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A greedy-based multiquadric method for LiDAR-derived ground data reduction / Chuanfa Chen in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
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Titre : A greedy-based multiquadric method for LiDAR-derived ground data reduction Type de document : Article/Communication Auteurs : Chuanfa Chen, Auteur ; Changqing Yan, Auteur ; Xuewei Cao, Auteur ; Jinyun Guo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 110 - 121 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données de terrain
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] interpolation
[Termes IGN] lissage de données
[Termes IGN] modèle numérique de surface
[Termes IGN] réductionRésumé : (auteur) A new greedy-based multiquadric method (MQ-G) has been developed to perform LiDAR-derived ground data reduction by selecting a certain amount of significant terrain points from the raw dataset to keep the accuracy of the constructed DEMs as high as possible, while maximally retaining terrain features. In the process of MQ-G, the significant terrain points were selected with an iterative process. First, the points with the maximum and minimum elevations were selected as the initial significant points. Next, a smoothing MQ was employed to perform an interpolation with the selected critical points. Then, the importance of all candidate points was assessed by interpolation error (i.e. the absolute difference between the interpolated and actual elevations). Lastly, the most significant point in the current iteration was selected and used for point selection in the next iteration. The process was repeated until the number of selected points reached a pre-set level or no point was found to have the interpolation error exceeding a user-specified accuracy tolerance. In order to avoid the huge computing cost, a new technique was presented to quickly solve the systems of MQ equations in the global interpolation process, and then the global MQ was replaced with the local one when a certain amount of critical points were selected. Four study sites with different morphologies (i.e. flat, undulating, hilly and mountainous terrains) were respectively employed to comparatively analyze the performances of MQ-G and the classical data selection methods including maximum z-tolerance (Max-Z) and the random method for reducing LiDAR-derived ground datasets. Results show that irrespective of the number of selected critical points and terrain characteristics, MQ-G is always more accurate than the other methods for DEM construction. Moreover, MQ-G has a better ability of preserving terrain feature lines, especially for the undulating and hilly terrains. Numéro de notice : A2015-693 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.01.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.01.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78327
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 110 - 121[article]Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass / Le Li in ISPRS Journal of photogrammetry and remote sensing, vol 102 (April 2015)
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Titre : Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass Type de document : Article/Communication Auteurs : Le Li, Auteur ; Qinghua Guo, Auteur ; Shengli Tao, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 198 - 208 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] biomasse forestière
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] régression linéaireRésumé : (auteur) Forests play a key role in the global carbon cycle, and forest above ground biomass (AGB) is an important indictor to the carbon storage capacity and the potential carbon pool size of a forest ecosystem. Accurate estimation of forest AGB has become increasingly important for a wide range of end-users. Although satellite remote sensing provides abundant observations to monitor forest coverage, validation of coarse-resolution AGB derived from satellite observations is difficult because of the scale mismatch between the footprints of satellite observations and field measurements. In this study, we use airborne Lidar to bridge the scale gaps between satellite-based and field-based studies, and evaluate satellite-derived indices to estimate regional forest AGB. We found that: (1) Lidar data can be used to accurately estimate forest AGB using tree height and tree quadratic height, (2) linear regression, among four tested models, achieve the best performance (R2 = 0.74; RMSE = 183.57 Mg/ha); (3) for MODIS-derived vegetation indices at varied spatial resolution (250–1000 m), accumulated NDVI, accumulated LAI, and accumulated FPAR could explain 53–74% variances of forest AGB, whereas accumulated NDVI derived from 1 km MODIS products gives higher R2 (74%) and lower RMSE (13.4 Mg/ha) than others. We conclude that Lidar data can be used to bridge the scale gap between satellite and field studies. Our results indicate that combining MODIS and Lidar data has the potential to estimate regional forest AGB. Numéro de notice : A2015-694 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2015.02.007 En ligne : https://doi.org/10.1016/j.isprsjprs.2015.02.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78328
