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Microwave indices from active and passive sensors for remote sensing applications / Emanuele Santi (2019)
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Titre : Microwave indices from active and passive sensors for remote sensing applications Type de document : Monographie Auteurs : Emanuele Santi, Éditeur scientifique ; Simonetta Paloscia, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 224 p. Format : 18 x 26 cm ISBN/ISSN/EAN : 978-3-03897-820-6 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande C
[Termes IGN] bande Ku
[Termes IGN] bande X
[Termes IGN] diffusométrie
[Termes IGN] filtrage spatiotemporel
[Termes IGN] glace de mer
[Termes IGN] humidité du sol
[Termes IGN] image radar moirée
[Termes IGN] phénologie
[Termes IGN] prairie
[Termes IGN] série temporelleRésumé : (éditeur) Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices. Note de contenu : Editorial
1- Ku-, X- and C-Band microwave backscatter indices from saline snow covers on Arctic first-year sea ice
2- Retrieval of effective correlation length and snow water equivalent from radar and passive microwave measurements
3- Soil moisture from fusion of scatterometer and SAR: closing the scale gap with temporal filtering
4- Using SAR-derived vegetation descriptors in a water cloud model to improve soil
moisture retrieval
5- Sensitivity of Sentinel-1 backscatter to vegetation dynamics: An Austrian case study
6- AMSR2 soil moisture downscaling using temperature and vegetation data
7- Analysis of the Radar Vegetation Index and potential improvements
8- Radiometric microwave indices for remote sensing of land surfaces
9- Soil moisture in the Biebrza wetlands retrieved from Sentinel-1 imagery
10- Exploiting time series of Sentinel-1 and Sentinel-2 imagery to detect meadow phenology in mountain regionsNuméro de notice : 25941 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03897-821-3 En ligne : https://doi.org/10.3390/books978-3-03897-821-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96313 Potential of Sentinel-1 data for monitoring temperate mixed forest phenology / Pierre-Louis Frison in Remote sensing, vol 10 n° 12 (December 2018)
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Titre : Potential of Sentinel-1 data for monitoring temperate mixed forest phenology Type de document : Article/Communication Auteurs : Pierre-Louis Frison , Auteur ; Bénédicte Fruneau
, Auteur ; Syrine Kmiha, Auteur ; Kamel Soudani, Auteur ; Eric Dufrêne, Auteur ; Thuy Le Toan, Auteur ; Thierry Koleck, Auteur ; Ludovic Villard, Auteur ; Eric Mougin, Auteur ; Jean-Paul Rudant
, Auteur
Année de publication : 2018 Projets : 3-projet - voir note / Article en page(s) : n° 2049 Note générale : bibliographie
This research was funding by the Centre National d’Etudes Spatiales (CNES), grant number DCT/SI/TR/2016-01532Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse diachronique
[Termes IGN] arbre caducifolié
[Termes IGN] coefficient de rétrodiffusion
[Termes IGN] cohérence des données
[Termes IGN] données polarimétriques
[Termes IGN] Fontainebleau, forêt de (Seine-et-Marne)
[Termes IGN] forêt tempérée
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] phénologie
[Termes IGN] signature spectrale
[Termes IGN] surveillance forestièreRésumé : (auteur) In this study, the potential of Sentinel-1 data to seasonally monitor temperate forests was investigated by analyzing radar signatures observed from plots in the Fontainebleau Forest of the Ile de France region, France, for the period extending from March 2015 to January 2016. Radar backscattering coefficients, σ0 and the amplitude of temporal interferometric coherence profiles in relation to environmental variables are shown, such as in situ precipitation and air temperature. The high temporal frequency of Sentinel-1 acquisitions (i.e., twelve days, or six, if both Sentinel-1A and B are combined over Europe) and the dual polarization configuration (VV and VH over most land surfaces) made a significant contribution. In particular, the radar backscattering coefficient ratio of VV to VH polarization, σ0VV/σ0VH , showed a well-pronounced seasonality that was correlated with vegetation phenology, as confirmed in comparison to NDVI profiles derived from Landsat-8 (r = 0.77) over stands of deciduous trees. These results illustrate the high potential of Sentinel-1 data for monitoring vegetation, and as these data are not sensitive to the atmosphere, the phenology could be estimated with more accuracy than optical data. These observations will be quantitatively analyzed with the use of electromagnetic models in the near future. Numéro de notice : A2018-669 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs10122049 Date de publication en ligne : 17/12/2018 En ligne : https://doi.org/10.3390/rs10122049 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94271
in Remote sensing > vol 10 n° 12 (December 2018) . - n° 2049[article]CAVIAR: an R package for checking, displaying and processing wood-formation-monitoring data / Cyrille B.K. Rathgeber in Tree Physiology, vol 38 n° 8 (August 2018)
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Titre : CAVIAR: an R package for checking, displaying and processing wood-formation-monitoring data Type de document : Article/Communication Auteurs : Cyrille B.K. Rathgeber, Auteur ; Philippe Santenoise, Auteur ; Henri E. Cuny , Auteur
Année de publication : 2018 Projets : ARBRE / AgroParisTech (2007 -) Article en page(s) : pp 1246 - 1260 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cerne
[Termes IGN] données allométriques
[Termes IGN] dynamique de la végétation
[Termes IGN] forêt boréale
[Termes IGN] forêt tempérée
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Loi de Gompertz
[Termes IGN] phénologie
[Termes IGN] Pinophyta
[Termes IGN] R (langage)
[Termes IGN] régression logistique
[Termes IGN] visualisation de données
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) In the last decade, the pervasive question of climate change impacts on forests has revived investigations on intra-annual dynamics of wood formation, involving disciplines such as plant ecology, tree physiology and dendrochronology. This resulted in the creation of many research groups working on this topic worldwide and a rapid increase in the number of studies and publications. Wood-formation-monitoring studies are generally based on a common conceptual model describing xylem cell formation as the succession of four differentiation phases (cell division, cell enlargement, cell wall thickening and mature cells). They generally use the same sampling techniques, sample preparation methods and anatomical criteria to separate between differentiation zones and discriminate and count forming xylem cells, resulting in very similar raw data. However, the way these raw data are then processed, producing the elaborated data on which statistical analyses are performed, still remains quite specific to each individual study. Thereby, despite very similar raw data, wood-formation-monitoring studies yield results that are still quite difficult to compare. CAVIAR—an R package specifically dedicated to the verification, visualization and manipulation of wood-formation-monitoring data—can help to improve this situation. Initially, CAVIAR was built to provide efficient algorithms to compute critical dates of wood formation phenology for conifers growing in temperate and cold environments. Recently, we developed it further to check, display and process wood-formation-monitoring data. Thanks to new and upgraded functions, raw data can now be consistently verified, standardized and modelled (using logistic regressions and Gompertz functions), in order to describe wood phenology and intra-annual dynamics of tree-ring formation. We believe that CAVIAR will help strengthening the science of wood formation dynamics by effectively contributing to the standardization of its concepts and methods, making thereby possible the comparison between data and results from different studies. Numéro de notice : A2018-657 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/treephys/tpy054 Date de publication en ligne : 19/05/2018 En ligne : https://doi.org/10.1093/treephys/tpy054 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93813
in Tree Physiology > vol 38 n° 8 (August 2018) . - pp 1246 - 1260[article]A 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)
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Titre : A generic remote sensing approach to derive operational essential biodiversity variables (EBVs) for conservation planning Type de document : Article/Communication Auteurs : Samuel Alleaume, Auteur ; Pauline Dusseux, Auteur ; Vincent Thieron, Auteur ; Loïc Commagnac , Auteur ; Sylvio Laventure, Auteur ; Marc Lang, Auteur ; Jean-Baptiste Féret, Auteur ; Laurence Hubert-Moy, Auteur ; Sandra Luque, Auteur
Année de publication : 2018 Projets : 3-projet - voir note / AgroParisTech (2007 -) Article en page(s) : pp 1822 - 1836 Note générale : bibliographie
The authors thank the French Ministry of Ecology, Sustainable Development and Energy (MEDDE) for partial financial supportLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Environnement
[Termes IGN] biodiversité
[Termes IGN] carte de la végétation
[Termes IGN] écosystème
[Termes IGN] habitat (nature)
[Termes IGN] image à très haute résolution
[Termes IGN] indicateur de biodiversité
[Termes IGN] phénologie
[Termes IGN] politique de conservation (biodiversité)
[Termes IGN] protection de la biodiversité
[Termes IGN] variableRésumé : (auteur) The open access availability of satellite images from new sensors characterized by various spatial and temporal resolutions provides new challenges and possibilities for biodiversity conservation. Methodologies aiming at characterizing vegetation type, phenology, and function can now benefit from metric spatial resolution imagery combined with an improved revisit capability. Here, we test hybrid methods and data fusion, using very high spatial resolution (VHSR) sensors in different complex landscapes encompassing three French biogeographical regions.
The methodological approach presented herein has a generic value in response to national conservation targets based on the concept of essential biodiversity variables accessed by remote sensing (RS‐enabled EBVs). We focused on deriving five RS‐enabled EBVs from natural and seminatural open ecosystems: (1) ecosystem distribution, (2) land cover, (3) heterogeneity, (4) primary productivity and (5) vegetation phenology. The challenge was to develop a method that would be technically feasible, economically viable, and sustainable in time.
