WorldWideScience

Sample records for terrestrial lidar datasets

  1. Terrestrial Lidar Datasets of New Orleans, Louisiana, Levee Failures from Hurricane Katrina, August 29, 2005

    Science.gov (United States)

    Collins, Brian D.; Kayen, Robert; Minasian, Diane L.; Reiss, Thomas

    2009-01-01

    Hurricane Katrina made landfall with the northern Gulf Coast on August 29, 2005, as one of the strongest hurricanes on record. The storm damage incurred in Louisiana included a number of levee failures that led to the inundation of approximately 85 percent of the metropolitan New Orleans area. Whereas extreme levels of storm damage were expected from such an event, the catastrophic failure of the New Orleans levees prompted a quick mobilization of engineering experts to assess why and how particular levees failed. As part of this mobilization, civil engineering members of the United States Geological Survey (USGS) performed terrestrial lidar topographic surveys at major levee failures in the New Orleans area. The focus of the terrestrial lidar effort was to obtain precise measurements of the ground surface to map soil displacements at each levee site, the nonuniformity of levee height freeboard, depth of erosion where scour occurred, and distress in structures at incipient failure. In total, we investigated eight sites in the New Orleans region, including both earth and concrete floodwall levee breaks. The datasets extend from the 17th Street Canal in the Orleans East Bank area to the intersection of the Gulf Intracoastal Waterway (GIWW) with the Mississippi River Gulf Outlet (MRGO) in the New Orleans East area. The lidar scan data consists of electronic files containing millions of surveyed points. These points characterize the topography of each levee's postfailure or incipient condition and are available for download through online hyperlinks. The data serve as a permanent archive of the catastrophic damage of Hurricane Katrina on the levee systems of New Orleans. Complete details of the data collection, processing, and georeferencing methodologies are provided in this report to assist in the visualization and analysis of the data by future users.

  2. Forest inventory with terrestrial LiDAR

    NARCIS (Netherlands)

    Bauwens, Sébastien; Bartholomeus, Harm; Calders, Kim; Lejeune, Philippe

    2016-01-01

    The application of static terrestrial laser scanning (TLS) in forest inventories is becoming more effective. Nevertheless, the occlusion effect is still limiting the processing efficiency to extract forest attributes. The use of a mobile laser scanner (MLS) would reduce this occlusion. In this

  3. Automated Feature Extraction of Foredune Morphology from Terrestrial Lidar Data

    Science.gov (United States)

    Spore, N.; Brodie, K. L.; Swann, C.

    2014-12-01

    Foredune morphology is often described in storm impact prediction models using the elevation of the dune crest and dune toe and compared with maximum runup elevations to categorize the storm impact and predicted responses. However, these parameters do not account for other foredune features that may make them more or less erodible, such as alongshore variations in morphology, vegetation coverage, or compaction. The goal of this work is to identify other descriptive features that can be extracted from terrestrial lidar data that may affect the rate of dune erosion under wave attack. Daily, mobile-terrestrial lidar surveys were conducted during a 6-day nor'easter (Hs = 4 m in 6 m water depth) along 20km of coastline near Duck, North Carolina which encompassed a variety of foredune forms in close proximity to each other. This abstract will focus on the tools developed for the automated extraction of the morphological features from terrestrial lidar data, while the response of the dune will be presented by Brodie and Spore as an accompanying abstract. Raw point cloud data can be dense and is often under-utilized due to time and personnel constraints required for analysis, since many algorithms are not fully automated. In our approach, the point cloud is first projected into a local coordinate system aligned with the coastline, and then bare earth points are interpolated onto a rectilinear 0.5 m grid creating a high resolution digital elevation model. The surface is analyzed by identifying features along each cross-shore transect. Surface curvature is used to identify the position of the dune toe, and then beach and berm morphology is extracted shoreward of the dune toe, and foredune morphology is extracted landward of the dune toe. Changes in, and magnitudes of, cross-shore slope, curvature, and surface roughness are used to describe the foredune face and each cross-shore transect is then classified using its pre-storm morphology for storm-response analysis.

  4. Radiometric Calibration of a Dual-Wavelength, Full-Waveform Terrestrial Lidar.

    Science.gov (United States)

    Li, Zhan; Jupp, David L B; Strahler, Alan H; Schaaf, Crystal B; Howe, Glenn; Hewawasam, Kuravi; Douglas, Ewan S; Chakrabarti, Supriya; Cook, Timothy A; Paynter, Ian; Saenz, Edward J; Schaefer, Michael

    2016-03-02

    Radiometric calibration of the Dual-Wavelength Echidna(®) Lidar (DWEL), a full-waveform terrestrial laser scanner with two simultaneously-pulsing infrared lasers at 1064 nm and 1548 nm, provides accurate dual-wavelength apparent reflectance (ρ(app)), a physically-defined value that is related to the radiative and structural characteristics of scanned targets and independent of range and instrument optics and electronics. The errors of ρ(app) are 8.1% for 1064 nm and 6.4% for 1548 nm. A sensitivity analysis shows that ρ(app) error is dominated by range errors at near ranges, but by lidar intensity errors at far ranges. Our semi-empirical model for radiometric calibration combines a generalized logistic function to explicitly model telescopic effects due to defocusing of return signals at near range with a negative exponential function to model the fall-off of return intensity with range. Accurate values of ρ(app) from the radiometric calibration improve the quantification of vegetation structure, facilitate the comparison and coupling of lidar datasets from different instruments, campaigns or wavelengths and advance the utilization of bi- and multi-spectral information added to 3D scans by novel spectral lidars.

  5. Quantifying Vegetation Structure with Lightweight, Rapid-Scanning Terrestrial Lidar

    Science.gov (United States)

    Paynter, I.; Genest, D.; Saenz, E. J.; Strahler, A. H.; Li, Z.; Peri, F.; Schaaf, C.

    2016-12-01

    Light Detection and Ranging (lidar) is proving a competent technology for observing vegetation structure. Terrestrial laser scanners (TLS) are ground-based instruments which utilize hundreds of thousands to millions of lidar observations to provide detailed structural and reflective information of their surroundings. TLS has enjoyed initial success as a validation tool for satellite and airborne estimates of vegetation structure, and are producing independent estimates with increasing accuracy. Reconstruction techniques for TLS observations of vegetation have also improved rapidly, especially for trees. However, uncertainties and challenges still remain in TLS modelling of vegetation structure, especially in geometrically complex ecosystems such as tropical forests (where observation extent and density is hampered by occlusion) and highly temporally dynamic coastal ecosystems (such as saltmarshes and mangroves), where observations may be restricted to narrow microstates. Some of these uncertainties can be mitigated, and challenges met, through the use of lidar instruments optimized for favorable deployment logistics through low weight, rapid scanning, and improved durability. We have conducted studies of vegetation structure in temperate and tropical forests, saltmarshes and mangroves, utilizing a highly portable TLS with considerable deployment flexibility, the Compact Biomass Lidar (CBL). We show results from studies in the temperate Long Term Ecological Research site of Harvard Forest (MA, USA); the tropical forested long-term Carbono sites of La Selva Biological Station (Sarapiqui, Costa Rica); and the saltmarsh LTER of Plum Island (MA, USA). These results demonstrate the improvements to observations in these ecosystems which are facilitated by the specifications of the CBL (and similar TLS) which are optimized for favorable deployment logistics and flexibility. We show the benefits of increased numbers of scanning positions, and specialized deployment

  6. Estimating Tropical Forest Structure Using a Terrestrial Lidar.

    Science.gov (United States)

    Palace, Michael; Sullivan, Franklin B; Ducey, Mark; Herrick, Christina

    2016-01-01

    Forest structure comprises numerous quantifiable biometric components and characteristics, which include tree geometry and stand architecture. These structural components are important in the understanding of the past and future trajectories of these biomes. Tropical forests are often considered the most structurally complex and yet least understood of forested ecosystems. New technologies have provided novel avenues for quantifying biometric properties of forested ecosystems, one of which is LIght Detection And Ranging (lidar). This sensor can be deployed on satellite, aircraft, unmanned aerial vehicles, and terrestrial platforms. In this study we examined the efficacy of a terrestrial lidar scanner (TLS) system in a tropical forest to estimate forest structure. Our study was conducted in January 2012 at La Selva, Costa Rica at twenty locations in a predominantly undisturbed forest. At these locations we collected field measured biometric attributes using a variable plot design. We also collected TLS data from the center of each plot. Using this data we developed relative vegetation profiles (RVPs) and calculated a series of parameters including entropy, Fast Fourier Transform (FFT), number of layers and plant area index to develop statistical relationships with field data. We developed statistical models using a series of multiple linear regressions, all of which converged on significant relationships with the strongest relationship being for mean crown depth (r2 = 0.88, p < 0.001, RMSE = 1.04 m). Tree density was found to have the poorest significant relationship (r2 = 0.50, p < 0.01, RMSE = 153.28 n ha-1). We found a significant relationship between basal area and lidar metrics (r2 = 0.75, p < 0.001, RMSE = 3.76 number ha-1). Parameters selected in our models varied, thus indicating the potential relevance of multiple features in canopy profiles and geometry that are related to field-measured structure. Models for biomass estimation included structural canopy

  7. Estimating Tropical Forest Structure Using a Terrestrial Lidar.

    Directory of Open Access Journals (Sweden)

    Michael Palace

    Full Text Available Forest structure comprises numerous quantifiable biometric components and characteristics, which include tree geometry and stand architecture. These structural components are important in the understanding of the past and future trajectories of these biomes. Tropical forests are often considered the most structurally complex and yet least understood of forested ecosystems. New technologies have provided novel avenues for quantifying biometric properties of forested ecosystems, one of which is LIght Detection And Ranging (lidar. This sensor can be deployed on satellite, aircraft, unmanned aerial vehicles, and terrestrial platforms. In this study we examined the efficacy of a terrestrial lidar scanner (TLS system in a tropical forest to estimate forest structure. Our study was conducted in January 2012 at La Selva, Costa Rica at twenty locations in a predominantly undisturbed forest. At these locations we collected field measured biometric attributes using a variable plot design. We also collected TLS data from the center of each plot. Using this data we developed relative vegetation profiles (RVPs and calculated a series of parameters including entropy, Fast Fourier Transform (FFT, number of layers and plant area index to develop statistical relationships with field data. We developed statistical models using a series of multiple linear regressions, all of which converged on significant relationships with the strongest relationship being for mean crown depth (r2 = 0.88, p < 0.001, RMSE = 1.04 m. Tree density was found to have the poorest significant relationship (r2 = 0.50, p < 0.01, RMSE = 153.28 n ha-1. We found a significant relationship between basal area and lidar metrics (r2 = 0.75, p < 0.001, RMSE = 3.76 number ha-1. Parameters selected in our models varied, thus indicating the potential relevance of multiple features in canopy profiles and geometry that are related to field-measured structure. Models for biomass estimation included

  8. Collection, Processing, and Accuracy of Mobile Terrestrial Lidar Survey Data in the Coastal Environment

    Science.gov (United States)

    2017-04-01

    technical report is to present how elevation data is collected along the coast using terrestrial lidar scanners coupled with a global position system...vi 1 Introduction ...Classified .las point cloud ........................................................................................... 23 5.2 Digital elevation model

  9. Correction of elevation offsets in multiple co-located lidar datasets

    Science.gov (United States)

    Thompson, David M.; Dalyander, P. Soupy; Long, Joseph W.; Plant, Nathaniel G.

    2017-04-07

    IntroductionTopographic elevation data collected with airborne light detection and ranging (lidar) can be used to analyze short- and long-term changes to beach and dune systems. Analysis of multiple lidar datasets at Dauphin Island, Alabama, revealed systematic, island-wide elevation differences on the order of 10s of centimeters (cm) that were not attributable to real-world change and, therefore, were likely to represent systematic sampling offsets. These offsets vary between the datasets, but appear spatially consistent within a given survey. This report describes a method that was developed to identify and correct offsets between lidar datasets collected over the same site at different times so that true elevation changes over time, associated with sediment accumulation or erosion, can be analyzed.

  10. Evaluation of Terrestrial LIDAR for Monitoring Geomorphic Change at Archeological Sites in Grand Canyon National Park, Arizona

    Science.gov (United States)

    Collins, Brian D.; Brown, Kristin M.; Fairley, Helen C.

    2008-01-01

    This report presents the results of an evaluation of terrestrial light detection and ranging (LIDAR) for monitoring geomorphic change at archeological sites located within Grand Canyon National Park, Ariz. Traditionally, topographic change-detection studies have used total station methods for the collection of data related to key measurable features of site erosion such as the location of thalwegs and knickpoints of gullies that traverse archeological sites (for example, Pederson and others, 2003). Total station methods require survey teams to walk within and on the features of interest within the archeological sites to take accurate measurements. As a result, site impacts may develop such as trailing, damage to cryptogamic crusts, and surface compaction that can exacerbate future erosion of the sites. National Park Service (NPS) resource managers have become increasingly concerned that repeated surveys for research and monitoring purposes may have a detrimental impact on the resources that researchers are trying to study and protect. Beginning in 2006, the Sociocultural Program of the U.S. Geological Survey's (USGS) Grand Canyon Monitoring and Research Center (GCMRC) initiated an evaluation of terrestrial LIDAR as a new monitoring tool that might enhance data quality and reduce site impacts. This evaluation was conducted as one part of an ongoing study to develop objective, replicable, quantifiable monitoring protocols for tracking the status and trend of variables affecting archeological site condition along the Colorado River corridor. The overall study consists of two elements: (1) an evaluation of the methodology through direct comparison to geomorphologic metrics already being collected by total station methods (this report) and (2) an evaluation of terrestrial LIDAR's ability to detect topographic change through the collection of temporally different datasets (a report on this portion of the study is anticipated early in 2009). The main goals of the first

  11. Prediction of Canopy Heights over a Large Region Using Heterogeneous Lidar Datasets: Efficacy and Challenges

    Directory of Open Access Journals (Sweden)

    Ranjith Gopalakrishnan

    2015-08-01

    Full Text Available Generating accurate and unbiased wall-to-wall canopy height maps from airborne lidar data for large regions is useful to forest scientists and natural resource managers. However, mapping large areas often involves using lidar data from different projects, with varying acquisition parameters. In this work, we address the important question of whether one can accurately model canopy heights over large areas of the Southeastern US using a very heterogeneous dataset of small-footprint, discrete-return airborne lidar data (with 76 separate lidar projects. A unique aspect of this effort is the use of nationally uniform and extensive field data (~1800 forested plots from the Forest Inventory and Analysis (FIA program of the US Forest Service. Preliminary results are quite promising: Over all lidar projects, we observe a good correlation between the 85th percentile of lidar heights and field-measured height (r = 0.85. We construct a linear regression model to predict subplot-level dominant tree heights from distributional lidar metrics (R2 = 0.74, RMSE = 3.0 m, n = 1755. We also identify and quantify the importance of several factors (like heterogeneity of vegetation, point density, the predominance of hardwoods or softwoods, the average height of the forest stand, slope of the plot, and average scan angle of lidar acquisition that influence the efficacy of predicting canopy heights from lidar data. For example, a subset of plots (coefficient of variation of vegetation heights <0.2 significantly reduces the RMSE of our model from 3.0–2.4 m (~20% reduction. We conclude that when all these elements are factored into consideration, combining data from disparate lidar projects does not preclude robust estimation of canopy heights.

  12. Implications of sensor configuration and topography on vertical plant profiles derived from terrestrial LiDAR

    NARCIS (Netherlands)

    Calders, K.; Armston, J.; Newnham, G.; Herold, M.; Goodwin, N.

    2014-01-01

    The vertical distribution of plant constituents is a key parameter to describe vegetation structure and influences several processes, such as radiation interception, growth and habitat. Terrestrial laser scanning (TLS), also referred to as terrestrial LiDAR, has the potential to measure the canopy

  13. Accuracy assessment of a mobile terrestrial lidar survey at Padre Island National Seashore

    Science.gov (United States)

    Lim, Samsung; Thatcher, Cindy A.; Brock, John C.; Kimbrow, Dustin R.; Danielson, Jeffrey J.; Reynolds, B.J.

    2013-01-01

    The higher point density and mobility of terrestrial laser scanning (light detection and ranging (lidar)) is desired when extremely detailed elevation data are needed for mapping vertically orientated complex features such as levees, dunes, and cliffs, or when highly accurate data are needed for monitoring geomorphic changes. Mobile terrestrial lidar scanners have the capability for rapid data collection on a larger spatial scale compared with tripod-based terrestrial lidar, but few studies have examined the accuracy of this relatively new mapping technology. For this reason, we conducted a field test at Padre Island National Seashore of a mobile lidar scanner mounted on a sport utility vehicle and integrated with a position and orientation system. The purpose of the study was to assess the vertical and horizontal accuracy of data collected by the mobile terrestrial lidar system, which is georeferenced to the Universal Transverse Mercator coordinate system and the North American Vertical Datum of 1988. To accomplish the study objectives, independent elevation data were collected by conducting a high-accuracy global positioning system survey to establish the coordinates and elevations of 12 targets spaced throughout the 12 km transect. These independent ground control data were compared to the lidar scanner-derived elevations to quantify the accuracy of the mobile lidar system. The performance of the mobile lidar system was also tested at various vehicle speeds and scan density settings (e.g. field of view and linear point spacing) to estimate the optimal parameters for desired point density. After adjustment of the lever arm parameters, the final point cloud accuracy was 0.060 m (east), 0.095 m (north), and 0.053 m (height). The very high density of the resulting point cloud was sufficient to map fine-scale topographic features, such as the complex shape of the sand dunes.

  14. Simulated full-waveform lidar compared to Riegl VZ-400 terrestrial laser scans

    Science.gov (United States)

    Kim, Angela M.; Olsen, Richard C.; Béland, Martin

    2016-05-01

    A 3-D Monte Carlo ray-tracing simulation of LiDAR propagation models the reflection, transmission and ab- sorption interactions of laser energy with materials in a simulated scene. In this presentation, a model scene consisting of a single Victorian Boxwood (Pittosporum undulatum) tree is generated by the high-fidelity tree voxel model VoxLAD using high-spatial resolution point cloud data from a Riegl VZ-400 terrestrial laser scanner. The VoxLAD model uses terrestrial LiDAR scanner data to determine Leaf Area Density (LAD) measurements for small volume voxels (20 cm sides) of a single tree canopy. VoxLAD is also used in a non-traditional fashion in this case to generate a voxel model of wood density. Information from the VoxLAD model is used within the LiDAR simulation to determine the probability of LiDAR energy interacting with materials at a given voxel location. The LiDAR simulation is defined to replicate the scanning arrangement of the Riegl VZ-400; the resulting simulated full-waveform LiDAR signals compare favorably to those obtained with the Riegl VZ-400 terrestrial laser scanner.

  15. Leveraging High Resolution Topography for Education and Outreach: Updates to OpenTopography to make EarthScope and Other Lidar Datasets more Prominent in Geoscience Education

    Science.gov (United States)

    Kleber, E.; Crosby, C. J.; Arrowsmith, R.; Robinson, S.; Haddad, D. E.

    2013-12-01

    The use of Light Detection and Ranging (lidar) derived topography has become an indispensable tool in Earth science research. The collection of high-resolution lidar topography from an airborne or terrestrial platform allows landscapes and landforms to be represented at sub-meter resolution and in three dimensions. In addition to its high value for scientific research, lidar derived topography has tremendous potential as a tool for Earth science education. Recent science education initiatives and a community call for access to research-level data make the time ripe to expose lidar data and derived data products as a teaching tool. High resolution topographic data fosters several Disciplinary Core Ideas (DCIs) of the Next Generation Science Standards (NGS, 2013), presents respective Big Ideas of the new community-driven Earth Science Literacy Initiative (ESLI, 2009), teaches to a number National Science Education Standards (NSES, 1996), and Benchmarks for Science Literacy (AAAS, 1993) for science education for undergraduate physical and environmental earth science classes. The spatial context of lidar data complements concepts like visualization, place-based learning, inquiry based teaching and active learning essential to teaching in the geosciences. As official host to EarthScope lidar datasets for tectonically active areas in the western United States, the NSF-funded OpenTopography facility provides user-friendly access to a wealth of data that is easily incorporated into Earth science educational materials. OpenTopography (www.opentopography.org), in collaboration with EarthScope, has developed education and outreach activities to foster teacher, student and researcher utilization of lidar data. These educational resources use lidar data coupled with free tools such as Google Earth to provide a means for students and the interested public to visualize and explore Earth's surface in an interactive manner not possible with most other remotely sensed imagery. The

  16. Application of a Terrestrial LIDAR System for Elevation Mapping in Terra Nova Bay, Antarctica

    Directory of Open Access Journals (Sweden)

    Hyoungsig Cho

    2015-09-01

    Full Text Available A terrestrial Light Detection and Ranging (LIDAR system has high productivity and accuracy for topographic mapping, but the harsh conditions of Antarctica make LIDAR operation difficult. Low temperatures cause malfunctioning of the LIDAR system, and unpredictable strong winds can deteriorate data quality by irregularly shaking co-registration targets. For stable and efficient LIDAR operation in Antarctica, this study proposes and demonstrates the following practical solutions: (1 a lagging cover with a heating pack to maintain the temperature of the terrestrial LIDAR system; (2 co-registration using square planar targets and two-step point-merging methods based on extracted feature points and the Iterative Closest Point (ICP algorithm; and (3 a georeferencing module consisting of an artificial target and a Global Navigation Satellite System (GNSS receiver. The solutions were used to produce a topographic map for construction of the Jang Bogo Research Station in Terra Nova Bay, Antarctica. Co-registration and georeferencing precision reached 5 and 45 mm, respectively, and the accuracy of the Digital Elevation Model (DEM generated from the LIDAR scanning data was ±27.7 cm.

  17. Application of a Terrestrial LIDAR System for Elevation Mapping in Terra Nova Bay, Antarctica.

    Science.gov (United States)

    Cho, Hyoungsig; Hong, Seunghwan; Kim, Sangmin; Park, Hyokeun; Park, Ilsuk; Sohn, Hong-Gyoo

    2015-09-16

    A terrestrial Light Detection and Ranging (LIDAR) system has high productivity and accuracy for topographic mapping, but the harsh conditions of Antarctica make LIDAR operation difficult. Low temperatures cause malfunctioning of the LIDAR system, and unpredictable strong winds can deteriorate data quality by irregularly shaking co-registration targets. For stable and efficient LIDAR operation in Antarctica, this study proposes and demonstrates the following practical solutions: (1) a lagging cover with a heating pack to maintain the temperature of the terrestrial LIDAR system; (2) co-registration using square planar targets and two-step point-merging methods based on extracted feature points and the Iterative Closest Point (ICP) algorithm; and (3) a georeferencing module consisting of an artificial target and a Global Navigation Satellite System (GNSS) receiver. The solutions were used to produce a topographic map for construction of the Jang Bogo Research Station in Terra Nova Bay, Antarctica. Co-registration and georeferencing precision reached 5 and 45 mm, respectively, and the accuracy of the Digital Elevation Model (DEM) generated from the LIDAR scanning data was ±27.7 cm.

  18. Modelling Soil-Landscapes in Coastal California Hills Using Fine Scale Terrestrial Lidar

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    Prentice, S.; Bookhagen, B.; Kyriakidis, P. C.; Chadwick, O.

    2013-12-01

    Digital elevation models (DEMs) are the dominant input to spatially explicit digital soil mapping (DSM) efforts due to their increasing availability and the tight coupling between topography and soil variability. Accurate characterization of this coupling is dependent on DEM spatial resolution and soil sampling density, both of which may limit analyses. For example, DEM resolution may be too coarse to accurately reflect scale-dependent soil properties yet downscaling introduces artifactual uncertainty unrelated to deterministic or stochastic soil processes. We tackle these limitations through a DSM effort that couples moderately high density soil sampling with a very fine scale terrestrial lidar dataset (20 cm) implemented in a semiarid rolling hillslope domain where terrain variables change rapidly but smoothly over short distances. Our guiding hypothesis is that in this diffusion-dominated landscape, soil thickness is readily predicted by continuous terrain attributes coupled with catenary hillslope segmentation. We choose soil thickness as our keystone dependent variable for its geomorphic and hydrologic significance, and its tendency to be a primary input to synthetic ecosystem models. In defining catenary hillslope position we adapt a logical rule-set approach that parses common terrain derivatives of curvature and specific catchment area into discrete landform elements (LE). Variograms and curvature-area plots are used to distill domain-scale terrain thresholds from short range order noise characteristic of very fine-scale spatial data. The revealed spatial thresholds are used to condition LE rule-set inputs, rendering a catenary LE map that leverages the robustness of fine-scale terrain data to create a generalized interpretation of soil geomorphic domains. Preliminary regressions show that continuous terrain variables alone (curvature, specific catchment area) only partially explain soil thickness, and only in a subset of soils. For example, at spatial

  19. Integrating terrestrial LiDAR and stereo photogrammetry to map the Tolay lakebed in northern San Francisco Bay

    Science.gov (United States)

    Woo, Isa; Storesund,; Takekawa, John Y.; Gardiner, Rachel J.; Ehret,

    2009-01-01

    The Tolay Creek Watershed drains approximately 3,520 ha along the northern edge of San Francisco Bay. Surrounded by a mosaic of open space conservation easements and public wildlife areas, it is one of the only watersheds in this urbanized estuary that is protected from its headwaters to the bay. Tolay Lake is a seasonal, spring-fed lake found in the upper watershed that historically extended over 120 ha. Although the lakebed was farmed since the early 1860s, the majority of the lakebed was recently acquired by the Sonoma County Regional Parks Department to restore its natural habitat values. As part of the restoration planning process, we produced a digital elevation model (DEM) of the historic extent of Tolay Lake by integrating terrestrial LiDAR (light detection and ranging) and stereo photogrammetry datasets, and real-time kinematic (RTK) global positioning system (GPS) surveys. We integrated the data, generated a DEM of the lakebed and upland areas, and analyzed errors. The accuracy of the composite DEM was verified using spot elevations obtained from the RTK GPS. Thus, we found that by combining photogrammetry, terrestrial LiDAR, and RTK GPS, we created an accurate baseline elevation map to use in watershed restoration planning and design.

  20. Assessing Structure and Condition of Temperate And Tropical Forests: Fusion of Terrestrial Lidar and Airborne Multi-Angle and Lidar Remote Sensing

    Science.gov (United States)

    Saenz, Edward J.

    Forests provide vital ecosystem functions and services that maintain the integrity of our natural and human environment. Understanding the structural components of forests (extent, tree density, heights of multi-story canopies, biomass, etc.) provides necessary information to preserve ecosystem services. Increasingly, remote sensing resources have been used to map and monitor forests globally. However, traditional satellite and airborne multi-angle imagery only provide information about the top of the canopy and little about the forest structure and understory. In this research, we investigative the use of rapidly evolving lidar technology, and how the fusion of aerial and terrestrial lidar data can be utilized to better characterize forest stand information. We further apply a novel terrestrial lidar methodology to characterize a Hemlock Woolly Adelgid infestation in Harvard Forest, Massachusetts, and adapt a dynamic terrestrial lidar sampling scheme to identify key structural vegetation profiles of tropical rainforests in La Selva, Costa Rica.

  1. Assessing hydrometeorological impacts with terrestrial and aerial Lidar data in Monterrey, México

    Science.gov (United States)

    Yepez Rincon, F.; Lozano Garcia, D.; Vela Coiffier, P.; Rivera Rivera, L.

    2013-10-01

    Light Detection Ranging (Lidar) is an efficient tool to gather points reflected from a terrain and store them in a xyz coordinate system, allowing the generation of 3D data sets to manage geoinformation. Translation of these coordinates, from an arbitrary system into a geographical base, makes data feasible and useful to calculate volumes and define topographic characteristics at different scales. Lidar technological advancement in topographic mapping enables the generation of highly accurate and densely sampled elevation models, which are in high demand by many industries like construction, mining and forestry. This study merges terrestrial and aerial Lidar data to evaluate the effectiveness of these tools assessing volumetric changes after a hurricane event of riverbeds and scour bridges The resulted information could be an optimal approach to improve hydrological and hydraulic models, to aid authorities in proper to decision making in construction, urban planning, and homeland security.

  2. Utilizing LiDAR Datasets From Experimental Watersheds to Advance Ecohydrological Understanding in Seasonally Snow-Covered Forests

    Science.gov (United States)

    Harpold, A. A.; Broxton, P. D.; Guo, Q.; Barlage, M. J.; Gochis, D. J.

    2014-12-01

    The Western U.S. is strongly reliant on snowmelt from forested areas for ecosystem services and downstream populations. The ability to manage water resources from snow-covered forests faces major challenges from drought, disturbance, and regional changes in climate. An exciting avenue for improving ecohydrological process understanding is Light Detection and Ranging (LiDAR) because the technology simultaneously observes topography, forest properties, and snow/ice at high-resolution (100 km2). The availability and quality of LiDAR datasets is increasing rapidly, however they remain under-utilized for process-based ecohydrology investigations. This presentation will illustrate how LiDAR datasets from the Critical Zone Observatory (CZO) network have been applied to advance ecohydrological understanding through direct empirical analysis, as well as model parameterization and verification. Direct analysis of the datasets has proved fruitful for pre- and post-disturbance snow distribution estimates and interpreting in-situ snow depth measurements across sites. In addition, we illustrate the potential value of LiDAR to parameterize and verify of physical models with two examples. First, we use LiDAR to parameterize a land surface model, Noah multi-parameterization (Noah-MP), to investigate the sensitivity of modeled water and energy fluxes to high-resolution forest information. Second, we present a Snow Physics and Laser Mapping (SnowPALM) model that is parameterized with LiDAR information at its native 1-m scale. Both modeling studies demonstrate the value of LiDAR for representing processes with greater fidelity. More importantly, the increased model fidelity led to different estimates of water and energy fluxes at larger, watershed scales. Creating a network of experimental watersheds with LiDAR datasets offers the potential to test theories and models in previously unexplored ways.

  3. Study of the Integration of LIDAR and Photogrammetric Datasets by in Situ Camera Calibration and Integrated Sensor Orientation

    Science.gov (United States)

    Mitishita, E.; Costa, F.; Martins, M.

    2017-05-01

    Photogrammetric and Lidar datasets should be in the same mapping or geodetic frame to be used simultaneously in an engineering project. Nowadays direct sensor orientation is a common procedure used in simultaneous photogrammetric and Lidar surveys. Although the direct sensor orientation technologies provide a high degree of automation process due to the GNSS/INS technologies, the accuracies of the results obtained from the photogrammetric and Lidar surveys are dependent on the quality of a group of parameters that models accurately the user conditions of the system at the moment the job is performed. This paper shows the study that was performed to verify the importance of the in situ camera calibration and Integrated Sensor Orientation without control points to increase the accuracies of the photogrammetric and LIDAR datasets integration. The horizontal and vertical accuracies of photogrammetric and Lidar datasets integration by photogrammetric procedure improved significantly when the Integrated Sensor Orientation (ISO) approach was performed using Interior Orientation Parameter (IOP) values estimated from the in situ camera calibration. The horizontal and vertical accuracies, estimated by the Root Mean Square Error (RMSE) of the 3D discrepancies from the Lidar check points, increased around of 37% and 198% respectively.

  4. STUDY OF THE INTEGRATION OF LIDAR AND PHOTOGRAMMETRIC DATASETS BY IN SITU CAMERA CALIBRATION AND INTEGRATED SENSOR ORIENTATION

    Directory of Open Access Journals (Sweden)

    E. Mitishita

    2017-05-01

    Full Text Available Photogrammetric and Lidar datasets should be in the same mapping or geodetic frame to be used simultaneously in an engineering project. Nowadays direct sensor orientation is a common procedure used in simultaneous photogrammetric and Lidar surveys. Although the direct sensor orientation technologies provide a high degree of automation process due to the GNSS/INS technologies, the accuracies of the results obtained from the photogrammetric and Lidar surveys are dependent on the quality of a group of parameters that models accurately the user conditions of the system at the moment the job is performed. This paper shows the study that was performed to verify the importance of the in situ camera calibration and Integrated Sensor Orientation without control points to increase the accuracies of the photogrammetric and LIDAR datasets integration. The horizontal and vertical accuracies of photogrammetric and Lidar datasets integration by photogrammetric procedure improved significantly when the Integrated Sensor Orientation (ISO approach was performed using Interior Orientation Parameter (IOP values estimated from the in situ camera calibration. The horizontal and vertical accuracies, estimated by the Root Mean Square Error (RMSE of the 3D discrepancies from the Lidar check points, increased around of 37% and 198% respectively.

  5. Illuminating wildfire erosion and deposition patterns with repeat terrestrial lidar

    Science.gov (United States)

    Rengers, Francis K.; Tucker, G.E.; Moody, J.A.; Ebel, Brian

    2016-01-01

    Erosion following a wildfire is much greater than background erosion in forests because of wildfire-induced changes to soil erodibility and water infiltration. While many previous studies have documented post-wildfire erosion with point and small plot-scale measurements, the spatial distribution of post-fire erosion patterns at the watershed scale remains largely unexplored. In this study lidar surveys were collected periodically in a small, first-order drainage basin over a period of 2 years following a wildfire. The study site was relatively steep with slopes ranging from 17° to > 30°. During the study period, several different types of rain storms occurred on the site including low-intensity frontal storms (2.4 mm h−1) and high-intensity convective thunderstorms (79 mm h−1). These storms were the dominant drivers of erosion. Erosion resulting from dry ravel and debris flows was notably absent at the site. Successive lidar surveys were subtracted from one another to obtain digital maps of topographic change between surveys. The results show an evolution in geomorphic response, such that the erosional response after rain storms was strongly influenced by the previous erosional events and pre-fire site morphology. Hillslope and channel roughness increased over time, and the watershed armored as coarse cobbles and boulders were exposed. The erosional response was spatially nonuniform; shallow erosion from hillslopes (87% of the study area) contributed 3 times more sediment volume than erosion from convergent areas (13% of the study area). However, the total normalized erosion depth (volume/area) was highest in convergent areas. From a detailed understanding of the spatial locations of erosion, we made inferences regarding the processes driving erosion. It appears that hillslope erosion is controlled by rain splash (for detachment) and overland flow (for transport and quasi-channelized erosion), with the sites of highest erosion corresponding to locations

  6. Effect of target color and scanning geometry on terrestrial LiDAR point-cloud noise and plane fitting

    Science.gov (United States)

    Bolkas, Dimitrios; Martinez, Aaron

    2018-01-01

    Point-cloud coordinate information derived from terrestrial Light Detection And Ranging (LiDAR) is important for several applications in surveying and civil engineering. Plane fitting and segmentation of target-surfaces is an important step in several applications such as in the monitoring of structures. Reliable parametric modeling and segmentation relies on the underlying quality of the point-cloud. Therefore, understanding how point-cloud errors affect fitting of planes and segmentation is important. Point-cloud intensity, which accompanies the point-cloud data, often goes hand-in-hand with point-cloud noise. This study uses industrial particle boards painted with eight different colors (black, white, grey, red, green, blue, brown, and yellow) and two different sheens (flat and semi-gloss) to explore how noise and plane residuals vary with scanning geometry (i.e., distance and incidence angle) and target-color. Results show that darker colors, such as black and brown, can produce point clouds that are several times noisier than bright targets, such as white. In addition, semi-gloss targets manage to reduce noise in dark targets by about 2-3 times. The study of plane residuals with scanning geometry reveals that, in many of the cases tested, residuals decrease with increasing incidence angles, which can assist in understanding the distribution of plane residuals in a dataset. Finally, a scheme is developed to derive survey guidelines based on the data collected in this experiment. Three examples demonstrate that users should consider instrument specification, required precision of plane residuals, required point-spacing, target-color, and target-sheen, when selecting scanning locations. Outcomes of this study can aid users to select appropriate instrumentation and improve planning of terrestrial LiDAR data-acquisition.

