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Mapping nighttime flood from MODIS observations using support vector machines / R. Zhang in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 11 (November 2012)
[article]
Titre : Mapping nighttime flood from MODIS observations using support vector machines Type de document : Article/Communication Auteurs : R. Zhang, Auteur ; D. Sun, Auteur ; Y. Yu, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 1151 - 1161 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] détection de changement
[Termes IGN] image Terra-MODIS
[Termes IGN] inondation
[Termes IGN] nuit
[Termes IGN] température de luminance
[Termes IGN] zone sinistréeRésumé : (Auteur) This work proposes a nighttime flood mapping method for Moderate Resolution Imaging Spectroradiometer (modis) data. Brightness temperatures at 3.9 um, and BT11 um channels (BT 3.9, and BT 11, respectively) and differences of brightness temperatures between 3.9 um and 4.0 um, and between 11 um and 12 um (BT 3.9-BT 4.0, and BT 11- BT 12, respectively) are used to identify nighttime water pixels by a support vector machines (SVM) classifier. Prominent flood locations are detected by a change detection process using a reference water-land map. To test the effectiveness of the proposed method, two flood cases caused by heavy rains were chosen as trial scenarios. The nighttime mapping results are validated with the flood maps, which are obtained from the visual interpretation based on the daytime flood identification results. The experimental results indicate that the proposed method is effective for the delineation of inundated areas with standing water during the nighttime. Numéro de notice : A2012-583 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.11.1151 En ligne : https://doi.org/10.14358/PERS.78.11.1151 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32029
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 11 (November 2012) . - pp 1151 - 1161[article]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 Increasing robustness of postclassification change detection using time series of land cover maps / Pieter Kempeneers in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)
[article]
Titre : Increasing robustness of postclassification change detection using time series of land cover maps Type de document : Article/Communication Auteurs : Pieter Kempeneers, Auteur ; F. Sedano, Auteur ; Peter Strobl, Auteur ; et al., Auteur Année de publication : 2012 Article en page(s) : pp 3327 - 3339 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte d'occupation du sol
[Termes IGN] détection de changement
[Termes IGN] Europe (géographie politique)
[Termes IGN] image Terra-MODIS
[Termes IGN] incendie de forêt
[Termes IGN] méthode robuste
[Termes IGN] occupation du sol
[Termes IGN] risque naturel
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétationRésumé : (Auteur) The monitoring of land cover requires that stable land cover classes be distinguished from changes over time. Within this paper, a postclassification method is presented that provides land cover change information, based on a time series of land cover maps. The method applies a kernel filter to sequential land cover maps. Under some basic assumptions, it shows robustness against classification errors. Despite seasonality, land cover changes often occur at a low temporal frequency (e.g., maximum once every 5-10 years). If land cover maps are available more frequently, some of the information will become redundant (oversampling). The proposed method uses this redundancy for tolerating (nonsystematic) misclassifications. In order to demonstrate the benefits and limitations of the proposed method, analytical expressions have been derived. When compared to a simple postclassification comparison, one of the key strengths of the proposed approach is that it is able to improve both the overall and user's accuracy of change, while also maintaining the same level of producer's accuracy. As a case study, MODerate Resolution Imaging Spectroradiometer remote sensing data from 2006-2010 were classified into forest (F)/nonforest (NF) at pan-European scale. Promising results were obtained for detecting forest loss due to natural disasters. Quality was assessed using burnt area maps in southern Europe and a forest damage report after a windstorm in France. Results indicated a considerable reduction of change detection errors, confirming the theoretical results. Numéro de notice : A2012-448 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2181854 Date de publication en ligne : 21/02/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2181854 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31894
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 9 (October 2012) . - pp 3327 - 3339[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Mapping fragmented agricultural systems in the Sudano-Sahelian environments of Africa using random forest and ensemble metrics of coarse resolution MODIS imagery / E. Vintrou in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
[article]
Titre : Mapping fragmented agricultural systems in the Sudano-Sahelian environments of Africa using random forest and ensemble metrics of coarse resolution MODIS imagery Type de document : Article/Communication Auteurs : E. Vintrou, Auteur ; M. Soumaré, Auteur ; Serge Bernard, Auteur ; Agnès Bégue, Auteur ; C. Baron, Auteur ; D. Lo Seen, Auteur Année de publication : 2012 Article en page(s) : pp 839 - 848 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse texturale
[Termes IGN] carte agricole
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Terra-MODIS
[Termes IGN] Mali
[Termes IGN] métrique
[Termes IGN] Sahel
