Relevant bibliographies by topics / DEM-LIDAR

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Academic literature on the topic 'DEM-LIDAR'

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Published: 24 April 2022

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Journal articles on the topic "DEM-LIDAR"

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Xiaoye Liu. "Airborne LiDAR for DEM generation: some critical issues." Progress in Physical Geography: Earth and Environment 32, no. 1 (February 2008): 31–49. http://dx.doi.org/10.1177/0309133308089496.

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Airborne LiDAR is one of the most effective and reliable means of terrain data collection. Using LiDAR data for digital elevation model (DEM) generation is becoming a standard practice in spatial related areas. However, the effective processing of the raw LiDAR data and the generation of an efficient and high-quality DEM remain big challenges. This paper reviews the recent advances of airborne LiDAR systems and the use of LiDAR data for DEM generation, with special focus on LiDAR data filters, interpolation methods, DEM resolution, and LiDAR data reduction. Separating LiDAR points into ground and non-ground is the most critical and difficult step for DEM generation from LiDAR data. Commonly used and most recently developed LiDAR filtering methods are presented. Interpolation methods and choices of suitable interpolator and DEM resolution for LiDAR DEM generation are discussed in detail. In order to reduce the data redundancy and increase the efficiency in terms of storage and manipulation, LiDAR data reduction is required in the process of DEM generation. Feature specific elements such as breaklines contribute significantly to DEM quality. Therefore, data reduction should be conducted in such a way that critical elements are kept while less important elements are removed. Given the high-density characteristic of LiDAR data, breaklines can be directly extracted from LiDAR data. Extraction of breaklines and integration of the breaklines into DEM generation are presented.
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Octariady, J., A. Hikmat, E. Widyaningrum, R. Mayasari, and M. K. Fajari. "VERTICAL ACCURACY COMPARISON OF DIGITAL ELEVATION MODEL FROM LIDAR AND MULTITEMPORAL SATELLITE IMAGERY." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-1/W1 (May 31, 2017): 419–23. http://dx.doi.org/10.5194/isprs-archives-xlii-1-w1-419-2017.

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Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo satellite imagery DEM. Multitemporal stereo satellite imagery generated semi-automatically by using 3 scene stereo satellite imagery with acquisition 2013–2014. The high value given each of DEM serve as the basis for calculating high accuracy DEM respectively. The results showed the high value differences in the fraction of the meter between LiDAR DEM and multitemporal stereo satellite imagery DEM.
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Cao, Hong, Zhao Pan, Qixin Chang, Aiguo Zhou, Xu Wang, and Ziyong Sun. "Stream Network Modeling Using Remote Sensing Data in an Alpine Cold Catchment." Water 13, no. 11 (June 4, 2021): 1585. http://dx.doi.org/10.3390/w13111585.

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The hydrological information derived from a digital elevation model is very important in distributed hydrological modeling. As part of alpine hydrological research on stream network modeling using remote sensing data in the northeast of the Tibetan Plateau, three digital elevation model (DEM) datasets were obtained for the purpose of hydrological features, mainly including channel network, watershed extent and terrain character. The data sources include the airborne light detection and ranging (LiDAR) with point spacing of 1 m, the High Mountain Asia (HMA) DEM and the Shuttle Radar Topography Mission (SRTM) DEM. Mapping of the watershed and stream network was conducted using each of the three DEM datasets. The modeled stream networks using the different DEMs were verified against the actual network mapped in the field. The results show that the stream network derived from the LiDAR DEM was the most accurate representation of the network mapped in the field. The SRTM DEM overestimated the basin hypsometry relative to the LiDAR watershed at the lowest elevation, while the HMA DEM underestimated the basin hypsometry relative to the LiDAR watershed at the highest elevation. This may be because, compared with the SRTM DEM and the HMA DEM, the LiDAR DEM has higher initial point density, accuracy and resolution. It can be seen that the LiDAR data have great potential for the application in hydrologic modeling and water resource management in small alpine catchments.
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Muhadi, Nur Atirah, Ahmad Fikri Abdullah, Siti Khairunniza Bejo, Muhammad Razif Mahadi, and Ana Mijic. "The Use of LiDAR-Derived DEM in Flood Applications: A Review." Remote Sensing 12, no. 14 (July 18, 2020): 2308. http://dx.doi.org/10.3390/rs12142308.