  7. Comparing RIEGL RiCOPTER UAV LiDAR Derived Canopy Height and DBH with Terrestrial LiDAR.

    Science.gov (United States)

    Brede, Benjamin; Lau, Alvaro; Bartholomeus, Harm M; Kooistra, Lammert

    2017-10-17

    In recent years, LIght Detection And Ranging (LiDAR) and especially Terrestrial Laser Scanning (TLS) systems have shown the potential to revolutionise forest structural characterisation by providing unprecedented 3D data. However, manned Airborne Laser Scanning (ALS) requires costly campaigns and produces relatively low point density, while TLS is labour intense and time demanding. Unmanned Aerial Vehicle (UAV)-borne laser scanning can be the way in between. In this study, we present first results and experiences with the RIEGL RiCOPTER with VUX ® -1UAV ALS system and compare it with the well tested RIEGL VZ-400 TLS system. We scanned the same forest plots with both systems over the course of two days. We derived Digital Terrain Model (DTMs), Digital Surface Model (DSMs) and finally Canopy Height Model (CHMs) from the resulting point clouds. ALS CHMs were on average 11.5 c m higher in five plots with different canopy conditions. This showed that TLS could not always detect the top of canopy. Moreover, we extracted trunk segments of 58 trees for ALS and TLS simultaneously, of which 39 could be used to model Diameter at Breast Height (DBH). ALS DBH showed a high agreement with TLS DBH with a correlation coefficient of 0.98 and root mean square error of 4.24 c m . We conclude that RiCOPTER has the potential to perform comparable to TLS for estimating forest canopy height and DBH under the studied forest conditions. Further research should be directed to testing UAV-borne LiDAR for explicit 3D modelling of whole trees to estimate tree volume and subsequently Above-Ground Biomass (AGB).

  8. Empirical Radiometric Normalization of Road Points from Terrestrial Mobile Lidar System

    Directory of Open Access Journals (Sweden)

    Tee-Ann Teo

    2015-05-01

    Full Text Available Lidar data provide both geometric and radiometric information. Radiometric information is influenced by sensor and target factors and should be calibrated to obtain consistent energy responses. The radiometric correction of airborne lidar system (ALS converts the amplitude into a backscatter cross-section with physical meaning value by applying a model-driven approach. The radiometric correction of terrestrial mobile lidar system (MLS is a challenging task because it does not completely follow the inverse square range function at near-range. This study proposed a radiometric normalization workflow for MLS using a data-driven approach. The scope of this study is to normalize amplitude of road points for road surface classification, assuming that road points from different scanners or strips should have similar responses in overlapped areas. The normalization parameters for range effect were obtained from crossroads. The experiment showed that the amplitude difference between scanners and strips decreased after radiometric normalization and improved the accuracy of road surface classification.

  9. Estimating terrestrial aboveground biomass estimation using lidar remote sensing: a meta-analysis

    Science.gov (United States)

    Zolkos, S. G.; Goetz, S. J.; Dubayah, R.

    2012-12-01

    Estimating biomass of terrestrial vegetation is a rapidly expanding research area, but also a subject of tremendous interest for reducing carbon emissions associated with deforestation and forest degradation (REDD). The accuracy of biomass estimates is important in the context carbon markets emerging under REDD, since areas with more accurate estimates command higher prices, but also for characterizing uncertainty in estimates of carbon cycling and the global carbon budget. There is particular interest in mapping biomass so that carbon stocks and stock changes can be monitored consistently across a range of scales - from relatively small projects (tens of hectares) to national or continental scales - but also so that other benefits of forest conservation can be factored into decision making (e.g. biodiversity and habitat corridors). We conducted an analysis of reported biomass accuracy estimates from more than 60 refereed articles using different remote sensing platforms (aircraft and satellite) and sensor types (optical, radar, lidar), with a particular focus on lidar since those papers reported the greatest efficacy (lowest errors) when used in the a synergistic manner with other coincident multi-sensor measurements. We show systematic differences in accuracy between different types of lidar systems flown on different platforms but, perhaps more importantly, differences between forest types (biomes) and plot sizes used for field calibration and assessment. We discuss these findings in relation to monitoring, reporting and verification under REDD, and also in the context of more systematic assessment of factors that influence accuracy and error estimation.

  10. Analyzing Hydro-Geomorphic Responses in Post-Fire Stream Channels with Terrestrial LiDAR

    Science.gov (United States)

    Nourbakhshbeidokhti, S.; Kinoshita, A. M.; Chin, A.

    2015-12-01

    Wildfires have potential to significantly alter soil properties and vegetation within watersheds. These alterations often contribute to accelerated erosion, runoff, and sediment transport in stream channels and hillslopes. This research applies repeated Terrestrial Laser Scanning (TLS) Light Detection and Ranging (LiDAR) to stream reaches within the Pike National Forest in Colorado following the 2012 Waldo Canyon Fire. These scans allow investigation of the relationship between sediment delivery and environmental characteristics such as precipitation, soil burn severity, and vegetation. Post-fire LiDAR images provide high resolution information of stream channel changes in eight reaches for three years (2012-2014). All images are processed with RiSCAN PRO to remove vegetation and triangulated and smoothed to create a Digital Elevation Model (DEM) with 0.1 m resolution. Study reaches with two or more successive DEM images are compared using a differencing method to estimate the volume of sediment erosion and deposition. Preliminary analysis of four channel reaches within Williams Canyon and Camp Creek yielded erosion estimates between 0.035 and 0.618 m3 per unit area. Deposition was estimated as 0.365 to 1.67 m3 per unit area. Reaches that experienced higher soil burn severity or larger rainfall events produced the greatest geomorphic changes. Results from LiDAR analyses can be incorporated into post-fire hydrologic models to improve estimates of runoff and sediment yield. These models will, in turn, provide guidance for water resources management and downstream hazards mitigation.

  11. Georeferencing UAS Derivatives Through Point Cloud Registration with Archived Lidar Datasets

    Science.gov (United States)

    Magtalas, M. S. L. Y.; Aves, J. C. L.; Blanco, A. C.

    2016-10-01

    Georeferencing gathered images is a common step before performing spatial analysis and other processes on acquired datasets using unmanned aerial systems (UAS). Methods of applying spatial information to aerial images or their derivatives is through onboard GPS (Global Positioning Systems) geotagging, or through tying of models through GCPs (Ground Control Points) acquired in the field. Currently, UAS (Unmanned Aerial System) derivatives are limited to meter-levels of accuracy when their generation is unaided with points of known position on the ground. The use of ground control points established using survey-grade GPS or GNSS receivers can greatly reduce model errors to centimeter levels. However, this comes with additional costs not only with instrument acquisition and survey operations, but also in actual time spent in the field. This study uses a workflow for cloud-based post-processing of UAS data in combination with already existing LiDAR data. The georeferencing of the UAV point cloud is executed using the Iterative Closest Point algorithm (ICP). It is applied through the open-source CloudCompare software (Girardeau-Montaut, 2006) on a `skeleton point cloud'. This skeleton point cloud consists of manually extracted features consistent on both LiDAR and UAV data. For this cloud, roads and buildings with minimal deviations given their differing dates of acquisition are considered consistent. Transformation parameters are computed for the skeleton cloud which could then be applied to the whole UAS dataset. In addition, a separate cloud consisting of non-vegetation features automatically derived using CANUPO classification algorithm (Brodu and Lague, 2012) was used to generate a separate set of parameters. Ground survey is done to validate the transformed cloud. An RMSE value of around 16 centimeters was found when comparing validation data to the models georeferenced using the CANUPO cloud and the manual skeleton cloud. Cloud-to-cloud distance computations of

  12. Characterizing Tropical Forest Structure using Field-based Measurements and a Terrestrial Lidar

    Science.gov (United States)

    Palace, M. W.; Sullivan, F.; Ducey, M. J.; Herrick, C.

    2015-12-01

    Forest structure comprises numerous quantifiable components of forest biometric characteristics, one of which is tree architecture. This structural component is important in the understanding of the past and future trajectories of these biomes. Tropical forests are often considered the most structurally complex and yet least understood of forested ecosystems. New technologies have provided novel avenues for quantifying properties of forested ecosystems, one of which is LIght Detection And Ranging (lidar). This sensor can be deployed on satellite, aircraft, unmanned aerial vehicles, and terrestrial platforms. In this study we examined the efficacy of a terrestrial lidar scanner (TLS) system in a tropical forest to estimate forest structure. Our study was conducted in January 2012 at La Selva, Costa Rica at twenty locations in predominantly undisturbed forest. At these locations we collected field measured biometric attributes using a variable plot design. We also collected TLS data from the center of each plot. Using this data we developed relative vegetation profiles (RVPs) and calculated a series of parameters including entropy, FFT, number of layers and plant area index to develop statistical relationships with field data. We developed statistical models using multiple linear regressions, all of which converged on statistically significant relationships with the strongest relationship being for mean crown depth (r2 = 0.87, p information on tropical forest structure.

  13. Extraction of Urban Trees from Integrated Airborne Based Digital Image and LIDAR Point Cloud Datasets - Initial Results

    Science.gov (United States)

    Dogon-yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

    2016-10-01

    Timely and accurate acquisition of information on the condition and structural changes of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting tree features include; ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraint, such as labour intensive field work, a lot of financial requirement, influences by weather condition and topographical covers which can be overcome by means of integrated airborne based LiDAR and very high resolution digital image datasets. This study presented a semi-automated approach for extracting urban trees from integrated airborne based LIDAR and multispectral digital image datasets over Istanbul city of Turkey. The above scheme includes detection and extraction of shadow free vegetation features based on spectral properties of digital images using shadow index and NDVI techniques and automated extraction of 3D information about vegetation features from the integrated processing of shadow free vegetation image and LiDAR point cloud datasets. The ability of the developed algorithms shows a promising result as an automated and cost effective approach to estimating and delineated 3D information of urban trees. The research also proved that integrated datasets is a suitable technology and a viable source of information for city managers to be used in urban trees management.

  14. Quantifying Standing Dead Tree Volume and Structural Loss with Voxelized Terrestrial Lidar Data

    Science.gov (United States)

    Popescu, S. C.; Putman, E.

    2017-12-01

    Standing dead trees (SDTs) are an important forest component and impact a variety of ecosystem processes, yet the carbon pool dynamics of SDTs are poorly constrained in terrestrial carbon cycling models. The ability to model wood decay and carbon cycling in relation to detectable changes in tree structure and volume over time would greatly improve such models. The overall objective of this study was to provide automated aboveground volume estimates of SDTs and automated procedures to detect, quantify, and characterize structural losses over time with terrestrial lidar data. The specific objectives of this study were: 1) develop an automated SDT volume estimation algorithm providing accurate volume estimates for trees scanned in dense forests; 2) develop an automated change detection methodology to accurately detect and quantify SDT structural loss between subsequent terrestrial lidar observations; and 3) characterize the structural loss rates of pine and oak SDTs in southeastern Texas. A voxel-based volume estimation algorithm, "TreeVolX", was developed and incorporates several methods designed to robustly process point clouds of varying quality levels. The algorithm operates on horizontal voxel slices by segmenting the slice into distinct branch or stem sections then applying an adaptive contour interpolation and interior filling process to create solid reconstructed tree models (RTMs). TreeVolX estimated large and small branch volume with an RMSE of 7.3% and 13.8%, respectively. A voxel-based change detection methodology was developed to accurately detect and quantify structural losses and incorporated several methods to mitigate the challenges presented by shifting tree and branch positions as SDT decay progresses. The volume and structural loss of 29 SDTs, composed of Pinus taeda and Quercus stellata, were successfully estimated using multitemporal terrestrial lidar observations over elapsed times ranging from 71 - 753 days. Pine and oak structural loss rates

  15. Evaluating scale and roughness effects in urban flood modelling using terrestrial LIDAR data

    Directory of Open Access Journals (Sweden)

    H. Ozdemir

    2013-10-01

    Full Text Available This paper evaluates the results of benchmark testing a new inertial formulation of the St. Venant equations, implemented within the LISFLOOD-FP hydraulic model, using different high resolution terrestrial LiDAR data (10 cm, 50 cm and 1 m and roughness conditions (distributed and composite in an urban area. To examine these effects, the model is applied to a hypothetical flooding scenario in Alcester, UK, which experienced surface water flooding during summer 2007. The sensitivities of simulated water depth, extent, arrival time and velocity to grid resolutions and different roughness conditions are analysed. The results indicate that increasing the terrain resolution from 1 m to 10 cm significantly affects modelled water depth, extent, arrival time and velocity. This is because hydraulically relevant small scale topography that is accurately captured by the terrestrial LIDAR system, such as road cambers and street kerbs, is better represented on the higher resolution DEM. It is shown that altering surface friction values within a wide range has only a limited effect and is not sufficient to recover the results of the 10 cm simulation at 1 m resolution. Alternating between a uniform composite surface friction value (n = 0.013 or a variable distributed value based on land use has a greater effect on flow velocities and arrival times than on water depths and inundation extent. We conclude that the use of extra detail inherent in terrestrial laser scanning data compared to airborne sensors will be advantageous for urban flood modelling related to surface water, risk analysis and planning for Sustainable Urban Drainage Systems (SUDS to attenuate flow.

  16. Establishing macroecological trait datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide

    DEFF Research Database (Denmark)

    Kissling, W. Daniel; Dalby, Lars; Fløjgaard, Camilla

    2014-01-01

    , the importance of diet for macroevolutionary and macroecological dynamics remains little explored, partly because of the lack of comprehensive trait datasets. We compiled and evaluated a comprehensive global dataset of diet preferences of mammals (“MammalDIET”). Diet information was digitized from two global...... species within the same genus, or family) and this extrapolation was subsequently validated both internally (with a jack-knife approach applied to the compiled species-level diet data) and externally (using independent species-level diet information from a comprehensive continentwide data source). Finally...... information (48% of all terrestrial mammal species), and only rarely from other species within the same genus (6%) or from family level (8%). Internal and external validation showed that: (1) extrapolations were most reliable for primary food items; (2) several diet categories (“Animal”, “Mammal...

  17. Rapid, high-resolution measurement of leaf area and leaf orientation using terrestrial LiDAR scanning data

    International Nuclear Information System (INIS)

    Bailey, Brian N; Mahaffee, Walter F

    2017-01-01

    The rapid evolution of high performance computing technology has allowed for the development of extremely detailed models of the urban and natural environment. Although models can now represent sub-meter-scale variability in environmental geometry, model users are often unable to specify the geometry of real domains at this scale given available measurements. An emerging technology in this field has been the use of terrestrial LiDAR scanning data to rapidly measure the three-dimensional geometry of trees, such as the distribution of leaf area. However, current LiDAR methods suffer from the limitation that they require detailed knowledge of leaf orientation in order to translate projected leaf area into actual leaf area. Common methods for measuring leaf orientation are often tedious or inaccurate, which places constraints on the LiDAR measurement technique. This work presents a new method to simultaneously measure leaf orientation and leaf area within an arbitrarily defined volume using terrestrial LiDAR data. The novelty of the method lies in the direct measurement of the fraction of projected leaf area G from the LiDAR data which is required to relate projected leaf area to total leaf area, and in the new way in which radiation transfer theory is used to calculate leaf area from the LiDAR data. The method was validated by comparing LiDAR-measured leaf area to (1) ‘synthetic’ or computer-generated LiDAR data where the exact area was known, and (2) direct measurements of leaf area in the field using destructive sampling. Overall, agreement between the LiDAR and reference measurements was very good, showing a normalized root-mean-squared-error of about 15% for the synthetic tests, and 13% in the field. (paper)

  18. Evaluation of short-term geomorphic changes along the Tagliamento river using LiDAR and terrestrial laser scanner surveys

    Directory of Open Access Journals (Sweden)

    R. Rainato

    2013-09-01

    Full Text Available In the recent years a change in the predominant morphology of several river environments has taken place, consisting in a reduction of the braided pattern in favor to wandering or straight configurations. This evolution seems to be due, according to the scientific community, to anthropic causes and, in particular, to the alteration of flow regimes as well as the reduction of sediment transport. Braided rivers are characterized by two or more active channels, separated by bars and fluvial islands and normally feature a high morphological dynamism. This dynamism is the result of the interaction among different elements as sediment supply, flow regime and in-channel and perifluvial vegetation. These factors have a fundamental role in the erosion and deposition processes which are the basis of the morphological changes. The aims of this study are the assessment of the short period geomorphic and volumetric changes occurred along a reach of the Tagliamento River and the comparison between the results obtained from LiDAR (Light Detection and Ranging and TLS (Terrestrial Laser Scanner data. The Tagliamento river is a natural gravel-bed river located in the NE of Italy, characterized by a relatively low degree of human disturbances. The analyses were carried out considering two different scales (a reach of about 430 ha and a sub-reach of about 25 ha and were based on two subsequent datasets in order to investigate the shortterm geomorphic changes due to eight significant floods. The surveys were performed using two different datasets derived from LiDAR and TLS technologies and used to analyze the reach and sub-reach respectively. The short-term estimates of geomorphic and volumetric changes were performed using DEMs of Difference (DoD based on a Fuzzy Inference System. The results have confirmed the high dynamism of the Tagliamento river, estimating a prevalent deposition at reach and a predominant erosion at sub-reach levels. Finally, a comparative

  19. CLOSE RANGE HYPERSPECTRAL IMAGING INTEGRATED WITH TERRESTRIAL LIDAR SCANNING APPLIED TO ROCK CHARACTERISATION AT CENTIMETRE SCALE

    Directory of Open Access Journals (Sweden)

    T. H. Kurz

    2012-07-01

    Full Text Available Compact and lightweight hyperspectral imagers allow the application of close range hyperspectral imaging with a ground based scanning setup for geological fieldwork. Using such a scanning setup, steep cliff sections and quarry walls can be scanned with a more appropriate viewing direction and a higher image resolution than from airborne and spaceborne platforms. Integration of the hyperspectral imagery with terrestrial lidar scanning provides the hyperspectral information in a georeferenced framework and enables measurement at centimetre scale. In this paper, three geological case studies are used to demonstrate the potential of this method for rock characterisation. Two case studies are applied to carbonate quarries where mapping of different limestone and dolomite types was required, as well as measurements of faults and layer thicknesses from inaccessible parts of the quarries. The third case study demonstrates the method using artificial lighting, applied in a subsurface scanning scenario where solar radiation cannot be utilised.

  20. Quantifying Local Ablation Rates for the Greenland Ice Sheet Using Terrestrial LIDAR

    Science.gov (United States)

    Kershner, C. M.; Pitcher, L. H.; LeWinter, A.; Finnegan, D. C.; Overstreet, B. T.; Miège, C.; Cooper, M. G.; Smith, L. C.; Rennermalm, A. K.

    2016-12-01

    Quantifying accurate ice surface ablation or melt rates for the Greenland Ice Sheet is important for calibrating and validating surface mass balance models and constraining sea level rise estimates. Common practice is to monitor surface ablation at defined points by manually measuring ice surface lowering in relation to stakes inserted into the ice / snow. However, this method does not account for the effects of local topography, solar zenith angle, and local variations in ice surface albedo/impurities on ablation rates. To directly address these uncertainties, we use a commercially available terrestrial LIDAR scanner (TLS) to monitor daily melt rates in the ablation zone of the Greenland Ice Sheet for 7 consecutive days in July 2016. Each survey is registered to previous scans using retroreflective cylinders and is georeferenced using static GPS measurements. Bulk ablation will be calculated using multi-temporal differential LIDAR techniques, and difficulties in referencing scans and collecting high quality surveys in this dynamic environment will be discussed, as well as areas for future research. We conclude that this novel application of TLS technology provides a spatially accurate, higher fidelity measurements of ablation across a larger area with less interpolation and less time spent than using traditional manual point based methods alone. Furthermore, this sets the stage for direct calibration, validation and cross-comparison with existing airborne (e.g. NASA's Airborne Topographic Mapper - ATM - onboard Operation IceBridge and NASA's Land, Vegetation & Ice Sensor - LVIS) and forthcoming spaceborne sensors (e.g. NASA's ICESat-2).

  1. Establishing macroecological trait datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide.

    Science.gov (United States)

    Kissling, Wilm Daniel; Dalby, Lars; Fløjgaard, Camilla; Lenoir, Jonathan; Sandel, Brody; Sandom, Christopher; Trøjelsgaard, Kristian; Svenning, Jens-Christian

    2014-07-01

    Ecological trait data are essential for understanding the broad-scale distribution of biodiversity and its response to global change. For animals, diet represents a fundamental aspect of species' evolutionary adaptations, ecological and functional roles, and trophic interactions. However, the importance of diet for macroevolutionary and macroecological dynamics remains little explored, partly because of the lack of comprehensive trait datasets. We compiled and evaluated a comprehensive global dataset of diet preferences of mammals ("MammalDIET"). Diet information was digitized from two global and cladewide data sources and errors of data entry by multiple data recorders were assessed. We then developed a hierarchical extrapolation procedure to fill-in diet information for species with missing information. Missing data were extrapolated with information from other taxonomic levels (genus, other species within the same genus, or family) and this extrapolation was subsequently validated both internally (with a jack-knife approach applied to the compiled species-level diet data) and externally (using independent species-level diet information from a comprehensive continentwide data source). Finally, we grouped mammal species into trophic levels and dietary guilds, and their species richness as well as their proportion of total richness were mapped at a global scale for those diet categories with good validation results. The success rate of correctly digitizing data was 94%, indicating that the consistency in data entry among multiple recorders was high. Data sources provided species-level diet information for a total of 2033 species (38% of all 5364 terrestrial mammal species, based on the IUCN taxonomy). For the remaining 3331 species, diet information was mostly extrapolated from genus-level diet information (48% of all terrestrial mammal species), and only rarely from other species within the same genus (6%) or from family level (8%). Internal and external

  2. Utilizing topobathy LIDAR datasets to identify shoreline variations and to direct charting updates in the northern Gulf of Mexico

    Science.gov (United States)

    Gremillion, S. L.; Wright, S. L.

    2017-12-01

    Topographic and bathymetric light detection and ranging (LIDAR), remote sensing tools used to measure vertical elevations, are commonly employed to monitor shoreline fluctuations. Many of these publicly available datasets provide wide-swath, nearshore topobathy which can be used to extract shoreline positions and analyze coastlines experiencing the greatest temporal and spatial variability. This study focused on the shorelines of Mississippi's Jackson County to determine the minimum time for significant positional changes to occur, relative to currently published NOAA navigational charts. Many of these dynamic shorelines are vulnerable to relative sea level rise, storm surge, and coastal erosion. Utilizing LIDAR datasets from 1998-2015, shoreline positions were derived and analyzed against NOAA's Continually Updated Shoreline Product (CUSP) to recommend the frequency at which future surveys should be conducted. Advisement of charting updates were based upon the resolution of published charts, and the magnitude of observed variances. Jackson County shorelines were divided into four areas for analysis; the mainland, Horn Island, Petit Bois Island (PBI), and a dredge spoil area west of PBI. The mainland shoreline experienced an average change rate of +0.57 m/yr during the study period. This stability was due to engineering structures implemented in the early 1920's to protect against tropical storms. Horn Island, the most stable barrier island, changed an average of -1.34 m/yr, while PBI had an average change of -2.70 m/yr throughout. Lastly, the dredge spoil area changed by +9.06 m/yr. Based on these results, it is recommended that LIDAR surveys for Jackson County's mainland be conducted at least every two years, while surveys of the offshore barrier islands be conducted annually. Furthermore, insufficient LIDAR data for Round Island and the Round Island Marsh Restoration Project highlight these two areas as priority targets for future surveys.

  3. A re-analysis of the Lake Suigetsu terrestrial radiocarbon calibration dataset

    International Nuclear Information System (INIS)

    Staff, R.A.; Bronk Ramsey, C.; Nakagawa, T.

    2010-01-01

    Lake Suigetsu, Honshu Island, Japan provides an ideal sedimentary sequence from which to derive a wholly terrestrial radiocarbon calibration curve back to the limits of radiocarbon detection (circa 60 ka bp). The presence of well-defined, annually-deposited laminae (varves) throughout the entirety of this period provides an independent, high resolution chronometer against which radiocarbon measurements of plant macrofossils from the sediment column can be directly related. However, data from the initial Lake Suigetsu project were found to diverge significantly from alternative, marine-based calibration datasets released around the same time (e.g. ). The main source of this divergence is thought to be the result of inaccuracies in the absolute age profile of the Suigetsu project, caused by both varve counting uncertainties and gaps in the sediment column of unknown duration between successively-drilled core sections. Here, a re-analysis of the previously-published Lake Suigetsu data is conducted. The most recent developments in Bayesian statistical modelling techniques (OxCal v4.1; ) are implemented to fit the Suigetsu data to the latest radiocarbon calibration datasets and thereby estimate the duration of the inter-core section gaps in the Suigetsu data. In this way, the absolute age of the Lake Suigetsu sediment profile is more accurately defined, providing significant information for both radiocarbon calibration and palaeoenvironmental reconstruction purposes.

  4. Waveform- and Terrestrial Lidar Assessment of the Usual (Structural) Suspects in a Forest Canopy

    Science.gov (United States)

    van Aardt, J. A.; Romanczyk, P.; Kelbe, D.; van Leeuwen, M.; Cawse-Nicholson, K.; Gough, C. M.; Kampe, T. U.

    2015-12-01

    Forest inventory has evolved from standard stem diameter-height relationships, to coarse canopy metrics, to more involved ecologically-meaningful variables, such as leaf area index (LAI) and even canopy radiative transfer as a function of canopy gaps, leaf clumping, and leaf angle distributions. Accurate and precise measurement of the latter set of variables presents a challenge to the ecological and modeling communities; however, relatively novel remote sensing modalities, e.g., waveform lidar (wlidar) and terrestrial lidar systems (TLS), have the potential to adress this challenge. Research teams at Rochester Institute of Technology (RIT) and the Virginia Commonwealth University (VCU) have been collaborating with the National Ecological Observation Network (NEON) to assess vegetation canopy structure and variation at the University of Michigan Biological Research Station and the NEON Northeast domain (Harvard Forest, MA). Airborne small-footprint wlidar data, in-situ TLS data, and first-principles, physics-based simulation tools are being used to study (i) the impact of vegetation canopy geometric elements on wlidar signals (twigs and petioles have been deemed negligible), (ii) the analysis of airborne wlidar data for top-down assessment of canopy metrics such as LAI, and (iii) our ability to extract "bottom-up" canopy structure from TLS using scans registered to each other using a novel marker-free registration approach (e.g., basal area: R2=0.82, RMSE=7.43 m2/ha). Such studies indicate that we can potentially assess radiative transfer through vegetation canopies remotely using a vertically-stratified approach with wlidar, and augment such an approach via rapid-scan TLS technology to gain a better understanding of fine-scale variation in canopy structure. This in turn is key to quantifying and modeling radiative transfer based on understanding of forest canopy structural change as a function of ecosystem development, climate, and anthropogenic drivers.

  5. CURB-BASED STREET FLOOR EXTRACTION FROM MOBILE TERRESTRIAL LIDAR POINT CLOUD

    Directory of Open Access Journals (Sweden)

    S. Ibrahim

    2012-07-01

    Full Text Available Mobile terrestrial laser scanners (MTLS produce huge 3D point clouds describing the terrestrial surface, from which objects like different street furniture can be generated. Extraction and modelling of the street curb and the street floor from MTLS point clouds is important for many applications such as right-of-way asset inventory, road maintenance and city planning. The proposed pipeline for the curb and street floor extraction consists of a sequence of five steps: organizing the 3D point cloud and nearest neighbour search; 3D density-based segmentation to segment the ground; morphological analysis to refine out the ground segment; derivative of Gaussian filtering to detect the curb; solving the travelling salesman problem to form a closed polygon of the curb and point-inpolygon test to extract the street floor. Two mobile laser scanning datasets of different scenes are tested with the proposed pipeline. The results of the extracted curb and street floor are evaluated based on a truth data. The obtained detection rates for the extracted street floor for the datasets are 95% and 96.53%. This study presents a novel approach to the detection and extraction of the road curb and the street floor from unorganized 3D point clouds captured by MTLS. It utilizes only the 3D coordinates of the point cloud.

  6. Studies of fracture network geometry of reservoir outcrop analogues from terrestrial lidar data: attempts to quantify spatial variations of fracture characteristics

    Science.gov (United States)

    Vsemirnova, E. A.; Jones, R. R.; McCaffrey, K. J. W.

    2012-04-01

    We describe studies analysing terrestrial lidar datasets of fracture systems from a range of reservoir analogues in clastic and carbonate lithologies that represent geological analogues of offshore hydrocarbon reservoirs for the UK continental shelf. As fracture networks (observed here from centimetre to kilometre scale) can significantly affect the permeability of a fractured reservoir, the definition of fracture network geometry at various scales has become an important goal of structural analysis. The main aim of the study has been to extend the investigation of fracture networks in order to quantify spatial variations in fracture parameters in a variety of lithologies. The datasets were pre-processed using RiSCAN PRO software, and then re-sampled and filtered to derive characteristics which are traditionally measured from outcrops, including size distributions, fracture spacing and clustering statistics. This type of analysis can significantly reduce the uncertainty associated with some field fracture network measurements. The digitised fracture networks datasets are then used to investigate various aspects of spatial heterogeneity. A series of fracture maps (joints and faults) were generated at different scales, and fracture trends were studied to test scale dependency of fracture orientations. Multiscale trend analysis was then applied to describe the trend structure of the fracture networks.

  7. SEMI-AUTOMATED APPROACH FOR MAPPING URBAN TREES FROM INTEGRATED AERIAL LiDAR POINT CLOUD AND DIGITAL IMAGERY DATASETS

    Directory of Open Access Journals (Sweden)

    M. A. Dogon-Yaro

    2016-09-01

    Full Text Available Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.

  8. Semi-Automated Approach for Mapping Urban Trees from Integrated Aerial LiDAR Point Cloud and Digital Imagery Datasets

    Science.gov (United States)

    Dogon-Yaro, M. A.; Kumar, P.; Rahman, A. Abdul; Buyuksalih, G.

    2016-09-01

    Mapping of trees plays an important role in modern urban spatial data management, as many benefits and applications inherit from this detailed up-to-date data sources. Timely and accurate acquisition of information on the condition of urban trees serves as a tool for decision makers to better appreciate urban ecosystems and their numerous values which are critical to building up strategies for sustainable development. The conventional techniques used for extracting trees include ground surveying and interpretation of the aerial photography. However, these techniques are associated with some constraints, such as labour intensive field work and a lot of financial requirement which can be overcome by means of integrated LiDAR and digital image datasets. Compared to predominant studies on trees extraction mainly in purely forested areas, this study concentrates on urban areas, which have a high structural complexity with a multitude of different objects. This paper presented a workflow about semi-automated approach for extracting urban trees from integrated processing of airborne based LiDAR point cloud and multispectral digital image datasets over Istanbul city of Turkey. The paper reveals that the integrated datasets is a suitable technology and viable source of information for urban trees management. As a conclusion, therefore, the extracted information provides a snapshot about location, composition and extent of trees in the study area useful to city planners and other decision makers in order to understand how much canopy cover exists, identify new planting, removal, or reforestation opportunities and what locations have the greatest need or potential to maximize benefits of return on investment. It can also help track trends or changes to the urban trees over time and inform future management decisions.

  9. Testing the Suitability of a Terrestrial 2D LiDAR Scanner for Canopy Characterization of Greenhouse Tomato Crops

    Directory of Open Access Journals (Sweden)

    Jordi Llop

    2016-09-01

    Full Text Available Canopy characterization is essential for pesticide dosage adjustment according to vegetation volume and density. It is especially important for fresh exportable vegetables like greenhouse tomatoes. These plants are thin and tall and are planted in pairs, which makes their characterization with electronic methods difficult. Therefore, the accuracy of the terrestrial 2D LiDAR sensor is evaluated for determining canopy parameters related to volume and density and established useful correlations between manual and electronic parameters for leaf area estimation. Experiments were performed in three commercial tomato greenhouses with a paired plantation system. In the electronic characterization, a LiDAR sensor scanned the plant pairs from both sides. The canopy height, canopy width, canopy volume, and leaf area were obtained. From these, other important parameters were calculated, like the tree row volume, leaf wall area, leaf area index, and leaf area density. Manual measurements were found to overestimate the parameters compared with the LiDAR sensor. The canopy volume estimated with the scanner was found to be reliable for estimating the canopy height, volume, and density. Moreover, the LiDAR scanner could assess the high variability in canopy density along rows and hence is an important tool for generating canopy maps.

  10. Automatic Matching of Large Scale Images and Terrestrial LIDAR Based on App Synergy of Mobile Phone

    Science.gov (United States)

    Xia, G.; Hu, C.

