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Drought stress detection in juvenile oilseed rape using hyperspectral imaging with a focus on spectra variability / Wiktor R. Żelazny in Remote sensing, vol 12 n° 20 (October 2020)  

Public [article]  inRemote sensing > vol 12 n° 20 (October 2020) . - 27 p. Titre : Drought stress detection in juvenile oilseed rape using hyperspectral imaging with a focus on spectra variability Type de document : Article/Communication Auteurs : Wiktor R. Żelazny, Auteur ; Jan Lukáš, Auteur Année de publication : 2020 Article en page(s) : 27 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Brassica napus subsp. napus [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] classification pixellaire [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] indice de végétation [Termes descripteurs IGN] modèle linéaire [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] sécheresse [Termes descripteurs IGN] segmentation d'image [Termes descripteurs IGN] stress hydrique Résumé : (auteur) Hyperspectral imaging (HSI) has been gaining recognition as a promising proximal and remote sensing technique for crop drought stress detection. A modelling approach accounting for the treatment effects on the stress indicators’ standard deviations was applied to proximal images of oilseed rape—a crop subjected to various HSI studies, with the exception of drought. The aim of the present study was to determine the spectral responses of two cultivars, `Cadeli` and `Viking’, representing distinctive water management strategies, to three types of watering regimes. Hyperspectral data cubes were acquired at the leaf level using a 2D frame camera. The influence of the experimental factors on the extent of leaf discolorations, vegetation index values, and principal component scores was investigated using Bayesian linear models. Clear treatment effects were obtained primarily for the vegetation indexes with respect to the watering regimes. The mean values of RGI, MTCI, RNDVI, and GI responded to the difference between the well-watered and water-deprived plants. The RGI index excelled among them in terms of effect strengths, which amounted to −0.96[−2.21,0.21] and −0.71[−1.97,0.49] units for each cultivar. A consistent increase in the multiple index standard deviations, especially RGI, PSRI, TCARI, and TCARI/OSAVI, was associated with worsening of the hydric regime. These increases were captured not only for the dry treatment but also for the plants subjected to regeneration after a drought episode, particularly by PSRI (a multiplicative effect of 0.33[0.16,0.68] for `Cadeli’). This result suggests a higher sensitivity of the vegetation index variability measures relative to the means in the context of the oilseed rape drought stress diagnosis and justifies the application of HSI to capture these effects. RGI is an index deserving additional scrutiny in future studies, as both its mean and standard deviation were affected by the watering regimes. Numéro de notice : A2020-656 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.3390/rs12203462 date de publication en ligne : 21/10/2020 En ligne : https://doi.org/10.3390/rs12203462 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96123 [article]

Use of Bayesian modeling to determine the effects of meteorological conditions, prescribed burn season, and tree characteristics on litterfall of pinus nigra and pinus pinaster stands / Juncal Espinosa in Forests, vol 11 n° 9 (September 2020)  

Public [article]  inForests > vol 11 n° 9 (September 2020) . - N° 1006 Titre : Use of Bayesian modeling to determine the effects of meteorological conditions, prescribed burn season, and tree characteristics on litterfall of pinus nigra and pinus pinaster stands Type de document : Article/Communication Auteurs : Juncal Espinosa, Auteur ; Óscar Rodríguez de Rivera, Auteur ; Javier Madrigal, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : N° 1006 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] classification bayesienne [Termes descripteurs IGN] données météorologiques [Termes descripteurs IGN] Espagne [Termes descripteurs IGN] estimation bayesienne [Termes descripteurs IGN] incendie de forêt [Termes descripteurs IGN] intégrale de Laplace [Termes descripteurs IGN] modèle linéaire [Termes descripteurs IGN] Pinus nigra [Termes descripteurs IGN] Pinus pinaster [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Research Highlights: Litterfall biomass after prescribed burning (PB) is significantly influenced by meteorological variables, stand characteristics, and the fire prescription. Some of the fire-adaptive traits of the species under study (Pinus nigra and Pinus pinaster) mitigate the effects of PB on litterfall biomass. The Bayesian approach, tested here for the first time, was shown to be useful for analyzing the complex combination of variables influencing the effect of PB on litterfall. Background and Objectives: The aims of the study focused on explaining the influence of meteorological conditions after PB on litterfall biomass, to explore the potential influence of stand characteristic and tree traits that influence fire protection, and to assess the influence of fire prescription and fire behavior. Materials and Methods: An experimental factorial design including three treatments (control, spring, and autumn burning), each with three replicates, was established at two experimental sites (N = 18; 50 × 50 m2 plots). The methodology of the International Co-operative Program on Assessment and Monitoring of Air Pollution Effects on Forests (ICP forests) was applied and a Bayesian approach was used to construct a generalized linear mixed model. Results: Litterfall was mainly affected by the meteorological variables and also by the type of stand and the treatment. The effects of minimum bark thickness and the height of the first live branch were random. The maximum scorch height was not high enough to affect the litterfall. Time during which the temperature exceeded 60 °C (cambium and bark) did not have an important effect. Conclusions: Our findings demonstrated that meteorological conditions were the most significant variables affecting litterfall biomass, with snowy and stormy days having important effects. Significant effects of stand characteristics (mixed and pure stand) and fire prescription regime (spring and autumn PB) were shown. The trees were completely protected by a combination of low-intensity PB and fire-adaptive tree traits, which prevent direct and indirect effects on litterfall. Identification of important variables can help to improve PB and reduce the vulnerability of stands managed by this method. Numéro de notice : A2020-753 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f11091006 date de publication en ligne : 18/09/2020 En ligne : https://doi.org/10.3390/f11091006 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96433 [article]