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Flood occurrence is increasing due to escalated urbanization and extreme climate change; hence, various studies on this issue and methods of flood monitoring and mapping are also increasing to reduce the severe impacts of flood disasters. The advancement of current technologies such as light detection and ranging (LiDAR) systems facilitated and improved flood applications. In a LiDAR system, a laser emits light that travels to the ground and reflects off objects like buildings and trees. The reflected light energy returns to the sensor, whereby the time interval is recorded. Since the conventional methods cannot produce high-resolution digital elevation model (DEM) data, which results in low accuracy of flood simulation results, LiDAR data are extensively used as an alternative. This review aims to study the potential and the applications of LiDAR-derived DEM in flood studies. It also provides insight into the operating principles of different LiDAR systems, system components, and advantages and disadvantages of each system. This paper discusses several topics relevant to flood studies from a LiDAR-derived DEM perspective. Furthermore, the challenges and future perspectives regarding DEM LiDAR data for flood mapping and assessment are also reviewed. This study demonstrates that LiDAR-derived data are useful in flood risk management, especially in the future assessment of flood-related problems.
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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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Kang, C. L., M. M. Zong, Y. Cheng, F. Wang, T. N. Lu, and G. Z. Liu. "RESEARCH ON CONSTRUCTING DEM WITH POINT CLOUD FILTERING ALGORITHM CONSIDERING SPECIAL TERRAIN." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W10 (February 7, 2020): 211–14. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w10-211-2020.

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Abstract. With the development of airborne LiDAR, the use of LiDAR point cloud to construct DEM model is a hot topic in recent years. For the characteristics of time cloud filtering and poor validity, and the efficiency of non-ground point filtering is not high, the filtered point cloud has problems such as errors and leaks. This paper proposes a method of constructing DEM based on the point cloud filtering algorithm of airborne Lidar point cloud data considering special terrain. The experiment proves that the algorithm of this paper is effective for establishing DEM model, and the quality of DEM model is good.
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Jakovljevic, Gordana, Miro Govedarica, Flor Alvarez-Taboada, and Vladimir Pajic. "Accuracy Assessment of Deep Learning Based Classification of LiDAR and UAV Points Clouds for DTM Creation and Flood Risk Mapping." Geosciences 9, no. 7 (July 23, 2019): 323. http://dx.doi.org/10.3390/geosciences9070323.

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Digital elevation model (DEM) has been frequently used for the reduction and management of flood risk. Various classification methods have been developed to extract DEM from point clouds. However, the accuracy and computational efficiency need to be improved. The objectives of this study were as follows: (1) to determine the suitability of a new method to produce DEM from unmanned aerial vehicle (UAV) and light detection and ranging (LiDAR) data, using a raw point cloud classification and ground point filtering based on deep learning and neural networks (NN); (2) to test the convenience of rebalancing datasets for point cloud classification; (3) to evaluate the effect of the land cover class on the algorithm performance and the elevation accuracy; and (4) to assess the usability of the LiDAR and UAV structure from motion (SfM) DEM in flood risk mapping. In this paper, a new method of raw point cloud classification and ground point filtering based on deep learning using NN is proposed and tested on LiDAR and UAV data. The NN was trained on approximately 6 million points from which local and global geometric features and intensity data were extracted. Pixel-by-pixel accuracy assessment and visual inspection confirmed that filtering point clouds based on deep learning using NN is an appropriate technique for ground classification and producing DEM, as for the test and validation areas, both ground and non-ground classes achieved high recall (>0.70) and high precision values (>0.85), which showed that the two classes were well handled by the model. The type of method used for balancing the original dataset did not have a significant influence in the algorithm accuracy, and it was suggested not to use any of them unless the distribution of the generated and real data set will remain the same. Furthermore, the comparisons between true data and LiDAR and a UAV structure from motion (UAV SfM) point clouds were analyzed, as well as the derived DEM. The root mean square error (RMSE) and the mean average error (MAE) of the DEM were 0.25 m and 0.05 m, respectively, for LiDAR data, and 0.59 m and –0.28 m, respectively, for UAV data. For all land cover classes, the UAV DEM overestimated the elevation, whereas the LIDAR DEM underestimated it. The accuracy was not significantly different in the LiDAR DEM for the different vegetation classes, while for the UAV DEM, the RMSE increased with the height of the vegetation class. The comparison of the inundation areas derived from true LiDAR and UAV data for different water levels showed that in all cases, the largest differences were obtained for the lowest water level tested, while they performed best for very high water levels. Overall, the approach presented in this work produced DEM from LiDAR and UAV data with the required accuracy for flood mapping according to European Flood Directive standards. Although LiDAR is the recommended technology for point cloud acquisition, a suitable alternative is also UAV SfM in hilly areas.
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Szypuła, Bartłomiej. "Quality assessment of DEM derived from topographic maps for geomorphometric purposes." Open Geosciences 11, no. 1 (November 30, 2019): 843–65. http://dx.doi.org/10.1515/geo-2019-0066.