    2018-04-01

    The digitalization of Cultural Heritage based on ground laser scanning technology has been widely applied. High-precision scanning and high-resolution photography of cultural relics are the main methods of data acquisition. The reconstruction with the complete point cloud and high-resolution image requires the matching of image and point cloud, the acquisition of the homonym feature points, the data registration, etc. However, the one-to-one correspondence between image and corresponding point cloud depends on inefficient manual search. The effective classify and management of a large number of image and the matching of large image and corresponding point cloud will be the focus of the research. In this paper, we propose automatic matching of large scale images and terrestrial LiDAR based on APP synergy of mobile phone. Firstly, we develop an APP based on Android, take pictures and record related information of classification. Secondly, all the images are automatically grouped with the recorded information. Thirdly, the matching algorithm is used to match the global and local image. According to the one-to-one correspondence between the global image and the point cloud reflection intensity image, the automatic matching of the image and its corresponding laser radar point cloud is realized. Finally, the mapping relationship between global image, local image and intensity image is established according to homonym feature point. So we can establish the data structure of the global image, the local image in the global image, the local image corresponding point cloud, and carry on the visualization management and query of image.

  11. Bounding uncertainty in volumetric geometric models for terrestrial lidar observations of ecosystems.

    Science.gov (United States)

    Paynter, Ian; Genest, Daniel; Peri, Francesco; Schaaf, Crystal

    2018-04-06

    Volumetric models with known biases are shown to provide bounds for the uncertainty in estimations of volume for ecologically interesting objects, observed with a terrestrial laser scanner (TLS) instrument. Bounding cuboids, three-dimensional convex hull polygons, voxels, the Outer Hull Model and Square Based Columns (SBCs) are considered for their ability to estimate the volume of temperate and tropical trees, as well as geomorphological features such as bluffs and saltmarsh creeks. For temperate trees, supplementary geometric models are evaluated for their ability to bound the uncertainty in cylinder-based reconstructions, finding that coarser volumetric methods do not currently constrain volume meaningfully, but may be helpful with further refinement, or in hybridized models. Three-dimensional convex hull polygons consistently overestimate object volume, and SBCs consistently underestimate volume. Voxel estimations vary in their bias, due to the point density of the TLS data, and occlusion, particularly in trees. The response of the models to parametrization is analysed, observing unexpected trends in the SBC estimates for the drumlin dataset. Establishing that this result is due to the resolution of the TLS observations being insufficient to support the resolution of the geometric model, it is suggested that geometric models with predictable outcomes can also highlight data quality issues when they produce illogical results.

  12. Development of teaching modules for geology and engineering coursework using terrestrial LiDAR scanning systems

    Science.gov (United States)

    Yarbrough, L. D.; Katzenstein, K.

    2012-12-01

    Exposing students to active and local examples of physical geologic processes is beneficial to the learning process. Students typically respond with interest to examples that use state-of-the-art technologies to investigate local or regional phenomena. For lower cognitive level of learning (e.g. knowledge, comprehension, and application), the use of "close-to-home" examples ensures that students better understand concepts. By providing these examples, the students may already have a familiarity or can easily visit the location. Furthermore, these local and regional examples help students to offer quickly other examples of similar phenomena. Investigation of these examples using normal photographic techniques, as well as a more sophisticated 3-D Light Detection And Ranging (LiDAR) (AKA Terrestrial Laser Scanning or TLS) system, allows students to gain a better understanding of the scale and the mechanics of the geologic processes and hazards. The systems are used for research, teaching and outreach efforts and depending on departmental policies can be accessible to students are various learning levels. TLS systems can yield scans at sub-centimeter resolution and contain surface reflectance of targets. These systems can serve a number of learning goals that are essential for training geoscientists and engineers. While querying the data to answer geotechnical or geomorphologic related questions, students will develop skills using large, spatial databases. The upper cognitive level of learning (e.g. analysis, synthesis, and evaluation) is also promoted by using a subset of the data and correlating the physical geologic process of stream bank erosion and rock slope failures with mathematical and computer models using the scanned data. Students use the examples and laboratory exercises to help build their engineering judgment skills with Earth materials. The students learn not only applications of math and engineering science but also the economic and social implication

  13. Three-Dimensional Reconstruction of the Virtual Plant Branching Structure Based on Terrestrial LIDAR Technologies and L-System

    Science.gov (United States)

    Gong, Y.; Yang, Y.; Yang, X.

    2018-04-01

    For the purpose of extracting productions of some specific branching plants effectively and realizing its 3D reconstruction, Terrestrial LiDAR data was used as extraction source of production, and a 3D reconstruction method based on Terrestrial LiDAR technologies combined with the L-system was proposed in this article. The topology structure of the plant architectures was extracted using the point cloud data of the target plant with space level segmentation mechanism. Subsequently, L-system productions were obtained and the structural parameters and production rules of branches, which fit the given plant, was generated. A three-dimensional simulation model of target plant was established combined with computer visualization algorithm finally. The results suggest that the method can effectively extract a given branching plant topology and describes its production, realizing the extraction of topology structure by the computer algorithm for given branching plant and also simplifying the extraction of branching plant productions which would be complex and time-consuming by L-system. It improves the degree of automation in the L-system extraction of productions of specific branching plants, providing a new way for the extraction of branching plant production rules.

  14. THREE-DIMENSIONAL RECONSTRUCTION OF THE VIRTUAL PLANT BRANCHING STRUCTURE BASED ON TERRESTRIAL LIDAR TECHNOLOGIES AND L-SYSTEM

    Directory of Open Access Journals (Sweden)

    Y. Gong

    2018-04-01

    Full Text Available For the purpose of extracting productions of some specific branching plants effectively and realizing its 3D reconstruction, Terrestrial LiDAR data was used as extraction source of production, and a 3D reconstruction method based on Terrestrial LiDAR technologies combined with the L-system was proposed in this article. The topology structure of the plant architectures was extracted using the point cloud data of the target plant with space level segmentation mechanism. Subsequently, L-system productions were obtained and the structural parameters and production rules of branches, which fit the given plant, was generated. A three-dimensional simulation model of target plant was established combined with computer visualization algorithm finally. The results suggest that the method can effectively extract a given branching plant topology and describes its production, realizing the extraction of topology structure by the computer algorithm for given branching plant and also simplifying the extraction of branching plant productions which would be complex and time-consuming by L-system. It improves the degree of automation in the L-system extraction of productions of specific branching plants, providing a new way for the extraction of branching plant production rules.

  15. Study of Diagenetic Features in Rudist Buildups of Cretaceous Edwards Formation Using Ground Based Hyperspectral Scanning and Terrestrial LiDAR

    Science.gov (United States)

    Krupnik, D.; Khan, S.; Okyay, U.; Hartzell, P. J.; Biber, K.

    2015-12-01

    Ground based remote sensing is a novel technique for development of digital outcrop models which can be instrumental in performing detailed qualitative and quantitative sedimentological analysis for the study of depositional environment, diagenetic processes, and hydrocarbon reservoir characterization. For this investigation, ground-based hyperspectral data collection is combined with terrestrial LiDAR to study outcrops of Late Albian rudist buildups of the Edwards formation in the Lake Georgetown Spillway in Williamson County, Texas. The Edwards formation consists of shallow water deposits of reef and associated inter-reef facies, including rudist bioherms and biostromes. It is a significant aquifer and was investigated as a hydrocarbon play in south central Texas. Hyperspectral data were used to map compositional variation in the outcrop by distinguishing spectral properties unique to each material. Lithological variation was mapped in detail to investigate the structure and composition of rudist buildups. Hyperspectral imagery was registered to a 3D model produced from the LiDAR point cloud with an accuracy of up to one pixel. Flat-topped toucasid-rich bioherm facies were distinguished from overlying toucasid-rich biostrome facies containing chert nodules, overlying sucrosic dolostones, and uppermost peloid wackestones and packstones of back-reef facies. Ground truth was established by petrographic study of samples from this area and has validated classification products of remote sensing data. Several types of porosity were observed and have been associated with increased dolomitization. This ongoing research involves integration of remotely sensed datasets to analyze geometrical and compositional properties of this carbonate formation at a finer scale than traditional methods have achieved and seeks to develop a workflow for quick and efficient ground based remote sensing-assisted outcrop studies.

  16. SIMULATING VARIOUS TERRESTRIAL AND UAV LIDAR SCANNING CONFIGURATIONS FOR UNDERSTORY FOREST STRUCTURE MODELLING

    Directory of Open Access Journals (Sweden)

    M. Hämmerle

    2017-09-01

    Full Text Available Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations. However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS or laser scanning from unmanned aerial vehicle platforms (ULS. A prominent challenge for scanning forests is posed by occlusion, calling for proper TLS scan position or ULS flight line configurations in order to achieve an accurate representation of understory vegetation. The aim of our study is to examine the effect of TLS or ULS scanning strategies on (1 the height of individual understory trees and (2 understory canopy height raster models. We simulate full-waveform TLS and ULS point clouds of a virtual forest plot captured from various combinations of max. 12 TLS scan positions or 3 ULS flight lines. The accuracy of the respective datasets is evaluated with reference values given by the virtually scanned 3D triangle mesh tree models. TLS tree height underestimations range up to 1.84 m (15.30 % of tree height for single TLS scan positions, but combining three scan positions reduces the underestimation to maximum 0.31 m (2.41 %. Combining ULS flight lines also results in improved tree height representation, with a maximum underestimation of 0.24 m (2.15 %. The presented simulation approach offers a complementary source of information for efficient planning of field campaigns aiming at understory vegetation modelling.

  17. Simulating Various Terrestrial and Uav LIDAR Scanning Configurations for Understory Forest Structure Modelling

    Science.gov (United States)

    Hämmerle, M.; Lukač, N.; Chen, K.-C.; Koma, Zs.; Wang, C.-K.; Anders, K.; Höfle, B.

    2017-09-01

    Information about the 3D structure of understory vegetation is of high relevance in forestry research and management (e.g., for complete biomass estimations). However, it has been hardly investigated systematically with state-of-the-art methods such as static terrestrial laser scanning (TLS) or laser scanning from unmanned aerial vehicle platforms (ULS). A prominent challenge for scanning forests is posed by occlusion, calling for proper TLS scan position or ULS flight line configurations in order to achieve an accurate representation of understory vegetation. The aim of our study is to examine the effect of TLS or ULS scanning strategies on (1) the height of individual understory trees and (2) understory canopy height raster models. We simulate full-waveform TLS and ULS point clouds of a virtual forest plot captured from various combinations of max. 12 TLS scan positions or 3 ULS flight lines. The accuracy of the respective datasets is evaluated with reference values given by the virtually scanned 3D triangle mesh tree models. TLS tree height underestimations range up to 1.84 m (15.30 % of tree height) for single TLS scan positions, but combining three scan positions reduces the underestimation to maximum 0.31 m (2.41 %). Combining ULS flight lines also results in improved tree height representation, with a maximum underestimation of 0.24 m (2.15 %). The presented simulation approach offers a complementary source of information for efficient planning of field campaigns aiming at understory vegetation modelling.

  18. 3D Spatial and Spectral Fusion of Terrestrial Hyperspectral Imagery and Lidar for Hyperspectral Image Shadow Restoration Applied to a Geologic Outcrop

    Science.gov (United States)

    Hartzell, P. J.; Glennie, C. L.; Hauser, D. L.; Okyay, U.; Khan, S.; Finnegan, D. C.

    2016-12-01

    Recent advances in remote sensing technology have expanded the acquisition and fusion of active lidar and passive hyperspectral imagery (HSI) from an exclusively airborne technique to terrestrial modalities. This enables high resolution 3D spatial and spectral quantification of vertical geologic structures for applications such as virtual 3D rock outcrop models for hydrocarbon reservoir analog analysis and mineral quantification in open pit mining environments. In contrast to airborne observation geometry, the vertical surfaces observed by horizontal-viewing terrestrial HSI sensors are prone to extensive topography-induced solar shadowing, which leads to reduced pixel classification accuracy or outright removal of shadowed pixels from analysis tasks. Using a precisely calibrated and registered offset cylindrical linear array camera model, we demonstrate the use of 3D lidar data for sub-pixel HSI shadow detection and the restoration of the shadowed pixel spectra via empirical methods that utilize illuminated and shadowed pixels of similar material composition. We further introduce a new HSI shadow restoration technique that leverages collocated backscattered lidar intensity, which is resistant to solar conditions, obtained by projecting the 3D lidar points through the HSI camera model into HSI pixel space. Using ratios derived from the overlapping lidar laser and HSI wavelengths, restored shadow pixel spectra are approximated using a simple scale factor. Simulations of multiple lidar wavelengths, i.e., multi-spectral lidar, indicate the potential for robust HSI spectral restoration that is independent of the complexity and costs associated with rigorous radiometric transfer models, which have yet to be developed for horizontal-viewing terrestrial HSI sensors. The spectral restoration performance is quantified through HSI pixel classification consistency between full sun and partial sun exposures of a single geologic outcrop.

  19. 3D Scan of Ornamental Column (huabiao Using Terrestrial LiDAR and Hand-held Imager

    Directory of Open Access Journals (Sweden)

    W. Zhang

    2015-08-01

    Full Text Available In ancient China, Huabiao was a type of ornamental column used to decorate important buildings. We carried out 3D scan of a Huabiao located in Peking University, China. This Huabiao was built no later than 1742. It is carved by white marble, 8 meters in height. Clouds and various postures of dragons are carved on its body. Two instruments were used to acquire the point cloud of this Huabiao, a terrestrial LiDAR (Riegl VZ-1000 and a hand-held imager (Mantis Vision F5. In this paper, the details of the experiment were described, including the differences between these two instruments, such as working principle, spatial resolution, accuracy, instrument dimension and working flow. The point clouds obtained respectively by these two instruments were compared, and the registered point cloud of Huabiao was also presented. These should be of interest and helpful for the research communities of archaeology and heritage.

  20. Foredune Classification and Storm Response: Automated Analysis of Terrestrial Lidar DEMs

    Science.gov (United States)

    2015-06-15

    since Hurricane Sandy. 041 20/3/2015 4 Figure 1. A. The study site in Duck , NC showing the alongshore coordinates of the local coordinate...waves on March 10: Hs = 4.8 m at 16 sec Coastal Lidar and Radar Imaging System (CLARIS) Nor’easter Storm Conditions Study Site: Duck , NC...Engineer Research and Development Center, Coastal & Hydraulics Laboratory, Coastal Observation & Analysis Branch, 1261 Duck Rd, Duck , NC 27949, USA

  1. Collection, Processing and Accuracy of Mobile Terrestrial Lidar Survey Data in the Coastal Environment

    Science.gov (United States)

    2017-04-01

    is built from sequential two-dimensional linescans. A typical survey will start with the vehicle positioned parallel to the dune near the dune toe ...these maps to assess where wave runup impacted the foreshore, upper beach, and dune toe , as well as areas where aeolian transport has deposited...the lidar data. These techniques can be expanded to calculate beach/berm widths, slopes, and dune toe and dune crest positions. ERDC/CHL TR-17-5 27

  2. Evaluation of Terrestrial Carbon Cycle with the Land Use Harmonization Dataset

    Science.gov (United States)

    Sasai, T.; Nemani, R. R.

    2017-12-01

    CO2 emission by land use and land use change (LULUC) has still had a large uncertainty (±50%). We need to more accurately reveal a role of each LULUC process on terrestrial carbon cycle, and to develop more complicated land cover change model, leading to improve our understanding of the mechanism of global warming. The existing biosphere model studies do not necessarily have enough major LULUC process in the model description (e.g., clear cutting and residual soil carbon). The issue has the potential for causing an underestimation of the effect of LULUC on the global carbon exchange. In this study, the terrestrial biosphere model was modified with several LULUC processes according to the land use harmonization data set. The global mean LULUC emission from the year 1850 to 2000 was 137.2 (PgC 151year-1), and we found the noticeable trend in tropical region. As with the case of primary production in the existing studies, our results emphasized the role of tropical forest on wood productization and residual soil organic carbon by cutting. Global mean NEP was decreased by LULUC. NEP is largely affected by decreasing leaf biomass (photosynthesis) by deforestation process and increasing plant growth rate by regrowth process. We suggested that the model description related to deforestation, residual soil decomposition, wood productization and plant regrowth is important to develop a biosphere model for estimating long-term global carbon cycle.

  3. Coastal monitoring solutions of the geomorphological response of beach-dune systems using multi-temporal LiDAR datasets (Vendée coast, France)

    Science.gov (United States)

    Le Mauff, Baptiste; Juigner, Martin; Ba, Antoine; Robin, Marc; Launeau, Patrick; Fattal, Paul

    2018-03-01

    Three beach and dune systems located in the northeastern part of the Bay of Biscay in France were monitored over 5 years with a time series of three airborne LiDAR datasets. The three study sites illustrate a variety of morphological beach types found in this region. Reproducible monitoring solutions adapted to basic and complex beach and dune morphologies using LiDAR time series were investigated over two periods bounded by the three surveys. The first period (between May 2008 and August 2010) is characterized by a higher prevalence of storm events, and thus has a greater potential for eroding the coast, than the second period (between August 2010 and September 2013). During the first period, the central and northeastern part of the Bay of Biscay was notably impacted by Storm Xynthia, with water levels and wave heights exceeding the 10-year return period and 1-year return period, respectively. Despite differences in dune morphology between the sites, the dune crest (Dhigh) and the dune base (Dlow) are efficiently extracted from each DEM. Based on the extracted dune base, an original shoreline mobility indicator is built displaying a combination of the horizontal and vertical migrations of this geomorphic indicator between two LiDAR datasets. A 'Geomorphic Change Detection' is also completed by computing DEMs of Difference (DoD) resulting in segregated maps of erosion and deposition and sediment budgets. Accounting for the accuracy of LiDAR datasets, a probabilistic approach at a 95% confidence interval is used as a threshold for the Geomorphic Change Detection showing more reliable results. However, caution should be taken when interpreting thresholded maps of changes and sediment budgets because some beach processes may be masked, especially on wide tidal beaches, by only keeping the most significant changes. The results of the shoreline mobility and Geomorphic Change Detection show a high variability in the beach responses between and within the three study

  4. Multi-sourced, 3D geometric characterization of volcanogenic karst features: Integrating lidar, sonar, and geophysical datasets (Invited)

    Science.gov (United States)

    Sharp, J. M.; Gary, M. O.; Reyes, R.; Halihan, T.; Fairfield, N.; Stone, W. C.

    2009-12-01

    Karstic aquifers can form very complex hydrogeological systems and 3-D mapping has been difficult, but Lidar, phased array sonar, and improved earth resistivity techniques show promise in this and in linking metadata to models. Zacatón, perhaps the Earth’s deepest cenote, has a sub-aquatic void space exceeding 7.5 x 106 cubic m3. It is the focus of this study which has created detailed 3D maps of the system. These maps include data from above and beneath the the water table and within the rock matrix to document the extent of the immense karst features and to interpret the geologic processes that formed them. Phase 1 used high resolution (20 mm) Lidar scanning of surficial features of four large cenotes. Scan locations, selected to achieve full feature coverage once registered, were established atop surface benchmarks with UTM coordinates established using GPS and Total Stations. The combined datasets form a geo-registered mesh of surface features down to water level in the cenotes. Phase 2 conducted subsurface imaging using Earth Resistivity Imaging (ERI) geophysics. ERI identified void spaces isolated from open flow conduits. A unique travertine morphology exists in which some cenotes are dry or contain shallow lakes with flat travertine floors; some water-filled cenotes have flat floors without the cone of collapse material; and some have collapse cones. We hypothesize that the floors may have large water-filled voids beneath them. Three separate flat travertine caps were imaged: 1) La Pilita, which is partially open, exposing cap structure over a deep water-filled shaft; 2) Poza Seca, which is dry and vegetated; and 3) Tule, which contains a shallow (<1 m) lake. A fourth line was run adjacent to cenote Verde. La Pilita ERI, verified by SCUBA, documented the existence of large water-filled void zones ERI at Poza Seca showed a thin cap overlying a conductive zone extending to at least 25 m depth beneath the cap with no lower boundary of this zone evident

  5. Development and validation of fuel height models for terrestrial lidar - RxCADRE 2012

    Science.gov (United States)

    Eric M. Rowell; Carl A. Seielstad; Roger D. Ottmar

    2016-01-01

    Terrestrial laser scanning (TLS) was used to collect spatially continuous measurements of fuelbed characteristics across the plots and burn blocks of the 2012 RxCADRE experiments in Florida. Fuelbeds were scanned obliquely from plot/block edges at a height of 20 m above ground. Pre-fire blocks were scanned from six perspectives and four perspectives for post-...

  6. Improvements to and Comparison of Static Terrestrial LiDAR Self-Calibration Methods

    Directory of Open Access Journals (Sweden)

    Preston Hartzell

    2013-05-01

    Full Text Available Terrestrial laser scanners are sophisticated instruments that operate much like high-speed total stations. It has previously been shown that unmodelled systematic errors can exist in modern terrestrial laser scanners that deteriorate their geometric measurement precision and accuracy. Typically, signalised targets are used in point-based self-calibrations to identify and model the systematic errors. Although this method has proven its effectiveness, a large quantity of signalised targets is required and is therefore labour-intensive and limits its practicality. In recent years, feature-based self-calibration of aerial, mobile terrestrial, and static terrestrial laser scanning systems has been demonstrated. In this paper, the commonalities and differences between point-based and plane-based self-calibration (in terms of model identification and parameter correlation are explored. The results of this research indicate that much of the knowledge from point-based self-calibration can be directly transferred to plane-based calibration and that the two calibration approaches are nearly equivalent. New network configurations, such as the inclusion of tilted scans, were also studied and prove to be an effective means for strengthening the self-calibration solution, and improved recoverability of the horizontal collimation axis error for hybrid scanners, which has always posed a challenge in the past.

  7. GIS-Based Detection of Gullies in Terrestrial LiDAR Data of the Cerro Llamoca Peatland (Peru

    Directory of Open Access Journals (Sweden)

    Markus Forbriger

    2013-11-01

    Full Text Available Cushion peatlands are typical features of the high altitude Andes in South America. Due to the adaptation to difficult environmental conditions, they are very fragile ecosystems and therefore vulnerable to environmental and climate changes. Peatland erosion has severe effects on their ecological functions, such as water storage capacity. Thus, erosion monitoring is highly advisable. Erosion quantification and monitoring can be supported by high-resolution terrestrial Light Detection and Ranging (LiDAR. In this study, a novel Geographic Information System (GIS-based method for the automatic delineation and geomorphometric description of gullies in cushion peatlands is presented. The approach is a multi-step workflow based on a gully edge extraction and a sink filling algorithm applied to a conditioned digital terrain model. Our method enables the creation of GIS-ready polygons of the gullies and the derivation of geomorphometric parameters along the entire channel course. Automatically derived boundaries and gully area values correspond to a high degree (93% with manually digitized reference polygons. The set of methods developed in this study offers a suitable tool for the monitoring and scientific analysis of fluvial morphology in cushion peatlands.

  8. Canopy rainfall partitioning across an urbanization gradient in forest structure as characterized by terrestrial LiDAR

    Science.gov (United States)

    Mesta, D. C.; Van Stan, J. T., II; Yankine, S. A.; Cote, J. F.; Jarvis, M. T.; Hildebrandt, A.; Friesen, J.; Maldonado, G.

    2017-12-01

    As urbanization expands, greater forest area is shifting from natural stand structures to urban stand structures, like forest fragments and landscaped tree rows. Changes in forest canopy structure have been found to drastically alter the amount of rainwater reaching the surface. However, stormwater management models generally treat all forest structures (beyond needle versus broadleaved) similarly. This study examines the rainfall partitioning of Pinus spp. canopies along a natural-to-urban forest gradient and compares these to canopy structural measurements using terrestrial LiDAR. Throughfall and meteorological observations were also used to estimate parameters of the commonly-used Gash interception model. Preliminary findings indicate that as forest structure changed from natural, closed canopy conditions to semi-closed canopy fragments and, ultimately, to exposed urban landscaping tree rows, the interchange between throughfall and rainfall interception also changed. This shift in partitioning between throughfall and rainfall interception may be linked to intuitive parameters, like canopy closure and density, as well as more complex metrics, like the fine-scale patterning of gaps (ie, lacunarity). Thus, results indicate that not all forests of the same species should be treated the same by stormwater models. Rather, their canopy structural characteristics should be used to vary their hydrometeorological interactions.

  9. Mapping Fearscapes of a Mammalian Herbivore using Terrestrial LiDAR and UAV Imagery

    Science.gov (United States)

    Olsoy, P.; Nobler, J. D.; Forbey, J.; Rachlow, J. L.; Burgess, M. A.; Glenn, N. F.; Shipley, L. A.

    2013-12-01

    Concealment allows prey animals to remain hidden from a predator and can influence both real and perceived risks of predation. The heterogeneous nature of vegetative structure can create a variable landscape of concealment - a 'fearscape' - that may influence habitat quality and use by prey. Traditional measurements of concealment rely on a limited number of distances, heights, and vantage points, resulting in small snapshots of concealment available to a prey animal. Our objective was to demonstrate the benefits of emerging remote sensing techniques to map fearscapes for pygmy rabbits (Brachylagus idahoensis) in sagebrush steppe habitat across a continuous range of scales. Specifically, we used vegetation height rasters derived from terrestrial laser scanning (TLS) to create viewsheds from multiple vantage points, representing predator visibility. The sum of all the viewsheds modeled horizontal concealment of prey at both the shrub and patch scales. We also used a small, unmanned aerial vehicle (UAV) to determine vertical concealment at a habitat scale. Terrestrial laser scanning provided similar estimates of horizontal concealment at the shrub scale when compared to photographic methods (R2 = 0.85). Both TLS and UAV provide the potential to quantify concealment of prey from multiple distances, heights, or vantage points, allowing the creation of a manipulable fearscape map that can be correlated with habitat use by prey animals. The predictive power of such a map also could identify shrubs or patches for fine scale nutritional and concealment analysis for future investigation and conservation efforts. Fearscape map at the mound-scale. Viewsheds were calculated from 100 equally spaced observer points located 4 m from the closest on-mound sagebrush of interest. Red areas offer low concealment, while green areas provide high concealment.

  10. AUTOMATIC THICKNESS AND VOLUME ESTIMATION OF SPRAYED CONCRETE ON ANCHORED RETAINING WALLS FROM TERRESTRIAL LIDAR DATA

    Directory of Open Access Journals (Sweden)

    J. Martínez-Sánchez

    2016-06-01

    Full Text Available When ground conditions are weak, particularly in free formed tunnel linings or retaining walls, sprayed concrete can be applied on the exposed surfaces immediately after excavation for shotcreting rock outcrops. In these situations, shotcrete is normally applied conjointly with rock bolts and mesh, thereby supporting the loose material that causes many of the small ground falls. On the other hand, contractors want to determine the thickness and volume of sprayed concrete for both technical and economic reasons: to guarantee their structural strength but also, to not deliver excess material that they will not be paid for. In this paper, we first introduce a terrestrial LiDAR-based method for the automatic detection of rock bolts, as typically used in anchored retaining walls. These ground support elements are segmented based on their geometry and they will serve as control points for the co-registration of two successive scans, before and after shotcreting. Then we compare both point clouds to estimate the sprayed concrete thickness and the expending volume on the wall. This novel methodology is demonstrated on repeated scan data from a retaining wall in the city of Vigo (Spain, resulting in a rock bolts detection rate of 91%, that permits to obtain a detailed information of the thickness and calculate a total volume of 3597 litres of concrete. These results have verified the effectiveness of the developed approach by increasing productivity and improving previous empirical proposals for real time thickness estimation.

  11. Automatic Thickness and Volume Estimation of Sprayed Concrete on Anchored Retaining Walls from Terrestrial LIDAR Data

    Science.gov (United States)

    Martínez-Sánchez, J.; Puente, I.; GonzálezJorge, H.; Riveiro, B.; Arias, P.

    2016-06-01

    When ground conditions are weak, particularly in free formed tunnel linings or retaining walls, sprayed concrete can be applied on the exposed surfaces immediately after excavation for shotcreting rock outcrops. In these situations, shotcrete is normally applied conjointly with rock bolts and mesh, thereby supporting the loose material that causes many of the small ground falls. On the other hand, contractors want to determine the thickness and volume of sprayed concrete for both technical and economic reasons: to guarantee their structural strength but also, to not deliver excess material that they will not be paid for. In this paper, we first introduce a terrestrial LiDAR-based method for the automatic detection of rock bolts, as typically used in anchored retaining walls. These ground support elements are segmented based on their geometry and they will serve as control points for the co-registration of two successive scans, before and after shotcreting. Then we compare both point clouds to estimate the sprayed concrete thickness and the expending volume on the wall. This novel methodology is demonstrated on repeated scan data from a retaining wall in the city of Vigo (Spain), resulting in a rock bolts detection rate of 91%, that permits to obtain a detailed information of the thickness and calculate a total volume of 3597 litres of concrete. These results have verified the effectiveness of the developed approach by increasing productivity and improving previous empirical proposals for real time thickness estimation.

  12. Flood Modeling Using a Synthesis of Multi-Platform LiDAR Data

    Directory of Open Access Journals (Sweden)

    Ryan M. Csontos

    2013-09-01

    Full Text Available This study examined the utility of a high resolution ground-based (mobile and terrestrial Light Detection and Ranging (LiDAR dataset (0.2 m point-spacing supplemented with a coarser resolution airborne LiDAR dataset (5 m point-spacing for use in a flood inundation analysis. The techniques for combining multi-platform LiDAR data into a composite dataset in the form of a triangulated irregular network (TIN are described, and quantitative comparisons were made to a TIN generated solely from the airborne LiDAR dataset. For example, a maximum land surface elevation difference of 1.677 m and a mean difference of 0.178 m were calculated between the datasets based on sample points. Utilizing the composite and airborne LiDAR-derived TINs, a flood inundation comparison was completed using a one-dimensional steady flow hydraulic modeling analysis. Quantitative comparisons of the water surface profiles and depth grids indicated an underestimation of flooding extent, volume, and maximum flood height using the airborne LiDAR data alone. A 35% increase in maximum flood height was observed using the composite LiDAR dataset. In addition, the extents of the water surface profiles generated from the two datasets were found to be statistically significantly different. The urban and mountainous characteristics of the study area as well as the density (file size of the high resolution ground based LiDAR data presented both opportunities and challenges for flood modeling analyses.

  13. A terrestrial lidar-based workflow for determining three-dimensional slip vectors and associated uncertainties

    Science.gov (United States)

    Gold, Peter O.; Cowgill, Eric; Kreylos, Oliver; Gold, Ryan D.

    2012-01-01

    Three-dimensional (3D) slip vectors recorded by displaced landforms are difficult to constrain across complex fault zones, and the uncertainties associated with such measurements become increasingly challenging to assess as landforms degrade over time. We approach this problem from a remote sensing perspective by using terrestrial laser scanning (TLS) and 3D structural analysis. We have developed an integrated TLS data collection and point-based analysis workflow that incorporates accurate assessments of aleatoric and epistemic uncertainties using experimental surveys, Monte Carlo simulations, and iterative site reconstructions. Our scanning workflow and equipment requirements are optimized for single-operator surveying, and our data analysis process is largely completed using new point-based computing tools in an immersive 3D virtual reality environment. In a case study, we measured slip vector orientations at two sites along the rupture trace of the 1954 Dixie Valley earthquake (central Nevada, United States), yielding measurements that are the first direct constraints on the 3D slip vector for this event. These observations are consistent with a previous approximation of net extension direction for this event. We find that errors introduced by variables in our survey method result in <2.5 cm of variability in components of displacement, and are eclipsed by the 10–60 cm epistemic errors introduced by reconstructing the field sites to their pre-erosion geometries. Although the higher resolution TLS data sets enabled visualization and data interactivity critical for reconstructing the 3D slip vector and for assessing uncertainties, dense topographic constraints alone were not sufficient to significantly narrow the wide (<26°) range of allowable slip vector orientations that resulted from accounting for epistemic uncertainties.

  14. Comparison of Stem Map Developed from Crown Geometry Allometry Linked Census Data to Airborne and Terrestrial Lidar at Harvard Forest, MA

    Science.gov (United States)

    Sullivan, F.; Palace, M. W.; Ducey, M. J.; David, O.; Cook, B. D.; Lepine, L. C.

    2014-12-01

    Harvard Forest in Petersham, MA, USA is the location of one of the temperate forest plots established by the Center for Tropical Forest Science (CTFS) as a joint effort with Harvard Forest and the Smithsonian Institute's Forest Global Earth Observatory (ForestGEO) to characterize ecosystem processes and forest dynamics. Census of a 35 ha plot on Prospect Hill was completed during the winter of 2014 by researchers at Harvard Forest. Census data were collected according to CTFS protocol; measured variables included species, stem diameter, and relative X-Y locations. Airborne lidar data were collected over the censused plot using the high spatial resolution Goddard LiDAR, Hyperspectral, and Thermal sensor package (G-LiHT) during June 2012. As part of a separate study, 39 variable radius plots (VRPs) were randomly located and sampled within and throughout the Prospect Hill CTFS/ForestGEO plot during September and October 2013. On VRPs, biometric properties of trees were sampled, including species, stem diameter, total height, crown base height, crown radii, and relative location to plot centers using a 20 Basal Area Factor prism. In addition, a terrestrial-based lidar scanner was used to collect one lidar scan at plot center for 38 of the 39 VRPs. Leveraging allometric equations of crown geometry and tree height developed from 374 trees and 16 different species sampled on 39 VRPs, a 3-dimensional stem map will be created using the Harvard Forest ForestGEO Prospect Hill census. Vertical and horizontal structure of 3d field-based stem maps will be compared to terrestrial and airborne lidar scan data. Furthermore, to assess the quality of allometric equations, a 2d canopy height raster of the field-based stem map will be compared to a G-LiHT derived canopy height model for the 35 ha census plot. Our automated crown delineation methods will be applied to the 2d representation of the census stem map and the G-LiHT canopy height model. For future work related to this study

  15. Magnitude-frequency and Spatial Distribution of Rockfalls in the White Canyon, British Columbia using Terrestrial LiDAR and Microseismic Monitoring Systems

    Science.gov (United States)

    van Veen, M.

