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Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons / Guillaume Lassalle (2019)
Titre : Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons Type de document : Thèse/HDR Auteurs : Guillaume Lassalle, Auteur ; Arnaud Elger, Directeur de thèse ; Sophie Fabre, Directeur de thèse Editeur : Toulouse : Université Fédérale Toulouse Midi-Pyrénées Année de publication : 2019 Autre Editeur : Toulouse : Institut Supérieur de l’Aéronautique et de l’Espace Importance : 277 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse délivré par l'Institut Supérieur de l’Aéronautique et de l’Espace, spécialité : Surfaces et interfaces continentales, Hydrologie Agrosystèmes, écosystèmes et environnementLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] canopée
[Termes IGN] contamination
[Termes IGN] feuille (végétation)
[Termes IGN] hydrocarbure
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] modèle de transfert radiatif
[Termes IGN] pollution des sols
[Termes IGN] prospection pétrolière
[Termes IGN] réflectance spectrale
[Termes IGN] régression multiple
[Termes IGN] signature spectrale
[Termes IGN] surveillance de la végétationIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Oil exploration and contamination monitoring remain limited in regions covered by vegetation. Natural seepages and oil leakages due to facility failures are often masked by the foliage, making ineffective the current technologies used for detecting crude oil and petroleum products. However, the exposure of vegetation to oil affects its health and, consequently, its optical properties in the [400:2500] nm domain. This suggest being able to detect seepages and leakages indirectly, by analyzing vegetation health through its spectral reflectance. Based on this assumption, this thesis evaluates the potential of airborne hyperspectral imagery with high spatial resolution for detecting and quantifying oil contamination in vegetated regions. To achieve this, a three-step multiscale approach was adopted. The first step aimed at developing a method for detecting and characterizing the contamination under controlled conditions, by exploiting the optical properties of Rubus fruticosus L. The proposed method combines 14 vegetation indices in classification and allows detecting various oil contaminants accurately, from leaf to canopy scale. Its use under natural conditions was validated on a contaminated mud pit colonized by the same species. During the second step, a method for quantifying total petroleum hydrocarbons, based on inverting the PROSPECT model, was developed. The method exploits the pigment content of leaves, estimated from their spectral signature, for predicting the level of hydrocarbon contamination in soils accurately. The last step of the approach demonstrated the robustness of the two methods using airborne imagery. They proved performing for detecting and quantifying mud pit contamination. Another method of quantification, based on multiple regression, was proposed. At the end of this thesis, the three methods proposed were validated for use both on the field, at leaf and canopy scales, and on airborne hyperspectral images with high spatial resolution. Their performances depend however on the species, the season and the level of soil contamination. A similar approach was conducted under tropical conditions, allowing the development of a method for quantifying the contamination adapted to this context. In a perspective of operational use, an important effort is still required for extending the scope of the methods to other contexts and for anticipating their use on satellite- and drone-embedded hyperspectral sensors. Finally, the contribution of active remote sensing (radar and LiDAR) should be considered in further research, in order to overcome some of the limits specific to passive optical remote sensing. Note de contenu : General introduction
1- State-of-the-art of passive hyperspectral remote sensing for oil exploration and contamination monitoring in vegetated regions
2- Development of methods for detecting and quantifying oil contamination based on vegetation optical properties, under controlled conditions
3- Application and evaluation of the methods under natural conditions, from field scale to airborne hyperspectral imagery
General conclusionNuméro de notice : 25946 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Spécialité : Surfaces et interfaces continentales, Hydrologie Agrosystèmes, écosystèmes et environnement : Toulouse : 2019 nature-HAL : Thèse DOI : sans En ligne : http://www.theses.fr/2019ESAE0030 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96343 Exploitation de séries temporelles d'images multi-sources pour la cartographie des surfaces en eau / Filsa Bioresita (2019)
Titre : Exploitation de séries temporelles d'images multi-sources pour la cartographie des surfaces en eau Type de document : Thèse/HDR Auteurs : Filsa Bioresita, Auteur ; Anne Puissant, Directeur de thèse Editeur : Strasbourg : Université de Strasbourg Année de publication : 2019 Importance : 214 p. Format : 21 x 30 cm Note générale : Bibliographie
PhD Thesis University of Strasbourg for obtaining the degree of Doctor of the University of Strasbourg, Speciality: Geography, GeomaticsLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte
[Termes IGN] biodiversité
[Termes IGN] eau de surface
[Termes IGN] estimation bayesienne
[Termes IGN] fusion d'images
[Termes IGN] image Sentinel-MSI
[Termes IGN] image Sentinel-SAR
[Termes IGN] inondation
[Termes IGN] nutriment végétal
[Termes IGN] polarimétrie
[Termes IGN] série temporelle
[Termes IGN] service écosystémique
[Termes IGN] surveillance hydrologique
[Termes IGN] télédétection spatiale
[Termes IGN] traitement automatique de donnéesIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Les eaux de surface sont des ressources importantes pour la biosphère et l'anthroposphère. Elles favorisent la préservation des habitats, le développement de la biodiversité et le maintien des services écosystémiques en contrôlant le cycle des nutriments et le carbone à l’échelle mondiale. Elles sont essentielles à la vie quotidienne de l’homme, notamment pour l'irrigation, la consommation d’eau potable, la production hydro-électrique, etc. Par ailleurs, lors des inondations, elles peuvent présenter des dangers pour l'homme, les habitations et les infrastructures. La surveillance des changements dynamiques des eaux de surface a donc un rôle primordial pour guider les choix des gestionnaires dans le processus d’aide à la décision. L’imagerie satellitaire constitue une source de données adaptée permettant de fournir des informations sur les eaux de surface. De nos jours, la télédétection satellitaire a connu une révolution avec le lancement des satellites Sentinel-1 (Radar) et Sentinel-2 (Optique) qui disposent d’une haute fréquence de revisite et d’une résolution spatiale moyenne à élevée. Ces données peuvent fournir des séries temporelles essentielles pour apporter davantage d'informations afin d'améliorer la capacité d'observation des eaux de surface. L’exploitation de telles données massives et multi-sources pose des défis en termes d’extraction de connaissances et de processus de traitement d’images car les chaines de traitement doivent être le plus automatiques possibles. Dans ce contexte, l'objectif de ce travail de thèse est de proposer de nouvelles approches permettant de cartographier l’extension spatiales des eaux de surface et des inondations, en explorant l'utilisation unique et combinée des données Sentinel-1 et Sentinel-2. Note de contenu : 1- Introduction, research questions and objectives
2- The state of the art
3- Study area, data sets and pre-processing of Sentinel 1 & 2
4- Detection of surface water area using mono-date Sentinel 1 amplitude data
5- Detection of surface water area using time series of Sentinel 1 amplitude data and Sentinel 2 data
6- Another methods and validation on different thematic context
7- General conclusions and perspectivesNuméro de notice : 25726 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : PhD Thesis : Geography, Geomatics : Strasbourg : 2019 nature-HAL : Thèse DOI : sans En ligne : https://hal.science/hal-03618382/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94887
Titre : Growth and ecosystem services of urban trees Type de document : Monographie Auteurs : Thomas Rötzer, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 170 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-03921-593-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre urbain
[Termes IGN] climat urbain
[Termes IGN] croissance des arbres
[Termes IGN] écosystème urbain
[Termes IGN] forêt urbaine
[Termes IGN] ilot thermique urbain
[Termes IGN] paysage urbain
[Termes IGN] phénologie
[Termes IGN] puits de carbone
[Termes IGN] service écosystémique
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (éditeur) Numerous studies indicate an accelerated growth of forest trees, induced by ongoing climate change. Similar trends were recently found for urban trees in major cities worldwide. Studies frequently report about substantial effects of climate change and the urban heat island effect (UHI) on plant growth. The combined effects of increasing temperatures, changing precipitation patterns, and extended growing season lengths, in addition to increasing nitrogen deposition and higher CO2 concentrations, can increase but also reduce plant growth. Closely related to this, the multiple functions and services provided by urban trees may be modified. Urban trees generate numerous ecosystem services, including carbon storage, mitigation of the heat island effect, reduction of rainwater runoff, pollutant filtering, recreation effects, shading, and cooling. The quantity of the ecosystem services is often closely associated with the species, structure, age, and size of the tree as well as with a tree’s vitality. Therefore, greening cities, and particularly planting trees, seems to be an effective option to mitigate climate change and the UHI. The focus of this Special Issue is to underline the importance of trees as part of the urban green areas for major cities in all climate zones. Empirical as well as modeling studies of urban tree growth and their services and disservices in cities worldwide are included. Articles about the dynamics, structures, and functions of urban trees as well as the influence of climate and climate change on urban tree growth, urban species composition, carbon storage, and biodiversity are also discussed. Note de contenu : 1- Growth of abies sachalinensis along an urban gradient affected by environmental pollution in Sapporo, Japan
2- Modeling ecosystem services for park trees: Sensitivity of i-tree eco simulations to light exposure and tree species classification
3- How do tilia cordata greenspire trees cope with drought stress regarding their biomass allocation and ecosystem services?
