 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] analyse spatio-temporelle
[Termes IGN] géostatistique
[Termes IGN] interpolation
[Termes IGN] précipitation
[Termes IGN] série temporelleRésumé : (Auteur) Accurate estimations of spatio-temporal fields at unsampled locations are important in a number of applications. Often, spatio-temporal fields are advected, which means the change in field values over time at a particular point in space stems to a large extent from motion of a more or less constant spatial field. For such dynamic fields, interpolation methods including information on the motion behaviour of the field are promising extensions of solely spatial (snapshot) and symmetric spatio-temporal methods. In this paper, the performance of different deterministic and geostatistical interpolation methods is compared for precipitation estimation from 1-minute time series of spatially distributed rain gauges. The focus is on spatio-temporal methods that include information on the motion behaviour of the rainfield, estimated from weather radar using optical flow. The different interpolation methods are introduced and evaluated using rain gauge measurements of a 15-day period and cross-validation. The results show that including information on the motion behaviour significantly improves interpolation quality in terms of RMSE. Numéro de notice : A2015-609 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1040022 En ligne : https://doi.org/10.1080/13658816.2015.1040022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78038
in International journal of geographical information science IJGIS > vol 29 n° 9 (September 2015) . - pp 1668 - 1693[article]Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia / Loïc Paul Dutrieux in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)
[article]
Titre : Monitoring forest cover loss using multiple data streams, a case study of a tropical dry forest in Bolivia Type de document : Article/Communication Auteurs : Loïc Paul Dutrieux, Auteur ; Jan Verbesselt, Auteur ; Lammert Kooistra, Auteur ; Martin Herold, Auteur Année de publication : 2015 Article en page(s) : pp 112 - 125 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Bolivie
[Termes IGN] déboisement
[Termes IGN] détection de changement
[Termes IGN] forêt tropicale
[Termes IGN] image Terra-MODIS
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] sécheresse
[Termes IGN] série temporelle
[Termes IGN] variabilitéRésumé : (auteur) Automatically detecting forest disturbances as they occur can be extremely challenging for certain types of environments, particularly those presenting strong natural variations. Here, we use a generic structural break detection framework (BFAST) to improve the monitoring of forest cover loss by combining multiple data streams. Forest change monitoring is performed using Landsat data in combination with MODIS or rainfall data to further improve the modelling and monitoring. We tested the use of the Normalized Difference Vegetation Index (NDVI) from the Moderate Resolution Imaging Spectroradiometer (MODIS) with varying spatial aggregation window sizes as well as a rainfall derived index as external regressors. The method was evaluated on a dry tropical forest area in lowland Bolivia where forest cover loss is known to occur, and we validated the results against a set of ground truth samples manually interpreted using the TimeSync environment. We found that the addition of an external regressor allows to take advantage of the difference in spatial extent between human induced and naturally induced variations and only detect the processes of interest. Of all configurations, we found the 13 by 13 km MODIS NDVI window to be the most successful, with an overall accuracy of 87%. Compared with a single pixel approach, the proposed method produced better time-series model fits resulting in increases of overall accuracy (from 82% to 87%), and decrease in omission and commission errors (from 33% to 24% and from 3% to 0% respectively). The presented approach seems particularly relevant for areas with high inter-annual natural variability, such as forests regularly experiencing exceptional drought events. Numéro de notice : A2015-726 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.03.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.03.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78378
in ISPRS Journal of photogrammetry and remote sensing > vol 107 (September 2015) . - pp 112 - 125[article]TerraSAR-X dual-pol time-series for mapping of wetland vegetation / Julie Betbeder in ISPRS Journal of photogrammetry and remote sensing, vol 107 (September 2015)
[article]