    2015-12-01

    Transportation corridors built along natural slopes are subject to frequent rockfall hazards, which can disrupt service and cause damage to infrastructure. Many of these areas exist along the Fraser-Thompson corridor of the CN rail line in Southern British Columbia, particularly in the White Canyon area near Lytton. Here the rail track is situated between the 500 m high slopes and the river, for 2.4 km. The frequency-magnitude relationship between these events and the percentage of rockfalls making it to track level are important components of hazard assessment for these slopes. Traditional methods of collecting rockfall data in this area involve visual inspection by maintenance personnel, however this is an onerous task for such a large slope with frequent rockfall activity, and therefore the rockfall record for this area is often lacking data. Since 2012, high-resolution terrestrial LiDAR (Light detection and ranging) data has been collected for the White Canyon area and analysis of change from sequential LiDAR scans provides detailed data that can't be obtained from traditional rockfall databases, including the magnitude and spatial distribution of rockfall events. While the LiDAR change detection can be useful in identifying rockfall volumes and source zones, it can be difficult to determine the end location of each rockfall and the exact timing of events, as scan data is usually collected over a period of several months. Recently, a microseismic monitoring system has been deployed over a section of the railway track and data is available on time and location of impact at the track level, which permits assessment of the number of rockfalls traversing the whole slope down to track level. This, in combination with data on rockfall magnitudes and source zones obtained from the LiDAR change detection can provide useful information for management of tracks in these hazardous settings and also provides data for calibration of rockfall modelling.

  16. Classification of forest development stages from national low-density lidar datasets: a comparison of machine learning methods

    Directory of Open Access Journals (Sweden)

    R. Valbuena

    2016-02-01

    Full Text Available The area-based method has become a widespread approach in airborne laser scanning (ALS, being mainly employed for the estimation of continuous variables describing forest attributes: biomass, volume, density, etc. However, to date, classification methods based on machine learning, which are fairly common in other remote sensing fields, such as land use / land cover classification using multispectral sensors, have been largely overseen in forestry applications of ALS. In this article, we wish to draw the attention on statistical methods predicting discrete responses, for supervised classification of ALS datasets. A wide spectrum of approaches are reviewed: discriminant analysis (DA using various classifiers –maximum likelihood, minimum volume ellipsoid, naïve Bayes–, support vector machine (SVM, artificial neural networks (ANN, random forest (RF and nearest neighbour (NN methods. They are compared in the context of a classification of forest areas into development classes (DC used in practical silvicultural management in Finland, using their low-density national ALS dataset. We observed that RF and NN had the most balanced error matrices, with cross-validated predictions which were mainly unbiased for all DCs. Although overall accuracies were higher for SVM and ANN, their results were very dissimilar across DCs, and they can therefore be only advantageous if certain DCs are targeted. DA methods underperformed in comparison to other alternatives, and were only advantageous for the detection of seedling stands. These results show that, besides the well demonstrated capacity of ALS for quantifying forest stocks, there is a great deal of potential for predicting categorical variables in general, and forest types in particular. In conclusion, we consider that the presented methodology shall also be adapted to the type of forest classes that can be relevant to Mediterranean ecosystems, opening a range of possibilities for future research, in which

  17. Estimating vegetation biomass and cover across large plots in shrub and grass dominated drylands using terrestrial lidar and machine learning

    Science.gov (United States)

    Anderson, Kyle E.; Glenn, Nancy F.; Spaete, Lucas P.; Shinneman, Douglas; Pilliod, David S.; Arkle, Robert; McIlroy, Susan; Derryberry, DeWayne R.

    2018-01-01

    Terrestrial laser scanning (TLS) has been shown to enable an efficient, precise, and non-destructive inventory of vegetation structure at ranges up to hundreds of meters. We developed a method that leverages TLS collections with machine learning techniques to model and map canopy cover and biomass of several classes of short-stature vegetation across large plots. We collected high-definition TLS scans of 26 1-ha plots in desert grasslands and big sagebrush shrublands in southwest Idaho, USA. We used the Random Forests machine learning algorithm to develop decision tree models predicting the biomass and canopy cover of several vegetation classes from statistical descriptors of the aboveground heights of TLS points. Manual measurements of vegetation characteristics collected within each plot served as training and validation data. Models based on five or fewer TLS descriptors of vegetation heights were developed to predict the canopy cover fraction of shrubs (R2 = 0.77, RMSE = 7%), annual grasses (R2 = 0.70, RMSE = 21%), perennial grasses (R2 = 0.36, RMSE = 12%), forbs (R2 = 0.52, RMSE = 6%), bare earth or litter (R2 = 0.49, RMSE = 19%), and the biomass of shrubs (R2 = 0.71, RMSE = 175 g) and herbaceous vegetation (R2 = 0.61, RMSE = 99 g) (all values reported are out-of-bag). Our models explained much of the variability between predictions and manual measurements, and yet we expect that future applications could produce even better results by reducing some of the methodological sources of error that we encountered. Our work demonstrates how TLS can be used efficiently to extend manual measurement of vegetation characteristics from small to large plots in grasslands and shrublands, with potential application to other similarly structured ecosystems. Our method shows that vegetation structural characteristics can be modeled without classifying and delineating individual plants, a challenging and time-consuming step common in previous

  18. GRIP LIDAR ATMOSPHERIC SENSING EXPERIMENT (LASE) V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GRIP Lidar Atmospheric Sensing Experiment (LASE) dataset was collected by NASA's Lidar Atmospheric Sensing Experiment (LASE) system, which is an airborne...

  19. Lidar to lidar calibration

    DEFF Research Database (Denmark)

    Fernandez Garcia, Sergio; Villanueva, Héctor

    This report presents the result of the lidar to lidar calibration performed for ground-based lidar. Calibration is here understood as the establishment of a relation between the reference lidar wind speed measurements with measurement uncertainties provided by measurement standard and corresponding...... lidar wind speed indications with associated measurement uncertainties. The lidar calibration concerns the 10 minute mean wind speed measurements. The comparison of the lidar measurements of the wind direction with that from the reference lidar measurements are given for information only....

  20. 2008 St. Johns County, FL Countywide Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Airborne terrestrial LiDAR was collected for St. Johns County, FL. System Parameters/Flight Plan. The LiDAR system acquisition parameters were developed based on a...

  1. Recording Cultural Heritage Using Terrestrial Laserscanning - Dealing with the System, the Huge Datasets they Create and Ways to Extract the Necessary Deliverables you can Work with

    Science.gov (United States)

    Christofori, E.; Bierwagen, J.

    2013-07-01

    Recording Cultural Heritage objects using terrestrial laserscanning becomes more and more popular over the last years. Since terrestrial Laserscanning System (TLS) Manufacturers have strongly increased the amount and speed of data captured with a single scan at each system upgrade and cutting down system costs the use of TLS Systems for recording cultural heritage is an option for recording worth to think about beside traditional methods like Photogrammetric. TLS Systems can be a great tool for capturing complex cultural heritage object within a short amount of time beside the traditional methods but can be a nightmare to handle for further process if not used right while capturing. Furthermore TLS Systems still have to be recognized as survey equipment, even though some of the manufactures promote them as everyday tool. They have to be used in an intelligent way having in mind the clients and the individual cultural objects needs. Thus the efficient way to use TLS Systems for data recording becomes a relevant topic to deal with the huge Amount of data the Systems collect while recording. Already small projects can turn into huge Pointcloud Datasets that End user, like Architects or Archaeologist neither can't deal with as their technical equipment doesn't fit the requirements of the Dataset nor do they have the software tools to use the Data as the current software tools still are high prized. Even the necessary interpretation of the Dataset can be a tough task if the people who have to work on with the Pointcloud aren't educated right in order to understand TLS and the results it creates. The use of TLS Systems has to have in mind the project requirements of the individual Heritage Object, like the required accuracy, standards for Levels of Details (e.g. "Empfehlungen für die Baudokumentation, Günther Eckstein, Germany"), the required kind of Deliverables (Visualization, 2D Drawings, True Deformation Drawings, 3D Models, BIM or 4D - Animations) as well as the

  2. RECORDING CULTURAL HERITAGE USING TERRESTRIAL LASERSCANNING – DEALING WITH THE SYSTEM, THE HUGE DATASETS THEY CREATE AND WAYS TO EXTRACT THE NECESSARY DELIVERABLES YOU CAN WORK WITH

    Directory of Open Access Journals (Sweden)

    E. Christofori

    2013-07-01

    Full Text Available Recording Cultural Heritage objects using terrestrial laserscanning becomes more and more popular over the last years. Since terrestrial Laserscanning System (TLS Manufacturers have strongly increased the amount and speed of data captured with a single scan at each system upgrade and cutting down system costs the use of TLS Systems for recording cultural heritage is an option for recording worth to think about beside traditional methods like Photogrammetric. TLS Systems can be a great tool for capturing complex cultural heritage object within a short amount of time beside the traditional methods but can be a nightmare to handle for further process if not used right while capturing. Furthermore TLS Systems still have to be recognized as survey equipment, even though some of the manufactures promote them as everyday tool. They have to be used in an intelligent way having in mind the clients and the individual cultural objects needs. Thus the efficient way to use TLS Systems for data recording becomes a relevant topic to deal with the huge Amount of data the Systems collect while recording. Already small projects can turn into huge Pointcloud Datasets that End user, like Architects or Archaeologist neither can't deal with as their technical equipment doesn't fit the requirements of the Dataset nor do they have the software tools to use the Data as the current software tools still are high prized. Even the necessary interpretation of the Dataset can be a tough task if the people who have to work on with the Pointcloud aren't educated right in order to understand TLS and the results it creates. The use of TLS Systems has to have in mind the project requirements of the individual Heritage Object, like the required accuracy, standards for Levels of Details (e.g. "Empfehlungen für die Baudokumentation, Günther Eckstein, Germany", the required kind of Deliverables (Visualization, 2D Drawings, True Deformation Drawings, 3D Models, BIM or 4D

  3. 2006 Volusia County Florida LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset is the lidar data for Volusia County, Florida, approximately 1,432 square miles, acquired in early March of 2006. A total of 143 flight lines of Lidar...

  4. 2007 USGS Lidar: Canyon Fire (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Southern California Light Detection and Ranging (LiDAR) data is to provide high accuracy LIDAR data. These datasets will be the initial acquisition to support...

  5. 3D terrestrial lidar data classification of complex natural scenes using a multi-scale dimensionality criterion: Applications in geomorphology

    Science.gov (United States)

    Brodu, N.; Lague, D.

    2012-03-01

    result is given at each point, allowing the user to remove the points for which the classification is uncertain. The process can be both fully automated (minimal user input once, all scenes treated in large computation batches), but also fully customized by the user including a graphical definition of the classifiers if so desired. Working classifiers can be exchanged between users independently of the instrument used to acquire the data avoiding the need to go through full training of the classifier. Although developed for fully 3D data, the method can be readily applied to 2.5D airborne lidar data.

  6. Forest Inventory with Terrestrial LiDAR: A Comparison of Static and Hand-Held Mobile Laser Scanning

    Directory of Open Access Journals (Sweden)

    Sébastien Bauwens

    2016-06-01

    Full Text Available The application of static terrestrial laser scanning (TLS in forest inventories is becoming more effective. Nevertheless, the occlusion effect is still limiting the processing efficiency to extract forest attributes. The use of a mobile laser scanner (MLS would reduce this occlusion. In this study, we assessed and compared a hand-held mobile laser scanner (HMLS with two TLS approaches (single scan: SS, and multi scan: MS for the estimation of several forest parameters in a wide range of forest types and structures. We found that SS is competitive to extract the ground surface of forest plots, while MS gives the best result to describe the upper part of the canopy. The whole cross-section at 1.3 m height is scanned for 91% of the trees (DBH > 10 cm with the HMLS leading to the best results for DBH estimates (bias of −0.08 cm and RMSE of 1.11 cm, compared to no fully-scanned trees for SS and 42% fully-scanned trees for MS. Irregularities, such as bark roughness and non-circular cross-section may explain the negative bias encountered for all of the scanning approaches. The success of using MLS in forests will allow for 3D structure acquisition on a larger scale and in a time-efficient manner.

  7. Simulation of Satellite, Airborne and Terrestrial LiDAR with DART (I):Waveform Simulation with Quasi-Monte Carlo Ray Tracing

    Science.gov (United States)

    Gastellu-Etchegorry, Jean-Philippe; Yin, Tiangang; Lauret, Nicolas; Grau, Eloi; Rubio, Jeremy; Cook, Bruce D.; Morton, Douglas C.; Sun, Guoqing

    2016-01-01

    Light Detection And Ranging (LiDAR) provides unique data on the 3-D structure of atmosphere constituents and the Earth's surface. Simulating LiDAR returns for different laser technologies and Earth scenes is fundamental for evaluating and interpreting signal and noise in LiDAR data. Different types of models are capable of simulating LiDAR waveforms of Earth surfaces. Semi-empirical and geometric models can be imprecise because they rely on simplified simulations of Earth surfaces and light interaction mechanisms. On the other hand, Monte Carlo ray tracing (MCRT) models are potentially accurate but require long computational time. Here, we present a new LiDAR waveform simulation tool that is based on the introduction of a quasi-Monte Carlo ray tracing approach in the Discrete Anisotropic Radiative Transfer (DART) model. Two new approaches, the so-called "box method" and "Ray Carlo method", are implemented to provide robust and accurate simulations of LiDAR waveforms for any landscape, atmosphere and LiDAR sensor configuration (view direction, footprint size, pulse characteristics, etc.). The box method accelerates the selection of the scattering direction of a photon in the presence of scatterers with non-invertible phase function. The Ray Carlo method brings traditional ray-tracking into MCRT simulation, which makes computational time independent of LiDAR field of view (FOV) and reception solid angle. Both methods are fast enough for simulating multi-pulse acquisition. Sensitivity studies with various landscapes and atmosphere constituents are presented, and the simulated LiDAR signals compare favorably with their associated reflectance images and Laser Vegetation Imaging Sensor (LVIS) waveforms. The LiDAR module is fully integrated into DART, enabling more detailed simulations of LiDAR sensitivity to specific scene elements (e.g., atmospheric aerosols, leaf area, branches, or topography) and sensor configuration for airborne or satellite LiDAR sensors.

  8. Comparing data of terrestrial LiDAR and UAV (photogrammetric) in the context of the project "SedAlp"

    Science.gov (United States)

    Abel, Judith; Wegner, Kerstin; Haas, Florian; Heckmann, Tobias; Becht, Michael

    2014-05-01

    The project "SedAlp" (Sediment management in Alpine basins: integrating sediment continuum, risk mitigation and hydropower) concentrates on problems and approaches related to sediment transfer in the alpine region and is embedded in the European transnational cooperation program "Alpine Space". The catholic University Eichstätt-Ingolstadt contributes the German part to this project on behalf of the Bavarian Environment Agency and in collaboration with the Authority of Water Resources Weilheim. The area of interest is the river Isar between the Sylvenstein reservoir and the city of Bad Tölz, Bavaria, Germany. The main aim of the activities is to quantify the transfer of sediments from the tributary catchments to the river Isar, specifically in light of the fact that the construction of the Sylvenstein reservoir in the mid 1950ies has created a barrier to longitudinal sediment transfer, thus heavily impacting the sediment budget and morphodynamics of the Isar reaches downstream. Moreover, the further development of artificially inserted gravel deposits and the effect of dismantling reinforcement structures at the river banks need investigation. Therefore, the dynamics of alluvial fans and gravel bars in the areas of confluence of tributary torrents are monitored using multitemporal surveys with terrestrial laserscanners and drone-based imagery. The latter is used both for the generation of high-resolution digital elevation models and for the mapping of changes in comparison to historical aerial photos. This study focuses on a comparison of TLS and UAV-based photogrammetric digital elevation models in order to highlight advantages and disadvantages of the two methods in relation to the SedAlp-specific research problems. It is shown that UAV-based elevation models are highly accurate alternatives to TLS-based models; due to their favourable acquisition geometry with respect to the topography in floodplain areas, and their large areal coverage, their use is seen as

  9. Improving LiDAR Biomass Model Uncertainty through Non-Destructive Allometry and Plot-level 3D Reconstruction with Terrestrial Laser Scanning

    Science.gov (United States)

    Stovall, A. E.; Shugart, H. H., Jr.

    2017-12-01

    Future NASA and ESA satellite missions plan to better quantify global carbon through detailed observations of forest structure, but ultimately rely on uncertain ground measurement approaches for calibration and validation. A significant amount of the uncertainty in estimating plot-level biomass can be attributed to inadequate and unrepresentative allometric relationships used to convert plot-level tree measurements to estimates of aboveground biomass. These allometric equations are known to have high errors and biases, particularly in carbon rich forests because they were calibrated with small and often biased samples of destructively harvested trees. To overcome this issue, a non-destructive methodology for estimating tree and plot-level biomass has been proposed through the use of Terrestrial Laser Scanning (TLS). We investigated the potential for using TLS as a ground validation approach in LiDAR-based biomass mapping though virtual plot-level tree volume reconstruction and biomass estimation. Plot-level biomass estimates were compared on the Virginia-based Smithsonian Conservation Biology Institute's SIGEO forest with full 3D reconstruction, TLS allometry, and Jenkins et al. (2003) allometry. On average, full 3D reconstruction ultimately provided the lowest uncertainty estimate of plot-level biomass (9.6%), followed by TLS allometry (16.9%) and the national equations (20.2%). TLS offered modest improvements to the airborne LiDAR empirical models, reducing RMSE from 16.2% to 14%. Our findings suggest TLS plot acquisitions and non-destructive allometry can play a vital role for reducing uncertainty in calibration and validation data for biomass mapping in the upcoming NASA and ESA missions.

  10. 2006 Fulton County Georgia Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of Fulton County. The Fulton County LiDAR Survey project area consists of approximately 690.5 square...

  11. Brief communication: 3-D reconstruction of a collapsed rock pillar from Web-retrieved images and terrestrial lidar data - the 2005 event of the west face of the Drus (Mont Blanc massif)

    Science.gov (United States)

    Guerin, Antoine; Abellán, Antonio; Matasci, Battista; Jaboyedoff, Michel; Derron, Marc-Henri; Ravanel, Ludovic

    2017-07-01

    In June 2005, a series of major rockfall events completely wiped out the Bonatti Pillar located in the legendary Drus west face (Mont Blanc massif, France). Terrestrial lidar scans of the west face were acquired after this event, but no pre-event point cloud is available. Thus, in order to reconstruct the volume and the shape of the collapsed blocks, a 3-D model has been built using photogrammetry (structure-from-motion (SfM) algorithms) based on 30 pictures collected on the Web. All these pictures were taken between September 2003 and May 2005. We then reconstructed the shape and volume of the fallen compartment by comparing the SfM model with terrestrial lidar data acquired in October 2005 and November 2011. The volume is calculated to 292 680 m3 (±5.6 %). This result is close to the value previously assessed by Ravanel and Deline (2008) for this same rock avalanche (265 000 ± 10 000 m3). The difference between these two estimations can be explained by the rounded shape of the volume determined by photogrammetry, which may lead to a volume overestimation. However it is not excluded that the volume calculated by Ravanel and Deline (2008) is slightly underestimated, the thickness of the blocks having been assessed manually from historical photographs.

  12. GRIP DOPPLER AEROSOL WIND LIDAR (DAWN) V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The GRIP Doppler Aerosol WiNd Lidar (DAWN) Dataset was collected by the Doppler Aerosol WiNd (DAWN), a pulsed lidar, which operated aboard a NASA DC-8 aircraft...

  13. NAMMA LIDAR ATMOSPHERIC SENSING EXPERIMENT (LASE) V1

    Data.gov (United States)

    National Aeronautics and Space Administration — The NAMMA Lidar Atmospheric Sensing Experiment (LASE) dataset used the LASE system using the Differential Absorption Lidar (DIAL) system was operated during the NASA...

  14. 2009 - 2011 CA Coastal Conservancy Coastal Lidar Project

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

  15. Leveraging Open Standards and Technologies to Enhance Community Access to Earth Science Lidar Data

    Science.gov (United States)

    Crosby, C. J.; Nandigam, V.; Krishnan, S.; Cowart, C.; Baru, C.; Arrowsmith, R.

    2011-12-01

    Lidar (Light Detection and Ranging) data, collected from space, airborne and terrestrial platforms, have emerged as an invaluable tool for a variety of Earth science applications ranging from ice sheet monitoring to modeling of earth surface processes. However, lidar present a unique suite of challenges from the perspective of building cyberinfrastructure systems that enable the scientific community to access these valuable research datasets. Lidar data are typically characterized by millions to billions of individual measurements of x,y,z position plus attributes; these "raw" data are also often accompanied by derived raster products and are frequently terabytes in size. As a relatively new and rapidly evolving data collection technology, relevant open data standards and software projects are immature compared to those for other remote sensing platforms. The NSF-funded OpenTopography Facility project has developed an online lidar data access and processing system that co-locates data with on-demand processing tools to enable users to access both raw point cloud data as well as custom derived products and visualizations. OpenTopography is built on a Service Oriented Architecture (SOA) in which applications and data resources are deployed as standards compliant (XML and SOAP) Web services with the open source Opal Toolkit. To develop the underlying applications for data access, filtering and conversion, and various processing tasks, OpenTopography has heavily leveraged existing open source software efforts for both lidar and raster data. Operating on the de facto LAS binary point cloud format (maintained by ASPRS), open source libLAS and LASlib libraries provide OpenTopography data ingestion, query and translation capabilities. Similarly, raster data manipulation is performed through a suite of services built on the Geospatial Data Abstraction Library (GDAL). OpenTopography has also developed our own algorithm for high-performance gridding of lidar point cloud data

  16. USGS Atchafalaya 2 LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Atchafalaya Basin project area. The entire survey area for Atchafalaya encompasses approximately...

  17. Making lidar more photogenic: creating band combinations from lidar information

    Science.gov (United States)

    Stoker, Jason M.

    2010-01-01

    Over the past five to ten years the use and applicability of light detection and ranging (lidar) technology has increased dramatically. As a result, an almost exponential amount of lidar data is being collected across the country for a wide range of applications, and it is currently the technology of choice for high resolution terrain model creation, 3-dimensional city and infrastructure modeling, forestry and a wide range of scientific applications (Lin and Mills, 2010). The amount of data that is being delivered across the country is impressive. For example, the U.S. Geological Survey’s (USGS) Center for Lidar Information Coordination and Knowledge (CLICK), which is a National repository of USGS and partner lidar point cloud datasets (Stoker et al., 2006), currently has 3.5 percent of the United States covered by lidar, and has approximately another 5 percent in the processing queue. The majority of data being collected by the commercial sector are from discrete-return systems, which collect billions of lidar points in an average project. There are also a lot of discussions involving a potential National-scale Lidar effort (Stoker et al., 2008).

  18. 2007 US Army Corps of Engineers (USACE), Jacksonville District US Virgin Islands LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) bare-earth classified LAS dataset is a topographic survey conducted for the USACE USVI LiDAR Project. These data were...

  19. 2009 - 2011 CA Coastal Conservancy Coastal Lidar Project: Hydro-flattened Bare Earth DEM

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

  20. Lidar to lidar calibration of Ground-based Lidar

    DEFF Research Database (Denmark)

    Fernandez Garcia, Sergio; Courtney, Michael

    This report presents the result of the lidar to lidar calibration performed for ground-based lidar. Calibration is here understood as the establishment of a relation between the reference lidar wind speed measurements with measurement uncertainties provided by measurement standard and corresponding...... lidar wind speed indications with associated measurement uncertainties. The lidar calibration concerns the 10 minute mean wind speed measurements. The comparison of the lidar measurements of the wind direction with that from the reference lidar measurements are given for information only....

  1. Post-wildfire landscape change and erosional processes from repeat terrestrial lidar in a steep headwater catchment, Chiricahua Mountains, Arizona, USA

    Science.gov (United States)

    DeLong, Stephen B.; Youberg, Ann M.; DeLong, Whitney M.; Murphy, Brendan P.

    2018-01-01

    Flooding and erosion after wildfires present increasing hazard as climate warms, semi-arid lands become drier, population increases, and the urban interface encroaches farther into wildlands. We quantify post-wildfire erosion in a steep, initially unchannelized, 7.5 ha headwater catchment following the 2011 Horseshoe 2 Fire in the Chiricahua Mountains of southeastern Arizona. Using time-lapse cameras, rain gauges, and repeat surveys by terrestrial laser scanner, we quantify the response of a burned landscape to subsequent precipitation events. Repeat surveys provide detailed pre-and post-rainfall measurements of landscape form associated with a range of weather events. The first post-fire precipitation led to sediment delivery equivalent to 0.017 m of erosion from hillslopes and 0.12 m of erosion from colluvial hollows. Volumetrically, 69% of sediment yield was generated from hillslope erosion and 31% was generated from gully channel establishment in colluvial hollows. Processes on hillslopes included erosion by extensive shallow overland flow, formation of rills and gullies, and generation of sediment-laden flows and possibly debris flows. Subsequent smaller rain events caused ongoing hillslope erosion and local deposition and erosion in gullies. Winter freeze-thaw led to soil expansion, likely related to frost-heaving, causing a net centimeter-scale elevation increase across soil-mantled slopes. By characterizing landscape form, the properties of near-surface materials, and measuring both precipitation and landscape change, we can improve our empirical understanding of landscape response to environmental forcing. This detailed approach to studying landscape response to wildfires may be useful in the improvement of predictive models of flood, debris flow and sedimentation hazards used in post-wildfire response assessments and land management, and may help improve process-based models of landscape evolution.

  2. Post-wildfire landscape change and erosional processes from repeat terrestrial lidar in a steep headwater catchment, Chiricahua Mountains, Arizona, USA

    Science.gov (United States)

    DeLong, Stephen B.; Youberg, Ann M.; DeLong, Whitney M.; Murphy, Brendan P.

    2018-01-01

    Flooding and erosion after wildfires present increasing hazard as climate warms, semi-arid lands become drier, population increases, and the urban interface encroaches farther into wildlands. We quantify post-wildfire erosion in a steep, initially unchannelized, 7.5 ha headwater catchment following the 2011 Horseshoe 2 Fire in the Chiricahua Mountains of southeastern Arizona. Using time-lapse cameras, rain gauges, and repeat surveys by terrestrial laser scanner, we quantify the response of a burned landscape to subsequent precipitation events. Repeat surveys provide detailed pre-and post-rainfall measurements of landscape form associated with a range of weather events. The first post-fire precipitation led to sediment delivery equivalent to 0.017 m of erosion from hillslopes and 0.12 m of erosion from colluvial hollows. Volumetrically, 69% of sediment yield was generated from hillslope erosion and 31% was generated from gully channel establishment in colluvial hollows. Processes on hillslopes included erosion by extensive shallow overland flow, formation of rills and gullies, and generation of sediment-laden flows and possibly debris flows. Subsequent smaller rain events caused ongoing hillslope erosion and local deposition and erosion in gullies. Winter freeze-thaw led to soil expansion, likely related to frost-heaving, causing a net centimeter-scale elevation increase across soil-mantled slopes. By characterizing landscape form, the properties of near-surface materials, and measuring both precipitation and landscape change, we can improve our empirical understanding of landscape response to environmental forcing. This detailed approach to studying landscape response to wildfires may be useful in the improvement of predictive models of flood, debris flow and sedimentation hazards used in post-wildfire response assessments and land management, and may help improve process-based models of landscape evolution.

  3. Analyzing post-fire topography at the hillslope-channel interface with terrestrial LiDAR: contrasting geomorphic responses from the 2012 Waldo Canyon Fire of Colorado and the 2013 Springs Fire of California

    Science.gov (United States)

    Storesund, R.; Chin, A.; Florsheim, J. L.; O'Hirok, L.; Williams, K.; Austin, K. E.

    2014-12-01

    Mountains areas are increasingly susceptible to wildfires because of warming climates. Although knowledge of the hydro-geomorphological impacts of wildfire has advanced in recent years, much is still unknown regarding how environmental fluxes move through burned watersheds. Because of the loss of vegetation and hydrophobic soils, flash floods often accompany elevated runoff events from burned watersheds, making direct process measurements challenging. Direct measurements are also only partly successful at capturing the spatial variations of post-fire effects. Coupled with short temporal windows for observing such responses, opportunities are often missed for collecting data needed for developing predictive models. Terrestrial LiDAR scanning (TLS) of burned areas allows detailed documentation of the post-fire topography to cm-level accuracy, providing pictures of geomorphic responses not previously possible. This paper reports a comparative study of hillslope-channel interactions, using repeat TLS, in two contrasting environments. Burned by the 2012 Waldo Canyon Fire and 2013 Springs Fire, in Colorado and California respectively, the study sites share many similarities including steep erosive slopes, small drainage areas, and step-pool channel morphologies. TLS provided a tool to test the central hypothesis that, dry ravel, distinct in the California Mediterranean environment, would prompt a greater sedimentological response from the Springs Fire compared to the Waldo Canyon Fire. At selected sites in each area, TLS documented baseline conditions immediately following the fire. Repeat scanning after major storms allowed detection of changes in the landscape. Results show a tendency for sedimentation in river channels in the study sites interacting with dry ravel on hillslopes, whereas erosion dominated the response from the Waldo Canyon Fire with an absence of dry ravel. These data provide clues to developing generalizations for post-fire effects at regional scales

  4. LIDAR Products, State of Rhode Island: LIDAR for the North East – ARRA and LiDAR for the North East Part II; LiDAR was collected in the Winter and Spring 2011 at a 1 meter or better nominal post spacing (1m GSD) for approximately 1,074 square miles of Rhode Island, whi, Published in 2012, 1:9600 (1in=800ft) scale, Rhode Island and Providence Plantations.

    Data.gov (United States)

    NSGIC State | GIS Inventory — LIDAR Products dataset current as of 2012. State of Rhode Island: LIDAR for the North East – ARRA and LiDAR for the North East Part II; LiDAR was collected in the...

  5. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    The datasets presented in this article are related to the research articles entitled “Neutrophil Extracellular Traps in Ulcerative Colitis: A Proteome Analysis of Intestinal Biopsies” (Bennike et al., 2015 [1]), and “Proteome Analysis of Rheumatoid Arthritis Gut Mucosa” (Bennike et al., 2017 [2])...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  6. Modelling the subsurface geomorphology of an active landslide using LIDAR.

    Science.gov (United States)

    2014-07-01

    The focus of this research was twofold: : 1. To determine millimeter/sub-millimeter movement within a slide body using high precision terrestrial LIDAR and : artificial targets. This allows movement not apparent to the naked eye to be verified. : 2. ...

  7. Lidar-based mapping of flood control levees in south Louisiana

    Science.gov (United States)

    Thatcher, Cindy A.; Lim, Samsung; Palaseanu-Lovejoy, Monica; Danielson, Jeffrey J.; Kimbrow, Dustin R.

    2016-01-01

    Flood protection in south Louisiana is largely dependent on earthen levees, and in the aftermath of Hurricane Katrina the state’s levee system has received intense scrutiny. Accurate elevation data along the levees are critical to local levee district managers responsible for monitoring and maintaining the extensive system of non-federal levees in coastal Louisiana. In 2012, high resolution airborne lidar data were acquired over levees in Lafourche Parish, Louisiana, and a mobile terrestrial lidar survey was conducted for selected levee segments using a terrestrial lidar scanner mounted on a truck. The mobile terrestrial lidar data were collected to test the feasibility of using this relatively new technology to map flood control levees and to compare the accuracy of the terrestrial and airborne lidar. Metrics assessing levee geometry derived from the two lidar surveys are also presented as an efficient, comprehensive method to quantify levee height and stability. The vertical root mean square error values of the terrestrial lidar and airborne lidar digital-derived digital terrain models were 0.038 m and 0.055 m, respectively. The comparison of levee metrics derived from the airborne and terrestrial lidar-based digital terrain models showed that both types of lidar yielded similar results, indicating that either or both surveying techniques could be used to monitor geomorphic change over time. Because airborne lidar is costly, many parts of the USA and other countries have never been mapped with airborne lidar, and repeat surveys are often not available for change detection studies. Terrestrial lidar provides a practical option for conducting repeat surveys of levees and other terrain features that cover a relatively small area, such as eroding cliffs or stream banks, and dunes.

  8. Lidar to lidar calibration phase 2

    DEFF Research Database (Denmark)

    Yordanova, Ginka; Courtney, Michael

    This report presents the results from phase 2 of a lidar to lidar (L2L) calibration procedure. Phase two of the project included two measurement campaigns conducted at given sites. The purpose was to find out if the lidar-to-lidar calibration procedure can be conducted with similar results...

  9. Lidar to lidar calibration phase 1

    DEFF Research Database (Denmark)

    Yordanova, Ginka; Courtney, Michael

    This report presents a feasibility study of a lidar to lidar (L2L) calibration procedure. Phase one of the project was conducted at Høvsøre, Denmark. Two windcubes were placed next to the 116m met mast and different methods were applied to obtain the sensing height error of the lidars. The purpose...... is to find the most consistent method and use it in a potential lidar to lidar calibration procedure....

  10. OpenTopography: Enabling Online Access to High-Resolution Lidar Topography Data and Processing Tools

    Science.gov (United States)

    Crosby, Christopher; Nandigam, Viswanath; Baru, Chaitan; Arrowsmith, J. Ramon

    2013-04-01

    resources. Datasets hosted by other organizations, as well as lidar-specific software, can be registered into the OpenTopography catalog, providing users a "one-stop shop" for such information. With several thousand active users, OpenTopography is an excellent example of a mature Spatial Data Infrastructure system that is enabling access to challenging data for research, education and outreach. Ongoing OpenTopography design and development work includes the archive and publication of datasets using digital object identifiers (DOIs); creation of a more flexible and scalable high-performance environment for processing of large datasets; expanded support for satellite and terrestrial lidar; and creation of a "pluggable" infrastructure for third-party programs and algorithms. OpenTopography has successfully created a facility for sharing lidar data. In the project's next phase, we are working to enable equally easy and successful sharing of services for processing and analysis of these data.

  11. 2012 NOAA American Samoa Lidar: Islands of Tutuila, Aunu'u, Ofu, Olosega, Ta'u and Rose Atoll

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

  12. Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase two, volume 3 : advanced consideration in LiDAR technology for bridge evaluation.

    Science.gov (United States)

    2012-03-01

    This report describes Phase Two enhancement of terrestrial LiDAR scanning for bridge damage : evaluation that was initially developed in Phase One. Considering the spatial and reflectivity : information contained in LiDAR scans, two detection algorit...