in ISPRS Journal of photogrammetry and remote sensing > vol 102 (April 2015) . - pp 198 - 208[article]Contextual classification of point cloud data by exploiting individual 3d neigbourhoods / Martin Weinmann in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)
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Titre : Contextual classification of point cloud data by exploiting individual 3d neigbourhoods Type de document : Article/Communication Auteurs : Martin Weinmann, Auteur ; A. Schmidt, Auteur ; Clément Mallet , Auteur ; Stefan Hinz, Auteur ; Franz Rottensteiner, Auteur ; Boris Jutzi, Auteur
Année de publication : 2015 Conférence : ISPRS 2015, PIA 2015 - HRIGI 2015 Joint ISPRS conference 25/03/2015 27/03/2015 Munich Allemagne ISPRS OA Annals Article en page(s) : pp 271 - 278 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse d'image orientée objet
[Termes IGN] classification contextuelle
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] scène urbaine
[Termes IGN] semis de points
[Termes IGN] voisinage (relation topologique)
[Termes IGN] zone urbaineRésumé : (auteur) The fully automated analysis of 3D point clouds is of great importance in photogrammetry, remote sensing and computer vision. For reliably extracting objects such as buildings, road inventory or vegetation, many approaches rely on the results of a point cloud classification, where each 3D point is assigned a respective semantic class label. Such an assignment, in turn, typically involves statistical methods for feature extraction and machine learning. Whereas the different components in the processing workflow have extensively, but separately been investigated in recent years, the respective connection by sharing the results of crucial tasks across all components has not yet been addressed. This connection not only encapsulates the interrelated issues of neighborhood selection and feature extraction, but also the issue of how to involve spatial context in the classification step. In this paper, we present a novel and generic approach for 3D scene analysis which relies on (i) individually optimized 3D neighborhoods for (ii) the extraction of distinctive geometric features and (iii) the contextual classification of point cloud data. For a labeled benchmark dataset, we demonstrate the beneficial impact of involving contextual information in the classification process and that using individual 3D neighborhoods of optimal size significantly increases the quality of the results for both pointwise and contextual classification. Numéro de notice : A2015--052 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W4-271-2015 Date de publication en ligne : 11/03/2015 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W4-271-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82698
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W4 (March 2015) . - pp 271 - 278[article]Documents numériques
en open access
Contextual classification of point cloud data ... - pdf éditeurAdobe Acrobat PDFExtracting mobile objects in images using a Velodyne lidar point cloud / Bruno Vallet in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)
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Titre : Extracting mobile objects in images using a Velodyne lidar point cloud Type de document : Article/Communication Auteurs : Bruno Vallet , Auteur ; Wen Xiao, Auteur ; Mathieu Brédif
, Auteur
Année de publication : 2015 Conférence : ISPRS 2015, PIA 2015 - HRIGI 2015 Joint ISPRS conference 25/03/2015 27/03/2015 Munich Allemagne ISPRS OA Annals Article en page(s) : pp 247 - 253 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme Graph-Cut
[Termes IGN] architecture pipeline (processeur)
[Termes IGN] classification de Dempster-Shafer
[Termes IGN] détection d'objet
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] image terrestre
[Termes IGN] objet mobile
[Termes IGN] semis de points
[Termes IGN] théorie de Dempster-ShaferRésumé : (auteur) This paper presents a full pipeline to extract mobile objects in images based on a simultaneous laser acquisition with a Velodyne scanner. The point cloud is first analysed to extract mobile objects in 3D. This is done using Dempster-Shafer theory and it results in weights telling for each points if it corresponds to a mobile object, a fixed object or if no decision can be made based on the data (unknown). These weights are projected in an image acquired simultaneously and used to segment the image between the mobile and the static part of the scene. Numéro de notice : A2015-757 Affiliation des auteurs : LASTIG MATIS (2012-2019) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W4-247-2015 Date de publication en ligne : 11/03/2015 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W4-247-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78753
