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High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations / Linwei Yue in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 123 (January 2017) . - pp 20 - 34 Titre : High-quality seamless DEM generation blending SRTM-1, ASTER GDEM v2 and ICESat/GLAS observations Type de document : Article/Communication Auteurs : Linwei Yue, Auteur ; Huanfeng Shen, Auteur ; Liangpei Zhang, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 20 - 34 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] classification par réseau neuronal [Termes IGN] données ICEsat [Termes IGN] évaluation [Termes IGN] fusion d'images [Termes IGN] image SRTM [Termes IGN] image Terra-ASTER [Termes IGN] modèle numérique de surface [Termes IGN] modèle numérique mondial de surface [Termes IGN] Triangulated Irregular Network Résumé : (Auteur) The absence of a high-quality seamless global digital elevation model (DEM) dataset has been a challenge for the Earth-related research fields. Recently, the 1-arc-second Shuttle Radar Topography Mission (SRTM-1) data have been released globally, covering over 80% of the Earth’s land surface (60°N–56°S). However, voids and anomalies still exist in some tiles, which has prevented the SRTM-1 dataset from being directly used without further processing. In this paper, we propose a method to generate a seamless DEM dataset blending SRTM-1, ASTER GDEM v2, and ICESat laser altimetry data. The ASTER GDEM v2 data are used as the elevation source for the SRTM void filling. To get a reliable filling source, ICESat GLAS points are incorporated to enhance the accuracy of the ASTER data within the void regions, using an artificial neural network (ANN) model. After correction, the voids in the SRTM-1 data are filled with the corrected ASTER GDEM values. The triangular irregular network based delta surface fill (DSF) method is then employed to eliminate the vertical bias between them. Finally, an adaptive outlier filter is applied to all the data tiles. The final result is a seamless global DEM dataset. ICESat points collected from 2003 to 2009 were used to validate the effectiveness of the proposed method, and to assess the vertical accuracy of the global DEM products in China. Furthermore, channel networks in the Yangtze River Basin were also extracted for the data assessment. Numéro de notice : A2017-007 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.11.002 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.11.002 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83906 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017013	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017012	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Geolocation error tracking of ZY-3 three line cameras / Hongbo Pan in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 123 (January 2017) . - pp 62 - 74 Titre : Geolocation error tracking of ZY-3 three line cameras Type de document : Article/Communication Auteurs : Hongbo Pan, Auteur Année de publication : 2017 Article en page(s) : pp 62 - 74 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s) [Termes IGN] direction de visée [Termes IGN] erreur géométrique [Termes IGN] géolocalisation [Termes IGN] géométrie épipolaire [Termes IGN] image à très haute résolution [Termes IGN] image ZiYuan-3 [Termes IGN] modèle stéréoscopique [Termes IGN] point d'appui [Termes IGN] three line cameras Résumé : (Auteur) The high-accuracy geolocation of high-resolution satellite images (HRSIs) is a key issue for mapping and integrating multi-temporal, multi-sensor images. In this manuscript, we propose a new geometric frame for analysing the geometric error of a stereo HRSI, in which the geolocation error can be divided into three parts: the epipolar direction, cross base direction, and height direction. With this frame, we proved that the height error of three line cameras (TLCs) is independent of nadir images, and that the terrain effect has a limited impact on the geolocation errors. For ZY-3 error sources, the drift error in both the pitch and roll angle and its influence on the geolocation accuracy are analysed. Epipolar and common tie-point constraints are proposed to study the bundle adjustment of HRSIs. Epipolar constraints explain that the relative orientation can reduce the number of compensation parameters in the cross base direction and have a limited impact on the height accuracy. The common tie points adjust the pitch-angle errors to be consistent with each other for TLCs. Therefore, free-net bundle adjustment of a single strip cannot significantly improve the geolocation accuracy. Furthermore, the epipolar and common tie-point constraints cause the error to propagate into the adjacent strip when multiple strips are involved in the bundle adjustment, which results in the same attitude uncertainty throughout the whole block. Two adjacent strips—Orbit 305 and Orbit 381, covering 7 and 12 standard scenes separately—and 308 ground control points (GCPs) were used for the experiments. The experiments validate the aforementioned theory. The planimetric and height root mean square errors were 2.09 and 1.28 m, respectively, when two GCPs were settled at the beginning and end of the block. Numéro de notice : A2017-008 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.11.007 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.11.007 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83909 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017013	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017012	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

A hierarchical methodology for urban facade parsing from TLS point clouds / Zhuqiang Li in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 123 (January 2017) . - pp 75 - 93 Titre : A hierarchical methodology for urban facade parsing from TLS point clouds Type de document : Article/Communication Auteurs : Zhuqiang Li, Auteur ; Liqiang Zhang, Auteur ; P. Takis Mathiopoulos, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 75 - 93 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse de données [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] évaluation [Termes IGN] façade [Termes IGN] semis de points [Termes IGN] télémétrie laser terrestre [Termes IGN] zone urbaine Résumé : (Auteur) The effective and automated parsing of building facades from terrestrial laser scanning (TLS) point clouds of urban environments is an important research topic in the GIS and remote sensing fields. It is also challenging because of the complexity and great variety of the available 3D building facade layouts as well as the noise and data missing of the input TLS point clouds. In this paper, we introduce a novel methodology for the accurate and computationally efficient parsing of urban building facades from TLS point clouds. The main novelty of the proposed methodology is that it is a systematic and hierarchical approach that considers, in an adaptive way, the semantic and underlying structures of the urban facades for segmentation and subsequent accurate modeling. Firstly, the available input point cloud is decomposed into depth planes based on a data-driven method; such layer decomposition enables similarity detection in each depth plane layer. Secondly, the labeling of the facade elements is performed using the SVM classifier in combination with our proposed BieS-ScSPM algorithm. The labeling outcome is then augmented with weak architectural knowledge. Thirdly, least-squares fitted normalized gray accumulative curves are applied to detect regular structures, and a binarization dilation extraction algorithm is used to partition facade elements. A dynamic line-by-line division is further applied to extract the boundaries of the elements. The 3D geometrical façade models are then reconstructed by optimizing facade elements across depth plane layers. We have evaluated the performance of the proposed method using several TLS facade datasets. Qualitative and quantitative performance comparisons with several other state-of-the-art methods dealing with the same facade parsing problem have demonstrated its superiority in performance and its effectiveness in improving segmentation accuracy. Numéro de notice : A2017-009 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.11.008 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.11.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83910 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017013	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017012	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features / Wang Min in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 123 (January 2017) . - pp 104 - 113 Titre : Raft cultivation area extraction from high resolution remote sensing imagery by fusing multi-scale region-line primitive association features Type de document : Article/Communication Auteurs : Wang Min, Auteur ; Qi Cui, Auteur ; Wang Jie, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 104 - 113 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] agriculture [Termes IGN] analyse de données [Termes IGN] analyse multiéchelle [Termes IGN] aquaponie [Termes IGN] détection de cible [Termes IGN] extraction automatique [Termes IGN] extraction de traits caractéristiques [Termes IGN] image à haute résolution [Termes IGN] segmentation d'image Résumé : (Auteur) In this paper, we first propose several novel concepts for object-based image analysis, which include line-based shape regularity, line density, and scale-based best feature value (SBV), based on the region-line primitive association framework (RLPAF). We then propose a raft cultivation area (RCA) extraction method for high spatial resolution (HSR) remote sensing imagery based on multi-scale feature fusion and spatial rule induction. The proposed method includes the following steps: (1) Multi-scale region primitives (segments) are obtained by image segmentation method HBC-SEG, and line primitives (straight lines) are obtained by phase-based line detection method. (2) Association relationships between regions and lines are built based on RLPAF, and then multi-scale RLPAF features are extracted and SBVs are selected. (3) Several spatial rules are designed to extract RCAs within sea waters after land and water separation. Experiments