  13. Integrated remote sensing and visualization (IRSV) system for transportation infrastructure operations and management, phase one, volume 3 : use of scanning LiDAR in structural evaluation of bridges.

    Science.gov (United States)

    2009-12-01

    This volume introduces several applications of remote bridge inspection technologies studied in : this Integrated Remote Sensing and Visualization (IRSV) study using ground-based LiDAR : systems. In particular, the application of terrestrial LiDAR fo...

  14. Proteomics dataset

    DEFF Research Database (Denmark)

    Bennike, Tue Bjerg; Carlsen, Thomas Gelsing; Ellingsen, Torkell

    2017-01-01

    patients (Morgan et al., 2012; Abraham and Medzhitov, 2011; Bennike, 2014) [8–10. Therefore, we characterized the proteome of colon mucosa biopsies from 10 inflammatory bowel disease ulcerative colitis (UC) patients, 11 gastrointestinal healthy rheumatoid arthritis (RA) patients, and 10 controls. We...... been deposited to the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifiers PXD001608 for ulcerative colitis and control samples, and PXD003082 for rheumatoid arthritis samples....

  15. Landforms in Lidar: Building a Catalog of Digital Landforms for Education and Outreach

    Science.gov (United States)

    Kleber, E.; Crosby, C.; Olds, S. E.; Arrowsmith, R.

    2012-12-01

    Lidar (Light Detection and Ranging) has emerged as a fundamental tool in the earth sciences. The collection of high-resolution lidar topography from an airborne or terrestrial platform allows landscapes and landforms to be spatially represented in at sub-meter resolution and in three dimensions. While the growing availability of lidar has led to numerous new scientific findings, these data also have tremendous value for earth science education. The study of landforms is an essential and basic element of earth science education that helps students to grasp fundamental earth system processes and how they manifest themselves in the world around us. Historically students are introduced to landforms and related processes through diagrams and images seen in earth science textbooks. Lidar data, coupled with free tools such as Google Earth, provide a means to allow students and the interested public to visualize, explore, and interrogate these same landforms in an interactive manner not possible in two-dimensional remotely sensed imagery. The NSF-funded OpenTopography facility hosts data collected for geologic, hydrologic, and biological research, covering a diverse range of landscapes, and thus provides a wealth of data that could be incorporated into educational materials. OpenTopography, in collaboration with UNAVCO, are developing a catalog of classic geologic landforms depicted in lidar. Beginning with textbook-examples of features such as faults and tectonic landforms, dunes, fluvial and glacial geomorphology, and natural hazards such as landslides and volcanoes, the catalog will be an online resource for educators and the interested public. Initially, the landforms will be sourced from pre-existing datasets hosted by OpenTopography. Users will see an image representative of the landform then have the option to download the data in Google Earth KMZ format, as a digital elevation model, or the original lidar point cloud file. By providing the landform in a range of

  16. 2013 Suwannee River Water Management District Lidar: Greenville (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G12PD00242 1.0 Meter LiDAR Survey Area 3, Classified Point Cloud, in north-central...

  17. 2014 Suwannee River Water Management District Lidar: Cooks Hammock (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River G14PD00206 0.7 Meter LiDAR Survey in central Florida and encompasses 571 square...

  18. 2013 Suwannee River Water Management District Lidar: Bell (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G13PD00141 1.0 Meter LiDAR Survey Area 4, Classified Point Cloud, in north-central...

  19. 2013 Suwannee River Water Management District Lidar: Mayo (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G12PD00242 1.0 Meter LiDAR Survey Area 4, Classified Point Cloud, in north-central...

  20. 2013 Suwannee River Water Management District Lidar: Obrien (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G13PD00141 1.0 Meter LiDAR Survey Area 1, Classified Point Cloud, in north-central...

  1. 2013 Suwannee River Water Management District (SRWMD) Lidar: Ichetucknee (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River G12PD00242 1.0 Meter LiDAR Survey area 2 in north-central Florida and encompasses...

  2. Suwannee River Water Management District Lidar: Falmouth (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River G12PD00242 1.0 Meter LiDAR Survey area 5 in north-central Florida and encompasses...

  3. 2013 Suwannee River Water Management District Lidar: Ocean Pond (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of Suwannee River G13PD00141 1.0 Meter LiDAR Survey Area 3, Classified Point Cloud, in north-central...

  4. North Carolina Statewide Lidar DEM 2014 Phase 1

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Geographic Extent: North Carolina Area of Interest for Sandy, covering approximately 9,396 square miles. Dataset Description: The North Carolina - Sandy LiDAR...

  5. 2010 ARRA Lidar: California Coastal Project (Zone 4)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (LiDAR)...

  6. 2005 Southwest Florida Water Management District (SWFWMD) Lidar: Manatee District

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Southwest Florida. These data were produced for the Southwest Florida Water...

  7. 2014 NCFMP Lidar: Statewide North Carolina (Phase 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Geographic Extent: North Carolina Area of Interest for Sandy, covering approximately 9,396 square miles. Dataset Description: The North Carolina - Sandy LiDAR...

  8. 2010 ARRA Lidar: California Coastal Project (Zone 3)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (LiDAR)...

  9. North Carolina Statewide Lidar DEM 2015 Phase 3

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Geographic Extent: North Carolina Area of Interest, covering approximately 7,197 square miles. Dataset Description: The North Carolina LiDAR project called for the...

  10. 2015 NCFMP Lidar: Statewide North Carolina (Phase 3)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Geographic Extent: North Carolina Area of Interest, covering approximately 7,197 square miles. Dataset Description: The North Carolina LiDAR project called for the...

  11. 2008 FEMA Lidar: South Oneida County (NY)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — For Oneida County, NY, there were two types of elevation datasets. The first type is LiDAR and the second one is Auto-correlation DEM. Auto-correlation DEM data was...

  12. 2011 - 2012 New York State Department of Environmental Conservation (NYSDEC) Lidar: Coastal New York (Long Island and along the Hudson River)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. This LiDAR dataset is a...

  13. 2015 OLC Lidar: Chelan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Chelan FEMA study area. This study area is located in...

  14. LIDAR Research & Development Lab

    Data.gov (United States)

    Federal Laboratory Consortium — The LIDAR Research and Development labs are used to investigate and improve LIDAR components such as laser sources, optical signal detectors and optical filters. The...

  15. 2005 Mississippi Merged LiDAR Data (2005 LiDAR data merged with 2005 Post-Katrina LiDAR data to create a bare-earth product for flood plain mapping in coastal Mississippi).

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Pre- and post-hurricane Katrina LiDAR datasets of Hancock, Harrison, and Jackson Counties, MS, were merged into a seamless coverage by URS. The pre-Katrina LiDAR...

  16. Lidar calibration experiments

    DEFF Research Database (Denmark)

    Ejsing Jørgensen, Hans; Mikkelsen, T.; Streicher, J.

    1997-01-01

    detection to test the reproducibility and uncertainty of lidars. Lidar data were obtained from both single-ended and double-ended Lidar configurations. A backstop was introduced in one of the experiments and a new method was developed where information obtained from the backstop can be used in the inversion...... algorithm. Independent in-situ aerosol plume concentrations were obtained from a simultaneous tracer gas experiment with SF6, and comparisons with the two lidars were made. The study shows that the reproducibility of the lidars is within 15%, including measurements from both sides of a plume...

  17. Large Scale Textured Mesh Reconstruction from Mobile Mapping Images and LIDAR Scans

    Science.gov (United States)

    Boussaha, M.; Vallet, B.; Rives, P.

    2018-05-01

    The representation of 3D geometric and photometric information of the real world is one of the most challenging and extensively studied research topics in the photogrammetry and robotics communities. In this paper, we present a fully automatic framework for 3D high quality large scale urban texture mapping using oriented images and LiDAR scans acquired by a terrestrial Mobile Mapping System (MMS). First, the acquired points and images are sliced into temporal chunks ensuring a reasonable size and time consistency between geometry (points) and photometry (images). Then, a simple, fast and scalable 3D surface reconstruction relying on the sensor space topology is performed on each chunk after an isotropic sampling of the point cloud obtained from the raw LiDAR scans. Finally, the algorithm proposed in (Waechter et al., 2014) is adapted to texture the reconstructed surface with the images acquired simultaneously, ensuring a high quality texture with no seams and global color adjustment. We evaluate our full pipeline on a dataset of 17 km of acquisition in Rouen, France resulting in nearly 2 billion points and 40000 full HD images. We are able to reconstruct and texture the whole acquisition in less than 30 computing hours, the entire process being highly parallel as each chunk can be processed independently in a separate thread or computer.

  18. LARGE SCALE TEXTURED MESH RECONSTRUCTION FROM MOBILE MAPPING IMAGES AND LIDAR SCANS

    Directory of Open Access Journals (Sweden)

    M. Boussaha

    2018-05-01

    Full Text Available The representation of 3D geometric and photometric information of the real world is one of the most challenging and extensively studied research topics in the photogrammetry and robotics communities. In this paper, we present a fully automatic framework for 3D high quality large scale urban texture mapping using oriented images and LiDAR scans acquired by a terrestrial Mobile Mapping System (MMS. First, the acquired points and images are sliced into temporal chunks ensuring a reasonable size and time consistency between geometry (points and photometry (images. Then, a simple, fast and scalable 3D surface reconstruction relying on the sensor space topology is performed on each chunk after an isotropic sampling of the point cloud obtained from the raw LiDAR scans. Finally, the algorithm proposed in (Waechter et al., 2014 is adapted to texture the reconstructed surface with the images acquired simultaneously, ensuring a high quality texture with no seams and global color adjustment. We evaluate our full pipeline on a dataset of 17 km of acquisition in Rouen, France resulting in nearly 2 billion points and 40000 full HD images. We are able to reconstruct and texture the whole acquisition in less than 30 computing hours, the entire process being highly parallel as each chunk can be processed independently in a separate thread or computer.

  19. 2015 Lowndes County (GA) Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: NOAA OCM Lidar for Lowndes County, GA with the option to Collect Lidar in Cook and Tift Counties, GA Lidar Data Acquisition and Processing Production Task...

  20. 2015 OLC Lidar: Wasco, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Wasco County, WA, study area. The Oregon LiDAR Consortium's Wasco County...

  1. ASSESSMENT OF BOTTOM-OF-ATMOSPHERE REFLECTANCE IN LIDAR DATA AS REFERENCE FOR HYPERSPECTRAL IMAGERY

    Directory of Open Access Journals (Sweden)

    A. Roncat

    2017-09-01

    Full Text Available 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. 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. 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.

  2. Jean Lafitte 2013, 1.0 Meter LiDAR, Classified point cloud

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Jean Lafitte,G13PD00214, 1.0 Meter LiDAR Survey Area in south of New Orleans and encompasses 77...

  3. FY12 St Johns River Water Management LiDAR Survey: Putnam (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the FY12 St Johns River Water Management LiDAR Survey, project area in north-central Florida and...

  4. Improving stream studies with a small-footprint green lidar

    Science.gov (United States)

    Jim McKean; Dan Isaak; Wayne Wright

    2009-01-01

    Technology is changing how scientists and natural resource managers describe and study streams and rivers. A new generation of airborne aquatic-terrestrial lidars is being developed that can penetrate water and map the submerged topography inside a stream as well as the adjacent subaerial terrain and vegetation in one integrated mission. A leading example of these new...

  5. 2006-2008 PAMAP LiDAR Data of Pennsylvania (Northern Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of classified LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. PAMAP data are organized into blocks, which...

  6. 2007 Bureau of Land Management (BLM) Lidar: Panther Creek Watershed, Yamhill County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The dataset represents LiDAR elevations acquired during a leaf-off and a leaf-on vegetative condition for the Upper Panther Creek Watershed in the Yamhill County...

  7. 2006 Florida LiDAR: Escambia, Santa Rosa, and Walton Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — ESCAMBIA: The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Escambia County, Florida. These data were produced for Dewberry and...

  8. 2010 U.S. Geological Survey (USGS) Topographic LiDAR: San Francisco Bay, California

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The primary purpose of this project was to develop a consistent and accurate surface elevation dataset derived from high-accuracy Light Detection and Ranging (LiDAR)...

  9. 2005/2006 Southwest Florida Water Management District (SWFWMD) Lidar: Peace River South (including Carter Creek)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Southwest Florida. These data were produced for the Southwest Florida Water...

  10. 2007 Florida Division of Emergency Management (FDEM) Lidar Project: Southwest Florida

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) LAS dataset is a topographic survey conducted for a coalition of GIS practitioners, including the Florida Division of...

  11. VT Lidar-based Aspect, Symbolized, Not Cached, VT State Plane Meters

    Data.gov (United States)

    Vermont Center for Geographic Information — ASPECT service (compass direction that a slope faces) derived from various VT Lidar datasets. A pre-defined SYMbology has been applied to the service. VT State Plane...

  12. 2007 Florida Division of Emergency Management (FDEM) Lidar Project: Bay County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) LAS dataset is a topographic survey conducted for a coalition of GIS practitioners, including the Florida Division of...

  13. 2007 Southwest Florida Water Management District (SWFWMD) LiDAR: Hernando County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset is one component of a digital terrain model (DTM) for the Southwest Florida Water Management Districts FY2006 Digital Orthophoto (B089) and LiDAR...

  14. 2006 Southwest Florida Water Management District (SWFWMD) Lidar: Rutland Ranch District

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Rutland Ranch. This data falls in Manatee County. These data were produced for...

  15. 2005 Southwest Florida Water Management District (SWFWMD) Lidar: Little Manatee District

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) LAS dataset is a survey of select areas within Southwest Florida. These data were produced for the Southwest Florida Water...

  16. 2006-2008 PAMAP LiDAR Data of Pennsylvania (Southern Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset consists of classified LiDAR (Light Detection and Ranging) elevation points produced by the PAMAP Program. Additional information is available at the...

  17. 2010 U.S. Geological Survey Topographic LiDAR: Atchafalaya Basin, Louisiana

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Atchafalaya Basin in south-central Louisiana. The entire survey area encompasses 981 square miles....

  18. 2008 Northwest Florida Water Management District (NWFWMD) LiDAR: Inland Okaloosa County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) LAS dataset is a survey of inland Okaloosa County, Florida not covered in the 2008 Florida Department of Emergency...

  19. 2012 FEMA Topographic Lidar: Hudson-Hoosic and Deerfield Watersheds, Massachusetts

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Light Detection and Ranging (LiDAR) dataset is a survey of the Hudson-Hoosic and Deerfield project area. The entire survey area for Massachusetts is...

  20. Evaluating lidar point densities for effective estimation of aboveground biomass

    Science.gov (United States)

    Wu, Zhuoting; Dye, Dennis G.; Stoker, Jason M.; Vogel, John M.; Velasco, Miguel G.; Middleton, Barry R.

    2016-01-01

    The U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) was recently established to provide airborne lidar data coverage on a national scale. As part of a broader research effort of the USGS to develop an effective remote sensing-based methodology for the creation of an operational biomass Essential Climate Variable (Biomass ECV) data product, we evaluated the performance of airborne lidar data at various pulse densities against Landsat 8 satellite imagery in estimating above ground biomass for forests and woodlands in a study area in east-central Arizona, U.S. High point density airborne lidar data, were randomly sampled to produce five lidar datasets with reduced densities ranging from 0.5 to 8 point(s)/m2, corresponding to the point density range of 3DEP to provide national lidar coverage over time. Lidar-derived aboveground biomass estimate errors showed an overall decreasing trend as lidar point density increased from 0.5 to 8 points/m2. Landsat 8-based aboveground biomass estimates produced errors larger than the lowest lidar point density of 0.5 point/m2, and therefore Landsat 8 observations alone were ineffective relative to airborne lidar for generating a Biomass ECV product, at least for the forest and woodland vegetation types of the Southwestern U.S. While a national Biomass ECV product with optimal accuracy could potentially be achieved with 3DEP data at 8 points/m2, our results indicate that even lower density lidar data could be sufficient to provide a national Biomass ECV product with accuracies significantly higher than that from Landsat observations alone.

  1. Measuring Oscillating Walking Paths with a LIDAR

    Directory of Open Access Journals (Sweden)

    Jordi Palacín

    2011-05-01

    Full Text Available This work describes the analysis of different walking paths registered using a Light Detection And Ranging (LIDAR laser range sensor in order to measure oscillating trajectories during unsupervised walking. The estimate of the gait and trajectory parameters were obtained with a terrestrial LIDAR placed 100 mm above the ground with the scanning plane parallel to the floor to measure the trajectory of the legs without attaching any markers or modifying the floor. Three different large walking experiments were performed to test the proposed measurement system with straight and oscillating trajectories. The main advantages of the proposed system are the possibility to measure several steps and obtain average gait parameters and the minimum infrastructure required. This measurement system enables the development of new ambulatory applications based on the analysis of the gait and the trajectory during a walk.

  2. A Scalable Infrastructure for Lidar Topography Data Distribution, Processing, and Discovery

    Science.gov (United States)

    Crosby, C. J.; Nandigam, V.; Krishnan, S.; Phan, M.; Cowart, C. A.; Arrowsmith, R.; Baru, C.

    2010-12-01

    High-resolution topography data acquired with lidar (light detection and ranging) technology have emerged as a fundamental tool in the Earth sciences, and are also being widely utilized for ecological, planning, engineering, and environmental applications. Collected from airborne, terrestrial, and space-based platforms, these data are revolutionary because they permit analysis of geologic and biologic processes at resolutions essential for their appropriate representation. Public domain lidar data collection by federal, state, and local agencies are a valuable resource to the scientific community, however the data pose significant distribution challenges because of the volume and complexity of data that must be stored, managed, and processed. Lidar data acquisition may generate terabytes of data in the form of point clouds, digital elevation models (DEMs), and derivative products. This massive volume of data is often challenging to host for resource-limited agencies. Furthermore, these data can be technically challenging for users who lack appropriate software, computing resources, and expertise. The National Science Foundation-funded OpenTopography Facility (www.opentopography.org) has developed a cyberinfrastructure-based solution to enable online access to Earth science-oriented high-resolution lidar topography data, online processing tools, and derivative products. OpenTopography provides access to terabytes of point cloud data, standard DEMs, and Google Earth image data, all co-located with computational resources for on-demand data processing. The OpenTopography portal is built upon a cyberinfrastructure platform that utilizes a Services Oriented Architecture (SOA) to provide a modular system that is highly scalable and flexible enough to support the growing needs of the Earth science lidar community. OpenTopography strives to host and provide access to datasets as soon as they become available, and also to expose greater application level functionalities to

  3. EPA Nanorelease Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — EPA Nanorelease Dataset. This dataset is associated with the following publication: Wohlleben, W., C. Kingston, J. Carter, E. Sahle-Demessie, S. Vazquez-Campos, B....

  4. LiDAR Vegetation Investigation and Signature Analysis System (LVISA)

    Science.gov (United States)

    Höfle, Bernhard; Koenig, Kristina; Griesbaum, Luisa; Kiefer, Andreas; Hämmerle, Martin; Eitel, Jan; Koma, Zsófia

    2015-04-01

    Our physical environment undergoes constant changes in space and time with strongly varying triggers, frequencies, and magnitudes. Monitoring these environmental changes is crucial to improve our scientific understanding of complex human-environmental interactions and helps us to respond to environmental change by adaptation or mitigation. The three-dimensional (3D) description of the Earth surface features and the detailed monitoring of surface processes using 3D spatial data have gained increasing attention within the last decades, such as in climate change research (e.g., glacier retreat), carbon sequestration (e.g., forest biomass monitoring), precision agriculture and natural hazard management. In all those areas, 3D data have helped to improve our process understanding by allowing quantifying the structural properties of earth surface features and their changes over time. This advancement has been fostered by technological developments and increased availability of 3D sensing systems. In particular, LiDAR (light detection and ranging) technology, also referred to as laser scanning, has made significant progress and has evolved into an operational tool in environmental research and geosciences. The main result of LiDAR measurements is a highly spatially resolved 3D point cloud. Each point within the LiDAR point cloud has a XYZ coordinate associated with it and often additional information such as the strength of the returned backscatter. The point cloud provided by LiDAR contains rich geospatial, structural, and potentially biochemical information about the surveyed objects. To deal with the inherently unorganized datasets and the large data volume (frequently millions of XYZ coordinates) of LiDAR datasets, a multitude of algorithms for automatic 3D object detection (e.g., of single trees) and physical surface description (e.g., biomass) have been developed. However, so far the exchange of datasets and approaches (i.e., extraction algorithms) among LiDAR users

  5. Water Mapping Using Multispectral Airborne LIDAR Data

    Science.gov (United States)

    Yan, W. Y.; Shaker, A.; LaRocque, P. E.

    2018-04-01

    This study investigates the use of the world's first multispectral airborne LiDAR sensor, Optech Titan, manufactured by Teledyne Optech to serve the purpose of automatic land-water classification with a particular focus on near shore region and river environment. Although there exist recent studies utilizing airborne LiDAR data for shoreline detection and water surface mapping, the majority of them only perform experimental testing on clipped data subset or rely on data fusion with aerial/satellite image. In addition, most of the existing approaches require manual intervention or existing tidal/datum data for sample collection of training data. To tackle the drawbacks of previous approaches, we propose and develop an automatic data processing workflow for land-water classification using multispectral airborne LiDAR data. Depending on the nature of the study scene, two methods are proposed for automatic training data selection. The first method utilizes the elevation/intensity histogram fitted with Gaussian mixture model (GMM) to preliminarily split the land and water bodies. The second method mainly relies on the use of a newly developed scan line elevation intensity ratio (SLIER) to estimate the water surface data points. Regardless of the training methods being used, feature spaces can be constructed using the multispectral LiDAR intensity, elevation and other features derived from these parameters. The comprehensive workflow was tested with two datasets collected for different near shore region and river environment, where the overall accuracy yielded better than 96 %.

  6. RAPID INSPECTION OF PAVEMENT MARKINGS USING MOBILE LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    H. Zhang

    2016-06-01

    Full Text Available This study aims at building a robust semi-automated pavement marking extraction workflow based on the use of mobile LiDAR point clouds. The proposed workflow consists of three components: preprocessing, extraction, and classification. In preprocessing, the mobile LiDAR point clouds are converted into the radiometrically corrected intensity imagery of the road surface. Then the pavement markings are automatically extracted with the intensity using a set of algorithms, including Otsu’s thresholding, neighbor-counting filtering, and region growing. Finally, the extracted pavement markings are classified with the geometric parameters using a manually defined decision tree. Case studies are conducted using the mobile LiDAR dataset acquired in Xiamen (Fujian, China with different road environments by the RIEGL VMX-450 system. The results demonstrated that the proposed workflow and our software tool can achieve 93% in completeness, 95% in correctness, and 94% in F-score when using Xiamen dataset.

  7. Terrestrial magnetosphere

    International Nuclear Information System (INIS)

    Pande, D.C.; Agarwal, D.C.

    1982-01-01

    This paper presents a review about terrestrial magnetosphere. During the last few years considerable investigation have been carried out about the properties of Solar Wind and its interaction with planetary magnetic fields. It is therefore of high importance to accumulate all the investigations in a comprehensive form. The paper reviews the property of earth's magnetosphere, magnetosheath, magneto pause, polar cusps, bow shook and plasma sheath. (author)

  8. Data Integration Framework Data Management Plan Remote Sensing Dataset

    Science.gov (United States)

    2016-07-01

    Department of the Army position unless so designated by other authorized documents. DESTROY THIS REPORT WHEN NO LONGER NEEDED . DO NOT RETURN IT TO THE...2013 — Point clouds . ..................................................... 25 Table A2. Mobile terrestrial lidar data 2011–2013 — Digital elevation...HQUSACE) Navigation Business Line Manager overseeing the CODS Program. W. Jeff Lillycrop, CHL, was the ERDC Technical Director for Civil Works and

  9. 2011 USGS Topographic LiDAR: Suwannee River Expansion

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — USGS Task Order No. G10PD00236 USGS Contract No. G10PC00093 The Light Detection and Ranging (LiDAR) dataset is a survey of the Suwannee River Expansion in...

  10. The Ålesund slide, March 2008: Lidar analysis of an urban human-induced rockslide

    Science.gov (United States)

    Derron, M.-H.; Melchiorre, C.; Blikra, L.; Loye, A.; Pedrazzini, A.

    2009-04-01

    On March 26 2008, a 2400 m3 rock block slid from an excavated slope on a six floors house in the city of Aalesund (Western coast of Norway). The whole house was displaced horizontally on its basement on about 6 meters and the two lower floors of the building collapsed. Five persons died during the event. Almost 500 inhabitants living in the surroundings had to be evacuated for 6 to 8 days because of a gas leakage. The site has been scanned three times with a terrestrial lidar. In the first dataset, made a couple of days after the event, the block and the house are present. In the second dataset, acquired about 3 months later, the house had been removed but most of the sliding block is still in place. The last scan, made six months after the events, shows very well the sliding surface, as the block had been removed too. These three scans completed by field measurement and observations have been used: 1) to characterize the geometry and volume of the block, 2) to determine the displacement vector, 3) to perform a analysis of discontinuities and some kinematics tests, 4) to estimate the roughness and the waviness of the sliding surface.

  11. 2003 Oahu Coastline Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser rangefinding, GPS positioning...

  12. Alexandrite Lidar Receiver

    National Research Council Canada - National Science Library

    Wilkerson, Thomas

    2000-01-01

    ...". The chosen vendor, Orca Photonics, In. (Redmond, WA), in close collaboration with USU personnel, built a portable, computerized lidar system that not only is suitable as a receiver for a near IR alexandrite laser, but also contains an independent Nd...

  13. LIDAR Thomson scattering

    International Nuclear Information System (INIS)

    1991-07-01

    This collection contains 21 papers on the application and development of LIDAR (Light Detection and Ranging) Thomson scattering techniques for the determination of spatially resolved electron temperature and density in magnetic confinement experiments, particularly tokamaks. Refs, figs and tabs

  14. Lidar 2009 - All Returns

    Data.gov (United States)

    Kansas Data Access and Support Center — LIDAR-derived binary (.las) files containing classified points of all returns. We have 3 classifications Unclassified, Ground, Low points. The average Ground Sample...

  15. Holographic Raman lidar

    International Nuclear Information System (INIS)

    Andersen, G.

    2000-01-01

    Full text: We have constructed a Raman lidar system that incorporates a holographic optical element. By resolving just 3 nitrogen lines in the Resonance Raman spectroscopy (RRS) spectrum, temperature fits as good as 1% at altitudes of 20km can be made in 30 minutes. Due to the narrowband selectivity of the HOE, the lidar provides measurements over a continuous 24hr period. By adding a 4th channel to capture the Rayleigh backscattered light, temperature profiles can be extended to 80km

  16. Installation report - Lidar

    DEFF Research Database (Denmark)

    Georgieva Yankova, Ginka; Villanueva, Héctor

    The report describes the installation, configuration and data transfer for the ground-based lidar. The unit is provided by a customer but is installed and operated by DTU while in this project.......The report describes the installation, configuration and data transfer for the ground-based lidar. The unit is provided by a customer but is installed and operated by DTU while in this project....

  17. G-LiHT: Goddard's LiDAR, Hyperspectral and Thermal Airborne Imager

    Science.gov (United States)

    Cook, Bruce; Corp, Lawrence; Nelson, Ross; Morton, Douglas; Ranson, Kenneth J.; Masek, Jeffrey; Middleton, Elizabeth

    2012-01-01

    Scientists at NASA's Goddard Space Flight Center have developed an ultra-portable, low-cost, multi-sensor remote sensing system for studying the form and function of terrestrial ecosystems. G-LiHT integrates two LIDARs, a 905 nanometer single beam profiler and 1550 nm scanner, with a narrowband (1.5 nanometers) VNIR imaging spectrometer and a broadband (8-14 micrometers) thermal imager. The small footprint (approximately 12 centimeters) LIDAR data and approximately 1 meter ground resolution imagery are advantageous for high resolution applications such as the delineation of canopy crowns, characterization of canopy gaps, and the identification of sparse, low-stature vegetation, which is difficult to detect from space-based instruments and large-footprint LiDAR. The hyperspectral and thermal imagery can be used to characterize species composition, variations in biophysical variables (e.g., photosynthetic pigments), surface temperature, and responses to environmental stressors (e.g., heat, moisture loss). Additionally, the combination of LIDAR optical, and thermal data from G-LiHT is being used to assess forest health by sensing differences in foliage density, photosynthetic pigments, and transpiration. Low operating costs (approximately $1 ha) have allowed us to evaluate seasonal differences in LiDAR, passive optical and thermal data, which provides insight into year-round observations from space. Canopy characteristics and tree allometry (e.g., crown height:width, canopy:ground reflectance) derived from G-LiHT data are being used to generate realistic scenes for radiative transfer models, which in turn are being used to improve instrument design and ensure continuity between LiDAR instruments. G-LiHT has been installed and tested in aircraft with fuselage viewports and in a custom wing-mounted pod that allows G-LiHT to be flown on any Cessna 206, a common aircraft in use throughout the world. G-LiHT is currently being used for forest biomass and growth estimation

  18. 2010 Northern San Francisco Bay Area Lidar: Portions of Alameda, Contra Costa, Marin, Napa, San Francisco, Solano, and Sonoma Counties

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This Light Detection and Ranging (LiDAR) dataset is a survey of northern San Francisco Bay, California. The project area consists of approximately 437 square miles...

  19. Voxel-Based LIDAR Analysis and Applications

    Science.gov (United States)

    Hagstrom, Shea T.

    One of the greatest recent changes in the field of remote sensing is the addition of high-quality Light Detection and Ranging (LIDAR) instruments. In particular, the past few decades have been greatly beneficial to these systems because of increases in data collection speed and accuracy, as well as a reduction in the costs of components. These improvements allow modern airborne instruments to resolve sub-meter details, making them ideal for a wide variety of applications. Because LIDAR uses active illumination to capture 3D information, its output is fundamentally different from other modalities. Despite this difference, LIDAR datasets are often processed using methods appropriate for 2D images and that do not take advantage of its primary virtue of 3-dimensional data. It is this problem we explore by using volumetric voxel modeling. Voxel-based analysis has been used in many applications, especially medical imaging, but rarely in traditional remote sensing. In part this is because the memory requirements are substantial when handling large areas, but with modern computing and storage this is no longer a significant impediment. Our reason for using voxels to model scenes from LIDAR data is that there are several advantages over standard triangle-based models, including better handling of overlapping surfaces and complex shapes. We show how incorporating system position information from early in the LIDAR point cloud generation process allows radiometrically-correct transmission and other novel voxel properties to be recovered. This voxelization technique is validated on simulated data using the Digital Imaging and Remote Sensing Image Generation (DIRSIG) software, a first-principles based ray-tracer developed at the Rochester Institute of Technology. Voxel-based modeling of LIDAR can be useful on its own, but we believe its primary advantage is when applied to problems where simpler surface-based 3D models conflict with the requirement of realistic geometry. To

  20. NOSQL FOR STORAGE AND RETRIEVAL OF LARGE LIDAR DATA COLLECTIONS

    Directory of Open Access Journals (Sweden)

    J. Boehm

    2015-08-01

    Full Text Available Developments in LiDAR technology over the past decades have made LiDAR to become a mature and widely accepted source of geospatial information. This in turn has led to an enormous growth in data volume. The central idea for a file-centric storage of LiDAR point clouds is the observation that large collections of LiDAR data are typically delivered as large collections of files, rather than single files of terabyte size. This split of the dataset, commonly referred to as tiling, was usually done to accommodate a specific processing pipeline. It makes therefore sense to preserve this split. A document oriented NoSQL database can easily emulate this data partitioning, by representing each tile (file in a separate document. The document stores the metadata of the tile. The actual files are stored in a distributed file system emulated by the NoSQL database. We demonstrate the use of MongoDB a highly scalable document oriented NoSQL database for storing large LiDAR files. MongoDB like any NoSQL database allows for queries on the attributes of the document. As a specialty MongoDB also allows spatial queries. Hence we can perform spatial queries on the bounding boxes of the LiDAR tiles. Inserting and retrieving files on a cloud-based database is compared to native file system and cloud storage transfer speed.

  1. Nosql for Storage and Retrieval of Large LIDAR Data Collections

    Science.gov (United States)

    Boehm, J.; Liu, K.

    2015-08-01

    Developments in LiDAR technology over the past decades have made LiDAR to become a mature and widely accepted source of geospatial information. This in turn has led to an enormous growth in data volume. The central idea for a file-centric storage of LiDAR point clouds is the observation that large collections of LiDAR data are typically delivered as large collections of files, rather than single files of terabyte size. This split of the dataset, commonly referred to as tiling, was usually done to accommodate a specific processing pipeline. It makes therefore sense to preserve this split. A document oriented NoSQL database can easily emulate this data partitioning, by representing each tile (file) in a separate document. The document stores the metadata of the tile. The actual files are stored in a distributed file system emulated by the NoSQL database. We demonstrate the use of MongoDB a highly scalable document oriented NoSQL database for storing large LiDAR files. MongoDB like any NoSQL database allows for queries on the attributes of the document. As a specialty MongoDB also allows spatial queries. Hence we can perform spatial queries on the bounding boxes of the LiDAR tiles. Inserting and retrieving files on a cloud-based database is compared to native file system and cloud storage transfer speed.

  2. Lidar-Based Rock-Fall Hazard Characterization of Cliffs

    Science.gov (United States)

    Collins, Brian D.; Greg M.Stock,

    2017-01-01

    Rock falls from cliffs and other steep slopes present numerous challenges for detailed geological characterization. In steep terrain, rock-fall source areas are both dangerous and difficult to access, severely limiting the ability to make detailed structural and volumetric measurements necessary for hazard assessment. Airborne and terrestrial lidar survey methods can provide high-resolution data needed for volumetric, structural, and deformation analyses of rock falls, potentially making these analyses straightforward and routine. However, specific methods to collect, process, and analyze lidar data of steep cliffs are needed to maximize analytical accuracy and efficiency. This paper presents observations showing how lidar data sets should be collected, filtered, registered, and georeferenced to tailor their use in rock fall characterization. Additional observations concerning surface model construction, volumetric calculations, and deformation analysis are also provided.

