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Predicting tree diameter distributions from airborne laser scanning, SPOT 5 satellite, and field sample data in the perm region, Russia / Jussi Peuhkurinen in Forests, vol 9 n° 10 (October 2018)
[article]
Titre : Predicting tree diameter distributions from airborne laser scanning, SPOT 5 satellite, and field sample data in the perm region, Russia Type de document : Article/Communication Auteurs : Jussi Peuhkurinen, Auteur ; Timo Tokola, Auteur ; Kseniia Plevak, Auteur ; Sanna Sirparanta, Auteur ; et al., Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies sibirica
[Termes IGN] Alnus incana
[Termes IGN] Betula pendula
[Termes IGN] classification barycentrique
[Termes IGN] diamètre des arbres
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image SPOT 5
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Picea abies
[Termes IGN] Pinus sibirica
[Termes IGN] Pinus sylvestris
[Termes IGN] placette d'échantillonnage
[Termes IGN] Populus tremula
[Termes IGN] Russie
[Termes IGN] Salix caprea
[Termes IGN] Tilia cordata
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) A tree list is a list of trees in the area of interest containing, for example, the species, diameter, height, and stem volume of each tree. Tree lists can be used to derive various characteristics of the growing stock, and are therefore versatile and informative sources of data for several forest management purposes. Especially in heterogonous and unmanaged forest structures with multiple species, tree list estimates imputed from local reference field data can provide an alternative to mean value estimates of growing stock (e.g., basal area, total stem volume, mean tree diameter, mean tree height, and number of trees). In this study, reference field plots, airborne laser scanning (ALS) data, and SPOT 5 satellite (Satellite Pour l’Observation de la Terre) imagery were used for tree list imputation applying the k most similar neighbors (k-MSN) estimation method in the West Ural taiga region of the Russian Federation for diameter distribution estimation. In k-MSN, weighted average of k field reference plots with highest similarity between field reference plot and target (forest grid cell, or field plot) based on ALS and SPOT 5 features were used to predict the mean values of growing stock and tree lists for the target object simultaneously. Diameter distributions were then constructed from the predicted tree lists. The prediction of mean values and diameter distributions was tested in 18 independent validation plots of 0.25–0.5 ha in size, whose species specific diameter distributions were measured in the field and grouped into three functional groups (Pines, Spruce/Fir, Broadleaf Group), each containing several species. In terms of root mean squared error relative to mean of validation plots, the accuracy of estimation was 0.14 and 0.17 for basal area and total stem volume, respectively. Reynolds error index values and visual inspection showed encouraging results in evaluating the goodness-of-fit statistics of the estimated diameter distributions. Although estimation accuracy was worse for functional group mean values and diameter distributions, the results indicate that it is possible to predict diameter distributions in forests of the test area with the tested methodology and materials. Numéro de notice : A2018-476 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f9100639 Date de publication en ligne : 13/10/2018 En ligne : https://doi.org/10.3390/f9100639 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91176
in Forests > vol 9 n° 10 (October 2018)[article]Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series / Gang Chen in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)
[article]
Titre : Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Jean-Claude Thill, Auteur ; Sutee Anantsuksomsri, Auteur ; Nij Tontisirin, Auteur ; Ran Tao, Auteur Année de publication : 2018 Article en page(s) : pp 94 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] Birmanie
[Termes IGN] Chine
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] Hevea brasiliensis
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Laos
[Termes IGN] modèle de croissance végétale
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] plantation forestière
[Termes IGN] série temporelleRésumé : (Auteur) Rubber (Hevea brasiliensis) plantations are a rapidly increasing source of land cover change in mainland Southeast Asia. Stand age of rubber plantations obtained at fine scales provides essential baseline data, informing the pace of industrial and smallholder agricultural activities in response to the changing global rubber markets, and local political and socioeconomic dynamics. In this study, we developed an integrated pixel- and object-based tree growth model using Landsat annual time series to estimate the age of rubber plantations in a 21,115 km2 tri-border region along the junction of China, Myanmar and Laos. We produced a rubber stand age map at 30 m resolution, with an accuracy of 87.00% for identifying rubber plantations and an average error of 1.53 years in age estimation. The integration of pixel- and object-based image analysis showed superior performance in building NDVI yearly time series that reduced spectral noises from background soil and vegetation in open-canopy, young rubber stands. The model parameters remained relatively stable during model sensitivity analysis, resulting in accurate age estimation robust to outliers. Compared to the typically weak statistical relationship between single-date spectral signatures and rubber tree age, Landsat image time series analysis coupled with tree growth modeling presents a viable alternative for fine-scale age estimation of rubber plantations. Numéro de notice : A2018-399 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.07.003 Date de publication en ligne : 13/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.07.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90828
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 94 - 104[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018103 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018102 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Unmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil / Sébastien Giordano in IEEE Transactions on geoscience and remote sensing, vol 56 n° 10 (October 2018)