4- Structure, diversity, and carbon stocks of the tree community of Kumasi, Ghana
5- Preferences of tourists for the service quality of Taichung Calligraphy Greenway in Taiwan
6- Mutual influences of urban microclimate and urban trees: An investigation of phenology and cooling capacity
7- The influence of individual-specific plant parameters and species composition on the
allergenic potential of urban green spaces
8- Tree vitality assessment in urban landscapes
9- Spatio-temporal patterns of urban forest basal area under China’s rapid urban expansion and greening: Implications for urban green infrastructure management
10- Urban park systems to support sustainability: The role of urban park systems in hot arid urban climatesNuméro de notice : 25961 Affiliation des auteurs : non IGN Thématique : FORET Nature : Monographie DOI : 10.3390/books978-3-03921-593-5 En ligne : https://doi.org/10.3390/books978-3-03921-593-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96506 A growth-model-driven technique for tree stem diameter estimation by using airborne LiDAR data / Claudia Paris in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)
[article]
Titre : A growth-model-driven technique for tree stem diameter estimation by using airborne LiDAR data Type de document : Article/Communication Auteurs : Claudia Paris, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2019 Article en page(s) : pp 76 - 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Alpes
[Termes IGN] analyse discriminante
[Termes IGN] croissance des arbres
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle de croissance végétale
[Termes IGN] Pinophyta
[Termes IGN] régression
[Termes IGN] structure d'un peuplement forestierRésumé : (Auteur) Diameter at breast height (DBH) is one of the most important tree parameter for forest inventory. In this paper, we present a novel method for the adaptive and the accurate DBH estimation of trees characterized by small and large stems. The method automatically discriminates among different tree growth models by means of a data-driven technique based on a clustering procedure. First, the method detects young trees belonging to the lowest forest layer by simply considering the vertical structure of the forest. Then, different clusters of mature trees that are expected to share the same growth-model are identified by analyzing the environmental factors that can affect the stem expansion (e.g., topography and forest density). For each detected growth-model cluster, a tailored regression analysis is performed to obtain accurate DBH estimation results. Experiments have been carried out in an homogeneous coniferous forest located in the Alpine mountainous scenario characterized by a complex topography and a wide range of soil fertility. The method was tested on two data sets characterized by different light detection and ranging (LiDAR) point densities and different forest properties. The results obtained demonstrate the effectiveness of having multiple regression models adapted to the different growth models. Numéro de notice : A2019-103 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2852364 Date de publication en ligne : 07/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2852364 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92409
in IEEE Transactions on geoscience and remote sensing > vol 57 n° 1 (January 2019) . - pp 76 - 92[article]Microwave indices from active and passive sensors for remote sensing applications / Emanuele Santi (2019)
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 Monitoring crops water needs at high spatio-temporal resolution by synergy of optical / thermal and radar observations / Abdelhakim Amazirh (2019)PermalinkPermalinkPermalinkCan forest structural diversity be a response to anthropogenic stress? A case study in old-growth fir Abies alba Mill. stands / Rafał Podlaski in Annals of Forest Science, vol 75 n° 4 (December 2018)PermalinkPolarization orientation angle and polarimetric SAR scattering characteristics of steep terrain / Jong-Sen Lee in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkPotential of Sentinel-1 data for monitoring temperate mixed forest phenology / Pierre-Louis Frison in Remote sensing, vol 10 n° 12 (December 2018)PermalinkWood density reduced while wood volume growth accelerated in Central European forests since 1870 / Hans Pretzsch in Forest ecology and management, vol 429 (1 December 2018)PermalinkAnalyzing the vertical distribution of crown material in mixed stand composed of two temperate tree species / Olivier Martin-Ducup in Forests, vol 9 n° 11 (November 2018)PermalinkFuzzy modelling of growth potential in forest development simulation / Damjan Strnad in Ecological Informatics, vol 48 (November 2018)PermalinkModels for diameter and height growth of Scots pine, Norway spruce and pubescent birch in drained peatland sites in Finland / Jaakko Repola in Silva fennica, vol 52 n° 5 (November 2018)PermalinkSpecies mixing effects on forest productivity : A case study at stand-, species- and tree-level in the Netherlands / Huicui Lu in Forests, vol 9 n° 11 (November 2018)PermalinkEstimating the leaf area of an individual tree in urban areas using terrestrial laser scanner and path length distribution model / Ronghai Hu in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)PermalinkEstimation of forest above-ground biomass by geographically weighted regression and machine learning with Sentinel imagery / Lin Chen in Forests, vol 9 n° 10 (October 2018)PermalinkA new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index / Huanhuan Yuan in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)PermalinkStand 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)PermalinkStrategies for climate-smart forest management in Austria / Robert Jandl in Forests, vol 9 n° 10 (October 2018)PermalinkDrought sensitiveness on forest growth in peninsular Spain and the Balearic Islands / Marina Peña-Gallardo in Forests, vol 9 n° 9 (September 2018)PermalinkEstimation of winter wheat crop growth parameters using time series Sentinel-1A SAR data / P. Kumar in Geocarto international, vol 33 n° 9 (September 2018)PermalinkResearch on the estimation model of vegetation water content in halophyte leaves based on the newly developed vegetation indices / Zhe Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 9 (September 2018)PermalinkVisible + Near Infrared spectroscopy as taxonomic tool for identifying birch species / Mulualem Tigabu in Silva fennica, vol 52 n° 4 (September 2018)PermalinkCAVIAR: 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)PermalinkDetecting newly grown tree leaves from unmanned-aerial-vehicle images using hyperspectral target detection techniques / Chinsu Lin 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)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)PermalinkEvolutionary approach for detection of buried remains using hyperspectral images / Leon Dozal in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 7 (juillet 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)PermalinkLive fuel moisture content (LFMC) time series for multiple sites and species in the French Mediterranean area since 1996 / N. Martin-St Paul in Annals of Forest Science, vol 75 n° 2 (June 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)PermalinkPost-1980 shifts in the sensitivity of boreal tree growth to North Atlantic Ocean dynamics and seasonal climate / Clémentine Ols in Global and Planetary Change, vol 165 (June 2018)PermalinkThe German Forest Strategy 2020: Target achievement control using national forest inventory results / Martin Lorenz in Annals of forest research, vol 61 n° 2 (July - December 2018)PermalinkWithin- and between-tree variation of wood density components in Pinus nigra at six sites in Portugal / Alexandra Dias in Annals of Forest Science, vol 75 n° 2 (June 2018)PermalinkManipulating tree crown structure to promote old-growth characteristics in second-growth redwood forest canopies / Stephen C. Sillett in Forest ecology and management, vol 417 (15 May 2018)PermalinkConnecting infrared spectra with plant traits to identify species / Maria F. Buitrago in ISPRS Journal of photogrammetry and remote sensing, vol 139 (May 2018)PermalinkEffect of first thinning type and age on growth, stem quality and financial performance of a Scots pine stand in Finland / Pentti Niemistö in Silva fennica, vol 52 n° 2 ([01/05/2018])PermalinkClose-range hyperspectral image analysis for the early detection of stress responses in individual plants in a high-throughput phenotyping platform / Mohd Shahrimie Mohd Asaari in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkMapping forest characteristics at fine resolution across large landscapes of the southeastern united states using NAIP imagery and FIA field plot data / John Hogland in ISPRS International journal of geo-information, vol 7 n° 4 (April 2018)PermalinkMapping spatial variability of foliar nitrogen in coffee (Coffea arabica L.) plantations with multispectral Sentinel-2 MSI data / Abel Chemura in ISPRS Journal of photogrammetry and remote sensing, vol 138 (April 2018)PermalinkRecent growth trends of black pine (Pinus nigra J.F. Arnold) in the eastern mediterranean / Ellen Janssen in Forest ecology and management, vol 412 (15 March 2018)PermalinkDynamics of diameter and height increment of Norway spruce and Scots pine in southern Finland / Harri Mäkinen in Annals of Forest Science, vol 75 n° 1 (March 2018)PermalinkClimate change risk to forests in China associated with warming / Yunhe Yin in Scientific reports, vol 8 (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)PermalinkPermalinkPermalinkMonitoring des impacts du changement climatique (ICC) sur la forêt - croissance des résineux dans un contexte de réchauffement [diaporama] / Jean-Daniel Bontemps (2018)PermalinkRealizing mitigation efficiency of European commercial forests by climate smart forestry / Rasoul Yousefpour in Scientific reports, vol 8 (2018)Permalink