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Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests / Jing Liu in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
[article]
Titre : Significant effect of topographic normalization of airborne LiDAR data on the retrieval of plant area index profile in mountainous forests Type de document : Article/Communication Auteurs : Jing Liu, Auteur ; Andrew K. Skidmore, Auteur ; Marco Heurich, Auteur ; Tiejun Wang, Auteur Année de publication : 2017 Article en page(s) : pp 77 - 87 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Allemagne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt alpestre
[Termes IGN] hauteur des arbres
[Termes IGN] lever topographique
[Termes IGN] normalisation
[Termes IGN] reliefRésumé : (Auteur) As an important metric for describing vertical forest structure, the plant area index (PAI) profile is used for many applications including biomass estimation and wildlife habitat assessment. PAI profiles can be estimated with the vertically resolved gap fraction from airborne LiDAR data. Most research utilizes a height normalization algorithm to retrieve local or relative height by assuming the terrain to be flat. However, for many forests this assumption is not valid. In this research, the effect of topographic normalization of airborne LiDAR data on the retrieval of PAI profile was studied in a mountainous forest area in Germany. Results show that, although individual tree height may be retained after topographic normalization, the spatial arrangement of trees is changed. Specifically, topographic normalization vertically condenses and distorts the PAI profile, which consequently alters the distribution pattern of plant area density in space. This effect becomes more evident as the slope increases. Furthermore, topographic normalization may also undermine the complexity (i.e., canopy layer number and entropy) of the PAI profile. The decrease in PAI profile complexity is not solely determined by local topography, but is determined by the interaction between local topography and the spatial distribution of each tree. This research demonstrates that when calculating the PAI profile from airborne LiDAR data, local topography needs to be taken into account. We therefore suggest that for ecological applications, such as vertical forest structure analysis and modeling of biodiversity, topographic normalization should not be applied in non-flat areas when using LiDAR data. Numéro de notice : A2017-639 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.08.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.08.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86992
in ISPRS Journal of photogrammetry and remote sensing > vol 132 (October 2017) . - pp 77 - 87[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2017101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017102 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017103 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt 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)
[article]
Titre : Forest canopy height estimation using satellite laser altimetry : a case study in the Western Ghats, India Type de document : Article/Communication Auteurs : S.M. Ghosh, Auteur ; M. Dev Behera, Auteur Année de publication : 2017 Article en page(s) : pp 159 - 166 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] altimétrie satellitaire par laser
[Termes IGN] données altimétriques
[Termes IGN] données ICEsat
[Termes IGN] données laser
[Termes IGN] données localisées 3D
[Termes IGN] forêt tropicale
[Termes IGN] Ghats occidentaux
[Termes IGN] hauteur des arbres
[Termes IGN] Inde
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] penteRésumé : (Auteur) Canopy height is a crucial metric required to quantify the aboveground plant biomass accurately. The study explores the data derived using Light Detection and Ranging (LiDAR) technology from GeoScience Laser Altimeter System (GLAS) aboard Ice, Cloud, and Land Elevation satellite (ICESat) to derive canopy height estimate equations in the tropical forests of the Western Ghats, India. The interpretation of LiDAR waveforms for the purpose of estimating canopy heights is not straightforward, especially over sloping terrain where vegetation and ground are found at comparable heights. Canopy height models are developed using GLAS waveform extent and terrain index, derived from ASTER digital elevation, to counter the effect of topographic relief effects in canopy height estimates over steep terrain. The model was applied to calculate tree heights for whole of the Western Ghats. Results showed that the model can estimate tree heights within the specified height range with an accuracy of more than 90% while using percent overestimation/underestimation method of validation. This shows the effectiveness of the model, especially over steep slopes, also revealing that the models were able to successfully account for the pulse broadening effect. The study highlights the development of a LiDAR-based canopy height model for tropical forest and its ability to yield better canopy height estimates especially over steep slopes. Numéro de notice : A2017-597 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s12518-017-0190-2 En ligne : https://doi.org/10.1007/s12518-017-0190-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86815
in Applied geomatics > vol 9 n° 3 (September 2017) . - pp 159 - 166[article]Safe separation distance score : a new metric for evaluating wildland firefighter safety zones using lidar / Michael J. Campbell in International journal of geographical information science IJGIS, vol 31 n° 7-8 (July - August 2017)
[article]
Titre : Safe separation distance score : a new metric for evaluating wildland firefighter safety zones using lidar Type de document : Article/Communication Auteurs : Michael J. Campbell, Auteur ; Philip E. Dennison, Auteur ; Bret W. Butler, Auteur Année de publication : 2017 Article en page(s) : pp 1448 - 1466 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte thématique
