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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 Analyzing 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)
[article]
Titre : Analyzing the vertical distribution of crown material in mixed stand composed of two temperate tree species Type de document : Article/Communication Auteurs : Olivier Martin-Ducup, Auteur ; Robert Schneider, Auteur ; Richard A. Fournier, Auteur Année de publication : 2018 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Abies balsamea
[Termes IGN] Acer saccharum
[Termes IGN] densité du feuillage
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] écologie forestière
[Termes IGN] feuille (végétation)
[Termes IGN] houppier
[Termes IGN] voxelRésumé : (Auteur) The material distribution inside tree crowns is difficult to quantify even though it is an important variable in forest management and ecology. The vertical distribution of a relative density index (i.e., vertical profile) of the total, woody, and leafy material at the crown scale were estimated from terrestrial laser scanner (TLS) data on two species, sugar maple (Acer saccharum Marsh.) and balsam fir (Abies Balsamea Mill.). An algorithm based on a geometrical approach readily available in the Computree open source platform was used. Beta distributions were then fitted to the vertical profiles and compared to each other. Total and leafy profiles had similar shapes, while woody profiles were different. Thus, the total vertical distribution could be a good proxy for the leaf distribution in the crown. Sugar maple and balsam fir had top heavy and bottom heavy distributions respectively, which can be explained by their respective architectural development. Moreover, the foliage distribution of sugar maples shifted towards the crown base when it was found in mixed stands, when compared to pure stands. The opposite behavior was observed for balsam firs, but less pronounced. According to the shape of the foliage distribution, sugar maple takes advantages from mixture contrarily to balsam fir. From a methodological point of view, we proposed an original approach to separate wood from leaf returns in TLS data while taking into account occlusion. Wood and leaf separation and occlusion problems are two challenging issues for most TLS-based studies in forest ecology. Numéro de notice : A2018-487 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f9110673 Date de publication en ligne : 26/10/2018 En ligne : https://doi.org/10.3390/f9110673 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91223
in Forests > vol 9 n° 11 (November 2018)[article]Estimating 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)
[article]
Titre : Estimating the leaf area of an individual tree in urban areas using terrestrial laser scanner and path length distribution model Type de document : Article/Communication Auteurs : Ronghai Hu, Auteur ; Elena Bournez, Auteur ; Shiyu Cheng, Auteur ; Hailan Jiang, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 357 - 368 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] arbre urbain
[Termes IGN] densité du feuillage
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] feuille (végétation)
[Termes IGN] longueur de trajet
[Termes IGN] semis de pointsRésumé : (Auteur) Urban leaf area measurement is crucial to properly determining the effect of urban trees on micro-climate regulation, heat island effect, building cooling, air quality improvement, and ozone formation. Previous works on the leaf area measurement have mainly focused on the stand level, although the presence of individual trees is more common than forests in urban areas. The only feasible ways for an operational non-destructive leaf area measurement, namely, optical indirect methods, are mostly limited in urban areas because light path is constantly intercepted by surrounding buildings or other objects. A terrestrial laser scanner (TLS), which can extract an individual tree by using its unique distance information, provides a possibility for indirectly measuring the leaf area index (LAI) in urban areas. However, indirect LAI measurement theory, which uses the cosine of an observation zenith angle for path-length correction, is incompatible for an individual tree because the representative projected area of LAI changes while the observation zenith angle changes, thus making the results incomparable and ambiguous. Therefore, we modified a path length distribution model for the leaf area measurement of an individual tree by replacing the traditional cosine path length correction for a continuous canopy with real path length distribution. We reconstructed the tree crown envelope from a TLS point cloud and calculated a real path length distribution through laser pulse-envelope intersections. Consequently, leaf area density was separated from the path length distribution model for leaf area calculation. Comparisons with reference measurement for an individual tree showed that the TLS-derived leaf area using the path length distribution is insensitive to the scanning resolution and agrees well with an allometric measurement with an overestimation from 5 m2 to 18 m2 (3–10%, respectively). Results from different stations are globally consistent, and using a weighted mean for different stations by sample numbers further improves the universality and efficiency of the proposed method. Further automation of the proposed method can facilitate a rapid and operational leaf area extraction of an individual tree for urban climate modeling. Numéro de notice : A2018-402 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.07.015 Date de publication en ligne : 14/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.07.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90854
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 357 - 368[article]Exemplaires(3)
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 Research 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)
[article]
Titre : Research on the estimation model of vegetation water content in halophyte leaves based on the newly developed vegetation indices Type de document : Article/Communication Auteurs : Zhe Li, Auteur ; Fei Zhang, Auteur ; Lihua Chen, Auteur ; Haiwei Zhang, Auteur ; Hsiang-Te Kung, Auteur Année de publication : 2018 Article en page(s) : pp 538 - 548 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] croissance végétale
[Termes IGN] feuille (végétation)
[Termes IGN] indice de végétation
[Termes IGN] plante halophile
[Termes IGN] Populus euphratica
[Termes IGN] signature spectrale
[Termes IGN] Sinkiang (Chine)
[Termes IGN] Tamarix (genre)
