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Airborne lidar estimation of aboveground forest biomass in the absence of field inventory / António Ferraz in Remote sensing, vol 8 n° 8 (August 2016)
[article]
Titre : Airborne lidar estimation of aboveground forest biomass in the absence of field inventory Type de document : Article/Communication Auteurs : António Ferraz , Auteur ; Sassan Saatchi, Auteur ; Clément Mallet , Auteur ; Stéphane Jacquemoud, Auteur ; Gil Rito-Gonçalves , Auteur ; Carlos Alberto Silva, Auteur ; Paola Soares, Auteur ; Margarida Tomé, Auteur ; Luisa Pereira, Auteur Année de publication : 2016 Projets : 3-projet - voir note / Article en page(s) : pp 1 - 18 Note générale : Bibliographie
This work was supported in part by the Portuguese Foundation for Science and Technology under Grant PTDC/AGR-CFL/72380/2006, co-financed by the European Fund of Regional Development (FEDER) through COMPETE—Operational Factors of Competitiveness Program (POFC) and the Grant Pest-OE/EEI/UI308/2014Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] allométrie
[Termes IGN] analyse de groupement
[Termes IGN] biomasse aérienne
[Termes IGN] biomasse forestière
[Termes IGN] classification automatique d'objets
[Termes IGN] couvert végétal
[Termes IGN] dendrométrie
[Termes IGN] données lidar
[Termes IGN] extraction d'arbres
[Termes IGN] fiabilité des données
[Termes IGN] houppier
[Termes IGN] Portugal
[Termes IGN] puits de carbone
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestierRésumé : (Auteur) The scientific community involved in the UN-REDD program is still reporting large uncertainties about the amount and spatial variability of CO2 stored in forests. The main limitation has been the lack of field samplings over space and time needed to calibrate and convert remote sensing measurements into aboveground biomass (AGB). As an alternative to costly field inventories, we examine the reliability of state-of-the-art lidar methods to provide direct retrieval of many forest metrics that are commonly collected through field sampling techniques (e.g., tree density, individual tree height, crown cover). AGB is estimated using existing allometric equations that are fed by lidar-derived metrics at either the individual tree- or forest layer-level (for the overstory or underneath layers, respectively). Results over 40 plots of a multilayered forest located in northwest Portugal show that the lidar method provides AGB estimates with a relatively small random error (RMSE = of 17.1%) and bias (of 4.6%). It provides local AGB baselines that meet the requirements in terms of accuracy to calibrate satellite remote sensing measurements (e.g., the upcoming lidar GEDI (Global Ecosystem Dynamics Investigation), and the Synthetic Aperture Radar (SAR) missions NISAR (National Aeronautics and Space Administration and Indian Space Research Organization SAR) and BIOMASS from the European Space Agency, ESA) for AGB mapping purposes. The development of similar techniques over a variety of forest types would be a significant improvement in quantifying CO2 stocks and changes to comply with the UN-REDD policies. Numéro de notice : A2016--104 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Autre URL associée : vers HAL Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs8080653 Date de publication en ligne : 12/08/2016 En ligne : https://doi.org/10.3390/rs8080653 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84675
in Remote sensing > vol 8 n° 8 (August 2016) . - pp 1 - 18[article]Documents numériques
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A2016--104_Airborne_lidar_estimation_of_aboveground_forest_biomassAdobe Acrobat PDF Automatic extraction of road networks from GPS traces / Jia Qiu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 8 (August 2016)
[article]
Titre : Automatic extraction of road networks from GPS traces Type de document : Article/Communication Auteurs : Jia Qiu, Auteur ; Ruisheng Wang, Auteur Année de publication : 2016 Article en page(s) : pp 593 - 604 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] analyse de groupement
[Termes IGN] appariement de points
[Termes IGN] compensation par moindres carrés
[Termes IGN] données GPS
[Termes IGN] extraction automatique
[Termes IGN] extraction de données
[Termes IGN] modèle de Markov
[Termes IGN] relation topologique
[Termes IGN] réseau routier
[Termes IGN] segmentationRésumé : (auteur) We propose a point segmentation and grouping method to generate road maps from GPS traces. First, we present a progressive point cloud segmentation algorithm based on Total Least Squares (TLS) line fitting. Second, we group topologically connected point clusters by the point's orientation and cluster's spatial proximity, where the topological relationship is generated using Hidden Markov Model (HMM) map matching. Finally, we refine the intersections of roads so that their geometrical and topological relationships are consistent with each other. Experimental results show that our algorithm is robust to noises and the generated road network has a high accuracy in terms of geometry and topology. Compare to the representative algorithms; the results of our new algorithm have a higher F-measure score for different matching thresholds. Numéro de notice : A2016-606 Affiliation des auteurs : non IGN Thématique : INFORMATIQUE/MATHEMATIQUE/POSITIONNEMENT Nature : Article DOI : 10.14358/PERS.82.8.593 En ligne : http://dx.doi.org/10.14358/PERS.82.8.593 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81796
