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1
Rudant, Jean-Paul, and Pierre-Louis Frison. "Lettre : Existe-t-il des relations formelles entre coefficients de diffusion radar et facteurs de réflectance en optique ?" Revue Française de Photogrammétrie et de Télédétection, no. 219-220 (January 17, 2020): 29–31. http://dx.doi.org/10.52638/rfpt.2019.461.
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Cette note tente de répondre à de fréquentes questions touchant à la comparaison optique et radar, par exemple : quelles sont les relations formelles existant entre coefficients de diffusion radar et facteurs de réflectance en optique ? Comment les images reflètent elles les coefficients optiques ou radar destinés à caractériser la surface ?
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Lafrance, Bruno, Xavier Lenot, Caroline Ruffel, Patrick Cao, and Thierry Rabaute. "Outils de prétraitements des images optiques Kalideos." Revue Française de Photogrammétrie et de Télédétection, no. 197 (April 21, 2014): 10–16. http://dx.doi.org/10.52638/rfpt.2012.78.
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La communauté scientifique a besoin de disposer de séries temporelles d'observations récurrentes, couvrant des sites d'intérêt pour le suivi de l'évolution des surfaces terrestres (études agronomiques par assimilation de données, suivi de traits de côte, glissements de terrain, surveillance des volcans, cartographie littorale, etc.). L'analyse de ces séries temporelles demande à avoir des images superposables entre elles qui renseignent sur la réflectance des sites (grandeur physique indépendante du capteur).Dans l'objectif de rendre accessibles de telles données physiques et de garantir une homogénéité des traitements de séries temporelles d'images, le CNES a mis en place le programme Kalideos. Dans ce cadre, CS SI a développé et opère les chaines de traitement des images.Cet article présente les traitements appliqués aux images optiques des bases Kalideos (capteurs Spot et Formosat). Ces traitements permettent de convertir les produits de niveau 1A en ortho-images, donnant la réflectance mesurée au sommet de l'atmosphère et celle estimée au niveau de la surface après correction des effets atmosphériques.
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LIN, C. S. "Ocean surface profiling lidar." International Journal of Remote Sensing 17, no. 13 (September 1996): 2667–80. http://dx.doi.org/10.1080/01431169608949098.
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CHAMP, M., and P. COLONNA. "Importance de l’endommagement de l’amidon dans les aliments pour animaux." INRAE Productions Animales 6, no. 3 (June 28, 1993): 185–98. http://dx.doi.org/10.20870/productions-animales.1993.6.3.4199.
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Les principales modifications de l’état de l’amidon, qui se produisent au cours des étapes de transformation et de fabrication des aliments pour animaux, sont l’augmentation de surface spécifique, une diminution de la cristallinité et une dépolymérisation de l’amylose et de l’amylopectine. Les différentes méthodes in vitro qui permettent d’étudier les facteurs influençant les cinétiques d’hydrolyse de l’amidon sont présentées. La microscopie permet des observations qualitatives. Les déterminations quantitatives sont fondées sur la susceptibilité aux amylases, les solubilités en milieux aqueux et alcooliques ainsi que l’absorption d’eau. Ces différents tests permettent de prédire la digestibilité de l’amidon dans la partie supérieure du tractus digestif. L’analyse par réflectance dans le moyen infra-rouge pourrait devenir un outil de contrôle en ligne.
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Belov, M. L., A. M. Belov, V. A. Gorodnichev, and S. V. Alkov. "Monopulse lidar Earth surface sounding method." IOP Conference Series: Materials Science and Engineering 537 (June 17, 2019): 022047. http://dx.doi.org/10.1088/1757-899x/537/2/022047.
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Mandlburger, Gottfried, and Boris Jutzi. "On the Feasibility of Water Surface Mapping with Single Photon LiDAR." ISPRS International Journal of Geo-Information 8, no. 4 (April 10, 2019): 188. http://dx.doi.org/10.3390/ijgi8040188.
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Single photon sensitive airborne Light Detection And Ranging (LiDAR) enables a higher area performance at the price of an increased outlier rate and a lower ranging accuracy compared to conventional Multi-Photon LiDAR. Single Photon LiDAR, in particular, uses green laser light potentially capable of penetrating clear shallow water. The technology is designed for large-area topographic mapping, which also includes the water surface. While the penetration capabilities of green lasers generally lead to underestimation of the water level heights, we specifically focus on the questions of whether Single Photon LiDAR (i) is less affected in this respect due to the high receiver sensitivity, and (ii) consequently delivers sufficient water surface echoes for precise high-resolution water surface reconstruction. After a review of the underlying sensor technology and the interaction of green laser light with water, we address the topic by comparing the surface responses of actual Single Photon LiDAR and Multi-Photon Topo-Bathymetric LiDAR datasets for selected horizontal water surfaces. The anticipated superiority of Single Photon LiDAR could not be verified in this study. While the mean deviations from a reference water level are less than 5 cm for surface models with a cell size of 10 m, systematic water level underestimation of 5–20 cm was observed for high-resolution Single Photon LiDAR based water surface models with cell sizes of 1–5 m. Theoretical photon counts obtained from simulations based on the laser-radar equation support the experimental data evaluation results and furthermore confirm the feasibility of Single Photon LiDAR based high-resolution water surface mapping when adopting specifically tailored flight mission parameters.
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Yang, Song, Qian Sun, and Yongchao Zheng. "Simulation Effects of Surface Geometry and Water Optical Properties on Hydrographic Lidar Returns." EPJ Web of Conferences 237 (2020): 08020. http://dx.doi.org/10.1051/epjconf/202023708020.
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. Water LiDAR model was applied to simulate the returned waveforms of hydrographic LiDAR considering the effects of surface geometry and water optical properties. The signal to noise ratio(SNR) of bottom returned peak was considered as a criterion for performance of hydrographic LiDAR. The behavior of LiDAR was sensitive to water optical properties and it was insensitive to water surface roughness.
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Sedláček, Jozef, Ondřej Šesták, and Miroslava Sliacka. "Comparison of Digital Elevation Models by Visibility Analysis in Landscape." Acta Horticulturae et Regiotecturae 19, no. 2 (November 1, 2016): 28–31. http://dx.doi.org/10.1515/ahr-2016-0007.
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Abstract The paper investigates suitability of digital surface model for visibility analysis in GIS. In experiment there were analysed viewsheds from 14 observer points calculated on digital surface model, digital terrain model and its comparison to field survey. Data sources for the investigated models were LiDAR digital terrain model and LiDAR digital surface model with vegetation distributed by the Czech Administration for Land Surveying and Cadastre. The overlay method was used for comparing accuracy of models and the reference model was LiDAR digital surface model. Average equalities in comparison with LiDAR digital terrain model, ZABAGED model and field survey were 15.5 %, 17.3% and 20.9%, respectively.
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Webster, Tim, Candace MacDonald, Kevin McGuigan, Nathan Crowell, Jean-Sebastien Lauzon-Guay, and Kate Collins. "Calculating macroalgal height and biomass using bathymetric LiDAR and a comparison with surface area derived from satellite data in Nova Scotia, Canada." Botanica Marina 63, no. 1 (February 25, 2020): 43–59. http://dx.doi.org/10.1515/bot-2018-0080.
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AbstractThe ability to map and monitor the macroalgal coastal resource is important to both the industry and the regulator. This study evaluates topo-bathymetric lidar (light detection and ranging) as a tool for estimating the surface area, height and biomass of Ascophyllum nodosum, an anchored and vertically suspended (floating) macroalga, and compares the surface area derived from lidar and WorldView-2 satellite imagery. Pixel-based Maximum Likelihood classification of low tide satellite data produced 2-dimensional maps of intertidal macroalgae with overall accuracy greater than 80%. Low tide and high tide topo-bathymetric lidar surveys were completed in southwestern Nova Scotia, Canada. Comparison of lidar-derived seabed elevations with ground-truth data collected using a survey grade global navigation satellite system (GNSS) indicated the low tide survey data have a positive bias of 15 cm, likely resulting from the seaweed being draped over the surface. The high tide survey data did not exhibit this bias, although the suspended canopy floating on the water surface reduced the seabed lidar point density. Validation of lidar-derived seaweed heights indicated a mean difference of 30 cm with a root mean square error of 62 cm. The modelled surface area of seaweed was 28% greater in the lidar model than the satellite model. The average lidar-derived biomass estimate was within one standard deviation of the mean biomass measured in the field. The lidar method tends to overestimate the biomass compared to field measurements that were spatially biased to the mid-intertidal level. This study demonstrates an innovative and cost-effective approach that uses a single high tide bathymetric lidar survey to map the height and biomass of dense macroalgae.
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Telling, Jennifer, Craig Glennie, Andrew Fountain, and David Finnegan. "Analyzing Glacier Surface Motion Using LiDAR Data." Remote Sensing 9, no. 3 (March 17, 2017): 283. http://dx.doi.org/10.3390/rs9030283.
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Yadav, M., B. Lohani, and A. K. Singh. "ROAD SURFACE DETECTION FROM MOBILE LIDAR DATA." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-5 (November 15, 2018): 95–101. http://dx.doi.org/10.5194/isprs-annals-iv-5-95-2018.
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<p><strong>Abstract.</strong> The accurate three-dimensional road surface information is highly useful for health assessment and maintenance of roads. It is basic information for further analysis in several applications including road surface settlement, pavement condition assessment and slope collapse. Mobile LiDAR system (MLS) is frequently used now a days to collect detail road surface and its surrounding information in terms three-dimensional (3D) point cloud. Extraction of road surface from volumetric point cloud data is still in infancy stage because of heavy data processing requirement and the complexity in the road environment. The extraction of roads especially rural road, where road-curb is not present is very tedious job especially in Indian roadway settings. Only a few studies are available, and none for Indian roads, in the literature for rural road detection. The limitations of existing studies are in terms of their lower accuracy, very slow speed of data processing and detection of other objects having similar characteristics as the road surface. A fast and accurate method is proposed for LiDAR data points of road surface detection, keeping in mind the essence of road surface extraction especially for Indian rural roads. The Mobile LiDAR data in <i>XYZI</i> format is used as input in the proposed method. First square gridding is performed and ground points are roughly extracted. Then planar surface detection using mathematical framework of principal component analysis (PCA) is performed and further road surface points are detected using similarity in intensity and height difference of road surface pointe in their neighbourhood.</p><p>A case study was performed on the MLS data points captured along wide-street (two-lane road without curb) of 156<span class="thinspace"></span>m length along rural roadway site in the outskirt of Bengaluru city (South-West of India). The proposed algorithm was implemented on the MLS data of test site and its performance was evaluated it terms of recall, precision and overall accuracy that were 95.27%, 98.85% and 94.23%, respectively. The algorithm was found computationally time efficient. A 7.6 million MLS data points of size 27.1<span class="thinspace"></span>MB from test site were processed in 24 minutes using the available computational resources. The proposed method is found to work even for worst case scenarios, i.e., complex road environments and rural roads, where road boundary is not clear and generally merged with road-side features.</p>
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Josset, Damien, Peng-Wang Zhai, Yongxiang Hu, Jacques Pelon, and Patricia L. Lucker. "Lidar equation for ocean surface and subsurface." Optics Express 18, no. 20 (September 17, 2010): 20862. http://dx.doi.org/10.1364/oe.18.020862.
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Bufton, Jack L. "Airborne lidar for profiling of surface topography." Optical Engineering 30, no. 1 (1991): 72. http://dx.doi.org/10.1117/12.55770.
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Lenac, Kruno, Andrej Kitanov, Robert Cupec, and Ivan Petrović. "Fast planar surface 3D SLAM using LIDAR." Robotics and Autonomous Systems 92 (June 2017): 197–220. http://dx.doi.org/10.1016/j.robot.2017.03.013.
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Mandlburger, G., and B. Jutzi. "FEASIBILITY INVESTIGATION ON SINGLE PHOTON LIDAR BASED WATER SURFACE MAPPING." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-1 (September 26, 2018): 109–16. http://dx.doi.org/10.5194/isprs-annals-iv-1-109-2018.
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<p><strong>Abstract.</strong> The recent advent of single photon sensitive airborne LiDAR (Light Detection And Ranging) sensors has enabled higher areal coverage performance at the price of an increased outlier rate and a lower ranging accuracy compared to conventional Multi-Photon LiDAR. Single Photon LiDAR, in particular, uses green laser light capable of penetrating clear shallow water. Although primarily designed for large area topographic mapping, the technique can also be used for mapping the water surface and shallow water bathymetry. In this contribution we investigate the capability of Single Photon LiDAR for large area mapping of water surface heights. While interface returns from conventional green-only bathymetric sensors generally suffer from water level underestimation due to the water penetration capabilities of green laser radiation, the specific questions are, if Single Photon LiDAR (i) is less affected by this well known effect due to the high receiver sensitivity and (ii) consequently delivers a higher number of water surface echoes. The topic is addressed empirically in a case study by comparing the water surface responses of Single Photon LiDAR (Navarra, Spain) and Multi-Photon Topo-Bathymetric LiDAR (Neubacher Au, Austria) for selected water bodies with a horizontal water surface (reservoirs, ponds). Although flown at different altitudes, both datasets are well comparable as they exhibit the same strip point density of ca. 14<span class="thinspace"></span>points/m<sup>2</sup>. The expected superiority of Single Photon LiDAR over conventional green-only bathymetric LiDAR for mapping water surfaces could not be verified in this investigation. While both datasets show good agreement compared to a reference water level when aggregating points into cells of 10<span class="thinspace"></span>&times;<span class="thinspace"></span>10<span class="thinspace"></span>m<sup>2</sup> (mean deviations &lt;<span class="thinspace"></span>5<span class="thinspace"></span>cm), higher resolution Single Photon LiDAR based water surface models (grid size 1&ndash;5<span class="thinspace"></span>m) show a systematic water level underestimation of 5&ndash;20<span class="thinspace"></span>cm. However, independently measured ground truth observations and simultaneous data acquisition of the same area with both techniques are necessary to verify the results.</p>
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K, Mr Pramod, and Akshay M C. "LIDAR Technology." International Journal for Research in Applied Science and Engineering Technology 10, no. 5 (May 31, 2022): 2976–82. http://dx.doi.org/10.22214/ijraset.2022.43007.
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Abstract: Since the 1960s, LiDAR (Light Detection And Ranging) technology has been in use. LiDAR has become a common sensor as technology has advanced. Automation, agriculture, archaeology, Information technology and the quantification of various atmosphericcomponents all use LiDARs. The present manuscripts cover the operation of LiDAR, its various varieties, history, and various applications. One may determine the distance between different objects in space and construct a 3D digital representation of the region in front of LiDAR using LiDAR readings. Lidar mapping is a wellknown technique for quickly generating precise georeferenced spatial data about the Earth's shape and surface features. Lidar mapping systems and their underlying technology have recently progressed, allowing scientists and mapping professionals to investigate natural and built environments at sizes never before feasible, with greater accuracy, precision, and cost effectively provide the best aspects of the culture of human civilization. Keywords: LiDAR, LASER, RADAR
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Zhu, Junqing, Yingda Gao, Siqi Huang, Tianxiang Bu, and Shun Jiang. "Measuring Surface Deformation of Asphalt Pavement via Airborne LiDAR: A Pilot Study." Drones 7, no. 9 (September 5, 2023): 570. http://dx.doi.org/10.3390/drones7090570.
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Measuring the surface deformation of asphalt pavement and acquiring the rutting condition is of great importance to transportation agencies. This paper proposes a rutting measuring method based on an unmanned aerial vehicle (UAV) mounted with Light Detection and Ranging (LiDAR). Firstly, an airborne LiDAR system is assembled and the data acquisition method is presented. Then, the method for point cloud processing and rut depth computation is presented and the results of field testing are discussed. Thirdly, to investigate error factors, the laser footprint positioning model is established and sensitivity analysis is conducted. Factors including flight height, LiDAR instantaneous angel, and ground inclination angle are discussed. The model was then implemented to obtain the virtual rut depth and to verify the accuracy of the field test results. The main conclusions include that the measurement error increases with the flight height, instantaneous angle, and angular resolution of the LiDAR. The inclination angle of the pavement surface has adverse impact on the measuring accuracy. The field test results show that the assembled airborne LiDAR system is more accurate when the rut depth is significant. The findings of this study pave the way for future exploration of rutting measurement with airborne LiDAR.
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Taheri Andani, Masood, Abdullah Mohammed, Ashish Jain, and Mehdi Ahmadian. "Application of LIDAR technology for rail surface monitoring and quality indexing." Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit 232, no. 5 (August 23, 2017): 1398–406. http://dx.doi.org/10.1177/0954409717727200.
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This paper investigates the application of Doppler Light Detection and Ranging (LIDAR) sensors for the assessment of the top of rail lubricity condition and layer material. Different top of rail conditions are distinguished by the system using a new pair of rail surface indices defined based on LIDAR measurements. These indices provide quantitative representations of the top of rail condition due to the fact that Doppler frequency range and spectral magnitude of a backscattered LIDAR beam are functions of the rail surface figure as well as the light absorption properties of the surface material. Laboratory tests are conducted to demonstrate the feasibility of the proposed top of rail indexing operation. The results indicate that LIDAR sensors are capable of detecting and distinguishing between different top of rail surface conditions. Instrumenting rail inspection vehicles with Doppler LIDAR systems reduces reliance on empirical top of rail lubricity and surface assessments (such as observing the sheen of the rail or tactilely sensing various residues on the rail), in favor of reliable and repeatable measurements.
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Tinkham, Wade T., Alistair M. S. Smith, Chad Hoffman, Andrew T. Hudak, Michael J. Falkowski, Mark E. Swanson, and Paul E. Gessler. "Investigating the influence of LiDAR ground surface errors on the utility of derived forest inventories." Canadian Journal of Forest Research 42, no. 3 (March 2012): 413–22. http://dx.doi.org/10.1139/x11-193.
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Light detection and ranging, or LiDAR, effectively produces products spatially characterizing both terrain and vegetation structure; however, development and use of those products has outpaced our understanding of the errors within them. LiDAR’s ability to capture three-dimensional structure has led to interest in conducting or augmenting forest inventories with LiDAR data. Prior to applying LiDAR in operational management, it is necessary to understand the errors in LiDAR-derived estimates of forest inventory metrics (i.e., tree height). Most LiDAR-based forest inventory metrics require creation of digital elevation models (DEM), and because metrics are calculated relative to the DEM surface, errors within the DEMs propagate into delivered metrics. This study combines LiDAR DEMs and 54 ground survey plots to investigate how surface morphology and vegetation structure influence DEM errors. The study further compared two LiDAR classification algorithms and found no significant difference in their performance. Vegetation structure was found to have no influence, whereas increased variability in the vertical error was observed on slopes exceeding 30°, illustrating that these algorithms are not limited by high-biomass western coniferous forests, but that slope and sensor accuracy both play important roles. The observed vertical DEM error translated into ±1%–3% error range in derived timber volumes, highlighting the potential of LiDAR-derived inventories in forest management.
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Yusuf, Muhammad Adnan, and Danang Setiaji. "Optimalisasi Data DEM LiDAR pada Area Perairan Sungai." Elipsoida : Jurnal Geodesi dan Geomatika 6, no. 1 (June 13, 2023): 12–22. http://dx.doi.org/10.14710/elipsoida.2023.17201.
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Light Detection and Ranging (LiDAR) merupakan salah satu alat yang dapat menghasilkan akurasi tinggi dalam mengukur tinggi di permukaan bumi. Dengan menggunakan teknologi LiDAR dapat digunakan untuk mendeteksi beberapa objek di permukaan bumi seperti ground, vegetasi atau bangunan, namun teknologi LiDAR mempunyai kelemahan yaitu sulit mendeteksi titik-titik di area perairan. Oleh karena itu kerapatan point cloud di daerah perairan termasuk kategori rendah, sehingga DEM yang diturunkan dari data LiDAR memiliki permukaan air yang tidak alami. Hydro-flattening adalah proses menciptakan DEM yang diturunkan dari data LiDAR dengan tujuan untuk membuat permukaan air sungai rata dan mengalir. Komponen penting dari pembuatan hydro flattening adalah breakline, Data utama pada proses ini adalah point cloud Lidar yang sudah terklasifkasi ground dan centerline. Ada 4 langkah dalam metode semi otomatis ini yaitu langkah pertama, Continous Bare Ground Surface (CBGS) dibuat dengan mencari elevasi terendah sepanjang sungai yang akan diproses. Pada langkah kedua, membuat radius pencarian berbentuk lingkaran yang berpusat pada centreline sungai untuk mencari elevasi point cloud LiDAR paling rendah di setiap lingkaran, elevasi tersebut digunakan untuk membuat Virtual Water Surface (VWS). VWS ini perlu dilakukan revisi karena ketinggian minimum pada data LiDAR tidak selalu merupakan ketinggian permukaan air, VWS yang direvisi ini disebut sengan Base Virtual Water Surface (B-VWS). Langkah ketiga adalah ekstraksi breakline dan smoothing hasil esktraksi breakline,. Langkah keempat adalah konversi breakline 2D ke 3D, hasil breakline 2D dimasukkan ketinggian dari B-VWS sehingga menjadi breakline 3D yang dapat digunakan untuk menghasilkan Hydro-flattening DEM. Hydro flattenning diterapkan pada 2 lokasi sungai yang berbeda-beda, dimana lokasi sungai 1 memiliki karakter sungai dengan kategori kecil, sedangkan sungai 2 memiliki karakter sungai yang bercabang. Dari hasil Hydro flattenning DEM LiDAR pada daerah perairan dapat sesuai dengan kondisi yang ada dilapangan yaitu perairan sungai yang datar dan mengalir dari hulu ke hilir. Dari kedua sungai tersebut membuktikan pentingnya dilakukan Hydro flattenning pada DEM LiDARKata kunci : LiDAR, Hydro-Flattening, Breakline, Continous Bare Ground Surface, Virtual Water Surface
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Lolli, Simone, Fabio Madonna, Marco Rosoldi, James R. Campbell, Ellsworth J. Welton, Jasper R. Lewis, Yu Gu, and Gelsomina Pappalardo. "Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects." Atmospheric Measurement Techniques 11, no. 3 (March 26, 2018): 1639–51. http://dx.doi.org/10.5194/amt-11-1639-2018.
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Abstract. In the past 2 decades, ground-based lidar networks have drastically increased in scope and relevance, thanks primarily to the advent of lidar observations from space and their need for validation. Lidar observations of aerosol and cloud geometrical, optical and microphysical atmospheric properties are subsequently used to evaluate their direct radiative effects on climate. However, the retrievals are strongly dependent on the lidar instrument measurement technique and subsequent data processing methodologies. In this paper, we evaluate the discrepancies between the use of Raman and elastic lidar measurement techniques and corresponding data processing methods for two aerosol layers in the free troposphere and for two cirrus clouds with different optical depths. Results show that the different lidar techniques are responsible for discrepancies in the model-derived direct radiative effects for biomass burning (0.05 W m−2 at surface and 0.007 W m−2 at top of the atmosphere) and dust aerosol layers (0.7 W m−2 at surface and 0.85 W m−2 at top of the atmosphere). Data processing is further responsible for discrepancies in both thin (0.55 W m−2 at surface and 2.7 W m−2 at top of the atmosphere) and opaque (7.7 W m−2 at surface and 11.8 W m−2 at top of the atmosphere) cirrus clouds. Direct radiative effect discrepancies can be attributed to the larger variability of the lidar ratio for aerosols (20–150 sr) than for clouds (20–35 sr). For this reason, the influence of the applied lidar technique plays a more fundamental role in aerosol monitoring because the lidar ratio must be retrieved with relatively high accuracy. In contrast, for cirrus clouds, with the lidar ratio being much less variable, the data processing is critical because smoothing it modifies the aerosol and cloud vertically resolved extinction profile that is used as input to compute direct radiative effect calculations.
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Brubaker, Kristen M., Wayne L. Myers, Patrick J. Drohan, Douglas A. Miller, and Elizabeth W. Boyer. "The Use of LiDAR Terrain Data in Characterizing Surface Roughness and Microtopography." Applied and Environmental Soil Science 2013 (2013): 1–13. http://dx.doi.org/10.1155/2013/891534.
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The availability of light detection and ranging data (LiDAR) has resulted in a new era of landscape analysis. For example, improvements in LiDAR data resolution may make it possible to accurately model microtopography over a large geographic area; however, data resolution and processing costs versus resulting accuracy may be too costly. We examined two LiDAR datasets of differing resolutions, a low point density (0.714 points/m2spacing) 1 m DEM available statewide in Pennsylvania and a high point density (10.28 points/m2spacing) 1 m DEM research-grade DEM, and compared the calculated roughness between both resulting DEMs using standard deviation of slope, standard deviation of curvature, a pit fill index, and the difference between a smoothed splined surface and the original DEM. These results were then compared to field-surveyed plots and transects of microterrain. Using both datasets, patterns of roughness were identified, which were associated with different landforms derived from hydrogeomorphic features such as stream channels, gullies, and depressions. Lowland areas tended to have the highest roughness values for all methods, with other areas showing distinctive patterns of roughness values across metrics. However, our results suggest that the high-resolution research-grade LiDAR did not improve roughness modeling in comparison to the coarser statewide LiDAR. We conclude that resolution and initial point density may not be as important as the algorithm and methodology used to generate a LiDAR-derived DEM for roughness modeling purposes.
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Davidson, L., J. P. Mills, I. Haynes, C. Augarde, P. Bryan, and M. Douglas. "AIRBORNE TO UAS LIDAR: AN ANALYSIS OF UAS LIDAR GROUND CONTROL TARGETS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-2/W13 (June 4, 2019): 255–62. http://dx.doi.org/10.5194/isprs-archives-xlii-2-w13-255-2019.
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<p><strong>Abstract.</strong> Creating accurate models of the Earth’s surface is an essential step when analysing geomorphological changes through time. Alongside photogrammetry, airborne lidar is an established method for measuring and modelling the Earth’s surface. However, improvements in size, weight and power requirements mean that lidar is now increasingly capable of being operated from Unpiloted Aircraft Systems (UASs). While academic literature is currently weighted towards issues associated with airborne laser scanning, UASs operate under different parameters to piloted aeroplanes and helicopters. In order to achieve desired results from UAS lidar, mission planning parameters and ground control requirements therefore need to be tailored to data collection from UAS platforms. This paper presents the preliminary results of how a variety control target designs responded to a UAS lidar survey flown along different trajectories at different heights above ground level. This research draws upon previous airborne laser scanning work and aims to provide guidance on considerations for UAS lidar specific ground control targets.</p>
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Hu, Y., K. Stamnes, M. Vaughan, J. Pelon, C. Weimer, D. Wu, M. Cisewski, et al. "Sea surface wind speed estimation from space-based lidar measurements." Atmospheric Chemistry and Physics 8, no. 13 (July 8, 2008): 3593–601. http://dx.doi.org/10.5194/acp-8-3593-2008.
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Abstract. Global satellite observations of lidar backscatter measurements acquired by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission and collocated sea surface wind speed data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), are used to investigate the relation between wind driven wave slope variance and sea surface wind speed. The new slope variance – wind speed relation established from this study is similar to the linear relation from Cox-Munk (1954) and the log-linear relation from Wu (1990) for wind speed larger than 7 m/s and 13.3 m/s, respectively. For wind speed less than 7 m/s, the slope variance is proportional to the square root of the wind speed, assuming a two dimensional isotropic Gaussian wave slope distribution. This slope variance – wind speed relation becomes linear if a one dimensional Gaussian wave slope distribution and linear slope variance – wind speed relation are assumed. Contributions from whitecaps and subsurface backscattering are effectively removed by using 532 nm lidar depolarization measurements. This new slope variance – wind speed relation is used to derive sea surface wind speed from CALIPSO single shot lidar measurements (70 m spot size), after correcting for atmospheric attenuation. The CALIPSO wind speed result agrees with the collocated AMSR-E wind speed, with 1.2 m/s rms error. Ocean surface with lowest atmospheric loading and moderate wind speed (7–9 m/s) is used as target for lidar calibration correction.
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Mo, Zhong, Sun, Wu, Du, Geng, and Cao. "Integrated Airborne LiDAR Data and Imagery for Suburban Land Cover Classification Using Machine Learning Methods." Sensors 19, no. 9 (April 28, 2019): 1996. http://dx.doi.org/10.3390/s19091996.
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It is valuable to study the land use/land cover (LULC) classification for suburbs. The fusion of Light Detection and Ranging (LiDAR) data and aerial imagery is often regarded as an effective method for the LULC classification; however, more in-depth analysis would be required to explore effective information for enhancing the suburban LULC classification. In this study, first, both aerial imageries and point clouds were simultaneously collected. Then, LiDAR-derived models, i.e., normalized digital surface model (nDSM) and surface intensity model (IM), were generated from the elevation and intensity of point clouds. Further, considering the surface characteristics of ground objects in suburb, we proposed a new LiDAR-derived model, namely surface roughness model (RM), to reveal the degree of surface fluctuations. Additionally, various combinations of aerial imageries and the LiDAR-derived data were used to analyze the effects of multi-variable fusion under different scenarios and optimize the multi-variable integration for suburban LULC classification. The mean decrease impurity method was used to identify the importance of variables; three machine learning classifiers, i.e., random forest (RF), k-nearest neighbor (KNN) and artificial neural network (ANN) were adopted in various scenarios. The results were as follows. The fusion of aerial imagery and all the LiDAR-derived models, i.e., nDSM, RM and IM, with RF classifier performs best in the suburban LULC classification (overall accuracy = 84.75%, kappa coefficient = 0.80). Variable importance analysis shows that nDSM has the highest variable importance proportion (VIP) value, followed by RM, IM, and spectral information, indicating the feasibility of this proposed LiDAR-derived model-RM. This research presents effective methods relating to the application of aerial imagery and LiDAR-derived model for the complex suburban surface scenarios.
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Li, Rui, Kristen D. Splinter, and Stefan Felder. "LIDAR Scanning as an Advanced Technology in Physical Hydraulic Modelling: The Stilling Basin Example." Remote Sensing 13, no. 18 (September 9, 2021): 3599. http://dx.doi.org/10.3390/rs13183599.
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In hydraulic engineering, stilling basin design is traditionally carried out using physical models, conducting visual flow observations as well as point-source measurements of pressure, flow depth, and velocity at locations of design relevance. Point measurements often fail to capture the strongly varying three-dimensionality of the flows within the stilling basin that are important for the best possible design of the structure. This study introduced fixed scanning 2D LIDAR technology for laboratory-scale physical hydraulic modelling of stilling basins. The free-surface motions were successfully captured along both longitudinal and transverse directions, providing a detailed free-surface map. LIDAR-derived free-surface elevations were compared with typical point-source measurements using air–water conductivity probes, showing that the elevations measured with LIDAR consistently corresponded to locations of strongest air–water flow interactions at local void fractions of approximately 50%. The comparison of LIDAR-derived free-surface elevations with static and dynamic pressure sensors confirmed differences between the two measurement devices in the most energetic parts of the jump roller. The present study demonstrates that LIDAR technology can play an important role in physical hydraulic modelling, enabling design improvement through detailed free-surface characterization of complex air–water flow motions beyond the current practice of point measurements and visual flow observations.
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Idris, R., R. Abu Bakar, and A. R. Abdul Rasam. "LIDAR ASSESSMENTS AND MAPPING FOR KLANG VALLEY: A CASE STUDY AT JINJANG DISTRICT, SELANGOR." International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W6-2022 (February 14, 2023): 445–50. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w6-2022-445-2023.
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Abstract. Light Detection and Ranging (LiDAR) technology has become a significant factor in producing up-to-date and accurate topographic data in the current world. LiDAR technology has been used for years for many applications, including the efficient creation of digital model for large scale, high accuracy mapping. This technology offers fast, accurate, expedient and cost-effective ways of capturing wide area elevation information to produce highly detailed digital model of the earth. LiDAR is based on airborne laser scanners enables to acquire dense and accurate 3D data of the surveyed area, i.e., the Digital Surface Model (DSM). This paper presents an exploratory study to assess the accuracy of constructed DTM (Digital Terrain Model) and evaluating ground height without surface features using LiDAR Digital Surface Model (DSM). The study area comprised of an undulated area situated at Jinjang in the Klang Valley region, Malaysia covering an area of one kilometre square. LiDAR DSM and DTM constructed and derived from LiDAR were critically assessed with reference to the USGS Map Accuracy Standards. The accuracy of derived DSM and DTM were evaluated using ground control points derived from conventional surveying technique. The constructed models were accessed quantitatively and qualitatively.
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Yan, Wai, Ahmed Shaker, and Paul LaRocque. "Scan Line Intensity-Elevation Ratio (SLIER): An Airborne LiDAR Ratio Index for Automatic Water Surface Mapping." Remote Sensing 11, no. 7 (April 4, 2019): 814. http://dx.doi.org/10.3390/rs11070814.
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Owing to the characteristics of how a laser interacts with the water surface and water column, the measured Light Detection and Ranging (LiDAR) intensity values are different with respect to the laser wavelength, the scanning geometry and the reflection mechanism. Depending on the instantaneous water condition and the laser incidence angle, laser dropouts can appear, causing null returns or empty holes found in the collected LiDAR data. This variable intensity response offers a valuable opportunity for using airborne LiDAR sensors for automatic identification of water regions, and thus, we previously proposed an airborne LiDAR-based ratio index named the scan line intensity-elevation ratio (SLIER). Over the water surface, airborne LiDAR data are always found to have a high fluctuation of the intensity value and low variation of the elevation along each scan line, and thus, the water region has a higher SLIER value compared to the land. We examined the SLIER on a multispectral airborne LiDAR dataset collected by Optech Titan and a monochromatic airborne LiDAR dataset collected by Optech Galaxy on a natural rocky shore and a man-made shore. Our experiments showed that SLIER was able to provide a high separability between land and water regions and was able to outperform the traditional normalized difference water index (NDWI) for estimation of the water surface. With the use of SLIER as a mechanism for training data selection, our case studies demonstrated an overall accuracy of 98% in the use of either monochromatic or multispectral LiDAR data, regardless of the laser channel being used.
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Roncat, A., N. Pfeifer, and C. Briese. "ASSESSMENT OF BOTTOM-OF-ATMOSPHERE REFLECTANCE IN LIDAR DATA AS REFERENCE FOR HYPERSPECTRAL IMAGERY." ISPRS Annals of Photogrammetry, Remote Sensing and Spatial Information Sciences IV-2/W4 (September 13, 2017): 131–37. http://dx.doi.org/10.5194/isprs-annals-iv-2-w4-131-2017.
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While airborne lidar has confirmed its leading role in delivering high-resolution 3D topographic information during the last decade, its radiometric potential has not yet been fully exploited. However, with the increasing availability of commercial lidar systems which (a) make use of full-waveform information and (b) operate at several wavelengths simultaneously, this potential is increasing as well. Radiometric calibration of the full-waveform information mentioned before allows for the derivation of physical target surface parameters such as the backscatter coefficient and a diffuse reflectance value at bottom of atmosphere (BOA), i.e. the target surface. <br><br> With lidar being an active remote sensing technique, these parameters can be derived from lidar data itself, accompanied by the measurement or estimation of reference data for diffuse reflectance. In contrast to this, such a radiometric calibration for passive hyperspectral imagery (HSI) requires the knowledge and/or estimation of much more unknowns. However, in case of corresponding wavelength(s) radiometrically calibrated lidar datasets can deliver an areawide reference for BOA reflectance. <br><br> This paper presents criteria to check where the assumption of diffuse BOA reflectance behaviour is fulfilled and how these criteria are assessed in lidar data; the assessment is illustrated by an extended lidar dataset. Moreover, for this lidar dataset and an HSI dataset recorded over the same area, the corresponding reflectance values are compared for different surface types.
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Luo, Hui, Le Wang, Chen Wu, and Lei Zhang. "An Improved Method for Impervious Surface Mapping Incorporating LiDAR Data and High-Resolution Imagery at Different Acquisition Times." Remote Sensing 10, no. 9 (August 24, 2018): 1349. http://dx.doi.org/10.3390/rs10091349.
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Impervious surface mapping incorporating high-resolution remote sensing imagery has continued to attract increasing interest, as it can provide detailed information about urban structure and distribution. Previous studies have suggested that the combination of LiDAR data and high-resolution imagery for impervious surface mapping yields better performance than the use of high-resolution imagery alone. However, due to LiDAR data’s high cost of acquisition, it is difficult to obtain LiDAR data that was acquired at the same time as the high-resolution imagery in order to conduct impervious surface mapping by multi-sensor remote sensing data. Consequently, the occurrence of real landscape changes between multi-sensor remote sensing data sets with different acquisition times results in misclassification errors in impervious surface mapping. This issue has generally been neglected in previous works. Furthermore, observation differences that were generated from multi-sensor data—including the problems of misregistration, missing data in LiDAR data, and shadow in high-resolution images—also present obstacles to achieving the final mapping result in the fusion of LiDAR data and high-resolution images. In order to resolve these issues, we propose an improved impervious surface-mapping method incorporating both LiDAR data and high-resolution imagery with different acquisition times that consider real landscape changes and observation differences. In the proposed method, multi-sensor change detection by supervised multivariate alteration detection (MAD) is employed to identify the changed areas and mis-registered areas. The no-data areas in the LiDAR data and the shadow areas in the high-resolution image are extracted via independent classification based on the corresponding single-sensor data. Finally, an object-based post-classification fusion is proposed that takes advantage of both independent classification results while using single-sensor data and the joint classification result using stacked multi-sensor data. The impervious surface map is subsequently obtained by combining the landscape classes in the accurate classification map. Experiments covering the study site in Buffalo, NY, USA demonstrate that our method can accurately detect landscape changes and unambiguously improve the performance of impervious surface mapping.
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Zhao, Yiming, Lin Bai, Ziming Zhang, and Xinming Huang. "A Surface Geometry Model for LiDAR Depth Completion." IEEE Robotics and Automation Letters 6, no. 3 (July 2021): 4457–64. http://dx.doi.org/10.1109/lra.2021.3068885.
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Aubertin, Jonathan D., and D. Jean Hutchinson. "Scale-dependent rock surface characterization using LiDAR surveys." Engineering Geology 301 (May 2022): 106614. http://dx.doi.org/10.1016/j.enggeo.2022.106614.
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Venkata, Srikanth, and John Reagan. "Aerosol Retrievals from CALIPSO Lidar Ocean Surface Returns." Remote Sensing 8, no. 12 (December 9, 2016): 1006. http://dx.doi.org/10.3390/rs8121006.
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Palmer, A. J. "Delta-k-lidar sensing of the ocean surface." Applied Optics 31, no. 21 (July 20, 1992): 4275. http://dx.doi.org/10.1364/ao.31.004275.
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Priestnall, G., J. Jaafar, and A. Duncan. "Extracting urban features from LiDAR digital surface models." Computers, Environment and Urban Systems 24, no. 2 (March 2000): 65–78. http://dx.doi.org/10.1016/s0198-9715(99)00047-2.
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Griffiths, A. D., S. D. Parkes, S. D. Chambers, M. F. McCabe, and A. G. Williams. "Improved mixing height monitoring through a combination of lidar and radon measurements." Atmospheric Measurement Techniques 6, no. 2 (February 1, 2013): 207–18. http://dx.doi.org/10.5194/amt-6-207-2013.
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Abstract. Surface-based radon (222Rn) measurements can be combined with lidar backscatter to obtain a higher quality time series of mixing height within the planetary boundary layer (PBL) than is possible from lidar alone, and a more quantitative measure of mixing height than is possible from only radon. The reason why lidar measurements are improved is that there are times when lidar signals are ambiguous, and reliably attributing the mixing height to the correct aerosol layer presents a challenge. By combining lidar with a mixing length scale derived from a time series of radon concentration, automated and robust attribution is possible during the morning transition. Radon measurements provide mixing information during the night, but concentrations also depend on the strength of surface emissions. After processing radon in combination with lidar, we obtain nightly measurements of radon emissions and are able to normalise the mixing length scale for changing emissions. After calibration with lidar, the radon-derived equivalent mixing height agrees with other measures of mixing on daily and hourly timescales and is a potential method for studying intermittent mixing in nocturnal boundary layers.
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Arouf, Assia, Hélène Chepfer, Thibault Vaillant de Guélis, Marjolaine Chiriaco, Matthew D. Shupe, Rodrigo Guzman, Artem Feofilov, et al. "The surface longwave cloud radiative effect derived from space lidar observations." Atmospheric Measurement Techniques 15, no. 12 (July 1, 2022): 3893–923. http://dx.doi.org/10.5194/amt-15-3893-2022.
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Abstract. Clouds warm the surface in the longwave (LW), and this warming effect can be quantified through the surface LW cloud radiative effect (CRE). The global surface LW CRE has been estimated over more than 2 decades using space-based radiometers (2000–2021) and over the 5-year period ending in 2011 using the combination of radar, lidar and space-based radiometers. Previous work comparing these two types of retrievals has shown that the radiometer-based cloud amount has some bias over icy surfaces. Here we propose new estimates of the global surface LW CRE from space-based lidar observations over the 2008–2020 time period. We show from 1D atmospheric column radiative transfer calculations that surface LW CRE linearly decreases with increasing cloud altitude. These computations allow us to establish simple parameterizations between surface LW CRE and five cloud properties that are well observed by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) space-based lidar: opaque cloud cover and altitude and thin cloud cover, altitude, and emissivity. We evaluate this new surface LWCRE–LIDAR product by comparing it to existing satellite-derived products globally on instantaneous collocated data at footprint scale and on global averages as well as to ground-based observations at specific locations. This evaluation shows good correlations between this new product and other datasets. Our estimate appears to be an improvement over others as it appropriately captures the annual variability of the surface LW CRE over bright polar surfaces and it provides a dataset more than 13 years long.
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O’Connor, Christopher S., and Ryan S. Mieras. "Beach Profile, Water Level, and Wave Runup Measurements Using a Standalone Line-Scanning, Low-Cost (LLC) LiDAR System." Remote Sensing 14, no. 19 (October 6, 2022): 4968. http://dx.doi.org/10.3390/rs14194968.
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A prototype rapidly deployable, Line-scanning, Low-Cost (LLC) LiDAR system (USD 400 per unit; 2020) was developed to measure coastal hydro-morphodynamic processes. A pilot field study was conducted at the U.S. Army Corps of Engineers, Field Research Facility (FRF) in Duck, North Carolina, USA to evaluate the efficacy of the LLC LiDAR in measuring beach morphology, wave runup, and free-surface elevations against proven approaches. A prototype LLC LiDAR collected continuous cross-shore line scans for 25 min of every half hour, at ~7 revolutions/s and ~1.3° angular resolution, at two locations (one day at each location), spanning 12 m (i) on the backshore berm (35 scans; Series B) and (ii) in the swash/inner surf zone (28 scans; Series C). LLC LiDAR time-averaged beach profiles and wave runup estimates were compared with the same quantities derived from the continuously sampling terrestrial LiDAR scanner installed atop the dune at the FRF (DUNE LiDAR). The average root-mean-square difference (RMSD) between 17 (6) time-averaged LLC and DUNE LiDAR beach profiles was 0.045 m (0.031 m) with a standard deviation of 0.004 m (0.002 m) during Series B (Series C). Small-scale (cm) swash zone bed level changes were resolved over 5-min increments with the LLC LiDAR. The RMSD between LLC- and DUNE LiDAR-derived wave runup excursions over two 25-min segments was 0.542 m (cross-shore) and 0.039 m (elevation) during the rising tide and 0.366 m (cross-shore) and 0.032 m (elevation) during the falling tide. Between 72–79% of the LLC LiDAR wave runup data were more accurate than the RMSD values, thereby demonstrating the LLC LiDAR is an effective, low-cost instrument for measuring wave runup and morphodynamic processes. Co-located water levels were measured with a continuously sampling (16 Hz) RBRsolo3 D|wave16 pressure logger during Series C. LLC LiDAR free-surface elevations at the nadir during one high tide (4.5 h) compared well with pressure-derived free-surface elevations (RMSD = 0.024 m, R2 = 0.85).
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Weaver, C., C. Kiemle, S. R. Kawa, T. Aalto, J. Necki, M. Steinbacher, J. Arduini, F. Apadula, H. Berkhout, and J. Hatakka. "Retrieval of methane source strengths in Europe using a simple modeling approach to assess the potential of spaceborne lidar observations." Atmospheric Chemistry and Physics 14, no. 5 (March 14, 2014): 2625–37. http://dx.doi.org/10.5194/acp-14-2625-2014.
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Abstract. We investigate the sensitivity of future spaceborne lidar measurements to changes in surface methane emissions. We use surface methane observations from nine European ground stations and a Lagrangian transport model to infer surface methane emissions for 2010. Our inversion shows the strongest emissions from the Netherlands, the coal mines in Upper Silesia, Poland, and wetlands in southern Finland. The simulated methane surface concentrations capture at least half of the daily variability in the observations, suggesting that the transport model is correctly simulating the regional transport pathways over Europe. With this tool we can test whether proposed methane lidar instruments will be sensitive to changes in surface emissions. We show that future lidar instruments should be able to detect a 50% reduction in methane emissions from the Netherlands and Germany, at least during summer.
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Hu, Y., K. Stamnes, M. Vaughan, J. Pelon, C. Weimer, D. Wu, M. Cisewski, et al. "Sea surface wind speed estimation from space-based lidar measurements." Atmospheric Chemistry and Physics Discussions 8, no. 1 (February 12, 2008): 2771–93. http://dx.doi.org/10.5194/acpd-8-2771-2008.
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Abstract. Global satellite observations of lidar backscatter measurements acquired by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) mission and collocated sea surface wind speed data from the Advanced Microwave Scanning Radiometer for the Earth Observing System (AMSR-E), are used to investigate the relation between wind driven wave slope variance and sea surface wind speed. The new slope variance – wind speed relation established from this study is similar to the linear relation from Cox-Munk (1954) and the log-linear relation from Wu (1972, 1990) for wind speed larger than 7 m/s and 13.3 m/s, respectively. For wind speed less than 7 m/s, the slope variance is proportional to the square root of the wind speed, assuming a two dimensional isotropic Gaussian wave slope distribution. This slope variance – wind speed relation becomes linear if a one dimensional Gaussian wave slope distribution is assumed. Contributions from whitecaps and subsurface backscattering are effectively removed by using 532 nm lidar depolarization measurements. This new slope variance – wind speed relation is used to derive sea surface wind speed from CALIPSO single shot lidar measurements (70 m spot size), after correcting for atmospheric attenuation. The CALIPSO wind speed result agrees with the collocated AMSR-E wind speed, with 1.2 m/s rms error.
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Wang, Cuizhen, Grayson R. Morgan, and James T. Morris. "Drone Lidar Deep Learning for Fine-Scale Bare Earth Surface and 3D Marsh Mapping in Intertidal Estuaries." Sustainability 15, no. 22 (November 10, 2023): 15823. http://dx.doi.org/10.3390/su152215823.
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Tidal marshes are dynamic environments providing important ecological and economic services in coastal regions. With accelerating climate change and sea level rise (SLR), marsh mortality and wetland conversion have been observed on global coasts. For sustainable coastal management, accurate projection of SLR-induced tidal inundation and flooding requires fine-scale 3D terrain of the intertidal zones. The airborne Lidar systems, although successful in extracting terrestrial topography, suffer from high vertical uncertainties in coastal wetlands due to tidal effects. This study tests the feasibility of drone Lidar leveraging deep learning of point clouds on 3D marsh mapping. In an ocean-front, pristine estuary dominated by Spartina alterniflora, drone Lidar point clouds, and in-field marsh samples were collected. The RandLA-Net deep learning model was applied to classify the Lidar point cloud to ground, low vegetation, and high vegetation with an overall accuracy of around 0.84. With the extracted digital terrain model and digital surface model, the cm-level bare earth surfaces and marsh heights were mapped. The bare earth terrain reached a vertical accuracy (root-mean-square error, or RMSE) of 5.55 cm. At the 65 marsh samples, the drone Lidar-extracted marsh height was lower than the in-field height measurements. However, their strongly significantly linear relationship (Pearson’s r = 0.93) reflects the validity of the drone Lidar for measuring marsh canopy height. The adjusted Lidar-extracted marsh height had an RMSE of 0.12 m. This experiment demonstrates a multi-step operational procedure to deploy drone Lidar for accurate, fine-scale terrain and 3D marsh mapping, which provides essential base layers for projecting wetland inundation in various climate change and SLR scenarios.
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Salles, Roberto Neves, Haroldo Fraga de Campos Velho, and Elcio Hideiti Shiguemori. "Automatic Position Estimation Based on Lidar × Lidar Data for Autonomous Aerial Navigation in the Amazon Forest Region." Remote Sensing 14, no. 2 (January 13, 2022): 361. http://dx.doi.org/10.3390/rs14020361.
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In this paper we post-process and evaluate the position estimation of pairs of template windows and geo-referenced images generated from LiDAR cloud point data using the Normalized Cross-Correlation (NCC) method. We created intensity, surface and terrain pairs of images for use with template matching, with 5 m pixel spacing, through binning. We evaluated square and circular binning approaches, without filtering the original data. Template matching achieved approximately 7 m root mean square error (RMSE) on intensity and surface templates on the respective geo-referenced images, while on terrain templates it had many mismatches due to insufficient terrain features over the assumed flight transect. Analysis of NCC showed the possibility of rejecting bad matches of intensity and surface templates, but terrain templates required an additional criteria of flatness for rejection. The combined NCC of intensity, surface and terrain proved stable for rejection of bad matches and had the lowest RMSE. Filtering outliers from surface images changed very little the accuracy of the matches, but greatly improved correlation values, indicating that the forest canopy might have the best features for geo-localization with template matching. Position estimation is essential for autonomous navigation of aerial vehicles and the these experiments with LiDAR data show potential for localization over densely forested regions where methods using optical camera data may fail to acquire distinguishable features.
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Damodaran, Deeptha, Saeed Mozaffari, Shahpour Alirezaee, and Mohammed Jalal Ahamed. "Experimental Analysis of the Behavior of Mirror-like Objects in LiDAR-Based Robot Navigation." Applied Sciences 13, no. 5 (February 24, 2023): 2908. http://dx.doi.org/10.3390/app13052908.
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Mobile robots are equipped with various sensors to perform object detection, localization, and navigation. Among these sensors, LiDAR (light detection and ranging) is the most widely used sensor for environment map creation. However, LiDAR-based localization is challenging in modern environments containing specular surfaces, such as mirrors and glasses, that cause light reflection, penetration, or diffusion. These conditions make the obtained map inaccurate, unreliable, and noisy. This paper presents the effects of mirror-like objects in various indoor arrangements on 2D LiDAR-based maps. Experiments were conducted using a mobile robot equipped with LiDAR navigating in an environment with several mirrors. Experiments suggest that laser scans may be fully reflected off mirrors, causing no range or intensity data and creating a faulty map. Objects or boundaries within the range of LiDAR may be mapped behind the surface of the mirror, and robot self-detection may occur on the surface of the mirror. This situation exacerbates when more than one mirror is present in the environment. The results presented in this paper can aid the development of LiDAR-based indoor navigation to identify and remove inconsistencies created in LiDAR maps due to mirror-like objects.
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Gobbi, G. P., F. Barnaba, R. van Dingenen, J. P. Putaud, M. Mircea, and M. C. Facchini. "Lidar and in situ observations of continental and Saharan aerosol: closure analysis of particles optical and physical properties." Atmospheric Chemistry and Physics Discussions 3, no. 1 (February 3, 2003): 445–77. http://dx.doi.org/10.5194/acpd-3-445-2003.
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Abstract. Single wavelength polarization lidar observations collected at Mt. Cimone (44.2° N, 10.7° E, 1870 m a.s.l.) during the June 2000 MINATROC campaign are analyzed to derive tropospheric profiles of aerosol extinction, depolarization, surface area and volume. Lidar retrievals for the 2170–2245 m level are compared to the same variables as computed from in situ measurements of particles size distributions, performed at the mountain top Station (2165 m a.s.l.) by a differential mobility analyzer (DMA) and an optical particle counter (OPC). A sensitivity analysis of this closure experiment shows that mean relative differences between the backscatter coefficients obtained by the two techniques undergo a 30% decrease when hygroscopic growth to ambient humidity is considered for the DMA dataset, otherwise representative of dry aerosols. Minimization of differences between lidar and size distribution-derived backscatter coefficients allowed to find values of the "best" refractive index, specific to each measurement. These results show the refractive index to increase for air masses proceeding from either continental Europe or Africa with respect to Mediterranean air. Lidar depolarization was observed to minimize mainly in airmasses proceeding from Western Europe, thus indicating a spherical, i.e. liquid nature for such aerosols. This analysis shows average relative differences between lidar and in-situ observations of 10% for backscatter, 37% for extinction and 44% for surface area and volume. These values are within the expected combined errors of the lidar and in situ retrievals. However, average differences strongly decrease during the Saharan dust transport event, when a lidar signal inversion model considering non-spherical scatterers is employed. The closure obtained between particle counter and lidar-derived aerosol surface area and volume constitutes a validation of the technique providing the latter estimates on the basis of single-wavelength lidar observations.
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Gobbi, G. P., F. Barnaba, R. Van Dingenen, J. P. Putaud, M. Mircea, and M. C. Facchini. "Lidar and in situ observations of continental and Saharan aerosol: closure analysis of particles optical and physical properties." Atmospheric Chemistry and Physics 3, no. 6 (December 5, 2003): 2161–72. http://dx.doi.org/10.5194/acp-3-2161-2003.
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Abstract. Single wavelength polarization lidar observations collected at Mt. Cimone (44.2º N, 10.7º E, 1870 m a.s.l.) during the June 2000 MINATROC campaign are analyzed to derive tropospheric profiles of aerosol extinction, depolarization, surface area and volume. Lidar retrievals for the 2170-2245 m level are compared to the same variables as computed from in situ measurements of particles size distributions, performed at the mountain top Station (2165 m a.s.l.) by a differential mobility analyzer (DMA) and an optical particle counter (OPC). A sensitivity analysis of this closure experiment shows that mean relative differences between the backscatter coefficients obtained by the two techniques undergo a sharp decrease when hygroscopic growth to ambient humidity is considered for the DMA dataset, otherwise representative of dry aerosols. Minimization of differences between lidar and size distribution-derived backscatter coefficients allowed to find values of the "best" refractive index, specific to each measurement. These results show the refractive index to increase for air masses proceeding from Africa and Western Europe. Lidar depolarization was observed to minimize mainly in airmasses proceeding from Western Europe, thus indicating a spherical, i.e. liquid nature for such aerosols. Conversely, African, Mediterranean and East Europe aerosol showed a larger depolarizing fraction, mainly due to coexisting refractory and soluble fractions. The analysis shows average relative differences between lidar and in-situ observations of 5% for backscatter, 36% for extinction 41% for surface area and 37% for volume. These values are well within the expected combined uncertainties of the lidar and in situ retrievals. Average differences further decrease during the Saharan dust transport event, when a lidar signal inversion model considering non-spherical scatterers is employed. The quality of the closure obtained between particle counter and lidar-derived aerosol surface area and volume observations constitutes a validation of the technique adopted to retrieve such aerosol properties on the basis of single-wavelength lidar observations.
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Mann, J., A. Peña, F. Bingöl, R. Wagner, and M. S. Courtney. "Lidar Scanning of Momentum Flux in and above the Atmospheric Surface Layer." Journal of Atmospheric and Oceanic Technology 27, no. 6 (June 1, 2010): 959–76. http://dx.doi.org/10.1175/2010jtecha1389.1.
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Abstract Methods to measure the vertical flux of horizontal momentum using both continuous wave and pulsed Doppler lidar profilers are evaluated. The lidar measurements are compared to momentum flux observations performed with sonic anemometers over flat terrain at Høvsøre, Denmark, and profile-derived vertical momentum flux observations at the Horns Rev wind farm in the North Sea. Generally, the momentum fluxes are reduced because of the finite measuring volume of the instruments, and the filtering is crudely accounted for theoretically. The essential parameter for the estimation of the reduction is the ratio of the turbulence scale to the size of the measuring volume. For the continuous wave lidar the reduction can largely be compensated by averaging Doppler spectra instead of radial velocities.
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Li, Xiaolu, and Yu Liang. "Remote measurement of surface roughness, surface reflectance, and body reflectance with LiDAR." Applied Optics 54, no. 30 (October 15, 2015): 8904. http://dx.doi.org/10.1364/ao.54.008904.
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Zheng, X., and C. Xiao. "TYPICAL APPLICATIONS OF AIRBORNE LIDAR TECHNOLAGY IN GEOLOGICAL INVESTIGATION." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (May 2, 2018): 2459–63. http://dx.doi.org/10.5194/isprs-archives-xlii-3-2459-2018.
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The technology of airborne light detection and ranging (LiDAR), also referred to as Airborne Laser Scanning, is widely used for high-resolution topographic data acquisition (even under forest cover) with sub-meter planimetric and vertical accuracy. This contribution constructs the real digital terrain model to provide the direct observation data for the landscape analysis in geological domains. Based on the advantage of LiDAR, the authors mainly deal with the applications of LiDAR data to such fields as surface land collapse, landslide and fault structure extraction. The review conclusion shows that airborne LiDAR technology is becoming an indispensable tool for above mentioned issues, especially in the local and large scale investigations of micro-topography. The technology not only can identify the surface collapse, landslide boundary and subtle faulted landform, but also be able to extract the filling parameters of collapsed surface, the geomorphic parameters of landslide stability evaluation and cracks. This technology has extensive prospect of applications in geological investigation.
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Zlinszky, A., G. Timár, R. Weber, B. Székely, C. Briese, C. Ressl, and N. Pfeifer. "Observation of a local gravity isosurface by airborne LIDAR of Lake Balaton, Hungary." Solid Earth Discussions 6, no. 1 (January 14, 2014): 119–44. http://dx.doi.org/10.5194/sed-6-119-2014.
Full textAbstract:
Abstract. Airborne LIDAR (Light Detection and Ranging) is a remote sensing method commonly used for mapping surface topography in high resolution. A water surface in hydrostatic equilibrium theoretically represents a gravity isosurface. Here we compare LIDAR-based ellipsoidal water surface height measurements all around the shore of a major lake with a local high resolution geoid model. The ellipsoidal heights of the 87 km2 we sampled all around the shore of the 597 km2 lake surface vary by 0.8 m and strong spatial correlation with the geoid undulation was calculated (R2=0.91). After subtraction of the local geoid undulation from the measured ellipsoidal water surface heights, their variation was considerably reduced. This demonstrates that the water surface heights of the lake were truly determined by the local gravity potential. We conclude that the accuracy of airborne LIDAR is sufficient for identifying the spatial variations of gravity potential over large inland water surfaces.
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Khattak, Aemal J., Shauna Hallmark, and Reginald Souleyrette. "Application of Light Detection and Ranging Technology to Highway Safety." Transportation Research Record: Journal of the Transportation Research Board 1836, no. 1 (January 2003): 7–15. http://dx.doi.org/10.3141/1836-02.
Full textAbstract:
An application of light detection and ranging (LIDAR) technology to highway intersection safety is presented. LIDAR can be used to collect information about a surface by reflecting thousands of light beams per second off the surface and measuring the return time of the beams. The surface profile is collected as a digital signature that can be used in a variety of applications. Collection of information on the surface profile of the earth in the form of elevation data is one of several LIDAR applications that have been used for mapping and contouring. The focus of the described application is use of LIDAR elevation data to obtain information on intersection geometry that can lead to the discovery of potential obstructions in driver sight lines. After appropriate transformations, LIDAR elevation data were used in line-of-sight analysis to obtain information on sight-line obstructions at six intersections on the IA-1 corridor in Iowa. Intersection crash frequency and data availability were considerations in the selection of the six intersections. Results from the line-of-sight analysis were validated by visits to the intersections in the field and verification of the existence of obstructions detected during the analysis. Sixty-six lines of sight were blocked during the line-of-sight analysis, of which 62 (89.8%) were confirmed during the validation process. Four (5.8%) sight-line obstructions were not confirmed during the validation. At least three (4.4%) potential sight-line obstructions discovered during validation were not detected during the line-of-sight analysis. The intersection with the highest crash frequency was correctly found to have obstructions located within the intersection sight triangles. It can be concluded that LIDAR elevation data can be used successfully for identifying potential sight-distance problems at intersections. Identified potential problems can be verified and rectified in the field. LIDAR is a relatively costly data source, and a single application, such as this one, cannot justify the high cost of LIDAR data acquisition. Other potential highway safety enhancing applications of LIDAR must be investigated to offset the high data-acquisition cost. Suggestions for other highway safety applications are provided.