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Polarimétrie radar complète et partielle pour le suivi des surfaces terrestres / Pierre-Louis Frison in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)
[article]
Titre : Polarimétrie radar complète et partielle pour le suivi des surfaces terrestres Type de document : Article/Communication Auteurs : Pierre-Louis Frison , Auteur ; Cédric Lardeux, Auteur ; Bénédicte Fruneau , Auteur ; Jean-Paul Rudant , Auteur Année de publication : 2019 Article en page(s) : pp 33 - 39 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] carte de la végétation
[Termes IGN] classification
[Termes IGN] extraction de la végétation
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] polarimétrie radar
[Termes IGN] sédimentation
[Termes IGN] TunisieRésumé : (auteur) This article presents some illustrations of (fully or partial) polarimetric radar data applications for the monitoring of terrestrial surfaces. The first part is dedicated to fully polarimetric radar data. Firstly, a theoretical reminder presents the specificity of fully polarimetric data. Then illustrations are given for vegetation types cartography as well as spatio-temporal processes of sedimentation in a semi-arid area in Tunisia. The second part focuses on partially polarimetric data, of the type acquired by the Sentinel-1A/1B satellite SAR sensors, which will be widely used in future years due to their significant contribution to land surface observations studies for environmental sciences. Numéro de notice : A2019-346 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.52638/rfpt.2019.464 En ligne : https://doi.org/10.52638/rfpt.2019.464 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93383
in Revue Française de Photogrammétrie et de Télédétection > n° 219-220 (juin - octobre 2019) . - pp 33 - 39[article]Efficiency of post-stratification for a large-scale forest inventory : case Finnish NFI / Helena Haakana in Annals of Forest Science, vol 76 n° 1 (March 2019)
[article]
Titre : Efficiency of post-stratification for a large-scale forest inventory : case Finnish NFI Type de document : Article/Communication Auteurs : Helena Haakana, Auteur ; Juha Heikkinen, Auteur ; Matti Katila, Auteur ; Annika S. Kangas, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] carte de la végétation
[Termes IGN] densité de la végétation
[Termes IGN] Finlande
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] ressources forestières
[Termes IGN] stratification
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message : Post-stratification based on remotely sensed data is an efficient method in estimating regional-level results in the operational National Forest Inventory. It also enables calculating the results accurately for smaller areas than with the default method of using the field plots only.
Context : The utilization of auxiliary information in survey sampling through model-assisted estimation or post-stratification has gained popularity in forest inventory recently. However, post-stratification at a large scale involves practical concerns such as the availability of auxiliary data independent of the sample at hand, and a large number of variables for which the results are needed.
Aims : We assessed the efficiency of two different types of post-stratification, either post-stratifying for each variable of interest separately or using one post-stratification for all variables, compared to the estimation based on the field sample plots only. In addition, we examined the precision of area and volume estimates, and the efficiency of post-stratification at different spatial scales.
Methods : For post-stratification, we used the volume maps based on Landsat satellite imagery, digital map data, and the sample plot data of the previous inventory. The efficiencies of post-stratifications based on the mean volume and the mean volumes by tree species were compared.
Results : In estimating the total volume, the relative efficiency of post-stratification compared to field plot based estimation was 1.54–3.54 over the provinces in South Finland. In estimating the volumes by tree species groups, the relative efficiency was 0.93–2.39. The gain with a separate stratification compared to the stratification based on total mean volume for all variables was at largest 0.69. In the small test areas, the relative standard errors of the total volume estimates decreased on average by 33% by using post-stratification instead of sample plots only. The mean relative efficiency was 2.36.