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Abstract Digital elevation models (DEMs) play a significant role in geomorphological research. For geomorphologists reconstructing landform and drainage structure is frequently as important as elevation accuracy. Consequently, large-scale topographic maps (with contours, height points and watercourses) constitute excellent material for creating models (here called Topo-DEM) in fine resolution. The purpose of the conducted analyses was to assess the quality of Topo-DEM against freely-available global DEMs and then to compare it with a reference model derived from laser scanning (LiDAR-DEM). The analysis also involved derivative maps of geomorphometric parameters (local relief, slope, curvature, aspect) generated on the basis of Topo-DEM and LiDAR-DEM. Moreover, comparative classification of landforms was carried out. It was indicated that Topo-DEM is characterised by good elevation accuracy (RMSE <2 m) and reflects the topography of the analyzed area surprisingly well. Additionally, statistical and percentage metrics confirm that it is possible to generate a DEM with very good quality parameters on the basis of a large-scale topographic map (1:10,000): elevation differences between Topo-DEM and: 1) topographic map amounted from−1.68 to +2.06 m,MAEis 0.10 m, RMSE 0.16 m; 2) LiDAR-DEM (MAE 1.13 m, RMSE 1.69 m, SD 1.83 m); 3) GPS RTK measurements amounted from−3.6 to +3.01 m, MAE is 0.72 m, RMSE 0.97 m, SD 0.97 m. For an area of several dozen km2 Topo-DEM with 10×10 m resolution proved more efficient than detailed (1×1 m) LiDAR-DEM.
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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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Gökgöz, Türkay, and Moustafa Baker. "Large Scale Landform Mapping Using Lidar DEM." ISPRS International Journal of Geo-Information 4, no. 3 (August 7, 2015): 1336–45. http://dx.doi.org/10.3390/ijgi4031336.

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Dissertations / Theses on the topic "DEM-LIDAR"

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Rangelova, Sandra. "Methods for assessing the consistency of the New National Height Model." Thesis, KTH, Fastigheter och byggande, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-299788.

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Digital Elevation Models (DEM) are a simple representation of the Earth’s surface. DEMs play an important role in the field of remote sensing and GIS and are used as basis for mapping and analysis for a vest majority of scientific applications. There are many ways of producing DEMs, however the direct geo-referencing technology has made Airborne Laser Scanning (ALS) a preferred technology for the acquisition of accurate surface models over broad areas. ALS uses LiDAR (Light Detection and Ranging) which uses light in a form of pulsed laser to measure distances. Before the introduction of the DEM called Ny Nationell Höjdmodell (NNH), the highest level of height data over Sweden was the GSD-altitude data (Geographical Sweden Data). The NNH was a project by Lantmäteriet, where between 2009-2019 the entire Sweden was laser scanned. The product was a new height model called Laser Data NH with positional accuracy of 0,1 m in height and relative accuracy of 0,15 m. This project focuses on testing few methods for consistency assessment between the overlapping strips using linear features. Linear features are extracted for each overlapping area, based on intersection between planar patches extracted from gable rooftops. The first method of this study computes the distance between the overlapping areas without linear features, using two approaches: cloud-to-cloud distance and mesh-to-cloud distance. The second method computes the transformation shifts and rotations needed for the linear features to align by registering the strips with both levelled and not levelled registration. In the third method, distances and angles are measured between the lines, to further analyze how well the strips fit together. The distances are measured as distance between a mid-point of one line in the first LiDAR strip and the line on the second LiDAR strip, for all linear features. The distances were measures both as 3D distances and separately as horizontal and vertical distances. As a final step a hypothesis testing was performed to determine whether the distances and angles between the lines are significant or whether any systematic error is present in the point cloud. Based on the results obtained from the first method, significant distance between the point clouds was obtained. The results from the mesh-to-cloud distance yielded better result with higher uncertainty. According to the second method significant distances between the linear features were obtained based on the registration. The mean absolute error of the registrations showed an error at a dm level, with a minimal rotation in the vertical plane for the coalignment for the levelled registration. The third method showed a mean distance between the linear features of 20 cm. Moreover, this method showed a significant inconsistence between the linear features in the vertical plane based on the high standard uncertainty.
Digitala höjdmodeller (DEM) är en enkel representation av jordens yta. DEM spelar en viktig roll inom fjärranalys och GIS och används som grund för kartläggning och analys för en majoritet av vetenskapliga tillämpningar. Det finns många sätt att producera DEM, men den direkta georefereringstekniken har gjort Airborne Laser Scanning (ALS) till en föredragen teknik för förvärv av exakta ytmodeller över breda områden. ALS använder LiDAR (Light Detection and Ranging) som använder ljus i form av pulserande laser för att mäta avstånd. Före introduktionen av Ny Nationell Höjdmodell (NNH) var den högsta nivån av höjddata över Sverige GSD-höjddata (Geographical Sweden Data). NNH var ett projekt av Lantmäteriet, där mellan 2009-2019 laserscannades hela Sverige. Produkten var en ny höjdmodell som heter Laserdata NH med positionsnoggrannhet på 0,1 m i höjd och relativ noggrannhet på 0,15 m. Detta projekt fokuserar på att testa få metoder för konsekvensbedömning mellan de överlappande remsorna med hjälp av linjära funktioner. Linjära funktioner extraheras för varje överlappande område, baserat på skärningspunkten mellan plana fläckar extraherade från gaveltak. Den första metoden för denna studie beräknar avståndet mellan de överlappande områdena utan linjära funktioner, med två metoder: moln-till-moln-avstånd och nät-till-moln-avstånd. Den andra metoden beräknar de transformationsförskjutningar och rotationer som behövs för att de linjära särdragen ska kola genom att registrera remsorna med både nivellerad och inte nivellerad registrering. I den tredje metoden mäts avstånd och vinklar mellan linjerna, för att ytterligare analysera hur bra remsorna passar ihop. Avstånden mäts som avstånd mellan en mittpunkt på en linje i den första LiDAR-remsan och linjen på den andra LiDAR-remsan, för alla linjära funktioner. Avstånden var mått både som 3D -avstånd och separat som horisontella och vertikala avstånd. Som ett sista steg utfördes en hypotesprovning för att avgöra om avstånden och vinklarna mellan linjerna är signifikanta eller om det finns något systematiskt fel i punktmolnet. Baserat på resultaten från den första metoden erhölls ett betydande avstånd mellan punktmolnen. Resultaten från mask-till-moln-avståndet gav bättre resultat med högre osäkerhet. Enligt den andra metoden erhölls betydande avstånd mellan de linjära särdragen baserat på registreringen. Det genomsnittliga absoluta felet för registreringarna visade ett fel på en dm -nivå, med en minimal rotation i det vertikala planet för samlinjering för den jämnade registreringen. Den tredje metoden visade ett medelavstånd mellan de linjära särdragen på 20 cm. Dessutom visade denna metod en signifikant inkonsekvens mellan de linjära särdragen i det vertikala planet baserat på hög standardosäkerhet.
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Gadre, Mandar M. "Automated building footprint extraction from high resolution LIDAR DEM imagery." Diss., Columbia, Mo. : University of Missouri-Columbia, 2005. http://hdl.handle.net/10355/4320.

