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Mapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery / J. Dong in ISPRS Journal of photogrammetry and remote sensing, vol 74 (Novembrer 2012)
[article]
Titre : Mapping tropical forests and rubber plantations in complex landscapes by integrating PALSAR and MODIS imagery Type de document : Article/Communication Auteurs : J. Dong, Auteur ; X. Xiao, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 20 - 33 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] afforestation
[Termes IGN] carte de la végétation
[Termes IGN] classification dirigée
[Termes IGN] classification par réseau neuronal
[Termes IGN] forêt tropicale
[Termes IGN] Hainan (Chine)
[Termes IGN] Hevea brasiliensis
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Terra-MODIS
[Termes IGN] traitement d'image
[Termes IGN] zone tropicale humideRésumé : (Auteur) Knowledge of the spatial distribution of forest types in tropical regions is important for implementation of Reducing Emissions from Deforestation and Forest Degradation (REDD), better understanding of the global carbon cycle, and optimal forest management. Frequent cloud cover in moist tropical regions poses challenges for using optical images to map and monitor forests. Recently, Japan Aerospace Exploration Agency (JAXA) released a 50 m orthorectified mosaic product from the Phased Array Type L-band Synthetic Aperture Radar (PALSAR) onboard the Advanced Land Observing Satellite (ALOS). PALSAR data provides information about the land surface without cloud interference. In this study we use the fine beam dual (FBD) polarization PALSAR 50 m mosaic imagery and a Neural Network (NN) method to produce a land cover map in Hainan Island, China. Subsequently, forest areas are classified into evergreen and deciduous forests and rubber plantations are mapped using vegetation and land surface water indices derived from 250 to 500 m resolution MODIS products. The PALSAR 50 m forest cover map, MODIS-based forest types and rubber plantation maps are fused to generate fractional maps of evergreen forest, deciduous forest and rubber plantation within 500 m or 250 m pixels. PALSAR data perform well for land cover classification (overall accuracy = 89% and Kappa Coefficient = 0.79) and forest identification (both the Producer’s Accuracy and User’s Accuracy are higher than 92%). The resulting land cover maps of forest, cropland, water and urban lands are consistent with the National Land Cover Dataset of China in 2005 (NLCD-2005). Validation from ground truth samples indicates that the resultant rubber plantation map is highly accurate (the overall accuracy = 85%). Overall, this study provides insight on the potential of integrating cloud-free 50 m PALSAR and temporal MODIS data on mapping forest types and rubber plantations in moist tropical regions. Numéro de notice : A2012-603 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.07.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.07.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32049
in ISPRS Journal of photogrammetry and remote sensing > vol 74 (Novembrer 2012) . - pp 20 - 33[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012081 SL Revue Centre de documentation Revues en salle Disponible Monitoring ground subsidence in Shanghai maglev area using two kinds of SAR data / J. Wu in Journal of applied geodesy, vol 6 n° 3-4 (November 2012)
[article]
Titre : Monitoring ground subsidence in Shanghai maglev area using two kinds of SAR data Type de document : Article/Communication Auteurs : J. Wu, Auteur ; L. Zhang, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 209 - 213 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] effondrement de terrain
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Envisat-ASAR
[Termes IGN] image radar moirée
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] réseau métropolitain
[Termes IGN] Shanghai (Chine)
[Termes IGN] subsidence
[Termes IGN] surveillance d'ouvrageRésumé : (Auteur) Shanghai maglev is a very fast traffic tool, so it is very strict with the stability of the roadbed. However, the ground subsidence is a problem in Shanghai because of the poor geological condition and human-induced factors. So it is necessary to monitor ground subsidence in the area along the Shanghai maglev precisely and frequently. Traditionally, a precise levelling method is used to survey along the track. It is expensive and time consuming, and can only get the ground subsidence information on sparse benchmarks. Recently, the small baseline differential SAR technique plays a valuable part in monitoring ground subsidence, which can extract ground subsidence information with high spatial resolution in a wide area. In this paper, L-band ALOS PALSAR data and C-band Envisat ASAR data are used to extract ground subsidence information using the SBAS method in the Shanghai maglev area. The results show that the general pattern of ground subsidence from InSAR processing of two differential bands of SAR images is similar. Both results show that there is no significant ground subsidence on the maglev line. Near the railway line, there are a few places with subsidence rates at about -20 mm/y or even more, such as Chuansha town, the junction of the maglev and Waihuan road. Numéro de notice : A2012-599 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1515/jag-2012-0024 En ligne : http://www.degruyter.com/view/j/jag.2012.6.issue-3-4/jag-2012-0024/jag-2012-0024 [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32045
in Journal of applied geodesy > vol 6 n° 3-4 (November 2012) . - pp 209 - 213[article]Detecting depolarized targets using a new geometrical perturbation filter / Armando Marino in IEEE Transactions on geoscience and remote sensing, vol 50 n° 10 Tome 1 (October 2012)
[article]
Titre : Detecting depolarized targets using a new geometrical perturbation filter Type de document : Article/Communication Auteurs : Armando Marino, Auteur ; S. Cloude, Auteur ; I. Woodhouse, Auteur Année de publication : 2012 Article en page(s) : pp 3787 - 3799 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] bande L
[Termes IGN] détection de cible
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image TerraSAR-X
[Termes IGN] polarimétrie radar
[Termes IGN] polarisationRésumé : (Auteur) Target detectors using polarimetry are often focused on single targets, since these can be characterized in a simpler and deterministic way. The algorithm proposed in this paper is aimed at the more difficult problem of partial-target detection (i.e., targets with arbitrary degree of polarization). The authors have already proposed a single-target detector employing filters based on a geometrical perturbation. In order to enhance the algorithm to the detection of partial targets, a new vector formalism is introduced. The latter is similar to the one exploited for single targets but suitable for complete characterization of partial targets. A new feature vector is generated starting from the covariance matrix and exploited for the perturbation method. Validation against L-band fully polarimetric airborne E-SAR and ALOS PALSAR data and X-band dual-polarimetric TerraSAR-X data is provided with significant agreement with the expected results. Additionally, a comparison with the supervised Wishart classifier is presented revealing improvements. Numéro de notice : A2012-525 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2012.2185703 Date de publication en ligne : 07/03/2012 En ligne : https://doi.org/10.1109/TGRS.2012.2185703 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31971
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 10 Tome 1 (October 2012) . - pp 3787 - 3799[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2012101A RAB Revue Centre de documentation En réserve L003 Disponible Quantifying deforestation in the Brazilian Amazon using advanced land observing satellite phased array L-band synthetic aperture radar (ALOS PALSAR) and shuttle imaging radar (SIR)-C data / M. Rahman in Geocarto international, vol 27 n° 6 (October 2012)
[article]
Titre : Quantifying deforestation in the Brazilian Amazon using advanced land observing satellite phased array L-band synthetic aperture radar (ALOS PALSAR) and shuttle imaging radar (SIR)-C data Type de document : Article/Communication Auteurs : M. Rahman, Auteur ; J. Tetuko Sri Sumantyo, Auteur Année de publication : 2012 Article en page(s) : pp 463 - 478 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Amazonie
[Termes IGN] bande L
[Termes IGN] Brésil
[Termes IGN] carte de la végétation
[Termes IGN] couvert forestier
[Termes IGN] déboisement
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar
[Termes IGN] image radar moirée
[Termes IGN] image SIR-C
[Termes IGN] matrice
[Termes IGN] zone intertropicaleRésumé : (Auteur) The study examined the capability of dual-polarization SAR data for forest cover mapping and change assessment in the Brazilian Amazon Forest regions. Shuttle Imaging Radar (SIR)-C and Advanced Land Observing Satellite Phased Array L-band Synthetic Aperture Radar (ALOS PALSAR) data were analysed to map and quantify deforestation. The images were classified using hybrid classifier, where each land cover was grouped in various spectral sub-classes interpreted on the imagery and later merged together to generate the desired land cover classes. The classification accuracy for forest was reasonably high (>90%). The technique applied in this study can be extended for operational mapping and monitoring of deforestation in the tropics, particularly for those regions which are often covered by cloud. Numéro de notice : A2012-509 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2011.638987 Date de publication en ligne : 13/01/2012 En ligne : https://doi.org/10.1080/10106049.2011.638987 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31955
in Geocarto international > vol 27 n° 6 (October 2012) . - pp 463 - 478[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2012061 RAB Revue Centre de documentation En réserve L003 Disponible A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region / Dong Lu ; E. Moran ; et al. in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)
[article]
Titre : A comparative analysis of ALOS PALSAR L-band and RADARSAT-2 C-band data for land-cover classification in a tropical moist region Type de document : Article/Communication Auteurs : Dong Lu, Auteur ; E. Moran, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 26 - 38 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse comparative
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] classification dirigée
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar
[Termes IGN] image Radarsat
[Termes IGN] occupation du sol
[Termes IGN] zone tropicale humideRésumé : (Auteur) This paper explores the use of ALOS (Advanced Land Observing Satellite) PALSARL-band (Phased Array type L-band Synthetic Aperture Radar) and RADARSAT-2 C-band data for land-cover classification in a tropical moist region. Transformed divergence was used to identify potential textural images which were calculated with the gray-level co-occurrence matrix method. The standard deviation of selected textural images and correlation coefficients between them were then used to determine the best combination of texture images for land-cover classification. Classification results based on different scenarios with maximum likelihood classifier were compared. Based on the identified best scenarios, different classification algorithms – maximum likelihood classifier, classification tree analysis, Fuzzy ARTMAP (a neural-network method), k-nearest neighbor, object-based classification, and support vector machine were compared for examining which algorithm was suitable for land-cover classification in the tropical moist region. This research indicates that the combination of radiometric images and their textures provided considerably better classification accuracies than individual datasets. The L-band data provided much better land-cover classification than C-band data but neither L-band nor C-band was suitable for fine land-cover classification system, no matter which classification algorithm was used. L-band data provided reasonably good classification accuracies for coarse land-cover classification system such as forest, succession, agropasture, water, wetland, and urban with an overall classification accuracy of 72.2%, but C-band data provided only 54.7%. Compared to the maximum likelihood classifier, both classification tree analysis and Fuzzy ARTMAP provided better performances, object-based classification and support vector machine had similar performances, and k-nearest neighbor performed poorly. More research should address the use of multitemporal radar data and the integration of radar and optical sensor data for improving land-cover classification. Numéro de notice : A2012-287 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.03.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.03.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31733
in ISPRS Journal of photogrammetry and remote sensing > vol 70 (June 2012) . - pp 26 - 38[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012041 SL Revue Centre de documentation Revues en salle Disponible Ionospheric artifacts in simultaneous L-band InSAR and GPS observations / J. Chen in IEEE Transactions on geoscience and remote sensing, vol 50 n° 4 (April 2012)PermalinkPotential of texture measurements of two-date dual polarization PALSAR data for the improvement of forest biomass estimation / M. Sarker in ISPRS Journal of photogrammetry and remote sensing, vol 69 (April 2012)PermalinkCharacterization of forests and deforestation in Cambodia using ALOS/PALSAR observation / R. Avtar in Geocarto international, vol 27 n° 2 (March 2012)PermalinkJoint processing of Landsat and ALOS-PALSAR data for forest mapping and monitoring / E. Lehmann in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkLong-term consecutive DInSAR for volume change estimation of land deformation / S. Sumantyo in IEEE Transactions on geoscience and remote sensing, vol 50 n° 1 (January 2012)PermalinkThe crustal deformation and fault model of the 2011 off the Pacific coast of Tohoku earthquake / T. Imakiire in Bulletin of the GeoSpatial Information authority of Japan, vol 59 (December 2011)PermalinkElectromagnetic land surface classification through integration of optical and radar remote sensing data / J. Baek in IEEE Transactions on geoscience and remote sensing, vol 49 n° 4 (April 2011)PermalinkGeodetically accurate InSAR data processor / H. Zebker in IEEE Transactions on geoscience and remote sensing, vol 48 n° 12 (December 2010)PermalinkMulti-path PALSAR interferometric observations of the 2008 magnitude 8.0 Wenchuan earthquake / K. Zhang in International Journal of Remote Sensing IJRS, vol 31 n° 13 (July /2010)Permalinkvol 31 n° 13 - July /2010 - Special issue : Satellite observations of the Wenchuan earthquake of 12 may 2008 (Bulletin de International Journal of Remote Sensing IJRS) / Ranjit SinghPermalink