Conclusion : The utilization of an old forest resources map and post-stratification based on the mean volume is an operational approach for the National Forest Inventory. Post-stratification also enables calculating the results accurately for markedly smaller areas than with the field plots only. Post-stratification reduced the probability of very high sampling variances, making the results more robust.Numéro de notice : A2019-042 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-018-0795-6 Date de publication en ligne : 30/01/2019 En ligne : https://doi.org/10.1007/s13595-018-0795-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92040
in Annals of Forest Science > vol 76 n° 1 (March 2019)[article]Tree cover mapping using hybrid fuzzy C-means method and multispectral satellite images / Linda Gulbe in Baltic forestry, vol 25 n° 1 ([01/02/2019])
[article]
Titre : Tree cover mapping using hybrid fuzzy C-means method and multispectral satellite images Type de document : Article/Communication Auteurs : Linda Gulbe, Auteur ; Aleksandrs Kozlovs, Auteur ; Janis Donis, Auteur ; Agris Tradkovs, Auteur Année de publication : 2019 Article en page(s) : pp 113 - 123 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] carte de la végétation
[Termes IGN] classification barycentrique
[Termes IGN] classification floue
[Termes IGN] estimation statistique
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] image multibande
[Termes IGN] image Sentinel-MSI
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] LettonieRésumé : (auteur) Countrywide up-to-date tree cover maps provide valuable information for planning and management purposes to investigate location of the resources and to identify afforestation and deforestation patterns. Landsat programme offers freely available satellite data with time span more than three decades and it can serve as bases for tree cover map calculation using satellite image classification; however, practical use of classification methods is limited due to lack of user-friendly solutions and complex interpretation of the results. The objective of this study is to evaluate user-friendly hybrid classification scheme for tree cover mapping in Latvia and to explore the nature of the spectral classes and consistency of the results when methodology is applied to images of different dates. Tree cover in this context means the area covered by crown of the tree, which may or may not be considered as forest according to local provisions. Tree cover is estimated using unsupervised fuzzy c-means methods with the stability check to ensure the presence of the same spectral classes in independent tests. Spectral classes are classified into two categories: tree cover and other by employing k-nearest neighbours. Such approach does not require high quality sample data and does not include user defined internal parameters of the algorithms (however, they can be specified if needed). The best overall accuracy achieved for year 2014 was 94.2% with producer's accuracy 98.7% (tree cover), 90.5% (other land cover), user's accuracy 90.0% (tree cover), 98.8% (other land cover) and kappa 0.89. Consistency studies showed high impact (within 10% of overall accuracy) of unique conditions during the image acquisition. Some of the spectral classes represent borderline case between relatively dense tree cover and other land cover types like sparse young stands. Those cases are the main threat to the consistency between the results of different dates and seasons. Numéro de notice : A2019-375 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : sans En ligne : https://balticforestry.lammc.lt/bf/PDF_Articles/2019-25%5B1%5D/Baltic%20Forestry [...] Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93417
in Baltic forestry > vol 25 n° 1 [01/02/2019] . - pp 113 - 123[article]Bridging the gap: toward a French MS-NFI for territories / Jean-Pierre Renaud (2019)
Titre : Bridging the gap: toward a French MS-NFI for territories Type de document : Article/Communication Auteurs : Jean-Pierre Renaud , Auteur ; Dinesh Babu Irulappa-Pillai-Vijayakumar , Auteur ; François Morneau , Auteur ; Cédric Vega , Auteur Editeur : Paris [France] : Office national des forêts ONF Année de publication : 2019 Conférence : Conference 2019, A century of national forest inventories – informing past, present and future decisions 19/05/2019 21/05/2019 Oslo Norvège programme sans actes Langues : Anglais (eng) Descripteur : [Termes IGN] carte forestière
[Termes IGN] classification barycentrique
[Termes IGN] densité de la végétation
[Termes IGN] données auxiliaires
[Termes IGN] données de terrain
[Termes IGN] feuillu
[Termes IGN] forêt tempérée
[Termes IGN] image aérienne
[Termes IGN] image Landsat
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] placette d'échantillonnage
[Termes IGN] surface terrière
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Introduction: National forest inventories are designed to produce statistics about forest attributes at a national to regional scales. Beyond these administrative units, the amount of points become limiting in terms of precision. In France, the establishment of regional programs for forest and wood (PRFB) require estimates at a smaller scale. The multisource inventory approaches allowed to bridge this gap (Tomppo et al. 2008). The methods rely on the combination of field plot information with auxiliary data (Kangas et al. 2018). The objective was to set up a multisource inventory workflow for the French Forest and to evaluate the gain in precision obtain at different administrative levels. Materials and methods: This research was conducted over a 7500 km2 area located in centre of France, of which 50 % is covered by forests dominated by broadleaved species. The forest area included 775 NFI plots collected during the 2009-2014 period. The auxiliary data were acquired in 2013-2014 and selected to fulfil the following criteria: Relevant, i.e. well correlated with the forest attributed under survey; Actualized Regularly for updating; Exhaustive over the whole territory; and Economical (RARE2). In this regard, we used the following data sources: Landsat images, 3D models derived from aerial photographs and a forest thematic map. We further evaluated the contribution of 3D models acquired 5 years apart in a subset area. The multisource approach relies on the non-parametric k-nearest neighbours (k-nn) approach owing to its multivariate capabilities. The k-nn was optimised for variable selection, number of neighbours (k) and distance metrics. Its performance