We demonstrated that it is possible to derive key parameters required to develop a set of EBVs from remote sensing (RS) data. The combined use of remote sensing data sources with various spatial, temporal, and spectral resolutions is essential to obtain different indicators of natural habitats.
One major current challenge for an improved contribution of RS to conservation is to strengthen multiple collaborative frameworks among remote sensing scientists, conservation biologists, and ecologists in order to increase the efficiency of methodological exchange and draw benefits for successful conservation planning strategies.Numéro de notice : A2018-659 Affiliation des auteurs : IGN+Ext (2012-2019) Thématique : BIODIVERSITE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.1111/2041-210X.13033 Date de publication en ligne : 06/08/2018 En ligne : https://doi.org/10.1111/2041-210X.13033 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93817
in Methods in ecology and evolution > vol 9 n° 8 (August 2018) . - pp 1822 - 1836[article]Intra-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)
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Titre : Intra-annual phenology for detecting understory plant invasion in urban forests Type de document : Article/Communication Auteurs : Kunwar K. Singh, Auteur ; Yin-Hsuen Chen, Auteur ; Lindsey Smart, Auteur ; Josh Gray, Auteur ; Ross K. Meentemeyer, Auteur Année de publication : 2018 Article en page(s) : pp 151 - 161 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Caroline du Nord (Etats-Unis)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] densité de la végétation
[Termes IGN] détection d'anomalie
[Termes IGN] espèce exotique envahissante
[Termes IGN] flore urbaine
[Termes IGN] forêt tempérée
[Termes IGN] image Landsat-TM
[Termes IGN] indice de végétation
[Termes IGN] Ligustrum sinense
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] phénologie
[Termes IGN] protection de la biodiversité
[Termes IGN] surveillance forestièreRésumé : (Auteur) Accurate and repeatable mapping of biological plant invasions is essential to develop successful management strategies for conserving native biodiversity. While overstory invasive plants have been successfully detected and mapped using multiple methods, understory invasive detection remains a challenge, particularly in dense forested environments. Very few studies have utilized an approach that identifies and aligns the acquisition timing of remote sensing imagery with peak phenological differences between understory and overstory vegetation types. We investigated this opportunity by analyzing a monthly time-series of 2011 Landsat TM data to identify acquisition periods with the highest phenological differences between understory and overstory vegetation for detecting the spatial distribution of the exotic understory plant Ligustrum sinense Lour., a rapidly spreading invader in urbanizing regions of the southeastern United States. We used vegetation indices (VI) to establish intra-annual phenological trends for L. sinense, evergreen forest, and deciduous forest located in Mecklenburg County, North Carolina, USA. We developed Random Forest (RF) models to detect L. sinense from those time steps exhibiting the highest phenological differences. We assessed the relative contribution of VI and topographic indices (TI) to the detection of L. sinense. We compared the top performing models and used the best overall model to produce a map of L. sinense for the study area. RF models that included VI, TI, and Landsat TM bands for March 13 and 29, 2011 (the periods with highest detected phenological differences), produced the highest overall accuracy and Kappa estimates, outperforming the combination of VI and TI by 8.5% in accuracy and 20.5% in Kappa. The top performing model from the RF produced a Kappa of 0.75. Our findings suggest that selecting remote sensing data for a period when phenological differences between L. sinense and forest types are at their peak can improve the detection and mapping of L. sinense. Numéro de notice : A2018-293 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.023 Date de publication en ligne : 15/06/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90411
in ISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 151 - 161[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2018081 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018083 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018082 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Mapping 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)
PermalinkA comparative analysis of the NDVIg and NDVI3g in monitoring vegetation phenology changes in the Northern Hemisphere / Qing Chang in Geocarto international, vol 33 n° 1 (January 2018)
PermalinkPermalinkEvaluation of seasonal variations of remotely sensed leaf area index over five evergreen coniferous forests / Rong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
PermalinkDeveloping an integrated cloud-based spatial-temporal system for monitoring phenology / M. Cope in Ecological Informatics, vol 39 (May 2017)
PermalinkTélédétection pour l'observation des surfaces continentales, Volume 3. Observation des surfaces continentales par télédétection 1 / Nicolas Baghdadi (2017)
PermalinkA simple method for detecting phenological change from time series of vegetation index / Jin Chen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 6 (June 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)
PermalinkBRDF-corrected vegetation indices confirm seasonal pattern in greening of French Guiana's forests / Emil A. Cherrington in Revue Française de Photogrammétrie et de Télédétection, n° 211 - 212 (juillet - décembre 2015)
PermalinkExigence et cartes de vigilance climatique des chênes pédonculé, sessiles et pubescent. / Jean Lemaire in Forêt entreprise, n° 218 (septembre-octobre 2014)
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