in Photogrammetric Engineering & Remote Sensing, PERS > vol 82 n° 8 (August 2016) . - pp 593 - 604[article]Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping / L. Drăguț in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)
[article]
Titre : Land-surface segmentation as a method to create strata for spatial sampling and its potential for digital soil mapping Type de document : Article/Communication Auteurs : L. Drăguț, Auteur ; A. Dornik, Auteur Année de publication : 2016 Article en page(s) : pp 1359 - 1376 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse d'image numérique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse de groupement
[Termes IGN] cartographie numérique
[Termes IGN] échantillonnage de données
[Termes IGN] modèle numérique de surface
[Termes IGN] validation des donnéesRésumé : (Auteur) Sampling efforts are constrained by limited availability of resources. Therefore, methods to reduce the number of samples, while still achieving reasonable accuracy are needed. Land-surface segmentation (LSS) has proven a powerful technique to partition digital elevation models (DEMs) and their derivatives into relatively homogeneous areas, which can be further employed as support in soil sampling. Though topography is one of the main soil forming factors, a robust assessment of the potential of this technique to digital soil mapping (DSM) is still missing. In this study, we aimed at evaluating the potential of LSS in stratifying a landscape into relatively homogeneous areas, which can be used as strata for guiding the selection of sampling points in DSM. The experiments were carried out in two study areas where soil samples were available. Land-surface derivatives were derived from DEMs and segmented with a tool based on the multiresolution segmentation algorithm, into objects considered as homogeneous soil-landscape divisions. Thus, one sample was randomly selected within each segment from the existing sample data, based on which predictions of soil classes/sub-orders and properties, i.e. soil texture and A-horizon thickness, were made. Results were compared with predictions based on simple random sampling (SRS) and conditioned Latin hypercube (cLHS). The segmentation-based sampling (SBS) scheme performed better than SRS and cLHS schemes in predicting the A-horizon thickness, soil texture fractions and soil classes, showing a high potential of LSS in stratifying a landscape for the purposes of DSM. The novelty of this study is in the way strata are constructed, rather than in the sampling design itself. Further research is needed to demonstrate the value of a SBS design for practical use. The analyses presented here further highlight the importance of considering locally adaptive techniques in optimization of sampling schemes and predictions of soil properties. Numéro de notice : A2016-307 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2015.1131828 En ligne : http://dx.doi.org/10.1080/13658816.2015.1131828 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80906
in International journal of geographical information science IJGIS > vol 30 n° 7- 8 (July - August 2016) . - pp 1359 - 1376[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016042 RAB Revue Centre de documentation En réserve L003 Disponible 079-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Pan-sharpening quality investigation of PLÉIADES-1A images / Mustafa Ozendi in Geocarto international, vol 31 n° 7 - 8 (July - August 2016)
[article]
Titre : Pan-sharpening quality investigation of PLÉIADES-1A images Type de document : Article/Communication Auteurs : Mustafa Ozendi, Auteur ; Hyseyin Topan, Auteur ; Murat Oruc, Auteur ; Ali Cam, Auteur Année de publication : 2016 Article en page(s) : pp 881 - 890 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] affinage d'image
[Termes IGN] analyse en composantes principales
[Termes IGN] coefficient de corrélation
[Termes IGN] évaluation des données
[Termes IGN] image Pléiades-HR
[Termes IGN] pansharpening (fusion d'images)
[Termes IGN] qualité du processus
[Termes IGN] transformation de Brovey
[Termes IGN] transformation intensité-teinte-saturationRésumé : (Auteur) Optical remote sensing satellites obtain MS and Pan images simultaneously over the same coverage area. Remote sensing and image processing communities are working on different pan-sharpening methods capable of taking advantage of MS and Pan images. Each remote sensing system has its own advantages and disadvantages, leading to the question ‘Which pan-sharpening method should be used for which type of imagery?’ The aim of this research is to investigate the pan-sharpening performance of PLÉIADES-1A images. For this purpose, pan-sharpened images were generated using PCA, IHS and Brovey Transform which are the most popular pan-sharpening methods. Then, the pan-sharpened images were evaluated quantitatively using Correlation Coefficient, Root Mean Square Error, Relative Average Spectral Error, Spectral Angle Mapper and Erreur Relative Globale Adimensionnelle de Synthése. In addition, pan-sharpened images were evaluated qualitatively by taking object availability and completeness into consideration. Numéro de notice : A2016-459 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2015.1094520 Date de publication en ligne : 20/10/2015 En ligne : http://dx.doi.org/10.1080/10106049.2015.1094520 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81383