[article]
Titre : Unmixing polarimetric radar images based on land cover type identified by higher resolution optical data before target decomposition: application to forest and bare soil Type de document : Article/Communication Auteurs : Sébastien Giordano , Auteur ; Grégoire Mercier, Auteur ; Jean-Paul Rudant , Auteur Année de publication : 2018 Projets : 1-Pas de projet / Article en page(s) : pp 5850 - 5862 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] analyse linéaire des mélanges spectraux
[Termes IGN] biomasse aérienne
[Termes IGN] décomposition spectrale
[Termes IGN] données polarimétriques
[Termes IGN] forêt
[Termes IGN] image Radarsat
[Termes IGN] matrice de covariance
[Termes IGN] occupation du sol
[Termes IGN] polarimétrie radar
[Termes IGN] sol nu
[Termes IGN] surface forestièreRésumé : (auteur) Extracting information from a polarimetric radar representation usually consists in decomposing it with target decomposition algorithms. This first step can be seen as a geometric analysis of the polarimetric information: the identification of physical radar scattering mechanisms. The problem is that average physical parameters are estimated. As a consequence, these parameters might not describe correctly any of the land cover types that can be mixed together into the radar resolution cell. Therefore, using the polarimetric parameters for land cover classification is challenging. The novelty of the method is to propose a thematic analysis of the polarimetric information preceding the geometric one. The objective is to assess if splitting off polarimetric information on a land cover type basis before applying usual target decomposition algorithms can produce more consistent radar scattering mechanisms when land cover classes are mixed inside the radar resolution cell. A cooperative fusion framework in which very high-resolution optical images are used to unmix physical radar scattering mechanisms is proposed. For bare soil and forests, we point out that a linear unmixing model applied to the covariance matrix is able to split off polarimetric information on a land cover type basis. The assessment of the unmixed radar matrices is carried out with polarimetric radar images from the Radarsat-2 satellite. It was found that despite speckle, the reconstructed radar information after the unmixing process is statistically relevant with the observations. The question whether the unmixed radar images contain relevant thematic information is more challenging, but results tend to validate this property. This method could be used to have a better estimation of vegetation biomass in the context of open forested areas. Numéro de notice : A2018-331 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2827258 Date de publication en ligne : 09/07/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2827258 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90475
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 10 (October 2018) . - pp 5850 - 5862[article]Assessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja, Nigeria / Christopher Ifechukwude Chima in Geocarto international, vol 33 n° 9 (September 2018)
[article]
Titre : Assessment of Nigeriasat-1 satellite data for urban land use/land cover analysis using object-based image analysis in Abuja, Nigeria Type de document : Article/Communication Auteurs : Christopher Ifechukwude Chima, Auteur ; Nigel Trodd, Auteur ; Matthew Blackett, Auteur Année de publication : 2018 Article en page(s) : pp 893 - 911 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] analyse d'image orientée objet
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] image Landsat-ETM+
[Termes IGN] image NigeriaSat
[Termes IGN] image SPOT 5
[Termes IGN] image SPOT-HRG
[Termes IGN] occupation du solRésumé : (Auteur) This study assesses the usefulness of Nigeriasat-1 satellite data for urban land cover analysis by comparing it with Landsat and SPOT data. The data-sets for Abuja were classified with pixel- and object-based methods. While the pixel-based method was classified with the spectral properties of the images, the object-based approach included an extra layer of land use cadastre data. The classification accuracy results for OBIA show that Landsat 7 ETM, Nigeriasat-1 SLIM and SPOT 5 HRG had overall accuracies of 92, 89 and 96%, respectively, while the classification accuracy for pixel-based classification were 88% for Landsat 7 ETM, 63% for Nigeriasat-1 SLIM and 89% for SPOT 5 HRG. The results indicate that given the right classification tools, the analysis of Nigeriasat-1 data can be compared with Landsat and SPOT data which are widely used for urban land use and land cover analysis. Numéro de notice : A2018-336 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1316778 Date de publication en ligne : 08/05/2017 En ligne : https://doi.org/10.1080/10106049.2017.1316778 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90550
in Geocarto international > vol 33 n° 9 (September 2018) . - pp 893 - 911[article]Effects of a large-scale late spring frost on a beech (Fagus sylvatica L.) dominated Mediterranean mountain forest derived from the spatio-temporal variations of NDVI / Angelo Nolè in Annals of Forest Science, vol 75 n° 3 (September 2018)
[article]
Titre : Effects of a large-scale late spring frost on a beech (Fagus sylvatica L.) dominated Mediterranean mountain forest derived from the spatio-temporal variations of NDVI Type de document : Article/Communication Auteurs : Angelo Nolè, Auteur ; Angelo Rita, Auteur ; Agostino Maria Silvio Ferrara, Auteur ; Marco Borghetti, Auteur Année de publication : 2018 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] canopée
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt alpestre
[Termes IGN] forêt méditerranéenne
[Termes IGN] gelée
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TIRS
[Termes IGN] Italie
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] variation temporelleRésumé : (Auteur) Key message: A remote sensing-based approach was implemented to detect the effect of a late spring frost on beech forests in the Mediterranean mountain region. The analysis of spatio-temporal variability of frost effects on normalised difference vegetation index (NDVI) highlighted the distribution of the canopy damage across the forest according to geomorphic factors such as slope, aspect, and altitude.
