ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1980 -) . vol 137Paru le : 01/03/2018 |
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Ajouter le résultat dans votre panierHarmonic regression of Landsat time series for modeling attributes from national forest inventory data / Barry T. Wilson in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
[article]
Titre : Harmonic regression of Landsat time series for modeling attributes from national forest inventory data Type de document : Article/Communication Auteurs : Barry T. Wilson, Auteur ; Joseph F. Knight, Auteur ; Ronald E. McRoberts, Auteur Année de publication : 2018 Article en page(s) : pp 29 - 46 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] attribut
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Minnesota (Etats-Unis)
[Termes IGN] plus proche voisin, algorithme du
[Termes IGN] régression harmonique
[Termes IGN] série temporelleRésumé : (Auteur) Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009–2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10–20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher. Numéro de notice : A2018-077 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.006 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89439
in ISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 29 - 46[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 3D micro-mapping : Towards assessing the quality of crowdsourcing to support 3D point cloud analysis / Benjamin Herfort in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
[article]
Titre : 3D micro-mapping : Towards assessing the quality of crowdsourcing to support 3D point cloud analysis Type de document : Article/Communication Auteurs : Benjamin Herfort, Auteur ; Bernhard Höfle, Auteur ; Carolin Klonner, Auteur Année de publication : 2018 Article en page(s) : pp 73 - 83 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] arbre (flore)
[Termes IGN] cartographie collaborative
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] données localisées des bénévoles
[Termes IGN] évaluation des données
[Termes IGN] production participative
[Termes IGN] qualité des données
[Termes IGN] semis de points
[Termes IGN] villeRésumé : (Auteur) In this paper, we propose a method to crowdsource the task of complex three-dimensional information extraction from 3D point clouds. We design web-based 3D micro tasks tailored to assess segmented LiDAR point clouds of urban trees and investigate the quality of the approach in an empirical user study. Our results for three different experiments with increasing complexity indicate that a single crowdsourcing task can be solved in a very short time of less than five seconds on average. Furthermore, the results of our empirical case study reveal that the accuracy, sensitivity and precision of 3D crowdsourcing are high for most information extraction problems. For our first experiment (binary classification with single answer) we obtain an accuracy of 91%, a sensitivity of 95% and a precision of 92%. For the more complex tasks of the second Experiment 2 (multiple answer classification) the accuracy ranges from 65% to 99% depending on the label class. Regarding the third experiment – the determination of the crown base height of individual trees – our study highlights that crowdsourcing can be a tool to obtain values with even higher accuracy in comparison to an automated computer-based approach. Finally, we found out that the accuracy of the crowdsourced results for all experiments is hardly influenced by characteristics of the input point cloud data and of the users. Importantly, the results’ accuracy can be estimated using agreement among volunteers as an intrinsic indicator, which makes a broad application of 3D micro-mapping very promising. Numéro de notice : A2018-078 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.009 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.009 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89440
in ISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 73 - 83[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery / Pablo J. Zarco-Tejada in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
[article]
Titre : Understanding the temporal dimension of the red-edge spectral region for forest decline detection using high-resolution hyperspectral and Sentinel-2a imagery Type de document : Article/Communication Auteurs : Pablo J. Zarco-Tejada, Auteur ; A. Hornero, Auteur ; Rocío Hernández-Clemente, Auteur ; P.S.A. Beck, Auteur Année de publication : 2018 Article en page(s) : pp 134 - 148 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] bande rouge
[Termes IGN] défoliation
[Termes IGN] données spatiotemporelles
[Termes IGN] image hyperspectrale
[Termes IGN] image Sentinel-MSI
[Termes IGN] modèle de transfert radiatif
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] Pinus (genre)
[Termes IGN] santé des forêts
