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Assessment of crop foliar nitrogen using a novel dual-wavelength laser system and implications for conducting laser-based plant physiology / Jan U.H. Eitel in ISPRS Journal of photogrammetry and remote sensing, vol 97 (November 2014)
[article]
Titre : Assessment of crop foliar nitrogen using a novel dual-wavelength laser system and implications for conducting laser-based plant physiology Type de document : Article/Communication Auteurs : Jan U.H. Eitel, Auteur ; Troy Magney, Auteur ; Lee Alexander Vierling, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 229 – 240 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] agriculture de précision
[Termes IGN] biochimie
[Termes IGN] distribution binomiale
[Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF
[Termes IGN] données lidarRésumé : (Auteur) Advanced technologies for improved nitrogen (N) fertilizer management are paramount for sustainably meeting future food demands. Green laser systems that measure pulse return intensity can provide more reliable information about foliar N than can traditional passive remote sensing devices during the critical early crop growth stages (e.g., before canopy closure when vegetation and soil signals are spectrally mixed) when further decisions regarding N management can be made. However, current green laser systems are not designed for agricultural applications and only employ a single green laser wavelength, which may limit applications because many factors that require normalization techniques can affect pulse return intensity. Here, we describe the design of a tractor-mountable, green (532 nm)- and red (658 nm) dual wavelength laser system and evaluate the potential of an additional red reference wavelength to improve laser based estimates of foliar N by calculating laser spectral indices based on ratio combinations of green laser return intensity (GLRI) and red laser return intensity (RLRI). We hypothesized that such laser spectral indices aid in accounting for factors that confound laser based foliar N estimates including variations in leaf angle, measurement distance, soil returns, and mixed edge returns. Leaf level measurements in winter wheat (Triticum aestivum) revealed that the two laser spectral indices improved the relationship with foliar N (r2 > 0.71, RMSE Numéro de notice : A2014-531 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.09.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.09.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74144
in ISPRS Journal of photogrammetry and remote sensing > vol 97 (November 2014) . - pp 229 – 240[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014111 RAB Revue Centre de documentation En réserve L003 Disponible Automatic 3D modelling of metal frame connections from LiDAR data for structural engineering purposes / M. Cabaleiro in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)
[article]
Titre : Automatic 3D modelling of metal frame connections from LiDAR data for structural engineering purposes Type de document : Article/Communication Auteurs : M. Cabaleiro, Auteur ; B. Riveiro, Auteur ; Pedro Arias, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 47 - 57 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] modélisation 3D
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] semis de points
[Termes IGN] surveillance d'ouvrage
[Termes IGN] transformation de HoughRésumé : (Auteur) The automatic generation of 3D as-built models from LiDAR data is a topic where significant progress has been made in recent years. This paper describes a new method for the detection and automatic 3D modelling of frame connections and the formation of profiles comprising a metal frame from LiDAR data. The method has been developed using an approach to create 2.5D density images for subsequent processing using the Hough transform. The structure connections can be automatically identified after selecting areas in the point cloud. As a result, the coordinates of the connection centre, composition (profiles, size and shape of the haunch) and direction of their profiles are extracted. A standard file is generated with the data obtained from the geometric and semantic characterisation of the connections. The 3D model of connections and metal frames, which are suitable for processing software for structural engineering applications, are generated automatically based on this file. The algorithm presented in this paper has been tested under laboratory conditions and also with several industrial portal frames, achieving promising results. Finally, 3D models were generated, and structural calculations were performed. Numéro de notice : A2014-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73810
in ISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 47 - 57[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014101 RAB Revue Centre de documentation En réserve L003 Disponible Deriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies / Jari Vauhkonen in ISPRS Journal of photogrammetry and remote sensing, vol 96 (October 2014)