[Termes IGN] teneur en eau de la végétationRésumé : (Auteur) The vegetation water content (VWC) quantitative is useful for monitoring vegetation physiological growth. The relationship between VWC and vegetation water indices was analyzed. The optimal estimation model was established. The results show that: (1) Absorption bands primarily fell within 380 to 400 nm, 680 to 720 nm, 1420 to 1450 nm, 1900 to 1940 nm, and 2450 to 2500 nm; (2) comparing published vegetation water indices and developed vegetation indices, it showed that DVI(1712,1382), NDSI(2201,1870) and RSI(2259,1870) had a better correlation with VWC than the published vegetation water; and (3) NDSI(2201,1870) and RSI(2259,1870) performed well in estimating vegetation water content, DVI(1712,1382) had a rough estimate of its water content. Moreover, the linear combination of DVI(1712,1382), NDSI(2201,1870) and RSI(2259,1870) improved the estimation of VWC. The best vegetation indices for estimating VWC were found to be the linear combination of DVI(1712,1382), NDSI(2201,1870) and RSI(2259,1870) in arid area of northwestern China. Numéro de notice : A2018-361 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.9.537 Date de publication en ligne : 01/09/2018 En ligne : https://doi.org/10.14358/PERS.84.9.537 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90672
in Photogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 9 (September 2018) . - pp 538 - 548[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2018091 RAB Revue Centre de documentation En réserve L003 Disponible Detecting 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)
[article]
Titre : Detecting newly grown tree leaves from unmanned-aerial-vehicle images using hyperspectral target detection techniques Type de document : Article/Communication Auteurs : Chinsu Lin, Auteur ; Shih-Yu Chen, Auteur ; Chia-Chun Chen, Auteur ; Chia-Huei Tai, Auteur Année de publication : 2018 Article en page(s) : pp 174 - 189 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse d'image orientée objet
[Termes IGN] changement climatique
[Termes IGN] croissance des arbres
[Termes IGN] drone
[Termes IGN] feuille (végétation)
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] image RVB
[Termes IGN] indice de végétation
[Termes IGN] Kappa de Cohen
[Termes IGN] Taïwan
[Vedettes matières IGN] Végétation et changement climatiqueRésumé : (auteur) Phenological events of tree leaves from initiation to senescence is generally influenced by temperature and water availability. Detection of newly grown leaves (NGL) is useful in the diagnosis of growth of trees, tree stress and even climatic change. Utilizing very high resolution UAV images, this paper examines the feasibility of NGL detection using hyperspectral detection algorithms and anomaly detectors. The issues of pixel resolution and hard decision thresholding in deriving accurate NGL maps are also explored. Results showed that the blind-detection algorithms RXDs are not suitable for NGL detection due to the spectra similarity between NGL and both mature leaves and grass, while brighter pixels, such as those produced by soil and concrete materials, are more easily recognized as anomaly in contrast to forest. Matching filter (MF) based detectors are, however, able to accurately detect NGL over forest stands and are even more effective in the sense of achieving satisfactory true positives and true negatives while providing minimal false alarms. Of the tested partial knowledge MF algorithms, the covariance matched filter based distance (KMFD) detector performed very well with overall accuracy (OA) 0.97 and kappa coefficient () 0.60 on a natural resolution of 6.75 cm image. When a variety of mature-leaf nonobjective targets are included in the detection, the orthogonal subspace projector (OSP) tends to suppress NGL pixels as an unwanted signature and this leads to poor detection. Conversely, the target constrained interference minimized filter (TCIMF) detector is still able to effectively detect NGL with a satisfactory OA and through effective matching filter of the target signature as the hard-decision threshold is subject to a level of 5% or 1% probability of false alarms. From decimeter resolution satellite images, the KMFD and TCIMF detectors are capable of achieving an accuracy of OA = 0.94 and = 0.56 or OA = 0.87 and = 0.48 for images with a resolution of 33.75 cm or 67.50 cm respectively. This indicates that hyperspectral target detection techniques have great potential in NGL detection via high spatial resolution satellite multispectral images. Numéro de notice : A2018-294 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.05.022 Date de publication en ligne : 15/06/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.05.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90412
in ISPRS Journal of photogrammetry and remote sensing > vol 142 (August 2018) . - pp 174 - 189[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 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)PermalinkVariance of light-related foliar traits across spatial and temporal scales in the Mediterranean evergreen Olea europaea L. / Adrián G. Escribano-Rocafort in Perspectives in Plant Ecology, Evolution and Systematics, vol 28 (October 2017)PermalinkEvaluation 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)PermalinkCharacterizing vegetation canopy structure using airborne remote sensing data / Debsunder Dutta in IEEE Transactions on geoscience and remote sensing, vol 55 n° 2 (February 2017)PermalinkExamining view angle effects on leaf N estimation in wheat using field reflectance spectroscopy / Xiao Song in ISPRS Journal of photogrammetry and remote sensing, vol 122 (December 2016)PermalinkMultisensor and multispectral Lidar characterization and classification of a forest environment / Christopher Hopkinson in Canadian journal of remote sensing, vol 42 n° 5 ([01/05/2016])PermalinkLaser scanning based growth analysis of plants as a new challenge for deformation monitoring / Jan Dupuis in Journal of applied geodesy, vol 10 n° 1 (March 2016)PermalinkChanges in thermal infrared spectra of plants caused by temperature and water stress / Maria F. Buitrago in ISPRS Journal of photogrammetry and remote sensing, vol 111 (January 2016)PermalinkMicrowave unmixing with video segmentation for inferring broadleaf and needleleaf brightness temperatures and abundances from mixed forest observations / Lingjia Gu in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)PermalinkCombining leaf physiology, hyperspectral imaging and partial least squares-regression (PLS-R) for grapevine water status assessment / Tal Rapaport in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)Permalink