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A semi-ellipsoid-model based fuzzy classifier to map grassland in Inner Mongolia, China / Hai Lan in ISPRS Journal of photogrammetry and remote sensing, vol 85 (November 2013)
[article]
Titre : A semi-ellipsoid-model based fuzzy classifier to map grassland in Inner Mongolia, China Type de document : Article/Communication Auteurs : Hai Lan, Auteur ; Yichun Xie, Auteur Année de publication : 2013 Article en page(s) : pp 21 - 31 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] classification floue
[Termes IGN] classification hybride
[Termes IGN] fusion d'images
[Termes IGN] image CBERS
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-TM
[Termes IGN] Mongolie intérieure (Chine)
[Termes IGN] prairieRésumé : (Auteur) Remote sensing techniques offer effective means for mapping plant communities. However, mapping grassland with fine vegetative classes over large areas has been challenging for either the coarse resolutions of remotely sensed images or the high costs of acquiring images with high-resolutions. An improved hybrid-fuzzy-classifier (HFC) derived from a semi-ellipsoid-model (SEM) is developed in this paper to achieve higher accuracy for classifying grasslands with Landsat images. The Xilin River Basin, Inner Mongolia, China, is chosen as the study area, because an acceptable volume of ground truthing data was previously collected by multiple research communities. The accuracy assessment is based on the comparison of the classification outcomes from four types of image sets: (1) Landsat ETM+ August 14, 2004, (2) Landsat TM August 12, 2009, (3) the fused images of ETM+ with CBERS, and (4) TM with CBERS, respectively, and by three classifiers, the proposed HFC-SEM, the tetragonal pyramid model (TPM) based HFC, and the support vector machine method. In all twelve classification experiments, the HFC-SEM classifier had the best overall accuracy statistics. This finding indicates that the medium resolution Landsat images can be used to map grassland vegetation with good vegetative detail when the proper classifier is applied. Numéro de notice : A2013-605 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.07.011 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.07.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32741
in ISPRS Journal of photogrammetry and remote sensing > vol 85 (November 2013) . - pp 21 - 31[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013111 RAB Revue Centre de documentation En réserve L003 Disponible The sights below / Kevin Corbley in GEO: Geoconnexion international, vol 12 n° 9 (october 2013)
[article]
Titre : The sights below Type de document : Article/Communication Auteurs : Kevin Corbley, Auteur Année de publication : 2013 Article en page(s) : pp 28 - 30 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Abou Dabi
[Termes IGN] fond marin
[Termes IGN] habitat animal
[Termes IGN] image Worldview
[Termes IGN] lever bathymétrique
[Termes IGN] milieu marin
[Termes IGN] réflectance spectrale
[Termes IGN] relief sous-marinRésumé : (Editeur) Seafloor mapping has traditionally been conducted by sonar or Lidar. However, an international environmental management project in Abu Dhabi is using new techniques to survey the seafloor to high accuracy using remote sensing satellite data. Numéro de notice : A2013-562 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32698
in GEO: Geoconnexion international > vol 12 n° 9 (october 2013) . - pp 28 - 30[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 062-2013091 SL Revue Centre de documentation Revues en salle Disponible Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data / Abel Ramoelo in ISPRS Journal of photogrammetry and remote sensing, vol 82 (August 2013)
[article]
Titre : Non-linear partial least square regression increases the estimation accuracy of grass nitrogen and phosphorus using in situ hyperspectral and environmental data Type de document : Article/Communication Auteurs : Abel Ramoelo, Auteur ; Andrew K. Skidmore, Auteur ; Moses Azong Cho, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 27 - 40 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Afrique du sud (état)
[Termes IGN] azote
[Termes IGN] données environnementales
[Termes IGN] herbe
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] parc naturel national
[Termes IGN] parcours
[Termes IGN] phosphore
[Termes IGN] régression non linéaire