Titre : TerraSAR-X dual-pol time-series for mapping of wetland vegetation Type de document : Article/Communication Auteurs : Julie Betbeder, Auteur ; Sébastien Rapinel, Auteur ; Samuel Corgne, Auteur ; Eric Pottier, Auteur ; Laurence Hubert-Moy, Auteur Année de publication : 2015 Article en page(s) : pp 90 - 98 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] 1:10.000
[Termes IGN] caractérisation
[Termes IGN] carte de la végétation
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données multitemporelles
[Termes IGN] données polarimétriques
[Termes IGN] image radar moirée
[Termes IGN] image TerraSAR-X
[Termes IGN] série temporelle
[Termes IGN] zone humideRésumé : (auteur) Mapping vegetation formations at a fine scale is crucial for assessing wetland functions and for better landscape management. Identification and characterization of vegetation formations is generally conducted at a fine scale using ecological ground surveys, which are limited to small areas. While optical remotely sensed imagery is limited to cloud-free periods, SAR time-series are used more extensively for wetland mapping and characterization using the relationship between distribution of vegetation formations and flood duration. The aim of this study was to determine the optimal number and key dates of SAR images to be classified to map wetland vegetation formations at a 1:10,000 scale. A series of eight dual-polarization TerraSAR-X images (HH/VV) was acquired in 2013 during dry and wet seasons in temperate climate conditions. One polarimetric parameter was extracted first, the Shannon entropy, which varies with wetland flooding status and vegetation roughness. Classification runs of all the possible combinations of SAR images using different k (number of images) subsets were performed to determine the best combinations of the Shannon entropy images to identify wetland vegetation formations. The classification runs were performed using Support Vector Machine techniques and were then analyzed using the McNemar test to investigate significant differences in the accuracy of all classification runs based on the different image subsets. The results highlight the relevant periods (i.e. late winter, spring and beginning of summer) for mapping vegetation formations, in accordance with ecological studies. They also indicate that a relationship can be established between vegetation formations and hydrodynamic processes with a short time-series of satellite images (i.e. 5 dates). This study introduces a new approach for herbaceous wetland monitoring using SAR polarimetric imagery. This approach estimates the number and key dates required for wetland management (e.g. restoration) and biodiversity studies using remote sensing data. Numéro de notice : A2015-727 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.05.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.05.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78377
in ISPRS Journal of photogrammetry and remote sensing > vol 107 (September 2015) . - pp 90 - 98[article]Measuring the directional variations of land surface reflectance from MODIS / François-Marie Bréon in IEEE Transactions on geoscience and remote sensing, vol 53 n° 8 (August 2015)PermalinkAn adaptive semisupervised approach to the detection of user-defined recurrent changes in image time series / Daniel Zanotta in IEEE Transactions on geoscience and remote sensing, vol 53 n° 7 (July 2015)PermalinkCartographie du châtaignier en Alsace par imagerie satellite multi-date / Colette Meyer in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)PermalinkNetwork-based estimation of time-dependent noise in GPS position time series / Ksenia Dimitrieva in Journal of geodesy, vol 89 n° 6 (June 2015)PermalinkIrregular variations in GPS time series by probability and noise analysis / Anna Klos in Survey review, vol 47 n° 342 (May 2015)PermalinkKALREF, a Kalman filter and time series approach to the International Terrestrial Reference Frame realization / Xiaoping Wu in Journal of geophysical research : Solid Earth, vol 120 n° 5 (May 2015)PermalinkCo-clustering geo-referenced time series: exploring spatio-temporal patterns in Dutch temperature data / Xiaojing Wu in International journal of geographical information science IJGIS, vol 29 n° 4 (April 2015)PermalinkImproving forest aboveground biomass estimation using seasonal Landsat NDVI time-series / Xiaolin Zhu in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)PermalinkThree-Corner Hat for the assessment of the uncertainty of non-linear residuals of space-geodetic time series in the context of terrestrial reference frame analysis / Claudio Abbondanza in Journal of geodesy, vol 89 n° 4 (April 2015)PermalinkCharacterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the Random Forest algorithm / Oumer S. Ahmed in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)Permalink