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Thesis (M.S.)--University of Missouri-Columbia, 2005.
The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file viewed on (July 13, 2006) Includes bibliographical references.
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Gagné, Marissa Marlene. "An Analysis and Critique of DEM Creaion and 3-D Modeling Using Airborne LIDAR and Photogrammetric Techniques." Thesis, Virginia Tech, 2001. http://hdl.handle.net/10919/43528.

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Three-dimensional (3D) visualization is rapidly becoming an important tool for many engineering projects. Accurate digital representations of terrain and ground features are extremely useful for efficient design, communication and data representation in projects involving land development, transportation planning, hydrologic analysis, environmental impact studies, and much more. Within the scope of terrain modeling lie a wide variety of techniques used to build digital elevation models (DEMs). Each approach has inherent problems and difficulties that can alter the accuracy and usability of the DEM produced. The main objectives of this study are to examine the various methods used for the creation of digital elevation models and make recommendations as to the appropriate techniques to use depending on specific project circumstances. Data sets generated using two of the methods, photogrammetry and LIDAR, are used to build digital terrain models in various software packages for an analysis of data usability and function. The key results of this research project are two DEMs of a real-world transportation study area and a set of conclusions and recommendations that give insight into the exact methods to be used on various projects. The paper ends with two short appendices, the first of which discusses several software packages and their effectiveness in DEM creation and 3-D modeling. The final appendix is a flow chart summarizing the recommendations for the seven DEM creation methods.
Master of Science
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Popescu, Sorin Cristian. "Estimating Plot-Level Forest Biophysical Parameters Using Small-Footprint Airborne Lidar Measurements." Diss., Virginia Tech, 2002. http://hdl.handle.net/10919/27109.