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W4 (March 2015) . - pp 247 - 253[article]Forest inventory attribute estimation using airborne laser scanning, aerial stereo imagery, radargrammetry and interferometry–Finnish experiences of the 3D techniques / Markus Holopainen in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 W4 (March 2015)
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Titre : Forest inventory attribute estimation using airborne laser scanning, aerial stereo imagery, radargrammetry and interferometry–Finnish experiences of the 3D techniques Type de document : Article/Communication Auteurs : Markus Holopainen, Auteur ; Mikko Vastaranta, Auteur ; Mika Karjalainen, Auteur ; et al., Auteur Année de publication : 2015 Conférence : ISPRS 2015, PIA 2015 - HRIGI 2015 Joint ISPRS conference 25/03/2015 27/03/2015 Munich Allemagne ISPRS OA Annals Article en page(s) : pp 63 - 69 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] estimation statistique
[Termes IGN] Finlande
[Termes IGN] forêt boréale
[Termes IGN] hauteur des arbres
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle numérique de surface
[Termes IGN] placette d'échantillonnage
[Termes IGN] radargrammétrie
[Termes IGN] semis de points
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Three-dimensional (3D) remote sensing has enabled detailed mapping of terrain and vegetation heights. Consequently, forest inventory attributes are estimated more and more using point clouds and normalized surface models. In practical applications, mainly airborne laser scanning (ALS) has been used in forest resource mapping. The current status is that ALS-based forest inventories are widespread, and the popularity of ALS has also raised interest toward alternative 3D techniques, including airborne and spaceborne techniques. Point clouds can be generated using photogrammetry, radargrammetry and interferometry. Airborne stereo imagery can be used in deriving photogrammetric point clouds, as very-high-resolution synthetic aperture radar (SAR) data are used in radargrammetry and interferometry. ALS is capable of mapping both the terrain and tree heights in mixed forest conditions, which is an advantage over aerial images or SAR data. However, in many jurisdictions, a detailed ALS-based digital terrain model is already available, and that enables linking photogrammetric or SAR-derived heights to heights above the ground. In other words, in forest conditions, the height of single trees, height of the canopy and/or density of the canopy can be measured and used in estimation of forest inventory attributes. In this paper, first we review experiences of the use of digital stereo imagery and spaceborne SAR in estimation of forest inventory attributes in Finland, and we compare techniques to ALS. In addition, we aim to present new implications based on our experiences. Numéro de notice : A2015-756 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprsannals-II-3-W4-63-2015 En ligne : http://dx.doi.org/10.5194/isprsannals-II-3-W4-63-2015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=78752
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol II-3 W4 (March 2015) . - pp 63 - 69[article]Characterizing stand-level forest canopy cover and height using Landsat time series, samples of airborne LiDAR, and the Random Forest algorithm / Oumer S. Ahmed in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)
PermalinkDéveloppement d'un logiciel de calcul de trajectoire pour un drone / Valerio Baiocchi in Géomatique expert, n° 103 (mars - avril 2015)
PermalinkEffects of LiDAR point density and landscape context on estimates of urban forest biomass / Kunwar K. Singh in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)
PermalinkFlexible building primitives for 3D building modeling / B. Xiong in ISPRS Journal of photogrammetry and remote sensing, vol 101 (March 2015)
PermalinkImproved area-based deformation analysis of a radio telescope’s main reflector based on terrestrial laser scanning / Christoph Holst in Journal of applied geodesy, vol 9 n° 1 (March 2015)
PermalinkModelling surface drainage patterns in altered landscapes using LiDAR / J.B. Lindsay in International journal of geographical information science IJGIS, vol 29 n° 3 (March 2015)
PermalinkSemiautomated extraction of street light poles from mobile LiDAR point-clouds / Yongtao Yu in IEEE Transactions on geoscience and remote sensing, vol 53 n° 3 (March 2015)
PermalinkA study of projections for key point based registration of panoramic terrestrial 3D laser scan / Hamidreza Houshiar in Geo-spatial Information Science, vol 18 n° 1 (March 2015)
PermalinkTree species biomass and carbon stock measurement using ground based-LiDAR / Gurveek Singh Maan in Geocarto international, vol 30 n° 3 - 4 (March - April 2015)
PermalinkValidation of terrestrial laser scanning data using conventional forest inventory methods / Taye Mengesha in European Journal of Forest Research, vol 134 n° 2 (March 2015)
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