[Termes IGN] savaneRésumé : (Auteur) Grass nitrogen (N) and phosphorus (P) concentrations are direct indicators of rangeland quality and provide imperative information for sound management of wildlife and livestock. It is challenging to estimate grass N and P concentrations using remote sensing in the savanna ecosystems. These areas are diverse and heterogeneous in soil and plant moisture, soil nutrients, grazing pressures, and human activities. The objective of the study is to test the performance of non-linear partial least squares regression (PLSR) for predicting grass N and P concentrations through integrating in situ hyperspectral remote sensing and environmental variables (climatic, edaphic and topographic). Data were collected along a land use gradient in the greater Kruger National Park region. The data consisted of: (i) in situ-measured hyperspectral spectra, (ii) environmental variables and measured grass N and P concentrations. The hyperspectral variables included published starch, N and protein spectral absorption features, red edge position, narrow-band indices such as simple ratio (SR) and normalized difference vegetation index (NDVI). The results of the non-linear PLSR were compared to those of conventional linear PLSR. Using non-linear PLSR, integrating in situ hyperspectral and environmental variables yielded the highest grass N and P estimation accuracy (R2 = 0.81, root mean square error (RMSE) = 0.08, and R2 = 0.80, RMSE = 0.03, respectively) as compared to using remote sensing variables only, and conventional PLSR. The study demonstrates the importance of an integrated modeling approach for estimating grass quality which is a crucial effort towards effective management and planning of protected and communal savanna ecosystems. Numéro de notice : A2013-409 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.04.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.04.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32547
in ISPRS Journal of photogrammetry and remote sensing > vol 82 (August 2013) . - pp 27 - 40[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2013081 RAB Revue Centre de documentation En réserve L003 Disponible Registration of aerial imagery and lidar data in desert areas using the centroids of bushes as control information / Na Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 8 (August 2013)
[article]
Titre : Registration of aerial imagery and lidar data in desert areas using the centroids of bushes as control information Type de document : Article/Communication Auteurs : Na Li, Auteur ; Xianfeng Huang, Auteur ; Fan Zhang, Auteur ; Le Wang, Auteur Année de publication : 2013 Article en page(s) : pp 743 - 752 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] appariement de données localisées
[Termes IGN] brousse
[Termes IGN] centroïde
[Termes IGN] désert
[Termes IGN] données lidar
[Termes IGN] Gobi, désert du
[Termes IGN] image aérienne
[Termes IGN] Ransac (algorithme)
[Termes IGN] semis de pointsRésumé : (Auteur) Geometric registration of multiple-source data is of great value for fusion processing and is very beneficial for the research of desert ecosystems. A lidar point cloud and optical image are two typical data that need to be integrated for data assimilation and information retrieval. This paper aims to solve the registration problem of aerial imagery and airborne lidar data in desert areas where traditional registration methods have difficulties in identifying registration primitives. In many deserts, such as the Sahara in Africa and Gobi in China, we observe that there are unevenly distributed desert bushes, which can be used as cues for registration. In this paper, we propose a registration approach using the centroids of bushes as registration primitives. This approach employs similar triangles created from both centroids as the evidence for matching and verifies the registration by the RANSAC algorithm. Experiments using data taken from the Dunhuang Gobi Desert in China show the registration surface model visually, and at the same time quantifies the deviation error, which corroborates that the proposed registration method is effective and feasible in desert areas. Numéro de notice : A2013-427 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.79.8.731 En ligne : https://doi.org/10.14358/PERS.79.8.731 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32565
in Photogrammetric Engineering & Remote Sensing, PERS > vol 79 n° 8 (August 2013) . - pp 743 - 752[article]Using hyperspectral reflectance data to assess biocontrol damage of giant salvinia / James H. Everitt in Geocarto international, vol 28 n° 5-6 (August - October 2013)
[article]
Titre : Using hyperspectral reflectance data to assess biocontrol damage of giant salvinia Type de document : Article/Communication Auteurs : James H. Everitt, Auteur ; Chenghai Yang, Auteur ; Julie G. Nachtrieb, Auteur Année de publication : 2013 Article en page(s) : pp 502 - 516 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse diachronique
[Termes IGN] analyse discriminante
[Termes IGN] espèce exotique envahissante
[Termes IGN] Etats-Unis
[Termes IGN] image hyperspectrale
[Termes IGN] lutte biologique
[Termes IGN] milieu naturel
[Termes IGN] plante aquatique d'eau salée
[Termes IGN] réflectance végétale
[Termes IGN] surveillance de la végétationMots-clés libres : Salvinia molesta Résumé : (Auteur) Field hyperspectral reflectance data were studied at 50 wavebands (10-nm bandwidth) over the 400- to 900-nm spectral range to determine their potential for distinguishing among giant salvinia (Salvinia molesta Mitchell) plants subjected to four population levels of salvinia weevils (Cyrtobagous salviniae Calder and Sands) to develop feeding damage to the plants. The four populations included a control with no insects and those with low, medium and high insect populations. The plants were studied in two experiments on each of two dates: 14 October 2010 and 21 July 2011. Two procedures were used to determine the optimum bands for discriminating among treatments: least significant difference (LSD) and stepwise discriminant analysis. The LSD comparison test results for both October and July experiments showed that generally the best bands for separating among treatments occurred in the green (505–595 nm), red (605–635 nm), red-near-infrared (NIR; 695–745 nm) edge and NIR (755–895 nm) regions where three to four treatments could be distinguished. Stepwise discriminant analysis identified four bands in the green, red and red-NIR edge to be significant to discriminate among the four treatments in Experiment 1 in October. For Experiment 2 in October, discriminant analysis identified five bands in the blue, green, red and NIR regions to be significant for distinguishing among the treatments. In Experiment 1 in July, five bands in the blue, green, red-NIR edge and NIR regions were found to be significant to discriminate among the treatments. For Experiment 2 in July, discriminant analysis identified four bands in the blue, green and red-NIR edge regions to be significant to discriminate among the treatments. Numéro de notice : A2013-550 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.724454 Date de publication en ligne : 25/09/2012 En ligne : https://doi.org/10.1080/10106049.2012.724454 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78074
in Geocarto international > vol 28 n° 5-6 (August - October 2013) . - pp 502 - 516[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2013031 RAB Revue Centre de documentation En réserve L003 Disponible Télédétection, SIG et modélisation de l'érosion hydrique dans le bassin versant de l'Oued Amzaz, Rif central / Jamal Chaaouan in Revue Française de Photogrammétrie et de Télédétection, n° 203 (Juillet 2013)PermalinkChallenges and lessons from a wetland LiDAR project: a case study of the Okefenokee Swamp, Georgia, USA / L. Shea Rose in Geocarto international, vol 28 n° 3-4 (June - July 2013)PermalinkAnalysis of desertification in the Upper East Region (UER) of Ghana using remote sensing, field study, and local knowledge / Alex B. Owusu in Cartographica, vol 48 n° 1 (March 2013)PermalinkModèle intégré de description verbale et de représentation spatiale au sein des SIG / David Brosset in Cartes & Géomatique, n° 215 (mars 2013)PermalinkCombination of overlap-driven adjustment and Phong model for LiDAR intensity correction / Q. Ding in ISPRS Journal of photogrammetry and remote sensing, vol 75 (January 2013)PermalinkUtilisation d'image satellitaire et d'un modèle numérique d'altitude pour la cartographie des zones à risque d'inondation sur le littoral méditerranéen de Saïdia (Nord-Est du Maroc) / M. Mouzouri in Revue Française de Photogrammétrie et de Télédétection, n° 201 (Janvier 2013)PermalinkApports des données ALOS PALSAR polarimétriques à la détection des zones humides littorales (Sassandra, Côte d'Ivoire) / Kouakou Hervé Kouassi in Photo interprétation, European journal of applied remote sensing, vol 48 n° 4 (décembre 2012)PermalinkCartographie des zones humides de montagne par télédétection : Potentialités des images à très haute résolution spatiale / L. Vacquié in Revue internationale de géomatique, vol 22 n° 4 (décembre 2012 – février 2013)PermalinkCartographier les réseaux écologiques de Rhône-Alpes : Entre science et gouvernance / H. Guilloy in Revue internationale de géomatique, vol 22 n° 4 (décembre 2012 – février 2013)PermalinkEvaluation of the spatial changes in seagrass cover in the lagoons of Lakshadweep islands, India, using IRS LISS III satellite images / E.P. Nobi in Geocarto international, vol 27 n° 8 (December 2012)Permalink