[Termes IGN] teneur en chlorophylle des feuillesRésumé : (Auteur) The operational monitoring of forest decline requires the development of remote sensing methods that are sensitive to the spatiotemporal variations of pigment degradation and canopy defoliation. In this context, the red-edge spectral region (RESR) was proposed in the past due to its combined sensitivity to chlorophyll content and leaf area variation. In this study, the temporal dimension of the RESR was evaluated as a function of forest decline using a radiative transfer method with the PROSPECT and 3D FLIGHT models. These models were used to generate synthetic pine stands simulating decline and recovery processes over time and explore the temporal rate of change of the red-edge chlorophyll index (CI) as compared to the trajectories obtained for the structure-related Normalized Difference Vegetation Index (NDVI). The temporal trend method proposed here consisted of using synthetic spectra to calculate the theoretical boundaries of the subspace for healthy and declining pine trees in the temporal domain, defined by CItime=n/CItime=n+1 vs. NDVItime=n/NDVItime=n+1. Within these boundaries, trees undergoing decline and recovery processes showed different trajectories through this subspace. The method was then validated using three high-resolution airborne hyperspectral images acquired at 40 cm resolution and 260 spectral bands of 6.5 nm full-width half-maximum (FWHM) over a forest with widespread tree decline, along with field-based monitoring of chlorosis and defoliation (i.e., ‘decline’ status) in 663 trees between the years 2015 and 2016. The temporal rate of change of chlorophyll vs. structural indices, based on reflectance spectra extracted from the hyperspectral images, was different for trees undergoing decline, and aligned towards the decline baseline established using the radiative transfer models. By contrast, healthy trees over time aligned towards the theoretically obtained healthy baseline. The applicability of this temporal trend method to the red-edge bands of the MultiSpectral Imager (MSI) instrument on board Sentinel-2a for operational forest status monitoring was also explored by comparing the temporal rate of change of the Sentinel-2-derived CI over areas with declining and healthy trees. Results demonstrated that the Sentinel-2a red-edge region was sensitive to the temporal dimension of forest condition, as the relationships obtained for pixels in healthy condition deviated from those of pixels undergoing decline. Numéro de notice : A2018-079 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.01.017 Date de publication en ligne : 17/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.01.017 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89441
in ISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 134 - 148[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt Important LiDAR metrics for discriminating forest tree species in Central Europe / Yifang Shi in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)
[article]
Titre : Important LiDAR metrics for discriminating forest tree species in Central Europe Type de document : Article/Communication Auteurs : Yifang Shi, Auteur ; Tiejun Wang, Auteur ; Andrew K. Skidmore, Auteur ; Marco Heurich, Auteur Année de publication : 2018 Article en page(s) : pp 163 - 174 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Allemagne
[Termes IGN] arbre (flore)
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Europe centrale
[Termes IGN] forêt tempérée
[Termes IGN] morphologie mathématiqueRésumé : (Auteur) Numerous airborne LiDAR-derived metrics have been proposed for classifying tree species. Yet an in-depth ecological and biological understanding of the significance of these metrics for tree species mapping remains largely unexplored. In this paper, we evaluated the performance of 37 frequently used LiDAR metrics derived under leaf-on and leaf-off conditions, respectively, for discriminating six different tree species in a natural forest in Germany. We firstly assessed the correlation between these metrics. Then we applied a Random Forest algorithm to classify the tree species and evaluated the importance of the LiDAR metrics. Finally, we identified the most important LiDAR metrics and tested their robustness and transferability. Our results indicated that about 60% of LiDAR metrics were highly correlated to each other (|r| > 0.7). There was no statistically significant difference in tree species mapping accuracy between the use of leaf-on and leaf-off LiDAR metrics. However, combining leaf-on and leaf-off LiDAR metrics significantly increased the overall accuracy from 58.2% (leaf-on) and 62.0% (leaf-off) to 66.5% as well as the kappa coefficient from 0.47 (leaf-on) and 0.51 (leaf-off) to 0.58. Radiometric features, especially intensity related metrics, provided more consistent and significant contributions than geometric features for tree species discrimination. Specifically, the mean intensity of first-or-single returns as well as the mean value of echo width were identified as the most robust LiDAR metrics for tree species discrimination. These results indicate that metrics derived from airborne LiDAR data, especially radiometric metrics, can aid in discriminating tree species in a mixed temperate forest, and represent candidate metrics for tree species classification and monitoring in Central Europe. Numéro de notice : A2018-080 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.02.002 Date de publication en ligne : 07/02/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.02.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89442
in ISPRS Journal of photogrammetry and remote sensing > vol 137 (March 2018) . - pp 163 - 174[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2018031 RAB Revue Centre de documentation En réserve L003 Disponible 081-2018033 DEP-EXM Revue LASTIG Dépôt en unité Exclu du prêt 081-2018032 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt