Centre de documentation
scientifique

Individual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data / Haijian Liu in Remote sensing of environment, vol 258 (June 2021)  

Public [article]  inRemote sensing of environment > vol 258 (June 2021) . - n° 112382 Titre : Individual tree identification using a new cluster-based approach with discrete-return airborne LiDAR data Type de document : Article/Communication Auteurs : Haijian Liu, Auteur ; Pinliang Dong, Auteur ; Changshan Wu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 112382 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse de groupement [Termes IGN] arbre (flore) [Termes IGN] détection d'arbres [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] houppier [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] modèle numérique de surface de la canopée [Termes IGN] peuplement mélangé [Termes IGN] semis de points [Termes IGN] surveillance forestière [Termes IGN] Wisconsin (Etats-Unis) Résumé : (auteur) Individual tree identification is a key step for forest surveying and monitoring. To identify individual trees with airborne LiDAR data, a local maximum (LM) filter technique is typically performed. With LM, the highest point in a filtering window is generally considered to represent the tree position. This assumption, however, has great limitations, especially for mixed forests. To address this problem, we developed a new approach, the cluster center of higher points (CCHP), for tree position detection with LiDAR data. CCHP assumes that a tree position is located at the clustering center of higher points within a spatial neighborhood, and the center can be detected by a location-based recursive algorithm. The developed CCHP method was applied to a simulated forest and then verified in two real urban forests. In comparison with the variable window-sized LM filter method and layer stacking method, CCHP successfully identified 97% of trees in the simulated forest, while only 78% and 81% of the trees were recognized by LM and layer stacking methods respectively. The average absolute and relative offsets of CCHP are 0.33 m and 6.59%, respectively, and over 80% of the detected trees have an offset of less than 10% of the tree crown radius. CCHP also correctly detected 93.80% and 88.74% of individual trees in the first and second real forests, respectively, but the detection rates from the variable window-sized LM approach and layer stacking were less than 80%. In addition, the tree positions located by CCHP are considerably more accurate than the other two methods. Therefore, CCHP is proven to be promising for detecting individual tree positions from airborne LiDAR data for both simulated and real forests. Numéro de notice : A2021-443 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112382 Date de publication en ligne : 06/03/2021 En ligne : https://doi.org/10.1016/j.rse.2021.112382 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97850 [article]

Incorporating crown shape information for identifying ash tree species / Haijian Liu in Photogrammetric Engineering & Remote Sensing, PERS, vol 84 n° 8 (août 2018)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 84 n° 8 (août 2018) . - pp 495 - 503 Titre : Incorporating crown shape information for identifying ash tree species Type de document : Article/Communication Auteurs : Haijian Liu, Auteur ; Changshan Wu, Auteur Année de publication : 2018 Article en page(s) : pp 495 - 503 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] Fraxinus (genre) [Termes IGN] fusion de données [Termes IGN] hauteur des arbres [Termes IGN] houppier [Termes IGN] image aérienne [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] Milwaukee [Termes IGN] photo-interprétation assistée par ordinateur [Termes IGN] zone urbaine Résumé : (Auteur) Identifying ash trees from other common deciduous trees is challenging due to subtle spectral differences of foliage among species. Although many researchers have integrated lidar-derived tree height and crown size metrics to improve tree species classification accuracy, these simple biophysical attributes provide inadequate explanatory power in distinguishing ash trees (Fraxinus, spp.) in urban ecosystems. To address this issue, shape-related features, including crown shape index (SI) and coefficient of variation (CV) of crown height, were extracted from lidar data, and fused with treetopbased spectra for ash tree species identification in Milwaukee City, Wisconsin, United States. Analysis results indicate shape features including SI and CV play a big role in improving the accuracy for ash tree identification. Specifically, Fusion of CV and treetop-based spectra improved the overall accuracy from 81.9 percent to 89 percent, and McNemar tests indicated the differences in accuracy between CV fusion and tree height fusion was statistically significant (p = 0.016). Numéro de notice : A2018-360 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.84.8.495 Date de publication en ligne : 01/08/2018 En ligne : https://doi.org/10.14358/PERS.84.8.495 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90600 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2018081	RAB	Revue	Centre de documentation	En réserve L003	Disponible

The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques / Chengbin Deng in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 100 - 110 Titre : The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques Type de document : Article/Communication Auteurs : Chengbin Deng, Auteur ; Changshan Wu, Auteur Année de publication : 2013 Article en page(s) : pp 100 - 110 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse de mélange spectral d’extrémités multiples [Termes IGN] analyse des mélanges spectraux [Termes IGN] apprentissage automatique [Termes IGN] image multibande [Termes IGN] image Terra-MODIS [Termes IGN] méthode des moindres carrés [Termes IGN] surface imperméable [Termes IGN] zone urbaine Résumé : (Auteur) Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available. Numéro de notice : A2013-705 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32841 [article]

Development of a Coordinate Transformation method for direct georeferencing in map projection frames / Haitao Zhao in ISPRS Journal of photogrammetry and remote sensing, vol 77 (March 2013)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 77 (March 2013) . - pp 94 - 103 Titre : Development of a Coordinate Transformation method for direct georeferencing in map projection frames Type de document : Article/Communication Auteurs : Haitao Zhao, Auteur ; Bing Zhang, Auteur ; Changshan Wu, Auteur ; et al., Auteur Année de publication : 2013 Article en page(s) : pp 94 - 103 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] géoréférencement direct [Termes IGN] GPS-INS [Termes IGN] orientation du capteur [Termes IGN] transformation de coordonnées Résumé : (Auteur) This paper develops a novel Coordinate Transformation method (CT-method), with which the orientation angles (roll, pitch, heading) of the local tangent frame of the GPS/INS system are transformed into those (omega, phi, kappa) of the map projection frame for direct georeferencing (DG). Especially, the orientation angles in the map projection frame were derived from a sequence of coordinate transformations. The effectiveness of orientation angles transformation was verified through comparing with DG results obtained from conventional methods (Legat method1 and POSPac method2) using empirical data. Moreover, the CT-method was also validated with simulated data. One advantage of the proposed method is that the orientation angles can be acquired simultaneously while calculating position elements of exterior orientation (EO) parameters and auxiliary points coordinates by coordinate transformation. These three methods were demonstrated and compared using empirical data. Empirical results show that the CT-method is both as sound and effective as Legat method. Compared with POSPac method, the CT-method is more suitable for calculating EO parameters for DG in map projection frames. DG accuracy of the CT-method and Legat method are at the same level. DG results of all these three methods have systematic errors in height due to inconsistent length projection distortion in the vertical and horizontal components, and these errors can be significantly reduced using the EO height correction technique in Legat’s approach. Similar to the results obtained with empirical data, the effectiveness of the CT-method was also proved with simulated data. Numéro de notice : A2013-118 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.12.004 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.12.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32256 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2013031	RAB	Revue	Centre de documentation	En réserve L003	Disponible