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[n° ou bulletin]
est un bulletin de ISPRS Journal of photogrammetry and remote sensing / International society for photogrammetry and remote sensing (1980 -) (1990 -) 
[n° ou bulletin]
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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 |
Dépouillements
Ajouter le résultat dans votre panierMethods for quantification of systematic distance deviations under incidence angle with scanning total stations / Miriam Zámečníková in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)
Titre : Methods for quantification of systematic distance deviations under incidence angle with scanning total stations Type de document : Article/Communication Auteurs : Miriam Zámečníková, Auteur ; Hans Neuner, Auteur Année de publication : 2018 Article en page(s) : pp 268 - 284 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie
[Termes IGN] angle d'incidence
[Termes IGN] erreur systématique
[Termes IGN] Multistation
[Termes IGN] tachéomètre électronique
[Termes IGN] télémètre laser terrestreRésumé : (Auteur) If scanning total stations (TLS+TS) are used in scanning mode for high accurate engineering applications, the systematic influence of the incidence angle (IA) on the reflectorless distance measurement has to be eliminated. At present, methods for quantifying the systematic distance deviations under IA are missing because the measured points are not reproducible. In this paper, three such methods are presented. They are conditional on the used instruments and the required accuracy. These methods are validated with respect to specified framework conditions. The distance deviations are derived in all three methods as difference between the distance measured with TLS+TS in the scanning mode (DTLS) and the corresponding reference distance (Dref). The Dref is determined in three steps: measurement of a high accuracy network, measurement for determining the starting point of the Dref; object measurement to determine the endpoints of Dref. The corresponding DTLS and Dref are identified by means of the horizontal direction Hz (HzTLS and Hzref) and the vertical angle V (VTLS and Vref), both pairs of angles referring to the same origin marked by the axis of the common coordinate system. Depending on the used method, the Dref is determined with a standard uncertainty of 0.1–0.3 mm (at a distance of 30 m). The quantified influence of IA on the distance measurement of the Leica MS50 at a distance of 30 m to a granite plate varies in the interval of 0.8 mm. The strong variation due to the IA occurs from 0 to 20 gon, its effect is stable from 20 to 60 gon. Numéro de notice : A2018-391 Affiliation des auteurs : non IGN Thématique : IMAGERIE/POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.07.008 Date de publication en ligne : 03/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.07.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90825
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 268 - 284[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
Titre : Deep multi-task learning for a geographically-regularized semantic segmentation of aerial images Type de document : Article/Communication Auteurs : Michele Volpi, Auteur ; Devis Tuia, Auteur Année de publication : 2018 Article en page(s) : pp 48 - 60 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] apprentissage profond
[Termes IGN] champ aléatoire conditionnel
[Termes IGN] image aérienne
[Termes IGN] orthoimage
[Termes IGN] réseau neuronal convolutif
[Termes IGN] segmentation sémantiqueRésumé : (Auteur) When approaching the semantic segmentation of overhead imagery in the decimeter spatial resolution range, successful strategies usually combine powerful methods to learn the visual appearance of the semantic classes (e.g. convolutional neural networks) with strategies for spatial regularization (e.g. graphical models such as conditional random fields). In this paper, we propose a method to learn evidence in the form of semantic class likelihoods, semantic boundaries across classes and shallow-to-deep visual features, each one modeled by a multi-task convolutional neural network architecture. We combine this bottom-up information with top-down spatial regularization encoded by a conditional random field model optimizing the label space across a hierarchy of segments with constraints related to structural, spatial and data-dependent pairwise relationships between regions. Our results show that such strategy provide better regularization than a series of strong baselines reflecting state-of-the-art technologies. The proposed strategy offers a flexible and principled framework to include several sources of visual and structural information, while allowing for different degrees of spatial regularization accounting for priors about the expected output structures. Numéro de notice : A2018-392 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.06.007 Date de publication en ligne : 05/07/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.06.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90826
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 48 - 60[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
Titre : Stand age estimation of rubber (Hevea brasiliensis) plantations using an integrated pixel- and object-based tree growth model and annual Landsat time series Type de document : Article/Communication Auteurs : Gang Chen, Auteur ; Jean-Claude Thill, Auteur ; Sutee Anantsuksomsri, Auteur ; Nij Tontisirin, Auteur ; Ran Tao, Auteur Année de publication : 2018 Article en page(s) : pp 94 - 104 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] Birmanie
[Termes IGN] Chine
[Termes IGN] croissance des arbres
[Termes IGN] dendrochronologie
[Termes IGN] Hevea brasiliensis
[Termes IGN] image Landsat