Recognizing linear building patterns in topographic data by using two new indices based on Delaunay triangulation / Xianjin He in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 14 p. Titre : Recognizing linear building patterns in topographic data by using two new indices based on Delaunay triangulation Type de document : Article/Communication Auteurs : Xianjin He, Auteur ; Min Deng, Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] adjacence [Termes descripteurs IGN] direction [Termes descripteurs IGN] discontinuité [Termes descripteurs IGN] données topographiques [Termes descripteurs IGN] modèle linéaire [Termes descripteurs IGN] modèle numérique du bâti [Termes descripteurs IGN] reconnaissance de formes [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] triangulation de Delaunay [Termes descripteurs IGN] voisinage (topologie) Résumé : (auteur) Building pattern recognition is fundamental to a wide range of downstream applications, such as urban landscape evaluation, social analyses, and map generalization. Although many studies have been conducted, there is still a lack of satisfactory results, due to the imprecision of the relative direction model of any two adjacent buildings and the ineffective extraction methods. This study aims to provide an alternative for quantifying the direction and the spatial continuity of any two buildings on the basis of the Delaunay triangulation for the recognition of linear building patterns. First, constrained Delaunay triangulations (CDTs) are created for all buildings within each block and every two adjacent buildings. Then, the spatial continuity index (SCI), the direction index (DI), and other spatial relations (e.g., distance) of every two adjacent buildings are derived using the CDT. Finally, the building block is modelled as a graph based on derived matrices, and a graph segmentation approach is proposed to extract linear building patterns. In the segmentation process, the edges of the graph are removed first, according to the global thresholds of the SCI and distance, and are subsequently subdivided into subgraphs on direction rules. The proposed method is tested using three datasets. The experimental results suggest that the proposed method can recognize both collinear and curvilinear building patterns, given that the correctness values are all above 92% for the three study areas. The results also demonstrate that the novel SCI can effectively filter many insignificant neighbor relationships in the graph segmentation process. It is noteworthy that the proposed DI is capable of measuring building relative directions accurately and works efficiently in linear building pattern extraction. Numéro de notice : A2020-267 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040231 date de publication en ligne : 09/04/2020 En ligne : https://doi.org/10.3390/ijgi9040231 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95031 [article]

On the detectability of mis-modeled biases in the network-derived positioning corrections and their user impact / Amir Khodabandeh in GPS solutions, vol 23 n° 3 (July 2019)  

