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Estimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry / Juliana Batistoti in Remote sensing, Vol 11 n° 20 (2 October 2019)  

Public [article]  inRemote sensing > Vol 11 n° 20 (2 October 2019) . - 12 p. Titre : Estimating pasture biomass and canopy height in brazilian savanna using UAV photogrammetry Type de document : Article/Communication Auteurs : Juliana Batistoti, Auteur ; José Marcato, Auteur ; Luis Itavo, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : 12 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] biomasse [Termes descripteurs IGN] Brésil [Termes descripteurs IGN] canopée [Termes descripteurs IGN] couvert végétal [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image de drone [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] modèle numérique de surface de la canopée [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] Poaceae [Termes descripteurs IGN] point d'appui [Termes descripteurs IGN] positionnement cinématique en temps réel Résumé : (auteur) The Brazilian territory contains approximately 160 million hectares of pastures, and it is necessary to develop techniques to automate their management and increase their production. This technical note has two objectives: First, to estimate the canopy height using unmanned aerial vehicle (UAV) photogrammetry; second, to propose an equation for the estimation of biomass of Brazilian savanna (Cerrado) pastures based on UAV canopy height. Four experimental units of Panicum maximum cv. BRS Tamani were evaluated. Herbage mass sampling, height measurements, and UAV image collection were simultaneously performed. The UAVs were flown at a height of 50 m, and images were generated with a mean ground sample distance (GSD) of approximately 1.55 cm. The forage canopy height estimated by UAVs was calculated as the difference between the digital surface model (DSM) and the digital terrain model (DTM). The R2 between ruler height and UAV height was 0.80; between biomass (kg ha−1 GB—green biomass) and ruler height, 0.81; and between biomass (kg ha−1 GB) and UAV height, 0.74. UAV photogrammetry proved to be a potential technique to estimate height and biomass in Brazilian Panicum maximum cv. BRS Tamani pastures located in the endangered Brazilian savanna (Cerrado) biome Numéro de notice : A2019-556 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs11202447 date de publication en ligne : 22/10/2019 En ligne : https://doi.org/10.3390/rs11202447 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94212 [article]

Increasing precision for French forest inventory estimates using the k-NN technique with optical and photogrammetric data and model-assisted estimators / Dinesh Babu Irulappa Pillai Vijayakumar in Remote sensing, vol 11 n° 8 (August 2019)  

Public [article]  inRemote sensing > vol 11 n° 8 (August 2019) Titre : Increasing precision for French forest inventory estimates using the k-NN technique with optical and photogrammetric data and model-assisted estimators Type de document : Article/Communication Auteurs : Dinesh Babu Irulappa Pillai Vijayakumar, Auteur ; Jean-Pierre Renaud, Auteur ; François Morneau, Auteur ; Ronald E. McRoberts, Auteur ; Cédric Vega , Auteur Année de publication : 2019 Projets : DIABOLO / Packalen, Tuula Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] arbre caducifolié [Termes descripteurs IGN] classification barycentrique [Termes descripteurs IGN] feuillu [Termes descripteurs IGN] image Landsat-8 [Termes descripteurs IGN] inférence statistique [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] inventaire forestier national (données France) [Termes descripteurs IGN] modèle numérique de surface de la canopée [Termes descripteurs IGN] Orléans, forêt d' (Loiret) [Termes descripteurs IGN] photogrammétrie numérique [Termes descripteurs IGN] Pinus pinaster [Termes descripteurs IGN] Pinus sylvestris [Termes descripteurs IGN] quercus pedunculata [Termes descripteurs IGN] quercus sessiliflora [Termes descripteurs IGN] Sologne (France) [Vedettes matières IGN] Inventaire forestier Résumé : (auteur) Multisource forest inventory methods were developed to improve the precision of national forest inventory estimates. These methods rely on the combination of inventory data and auxiliary information correlated with forest attributes of interest. As these methods have been predominantly tested over coniferous forests, the present study used this approach for heterogeneous and complex deciduous forests in the center of France. The auxiliary data considered included a forest type map, Landsat 8 spectral bands and derived vegetation indexes, and 3D variables derived from photogrammetric canopy height models. On a subset area, changes in canopy height estimated from two successive photogrammetric models were also used. A model-assisted inference framework, using a k nearest-neighbors approach, was used to predict 11 field inventory variables simultaneously. The results showed that among the auxiliary variables tested, 3D metrics improved the precision of dendrometric estimates more than other auxiliary variables. Relative efficiencies (RE) varying from 2.15 for volume to 1.04 for stand density were obtained using all auxiliary variables. Canopy height changes also increased RE from 3% to 26%. Our results confirmed the importance of 3D metrics as auxiliary variables and demonstrated the value of canopy change variables for increasing the precision of estimates of forest structural attributes such as density and quadratic mean diameter. Numéro de notice : A2019-382 Thématique : FORET/IMAGERIE/MATHEMATIQUE Nature : Article DOI : 10.3390/rs11080991 date de publication en ligne : 25/04/2019 En ligne : https://doi.org/10.3390/rs11080991 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93456 [article]

RegisTree: a registration algorithm to enhance forest inventory plot georeferencing / Maryem Fadili in Annals of Forest Science [en ligne], vol 76 n° 2 (June 2019)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 76 n° 2 (June 2019) Titre : RegisTree: a registration algorithm to enhance forest inventory plot georeferencing Type de document : Article/Communication Auteurs : Maryem Fadili , Auteur ; Jean-Pierre Renaud, Auteur ; Jérôme Bock, Auteur ; Cédric Vega , Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] inventaire forestier national (données France) [Termes descripteurs IGN] modèle numérique de surface de la canopée [Termes descripteurs IGN] placette d'échantillonnage [Termes descripteurs IGN] superposition de données Résumé : (auteur) Key message : The accuracy of remote sensing-based models of forest attributes could be improved by controlling the spatial registration of field and remote sensing data. We have demonstrated the potential of an algorithm matching plot-level field tree positions with lidar canopy height models and derived local maxima to achieve a precise registration automatically. Context : The accuracy of remote sensing-based estimates of forest parameters depends on the quality of the spatial registration of the training data. Aims : This study introduces an algorithm called RegisTree to correct field plot positions by matching a spatialized field tree height map with lidar canopy height models (CHMs). Methods : RegisTree is based on a point (field positions) to surface (CHM) adjustment approach modified to ensure that at least one field tree position corresponds to CHM local maxima. Results : RegisTree has been validated with respect to positioning errors and the performance of lidar-derived estimation of plot volume. Overall, RegisTree enabled to register field plots surveyed in a range of forest conditions with a precision of 1.5 m (± 1.23 m), but a higher performance for conifer plots, and a limited efficiency in homogeneous stands, having similar heights. Improved plot positions were found to have a limited impact on volume predictions under the range of tested conditions, with a gain up to 1.3%. Conclusion : RegisTree could be used to improve the forest plot position from field surveys collected with low-grade GPS and to contribute to the development of processing chains of 3D remote sensing-based models of forest parameters. Numéro de notice : A2019-339 Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-019-0814-2 date de publication en ligne : 02/04/2019 En ligne : http://dx.doi.org/10.1007/s13595-019-0814-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93373 [article]

A local projection-based approach to individual tree detection and 3-D crown delineation in multistoried coniferous forests using high-density airborne LiDAR data / Aravind Harikumar in IEEE Transactions on geoscience and remote sensing, vol 57 n° 2 (February 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 2 (February 2019) . - pp 1168 - 1182 Titre : A local projection-based approach to individual tree detection and 3-D crown delineation in multistoried coniferous forests using high-density airborne LiDAR data Type de document : Article/Communication Auteurs : Aravind Harikumar, Auteur ; Francesca Bovolo, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2019 Article en page(s) : pp 1168 - 1182 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] arbre dominant [Termes descripteurs IGN] détection d'arbres [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] extraction de traits caractéristiques [Termes descripteurs IGN] forêt [Termes descripteurs IGN] houppier [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] modèle numérique de surface de la canopée [Termes descripteurs IGN] pinophyta [Termes descripteurs IGN] projection [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] Trente Résumé : (Auteur) Accurate crown detection and delineation of dominant and subdominant trees are crucial for accurate inventorying of forests at the individual tree level. The state-of-the-art tree detection and crown delineation methods have good performance mostly with dominant trees, whereas exhibits a reduced accuracy when dealing with subdominant trees. In this paper, we propose a novel approach to accurately detect and delineate both the dominant and subdominant tree crowns in conifer-dominated multistoried forests using small footprint high-density airborne Light Detection and Ranging data. Here, 3-D candidate cloud segments delineated using a canopy height model segmentation technique are projected onto a novel 3-D space where both the dominant and subdominant tree crowns can be accurately detected and delineated. Tree crowns are detected using 2-D features derived from the projected data. The delineation of the crown is performed at the voxel level with the help of both the 2-D features and 3-D texture information derived from the cloud segment. The texture information is modeled by using 3-D Gray Level Co-occurrence Matrix. The performance evaluation was done on a set of six circular plots for which reference data are available. The high detection and delineation accuracies obtained over the state of the art prove the performance of the proposed method. Numéro de notice : A2019-112 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2865014 date de publication en ligne : 10/09/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2865014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92452 [article]

Modelling forest canopy gaps using LiDAR-derived variables / Leighton Lombard in Geocarto international, vol 34 n° 2 ([01/02/2019])  

Public [article]  inGeocarto international > vol 34 n° 2 [01/02/2019] . - pp 179 - 193 Titre : Modelling forest canopy gaps using LiDAR-derived variables Type de document : Article/Communication Auteurs : Leighton Lombard, Auteur ; Riyad Ismael, Auteur ; Nitesh Poona, Auteur Année de publication : 2019 Article en page(s) : pp 179 - 193 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] croissance végétale [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] Eucalyptus grandis [Termes descripteurs IGN] forêt privée [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] inventaire forestier (techniques et méthodes) [Termes descripteurs IGN] modèle numérique de surface de la canopée Résumé : (auteur) Remote sensing has revolutionized forest management and has been widely employed to model canopy gaps. In this study, a canopy height model (CHM) and an intensity raster (IR) derived from light detection and ranging (LiDAR) data were used to model canopy gaps within a four-year-old Eucalyptus grandis forest using an object-based image analysis (OBIA) approach. Model thematic accuracies using the CHM, intensity raster and combined data set (CHM and IR) were all above 90%, with KHAT values ranging from 0.88 to 0.96. Independent test thematic accuracies were also above 90%, with KHAT values ranging from 0.82 to 0.91. A comparative area-based assessment yielded accuracies ranging from 70 to 90%, with the highest accuracies achieved using the combined data set. The results of this study show that using a CHM and intensity raster, and an OBIA approach, provides a viable framework to accurately detect and delineate canopy gaps within a commercial forest environment. Numéro de notice : A2019-221 Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2017.1377775 date de publication en ligne : 12/10/2017 En ligne : https://doi.org/10.1080/10106049.2017.1377775 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92739 [article]

Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest / Jing Liu in ISPRS Journal of photogrammetry and remote sensing, vol 148 (February 2019)  

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Individual tree detection and crown delineation with 3D information from multi-view satellite Images / Changlin Xiao in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)  

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A new generation of the United States National Land Cover Database : Requirements, research priorities, design, and implementation strategies / Limin Yang in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)  

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Comparison of high-density LiDAR and satellite photogrammetry for forest inventory / Grant D. Pearse in ISPRS Journal of photogrammetry and remote sensing, vol 142 (August 2018)  

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Stand-level wind damage can be assessed using diachronic photogrammetric canopy height models / Jean-Pierre Renaud in Annals of Forest Science [en ligne], vol 74 n° 4 (December 2017)  

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Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables / Sakari Tuominen in Silva fennica, vol 51 n° 5 (2017)  

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Forest canopy height estimation using satellite laser altimetry : a case study in the Western Ghats, India / S.M. Ghosh in Applied geomatics, vol 9 n° 3 (September 2017)  

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Improving Finnish multi-source national forest inventory by 3D aerial imaging / Sakari Tuominen in Silva fennica, vol 51 n° 4 (2017)

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Modeling canopy reflectance over sloping terrain based on path length correction / Gaofei Yin in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)  

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Application of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index / Titta Majasalmi in International journal of applied Earth observation and geoinformation, vol 59 (July 2017)  

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