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Laos
[Termes IGN] modèle de croissance végétale
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] plantation forestière
[Termes IGN] série temporelleRésumé : (Auteur) Rubber (Hevea brasiliensis) plantations are a rapidly increasing source of land cover change in mainland Southeast Asia. Stand age of rubber plantations obtained at fine scales provides essential baseline data, informing the pace of industrial and smallholder agricultural activities in response to the changing global rubber markets, and local political and socioeconomic dynamics. In this study, we developed an integrated pixel- and object-based tree growth model using Landsat annual time series to estimate the age of rubber plantations in a 21,115 km2 tri-border region along the junction of China, Myanmar and Laos. We produced a rubber stand age map at 30 m resolution, with an accuracy of 87.00% for identifying rubber plantations and an average error of 1.53 years in age estimation. The integration of pixel- and object-based image analysis showed superior performance in building NDVI yearly time series that reduced spectral noises from background soil and vegetation in open-canopy, young rubber stands. The model parameters remained relatively stable during model sensitivity analysis, resulting in accurate age estimation robust to outliers. Compared to the typically weak statistical relationship between single-date spectral signatures and rubber tree age, Landsat image time series analysis coupled with tree growth modeling presents a viable alternative for fine-scale age estimation of rubber plantations. Numéro de notice : A2018-399 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.07.003 Date de publication en ligne : 13/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.07.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90828
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 94 - 104[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
Titre : International benchmarking of terrestrial laser scanning approaches for forest inventories Type de document : Article/Communication Auteurs : Xinlian Liang, Auteur ; Juha Hyyppä, Auteur ; Harri Kaartinen, Auteur ; Matti Lehtomäki, Auteur ; Jiri Pyorala, Auteur ; Norbert Pfeifer, Auteur ; Markus Holopainen, Auteur ; Gabor Brolly, Auteur ; Francesco Pirotti, Auteur ; Jan Hackenberg Année de publication : 2018 Projets : DIABOLO / Packalen, Tuula Article en page(s) : pp 137 - 179 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithmique
[Termes IGN] benchmark spatial
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] état de l'art
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] lasergrammétrie
[Termes IGN] semis de points
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The last two decades have witnessed increasing awareness of the potential of terrestrial laser scanning (TLS) in forest applications in both public and commercial sectors, along with tremendous research efforts and progress. It is time to inspect the achievements of and the remaining barriers to TLS-based forest investigations, so further research and application are clearly orientated in operational uses of TLS. In such context, the international TLS benchmarking project was launched in 2014 by the European Spatial Data Research Organization and coordinated by the Finnish Geospatial Research Institute. The main objectives of this benchmarking study are to evaluate the potential of applying TLS in characterizing forests, to clarify the strengths and the weaknesses of TLS as a measure of forest digitization, and to reveal the capability of recent algorithms for tree-attribute extraction. The project is designed to benchmark the TLS algorithms by processing identical TLS datasets for a standardized set of forest attribute criteria and by evaluating the results through a common procedure respecting reliable references. Benchmarking results reflect large variances in estimating accuracies, which were unveiled through the 18 compared algorithms and through the evaluation framework, i.e., forest complexity categories, TLS data acquisition approaches, tree attributes and evaluation procedures. The evaluation framework includes three new criteria proposed in this benchmarking and the algorithm performances are investigated through combining two or more criteria (e.g., the accuracy of the individual tree attributes are inspected in conjunction with plot-level completeness) in order to reveal algorithms’ overall performance. The results also reveal some best available forest attribute estimates at this time, which clarify the status quo of TLS-based forest investigations. Some results are well expected, while some are new, e.g., the variances of estimating accuracies between single-/multi-scan, the principle of the algorithm designs and the possibility of a computer outperforming human operation. With single-scan data, i.e., one hemispherical scan per plot, most of the recent algorithms are capable of achieving stem detection with approximately 75% completeness and 90% correctness in the easy forest stands (easy plots: 600 stems/ha, 20 cm mean DBH). The detection rate decreases when the stem density increases and the average DBH decreases, i.e., 60% completeness with 90% correctness (medium plots: 1000 stem/ha, 15 cm mean DBH) and 30% completeness with 90% correctness (difficult plots: 2000 stems/ha, 10 cm mean DBH). The application of the multi-scan approach, i.e., five scans per plot at the center and four quadrant angles, is more effective in complex stands, increasing the completeness to approximately 90% for medium plots and to approximately 70% for difficult plots, with almost 100% correctness. The results of this benchmarking also show that the TLS-based approaches can provide the