[Termes IGN] zone arideRésumé : (Auteur) We worked on the assumption that agricultural systems shaped the landscape through human cropping practices, and that the resulting landscape can be described with a set of coarse resolution satellite-derived metrics (spectral, textural, temporal, and spatial metrics). A Random Forest classification model was developed at the village scale in South Mali, based on 100 samples, with data on the main type of agricultural system in each village (three-class typology), and 30 MODIS-derived and socio-environmental metrics calculated on agricultural areas. The model was found to perform well (overall accuracy of 60 percent) and was stable. Class A (food crops) and B (intensive agriculture) displayed good producer's accuracy (70 percent and 67 percent, respectively), while class C (mixed agriculture) was less accurate (50 percent). The most important metrics were shown to be the annual mean of NDVI, followed by the phenology transition dates and texture metrics. However, when considering each set of metrics separately, texture emerged as the most discriminating factor (with 53 percent of global accuracy). This result, i.e., that even coarse resolution imagery contains textural information that can be used for crop mapping, is new. Such maps could be used in food security systems as an indicator of system vulnerability, or as spatial inputs for crop yield models. Numéro de notice : A2012-430 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.839 En ligne : https://doi.org/10.14358/PERS.78.8.839 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31876
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 839 - 848[article]Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley / L. Zhong in Photogrammetric Engineering & Remote Sensing, PERS, vol 78 n° 8 (August 2012)
[article]
Titre : Phenology-based crop classification algorithm and its implications on agricultural water use assessments in California's central valley Type de document : Article/Communication Auteurs : L. Zhong, Auteur ; P. Gong, Auteur ; Gregory S. Biging, Auteur Année de publication : 2012 Article en page(s) : pp 799 - 813 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte agricole
[Termes IGN] classification par arbre de décision
[Termes IGN] cultures
[Termes IGN] Enhanced vegetation index
[Termes IGN] évapotranspiration
[Termes IGN] fusion d'images
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] image Terra-MODIS
[Termes IGN] phénologie
[Termes IGN] segmentation d'imageRésumé : (Auteur) The overarching goal of this study was to map specific crop types in the Central Valley, California and estimate the effect of classification uncertainty on the calculation of crop evapotranspiration (ETc). A phenology-based classification (PBC) approach was developed to identify crop types based on phenological and spectral metrics derived from the time series of Landsat TM/ETM_ imagery. Phenological metrics, calculated by fitting asymmetric double sigmoid functions to temporal profiles of enhanced vegetation index (EVI), were capable of separating crop types with distinct crop calendars. An innovative method was used to compute spectral metrics to represent crops' spectral characteristics at certain phenological stages instead of any specific imaging date. Crop mapping using these metrics showed a stable performance without influences of low-quality data and inter-annual differences in imaging dates. The requirement for ground reference data by the PBC approach was low because classification algorithms were mostly built according to the knowledge on crop calendars and agricultural practices. Techniques including image segmentation, data fusion with MODIS imagery, and decision tree were incorporated to make the approach effective and efficient. Though moderate accuracy (~65.0 percent) was achieved, ETc calculated by the Food and Agriculture Organization (FAO) 56 method showed that the estimate of water use was not likely to be significantly affected by the classification error in PBC. All these advantages imply the strength of the PBC approach in the regular crop mapping of the Central Valley. Numéro de notice : A2012-428 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.78.8.799 En ligne : https://doi.org/10.14358/PERS.78.8.799 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31874
in Photogrammetric Engineering & Remote Sensing, PERS > vol 78 n° 8 (August 2012) . - pp 799 - 813[article]Comparison of support vector machine, neural network, and CART algorithms for the land-cover classification using limited training data points / Y. Shao in ISPRS Journal of photogrammetry and remote sensing, vol 70 (June 2012)PermalinkEarth Observation scientific workflows in a distributed computing environment / T. Van Zyl in Transactions in GIS, vol 16 n° 2 (April 2012)PermalinkCarbon Stock of European Beech Forest : A Case at M. Pizzalto, Italy / Aida Taghavi Bayat in APCBEE Procedia, vol 1 (2-20)PermalinkSub-canopy soil moisture modeling in n-dimensional spectral feature space / A. Ghulam in Photogrammetric Engineering & Remote Sensing, PERS, vol 77 n° 2 (February 2011)PermalinkPM10 remote sensing from geostationary SEVIRI and polar-orbiting MODIS sensors over the complex terrain of the European Alpine region / E. Emili in Remote sensing of environment, vol 114 n° 11 (15/11/2010)PermalinkAtmospheric correction to IRS-P6 AWiFS data and its validation with ground measurements: a study over the semi-arid region / Ashu Sharma in Geocarto international, vol 25 n° 7 (November 2010)PermalinkMapping the North : the updated North Circumpolar Region map by the atlas of Canada / R.E. Kramers in Cartographica, vol 45 n° 3 (September 2010)PermalinkLand cover characterization for hydrological modelling using thermal infrared emissivities / A. French in International Journal of Remote Sensing IJRS, vol 31 n° 14 (July 2010)PermalinkRetrieval of dissolved inorganic nitrogen from multi-temporal MODIS data in Haizhou Bay / Y. Xu in Marine geodesy, vol 33 n° 1 (January - March 2010)PermalinkInfluence of resolution in irrigated area mapping and area estimations / N. Velpuri in Photogrammetric Engineering & Remote Sensing, PERS, vol 75 n° 12 (December 2009)Permalink