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The main study objective was to develop robust processing and analysis techniques to facilitate the use of small-footprint lidar data for estimating forest biophysical parameters measuring individual trees identifiable on the three-dimensional lidar surface. This study derived the digital terrain model from lidar data using an iterative slope-based algorithm and developed processing methods for directly measuring tree height, crown diameter, and stand density. The lidar system used for this study recorded up to four returns per pulse, with an average footprint of 0.65 m and an average distance between laser shots of 0.7 m. The lidar data set was acquired over deciduous, coniferous, and mixed stands of varying age classes and settings typical of the southeastern United States (37° 25' N, 78° 41' W). Lidar processing techniques for identifying and measuring individual trees included data fusion with multispectral optical data and local filtering with both square and circular windows of variable size. The window size was based on canopy height and forest type. The crown diameter was calculated as the average of two values measured along two perpendicular directions from the location of each tree top, by fitting a four-degree polynomial on both profiles. The ground-truth plot design followed the U.S. National Forest Inventory and Analysis (FIA) field data layout. The lidar-derived tree measurements were used with regression models and cross-validation to estimate plot level field inventory data, including volume, basal area, and biomass. FIA subplots of 0.017 ha each were pooled together in two categories, deciduous trees and pines. For the pine plots, lidar measurements explained 97% of the variance associated with the mean height of dominant trees. For deciduous plots, regression models explained 79% of the mean height variance for dominant trees. Results for estimating crown diameter were similar for both pines and deciduous trees, with R2 values of 0.62-0.63 for the dominant trees. R2 values for estimating biomass were 0.82 for pines (RMSE 29 Mg/ha) and 0.32 for deciduous (RMSE 44 Mg/ha). Overall, plot level tree height and crown diameter calculated from individual tree lidar measurements were particularly important in contributing to model fit and prediction of forest volume and biomass.
Ph. D.
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Fava, Marica. "LIDAR Aviotrasportati Mediante RPAS." Bachelor's thesis, Alma Mater Studiorum - Università di Bologna, 2016.

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Tesi riguardante i LIDAR aviotrasportati mediante RPAS, cioè relativa alla realizzazione di rilievi LIDAR utilizzando come mezzo di trasporto dei sensori (Laser scanner, Piattaforma inerziale, ricevitore GPS) i droni. Nella trattazione, sono state affrontate le principali caratteristiche tecnologiche e funzionali dei vari strumenti impiegati nel rilievo LIDAR, cercando di comprenderne il ruolo individuale e la relativa sinergia.
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Bogren, Fredrik. "LIDAR-analys av flygsanddyner i Västerbottens inland : Har dynmorfologi bildad under tidigare interstadialer bevarats i landskapet?" Thesis, Umeå universitet, Institutionen för ekologi, miljö och geovetenskap, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-104812.

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The aim of this study was to map the prevalence of aeolian sand dunes in Västerbotten, northern Sweden to find dunes formed during earlier deglaciation phases, which was then preserved in cold-based conditions during the youngest stadial of the Weichselian glaciation. These preserved dunes were expected to be covered by a layer of till and have a rather faint morphology compared to dunes formed during the Holocene. Consequently, high resolution LIDAR-derived images from the Swedish mapping, cadastral and land registration authority (Lantmäteriet) was used to detect the dunes throughout an area covering most of Västerbotten, above the highest coastline and below the mountain range. The analysis resulted in several new findings of aeolian dunes compared to the findings in the quaternary soil map created by the Geological Survey of Sweden. Despite the fact some of the dunes at the LIDAR-derived image had a strange faint appearance, it was quickly evident during the fieldwork that the aeolian sand was not covered by till on any of the dunes visited. The common view during the last decades has been that cold-based ice will not erode or alter the morphology of the landscape beneath the ice. However, this study suggests that hypothesis may not be entirely correct, and therefore it can be hard to use geomorphological implications to reconstruct past glacial environments. Thus, it can be concluded that even under cold-based conditions, preservation of aeolian sand dunes in Västerbotten is probably not very common.
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Crosby, David Alexander. "The Effect of DEM Resolution on the Computation of Hydrologically Significant Topographic Attributes." Scholar Commons, 2006. http://scholarcommons.usf.edu/etd/3859.

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Terrain attributes computed from Digital Elevation Models (DEMs) are widely used in hydrology and hydrologic modeling. It is important to consider that the values of the attributes can be different depending on the resolution of the DEM from which they are derived. The question arises as to how much exactly the high-resolution DEMs created through LIDAR remote sensing techniques change the values of the terrain attributes when compared to lower resolution DEMs.In this thesis a LIDAR-derived DEM of 20 feet resolution was resampled using a nearest-neighbour algorithm to various coarser resolutions to examine and quantify the effect of DEM resolution upon a series of hydrologically significant terrain attributes including slope, surface curvature, topographic wetness index, stream power index and stream networks. Values for slope and surface curvature are found to be smaller when computed from lower resolution DEMs; values for the topographic wetness index and stream power index are found to increase as DEM cell size increases.The derived stream networks for each resolution were compared in terms of length per stream order, drainage density, bifurcation ratio, and overall accuracy indicating a loss of small detail, but only a modest change in the overall stream network morphometry. This research suggests that it is possible to establish relationships that quantify the effects of DEM resolution upon hydrologically significant terrain attributes, which can then be considered when processing DEMs from various resolutions for the purpose of parameterizing hydrologic models.
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Bhadra, Sourav. "Assessing the Impacts of Anthropogenic Drainage Structures on Hydrologic Connectivity Using High-Resolution Digital Elevation Models." OpenSIUC, 2019. https://opensiuc.lib.siu.edu/theses/2573.