[article]
Titre : Deriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies Type de document : Article/Communication Auteurs : Jari Vauhkonen, Auteur ; Erik Naesset, Auteur ; Terje Gobakken, Auteur Année de publication : 2014 Article en page(s) : pp 57 -66 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] estimation statistique
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] troncRésumé : (Auteur)A computational canopy volume (CCV) based on airborne laser scanning (ALS) data is proposed to improve predictions of forest biomass and other related attributes like stem volume and basal area. An approach to derive the CCV based on computational geometry, topological connectivity and numerical optimization was tested with sparse-density, plot-level ALS data acquired from 40 field sample plots of 500–1000 m2 located in a boreal forest in Norway. The CCV had a high correspondence with the biomass attributes considered when derived from optimized filtrations, i.e. ordered sets of simplices belonging to the triangulations based on the point data. Coefficients of determination (R2) between the CCV and total above-ground biomass, canopy biomass, stem volume, and basal area were 0.88–0.89, 0.89, 0.83–0.97, and 0.88–0.92, respectively, depending on the applied filtration. The magnitude of the required filtration was found to increase according to an increasing basal area, which indicated a possibility to predict this magnitude by means of ALS-based height and density metrics. A simple prediction model provided CCVs which had R2 of 0.77–0.90 with the aforementioned forest attributes. The derived CCVs always produced complementary information and were mainly able to improve the predictions of forest biomass relative to models based on the height and density metrics, yet only by 0–1.9 percentage points in terms of relative root mean squared error. Possibilities to improve the CCVs by a further analysis of topological persistence are discussed. Numéro de notice : A2014-384 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2014.07.001 En ligne : https://doi.org/10.1016/j.isprsjprs.2014.07.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73811
in ISPRS Journal of photogrammetry and remote sensing > vol 96 (October 2014) . - pp 57 -66[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 081-2014101 RAB Revue Centre de documentation En réserve L003 Disponible Fusion of airborne LiDAR with multispectral SPOT 5 image for enhancement of feature extraction using dempster–shafer theory / Vahideh Saeidi in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)
[article]
Titre : Fusion of airborne LiDAR with multispectral SPOT 5 image for enhancement of feature extraction using dempster–shafer theory Type de document : Article/Communication Auteurs : Vahideh Saeidi, Auteur ; Biswajeet Pradhan, Auteur ; O. Idrees Mohammed, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 6017 - 6025 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] données lidar
[Termes IGN] fusion d'images
[Termes IGN] image SPOT 5
[Termes IGN] indice de végétation
[Termes IGN] théorie de Dempster-ShaferRésumé : (Auteur) This paper presents an application of data-driven Dempster-Shafer theory (DST) of evidence to fuse multisensor data for land-cover feature extraction. Over the years, researchers have focused on DST for a variety of applications. However, less attention has been given to generate and interpret probability, certainty, and conflict maps. Moreover, quantitative assessment of DST performance is often overlooked. In this paper, for implementation of DST, two main types of data were used: multisensor data such as Light Detection and Ranging (LiDAR) and multispectral satellite imagery [Satellite Pour l'Observation de la Terre 5 (SPOT 5)]. The objectives are to classify land-cover types from fused multisensor data using DST, to quantitatively assess the accuracy of the classification, and to examine the potential of slope data derived from LiDAR for feature detection. First, we derived the normalized difference vegetation index (NDVI) from SPOT 5 image and the normalized digital surface model (DSM) (nDSM) from LiDAR by subtracting the digital terrain model from the DSM. The two products were fused using the DST algorithm, and the accuracy of the classification was assessed. Second, we generated a surface slope from LiDAR and fused it with NDVI. Subsequently, the classification accuracy was assessed using an IKONOS image of the study area as ground truth data. From the two processing stages, the NDVI/nDSM fusion had an overall accuracy of 88.7%, while the NDVI/slope fusion had 75.3%. The result indicates that NDVI/nDSM integration performed better than NDVI/slope. Although the overall accuracy of the former is better than the latter (NDVI/slope), the contribution of individual class reveals that building extraction from fused slope and NDVI performed poorly. This study proves that DST is a time- and cost-effective method for accurate land-cover feature identification and extraction without the need for a prior knowledge of the scene. Furthermore, the ability to generate other products like certainty, conflict, and maximum probability maps for better visual understanding of the decision process makes it more reliable for applications such as urban planning, forest management, 3-D feature extraction, and map updating. Numéro de notice : A2014-488 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2294398 En ligne : https://doi.org/10.1109/TGRS.2013.2294398 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74077