in Geocarto international > vol 31 n° 7 - 8 (July - August 2016) . - pp 881 - 890[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Sparse and low-rank graph for discriminant analysis of hyperspectral imagery / Wei Li in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)
[article]
Titre : Sparse and low-rank graph for discriminant analysis of hyperspectral imagery Type de document : Article/Communication Auteurs : Wei Li, Auteur ; Jiabin Liu, Auteur ; Qian Du, Auteur Année de publication : 2016 Article en page(s) : pp 4094 - 4105 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse discriminante
[Termes IGN] analyse en composantes principales
[Termes IGN] graphe
[Termes IGN] image hyperspectrale
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] valeur propreRésumé : (Auteur) Recently, sparse graph-based discriminant analysis (SGDA) has been developed for the dimensionality reduction and classification of hyperspectral imagery. In SGDA, a graph is constructed by ℓ1-norm optimization based on available labeled samples. Different from traditional methods (e.g., k-nearest neighbor with Euclidean distance), weights in an ℓ1-graph derived via a sparse representation can automatically select more discriminative neighbors in the feature space. However, the sparsity-based graph represents each sample individually, lacking a global constraint on each specific solution. As a consequence, SGDA may be ineffective in capturing the global structures of data. To overcome this drawback, a sparse and low-rank graph-based discriminant analysis (SLGDA) is proposed. Low-rank representation has been proved to be capable of preserving global data structures, although it may result in a dense graph. In SLGDA, a more informative graph is constructed by combining both sparsity and low rankness to maintain global and local structures simultaneously. Experimental results on several different multiple-class hyperspectral-classification tasks demonstrate that the proposed SLGDA significantly outperforms the state-of-the-art SGDA. Numéro de notice : A2016-879 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2016.2536685 En ligne : http://dx.doi.org/10.1109/TGRS.2016.2536685 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83042
in IEEE Transactions on geoscience and remote sensing > vol 54 n° 7 (July 2016) . - pp 4094 - 4105[article]Use of doppler parameters for ship velocity computation in SAR images / Alfredo Renga in IEEE Transactions on geoscience and remote sensing, vol 54 n° 7 (July 2016)PermalinkSupervised classification of very high resolution optical images using wavelet-based textural features / Olivier Regniers in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 2016)PermalinkAn effective toolkit for the interpolation and gross error detection of GPS time series / X. Wang in Survey review, vol 48 n° 348 (May 2016)PermalinkTowards reliable velocities of permanent GNSS stations / Janusz Bogusz in Reports on geodesy and geoinformatics, vol 100 (May 2016)PermalinkClassified and clustered data constellation: An efficient approach of 3D urban data management / Suhaibah Azri in ISPRS Journal of photogrammetry and remote sensing, vol 113 (March 2016)PermalinkComparative analysis on utilisation of linear spectral unmixing and band ratio methods for processing ASTER data to delineate bauxite over a part of Chotonagpur plateau, Jharkhand, India / Arindam Guha in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)PermalinkUniformity-based superpixel segmentation of hyperspectral images / Arun M. Saranathan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)PermalinkMatrix-based discriminant subspace ensemble for hyperspectral image spatial–spectral feature fusion / Renlong Hang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)PermalinkValidation of medium-scale historical maps of southern Latvia for evaluation of impact of continuous forest cover on the present-day mean stand area and tree species richness / Anda Fescenko in Baltic forestry, vol 22 n° 1 ([01/02/2016])PermalinkContributions à la segmentation non supervisée d'images hyperspectrales : trois approches algébriques et géométriques / Saadallah El Asmar (2016)PermalinkEnabling geovisual analytics of health data using a server-side approach / Ulanbek Turdukulov in Cartography and Geographic Information Science, Vol 43 n° 1 (January 2016)PermalinkEuropean handbook of crowdsourced geographic information, ch. 12. Gaining knowledge from georeferenced social media data with visual analytics / Gennady Andrienko (2016)PermalinkMultifractal analysis for multivariate data with application to remote sensing / Sébastien Combrexelle (2016)PermalinkRemote Sensing Observations of Continental Surfaces, ch. 6. Airborne lidar data processing / Clément Mallet (2016)PermalinkPermalinkSpatially constrained clustering of ecological units to facilitate the design of integrated water monitoring networks in the St. Lawrence Basin / M.D. Adams in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkThe iQmulus urban showcase: automatic tree classification and identification in huge mobile mapping point clouds / Jan Böhm (2016)PermalinkVegetation classification and biogeography of European floodplain forests and alder carrs / Jan Douda in Applied Vegetation Science, vol 19 n° 1 (January 2016)PermalinkDiscrimination of deciduous tree species from time series of unmanned aerial system imagery / Jonathan Lisein in Plos one, vol 10 n° 11 (November 2015)PermalinkAPFiLoc: An Infrastructure-Free Indoor Localization method fusing smartphone inertial sensors, landmarks and map information / Jianga Shang in Sensors, vol 15 n° 10 (October 2015)Permalink