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Stream flowline delineation from high-resolution digital elevation models (HRDEMs) can be problematic due to the fine representation of terrain features as well as anthropogenic drainage structures (e.g., bridges, culverts) within the grid surface. The anthropogenic drainage structures (ADS) may create digital dams while delineating stream flowlines from HRDEMs. The study assessed the effects of ADS locations, spatial resolution (ranged from 1m to 10m), depression processing methods, and flow direction algorithms (D8, D-Infinity, and MFD-md) on hydrologic connectivity through digital dams using HRDEMs in Nebraska. The assessment was conducted based on the offset distances between modeled stream flowlines and original ADS locations using kernel density estimation (KDE) and calculated frequency of ADS samples within offset distances. Three major depression processing techniques (i.e., depression filling, stream breaching, and stream burning) were considered for this study. Finally, an automated method, constrained burning was proposed for HRDEMs which utilizes ancillary datasets to create underneath stream crossings at possible ADS locations and perform DEM reconditioning. The results suggest that coarser resolution DEMs with depression filling and breaching can produce better hydrologic connectivity through ADS compared with finer resolution DEMs with different flow direction algorithms. It was also found that stream burning with known stream crossings at ADS locations outperformed depression filling and breaching techniques for HRDEMs in terms of hydrologic connectivity. The flow direction algorithms combining with depression filling and breaching techniques do not have significant effects on the hydrologic connectivity of modeled stream flowlines. However, for stream burning methods, D8 was found as the best performing flow direction algorithm in HRDEMs with statistical significance. The stream flowlines delineated using the proposed constrained burning method from the HRDEM was found better than depression filling and breaching techniques. This method has an overall accuracy of 78.82% in detecting possible ADS locations within the study area.
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Kniess, Ulrich. "Quantification de l’évolution de glissements de terrain argileux par des techniques de télédétection. Application à la région du Trièves (Alpes Françaises)." Thesis, Grenoble, 2011. http://www.theses.fr/2011GRENU038/document.

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Trois méthodes de télédétection (Lidar, interférométrie radar satellitaire et photogrammétrie aérienne) ont été appliquées pour quantifier les évolutions spatiales et temporelles de deux glissements argileux (Harmalière et Avignonet, situés dans la région du Trièves, Alpes françaises) en complément d’instrumentation in-situ. Une analyse géomorphologique a été réalisée à partir d’ortho-photos (depuis 1948) et du MNT Lidar filtré. Couplée à des reconnaissances géophysiques, elle a montré que la cinématique différente des deux glissements contigus était partiellement contrôlée par la paléotopographie sur laquelle s’est déposée la couche d’argile. La rugosité directionnelle a permis de distinguer les processus d’érosion résultant de mouvements gravitaires et de ravinement. Une technique de corrélation d'images adaptée aux MNT a été développée pour obtenir les vecteurs de déplacement 3D entre deux acquisitions Lidar (2006 - 2009), avec une attention particulière portée à l’évaluation de la qualité des mesures. La carte des déplacements obtenue montre que la zone la plus active du glissement de Harmalière entre 1981 et 2001 est maintenant relativement lente (déplacement <0.4 m en 3 ans), contrairement à d’autres zones proches montrant des mouvements importants atteignant 3m avec une composante rotationnelle. Pour le glissement d’Avignonet, les déplacements déduits augmentent généralement vers le pied du glissement et peuvent atteindre 1 m. La technique des réflecteurs permanents en interférométrie radar a permis de déterminer de nouvelles valeurs de taux de déplacements (entre 1992 et 2000) en 16 points du glissement, qui sont cohérentes avec les données GPS existantes. Le taux moyen de recul à long terme de l’escarpement principal a été estimé à 1-5 cm/an à Avignonet et entre 7 et 14 cm/an à l'Harmalière. La régression du glissement d’Avignonet semble contrôlée par l’érosion du sommet de la couche d’alluvions compactes reposant sur le substratum. La présence d’une paleovallée du Drac sous le pied du glissement de l'Harmalière pourrait expliquer cette différence de cinématique entre les deux glissements
Three remote sensing techniques, Lidar, satellite radar interferometry and aerial photogrammetry are applied to quantify the spatial and temporal evolution of two clayey landslides (Avignonet and Harmalière, located in the Trièves area, French Alps) in complement to in-situ instrumentations. A geomorphological analysis based on Lidar-derived filtered DEM, coupled to analysis of ortho-photos dating back to 1948 and geophysical investigations, shows that the different evolution of the neighbouring landslides could be partly controlled by the paleotopography of the bedrock underlying the clay layer. Directional roughness is shown to help distinguishing between landsliding and gully erosion patterns. Cross-correlation technique adapted to DEMs has been developed to derive 3D-displacement-vectors between two Lidar acquisitions (2006 and 2009), paying attention on measure quality assessment. The displacement map reveals that, at the Harmalière landslide, the main sliding channel, very active from 1981 - 2001, is now relatively slow (< 0.4 m over 3 years), in contrast with four surrounding distinct areas of large movements (up to 3 m) partly with rotational components. At the Avignonet landslide, displacements generally increase towards the toe (up to 1 m near the drainage outlets). Persistent Scatterers Interferometry technique allows to derive new reliable displacement-rates (1992 - 2000) at 16 points of the Avignonet landslide, consistent with GPS time-series. The long-term average headscarp retreat rates are estimated to 1 - 5 cm/y at Avignonet and 7 - 14cm/y at Harmalière. The retreat of the Avignonet landslide seems to be controlled by the erosion of the top of the underlying compacted alluvial layers. The presence of a paleovalley (Drac river) below the Harmalière toe could explain the difference of kinematics between the two landslides
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Mora, Omar Ernesto. "Morphology-Based Identification of Surface Features to Support Landslide Hazard Detection Using Airborne LiDAR Data." The Ohio State University, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=osu1429861576.