estimates of the DBH and the stem curve at a 1–2 cm accuracy that are close to what is required in practical applications, e.g., national forest inventories (NFIs). In terms of algorithm development, a high level of automation is a commonly shared standard, but a bottleneck occurs at stem detection and tree height estimation, especially in multilayer and dense forest stands. The greatest challenge is that even with the multi-scan approach, it is still hard to completely and accurately record stems of all trees in a plot due to the occlusion effects of the trees and bushes in forests. Future development must address the redundant yet incomplete point clouds of forest sample plots and recognize trees more accurately and efficiently. It is worth noting that TLS currently provides the best quality terrestrial point clouds in comparison with all other technologies, meaning that all the benchmarks labeled in this paper can also serve as a reference for other terrestrial point clouds sources. Numéro de notice : A2018-400 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.06.021 Date de publication en ligne : 24/07/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.06.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90829
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 137 - 179[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
Titre : Towards a polyalgorithm for land use change detection Type de document : Article/Communication Auteurs : Rishu Saxena, Auteur ; Layne T. Watson, Auteur ; Randolph H. Wynne, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 217 - 234 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] changement d'occupation du sol
[Termes IGN] détection de changement
[Termes IGN] série temporelleMots-clés libres : EWMACD Exponentially weighted moving average change detection LandTrendR Résumé : (Auteur) One way of analyzing satellite images for land use and land cover change (LULCC) is time series analysis (TSA). Most of the many TSA based LULCC algorithms proposed in the remote sensing community perform well on datasets for which they were designed, but their performance on randomly chosen datasets from across the globe has not been studied. A polyalgorithm combines several basic algorithms, each meant to solve the same problem, producing a strategy that unites the strengths and circumvents the weaknesses of constituent algorithms. The foundation of the proposed TSA based ‘polyalgorithm’ for LULCC is three algorithms (BFAST, EWMACD, and LandTrendR), precisely described mathematically, and chosen to be fundamentally distinct from each other in design and in the phenomena they capture. Analysis of results representing success, failure, and parameter sensitivity for each algorithm is presented. For a given pixel, Hausdorff distance is used to compare the distance between the change times (breakpoints) obtained from two different algorithms. Timesync validation data, a dataset that is based on human interpretation of Landsat time series in concert with historical aerial photography, is used for validation. The polyalgorithm yields more accurate results than EWMACD and LandTrendR alone, but counterintuitively not better than BFAST alone. This nascent work will be directly useful in land use and land cover change studies, of interest to terrestrial science research, especially regarding anthropogenic impacts on the environment. Numéro de notice : A2018-401 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.07.002 Date de publication en ligne : 27/07/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.07.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90832
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 217 - 234[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
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
Titre : A new algorithm predicting the end of growth at five evergreen conifer forests based on nighttime temperature and the enhanced vegetation index Type de document : Article/Communication Auteurs : Huanhuan Yuan, Auteur ; Chaoyang Wu, Auteur ; Linlin Lu, Auteur ; Xiaoyue Wang, Auteur Année de publication : 2018 Article en page(s) : pp 390 - 399 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Canada
[Termes IGN] croissance des arbres
[Termes IGN] Enhanced vegetation index
[Termes IGN] forêt
[Termes IGN] modèle de simulation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] nuit
[Termes IGN] Pinophyta
[Termes IGN] production primaire brute
[Termes IGN] simulation numérique
[Termes IGN] température au solRésumé : (Auteur) Accurate estimation of vegetation phenology (the start/end of growing season, SOS/EOS) is important to understand the feedbacks of vegetation to meteorological circumstances. Because the evergreen forests have limited change in greenness, there are relatively less study to predict evergreen conifer forests phenology, especially for EOS in autumn. Using 11-year (2000–2010) records of MODIS normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI), together with gross primary production (GPP) and temperature data at five evergreen conifer forests flux sites in Canada, we comprehensively evaluated the performances of several variables in modeling flux-derived EOS. Results showed that neither NDVI nor EVI can be used to predict EOS as they had no significant correlation with ground observations. In comparison, temperature had a better predictive strength for EOS, and R2 between EOS and mean temperature (Tmean), the maximum temperature (Tmax, daytime temperature) and the minimum temperature (Tmin, nighttime temperature) were 0.45 (RMSE = 5.1 days), 0.32 (RMSE = 5.7 days) and 0.58 (RMSE = 4.6 days), respectively. These results suggest an unreported role of nighttime temperature in regulating EOS of evergreen forests, in comparison with previous study showing leaf-out in spring by daytime temperature. Furthermore, we demonstrated that it may be because nighttime temperature has a higher relationship with soil temperature (Ts) (R2 = 0.67, p Numéro de notice : A2018-403 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.08.013 Date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.08.013 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90855
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 390 - 399[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
Titre : A 3D convolutional neural network method for land cover classification using LiDAR and multi-temporal Landsat imagery Type de document : Article/Communication Auteurs : Zewei Xu, Auteur ; Kaiyu Guan, Auteur ; Nathan Casler, Auteur ; Bin Peng, Auteur ; Shaowen Wang, Auteur Année de publication : 2018 Article en page(s) : pp 423 - 434 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] Illinois (Etats-Unis)
[Termes IGN] image Landsat
[Termes IGN] image multitemporelle
[Termes IGN] réseau neuronal convolutif
[Termes IGN] semis de pointsRésumé : (Auteur) Terrestrial landscape has complex three-dimensional (3D) features that are difficult to extract using traditional methods based on 2D representations. These methods often relegate such features to raster or metric-based (two-dimensional) representations based on Digital Surface Models (DSM) or Digital Elevation Models (DEM), and thus are not suitable for resolving morphological and intensity features for fine-scale land cover mapping. Small-footprint LiDAR provides an ideal way for capturing these 3D features. This research develops a novel method of integrating airborne LiDAR derived features and multi-temporal Landsat images to classify land cover types. We tested our approach in Williamson County, Illinois, which has diverse and mixed landscape features. Specifically, our method applied a 3D convolutional neural network (CNN) approach to extract features from LiDAR point clouds by (1) creating an occupancy grid, an intensity grid at 1-meter resolution, and then (2) normalizing and incorporating data into the 3D CNN. The extracted features (e.g., morphological and intensity features) from the 3D CNN were finally combined with multi-temporal spectral data to enhance the performance of land cover classification based on a Support Vector Machine classifier. Visual interpretation from both hyper-resolution photos and point clouds was used for training and preparation of testing data. The classification results show that our method outperforms a traditional method by 2.65% (from 81.52% to 84.17%) when solely using LiDAR and 2.19% (from 90.20% to 92.57%) when combining all available imageries. We demonstrate that our method can effectively extract LiDAR features and improve fine-scale land cover mapping through fusion of complementary types of remote sensing data. Numéro de notice : A2018-405 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.08.005 Date de publication en ligne : 22/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.08.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90859
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 423 - 434[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
Titre : A new method for 3D individual tree extraction using multispectral airborne LiDAR point clouds Type de document : Article/Communication Auteurs : Wenxia Dai, Auteur ; Yang Bisheng, Auteur ; Zhen Dong, Auteur ; Ahmed Shaker, Auteur Année de publication : 2018 Article en page(s) : pp 400 - 411 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] extraction d'arbres
[Termes IGN] forêt
[Termes IGN] houppier
[Termes IGN] Ontario (Canada)
[Termes IGN] Pinophyta
[Termes IGN] segmentation
[Termes IGN] semis de pointsRésumé : (Auteur) Characterization of individual trees is essential for many applications in forest management and ecology. Previous studies relied on single tree detection from monochromatic wavelength airborne laser scanning (ALS) systems and they focused on the use of the geometric spatial information of the point clouds (i.e., X, Y, and Z coordinates). However, there is quite often a difficulty dealing with clumped trees when only the geometric spatial information is considered. The emergence of multispectral LiDAR sensors provides a new solution for individual tree structure acquisition. The aim of this paper is to investigate the performance of multispectral ALS data for delineating individual trees which are challenging by using the monochromatic wavelength ALS system. The proposed workflow utilizes the mean shift segmentation method on different feature spaces for crown isolation. In addition, both spatial domain and multispectral domain are used to refine the under-segmentation crown segments. Ten plots (2 sets of different structural complexity) located in the dense coniferous forest area in Tobermory, Ontario, Canada are selected as experiment data. Results show that the developed method correctly detects 88% and 82% of the dominant trees with and without multispectral information, respectively. Compared with segmentation using geometric spatial information solely, the main improvements are achieved for clumped tree segment with the distinguished multispectral features. This study demonstrates that multispectral airborne laser scanning data is more capable for individual tree delineation than monochromatic wavelength laser scanning data in dealing with forests with clumped crowns in dense forests. Numéro de notice : A2018-404 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.08.010 Date de publication en ligne : 17/08/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.08.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90862
in ISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 400 - 411[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
