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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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Titre : Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables Type de document : Article/Communication Auteurs : Sakari Tuominen, Auteur ; Andras Balazs, Auteur ; Eija Honkavaara, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique
[Termes IGN] diamètre des arbres
[Termes IGN] étalonnage radiométrique
[Termes IGN] hauteur des arbres
[Termes IGN] image aérienne
[Termes IGN] image captée par drone
[Termes IGN] image hyperspectrale
[Termes IGN] image RVB
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] peuplement forestier
[Termes IGN] photogrammétrie numérique
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Remote sensing using unmanned aerial vehicle (UAV) -borne sensors is currently a highly interesting approach for the estimation of forest characteristics. 3D remote sensing data from airborne laser scanning or digital stereo photogrammetry enable highly accurate estimation of forest variables related to the volume of growing stock and dimension of the trees, whereas recognition of tree species dominance and proportion of different tree species has been a major complication in remote sensing-based estimation of stand variables. In this study, the use of UAV-borne hyperspectral imagery was examined in combination with a high-resolution photogrammetric canopy height model in estimating forest variables of 298 sample plots. Data were captured from eleven separate test sites under weather conditions varying from sunny to cloudy and partially cloudy. Both calibrated hyperspectral reflectance images and uncalibrated imagery were tested in combination with a canopy height model based on RGB camera imagery using the k-nearest neighbour estimation method. The results indicate that this data combination allows accurate estimation of stand volume, mean height and diameter: the best relative RMSE values for those variables were 22.7%, 7.4% and 14.7%, respectively. In estimating volume and dimension-related variables, the use of a calibrated image mosaic did not bring significant improvement in the results. In estimating the volumes of individual tree species, the use of calibrated hyperspectral imagery generally brought marked improvement in the estimation accuracy; the best relative RMSE values for the volumes for pine, spruce, larch and broadleaved trees were 34.5%, 57.2%, 45.7% and 42.0%, respectively. Numéro de notice : A2017-645 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.14214/sf.7721 En ligne : https://doi.org/10.14214/sf.7721 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87000
in Silva fennica > vol 51 n° 5 (2017)[article]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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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]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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Titre : Improving Finnish multi-source national forest inventory by 3D aerial imaging Type de document : Article/Communication Auteurs : Sakari Tuominen, Auteur ; Timo P Pitkänen, Auteur ; Andras Balazs, Auteur ; et al., Auteur Année de publication : 2017 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] classification barycentrique
[Termes IGN] corrélation automatique de points homologues
[Termes IGN] distribution spatiale
[Termes IGN] Finlande
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] photogrammétrie numérique
[Termes IGN] placette d'échantillonnage
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Optical 2D remote sensing techniques such as aerial photographing and satellite imaging have been used in forest inventory for a long time. During the last 15 years, airborne laser scanning (ALS) has been adopted in many countries for the estimation of forest attributes at stand and sub-stand levels. Compared to optical remote sensing data sources, ALS data are particularly well-suited for the estimation of forest attributes related to the physical dimensions of trees due to its 3D information. Similar to ALS, it is possible to derive a 3D forest canopy model based on aerial imagery using digital aerial photogrammetry. In this study, we compared the accuracy and spatial characteristics of 2D satellite and aerial imagery as well as 3D ALS and photogrammetric remote sensing data in the estimation of forest inventory variables using k-NN imputation and 2469 National Forest Inventory (NFI) sample plots in a study area covering approximately 5800 km2. Both 2D data were very close to each other in terms of accuracy, as were both the 3D materials. On the other hand, the difference between the 2D and 3D materials was very clear. The 3D data produce a map where the hotspots of volume, for instance, are much clearer than with 2D remote sensing imagery. The spatial correlation in the map produced with 2D data shows a lower short-range correlation, but the correlations approach the same level after 200 meters. The difference may be of importance, for instance, when analyzing the efficiency of different sampling designs and when estimating harvesting potential. Numéro de notice : A2017-646 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article En ligne : https://doi.org/10.14214/sf.7743 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=87003
in Silva fennica > vol 51 n° 4 (2017)[article]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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Titre : Modeling canopy reflectance over sloping terrain based on path length correction Type de document : Article/Communication Auteurs : Gaofei Yin, Auteur ; Ainong Li, Auteur ; Wei Zhao, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 4597 - 4609 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] distorsion du signal
[Termes IGN] figuré du terrain
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] modèle de simulation
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] montagne
[Termes IGN] pente
[Termes IGN] réflectance végétaleRésumé : (Auteur) Sloping terrain induces distortion of canopy reflectance (CR), and the retrieval of biophysical variables from remote sensing data needs to account for topographic effects. We developed a 1-D model (the path length correction (PLC) based model) for simulating CR over sloping terrain. The effects of sloping terrain on single-order and diffuse scatterings are accounted for by PLC and modification of the fraction of incoming diffuse irradiance, respectively. The PLC model was validated via both Monte Carlo and remote sensing image simulations. The comparison with the Monte Carlo simulation revealed that the PLC model can capture the pattern of slope-induced reflectance distortion with high accuracy (red band: R2 = 0.88; root-mean-square error (RMSE) = 0.0045; relative RMSE (RRMSE) = 15%; near infrared response (NIR) band: R2 = 0.79; RMSE = 0.041; RRMSE = 16%). The comparison of the PLC-simulated results with remote sensing observations acquired by the Landsat8-OLI sensor revealed an accuracy similar to that with the Monte Carlo simulation (red band: R2 = 0.83; RMSE = 0.0053; RRMSE = 13%; NIR band: R2 = 0.77; RMSE = 0.023; RRMSE = 8%). To further validate the PLC model, we used it to implement topographic normalization; the results showed a large reduction in topographic effects after normalization, which implied that the PLC model captures reflectance variations caused by terrain. The PLC model provides a promising tool to improve the simulation of CR and the retrieval of biophysical variables over mountainous regions. Numéro de notice : A2017-500 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2694483 En ligne : http://dx.doi.org/10.1109/TGRS.2017.2694483 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86442
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 8 (August 2017) . - pp 4597 - 4609[article]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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Titre : Application of 3D triangulations of airborne laser scanning data to estimate boreal forest leaf area index Type de document : Article/Communication Auteurs : Titta Majasalmi, Auteur ; Lauri Korhonen, Auteur ; Ilkka Korpela, Auteur ; Jari Vauhkonen, Auteur Année de publication : 2017 Article en page(s) : pp 53 - 62 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] canopée
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] houppier
[Termes IGN] Leaf Area Index
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] Triangulated Irregular Network
[Termes IGN] volume (grandeur)Numéro de notice : A2017-365 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2017.02.022 En ligne : https://doi.org/10.1016/j.jag.2017.02.022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85792
in International journal of applied Earth observation and geoinformation > vol 59 (July 2017) . - pp 53 - 62[article]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)
PermalinkCaractérisation de la végétation de Rennes Métropole par relevé LiDAR en vue de sa modélisation / Clément Doceul (2017)
PermalinkHandbook on advances in remote sensing and geographic information systems / Margarita N. Favorskaya (2017)
PermalinkMatching plot-level tree maps with 3D remote sensing data for assessing and estimating forest parameters / Cédric Vega (2017)
PermalinkUtilisation d’un modèle numérique de hauteur en stratification des données de l’Inventaire Forestier National / Sophie Georges (2017)
PermalinkLidar detection of individual tree size in tropical forests / António Ferraz in Remote sensing of environment, vol 183 (15 September 2016)
PermalinkExpérience pratique de la réalisation du projet démonstrateur « LiDAR forestier » / Didier Canteloup in Rendez-vous techniques, n° 50 (Hiver 2016)
PermalinkMultisensor and multispectral Lidar characterization and classification of a forest environment / Christopher Hopkinson in Canadian journal of remote sensing, vol 42 n° 5 ([01/05/2016])
PermalinkOn the interest of penetration depth, canopy area and volume metrics to improve Lidar-based models of forest parameters / Cédric Vega in Remote sensing of environment, vol 175 (15 March 2016)
PermalinkApplication des techniques de photogrammétrie par drone à la caractérisation des ressources forestières / Jonathan Lisein (2016)
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