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 10 tome 1 (October 2014) . - pp 6017 - 6025[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2014101A RAB Revue Centre de documentation En réserve L003 Disponible Integration of Lidar and Landsat to estimate forest canopy cover in coastal British Columbia / Oumer S. Ahmed in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 10 (October 2014)
[article]
Titre : Integration of Lidar and Landsat to estimate forest canopy cover in coastal British Columbia Type de document : Article/Communication Auteurs : Oumer S. Ahmed, Auteur ; Steven E. Franklin, Auteur ; Michael A. Wulder, Auteur Année de publication : 2014 Article en page(s) : pp 953 - 961 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] canopée
[Termes IGN] Colombie-Britannique (Canada)
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] feuillu
[Termes IGN] image Landsat
[Termes IGN] occupation du sol
[Termes IGN] PinophytaRésumé : (auteur) Airborne Light Detection and Ranging (lidar) data provide useful measurements of forest canopy structure but are often limited in spatial coverage. Satellite remote sensing data from Landsat can provide extensive spatial coverage of generalized forest information. A forest survey approach that integrates airborne lidar and satellite data would potentially capitalize upon these distinctive characteristics. In this study in coastal forests of British Columbia, the main objective was to determine the potential of Landsat imagery to accurately estimate forest canopy cover measured from small-footprint airborne lidar data in order to expand the lidar measurements to a larger area. Landsat-derived Tasseled Cap Angle (TCA) and spectral mixture analysis (SMA) endmember fractions (i.e., sunlit canopy, non-phofosynthetic vegetation (NPV), shade and exposed soil) were compared to lidar-derived canopy cover estimates. Pixel-based analysis and object-based area-weighted error calculations were used to assess regression model performance. The best canopy cover estimate was obtained (in the object-based deciduous forest models) with a mean object size (MOS) of 2.5 hectares (adjusted R2 = O.86 and RMSE = 0.28). Overall, lower canopy cover estimation accuracy was obtained for coniferous forests compared to deciduous forests in both the pixel and object-based approaches. Numéro de notice : A2014-672 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14358/PERS.80.10.953 En ligne : https://doi.org/10.14358/PERS.80.10.953 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75152
in Photogrammetric Engineering & Remote Sensing, PERS > vol 80 n° 10 (October 2014) . - pp 953 - 961[article]Measurements of forest biomass change using P-Band synthetic aperture radar backscatter / Gustaf Sandberg in IEEE Transactions on geoscience and remote sensing, vol 52 n° 10 tome 1 (October 2014)PermalinkNow you see it… Now you don’t: Understanding airborne mapping LiDAR collection and data product generation for archaeological research in Mesoamerica / Juan Fernandez-Diaz in Remote sensing, vol 6 n° 10 (October 2014)PermalinkCombinatorial clustering and its application to 3D polygonal traffic sign reconstruction from multiple images / Bruno Vallet in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)PermalinkSemantic 3D scene interpretation: A framework combining optimal neighborhood size selection with relevant features / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)PermalinkAssessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests / Jason R. Parent in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)PermalinkComparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves / Rubén Valbuena in ISPRS Journal of photogrammetry and remote sensing, vol 95 (September 2014)PermalinkDéveloppement et exploitation d'un produit de type "image solide". Application à l'analyse géostructurale des ouvrages rocheux de la SNCF / Antoine Gozé in XYZ, n° 140 (septembre - novembre 2014)PermalinkError analysis of a mobile terrestrial LiDAR system / M. Leslar in Geomatica, vol 68 n° 3 (September 2014)PermalinkFrankenstein's data / Keiran Millard in GEO: Geoconnexion international, vol 13 n° 8 (september 2014)PermalinkGenerating pit-free canopy height models from airborne lidar / Anahita Khosravipour in Photogrammetric Engineering & Remote Sensing, PERS, vol 80 n° 9 (September 2014)Permalink