  3. An error reduction algorithm to improve lidar turbulence estimates for wind energy

    Directory of Open Access Journals (Sweden)

    J. F. Newman

    2017-02-01

    -learning methods in L-TERRA was highly dependent on the input variables and training dataset used, suggesting that machine learning may not be the best technique for reducing lidar turbulence intensity (TI error. Future work will include the use of a lidar simulator to better understand how different factors affect lidar turbulence error and to determine how these errors can be reduced using information from a stand-alone lidar.

  4. 2014 OLC Lidar: Colville, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI, a Quantum Spatial company, has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Colville study area. This study area is...

  5. 2015 OLC Lidar DEM: Chelan

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Chelan FEMA study area. This study area is located in...

  6. 2015 OLC Lidar: Okanogan WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Okanogan FEMA study area. This study area is located in...

  7. 2012 USGS Lidar: Juneau (AK)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This task order is for planning, acquisition, processing, and derivative products of LiDAR data to be collected for Juneau, Alaska. LiDAR data, and derivative...

  8. Terrestrial ecology

    International Nuclear Information System (INIS)

    Anon.

    1977-01-01

    The main effort of the Terrestrial Ecology Division has been redirected to a comprehensive study of the Espiritu Santo Drainage Basin located in northeastern Puerto Rico. The general objective are to provide baseline ecological data for future environmental assessment studies at the local and regional levels, and to provide through an ecosystem approach data for the development of management alternatives for the wise utilization of energy, water, and land resources. The interrelationships among climate, vegetation, soils, and man, and their combined influence upon the hydrologic cycle will be described and evaluated. Environmental management involves planning and decision making, and both require an adequate data base. At present, little is known about the interworkings of a complete, integrated system such as a drainage basin. A literature survey of the main research areas confirmed that, although many individual ecologically oriented studies have been carried out in a tropical environment, few if any provide the data base required for environmental management. In view of rapidly changing socio-economic conditions and natural resources limitations, management urgently requires data from these systems: physical (climatological), biological, and cultural. This integrated drainage basin study has been designed to provide such data. The scope of this program covers the hydrologic cycle as it is affected by the interactions of the physical, biological, and cultural systems

  9. Aaron Journal article datasets

    Data.gov (United States)

    U.S. Environmental Protection Agency — All figures used in the journal article are in netCDF format. This dataset is associated with the following publication: Sims, A., K. Alapaty , and S. Raman....

  10. Integrated Surface Dataset (Global)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Integrated Surface (ISD) Dataset (ISD) is composed of worldwide surface weather observations from over 35,000 stations, though the best spatial coverage is...

  11. Control Measure Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — The EPA Control Measure Dataset is a collection of documents describing air pollution control available to regulated facilities for the control and abatement of air...

  12. National Hydrography Dataset (NHD)

    Data.gov (United States)

    Kansas Data Access and Support Center — The National Hydrography Dataset (NHD) is a feature-based database that interconnects and uniquely identifies the stream segments or reaches that comprise the...

  13. Market Squid Ecology Dataset

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This dataset contains ecological information collected on the major adult spawning and juvenile habitats of market squid off California and the US Pacific Northwest....

  14. Tables and figure datasets

    Data.gov (United States)

    U.S. Environmental Protection Agency — Soil and air concentrations of asbestos in Sumas study. This dataset is associated with the following publication: Wroble, J., T. Frederick, A. Frame, and D....

  15. Calibration of scanning Lidar

    DEFF Research Database (Denmark)

    Gómez Arranz, Paula; Courtney, Michael

    This report describes the tests carried out on a scanning lidar at the DTU Test Station for large wind turbines, Høvsøre. The tests were divided in two parts. In the first part, the purpose was to obtain wind speed calibrations at two heights against two cup anemometers mounted on a mast. Additio......This report describes the tests carried out on a scanning lidar at the DTU Test Station for large wind turbines, Høvsøre. The tests were divided in two parts. In the first part, the purpose was to obtain wind speed calibrations at two heights against two cup anemometers mounted on a mast...

  16. Novel Methods for Measuring LiDAR

    Science.gov (United States)

    Ayrey, E.; Hayes, D. J.; Fraver, S.; Weiskittel, A.; Cook, B.; Kershaw, J.

    2017-12-01

    The estimation of forest biometrics from airborne LiDAR data has become invaluable for quantifying forest carbon stocks, forest and wildlife ecology research, and sustainable forest management. The area-based approach is arguably the most common method for developing enhanced forest inventories from LiDAR. It involves taking a series of vertical height measurements of the point cloud, then using those measurements with field measured data to develop predictive models. Unfortunately, there is considerable variation in methodology for collecting point cloud data, which can vary in pulse density, seasonality, canopy penetrability, and instrument specifications. Today there exists a wealth of public LiDAR data, however the variation in acquisition parameters makes forest inventory prediction by traditional means unreliable across the different datasets. The goal of this project is to test a series of novel point cloud measurements developed along a conceptual spectrum of human interpretability, and then to use the best measurements to develop regional enhanced forest inventories on Northern New England's and Atlantic Canada's public LiDAR. Similarly to a field-based inventory, individual tree crowns are being segmented, and summary statistics are being used as covariates. Established competition and structural indices are being generated using each tree's relationship to one another, whilst existing allometric equations are being used to estimate diameter and biomass of each tree measured in the LiDAR. Novel metrics measuring light interception, clusteredness, and rugosity are also being measured as predictors. On the other end of the human interpretability spectrum, convolutional neural networks are being employed to directly measure both the canopy height model, and the point clouds by scanning each using two and three dimensional kernals trained to identify features useful for predicting biological attributes such as biomass. Predictive models will be trained and

  17. Registration of Aerial Optical Images with LiDAR Data Using the Closest Point Principle and Collinearity Equations.

    Science.gov (United States)

    Huang, Rongyong; Zheng, Shunyi; Hu, Kun

    2018-06-01

    Registration of large-scale optical images with airborne LiDAR data is the basis of the integration of photogrammetry and LiDAR. However, geometric misalignments still exist between some aerial optical images and airborne LiDAR point clouds. To eliminate such misalignments, we extended a method for registering close-range optical images with terrestrial LiDAR data to a variety of large-scale aerial optical images and airborne LiDAR data. The fundamental principle is to minimize the distances from the photogrammetric matching points to the terrestrial LiDAR data surface. Except for the satisfactory efficiency of about 79 s per 6732 × 8984 image, the experimental results also show that the unit weighted root mean square (RMS) of the image points is able to reach a sub-pixel level (0.45 to 0.62 pixel), and the actual horizontal and vertical accuracy can be greatly improved to a high level of 1/4⁻1/2 (0.17⁻0.27 m) and 1/8⁻1/4 (0.10⁻0.15 m) of the average LiDAR point distance respectively. Finally, the method is proved to be more accurate, feasible, efficient, and practical in variety of large-scale aerial optical image and LiDAR data.

  18. Probabilistic change mapping from airborne LiDAR for post-disaster damage assessment

    Science.gov (United States)

    Jalobeanu, A.; Runyon, S. C.; Kruse, F. A.

    2013-12-01

    When both pre- and post-event LiDAR point clouds are available, change detection can be performed to identify areas that were most affected by a disaster event, and to obtain a map of quantitative changes in terms of height differences. In the case of earthquakes in built-up areas for instance, first responders can use a LiDAR change map to help prioritize search and recovery efforts. The main challenge consists of producing reliable change maps, robust to collection conditions, free of processing artifacts (due for instance to triangulation or gridding), and taking into account the various sources of uncertainty. Indeed, datasets acquired within a few years interval are often of different point density (sometimes an order of magnitude higher for recent data), different acquisition geometries, and very likely suffer from georeferencing errors and geometric discrepancies. All these differences might not be important for producing maps from each dataset separately, but they are crucial when performing change detection. We have developed a novel technique for the estimation of uncertainty maps from the LiDAR point clouds, using Bayesian inference, treating all variables as random. The main principle is to grid all points on a common grid before attempting any comparison, as working directly with point clouds is cumbersome and time consuming. A non-parametric approach based on local linear regression was implemented, assuming a locally linear model for the surface. This enabled us to derive error bars on gridded elevations, and then elevation differences. In this way, a map of statistically significant changes could be computed - whereas a deterministic approach would not allow testing of the significance of differences between the two datasets. This approach allowed us to take into account not only the observation noise (due to ranging, position and attitude errors) but also the intrinsic roughness of the observed surfaces occurring when scanning vegetation. As only

  19. Characterizing the Vertical Distribution of Aerosols using Ground-based Multiwavelength Lidar Data

    Science.gov (United States)

    Ferrare, R. A.; Thorsen, T. J.; Clayton, M.; Mueller, D.; Chemyakin, E.; Burton, S. P.; Goldsmith, J.; Holz, R.; Kuehn, R.; Eloranta, E. W.; Marais, W.; Newsom, R. K.; Liu, X.; Sawamura, P.; Holben, B. N.; Hostetler, C. A.

    2016-12-01

    Observations of aerosol optical and microphysical properties are critical for developing and evaluating aerosol transport model parameterizations and assessing global aerosol-radiation impacts on climate. During the Combined HSRL And Raman lidar Measurement Study (CHARMS), we investigated the synergistic use of ground-based Raman lidar and High Spectral Resolution Lidar (HSRL) measurements to retrieve aerosol properties aloft. Continuous (24/7) operation of these co-located lidars during the ten-week CHARMS mission (mid-July through September 2015) allowed the acquisition of a unique, multiwavelength ground-based lidar dataset for studying aerosol properties above the Southern Great Plains (SGP) site. The ARM Raman lidar measured profiles of aerosol backscatter, extinction and depolarization at 355 nm as well as profiles of water vapor mixing ratio and temperature. The University of Wisconsin HSRL simultaneously measured profiles of aerosol backscatter, extinction and depolarization at 532 nm and aerosol backscatter at 1064 nm. Recent advances in both lidar retrieval theory and algorithm development demonstrate that vertically-resolved retrievals using such multiwavelength lidar measurements of aerosol backscatter and extinction can help constrain both the aerosol optical (e.g. complex refractive index, scattering, etc.) and microphysical properties (e.g. effective radius, concentrations) as well as provide qualitative aerosol classification. Based on this work, the NASA Langley Research Center (LaRC) HSRL group developed automated algorithms for classifying and retrieving aerosol optical and microphysical properties, demonstrated these retrievals using data from the unique NASA/LaRC airborne multiwavelength HSRL-2 system, and validated the results using coincident airborne in situ data. We apply these algorithms to the CHARMS multiwavelength (Raman+HSRL) lidar dataset to retrieve aerosol properties above the SGP site. We present some profiles of aerosol effective

  20. 2004 Alaska Lidar Mapping

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The data sets are generated using the OPTECH ALTM 70 kHz LIDAR system mounted onboard AeroMap's twin-engine Cessna 320 aircraft. Classified data sets such as this...

  1. Calibrating nacelle lidars

    Energy Technology Data Exchange (ETDEWEB)

    Courtney, M.

    2013-01-15

    Nacelle mounted, forward looking wind lidars are beginning to be used to provide reference wind speed measurements for the power performance testing of wind turbines. In such applications, a formal calibration procedure with a corresponding uncertainty assessment will be necessary. This report presents four concepts for performing such a nacelle lidar calibration. Of the four methods, two are found to be immediately relevant and are pursued in some detail. The first of these is a line of sight calibration method in which both lines of sight (for a two beam lidar) are individually calibrated by accurately aligning the beam to pass close to a reference wind speed sensor. A testing procedure is presented, reporting requirements outlined and the uncertainty of the method analysed. It is seen that the main limitation of the line of sight calibration method is the time required to obtain a representative distribution of radial wind speeds. An alternative method is to place the nacelle lidar on the ground and incline the beams upwards to bisect a mast equipped with reference instrumentation at a known height and range. This method will be easier and faster to implement and execute but the beam inclination introduces extra uncertainties. A procedure for conducting such a calibration is presented and initial indications of the uncertainties given. A discussion of the merits and weaknesses of the two methods is given together with some proposals for the next important steps to be taken in this work. (Author)

  2. Nacelle lidar power curve

    DEFF Research Database (Denmark)

    Gómez Arranz, Paula; Wagner, Rozenn

    This report describes the power curve measurements performed with a nacelle LIDAR on a given wind turbine in a wind farm and during a chosen measurement period. The measurements and analysis are carried out in accordance to the guidelines in the procedure “DTU Wind Energy-E-0019” [1]. The reporting...

  3. Lidar 2009 - IMG

    Data.gov (United States)

    Kansas Data Access and Support Center — ESRI Grids 1 meter resolution are created from the ground classified lidar points. The tiles are delivered in 5,000m by 5,000m tiles. The ESRI grids are exported to...

  4. Isfahan MISP Dataset.

    Science.gov (United States)

    Kashefpur, Masoud; Kafieh, Rahele; Jorjandi, Sahar; Golmohammadi, Hadis; Khodabande, Zahra; Abbasi, Mohammadreza; Teifuri, Nilufar; Fakharzadeh, Ali Akbar; Kashefpoor, Maryam; Rabbani, Hossein

    2017-01-01

    An online depository was introduced to share clinical ground truth with the public and provide open access for researchers to evaluate their computer-aided algorithms. PHP was used for web programming and MySQL for database managing. The website was entitled "biosigdata.com." It was a fast, secure, and easy-to-use online database for medical signals and images. Freely registered users could download the datasets and could also share their own supplementary materials while maintaining their privacies (citation and fee). Commenting was also available for all datasets, and automatic sitemap and semi-automatic SEO indexing have been set for the site. A comprehensive list of available websites for medical datasets is also presented as a Supplementary (http://journalonweb.com/tempaccess/4800.584.JMSS_55_16I3253.pdf).

  5. Using LiDAR to as a Potential Method for Detection Plastics in Water

    Science.gov (United States)

    Lee, G.; Neal, A.; Mielke, R.; Bookhagen, B.

    2010-12-01

    We conducted a series of experiments using Light Detection and Range (LiDAR) technology as an innovative way to detect the presence of plastics in water. The purpose of this study was to determine if LiDAR technology is a feasible, non-intrusive alternative to dredging in the ocean to determine the amount of plastics in the ocean. We used a tripod mounted RIEGL LMS-Z420i terrestrial LiDAR 3-D scanner and the associated operating software RiSCAN Pro. The terrestrial LiDAR is an optical remote sensing technology that measures the reflection of near infared light to find the range of a distant target that is most commonly used to create high precision digital elevation models of terrestrial surfaces. In theory, water should absorb the near infared light, while the plastics should reflect the light. The experiments consisted of different scale models of plastic pellets in water, ranging from a small plastic dish to a large tank to test the range of the LiDAR in different salt and fresh water mediums.

  6. Mridangam stroke dataset

    OpenAIRE

    CompMusic

    2014-01-01

    The audio examples were recorded from a professional Carnatic percussionist in a semi-anechoic studio conditions by Akshay Anantapadmanabhan using SM-58 microphones and an H4n ZOOM recorder. The audio was sampled at 44.1 kHz and stored as 16 bit wav files. The dataset can be used for training models for each Mridangam stroke. /n/nA detailed description of the Mridangam and its strokes can be found in the paper below. A part of the dataset was used in the following paper. /nAkshay Anantapadman...

  7. The GTZAN dataset

    DEFF Research Database (Denmark)

    Sturm, Bob L.

    2013-01-01

    The GTZAN dataset appears in at least 100 published works, and is the most-used public dataset for evaluation in machine listening research for music genre recognition (MGR). Our recent work, however, shows GTZAN has several faults (repetitions, mislabelings, and distortions), which challenge...... of GTZAN, and provide a catalog of its faults. We review how GTZAN has been used in MGR research, and find few indications that its faults have been known and considered. Finally, we rigorously study the effects of its faults on evaluating five different MGR systems. The lesson is not to banish GTZAN...

  8. Automated Detection of Geomorphic Features in LiDAR Point Clouds of Various Spatial Density

    Science.gov (United States)

    Dorninger, Peter; Székely, Balázs; Zámolyi, András.; Nothegger, Clemens

    2010-05-01

    LiDAR, also referred to as laser scanning, has proved to be an important tool for topographic data acquisition. Terrestrial laser scanning allows for accurate (several millimeter) and high resolution (several centimeter) data acquisition at distances of up to some hundred meters. By contrast, airborne laser scanning allows for acquiring homogeneous data for large areas, albeit with lower accuracy (decimeter) and resolution (some ten points per square meter) compared to terrestrial laser scanning. Hence, terrestrial laser scanning is preferably used for precise data acquisition of limited areas such as landslides or steep structures, while airborne laser scanning is well suited for the acquisition of topographic data of huge areas or even country wide. Laser scanners acquire more or less homogeneously distributed point clouds. These points represent natural objects like terrain and vegetation and artificial objects like buildings, streets or power lines. Typical products derived from such data are geometric models such as digital surface models representing all natural and artificial objects and digital terrain models representing the geomorphic topography only. As the LiDAR technology evolves, the amount of data produced increases almost exponentially even in smaller projects. This means a considerable challenge for the end user of the data: the experimenter has to have enough knowledge, experience and computer capacity in order to manage the acquired dataset and to derive geomorphologically relevant information from the raw or intermediate data products. Additionally, all this information might need to be integrated with other data like orthophotos. In all theses cases, in general, interactive interpretation is necessary to determine geomorphic structures from such models to achieve effective data reduction. There is little support for the automatic determination of characteristic features and their statistical evaluation. From the lessons learnt from automated

  9. A FAST AND ROBUST ALGORITHM FOR ROAD EDGES EXTRACTION FROM LIDAR DATA

    Directory of Open Access Journals (Sweden)

    K. Qiu

    2016-06-01

    Full Text Available Fast mapping of roads plays an important role in many geospatial applications, such as infrastructure planning, traffic monitoring, and driver assistance. How to extract various road edges fast and robustly is a challenging task. In this paper, we present a fast and robust algorithm for the automatic road edges extraction from terrestrial mobile LiDAR data. The algorithm is based on a key observation: most roads around edges have difference in elevation and road edges with pavement are seen in two different planes. In our algorithm, we firstly extract a rough plane based on RANSAC algorithm, and then multiple refined planes which only contains pavement are extracted from the rough plane. The road edges are extracted based on these refined planes. In practice, there is a serious problem that the rough and refined planes usually extracted badly due to rough roads and different density of point cloud. To eliminate the influence of rough roads, the technology which is similar with the difference of DSM (digital surface model and DTM (digital terrain model is used, and we also propose a method which adjust the point clouds to a similar density to eliminate the influence of different density. Experiments show the validities of the proposed method with multiple datasets (e.g. urban road, highway, and some rural road. We use the same parameters through the experiments and our algorithm can achieve real-time processing speeds.

  10. Localized Segment Based Processing for Automatic Building Extraction from LiDAR Data

    Science.gov (United States)

    Parida, G.; Rajan, K. S.

    2017-05-01

    The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

  11. LOCALIZED SEGMENT BASED PROCESSING FOR AUTOMATIC BUILDING EXTRACTION FROM LiDAR DATA

    Directory of Open Access Journals (Sweden)

    G. Parida

    2017-05-01

    Full Text Available The current methods of object segmentation and extraction and classification of aerial LiDAR data is manual and tedious task. This work proposes a technique for object segmentation out of LiDAR data. A bottom-up geometric rule based approach was used initially to devise a way to segment buildings out of the LiDAR datasets. For curved wall surfaces, comparison of localized surface normals was done to segment buildings. The algorithm has been applied to both synthetic datasets as well as real world dataset of Vaihingen, Germany. Preliminary results show successful segmentation of the buildings objects from a given scene in case of synthetic datasets and promissory results in case of real world data. The advantages of the proposed work is non-dependence on any other form of data required except LiDAR. It is an unsupervised method of building segmentation, thus requires no model training as seen in supervised techniques. It focuses on extracting the walls of the buildings to construct the footprint, rather than focussing on roof. The focus on extracting the wall to reconstruct the buildings from a LiDAR scene is crux of the method proposed. The current segmentation approach can be used to get 2D footprints of the buildings, with further scope to generate 3D models. Thus, the proposed method can be used as a tool to get footprints of buildings in urban landscapes, helping in urban planning and the smart cities endeavour.

  12. 2015 OLC Lidar DEM: Wasco, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Wasco County, WA, study area. The Oregon LiDAR Consortium's Wasco County...

  13. 2006 MDEQ Camp Shelby, MS Lidar Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata record describes the acquisition and processing of bare earth lidar data, raw point cloud lidar data, lidar intensity data, and floodmap breaklines...

  14. Dataset - Adviesregel PPL 2010

    NARCIS (Netherlands)

    Evert, van F.K.; Schans, van der D.A.; Geel, van W.C.A.; Slabbekoorn, J.J.; Booij, R.; Jukema, J.N.; Meurs, E.J.J.; Uenk, D.

    2011-01-01

    This dataset contains experimental data from a number of field experiments with potato in The Netherlands (Van Evert et al., 2011). The data are presented as an SQL dump of a PostgreSQL database (version 8.4.4). An outline of the entity-relationship diagram of the database is given in an

  15. Remote identification of potential polar bear maternal denning habitat in northern Alaska using airborne LiDAR

    Science.gov (United States)

    Jones, B. M.; Durner, G. M.; Stoker, J.; Shideler, R.; Perham, C.; Liston, G. E.

    2013-12-01

    Polar bear (Ursus maritimus) populations throughout the Arctic are being threatened by reductions in critical sea ice habitat. Throughout much of their range, polar bears give birth to their young in winter dens that are excavated in snowdrifts. New-born cubs, which are unable to survive exposure to Arctic winter weather, require 2-3 months of the relatively warm, stable, and undisturbed environment of the den for their growth. In the southern Beaufort Sea (BS), polar bears may den on the Alaskan Arctic Coastal Plain (ACP).The proportion of dens occurring on land has increased because of reductions in stable multi-year ice, increases in unconsolidated ice, and lengthening of the fall open-water period. Large portions of the ACP are currently being used for oil and gas activities and proposed projects will likely expand this footprint in the near future. Since petroleum exploration and development activities increase during winter there is the potential for human activities to disturb polar bears in maternal dens. Thus, maps showing the potential distribution of terrestrial denning habitat can help to mitigate negative interactions. Prior remote sensing efforts have consisted of manual interpretation of vertical aerial photography and automated classification of Interferometric Synthetic Aperture (IfSAR) derived digital terrain models (DTM) (5-m spatial resolution) focused on the identification of snowdrift forming landscape features. In this study, we assess the feasibility of airborne Light Detection and Ranging (LiDAR) data (2-m spatial resolution) for the automated classification of potential polar bear maternal denning habitat in a 1,400 km2 area on the central portion of the ACP. The study region spans the BS coast from the Prudhoe Bay oilfield in the west to near Point Thompson in the east and extends inland from 10 to 30 km. Approximately 800 km2 of the study area contains 19 known den locations, 51 field survey sites with information on bank height and

  16. Lidar: air pollution applications

    International Nuclear Information System (INIS)

    Collis, R.T.H.

    1977-01-01

    This introduction to the use of lidar in air pollution applications is mainly concerned with its capability to detect and monitor atmospheric particulates by elastic backscattering. Even when quite imperceptible to the eye, such particulates may be detected at ranges of several kilometers even by lidars of modest performance. This capability is valuable in connection with air pollution in the following ways: by mapping and tracking inhomogeneities in particulate concentration, atmospheric structure and motion may be monitored; measurements of the optical properties of the atmosphere provide an indication of turbidity or of particulate number or mass concentrations; and the capability of obtaining at a single point return signals from remote atmospheric volumes makes it possible to make range-resolved measurements of gaseous concentration along the path by using the resonant absorption of energy of appropriate wavelengths

  17. Let’s agree on the casing of Lidar

    Science.gov (United States)

    Deering, Carol; Stoker, Jason M.

    2014-01-01

    Is it lidar, Lidar, LiDAR, LIDAR, LiDar, LiDaR, or liDAR? A comprehensive review of the scientific/technical literature reveals seven different casings of this short form for light detection and ranging. And there could be more.

  18. Can Wind Lidars Measure Turbulence?

    DEFF Research Database (Denmark)

    Sathe, Ameya; Mann, Jakob; Gottschall, Julia

    2011-01-01

    Modeling of the systematic errors in the second-order moments of wind speeds measured by continuous-wave (ZephIR) and pulsed (WindCube) lidars is presented. These lidars use the conical scanning technique to measure the velocity field. The model captures the effect of volume illumination and coni...

  19. Digital Elevation Model (DEM), LiDAR acquired and processed over the entire county to support the generation of 1"=100' scale orthophotos & 2' contours. The Lidar LAS data has been classified to bare-earth as well as first-return points., Published in 2009, 1:1200 (1in=100ft) scale, Maryland National Capital Park and Planning Commission.

    Data.gov (United States)

    NSGIC Non-Profit | GIS Inventory — Digital Elevation Model (DEM) dataset current as of 2009. LiDAR acquired and processed over the entire county to support the generation of 1"=100' scale orthophotos...

  20. Statistical correction of lidar-derived digital elevation models with multispectral airborne imagery in tidal marshes

    Science.gov (United States)

    Buffington, Kevin J.; Dugger, Bruce D.; Thorne, Karen M.; Takekawa, John Y.

    2016-01-01

    Airborne light detection and ranging (lidar) is a valuable tool for collecting large amounts of elevation data across large areas; however, the limited ability to penetrate dense vegetation with lidar hinders its usefulness for measuring tidal marsh platforms. Methods to correct lidar elevation data are available, but a reliable method that requires limited field work and maintains spatial resolution is lacking. We present a novel method, the Lidar Elevation Adjustment with NDVI (LEAN), to correct lidar digital elevation models (DEMs) with vegetation indices from readily available multispectral airborne imagery (NAIP) and RTK-GPS surveys. Using 17 study sites along the Pacific coast of the U.S., we achieved an average root mean squared error (RMSE) of 0.072 m, with a 40–75% improvement in accuracy from the lidar bare earth DEM. Results from our method compared favorably with results from three other methods (minimum-bin gridding, mean error correction, and vegetation correction factors), and a power analysis applying our extensive RTK-GPS dataset showed that on average 118 points were necessary to calibrate a site-specific correction model for tidal marshes along the Pacific coast. By using available imagery and with minimal field surveys, we showed that lidar-derived DEMs can be adjusted for greater accuracy while maintaining high (1 m) resolution.

  1. LIDAR COMBINED SCANNING UNIT

    Directory of Open Access Journals (Sweden)

    V. V. Elizarov

    2016-11-01

    Full Text Available Subject of Research. The results of lidar combined scanning unit development for locating leaks of hydrocarbons are presented The unit enables to perform high-speed scanning of the investigated space in wide and narrow angle fields. Method. Scanning in a wide angular field is produced by one-line scanning path by means of the movable aluminum mirror with a frequency of 20Hz and amplitude of 20 degrees of swing. Narrowband scanning is performed along a spiral path by the deflector. The deflection of the beam is done by rotation of the optical wedges forming part of the deflector at an angle of ±50. The control function of the scanning node is performed by a specialized software product written in C# programming language. Main Results. This scanning unit allows scanning the investigated area at a distance of 50-100 m with spatial resolution at the level of 3 cm. The positioning accuracy of the laser beam in space is 15'. The developed scanning unit gives the possibility to browse the entire investigated area for the time not more than 1 ms at a rotation frequency of each wedge from 50 to 200 Hz. The problem of unambiguous definition of the beam geographical coordinates in space is solved at the software level according to the rotation angles of the mirrors and optical wedges. Lidar system coordinates are determined by means of GPS. Practical Relevance. Development results open the possibility for increasing the spatial resolution of scanning systems of a wide range of lidars and can provide high positioning accuracy of the laser beam in space.

  2. Balloonborne lidar experiment

    Science.gov (United States)

    Shepherd, O.; Aurilio, G.; Bucknam, R. D.; Brooke, R. W.; Hurd, A. G.

    1980-12-01

    The object of this contract was to design a balloonborne lidar experiment capable of performing nightime atmospheric density measurements in the 10 to 40 km altitude domain with a resolution of 100 meters. The payload includes a frequency-tripled Nd:YAG laser with outputs at 353 and 1064 nm, a telescoped receiver with PMT detectors, a command-controlled optical pointing system, and support systems, including thermal control, telemetry, command, and power. Density measurements would be made using the back-scattered 353 nm radiation data with aerosol corrections obtained from 1064 nm radiation scatterings.

  3. Compressive full waveform lidar

    Science.gov (United States)

    Yang, Weiyi; Ke, Jun

    2017-05-01

    To avoid high bandwidth detector, fast speed A/D converter, and large size memory disk, a compressive full waveform LIDAR system, which uses a temporally modulated laser instead of a pulsed laser, is studied in this paper. Full waveform data from NEON (National Ecological Observatory Network) are used. Random binary patterns are used to modulate the source. To achieve 0.15 m ranging resolution, a 100 MSPS A/D converter is assumed to make measurements. SPIRAL algorithm with canonical basis is employed when Poisson noise is considered in the low illuminated condition.

  4. Lidar Remote Sensing for Characterizing Forest Vegetation - Special Issue. Foreword

    Science.gov (United States)

    Popescu, Sorin C.; Nelson, Ross F.

    2011-01-01

    , and 6) forest inventory, (7) silvicultural and ecological applications, and (8) terrestrial lidar applications. Within the constraint limiting the number of papers that could be fitted into the special issue we attempted to select those papers that best represented these conference topics and sections, giving special consideration to studies using forestry lidar data collected from each of the three platforms -- terrestrial, airborne, and spaceborne. Reflecting the international participation and reach of the conference, the studies presented here took place in the USA, Canada, Taiwan, the UK, and China.

  5. Lunar and Planetary Science XXXV: Mars: Remote Sensing and Terrestrial Analogs

    Science.gov (United States)

    2004-01-01

    The session "Mars: Remote Sensing and Terrestrial Analogs" included the following:Physical Meaning of the Hapke Parameter for Macroscopic Roughness: Experimental Determination for Planetary Regolith Surface Analogs and Numerical Approach; Near-Infrared Spectra of Martian Pyroxene Separates: First Results from Mars Spectroscopy Consortium; Anomalous Spectra of High-Ca Pyroxenes: Correlation Between Ir and M ssbauer Patterns; THEMIS-IR Emissivity Spectrum of a Large Dark Streak near Olympus Mons; Geomorphologic/Thermophysical Mapping of the Athabasca Region, Mars, Using THEMIS Infrared Imaging; Mars Thermal Inertia from THEMIS Data; Multispectral Analysis Methods for Mapping Aqueous Mineral Depostis in Proposed Paleolake Basins on Mars Using THEMIS Data; Joint Analysis of Mars Odyssey THEMIS Visible and Infrared Images: A Magic Airbrush for Qualitative and Quantitative Morphology; Analysis of Mars Thermal Emission Spectrometer Data Using Large Mineral Reference Libraries ; Negative Abundance : A Problem in Compositional Modeling of Hyperspectral Images; Mars-LAB: First Remote Sensing Data of Mineralogy Exposed at Small Mars-Analog Craters, Nevada Test Site; A Tool for the 2003 Rover Mini-TES: Downwelling Radiance Compensation Using Integrated Line-Sight Sky Measurements; Learning About Mars Geology Using Thermal Infrared Spectral Imaging: Orbiter and Rover Perspectives; Classifying Terrestrial Volcanic Alteration Processes and Defining Alteration Processes they Represent on Mars; Cemented Volcanic Soils, Martian Spectra and Implications for the Martian Climate; Palagonitic Mars: A Basalt Centric View of Surface Composition and Aqueous Alteration; Combining a Non Linear Unmixing Model and the Tetracorder Algorithm: Application to the ISM Dataset; Spectral Reflectance Properties of Some Basaltic Weathering Products; Morphometric LIDAR Analysis of Amboy Crater, California: Application to MOLA Analysis of Analog Features on Mars; Airborne Radar Study of Soil Moisture at

  6. Terrestrial multi-view photogrammetry for landslide monitoring

    Science.gov (United States)

    Stumpf, A.; Malet, J.; Allemand, P.; Skupinski, G.; Pierrot-Deseilligny, M.

    2013-12-01

    Multi-view stereo (MVS) surface reconstruction from large photo collections is being increasingly used for geoscience applications, and a number of different software solution and processing streamlines have been suggested. Open source libraries to perform feature point extraction, pose estimation, bundle adjustment and dense matching are available providing high quality results at low costs, and transparency of the implemented algorithms. Within the computer vision community benchmark datasets with toy examples and architectural scenes are frequently used to evaluate dense matching algorithms but relatively few studies have addressed the evaluation of complete processing pipelines for complex natural landscapes such as landslides developed in high mountain terrains. In order to obtain surface displacement maps of an active landslide (Super-Sauze, Southern French Alps) from multi-temporal terrestrial photographs over a period of three years, this work targeted the evaluation of three different non-commercial processing pipelines. The tested packages include VisualSfM[1], CMVS-PMVS [2], Apero and MicMac [URL]. The image acquisition focused on either subparts of the landslide (toe, main scarp) or targeted the reconstruction of a global model of the entire landslide. All images were processed with three different pipelines namely VisualSfM + CMVS-PMVS, Apero + CMVS-PMVS and Apero + MicMac and the resulting point clouds were evaluated with terrestrial and airborne LiDAR. Our results show that all multi-view stereo pipelines provide useful results to quantify surface displacement at accuracies between 1-10 cm depending on the acquisition geometry and the object distance. For pose estimation and bundle adjustment, Apero is the more accurate and versatile tool allowing the use of more sophisticated lens models and the direct integration of ground control points in the bundle adjustment. The dense matching algorithms with MicMac enables the reconstruction of denser point

  7. i-LOVE: ISS-JEM lidar for observation of vegetation environment

    Science.gov (United States)

    Asai, Kazuhiro; Sawada, Haruo; Sugimoto, Nobuo; Mizutani, Kohei; Ishii, Shoken; Nishizawa, Tomoaki; Shimoda, Haruhisa; Honda, Yoshiaki; Kajiwara, Koji; Takao, Gen; Hirata, Yasumasa; Saigusa, Nobuko; Hayashi, Masatomo; Oguma, Hiroyuki; Saito, Hideki; Awaya, Yoshio; Endo, Takahiro; Imai, Tadashi; Murooka, Jumpei; Kobatashi, Takashi; Suzuki, Keiko; Sato, Ryota

    2012-11-01

    It is very important to watch the spatial distribution of vegetation biomass and changes in biomass over time, representing invaluable information to improve present assessments and future projections of the terrestrial carbon cycle. A space lidar is well known as a powerful remote sensing technology for measuring the canopy height accurately. This paper describes the ISS(International Space Station)-JEM(Japanese Experimental Module)-EF(Exposed Facility) borne vegetation lidar using a two dimensional array detector in order to reduce the root mean square error (RMSE) of tree height due to sloped surface.