[Termes IGN] distance euclidienne
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] hauteur des arbres
[Termes IGN] incendie de forêt
[Termes IGN] protection civile
[Termes IGN] topographie locale
[Termes IGN] zone tamponRésumé : (Ateur) Safety zones are areas where firefighters can retreat to in order to avoid bodily harm when threatened by burnover or entrapment from wildland fire. At present, safety zones are primarily designated by firefighting personnel as part of daily fire management activities. Though critical to safety zone assessment, the effectiveness of this approach is inherently limited by the individual firefighter’s or crew boss’s ability to accurately and consistently interpret vegetation conditions, topography, and spatial characteristics of potential safety zones (e.g. area and geometry of a forest clearing). In order to facilitate the safety zone identification and characterization process, this study introduces a new metric for safety zone evaluation: the Safe Separation Distance Score (SSDS). The SSDS is a numerical representation of the relative suitability of a given area as a safety zone according to its size, geometry, and surrounding vegetation height. This paper describes an algorithm for calculating pixel-based and polygon-based SSDS from lidar data. SSDS is calculated for every potential safety zone within a lidar dataset covering Tahoe National Forest, California, USA. A total of 2367 potential safety zones with an SSDS ≥1 were mapped, representing areas that are suitable for fires burning in low wind and low slope conditions. The highest SSDS calculated within the study area was 9.65, a score that represents suitability in the highest wind-steepest slope conditions. Potential safety zones were clustered in space, with areas in the northern and eastern portions of the National Forest containing an abundance of safety zones while areas to the south and west were completely devoid of them. SSDS can be calculated for potential safety zones in advance of firefighting, and can allow firefighters to carefully compare and select safety zones based on their location, terrain, and wind conditions. This technique shows promise as a standard method for objectively identifying and ranking safety zones on a spatial basis. Numéro de notice : A2017-308 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1270453 En ligne : http://dx.doi.org/10.1080/13658816.2016.1270453 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85355
in International journal of geographical information science IJGIS > vol 31 n° 7-8 (July - August 2017) . - pp 1448 - 1466[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2017041 RAB Revue Centre de documentation En réserve L003 Disponible 079-2017042 RAB Revue Centre de documentation Revues en salle Disponible Determining tree height and crown diameter from high-resolution UAV imagery / Dimitrios Panagiotidis in International Journal of Remote Sensing IJRS, vol 38 n° 8-10 (April 2017)
[article]
Titre : Determining tree height and crown diameter from high-resolution UAV imagery Type de document : Article/Communication Auteurs : Dimitrios Panagiotidis, Auteur ; Azadeh Abdollahnejad, Auteur ; Peter Surový, Auteur ; Vasco Chiteculo, Auteur Année de publication : 2017 Article en page(s) : pp 2392 - 2410 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Betula pendula
[Termes IGN] hauteur des arbres
[Termes IGN] houppier
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] Larix decidua
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Picea abies
[Termes IGN] Pinus sylvestris
[Termes IGN] reconstruction 3D
[Termes IGN] séquence d'images
[Termes IGN] structure-from-motion
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Advances in computer vision and the parallel development of unmanned aerial vehicles (UAVs) allow for the extensive use of UAV in forest inventory and in indirect measurements of tree features. We used UAV-sensed high-resolution imagery through photogrammetry and Structure from Motion (SfM) to estimate tree heights and crown diameters. We reconstructed 3D structures from 2D image sequences for two study areas (25 × 25 m). Species composition for Plot 1 included Norway spruce (Picea abies L.) together with European larch (Larix decidua Mill.) and Scots pine (Pinus sylvestris L.), whereas Plot 2 was mainly Norway spruce and Scots pine together with scattered individuals of European larch and Silver birch (Betula pendula Roth.). The involved workflow used canopy height models (CHMs) for the extraction of height, the smoothing of raster images for the determination of the local maxima, and Inverse Watershed Segmentation (IWS) for the estimation of the crown diameters with the help of a geographical information system (GIS). Finally, we validated the accuracies of the two methods by comparing the UAV results with ground measurements. The results showed higher agreement between field and remote-sensed data for heights than for crown diameters based on RMSE%, which were in the range 11.42–12.62 for height and 14.29–18.56 for crown diameter. Overall, the accuracy of the results was acceptable and showed that the methods were feasible for detecting tree heights and crown diameter. Numéro de notice : A2017-683 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01431161.2016.1264028 En ligne : http://dx.doi.org/10.1080/01431161.2016.1264028 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87246
in International Journal of Remote Sensing IJRS > vol 38 n° 8-10 (April 2017) . - pp 2392 - 2410[article]Mapping spatial distribution of forest age in China / Yuan Zhang in Earth and space science, vol 4 n° 3 (March 2017)
[article]
Titre : Mapping spatial distribution of forest age in China Type de document : Article/Communication Auteurs : Yuan Zhang, Auteur ; Yitong Yao, Auteur ; Xuhui Wang, Auteur ; Yongwen Liu, Auteur ; Shilong Piao, Auteur Année de publication : 2017 Article en page(s) : pp 108 - 116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] carte forestière
[Termes IGN] Chine
[Termes IGN] Cupressaceae
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt ancienne
[Termes IGN] hauteur des arbres
[Termes IGN] incertitude des données
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] peuplement forestier
[Termes IGN] Pinophyta
[Termes IGN] Pinus massoniana
[Termes IGN] puits de carboneRésumé : (auteur) Forest stand age is a meaningful metric, which reflects the past disturbance legacy, provides guidelines for forest management practices, and is an important factor in qualifying forest carbon cycles and carbon sequestration potential. Reliable large-scale forest stand age information with high spatial resolutions, however, is difficult to obtain. In this study, we developed a top-down method to downscale the provincial statistics of national forest inventory data into 1 km stand age map using climate data and light detection and ranging-derived forest height. We find that the distribution of forest stand age in China is highly heterogeneous across the country, with a mean value of ~42.6 years old. The relatively young stand age for Chinese forests is mostly due to the large proportion of newly planted forests (0–40 years old), which are more prevailing in south China. Older forests (stand age > 60 years old) are more frequently found in east Qinghai-Tibetan Plateau and the central mountain areas of west and northeast China, where human activities are less intensive. Among the 15 forest types, forests dominated by species of , with the exception of Cunninghamia lanceolata stands, have the oldest mean stand age (136 years), whereas Pinus massoniana forests are the youngest (18 years). We further identified uncertainties associated with our forest age map, which are high in west and northeast China. Our work documents the distribution of forest stand age in China at a high resolution which is useful for carbon cycle modeling and the sustainable use of China's forest resources. Numéro de notice : A2107-277 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1002/2016EA000177 En ligne : https://doi.org/10.1002/2016EA000177 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85298
in Earth and space science > vol 4 n° 3 (March 2017) . - pp 108 - 116[article]Utilisation d’un modèle numérique de hauteur en stratification des données de l’Inventaire Forestier National / Sophie Georges (2017)PermalinkTree diversity effect on dominant height in temperate forest / Patrick Vallet in Forest ecology and management, vol 381 (1 December 2016)PermalinkAccuracy of tree geometric parameters depending on the LiDAR data density / Edyta Hadas in European journal of remote sensing, vol 49 n° 1 (2016)PermalinkA functional regression model for inventories supported by aerial laser scanner data or photogrammetric point clouds / Magnussen, Steen in Remote sensing of environment, vol 184 (October 2016)PermalinkLidar detection of individual tree size in tropical forests / António Ferraz in Remote sensing of environment, vol 183 (15 September 2016)PermalinkCHP toolkit : case study of LAIe sensitivity to discontinuity of canopy cover in fruit plantations / Karolina D. Fieber in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)PermalinkPropagating uncertainty through individual tree volume model predictions to large-area volume estimates / Ronald E. McRoberts in Annals of Forest Science, vol 73 n° 3 (September 2016)PermalinkUnsupervised classification of airborne laser scanning data to locate potential wildlife habitats for forest management planning / Jari Vauhkonen in Forestry, an international journal of forest research, vol 89 n° 4 (August 2016)PermalinkLidar imagery and InSAR for digital forestry / Benoît Saint-Onge in GIM international [en ligne], vol 30 n° 7 (July 2016)PermalinkNationwide airborne laser scanning based models for volume, biomass and dominant height in Finland / Eetu Kotivuori in Silva fennica, vol 50 n° 4 (2016)PermalinkDeveloping a dynamic growth model for maritime pine in Asturias (NW Spain): comparison with nearby regions / Manuel Arias-Rodil in Annals of Forest Science, vol 73 n° 2 (June 2016)PermalinkExpérience pratique de la réalisation du projet démonstrateur « LiDAR forestier » / Didier Canteloup in Rendez-vous techniques, n° 50 (Hiver 2016)PermalinkRelationship between landform classification and vegetation (case study: southwest of Fars province, Iran) / Marzieh Mokarram in Open geosciences, vol 8 n° 1 (January - July 2016)PermalinkUsing classification trees to predict forest structure types from LiDAR data / Chiara Torresan in Annals of forest research, vol 59 n° 2 (July - December 2016)PermalinkICESat/GLAS canopy height sensitivity inferred from Airborne Lidar / Craig Mahoney in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 5 (May 2016)PermalinkEstimating forest and woodland aboveground biomass using active and passive remote sensing / Zhuoting Wu in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 4 (April 2016)PermalinkRegional scale rain-forest height mapping using regression-kriging of spaceborne and airborne Lidar data: application on French Guiana / Ibrahim Fayad in Remote sensing, vol 8 n° 3 (March 2016)PermalinkApplication des techniques de photogrammétrie par drone à la caractérisation des ressources forestières / Jonathan Lisein (2016)PermalinkAssessment of forest canopy vertical structure with multi - scale remote sensing : from the plot to the large area / Phil Wilkes (2016)PermalinkGini coefficient predictions from airborne lidar remote sensing display the effect of management intensity on forest structure / Rubén Valbuena in Ecological indicators, vol 60 (January 2016)Permalink