Public [article]  inGPS solutions > vol 23 n° 3 (July 2019) Titre : On the detectability of mis-modeled biases in the network-derived positioning corrections and their user impact Type de document : Article/Communication Auteurs : Amir Khodabandeh, Auteur ; Jinling Wang, Auteur ; Chris Rizos, Auteur ; Ahmed El-Mowafy, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes descripteurs IGN] correction [Termes descripteurs IGN] filtre de Kalman [Termes descripteurs IGN] inférence statistique [Termes descripteurs IGN] intégrité des données [Termes descripteurs IGN] modèle linéaire [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] positionnement par GNSS [Termes descripteurs IGN] positionnement ponctuel précis [Termes descripteurs IGN] précision du positionnement [Termes descripteurs IGN] Receiver Autonomous Integrity Monitoring [Termes descripteurs IGN] traitement de données GNSS Résumé : (auteur) High-precision single-receiver positioning requires the provision of reliable network-derived corrections. Care must therefore be exercised to continuously check the quality of the corrections and to detect the possible presence of mis-modeled biases in the network data. In network-RTK or its state-space implementation, PPP-RTK, quality control of the solutions is executed in two separate phases: the network component and the user component. Once confidence in the network-derived solutions is declared, a subset of the solutions is sent as corrections to a single-receiver user, thereby allowing the user to separately check the integrity of his network-aided model. In such a two-step integrity monitoring procedure, an intermediate step is missing, the integrity monitoring of the corrections themselves. It is the goal of this contribution to provide a quality control procedure for GNSS parameter solutions at the correction level, and to measure the impact a missed detection bias has on the (ambiguity-resolved) user position. New detection test statistics are derived with which the single-receiver user can check the overall validity of the corrections even before applying them to his data. A small-scale network of receivers is utilized to provide numerical insights into the detectability of mis-modeled biases using the proposed detectors and to analyze the impact of such biases on the user positioning performance. Numéro de notice : A2019-195 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-019-0863-x date de publication en ligne : 14/05/2019 En ligne : https://doi.org/10.1007/s10291-019-0863-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92649 [article]

Atmospheric artifacts correction with a covariance-weighted linear model over mountainous regions / Zhongbo Hu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 56 n° 12 (December 2018) . - pp 6995 - 70008 Titre : Atmospheric artifacts correction with a covariance-weighted linear model over mountainous regions Type de document : Article/Communication Auteurs : Zhongbo Hu, Auteur ; Hongdong Fan, Auteur ; Jordi J. Mallorquí, Auteur Année de publication : 2018 Article en page(s) : pp 6995 - 70008 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] correction atmosphérique [Termes descripteurs IGN] image Sentinel-SAR [Termes descripteurs IGN] interferométrie différentielle [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] matrice de covariance [Termes descripteurs IGN] modèle linéaire [Termes descripteurs IGN] montagne [Termes descripteurs IGN] retard troposphérique [Termes descripteurs IGN] Tenerife [Termes descripteurs IGN] variogramme Résumé : (auteur) Mitigating the atmospheric phase delay is one of the largest challenges faced by the differential synthetic aperture radar (SAR) interferometry community. Recently, many publications have studied correcting the stratified tropospheric phase delay by assuming a linear model between them and the topography. However, most of these studies have not considered the effect of turbulent atmospheric artifacts when adjusting the linear model to data. In this paper, we present an improved technique that minimizes the influence of the turbulent atmosphere in the model adjustment. In the proposed algorithm, the model is adjusted to the phase differences of pixels instead of using the unwrapped phase of each pixel. In addition, the different phase differences are weighted as a function of its atmospheric phase screen covariance estimated from an empirical variogram to reduce, in the model adjustment, the impact of pixel pairs with a significant turbulent atmosphere. The good performance of the proposed method has been validated with both the simulated and real Sentinel-1A SAR data in the mountainous area of Tenerife island, Spain. Numéro de notice : A2018- 553 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2846885 date de publication en ligne : 17/07/2018 En ligne : http://dx.doi.org/ 10.1109/TGRS.2018.2846885 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91652 [article]

Models 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)  

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A two-stage estimation method with bootstrap inference for semi-parametric geographically weighted generalized linear models / Dengkui Li in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)  

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Unsupervised detection of ruptures in spatial relationships in video sequences based on log‑likelihood ratio / Abdalbassir Abou-Elailah in Pattern Analysis and Applications, vol 21 n° 3 (August 2018)  

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A typification method for linear pattern in urban building generalisation / Xianyong Gong in Geocarto international, vol 33 n° 2 (February 2018)  

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How does spatial scale affect species richness modelling? A test using remote sensing data and geostatistics / M. Marcantonio in Annali di Botanica, vol 7 (2017)  

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Traitement de données LiDAR pour la modélisation d'indicateurs de biodiversité forestière / Sylvain Jourdana (2017) 

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Apport de la prise en compte de la variabilité intra-classe dans les méthodes de démélange hyperspectral pour l'imagerie urbaine / Charlotte Revel (2016)  

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Eléments de géodésie et de la théorie des moindres carrés / Abdelmajid Ben Hadj Salem (février 2016) 

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A multilinear mixing model for nonlinear spectral unmixing / Rob Heylen in IEEE Transactions on geoscience and remote sensing, vol 54 n° 1 (January 2016)  

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Comparison of linear mixed effects model and generalized model of the tree height-diameter relationship / Z. Adamec in Journal of forest science, vol 61 n° 10 (October 2015)  

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