show that the proposed method can successfully extract different-shaped RCAs from HR images with good performance. Numéro de notice : A2017-010 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.10.008 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.10.008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83911 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017013	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017012	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Feasibility of Terrestrial laser scanning for collecting stem volume information from single trees / Ninni Saarinen in ISPRS Journal of photogrammetry and remote sensing, vol 123 (January 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 123 (January 2017) . - pp 140 - 158 Titre : Feasibility of Terrestrial laser scanning for collecting stem volume information from single trees Type de document : Article/Communication Auteurs : Ninni Saarinen, Auteur ; Ville Kankare, Auteur ; Mikko Vastaranta, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 140 - 158 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] allométrie [Termes IGN] biomasse forestière [Termes IGN] forêt boréale [Termes IGN] modélisation [Termes IGN] semis de points [Termes IGN] télémétrie laser terrestre [Termes IGN] tronc [Termes IGN] volume en bois Résumé : (Auteur) Interest in measuring forest biomass and carbon stock has increased as a result of the United Nations Framework Convention on Climate Change, and sustainable planning of forest resources is therefore essential. Biomass and carbon stock estimates are based on the large area estimates of growing stock volume provided by national forest inventories (NFIs). The estimates for growing stock volume based on the NFIs depend on stem volume estimates of individual trees. Data collection for formulating stem volume and biomass models is challenging, because the amount of data required is considerable, and the fact that the detailed destructive measurements required to provide these data are laborious. Due to natural diversity, sample size for developing allometric models should be rather large. Terrestrial laser scanning (TLS) has proved to be an efficient tool for collecting information on tree stems. Therefore, we investigated how TLS data for deriving stem volume information from single trees should be collected. The broader context of the study was to determine the feasibility of replacing destructive and laborious field measurements, which have been needed for development of empirical stem volume models, with TLS. The aim of the study was to investigate the effect of the TLS data captured at various distance (i.e. corresponding 25%, 50%, 75% and 100% of tree height) on the accuracy of the stem volume derived. In addition, we examined how multiple TLS point cloud data acquired at various distances improved the results. Analysis was carried out with two ways when multiple point clouds were used: individual tree attributes were derived from separate point clouds and the volume was estimated based on these separate values (multiple-scan A), and point clouds were georeferenced as a combined point cloud from which the stem volume was estimated (multiple-scan B). This permitted us to deal with the practical aspects of TLS data collection and data processing for development of stem volume equations in boreal forests. The results indicated that a scanning distance of approximately 25% of tree height would be optimal for stem volume estimation with TLS if a single scan was utilized in boreal forest conditions studied here and scanning resolution employed. Larger distances increased the uncertainty, especially when the scanning distance was greater than approximately 50% of tree height, because the number of successfully measured diameters from the TLS point cloud was not sufficient for estimating the stem volume. When two TLS point clouds were utilized, the accuracy of stem volume estimates was improved: RMSE decreased from 12.4% to 6.8%. When two point clouds were processed separately (i.e. tree attributes were derived from separate point clouds and then combined) more accurate results were obtained; smaller RMSE and relative error were achieved compared to processing point clouds together (i.e. tree attributes were derived from a combined point cloud). TLS data collection and processing for the optimal setup in this study required only one sixth of time that was necessary to obtain the field reference. These results helped to further our knowledge on TLS in estimating stem volume in boreal forests studied here and brought us one step closer in providing best practices how a phase-shift TLS can be utilized in collecting data when developing stem volume models. Numéro de notice : A2017-011 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.11.012 En ligne : http://dx.doi.org/10.1016/j.isprsjprs.2016.11.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=83912 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017011	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017013	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017012	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt