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Under-canopy UAV laser scanning for accurate forest field measurements / Eric Hyyppä in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 164 (June 2020) . - pp 41 - 60 Titre : Under-canopy UAV laser scanning for accurate forest field measurements Type de document : Article/Communication Auteurs : Eric Hyyppä, Auteur ; Juha Hyyppä, Auteur ; Teemu Hakala, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 41 - 60 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] balayage laser [Termes IGN] canopée [Termes IGN] cartographie et localisation simultanées [Termes IGN] densité du bois [Termes IGN] diamètre à hauteur de poitrine [Termes IGN] données lidar [Termes IGN] erreur moyenne quadratique [Termes IGN] Finlande [Termes IGN] forêt boréale [Termes IGN] hauteur à la base du houppier [Termes IGN] hauteur des arbres [Termes IGN] image captée par drone [Termes IGN] inventaire forestier local [Termes IGN] modèle de croissance végétale [Termes IGN] semis de points [Termes IGN] télédétection aérienne [Termes IGN] télémètre laser terrestre [Termes IGN] télémétrie laser aéroporté [Termes IGN] tronc Résumé : (auteur) Surveying and robotic technologies are converging, offering great potential for robotic-assisted data collection and support for labour intensive surveying activities. From a forest monitoring perspective, there are several technological and operational aspects to address concerning under-canopy flying unmanned airborne vehicles (UAV). To demonstrate this emerging technology, we investigated tree detection and stem curve estimation using laser scanning data obtained with an under-canopy flying UAV. To this end, we mounted a Kaarta Stencil-1 laser scanner with an integrated simultaneous localization and mapping (SLAM) system on board an UAV that was manually piloted with the help of video goggles receiving a live video feed from the onboard camera of the UAV. Using the under-canopy flying UAV, we collected SLAM-corrected point cloud data in a boreal forest on two 32 m 32 m test sites that were characterized as sparse ( = 42 trees) and obstructed ( = 43 trees), respectively. Novel data processing algorithms were applied for the point clouds in order to detect the stems of individual trees and to extract their stem curves and diameters at breast height (DBH). The estimated tree attributes were compared against highly accurate field reference data that was acquired semi-manually with a multi-scan terrestrial laser scanner (TLS). The proposed method succeeded in detecting 93% of the stems in the sparse plot and 84% of the stems in the obstructed plot. In the sparse plot, the DBH and stem curve estimates had a root-mean-squared error (RMSE) of 0.60 cm (2.2%) and 1.2 cm (5.0%), respectively, whereas the corresponding values for the obstructed plot were 0.92 cm (3.1%) and 1.4 cm (5.2%). By combining the stem curves extracted from the under-canopy UAV laser scanning data with tree heights derived from above-canopy UAV laser scanning data, we computed stem volumes for the detected trees with a relative RMSE of 10.1% in both plots. Thus, the combination of under-canopy and above-canopy UAV laser scanning allowed us to extract the stem volumes with an accuracy comparable to the past best studies based on TLS in boreal forest conditions. Since the stems of several spruces located on the test sites suffered from severe occlusion and could not be detected with the stem-based method, we developed a separate work flow capable of detecting trees with occluded stems. The proposed work flow enabled us to detect 98% of trees in the sparse plot and 93% of the trees in the obstructed plot with a 100% correction level in both plots. A key benefit provided by the under-canopy UAV laser scanner is the short period of time required for data collection, currently demonstrated to be much faster than the time required for field measurements and TLS. The quality of the measurements acquired with the under-canopy flying UAV combined with the demonstrated efficiency indicates operational potential for supporting fast and accurate forest resource inventories. Numéro de notice : A2020-240 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.03.021 Date de publication en ligne : 11/04/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.03.021 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94994 [article]

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International benchmarking of terrestrial laser scanning approaches for forest inventories / Xinlian Liang in ISPRS Journal of photogrammetry and remote sensing, vol 144 (October 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 144 (October 2018) . - pp 137 - 179 Titre : International benchmarking of terrestrial laser scanning approaches for forest inventories Type de document : Article/Communication Auteurs : Xinlian Liang, Auteur ; Juha Hyyppä, Auteur ; Harri Kaartinen, Auteur ; Matti Lehtomäki, Auteur ; Jiri Pyorala, Auteur ; Norbert Pfeifer, Auteur ; Markus Holopainen, Auteur ; Gabor Brolly, Auteur ; Francesco Pirotti, Auteur ; Jan Hackenberg , Auteur Année de publication : 2018 Projets : DIABOLO / Packalen, Tuula Article en page(s) : pp 137 - 179 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithmique [Termes IGN] benchmark spatial [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] état de l'art [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] lasergrammétrie [Termes IGN] semis de points [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) The last two decades have witnessed increasing awareness of the potential of terrestrial laser scanning (TLS) in forest applications in both public and commercial sectors, along with tremendous research efforts and progress. It is time to inspect the achievements of and the remaining barriers to TLS-based forest investigations, so further research and application are clearly orientated in operational uses of TLS. In such context, the international TLS benchmarking project was launched in 2014 by the European Spatial Data Research Organization and coordinated by the Finnish Geospatial Research Institute. The main objectives of this benchmarking study are to evaluate the potential of applying TLS in characterizing forests, to clarify the strengths and the weaknesses of TLS as a measure of forest digitization, and to reveal the capability of recent algorithms for tree-attribute extraction. The project is designed to benchmark the TLS algorithms by processing identical TLS datasets for a standardized set of forest attribute criteria and by evaluating the results through a common procedure respecting reliable references. Benchmarking results reflect large variances in estimating accuracies, which were unveiled through the 18 compared algorithms and through the evaluation framework, i.e., forest complexity categories, TLS data acquisition approaches, tree attributes and evaluation procedures. The evaluation framework includes three new criteria proposed in this benchmarking and the algorithm performances are investigated through combining two or more criteria (e.g., the accuracy of the individual tree attributes are inspected in conjunction with plot-level completeness) in order to reveal algorithms’ overall performance. The results also reveal some best available forest attribute estimates at this time, which clarify the status quo of TLS-based forest investigations. Some results are well expected, while some are new, e.g., the variances of estimating accuracies between single-/multi-scan, the principle of the algorithm designs and the possibility of a computer outperforming human operation. With single-scan data, i.e., one hemispherical scan per plot, most of the recent algorithms are capable of achieving stem detection with approximately 75% completeness and 90% correctness in the easy forest stands (easy plots: 600 stems/ha, 20 cm mean DBH). The detection rate decreases when the stem density increases and the average DBH decreases, i.e., 60% completeness with 90% correctness (medium plots: 1000 stem/ha, 15 cm mean DBH) and 30% completeness with 90% correctness (difficult plots: 2000 stems/ha, 10 cm mean DBH). The application of the multi-scan approach, i.e., five scans per plot at the center and four quadrant angles, is more effective in complex stands, increasing the completeness to approximately 90% for medium plots and to approximately 70% for difficult plots, with almost 100% correctness. The results of this benchmarking also show that the TLS-based approaches can provide the estimates of the DBH and the stem curve at a 1–2 cm accuracy that are close to what is required in practical applications, e.g., national forest inventories (NFIs). In terms of algorithm development, a high level of automation is a commonly shared standard, but a bottleneck occurs at stem detection and tree height estimation, especially in multilayer and dense forest stands. The greatest challenge is that even with the multi-scan approach, it is still hard to completely and accurately record stems of all trees in a plot due to the occlusion effects of the trees and bushes in forests. Future development must address the redundant yet incomplete point clouds of forest sample plots and recognize trees more accurately and efficiently. It is worth noting that TLS currently provides the best quality terrestrial point clouds in comparison with all other technologies, meaning that all the benchmarks labeled in this paper can also serve as a reference for other terrestrial point clouds sources. Numéro de notice : A2018-400 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.06.021 Date de publication en ligne : 24/07/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.06.021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90829 [article]

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In-situ measurements from mobile platforms: An emerging approach to address the old challenges associated with forest inventories / Xinlian Liang in ISPRS Journal of photogrammetry and remote sensing, vol 143 (September 2018)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 143 (September 2018) . - pp 97 - 107 Titre : In-situ measurements from mobile platforms: An emerging approach to address the old challenges associated with forest inventories Type de document : Article/Communication Auteurs : Xinlian Liang, Auteur ; Antero Kukko, Auteur ; Juha Hyyppä, Auteur ; Matti Lehtomäki, Auteur ; Jiri Pyorala, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 97 - 107 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] estimation de précision [Termes IGN] exhaustivité des données [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] lasergrammétrie [Termes IGN] lidar mobile [Termes IGN] semis de points [Vedettes matières IGN] Inventaire forestier Résumé : (Auteur) Accurate assessments of forest resources rely on ground truth data that are collected via in-situ measurements, which are fundamental for all other statistical- and/or remote-sensing-based deductions on quantified forest attributes. The major bottleneck of the current in-situ observation system is that the data collection is time consuming, and, thus, limited in extent, which potentially biases any further inferences made. Consequently, conventional field-data-collection approaches can hardly keep pace with the coverage, scale and frequency required for contemporary and future forest inventories. In-situ measurements from mobile platforms seem to be a promising technique to solve this problem and are estimated at least 10 times faster than static techniques (e.g., terrestrial laser scanning, TLS) at the plot level. However, the mobile platforms are still at the very early stages of development, and it is unclear which three-dimensional (3D) forest measurements the mobile systems can provide and at what accuracy. This study presents a quantitative evaluation of the performance of mobile platforms in a variety of forest conditions and through a comparison with state-of-the-art static in-situ observations. Two mobile platforms were used to collect field data, where the same laser-scanning system was both mounted on top of a vehicle and wore by an operator. The static in-situ observation from TLS is used as a baseline for the evaluation. All point clouds involved were processed through the same processing chain and compared to conventional manual measurement. The evaluation results indicate that the mobile platforms can assess homogeneous forests as well as static observations, but they cannot yet assess heterogeneous forest as required by practical applications. The major challenge is twofold: mobile-data coverage and accuracy. Future research should focus on the robust registration techniques between strips, especially in complex forest conditions, since errors of data registration results in significant impacts on tree attributes estimation accuracy. In cases that the spatial inconstancy cannot be eliminated, attributes estimation in single strips, i.e., the multi-single-scan approach, is an alternative. Meanwhile, operator training deserves attention since the data quality from mobile platforms is partly determined by the operators’ selection of trajectory in the field. Numéro de notice : A2018-357 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2018.04.019 Date de publication en ligne : 18/06/2018 En ligne : https://doi.org/10.1016/j.isprsjprs.2018.04.019 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90591 [article]

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Advances in airborne Lidar systems and data processing / Jie Shan (2018)  

Public Titre : Advances in airborne Lidar systems and data processing Type de document : Monographie Auteurs : Jie Shan, Éditeur scientifique ; Juha Hyyppä, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2018 Importance : 493 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-03842-673-8 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] apprentissage profond [Termes IGN] détection d'arbres [Termes IGN] données lidar [Termes IGN] enregistrement de données [Termes IGN] hauteur des arbres [Termes IGN] image multibande [Termes IGN] modèle numérique de terrain [Termes IGN] photon [Termes IGN] reconstruction 3D du bâti [Termes IGN] semis de points [Termes IGN] télédétection par lidar Résumé : (éditeur) This book collects the papers in the special issue "Airborne Laser Scanning" in Remote Sensing (Nov. 2016) and several other selected papers published in the same journal in the past few years. Our intention is to reflect recent technological developments and innovative techniques in this field. The book consists of 23 papers in six subject areas: 1) Single photon and Geiger-mode Lidar, 2) Multispectral lidar, 3) Waveform lidar, 4) Registration of point clouds, 5) Trees and terrain, and 6) Building extraction. The book is a valuable resource for scientists, engineers, developers, instructors, and graduate students interested in lidar systems and data processing. Note de contenu : 1- Single photon and Geiger-mode Lidar 2- Multispectral Lidar 3- Waveform Lidar 4- Registration of Point Clouds 5- Trees and Terrain 6- Building Extraction Numéro de notice : 25932 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie En ligne : https://doi.org/10.3390/books978-3-03842-674-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96235

Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating / Leena Matikainen in ISPRS Journal of photogrammetry and remote sensing, vol 128 (June 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 128 (June 2017) . - pp 298 - 313 Titre : Object-based analysis of multispectral airborne laser scanner data for land cover classification and map updating Type de document : Article/Communication Auteurs : Leena Matikainen, Auteur ; Kirsi Karila, Auteur ; Juha Hyyppä, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 298 - 313 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] analyse d'image orientée objet [Termes IGN] classification dirigée [Termes IGN] image 3D [Termes IGN] image multibande [Termes IGN] instrumentation Optech [Termes IGN] mise à jour cartographique [Termes IGN] occupation du sol [Termes IGN] semis de points [Termes IGN] télémétrie laser aéroporté Résumé : (Auteur) During the last 20 years, airborne laser scanning (ALS), often combined with passive multispectral information from aerial images, has shown its high feasibility for automated mapping processes. The main benefits have been achieved in the mapping of elevated objects such as buildings and trees. Recently, the first multispectral airborne laser scanners have been launched, and active multispectral information is for the first time available for 3D ALS point clouds from a single sensor. This article discusses the potential of this new technology in map updating, especially in automated object-based land cover classification and change detection in a suburban area. For our study, Optech Titan multispectral ALS data over a suburban area in Finland were acquired. Results from an object-based random forests analysis suggest that the multispectral ALS data are very useful for land cover classification, considering both elevated classes and ground-level classes. The overall accuracy of the land cover classification results with six classes was 96% compared with validation points. The classes under study included building, tree, asphalt, gravel, rocky area and low vegetation. Compared to classification of single-channel data, the main improvements were achieved for ground-level classes. According to feature importance analyses, multispectral intensity features based on several channels were more useful than those based on one channel. Automatic change detection for buildings and roads was also demonstrated by utilising the new multispectral ALS data in combination with old map vectors. In change detection of buildings, an old digital surface model (DSM) based on single-channel ALS data was also used. Overall, our analyses suggest that the new data have high potential for further increasing the automation level in mapping. Unlike passive aerial imaging commonly used in mapping, the multispectral ALS technology is independent of external illumination conditions, and there are no shadows on intensity images produced from the data. These are significant advantages in developing automated classification and change detection procedures. Numéro de notice : A2017-336 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.04.005 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.04.005 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85499 [article]

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International benchmarking of the individual tree detection methods for modeling 3-D canopy structure for silviculture and forest ecology using airborne laser scanning / Yunsheng Wang in IEEE Transactions on geoscience and remote sensing, vol 54 n° 9 (September 2016)    

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Terrestrial laser scanning in forest inventories / Xinlian Liang in ISPRS Journal of photogrammetry and remote sensing, vol 115 (May 2016)  

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Object classification and recognition from mobile laser scanning point clouds in a road environment / Matti Lehtomäki in IEEE Transactions on geoscience and remote sensing, vol 54 n° 2 (February 2016)  

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Terrestrial laser scanning in forest inventories / Xinlian Liang in GIM international [en ligne], vol 30 n° 2 (February 2016)

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Automated stem curve measurement using terrestrial laser scanning / Xinlian Liang in IEEE Transactions on geoscience and remote sensing, vol 52 n° 3 (March 2014)  

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EuroSDR project Commission 2, Mobile mapping - road environment mapping using mobile laser scanning / Harri Kaartinen (2013)

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I-7 - 2012 - [actes] XXII ISPRS Congress, Technical Commission 7, 25 August – 01 September 2012, Melbourne, Australia (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / M. Shortis  

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Automatic stem mapping using single-scan terrestrial laser scanning / X. Liang in IEEE Transactions on geoscience and remote sensing, vol 50 n° 2 (February 2012)  

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Tree species classification with multiple source remote sensing data / Eetu Puttonen (2012)  

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A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements / Anttoni Jaakkola in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 6 (November - December 2010)  

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