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Book chapters on the topic "DEM-LIDAR"

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Jaboyedoff, M., M. Choffet, M. H. Derron, P. Horton, A. Loye, C. Longchamp, B. Mazotti, C. Michoud, and A. Pedrazzini. "Preliminary Slope Mass Movement Susceptibility Mapping Using DEM and LiDAR DEM." In Terrigenous Mass Movements, 109–70. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25495-6_5.

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Saraf, Noraain Mohamed, Khairun Najwa Kamarolzaman, Nurhafiza Md Saad, Nafisah Khalid, Abdul Rauf Abdul Rasam, and Ainon Nisa Othman. "Data Verification of LiDAR-Derived DEM from Different Interpolation Techniques." In Charting the Sustainable Future of ASEAN in Science and Technology, 361–75. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-3434-8_31.

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Dolžan, Erazem, and Mateja Jemec Auflič. "Using Lidar DEM to Map Landslides: Škofjeloško Cerkljansko Hills, Slovenia." In Advancing Culture of Living with Landslides, 191–99. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53498-5_22.

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Crosta, Giovanni B., Giorgio Lollino, Frattini Paolo, Daniele Giordan, Tamburini Andrea, Rivolta Carlo, and Bertolo Davide. "Rockslide Monitoring Through Multi-temporal LiDAR DEM and TLS Data Analysis." In Engineering Geology for Society and Territory - Volume 2, 613–17. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-09057-3_102.

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Wu, Jee-Cheng, and Chia-Hao Chang. "Classification of Landslide Features Using a LiDAR DEM and Back-Propagation Neural Network." In Advances in Remote Sensing and Geo Informatics Applications, 155–58. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-01440-7_36.

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Mihalić, Snježana, Hideaki Marui, Osamu Nagai, Hiroshi Yagi, and Toyohiko Miyagi. "Landslide Inventory in the Area of Zagreb City: Effectiveness of Using LiDAR DEM." In Landslide Science and Practice, 155–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-31325-7_20.

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Pradhan, Biswajeet, and Waleed M. Abdulwahid. "Landslide Risk Assessment Using Multi-hazard Scenario Produced by Logistic Regression and LiDAR-Based DEM." In Laser Scanning Applications in Landslide Assessment, 253–75. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55342-9_13.

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Hsieh, Yu-Chung, Chih-Yu Kuo, Yi-Zhong Chen, Chin-Shyong Hou, Ruo-Ying Wu, and Rou-Fei Chen. "Using Airborne LiDAR DEM to Determine the Bedrock Incision Rate: An Indirect Dating from Landslide Sliding Surface, Taiwan." In Engineering Geology for Society and Territory - Volume 2, 429–34. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-09057-3_69.

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Mann, Ulrich, Biswajeet Pradhan, Nikolas Prechtel, and Manfred F. Buchroithner. "An Automated Approach for Detection of Shallow Landslides from LiDAR Derived DEM Using Geomorphological Indicators in a Tropical Forest." In Terrigenous Mass Movements, 1–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-25495-6_1.