Context: Increased intensity and frequency of extreme temperatures such as late spring frosts and heat waves represent the main drivers affecting forest ecosystem structure and composition in the Mediterranean region.
Aims: The main objective of this study was to evaluate the effects of a late spring frost disturbance, which occurred during spring 2016 in southern Italy, through the assessment of the spatial pattern of the damage to the beech forest canopy associated with the peak decrease in normalised difference vegetation index (NDVI), and the analysis of the NDVI temporal recovery after this frost disturbance.
Methods: The forest areas affected by frost were detected through the NDVI differencing technique based on Landsat 8 (OLI/TIRS) imagery time series. The influence of local geomorphic factors (i.e., aspect, elevation, and slope) on forest NDVI patterns was assessed by means of a generalized additive model (GAM).
Results: A rather counterintuitive NDVI patterns emerged according to the forest exposition, with NDVI significantly higher on the north facing areas than the southerly ones. The main canopy damage occurred at about 1250 m and reached up to 1500 m asl, representing the altitudinal range affected by the frost disturbance. Finally, the full canopy recovery occurred within 3 months of the frost event.
Conclusion: The analysis of seasonal Landsat 8 image time series related to local geomorphic factors, such as aspect, slope, and altitude, and plant phenology on a frost event date, contributed to highlight the NDVI spatio-temporal variation and canopy recovery of a Mediterranean mountain beech forest.Numéro de notice : A2018-328 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-018-0763-1 Date de publication en ligne : 16/08/2018 En ligne : https://doi.org/10.1007/s13595-018-0763-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90472
in Annals of Forest Science > vol 75 n° 3 (September 2018)[article]Estimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)PermalinkImprovement of countrywide vegetation mapping over Japan and comparison to existing maps / Ram C. Sharma in Advances in Remote Sensing, vol 7 n° 3 (September 2018)PermalinkIntegration of ZY3-02 satellite laser altimetry data and stereo images for high-accuracy mapping / Guoyuan Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 9 (September 2018)PermalinkInvestigation of the success of monitoring slow motion landslides using Persistent Scatterer Interferometry and GNSS methods / K.O. Hastaoglu in Survey review, vol 50 n° 363 (September 2018)PermalinkSynergetic use of Sentinel-1 and Sentinel-2 for assessments of heathland conservation status / Johannes Schmidt in Remote sensing in ecology and conservation, vol 4 n° 3 (September 2018)PermalinkThe 2015 Mw 6.4 Pishan earthquake, China: geodetic modelling inferred from Sentinel-1A TOPS interferometry / Yongsheng Li in Survey review, vol 50 n° 363 (September 2018)PermalinkAn improved temporal mixture analysis unmixing method for estimating impervious surface area based on MODIS and DMSP-OLS data / Li Zhuo in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkComparison of high-density LiDAR and satellite photogrammetry for forest inventory / Grant D. Pearse in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkA generic remote sensing approach to derive operational essential biodiversity variables (EBVs) for conservation planning / Samuel Alleaume in Methods in ecology and evolution, vol 9 n° 8 (August 2018)PermalinkICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas / Karine R.M. Adeline in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkIntra-annual phenology for detecting understory plant invasion in urban forests / Kunwar K. Singh in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)PermalinkMapping ecosystem services at the regional scale: the validity of an upscaling approach / Solen Le Clec'h in International journal of geographical information science IJGIS, vol 32 n° 7-8 (July - August 2018)PermalinkA method of downscaling temperature maps based on analytical hillshading for use in species distribution modelling / Ángel M. Felicísimo in Cartography and Geographic Information Science, Vol 45 n° 4 (July 2018)PermalinkMulti-scale assessment of invasive plant species diversity using Pléiades 1A, RapidEye and Landsat-8 data / Siddhartha Khare in Geocarto international, vol 33 n° 7 (July 2018)PermalinkSoil moisture estimation in Ferlo region (Senegal) using radar (ENVISAT/ASAR) and optical (SPOT/VEGETATION) data / Gayane Faye in The Egyptian Journal of Remote Sensing and Space Science, Vol. 21 suppl.1 (juillet 2018)PermalinkAssessment of Sentinel-1A data for rice crop classification using random forests and support vector machines / Nguyen-Thanh Son in Geocarto international, vol 33 n° 6 (June 2018)PermalinkClassification à très large échelle d’images satellites à très haute résolution spatiale par réseaux de neurones convolutifs / Tristan Postadjian in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)PermalinkFusion tardive d’images SPOT 6/7 et de données multitemporelles Sentinel-2 pour la détection de la tache urbaine / Cyril Wendl in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)PermalinkMapping rubber trees based on phenological analysis of Landsat time series data-sets / Janatul Aziera binti Abd Razak in Geocarto international, vol 33 n° 6 (June 2018)PermalinkModeling of inland flood vulnerability zones through remote sensing and GIS techniques in the highland region of Papua New Guinea / Porejane Harley in Applied geomatics, vol 10 n° 2 (June 2018)Permalink