was tested under a model-assisted framework using estimators from Mandallaz (2013) for various administrative levels. Results: Among the auxiliary variables tested, the 3D data source from aerial photographs performed best, as compared to Landsat, or forest thematic maps. The best combination of data included all sources and provide relative efficiencies (RE) varying from 2.05 for volume to 1.03 for stand density. Over the subset area, the diachronic data allow to improve the RE from 3-26 %. The diachronic data markedly improved the efficiency in estimations of forest type volumes, basal area and stand density. Similar RE were obtained for small area estimation at the scale of Canton and Municipalities. Conclusion: Our results confirmed the importance of 3D models of forest canopies and demonstrated the interest of canopy changes to improve precision of some forest attributes such as production volume and density, which are associated with fluxes. Numéro de notice : C2019-064 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96975 Polarimetric radar vegetation index for biomass estimation in desert fringe ecosystems / Jisung Geba Chang in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)
[article]
Titre : Polarimetric radar vegetation index for biomass estimation in desert fringe ecosystems Type de document : Article/Communication Auteurs : Jisung Geba Chang, Auteur ; Maxim Shoshany, Auteur ; Yisok Oh, Auteur Année de publication : 2018 Article en page(s) : pp 7102 - 7108 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] allométrie
[Termes IGN] bande C
[Termes IGN] bande L
[Termes IGN] bassin méditerranéen
[Termes IGN] biomasse
[Termes IGN] carte de la végétation
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] données de terrain
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image Sentinel-SAR
[Termes IGN] indice de végétation
[Termes IGN] polarimétrie radar
[Termes IGN] zone aride
[Termes IGN] zone semi-arideRésumé : (auteur) Biomass estimation of eastern Mediterranean shrublands was investigated using PALSAR full- and dual-polarization L-band and Sentinel-1 dual-polarization C-band data. First, we conducted an empirical assessment of single and multiple regressions between polarized backscattering coefficients and shrubland biomass distribution along the climatic gradient between semiarid and arid regions. We then found that the PALSAR L-band HV-polarized backscattering coefficient has higher biomass information content than Sentinel-1 C-band data. Based on a theoretical volume scattering model and a semiempirical model, we propose a new polarimetric radar vegetation index (PRVI) that utilizes the degree of polarization and the cross-polarized backscattering coefficient. The relationship between the new index and the biomass was assessed with reference to normalized difference vegetation index-based biomass estimates calculated using Landsat imagery. The PRVI was found to have higher correlation with biomass compared with other radar polarization parameters, in general, and an existing radar vegetation index (RVI), in particular. Assessment of PRVI-based biomass predictions compared with allometric data extracted from air photographs, Lidar, and field data for 67 sites across the desert fringe zone indicated moderate performance with an RMSE of 0.329 kg/m 2 , while an RVI-based biomass estimation had an RMSE of 0.439 kg/m². Numéro de notice : A2018-553 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2848285 Date de publication en ligne : 03/07/2018 En ligne : http://dx.doi.org/10.1109/TGRS.2018.2848285 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91659
in IEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 7102 - 7108[article]Separating the influence of vegetation changes in polarimetric differential SAR interferometry / Virginia Brancato in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkCartographie des forêts humides dans la région d’El Kala (Algérie) à l’aide des outils d’observation de la Terre / Asma Kahli in Revue d'écologie, vol 73 n° 4 (octobre - décembre 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)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)PermalinkUncertainties in tree cover maps of Sub-Saharan Africa and their implications for measuring progress towards CBD Aichi Targets / Dorit Gross in Remote sensing in ecology and conservation, vol 4 n° 2 (June 2018)PermalinkAn object-based approach for mapping forest structural types based on low-density LiDAR and multispectral imagery / Luis Angel Ruiz in Geocarto international, vol 33 n° 5 (May 2018)PermalinkCartographie des défoliations du massif forestier du Pays des étangs en Lorraine : Apports potentiels de la télédétection / Thierry Bélouard in Revue forestière française, vol 70 n° 5 (2018)PermalinkMapping tree cover with Sentinel-2 data using the Support Vector Machine (SVM) / Anna Mirończuk in Geoinformation issues, Vol 9 n° 1 (2017)PermalinkProgrès de la cartographie forestière mais persistance d'incertitudes : Cas de Madagascar / Georges Serpantié in Cartes & Géomatique, n° 235-236 (mars - juin 2018)PermalinkEstimation cohérente de l'indice de surface foliaire en utilisant des données terrestres et aéroportées / Ronghai Hu (2018)PermalinkUn inventaire forestier multisource pour la gestion des territoires / Dinesh Babu Irulappa-Pillai-Vijayakumar (2018)PermalinkMéthodes d'inventaire multisource : améliorer la précision des estimations de l'IFN et atteindre l'échelle des territoires [diaporama] / Cédric Vega (2018)PermalinkSynergie des données Sentinel optiques et radar pour l’observation et l’analyse de la végétation du littoral du Pays de Brest / Antoine Billey (2018)PermalinkUtilisation de QGIS en télédétection, ch. 6. Cartographie de la végétation à partir d'images radar Sentinel-1 / Pierre-Louis Frison (2018)PermalinkA mangrove forest map of China in 2015: Analysis of time series Landsat 7/8 and Sentinel-1A imagery in Google Earth Engine cloud computing platform / Bangqian Chen in ISPRS Journal of photogrammetry and remote sensing, vol 131 (September 2017)PermalinkReducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data / Timo P Pitkänen in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)PermalinkMapping forest attributes using data from stereophotogrammetry of aerial images and field data from the national forest inventory / Jonas Bohlin in Silva fennica, vol 51 n° 2 (2017)PermalinkMapping spatial distribution of forest age in China / Yuan Zhang in Earth and space science, vol 4 n° 3 (March 2017)PermalinkPermalinkPermalink