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Hasegawa, Shuichi, Atsuko Nonomura, Jun’ichi Uchida, Katsushi Kawato, Ryota Kageura, Tatsuro Chiba, and Satoshi Onoda. "Hazard Mapping of Earthquake-Induced Deep-Seated Catastrophic Landslides Along the Median Tectonic Line in Shikoku by Using LiDAR DEM and Airborne Resistivity Data." In Engineering Geology for Society and Territory - Volume 2, 717–20. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-09057-3_120.

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Conference papers on the topic "DEM-LIDAR"

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Li, Jing, and Xiangtao Fan. "Height aided GPS navigation using LiDAR DEM." In 2011 19th International Conference on Geoinformatics. IEEE, 2011. http://dx.doi.org/10.1109/geoinformatics.2011.5980967.

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Yuan Feng, Zhang Ji-xian, Zhang Li, and Gao Jing-xiang. "Urban DEM generation from airborne Lidar data." In 2009 Joint Urban Remote Sensing Event. IEEE, 2009. http://dx.doi.org/10.1109/urs.2009.5137643.

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Jiang Ruibo, Yang Mingdong, Pan Jiechen, Wang Dongmei, Yang Fuqin, and Xu Liang. "Compilation of DEM based on lidar data." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5622950.

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Li, Yong, and Huayi Wu. "DEM Extraction from LIDAR Data by Morphological Gradient." In 2009 Fifth International Joint Conference on INC, IMS and IDC. IEEE, 2009. http://dx.doi.org/10.1109/ncm.2009.46.

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Lai, Xudong, Xuedong Zheng, and Junwei Jiang. "A Flow to Generate DEM from Lidar Data." In 2009 International Conference on Information Engineering and Computer Science. IEEE, 2009. http://dx.doi.org/10.1109/iciecs.2009.5363331.

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Neurauter, Scott, Sabrina Szeto, Matt Tindall, Yan Wong, and Chris Wright. "3D Visualization for Hydrocarbon Project Design." In 2008 7th International Pipeline Conference. ASMEDC, 2008. http://dx.doi.org/10.1115/ipc2008-64588.

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3D visualization is the process of displaying spatial data to simulate and model a real three dimensional space. Using 3D visualization, Geomatic professionals are enabling pipeline engineers to make better decisions by providing an increased understanding of potential costs earlier in the design process. This paper will focus on the value of visualizing Digital Elevation Model (DEM) data through the use of hillshades and imagery-draped 3D models. From free online DEM data to high resolution Light Detection and Ranging (LiDAR) derived DEM data, the increased availability allows for a broader use of 3D visualization techniques beyond 3D analysis. Of the numerous sources available, two DEM sources will be discussed in this paper, the free low resolution DEM (CDED Level 1) and the more costly but higher resolution LiDAR based DEM. Traditional methods of evaluating potential locations for route and facilities involved a significant cost for ground truthing. Through the use of 3D visualization products, multiple potential locations can be examined for suitability without the expense of field visits for every candidate site. By focusing on the selected candidate locations using a visual desktop study, the time and expense of ground truthing all of the potential sites can be reduced significantly. Exploiting the visual value of DEM permits a productive and cost efficient methodology for initial route and facility placement on hydrocarbon projects.
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Jia, Yafei, Tian Lan, Tao Peng, Hongbo Wu, Cuiling Li, and Guoqiang Ni. "Effects of point density on DEM accuracy of airborne LiDAR." In IGARSS 2013 - 2013 IEEE International Geoscience and Remote Sensing Symposium. IEEE, 2013. http://dx.doi.org/10.1109/igarss.2013.6721200.

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Xu, Jingzhong, Yuan Kou, and Jun Wang. "High-precision DEM reconstruction based on airborne LiDAR point clouds." In Remote Sensing of the Environment: 18th National Symposium on Remote Sensing of China, edited by Qingxi Tong, Jie Shan, and Boqin Zhu. SPIE, 2014. http://dx.doi.org/10.1117/12.2064237.

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Charalampidis, Dimitrios, and Keith Alphonso. "A texture-based technique for DEM generation from LIDAR data." In Defense and Security Symposium, edited by Monte D. Turner and Gary W. Kamerman. SPIE, 2007. http://dx.doi.org/10.1117/12.719935.

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Zhang, Shaochen, Zhao Yan, and Falin Wu. "A lunar landing safety estimation methodology using lidar acquired DEM." In 2013 IEEE International Conference on Imaging Systems and Techniques (IST). IEEE, 2013. http://dx.doi.org/10.1109/ist.2013.6729734.

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Reports on the topic "DEM-LIDAR"

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Puetz, Angela M., R. C. Olsen, and Brian Anderson. Effects of LIDAR Point Density on Bare Earth Extraction and DEM Creation. Fort Belvoir, VA: Defense Technical Information Center, January 2009. http://dx.doi.org/10.21236/ada534534.

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