  8. Doppler Lidar Vector Retrievals and Atmospheric Data Visualization in Mixed/Augmented Reality

    Science.gov (United States)

    Cherukuru, Nihanth Wagmi

    Environmental remote sensing has seen rapid growth in the recent years and Doppler wind lidars have gained popularity primarily due to their non-intrusive, high spatial and temporal measurement capabilities. While lidar applications early on, relied on the radial velocity measurements alone, most of the practical applications in wind farm control and short term wind prediction require knowledge of the vector wind field. Over the past couple of years, multiple works on lidars have explored three primary methods of retrieving wind vectors viz., using homogeneous windfield assumption, computationally extensive variational methods and the use of multiple Doppler lidars. Building on prior research, the current three-part study, first demonstrates the capabilities of single and dual Doppler lidar retrievals in capturing downslope windstorm-type flows occurring at Arizona's Barringer Meteor Crater as a part of the METCRAX II field experiment. Next, to address the need for a reliable and computationally efficient vector retrieval for adaptive wind farm control applications, a novel 2D vector retrieval based on a variational formulation was developed and applied on lidar scans from an offshore wind farm and validated with data from a cup and vane anemometer installed on a nearby research platform. Finally, a novel data visualization technique using Mixed Reality (MR)/ Augmented Reality (AR) technology is presented to visualize data from atmospheric sensors. MR is an environment in which the user's visual perception of the real world is enhanced with live, interactive, computer generated sensory input (in this case, data from atmospheric sensors like Doppler lidars). A methodology using modern game development platforms is presented and demonstrated with lidar retrieved wind fields. In the current study, the possibility of using this technology to visualize data from atmospheric sensors in mixed reality is explored and demonstrated with lidar retrieved wind fields as well as

  9. 2012 Oregon Lidar Consortium (OLC) Lidar DEM: Keno (OR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data of the Oregon Keno Study Area for the Oregon Department of Geology and Mineral...

  10. 2012 Oregon Lidar Consortium (OLC) Lidar: Keno (OR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data of the Oregon Keno Study Area for the Oregon Department of Geology and Mineral...

  11. Characterizing Terrestrial Exoplanets

    Science.gov (United States)

    Meadows, V. S.; Lustig-Yaeger, J.; Lincowski, A.; Arney, G. N.; Robinson, T. D.; Schwieterman, E. W.; Deming, L. D.; Tovar, G.

    2017-11-01

    We will provide an overview of the measurements, techniques, and upcoming missions required to characterize terrestrial planet environments and evolution, and search for signs of habitability and life.

  12. 2009 SCDRN Lidar: Florence County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The South Carolina Department of Natural Resources (SCDNR) contracted with Sanborn to provide LiDAR mapping services for Florence County, SC. Utilizing multi-return...

  13. 2006 FEMA Lidar: Hawaiian Islands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The FEMA Task Order 26 LiDAR data set was collected by Airborne 1 Corporation of El Segundo, California in September - December of 2006 for URS Corp.

  14. 2009 SCDNR Charleston County Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Photoscience completed the original collection and classification of the multiple return LiDAR of Charleston County, South Carolina in the winter of 2006-2007. In...

  15. 2009 Chatham County Georgia Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR generated point cloud acquired in spring 2009 for Chatham County, Georgia for the Metropolitan Planning Commission. The data are classified as follows: Class 1...

  16. 2014 NJMC Lidar: Hackensack Meadowlands

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In February 2014, Quantum Spatial, Inc. (QSI) was contracted by the New Jersey Meadowlands Commission (NJMC) to collect Light Detection and Ranging (LiDAR) data in...

  17. Alabama 2003 Lidar Coverage, USACE

    Data.gov (United States)

    Army Corps of Engineers, Department of the Army, Department of Defense — The Joint Airborne Lidar Bathymetry Technical Center of Expertise (JALBTCX) has performed a coastal survey along the Gulf of Mexico in the summer of 2003. The data...

  18. 2014 Mobile County, AL Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Atlantic was contracted to acquire high resolution topographic LiDAR (Light Detection and Ranging) data located in Mobile County, Alabama. The intent was to collect...

  19. 2008 City of Baltimore Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In the spring of 2008, the City of Baltimore expressed an interest to upgrade the City GIS Database with mapping quality airborne LiDAR data. The City of Baltimore...

  20. 2013 USGS Lidar: Norfolk (VA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Laser Mapping Specialist, Inc (LMSI) and The Atlantic Group (Atlantic) provided high accuracy, calibrated multiple return LiDAR for roughly 1,130 square miles around...

  1. 2009 SCDNR Horry County Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Sanborn Map Company completed the original classification of the multiple return LiDAR of Horry County, South Carolina in 2009. In 2013, Dewberry was tasked with...

  2. LIDAR and atmosphere remote sensing

    CSIR Research Space (South Africa)

    Venkataraman, S

    2008-05-01

    Full Text Available using state of the art Light Detection And Ranging (LiDAR) instrumentation and other active and passive remote sensing tools. First “Lidar Field Campaign” • 2-day measurement campaign at University of Pretoria • First 23-hour continuous measurement... head2rightCirrus cloud morphology and dynamics. Atmospheric Research in Southern Africa and Indian Ocean (ARSAIO) Slide 24 © CSIR 2008 www.csir.co.za Middle atmosphere dynamics and thermal structure: comparative studies from...

  3. A generalized adaptive mathematical morphological filter for LIDAR data

    Science.gov (United States)

    Cui, Zheng

    Airborne Light Detection and Ranging (LIDAR) technology has become the primary method to derive high-resolution Digital Terrain Models (DTMs), which are essential for studying Earth's surface processes, such as flooding and landslides. The critical step in generating a DTM is to separate ground and non-ground measurements in a voluminous point LIDAR dataset, using a filter, because the DTM is created by interpolating ground points. As one of widely used filtering methods, the progressive morphological (PM) filter has the advantages of classifying the LIDAR data at the point level, a linear computational complexity, and preserving the geometric shapes of terrain features. The filter works well in an urban setting with a gentle slope and a mixture of vegetation and buildings. However, the PM filter often removes ground measurements incorrectly at the topographic high area, along with large sizes of non-ground objects, because it uses a constant threshold slope, resulting in "cut-off" errors. A novel cluster analysis method was developed in this study and incorporated into the PM filter to prevent the removal of the ground measurements at topographic highs. Furthermore, to obtain the optimal filtering results for an area with undulating terrain, a trend analysis method was developed to adaptively estimate the slope-related thresholds of the PM filter based on changes of topographic slopes and the characteristics of non-terrain objects. The comparison of the PM and generalized adaptive PM (GAPM) filters for selected study areas indicates that the GAPM filter preserves the most "cut-off" points removed incorrectly by the PM filter. The application of the GAPM filter to seven ISPRS benchmark datasets shows that the GAPM filter reduces the filtering error by 20% on average, compared with the method used by the popular commercial software TerraScan. The combination of the cluster method, adaptive trend analysis, and the PM filter allows users without much experience in

  4. Detecting Multi-layered Forest Stands Using High Density Airborne LiDAR Data. GI_Forum|GI_Forum 2015 – Geospatial Minds for Society|

    OpenAIRE

    Schultz, Alfred; Mund, Jan-Peter; Körner, Michael; Wilke, Robert

    2016-01-01

    Since two decades, the use of terrestrial laser scanning (TLS) and Airborne Light Detection and Ranging (LIDAR) has become very prominent in analysing 3D forest structures (AKAY et al. 2009). The potential of full waveform analysis of high density Airborne LiDAR data (ALS) for the detection and structural analysis of multi-layered forest stands is not yet well investigated (JASKIERNIAK et al. 2011), although ALS data provide exact information on tree heights of multi-layered forest stands usi...

  5. Balloonborne lidar payloads for remote sensing

    Science.gov (United States)

    Shepherd, O.; Aurilio, G.; Hurd, A. G.; Rappaport, S. A.; Reidy, W. P.; Rieder, R. J.; Bedo, D. E.; Swirbalus, R. A.

    1994-02-01

    A series of lidar experiments has been conducted using the Atmospheric Balloonborne Lidar Experiment payload (ABLE). These experiments included the measurement of atmospheric Rayleigh and Mie backscatter from near space (approximately 30 km) and Raman backscatter measurements of atmospheric constituents as a function of altitude. The ABLE payload consisted of a frequency-tripled Nd:YAG laser transmitter, a 50 cm receiver telescope, and filtered photodetectors in various focal plane configurations. The payload for lidar pointing, thermal control, data handling, and remote control of the lidar system. Comparison of ABLE performance with that of a space lidar shows significant performance advantages and cost effectiveness for balloonborne lidar systems.

  6. Dietary characterization of terrestrial mammals.

    Science.gov (United States)

    Pineda-Munoz, Silvia; Alroy, John

    2014-08-22

    Understanding the feeding behaviour of the species that make up any ecosystem is essential for designing further research. Mammals have been studied intensively, but the criteria used for classifying their diets are far from being standardized. We built a database summarizing the dietary preferences of terrestrial mammals using published data regarding their stomach contents. We performed multivariate analyses in order to set up a standardized classification scheme. Ideally, food consumption percentages should be used instead of qualitative classifications. However, when highly detailed information is not available we propose classifying animals based on their main feeding resources. They should be classified as generalists when none of the feeding resources constitute over 50% of the diet. The term 'omnivore' should be avoided because it does not communicate all the complexity inherent to food choice. Moreover, the so-called omnivore diets actually involve several distinctive adaptations. Our dataset shows that terrestrial mammals are generally highly specialized and that some degree of food mixing may even be required for most species.

  7. National Elevation Dataset

    Science.gov (United States)

    ,

    2002-01-01

    The National Elevation Dataset (NED) is a new raster product assembled by the U.S. Geological Survey. NED is designed to provide National elevation data in a seamless form with a consistent datum, elevation unit, and projection. Data corrections were made in the NED assembly process to minimize artifacts, perform edge matching, and fill sliver areas of missing data. NED has a resolution of one arc-second (approximately 30 meters) for the conterminous United States, Hawaii, Puerto Rico and the island territories and a resolution of two arc-seconds for Alaska. NED data sources have a variety of elevation units, horizontal datums, and map projections. In the NED assembly process the elevation values are converted to decimal meters as a consistent unit of measure, NAD83 is consistently used as horizontal datum, and all the data are recast in a geographic projection. Older DEM's produced by methods that are now obsolete have been filtered during the NED assembly process to minimize artifacts that are commonly found in data produced by these methods. Artifact removal greatly improves the quality of the slope, shaded-relief, and synthetic drainage information that can be derived from the elevation data. Figure 2 illustrates the results of this artifact removal filtering. NED processing also includes steps to adjust values where adjacent DEM's do not match well, and to fill sliver areas of missing data between DEM's. These processing steps ensure that NED has no void areas and artificial discontinuities have been minimized. The artifact removal filtering process does not eliminate all of the artifacts. In areas where the only available DEM is produced by older methods, then "striping" may still occur.

  8. V. Terrestrial vertebrates

    Science.gov (United States)

    Dean Pearson; Deborah Finch

    2011-01-01

    Within the Interior West, terrestrial vertebrates do not represent a large number of invasive species relative to invasive weeds, aquatic vertebrates, and invertebrates. However, several invasive terrestrial vertebrate species do cause substantial economic and ecological damage in the U.S. and in this region (Pimental 2000, 2007; Bergman and others 2002; Finch and...

  9. Parallel Landscape Driven Data Reduction & Spatial Interpolation Algorithm for Big LiDAR Data

    Directory of Open Access Journals (Sweden)

    Rahil Sharma

    2016-06-01

    Full Text Available Airborne Light Detection and Ranging (LiDAR topographic data provide highly accurate digital terrain information, which is used widely in applications like creating flood insurance rate maps, forest and tree studies, coastal change mapping, soil and landscape classification, 3D urban modeling, river bank management, agricultural crop studies, etc. In this paper, we focus mainly on the use of LiDAR data in terrain modeling/Digital Elevation Model (DEM generation. Technological advancements in building LiDAR sensors have enabled highly accurate and highly dense LiDAR point clouds, which have made possible high resolution modeling of terrain surfaces. However, high density data result in massive data volumes, which pose computing issues. Computational time required for dissemination, processing and storage of these data is directly proportional to the volume of the data. We describe a novel technique based on the slope map of the terrain, which addresses the challenging problem in the area of spatial data analysis, of reducing this dense LiDAR data without sacrificing its accuracy. To the best of our knowledge, this is the first ever landscape-driven data reduction algorithm. We also perform an empirical study, which shows that there is no significant loss in accuracy for the DEM generated from a 52% reduced LiDAR dataset generated by our algorithm, compared to the DEM generated from an original, complete LiDAR dataset. For the accuracy of our statistical analysis, we perform Root Mean Square Error (RMSE comparing all of the grid points of the original DEM to the DEM generated by reduced data, instead of comparing a few random control points. Besides, our multi-core data reduction algorithm is highly scalable. We also describe a modified parallel Inverse Distance Weighted (IDW spatial interpolation method and show that the DEMs it generates are time-efficient and have better accuracy than the one’s generated by the traditional IDW method.

  10. An Easy-to-Use Airborne LiDAR Data Filtering Method Based on Cloth Simulation

    Directory of Open Access Journals (Sweden)

    Wuming Zhang

    2016-06-01

    Full Text Available Separating point clouds into ground and non-ground measurements is an essential step to generate digital terrain models (DTMs from airborne LiDAR (light detection and ranging data. However, most filtering algorithms need to carefully set up a number of complicated parameters to achieve high accuracy. In this paper, we present a new filtering method which only needs a few easy-to-set integer and Boolean parameters. Within the proposed approach, a LiDAR point cloud is inverted, and then a rigid cloth is used to cover the inverted surface. By analyzing the interactions between the cloth nodes and the corresponding LiDAR points, the locations of the cloth nodes can be determined to generate an approximation of the ground surface. Finally, the ground points can be extracted from the LiDAR point cloud by comparing the original LiDAR points and the generated surface. Benchmark datasets provided by ISPRS (International Society for Photogrammetry and Remote Sensing working Group III/3 are used to validate the proposed filtering method, and the experimental results yield an average total error of 4.58%, which is comparable with most of the state-of-the-art filtering algorithms. The proposed easy-to-use filtering method may help the users without much experience to use LiDAR data and related technology in their own applications more easily.

  11. The use of lidar images in Costa Rica : case studies applied in geology, engineering, and archaeology

    International Nuclear Information System (INIS)

    Ruiz, Paulo; Garro, Jose F.; Soto, Gerardo J.

    2014-01-01

    A historical review is made about evolution of technology Lidar (Laser Imaging Detection and Ranging). The improvements of this technology and additions from other technologies are annotated in the last 15 years. The information of the aerial and terrestrial lidar operation, technical parameters for data acquisition and resolutions are presented. The results from four studies are presented in Costa Rica: 1) The discovery of pre-Columbian trails in the area of Volcan Arenal, 2) A case of geological mapping and discovery of new volcanic structures in the North area of the Volcan Poas, 3) The characterization of a landslide near Palmares that represents a hazard for the road network, 4) A detail survey of a pre-Columbian sphere. The results from new Lidar will become more frequent in the following years because its cost will be more affordable. The transference of data between institutions will generate new applications in different fields. (author) [es

  12. NP-PAH Interaction Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Dataset presents concentrations of organic pollutants, such as polyaromatic hydrocarbon compounds, in water samples. Water samples of known volume and concentration...

  13. Integrated remotely sensed datasets for disaster management

    Science.gov (United States)

    McCarthy, Timothy; Farrell, Ronan; Curtis, Andrew; Fotheringham, A. Stewart

    2008-10-01

    Video imagery can be acquired from aerial, terrestrial and marine based platforms and has been exploited for a range of remote sensing applications over the past two decades. Examples include coastal surveys using aerial video, routecorridor infrastructures surveys using vehicle mounted video cameras, aerial surveys over forestry and agriculture, underwater habitat mapping and disaster management. Many of these video systems are based on interlaced, television standards such as North America's NTSC and European SECAM and PAL television systems that are then recorded using various video formats. This technology has recently being employed as a front-line, remote sensing technology for damage assessment post-disaster. This paper traces the development of spatial video as a remote sensing tool from the early 1980s to the present day. The background to a new spatial-video research initiative based at National University of Ireland, Maynooth, (NUIM) is described. New improvements are proposed and include; low-cost encoders, easy to use software decoders, timing issues and interoperability. These developments will enable specialists and non-specialists collect, process and integrate these datasets within minimal support. This integrated approach will enable decision makers to access relevant remotely sensed datasets quickly and so, carry out rapid damage assessment during and post-disaster.

  14. CALIBRATION OF LOW COST DIGITAL CAMERA USING DATA FROM SIMULTANEOUS LIDAR AND PHOTOGRAMMETRIC SURVEYS

    Directory of Open Access Journals (Sweden)

    E. Mitishita

    2012-07-01

    Full Text Available Digital photogrammetric products from the integration of imagery and lidar datasets are a reality nowadays. When the imagery and lidar surveys are performed together and the camera is connected to the lidar system, a direct georeferencing can be applied to compute the exterior orientation parameters of the images. Direct georeferencing of the images requires accurate interior orientation parameters to perform photogrammetric application. Camera calibration is a procedure applied to compute the interior orientation parameters (IOPs. Calibration researches have established that to obtain accurate IOPs, the calibration must be performed with same or equal condition that the photogrammetric survey is done. This paper shows the methodology and experiments results from in situ self-calibration using a simultaneous images block and lidar dataset. The calibration results are analyzed and discussed. To perform this research a test field was fixed in an urban area. A set of signalized points was implanted on the test field to use as the check points or control points. The photogrammetric images and lidar dataset of the test field were taken simultaneously. Four strips of flight were used to obtain a cross layout. The strips were taken with opposite directions of flight (W-E, E-W, N-S and S-N. The Kodak DSC Pro SLR/c digital camera was connected to the lidar system. The coordinates of the exposition station were computed from the lidar trajectory. Different layouts of vertical control points were used in the calibration experiments. The experiments use vertical coordinates from precise differential GPS survey or computed by an interpolation procedure using the lidar dataset. The positions of the exposition stations are used as control points in the calibration procedure to eliminate the linear dependency of the group of interior and exterior orientation parameters. This linear dependency happens, in the calibration procedure, when the vertical images and

  15. 2015 OLC Lidar DEM: Big Wood, ID

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Big Wood 2015 study area. This study area is located in...

  16. Iowa LiDAR Mapping Project

    Data.gov (United States)

    Federal Emergency Management Agency, Department of Homeland Security — This is collection level metadata for LAS and ASCII data files from the statewide Iowa Lidar Project. The Iowa Light Detection and Ranging (LiDAR) Project collects...

  17. 2007 South Carolina DNR Lidar: Dorchester County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Woolpert Inc. conducted a LiDAR survey to acquire LiDAR capable of producing a DEM for orthophoto rectification and able to support 2-foot contour specifications....

  18. 2015 OLC FEMA Lidar: Snake River, ID

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Snake River FEMA study area. This study area is located...

  19. 2007 South Carolina DNR Lidar: Anderson County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The LiDAR data acquisition was executed in 5 sessions, from March 7 to March 9, 2007. The airborne GPS (ABGPS) base stations supporting the LiDAR acquisition...

  20. 2011 South Carolina DNR Lidar: York County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Towill Inc. collected LiDAR for over 3,500 square miles in York, Pickens, Anderson, and Oconee Counties in South Carolina. This metadata covers the LiDAR produced...

  1. 2014 PSLC Lidar: City of Redmond

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In February 2014, Quantum Spatial (QSI) was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data for the City of...

  2. Elevation - LIDAR Survey - Roseau County, Minnesota

    Data.gov (United States)

    Army Corps of Engineers, Department of the Army, Department of Defense — LIDAR Data for Roseau County Minnesota. This project consists of approximately 87 square miles of LIDAR mapping in Roseau County, Minnesota at two sites: area 1,...

  3. 2009 Bayfield County Lake Superior Lidar Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The LIDAR survey presents digital elevation data sets of a bald earth surface model and 2ft interval contours covering Bayfield County, Wisconsin. The LIDAR data was...

  4. 2014 OLC Lidar DEM: Colville, WA

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI, a Quantum Spatial company, has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Colville study area. This study area is...

  5. 2014 Horry County, South Carolina Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is comprised of lidar point cloud data. This project required lidar data to be acquired over Horry County, South Carolina. The total area of the Horry...

  6. 2010 ARRA Lidar: 4 Southeast Counties (MI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Southeast Michigan LiDAR LiDAR Data Acquisition and Processing Production Task- Monroe, St. Clair, Macomb, and Livingston Counties SEMCOG CONTRACT:...

  7. 2015 Oregon Department Forestry Lidar: Northwest OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GeoTerra, Inc. was selected by Oregon Department of Forestry to provide Lidar remote sensing data including LAZ files of the classified Lidar points and surface...

  8. APPLICABILITY ANALYSIS OF CLOTH SIMULATION FILTERING ALGORITHM FOR MOBILE LIDAR POINT CLOUD

    Directory of Open Access Journals (Sweden)

    S. Cai

    2018-04-01

    Full Text Available Classifying the original point clouds into ground and non-ground points is a key step in LiDAR (light detection and ranging data post-processing. Cloth simulation filtering (CSF algorithm, which based on a physical process, has been validated to be an accurate, automatic and easy-to-use algorithm for airborne LiDAR point cloud. As a new technique of three-dimensional data collection, the mobile laser scanning (MLS has been gradually applied in various fields, such as reconstruction of digital terrain models (DTM, 3D building modeling and forest inventory and management. Compared with airborne LiDAR point cloud, there are some different features (such as point density feature, distribution feature and complexity feature for mobile LiDAR point cloud. Some filtering algorithms for airborne LiDAR data were directly used in mobile LiDAR point cloud, but it did not give satisfactory results. In this paper, we explore the ability of the CSF algorithm for mobile LiDAR point cloud. Three samples with different shape of the terrain are selected to test the performance of this algorithm, which respectively yields total errors of 0.44 %, 0.77 % and1.20 %. Additionally, large area dataset is also tested to further validate the effectiveness of this algorithm, and results show that it can quickly and accurately separate point clouds into ground and non-ground points. In summary, this algorithm is efficient and reliable for mobile LiDAR point cloud.

  9. CO-REGISTRATION OF PHOTOGRAMMETRIC AND LIDAR DATA: METHODOLOGY AND CASE STUDY

    Directory of Open Access Journals (Sweden)

    Mwafag Ghanma

    2004-07-01

    Full Text Available Registration activities combine data from different sources in order to attain higher accuracy and derive more information than available from one source. The increasing availability of a wide variety of sensors capable of capturing high quality and complementary data requires parallel efforts for developing accurate and robust registration techniques. Currently, photogrammetric and LIDAR systems are being incorporated in a wide spectrum of mapping applica¬tions such as city modeling, surface reconstruction, and object recognition. Photogrammetric processing of overlapping imagery provides accurate information regarding object space break-lines in addition to an explicit semantic description of the photographed objects. On the other hand, LIDAR systems supply dense geometric surface information in the form of non-selective points. Considering the properties of photogrammetric and LIDAR data, it is clear that the two technologies provide complementary information. However, the synergic characteristics of both systems can be fully utilized only after successful registration of the photogrammetric and LIDAR data relative to a common reference frame. The registration methodology has to deal with three issues: registration primitives, transformation function, and similarity measure. This paper presents two methodologies for utilizing straight-line features derived from both datasets as the registration primitives. The first methodology directly incorporates the LIDAR lines as control information in the photogrammetric triangulation. The second methodology starts by generating a photogrammetric model relative to an arbitrary datum. Then, LIDAR features are used as control information for the absolute orientation of the photogram¬metric model. In addition to the registration methodologies, the paper presents a comparative analysis between two approaches for extracting linear features from raw and processed/interpolated LIDAR data. Also, a comparative

  10. Editorial: Datasets for Learning Analytics

    NARCIS (Netherlands)

    Dietze, Stefan; George, Siemens; Davide, Taibi; Drachsler, Hendrik

    2018-01-01

    The European LinkedUp and LACE (Learning Analytics Community Exchange) project have been responsible for setting up a series of data challenges at the LAK conferences 2013 and 2014 around the LAK dataset. The LAK datasets consists of a rich collection of full text publications in the domain of

  11. LIDAR e Fotogrammetria Digitale verso una nuova integrazione

    Directory of Open Access Journals (Sweden)

    Fulvio Rinaudo

    2012-04-01

    Full Text Available In tutte le applicazioni del rilevo metrico la tecnica LIDAR e la Fotogrammetria Digitale giocano ormai un ruoloquasi esclusivo. Gli efficienti servizi forniti dalle reti di stazioni permanenti e dalle piattaforme GNSS/IMU hannoconsentito una rapida diffusione e una affidabilità mai raggiunta per altre tecniche di rilievo in ambito territoriale,così come pure nelle applicazioni terrestri quali il rilievo architettonico o il monitoraggio di fenomeni naturali, ovesono stati sostituiti quasi integralmente gli approcci tradizionali del rilievo topografico terrestre.LIDAR and Digital Photogrammetry towards a new integration A new integration approach between digital photogrammetry and LiDAR is presented in this paper. Up to now LiDAR use some  photogrammetric  topics  to  manage  point  clouds  and digital photogrammetry extract useful information from LiDAR data to produce traditional and accurate orthophoto. Considering that in traditional photogrammetric plotting the surveyor define the 3D location of the break-lines and add points just in those parts of the object where smooth surfaces can be defined, the proposed solution foresees a continuous exchange of information between those techniques in order to automatically extract the break-lines of the surveyed object. The final results  is  the  complete  breack-lines  3D  description  and  the point clouds portions useful to define smooth surfaces.  At the end of the automatic procedure a complete 3D set of information is produced in order to build up the fine 3D model of the surveyed object.

  12. LIDAR e Fotogrammetria Digitale verso una nuova integrazione

    Directory of Open Access Journals (Sweden)

    Fulvio Rinaudo

    2012-04-01

    Full Text Available In tutte le applicazioni del rilevo metrico la tecnica LIDAR e la Fotogrammetria Digitale giocano ormai un ruoloquasi esclusivo. Gli efficienti servizi forniti dalle reti di stazioni permanenti e dalle piattaforme GNSS/IMU hannoconsentito una rapida diffusione e una affidabilità mai raggiunta per altre tecniche di rilievo in ambito territoriale,così come pure nelle applicazioni terrestri quali il rilievo architettonico o il monitoraggio di fenomeni naturali, ovesono stati sostituiti quasi integralmente gli approcci tradizionali del rilievo topografico terrestre. LIDAR and Digital Photogrammetry towards a new integration A new integration approach between digital photogrammetry and LiDAR is presented in this paper. Up to now LiDAR use some  photogrammetric  topics  to  manage  point  clouds  and digital photogrammetry extract useful information from LiDAR data to produce traditional and accurate orthophoto. Considering that in traditional photogrammetric plotting the surveyor define the 3D location of the break-lines and add points just in those parts of the object where smooth surfaces can be defined, the proposed solution foresees a continuous exchange of information between those techniques in order to automatically extract the break-lines of the surveyed object. The final results  is  the  complete  breack-lines  3D  description  and  the point clouds portions useful to define smooth surfaces.  At the end of the automatic procedure a complete 3D set of information is produced in order to build up the fine 3D model of the surveyed object.

  13. Open University Learning Analytics dataset.

    Science.gov (United States)

    Kuzilek, Jakub; Hlosta, Martin; Zdrahal, Zdenek

    2017-11-28

    Learning Analytics focuses on the collection and analysis of learners' data to improve their learning experience by providing informed guidance and to optimise learning materials. To support the research in this area we have developed a dataset, containing data from courses presented at the Open University (OU). What makes the dataset unique is the fact that it contains demographic data together with aggregated clickstream data of students' interactions in the Virtual Learning Environment (VLE). This enables the analysis of student behaviour, represented by their actions. The dataset contains the information about 22 courses, 32,593 students, their assessment results, and logs of their interactions with the VLE represented by daily summaries of student clicks (10,655,280 entries). The dataset is freely available at https://analyse.kmi.open.ac.uk/open_dataset under a CC-BY 4.0 license.

  14. Generic methodology for calibrating profiling nacelle lidars

    DEFF Research Database (Denmark)

    Borraccino, Antoine; Courtney, Michael; Wagner, Rozenn

    Improving power performance assessment by measuring at different heights has been demonstrated using ground-based profiling LIDARs. More recently, nacelle-mounted lidars studies have shown promising capabilities to assess power performance. Using nacelle lidars avoids the erection of expensive me...

  15. Lidar extinction measurement in the mid infrared

    Science.gov (United States)

    Mitev, Valentin; Babichenko, S.; Borelli, R.; Fiorani, L.; Grigorov, I.; Nuvoli, M.; Palucci, A.; Pistilli, M.; Puiu, Ad.; Rebane, Ott; Santoro, S.

    2014-11-01

    We present a lidar measurement of atmospheric extinction coefficient. The measurement is performed by inversion of the backscatter lidar signal at wavelengths 3'000nm and 3'500nm. The inversion of the backscatter lidar signal was performed with constant extinction-to-backscatter ration values of 104 and exponential factor 0.1.

  16. Introduced Terrestrial Species (Future)

    Data.gov (United States)

    U.S. Environmental Protection Agency — These data represent predicted future potential distributions of terrestrial plants, animals, and pathogens non-native to the Middle-Atlantic region. These data are...

  17. PROGRESSIVE DENSIFICATION AND REGION GROWING METHODS FOR LIDAR DATA CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    J. L. Pérez-García

    2012-07-01

    Full Text Available At present, airborne laser scanner systems are one of the most frequent methods used to obtain digital terrain elevation models. While having the advantage of direct measurement on the object, the point cloud obtained has the need for classification of their points according to its belonging to the ground. This need for classification of raw data has led to appearance of multiple filters focused LiDAR classification information. According this approach, this paper presents a classification method that combines LiDAR data segmentation techniques and progressive densification to carry out the location of the points belonging to the ground. The proposed methodology is tested on several datasets with different terrain characteristics and data availability. In all case, we analyze the advantages and disadvantages that have been obtained compared with the individual techniques application and, in a special way, the benefits derived from the integration of both classification techniques. In order to provide a more comprehensive quality control of the classification process, the obtained results have been compared with the derived from a manual procedure, which is used as reference classification. The results are also compared with other automatic classification methodologies included in some commercial software packages, highly contrasted by users for LiDAR data treatment.

  18. MONITORING CONCEPTS FOR COASTAL AREAS USING LIDAR DATA

    Directory of Open Access Journals (Sweden)

    A. Schmidt

    2013-05-01

    Full Text Available Coastal areas are characterized by high spatial and temporal variability. In order to detect undesired changes at early stages, enabling rapid countermeasures to mitigate or minimize potential harm or hazard, a recurrent monitoring becomes necessary. In this paper, we focus on two monitoring task: the analysis of morphological changes and the classification and mapping of habitats. Our concepts are solely based on airborne lidar data which provide substantial information in coastal areas. For the first task, we generate a digital terrain model (DTM from the lidar point cloud and analyse the dynamic of an island by comparing the DTMs of different epochs with a time difference of six years. For the deeper understanding of the habitat composition in coastal areas, we classify the lidar point cloud by a supervised approach based on Conditional Random Fields. From the classified point cloud, water-land-boundaries as well as mussel bed objects are derived afterwards. We evaluate our approaches on two datasets of the German Wadden Sea.

  19. Rockfall hazard analysis using LiDAR and spatial modeling

    Science.gov (United States)

    Lan, Hengxing; Martin, C. Derek; Zhou, Chenghu; Lim, Chang Ho

    2010-05-01

    Rockfalls have been significant geohazards along the Canadian Class 1 Railways (CN Rail and CP Rail) since their construction in the late 1800s. These rockfalls cause damage to infrastructure, interruption of business, and environmental impacts, and their occurrence varies both spatially and temporally. The proactive management of these rockfall hazards requires enabling technologies. This paper discusses a hazard assessment strategy for rockfalls along a section of a Canadian railway using LiDAR and spatial modeling. LiDAR provides accurate topographical information of the source area of rockfalls and along their paths. Spatial modeling was conducted using Rockfall Analyst, a three dimensional extension to GIS, to determine the characteristics of the rockfalls in terms of travel distance, velocity and energy. Historical rockfall records were used to calibrate the physical characteristics of the rockfall processes. The results based on a high-resolution digital elevation model from a LiDAR dataset were compared with those based on a coarse digital elevation model. A comprehensive methodology for rockfall hazard assessment is proposed which takes into account the characteristics of source areas, the physical processes of rockfalls and the spatial attribution of their frequency and energy.

  20. Lidar-based individual tree species classification using convolutional neural network

    Science.gov (United States)

    Mizoguchi, Tomohiro; Ishii, Akira; Nakamura, Hiroyuki; Inoue, Tsuyoshi; Takamatsu, Hisashi

    2017-06-01

    Terrestrial lidar is commonly used for detailed documentation in the field of forest inventory investigation. Recent improvements of point cloud processing techniques enabled efficient and precise computation of an individual tree shape parameters, such as breast-height diameter, height, and volume. However, tree species are manually specified by skilled workers to date. Previous works for automatic tree species classification mainly focused on aerial or satellite images, and few works have been reported for classification techniques using ground-based sensor data. Several candidate sensors can be considered for classification, such as RGB or multi/hyper spectral cameras. Above all candidates, we use terrestrial lidar because it can obtain high resolution point cloud in the dark forest. We selected bark texture for the classification criteria, since they clearly represent unique characteristics of each tree and do not change their appearance under seasonable variation and aged deterioration. In this paper, we propose a new method for automatic individual tree species classification based on terrestrial lidar using Convolutional Neural Network (CNN). The key component is the creation step of a depth image which well describe the characteristics of each species from a point cloud. We focus on Japanese cedar and cypress which cover the large part of domestic forest. Our experimental results demonstrate the effectiveness of our proposed method.

  1. A Review of LIDAR Radiometric Processing: From Ad Hoc Intensity Correction to Rigorous Radiometric Calibration

    Directory of Open Access Journals (Sweden)

    Alireza G. Kashani

    2015-11-01

    Full Text Available In addition to precise 3D coordinates, most light detection and ranging (LIDAR systems also record “intensity”, loosely defined as the strength of the backscattered echo for each measured point. To date, LIDAR intensity data have proven beneficial in a wide range of applications because they are related to surface parameters, such as reflectance. While numerous procedures have been introduced in the scientific literature, and even commercial software, to enhance the utility of intensity data through a variety of “normalization”, “correction”, or “calibration” techniques, the current situation is complicated by a lack of standardization, as well as confusing, inconsistent use of terminology. In this paper, we first provide an overview of basic principles of LIDAR intensity measurements and applications utilizing intensity information from terrestrial, airborne topographic, and airborne bathymetric LIDAR. Next, we review effective parameters on intensity measurements, basic theory, and current intensity processing methods. We define terminology adopted from the most commonly-used conventions based on a review of current literature. Finally, we identify topics in need of further research. Ultimately, the presented information helps lay the foundation for future standards and specifications for LIDAR radiometric calibration.

  2. A Review of LIDAR Radiometric Processing: From Ad Hoc Intensity Correction to Rigorous Radiometric Calibration.

    Science.gov (United States)

    Kashani, Alireza G; Olsen, Michael J; Parrish, Christopher E; Wilson, Nicholas

    2015-11-06

    In addition to precise 3D coordinates, most light detection and ranging (LIDAR) systems also record "intensity", loosely defined as the strength of the backscattered echo for each measured point. To date, LIDAR intensity data have proven beneficial in a wide range of applications because they are related to surface parameters, such as reflectance. While numerous procedures have been introduced in the scientific literature, and even commercial software, to enhance the utility of intensity data through a variety of "normalization", "correction", or "calibration" techniques, the current situation is complicated by a lack of standardization, as well as confusing, inconsistent use of terminology. In this paper, we first provide an overview of basic principles of LIDAR intensity measurements and applications utilizing intensity information from terrestrial, airborne topographic, and airborne bathymetric LIDAR. Next, we review effective parameters on intensity measurements, basic theory, and current intensity processing methods. We define terminology adopted from the most commonly-used conventions based on a review of current literature. Finally, we identify topics in need of further research. Ultimately, the presented information helps lay the foundation for future standards and specifications for LIDAR radiometric calibration.

  3. Improving low-relief coastal LiDAR DEMs with hydro-conditioning of fine-scale and artificial drainages

    Directory of Open Access Journals (Sweden)

    Thomas Richard Allen

    2015-11-01

    Full Text Available Improvements in Light Detection and Ranging (LiDAR technology and spatial analysis of high-resolution digital elevation models (DEMs have advanced the accuracy and diversity of applications for coastal hazards and natural resources management. This article presents a concise synthesis of LiDAR analysis for coastal flooding and management applications in low-relief coastal plains and a case study demonstration of a new, efficient drainage mapping algorithm. The impetus for these LiDAR applications follows historic flooding from Hurricane Floyd in 1999, after which the State of North Carolina and the Federal Emergency Management Agency undertook extensive LiDAR data acquisition and technological developments for high-resolution floodplain mapping. An efficient algorithm is outlined for hydro-conditioning bare earth LiDAR DEMs using available US Geological Survey National Hydrography Dataset canal and ditch vectors. The methodology is illustrated in Moyock, North Carolina, for refinement of hydro-conditioning by combines pre-existing bare earth DEMs with spatial analysis of LiDAR point clouds in segmented and buffered ditch and canal networks. The methodology produces improved maps of fine-scale drainage, reduced omission of areal flood inundation, and subwatershed delineations that typify heavily ditched and canalled drainage areas. These preliminary results illustrate the capability of the technique to improve the representation of ditches in DEMs as well as subsequent flow and inundation modeling that could spur further research on low-relief coastal LiDAR applications.

  4. Terrestrial ecosystems and biodiversity

    CSIR Research Space (South Africa)

    Davis-Reddy, Claire

    2017-10-01

    Full Text Available Ecoregions Terrestrial Biomes Protected Areas Climate Risk and Vulnerability: A Handbook for Southern Africa | 75 7.2. Non-climatic drivers of ecosystem change 7.2.1. Land-use change, habitat loss and fragmentation Land-use change and landscape... concentrations of endemic plant and animal species, but these mainly occur in areas that are most threatened by human activity. Diverse terrestrial ecosystems in the region include tropical and sub-tropical forests, deserts, savannas, grasslands, mangroves...

  5. Lidar sounding of volcanic plumes

    Science.gov (United States)

    Fiorani, Luca; Aiuppa, Alessandro; Angelini, Federico; Borelli, Rodolfo; Del Franco, Mario; Murra, Daniele; Pistilli, Marco; Puiu, Adriana; Santoro, Simone

    2013-10-01

    Accurate knowledge of gas composition in volcanic plumes has high scientific and societal value. On the one hand, it gives information on the geophysical processes taking place inside volcanos; on the other hand, it provides alert on possible eruptions. For this reasons, it has been suggested to monitor volcanic plumes by lidar. In particular, one of the aims of the FP7 ERC project BRIDGE is the measurement of CO2 concentration in volcanic gases by differential absorption lidar. This is a very challenging task due to the harsh environment, the narrowness and weakness of the CO2 absorption lines and the difficulty to procure a suitable laser source. This paper, after a review on remote sensing of volcanic plumes, reports on the current progress of the lidar system.

  6. Remote sensing the vulnerability of vegetation in natural terrestrial ecosystems

    Science.gov (United States)

    Alistair M. S. Smith; Crystal A. Kolden; Wade T. Tinkham; Alan F. Talhelm; John D. Marshall; Andrew T. Hudak; Luigi Boschetti; Michael J. Falkowski; Jonathan A. Greenberg; John W. Anderson; Andrew Kliskey; Lilian Alessa; Robert F. Keefe; James R. Gosz

    2014-01-01

    Climate change is altering the species composition, structure, and function of vegetation in natural terrestrial ecosystems. These changes can also impact the essential ecosystem goods and services derived from these ecosystems. Following disturbances, remote-sensing datasets have been used to monitor the disturbance and describe antecedent conditions as a means of...

  7. ALTERNATIVE METHODOLOGIES FOR THE ESTIMATION OF LOCAL POINT DENSITY INDEX: MOVING TOWARDS ADAPTIVE LIDAR DATA PROCESSING

    Directory of Open Access Journals (Sweden)

    Z. Lari

    2012-07-01

    Full Text Available Over the past few years, LiDAR systems have been established as a leading technology for the acquisition of high density point clouds over physical surfaces. These point clouds will be processed for the extraction of geo-spatial information. Local point density is one of the most important properties of the point cloud that highly affects the performance of data processing techniques and the quality of extracted information from these data. Therefore, it is necessary to define a standard methodology for the estimation of local point density indices to be considered for the precise processing of LiDAR data. Current definitions of local point density indices, which only consider the 2D neighbourhood of individual points, are not appropriate for 3D LiDAR data and cannot be applied for laser scans from different platforms. In order to resolve the drawbacks of these methods, this paper proposes several approaches for the estimation of the local point density index which take the 3D relationship among the points and the physical properties of the surfaces they belong to into account. In the simplest approach, an approximate value of the local point density for each point is defined while considering the 3D relationship among the points. In the other approaches, the local point density is estimated by considering the 3D neighbourhood of the point in question and the physical properties of the surface which encloses this point. The physical properties of the surfaces enclosing the LiDAR points are assessed through eigen-value analysis of the 3D neighbourhood of individual points and adaptive cylinder methods. This paper will discuss these approaches and highlight their impact on various LiDAR data processing activities (i.e., neighbourhood definition, region growing, segmentation, boundary detection, and classification. Experimental results from airborne and terrestrial LiDAR data verify the efficacy of considering local point density variation for

  8. Lidar configurations for wind turbine control

    DEFF Research Database (Denmark)

    Mirzaei, Mahmood; Mann, Jakob

    2016-01-01

    Lidar sensors have proved to be very beneficial in the wind energy industry. They can be used for yaw correction, feed-forward pitch control and load verification. However, the current lidars are expensive. One way to reduce the price is to use lidars with few measurement points. Finding the best...... by the lidar is compared against the effective wind speed on a wind turbine rotor both theoretically and through simulations. The study provides some results to choose the best configuration of the lidar with few measurement points....

  9. Calibration of Ground-based Lidar instrument

    DEFF Research Database (Denmark)

    Yordanova, Ginka; Gómez Arranz, Paula

    This report presents the result of the lidar calibration performed for the given Ground-based Lidar at DTU’s test site for large wind turbines at Høvsøre, Denmark. Calibration is here understood as the establishment of a relation between the reference wind speed measurements with measurement...... uncertainties provided by measurement standard and corresponding lidar wind speed indications with associated measurement uncertainties. The lidar calibration concerns the 10 minute mean wind speed measurements. The comparison of the lidar measurements of the wind direction with that from wind vanes...

  10. GLEAM version 3: Global Land Evaporation Datasets and Model

    Science.gov (United States)

    Martens, B.; Miralles, D. G.; Lievens, H.; van der Schalie, R.; de Jeu, R.; Fernandez-Prieto, D.; Verhoest, N.

    2015-12-01

    Terrestrial evaporation links energy, water and carbon cycles over land and is therefore a key variable of the climate system. However, the global-scale magnitude and variability of the flux, and the sensitivity of the underlying physical process to changes in environmental factors, are still poorly understood due to limitations in in situ measurements. As a result, several methods have risen to estimate global patterns of land evaporation from satellite observations. However, these algorithms generally differ in their approach to model evaporation, resulting in large differences in their estimates. One of these methods is GLEAM, the Global Land Evaporation: the Amsterdam Methodology. GLEAM estimates terrestrial evaporation based on daily satellite observations of meteorological variables, vegetation characteristics and soil moisture. Since the publication of the first version of the algorithm (2011), the model has been widely applied to analyse trends in the water cycle and land-atmospheric feedbacks during extreme hydrometeorological events. A third version of the GLEAM global datasets is foreseen by the end of 2015. Given the relevance of having a continuous and reliable record of global-scale evaporation estimates for climate and hydrological research, the establishment of an online data portal to host these data to the public is also foreseen. In this new release of the GLEAM datasets, different components of the model have been updated, with the most significant change being the revision of the data assimilation algorithm. In this presentation, we will highlight the most important changes of the methodology and present three new GLEAM datasets and their validation against in situ observations and an alternative dataset of terrestrial evaporation (ERA-Land). Results of the validation exercise indicate that the magnitude and the spatiotemporal variability of the modelled evaporation agree reasonably well with the estimates of ERA-Land and the in situ

  11. Semiconductor Laser Wind Lidar for Turbine Control

    DEFF Research Database (Denmark)

    Hu, Qi

    This thesis describes an experimentally oriented study of continuous wave (CW) coherent Doppler lidar system design. The main application is remote wind sensing for active wind turbine control using nacelle mounted lidar systems; and the primary focus is to devise an industrial instrument that can...... historical overview within the topic of wind lidar systems. Both the potential and the challenges of an industrialized wind lidar has been addressed here. Furthermore, the basic concept behind the heterodyne detection and a brief overview of the lidar signal processing is explained; and a simple...... investigation of the telescope truncation and lens aberrations is conducted, both numerically and experimentally. It is shown that these parameters dictate the spatial resolution of the lidar system, and have profound impact on the SNR. In this work, an all-semiconductor light source is used in the lidar design...

  12. Turkey Run Landfill Emissions Dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — landfill emissions measurements for the Turkey run landfill in Georgia. This dataset is associated with the following publication: De la Cruz, F., R. Green, G....

  13. Dataset of NRDA emission data

    Data.gov (United States)

    U.S. Environmental Protection Agency — Emissions data from open air oil burns. This dataset is associated with the following publication: Gullett, B., J. Aurell, A. Holder, B. Mitchell, D. Greenwell, M....

  14. Chemical product and function dataset

    Data.gov (United States)

    U.S. Environmental Protection Agency — Merged product weight fraction and chemical function data. This dataset is associated with the following publication: Isaacs , K., M. Goldsmith, P. Egeghy , K....

  15. EXTRACTION OF BUILDING BOUNDARY LINES FROM AIRBORNE LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    Y.-H. Tseng

    2016-10-01

    Full Text Available Building boundary lines are important spatial features that characterize the topographic maps and three-dimensional (3D city models. Airborne LiDAR Point clouds provide adequate 3D spatial information for building boundary mapping. However, information of boundary features contained in point clouds is implicit. This study focuses on developing an automatic algorithm of building boundary line extraction from airborne LiDAR data. In an airborne LiDAR dataset, top surfaces of buildings, such as roofs, tend to have densely distributed points, but vertical surfaces, such as walls, usually have sparsely distributed points or even no points. The intersection lines of roof and wall planes are, therefore, not clearly defined in point clouds. This paper proposes a novel method to extract those boundary lines of building edges. The extracted line features can be used as fundamental data to generate topographic maps of 3D city model for an urban area. The proposed method includes two major process steps. The first step is to extract building boundary points from point clouds. Then the second step is followed to form building boundary line features based on the extracted boundary points. In this step, a line fitting algorithm is developed to improve the edge extraction from LiDAR data. Eight test objects, including 4 simple low buildings and 4 complicated tall buildings, were selected from the buildings in NCKU campus. The test results demonstrate the feasibility of the proposed method in extracting complicate building boundary lines. Some results which are not as good as expected suggest the need of further improvement of the method.

  16. VEHICLE LOCALIZATION BY LIDAR POINT CORRELATION IMPROVED BY CHANGE DETECTION

    Directory of Open Access Journals (Sweden)

    A. Schlichting

    2016-06-01

    Full Text Available LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position and 0.06° (heading, and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

  17. Vehicle Localization by LIDAR Point Correlation Improved by Change Detection

    Science.gov (United States)

    Schlichting, A.; Brenner, C.

    2016-06-01

    LiDAR sensors are proven sensors for accurate vehicle localization. Instead of detecting and matching features in the LiDAR data, we want to use the entire information provided by the scanners. As dynamic objects, like cars, pedestrians or even construction sites could lead to wrong localization results, we use a change detection algorithm to detect these objects in the reference data. If an object occurs in a certain number of measurements at the same position, we mark it and every containing point as static. In the next step, we merge the data of the single measurement epochs to one reference dataset, whereby we only use static points. Further, we also use a classification algorithm to detect trees. For the online localization of the vehicle, we use simulated data of a vertical aligned automotive LiDAR sensor. As we only want to use static objects in this case as well, we use a random forest classifier to detect dynamic scan points online. Since the automotive data is derived from the LiDAR Mobile Mapping System, we are able to use the labelled objects from the reference data generation step to create the training data and further to detect dynamic objects online. The localization then can be done by a point to image correlation method using only static objects. We achieved a localization standard deviation of about 5 cm (position) and 0.06° (heading), and were able to successfully localize the vehicle in about 93 % of the cases along a trajectory of 13 km in Hannover, Germany.

  18. Performance testing of LiDAR exploitation software

    Science.gov (United States)

    Varela-González, M.; González-Jorge, H.; Riveiro, B.; Arias, P.

    2013-04-01

    Mobile LiDAR systems are being used widely in recent years for many applications in the field of geoscience. One of most important limitations of this technology is the large computational requirements involved in data processing. Several software solutions for data processing are available in the market, but users are often unknown about the methodologies to verify their performance accurately. In this work a methodology for LiDAR software performance testing is presented and six different suites are studied: QT Modeler, AutoCAD Civil 3D, Mars 7, Fledermaus, Carlson and TopoDOT (all of them in x64). Results depict as QTModeler, TopoDOT and AutoCAD Civil 3D allow the loading of large datasets, while Fledermaus, Mars7 and Carlson do not achieve these powerful performance. AutoCAD Civil 3D needs large loading time in comparison with the most powerful softwares such as QTModeler and TopoDOT. Carlson suite depicts the poorest results among all the softwares under study, where point clouds larger than 5 million points cannot be loaded and loading time is very large in comparison with the other suites even for the smaller datasets. AutoCAD Civil 3D, Carlson and TopoDOT show more threads than other softwares like QTModeler, Mars7 and Fledermaus.

  19. Terrestrial Analogs to Mars

    Science.gov (United States)

    Farr, T. G.; Arcone, S.; Arvidson, R. W.; Baker, V.; Barlow, N. G.; Beaty, D.; Bell, M. S.; Blankenship, D. D.; Bridges, N.; Briggs, G.; Bulmer, M.; Carsey, F.; Clifford, S. M.; Craddock, R. A.; Dickerson, P. W.; Duxbury, N.; Galford, G. L.; Garvin, J.; Grant, J.; Green, J. R.; Gregg, T. K. P.; Guinness, E.; Hansen, V. L.; Hecht, M. H.; Holt, J.; Howard, A.; Keszthelyi, L. P.; Lee, P.; Lanagan, P. D.; Lentz, R. C. F.; Leverington, D. W.; Marinangeli, L.; Moersch, J. E.; Morris-Smith, P. A.; Mouginis-Mark, P.; Olhoeft, G. R.; Ori, G. G.; Paillou, P.; Reilly, J. F., II; Rice, J. W., Jr.; Robinson, C. A.; Sheridan, M.; Snook, K.; Thomson, B. J.; Watson, K.; Williams, K.; Yoshikawa, K.

    2002-08-01

    It is well recognized that interpretations of Mars must begin with the Earth as a reference. The most successful comparisons have focused on understanding geologic processes on the Earth well enough to extrapolate to Mars' environment. Several facets of terrestrial analog studies have been pursued and are continuing. These studies include field workshops, characterization of terrestrial analog sites, instrument tests, laboratory measurements (including analysis of Martian meteorites), and computer and laboratory modeling. The combination of all these activities allows scientists to constrain the processes operating in specific terrestrial environments and extrapolate how similar processes could affect Mars. The Terrestrial Analogs for Mars Community Panel has considered the following two key questions: (1) How do terrestrial analog studies tie in to the Mars Exploration Payload Assessment Group science questions about life, past climate, and geologic evolution of Mars, and (2) How can future instrumentation be used to address these questions. The panel has considered the issues of data collection, value of field workshops, data archiving, laboratory measurements and modeling, human exploration issues, association with other areas of solar system exploration, and education and public outreach activities.

  20. Complex terrain and wind lidars

    Energy Technology Data Exchange (ETDEWEB)

    Bingoel, F.

    2009-08-15

    This thesis includes the results of a PhD study about complex terrain and wind lidars. The study mostly focuses on hilly and forested areas. Lidars have been used in combination with cups, sonics and vanes, to reach the desired vertical measurement heights. Several experiments are performed in complex terrain sites and the measurements are compared with two different flow models; a linearised flow model LINCOM and specialised forest model SCADIS. In respect to the lidar performance in complex terrain, the results showed that horizontal wind speed errors measured by a conically scanning lidar can be of the order of 3-4% in moderately-complex terrain and up to 10% in complex terrain. The findings were based on experiments involving collocated lidars and meteorological masts, together with flow calculations over the same terrains. The lidar performance was also simulated with the commercial software WAsP Engineering 2.0 and was well predicted except for some sectors where the terrain is particularly steep. Subsequently, two experiments were performed in forested areas; where the measurements are recorded at a location deep-in forest and at the forest edge. Both sites were modelled with flow models and the comparison of the measurement data with the flow model outputs showed that the mean wind speed calculated by LINCOM model was only reliable between 1 and 2 tree height (h) above canopy. The SCADIS model reported better correlation with the measurements in forest up to approx6h. At the forest edge, LINCOM model was used by allocating a slope half-in half out of the forest based on the suggestions of previous studies. The optimum slope angle was reported as 17 deg.. Thus, a suggestion was made to use WAsP Engineering 2.0 for forest edge modelling with known limitations and the applied method. The SCADIS model worked better than the LINCOM model at the forest edge but the model reported closer results to the measurements at upwind than the downwind and this should be

  1. Lidar and Hyperspectral Remote Sensing for the Analysis of Coniferous Biomass Stocks and Fluxes

    Science.gov (United States)

    Halligan, K. Q.; Roberts, D. A.

    2006-12-01

    Airborne lidar and hyperspectral data can improve estimates of aboveground carbon stocks and fluxes through their complimentary responses to vegetation structure and biochemistry. While strong relationships have been demonstrated between lidar-estimated vegetation structural parameters and field data, research is needed to explore the portability of these methods across a range of topographic conditions, disturbance histories, vegetation type and climate. Additionally, research is needed to evaluate contributions of hyperspectral data in refining biomass estimates and determination of fluxes. To address these questions we are a conducting study of lidar and hyperspectral remote sensing data across sites including coniferous forests, broadleaf deciduous forests and a tropical rainforest. Here we focus on a single study site, Yellowstone National Park, where tree heights, stem locations, above ground biomass and basal area were mapped using first-return small-footprint lidar data. A new method using lidar intensity data was developed for separating the terrain and vegetation components in lidar data using a two-scale iterative local minima filter. Resulting Digital Terrain Models (DTM) and Digital Canopy Models (DCM) were then processed to retrieve a diversity of vertical and horizontal structure metrics. Univariate linear models were used to estimate individual tree heights while stepwise linear regression was used to estimate aboveground biomass and basal area. Three small-area field datasets were compared for their utility in model building and validation of vegetation structure parameters. All structural parameters were linearly correlated with lidar-derived metrics, with higher accuracies obtained where field and imagery data were precisely collocated . Initial analysis of hyperspectral data suggests that vegetation health metrics including measures of live and dead vegetation and stress indices may provide good indicators of carbon flux by mapping vegetation

  2. TerraClimate, a high-resolution global dataset of monthly climate and climatic water balance from 1958–2015

    OpenAIRE

    Abatzoglou, John T.; Dobrowski, Solomon Z.; Parks, Sean A.; Hegewisch, Katherine C.

    2018-01-01

    We present TerraClimate, a dataset of high-spatial resolution (1/24°, ~4-km) monthly climate and climatic water balance for global terrestrial surfaces from 1958–2015. TerraClimate uses climatically aided interpolation, combining high-spatial resolution climatological normals from the WorldClim dataset, with coarser resolution time varying (i.e., monthly) data from other sources to produce a monthly dataset of precipitation, maximum and minimum temperature, wind speed, vapor pressure, and sol...

  3. Modeling Forest Biomass and Growth: Coupling Long-Term Inventory and Lidar Data

    Science.gov (United States)

    Babcock, Chad; Finley, Andrew O.; Cook, Bruce D.; Weiskittel, Andrew; Woodall, Christopher W.

    2016-01-01

    Combining spatially-explicit long-term forest inventory and remotely sensed information from Light Detection and Ranging (LiDAR) datasets through statistical models can be a powerful tool for predicting and mapping above-ground biomass (AGB) at a range of geographic scales. We present and examine a novel modeling approach to improve prediction of AGB and estimate AGB growth using LiDAR data. The proposed model accommodates temporal misalignment between field measurements and remotely sensed data-a problem pervasive in such settings-by including multiple time-indexed measurements at plot locations to estimate AGB growth. We pursue a Bayesian modeling framework that allows for appropriately complex parameter associations and uncertainty propagation through to prediction. Specifically, we identify a space-varying coefficients model to predict and map AGB and its associated growth simultaneously. The proposed model is assessed using LiDAR data acquired from NASA Goddard's LiDAR, Hyper-spectral & Thermal imager and field inventory data from the Penobscot Experimental Forest in Bradley, Maine. The proposed model outperformed the time-invariant counterpart models in predictive performance as indicated by a substantial reduction in root mean squared error. The proposed model adequately accounts for temporal misalignment through the estimation of forest AGB growth and accommodates residual spatial dependence. Results from this analysis suggest that future AGB models informed using remotely sensed data, such as LiDAR, may be improved by adapting traditional modeling frameworks to account for temporal misalignment and spatial dependence using random effects.

  4. Modeling Aboveground Biomass in Hulunber Grassland Ecosystem by Using Unmanned Aerial Vehicle Discrete Lidar.

    Science.gov (United States)

    Wang, Dongliang; Xin, Xiaoping; Shao, Quanqin; Brolly, Matthew; Zhu, Zhiliang; Chen, Jin

    2017-01-19

    Accurate canopy structure datasets, including canopy height and fractional cover, are required to monitor aboveground biomass as well as to provide validation data for satellite remote sensing products. In this study, the ability of an unmanned aerial vehicle (UAV) discrete light detection and ranging (lidar) was investigated for modeling both the canopy height and fractional cover in Hulunber grassland ecosystem. The extracted mean canopy height, maximum canopy height, and fractional cover were used to estimate the aboveground biomass. The influences of flight height on lidar estimates were also analyzed. The main findings are: (1) the lidar-derived mean canopy height is the most reasonable predictor of aboveground biomass ( R ² = 0.340, root-mean-square error (RMSE) = 81.89 g·m -2 , and relative error of 14.1%). The improvement of multiple regressions to the R ² and RMSE values is unobvious when adding fractional cover in the regression since the correlation between mean canopy height and fractional cover is high; (2) Flight height has a pronounced effect on the derived fractional cover and details of the lidar data, but the effect is insignificant on the derived canopy height when the flight height is within the range (lidar returns.

  5. The NOAA Dataset Identifier Project

    Science.gov (United States)

    de la Beaujardiere, J.; Mccullough, H.; Casey, K. S.

    2013-12-01

    The US National Oceanic and Atmospheric Administration (NOAA) initiated a project in 2013 to assign persistent identifiers to datasets archived at NOAA and to create informational landing pages about those datasets. The goals of this project are to enable the citation of datasets used in products and results in order to help provide credit to data producers, to support traceability and reproducibility, and to enable tracking of data usage and impact. A secondary goal is to encourage the submission of datasets for long-term preservation, because only archived datasets will be eligible for a NOAA-issued identifier. A team was formed with representatives from the National Geophysical, Oceanographic, and Climatic Data Centers (NGDC, NODC, NCDC) to resolve questions including which identifier scheme to use (answer: Digital Object Identifier - DOI), whether or not to embed semantics in identifiers (no), the level of granularity at which to assign identifiers (as coarsely as reasonable), how to handle ongoing time-series data (do not break into chunks), creation mechanism for the landing page (stylesheet from formal metadata record preferred), and others. Decisions made and implementation experience gained will inform the writing of a Data Citation Procedural Directive to be issued by the Environmental Data Management Committee in 2014. Several identifiers have been issued as of July 2013, with more on the way. NOAA is now reporting the number as a metric to federal Open Government initiatives. This paper will provide further details and status of the project.

  6. Terrestrial and extraterrestrial fullerenes

    Energy Technology Data Exchange (ETDEWEB)

    Heymann, D.; Jenneskens, L.W.; Jehlicka, J; Koper, C.; Vlietstra, E. [Rice Univ, Houston, TX (United States). Dept. of Earth Science

    2003-07-01

    This paper reviews reports of occurrences of fullerenes in circumstellar media, interstellar media, meteorites, interplanetary dust particles (IDPs), lunar rocks, hard terrestrial rocks from Shunga (Russia), Sudbury (Canada) and Mitov (Czech Republic), coal, terrestrial sediments from the Cretaceous-Tertiary-Boundary and Pennian-Triassic-Boundary, fulgurite, ink sticks, dinosaur eggs, and a tree char. The occurrences are discussed in the context of known and postulated processes of fullerene formation, including the suggestion that some natural fullerenes might have formed from biological (algal) remains.

  7. Remote Sensing of Aerosol Backscatter and Earth Surface Targets By Use of An Airborne Focused Continuous Wave CO2 Doppler Lidar Over Western North America

    Science.gov (United States)

    Jarzembski, Maurice A.; Srivastava, Vandana; Goodman, H. Michael (Technical Monitor)

    2000-01-01

    Airborne lidar systems are used to determine wind velocity and to measure aerosol or cloud backscatter variability. Atmospheric aerosols, being affected by local and regional sources, show tremendous variability. Continuous wave (cw) lidar can obtain detailed aerosol loading with unprecedented high resolution (3 sec) and sensitivity (1 mg/cubic meter) as was done during the 1995 NASA Multi-center Airborne Coherent Atmospheric Wind Sensor (MACAWS) mission over western North America and the Pacific Ocean. Backscatter variability was measured at a 9.1 micron wavelength cw focused CO2 Doppler lidar for approximately 52 flight hours, covering an equivalent horizontal distance of approximately 30,000 km in the troposphere. Some quasi-vertical backscatter profiles were also obtained during various ascents and descents at altitudes that ranged from approximately 0.1 to 12 km. Similarities and differences for aerosol loading over land and ocean were observed. Mid-tropospheric aerosol backscatter background mode was approximately 6 x 10(exp -11)/ms/r, consistent with previous lidar datasets. While these atmospheric measurements were made, the lidar also retrieved a distinct backscatter signal from the Earth's surface from the unfocused part of the focused cw lidar beam during aircraft rolls. Atmospheric backscatter can be highly variable both spatially and temporally, whereas, Earth-surface backscatter is relatively much less variant and can be quite predictable. Therefore, routine atmospheric backscatter measurements by an airborne lidar also give Earth surface backscatter which can allow for investigating the Earth terrain. In the case where the Earth's surface backscatter is coming from a well-known and fairly uniform region, then it can potentially offer lidar calibration opportunities during flight. These Earth surface measurements over varying Californian terrain during the mission were compared with laboratory backscatter measurements using the same lidar of various

  8. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Tulalip Partnership

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In October 2012, WSI (Watershed Sciences, Inc.) was contracted by the Puget Sound LiDAR Consortium (PSLC)to collect Light Detection and Ranging (LiDAR) data on a...

  9. 2014 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Willapa Valley (Delivery 1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In January, 2014 WSI, a Quantum Spatial (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data...

  10. 2013 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Saddle Mountain

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In October 2013, WSI, a Quantum Spatial Company (QSI), was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR) data...

  11. 2015 Puget Sound LiDAR Consortium (PSLC) LiDAR: WA DNR Lands (P2)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In June 2014, WSI, a Quantum Spatial Inc. (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  12. 2015 Puget Sound LiDAR Consortium (PSLC) LiDAR: WA DNR Lands (P1)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — In June 2014, WSI, a Quantum Spatial Inc. (QSI) company, was contracted by the Puget Sound LiDAR Consortium (PSLC) to collect Light Detection and Ranging (LiDAR)...

  13. 2012 MEGIS Topographic Lidar: Statewide Lidar Project Area 1 (Aroostook), Maine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

  14. 2009 Puget Sound LiDAR Consortium (PSLC) Topographic LiDAR: Lewis County, Washington

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WSI) collected Light Detection and Ranging (LiDAR) data for the Lewis County survey area for the Puget Sound LiDAR Consortium. This data...

  15. 2012 MEGIS Topographic Lidar: Statewide Lidar Project Areas 2 and 3 (Mid-Coastal Cleanup), Maine

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

  16. Applying a weighted random forests method to extract karst sinkholes from LiDAR data

    Science.gov (United States)

    Zhu, Junfeng; Pierskalla, William P.

    2016-02-01

    Detailed mapping of sinkholes provides critical information for mitigating sinkhole hazards and understanding groundwater and surface water interactions in karst terrains. LiDAR (Light Detection and Ranging) measures the earth's surface in high-resolution and high-density and has shown great potentials to drastically improve locating and delineating sinkholes. However, processing LiDAR data to extract sinkholes requires separating sinkholes from other depressions, which can be laborious because of the sheer number of the depressions commonly generated from LiDAR data. In this study, we applied the random forests, a machine learning method, to automatically separate sinkholes from other depressions in a karst region in central Kentucky. The sinkhole-extraction random forest was grown on a training dataset built from an area where LiDAR-derived depressions were manually classified through a visual inspection and field verification process. Based on the geometry of depressions, as well as natural and human factors related to sinkholes, 11 parameters were selected as predictive variables to form the dataset. Because the training dataset was imbalanced with the majority of depressions being non-sinkholes, a weighted random forests method was used to improve the accuracy of predicting sinkholes. The weighted random forest achieved an average accuracy of 89.95% for the training dataset, demonstrating that the random forest can be an effective sinkhole classifier. Testing of the random forest in another area, however, resulted in moderate success with an average accuracy rate of 73.96%. This study suggests that an automatic sinkhole extraction procedure like the random forest classifier can significantly reduce time and labor costs and makes its more tractable to map sinkholes using LiDAR data for large areas. However, the random forests method cannot totally replace manual procedures, such as visual inspection and field verification.

  17. The Harvard organic photovoltaic dataset.

    Science.gov (United States)

    Lopez, Steven A; Pyzer-Knapp, Edward O; Simm, Gregor N; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R; Hachmann, Johannes; Aspuru-Guzik, Alán

    2016-09-27

    The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications.

  18. The Harvard organic photovoltaic dataset

    Science.gov (United States)

    Lopez, Steven A.; Pyzer-Knapp, Edward O.; Simm, Gregor N.; Lutzow, Trevor; Li, Kewei; Seress, Laszlo R.; Hachmann, Johannes; Aspuru-Guzik, Alán

    2016-01-01

    The Harvard Organic Photovoltaic Dataset (HOPV15) presented in this work is a collation of experimental photovoltaic data from the literature, and corresponding quantum-chemical calculations performed over a range of conformers, each with quantum chemical results using a variety of density functionals and basis sets. It is anticipated that this dataset will be of use in both relating electronic structure calculations to experimental observations through the generation of calibration schemes, as well as for the creation of new semi-empirical methods and the benchmarking of current and future model chemistries for organic electronic applications. PMID:27676312

  19. Geotechnical applications of LiDAR pertaining to geomechanical evaluation and hazard identification

    Science.gov (United States)

    Lato, Matthew J.

    Natural hazards related to ground movement that directly affect the safety of motorists and highway infrastructure include, but are not limited to, rockfalls, rockslides, debris flows, and landslides. This thesis specifically deals with the evaluation of rockfall hazards through the evaluation of LiDAR data. Light Detection And Ranging (LiDAR) is an imaging technology that can be used to delineate and evaluate geomechanically-controlled hazards. LiDAR has been adopted to conduct hazard evaluations pertaining to rockfall, rock-avalanches, debris flows, and landslides. Characteristics of LiDAR surveying, such as rapid data acquisition rates, mobile data collection, and high data densities, pose problems to traditional CAD or GIS-based mapping methods. New analyses methods, including tools specifically oriented to geomechanical analyses, are needed. The research completed in this thesis supports development of new methods, including improved survey techniques, innovative software workflows, and processing algorithms to aid in the detection and evaluation of geomechanically controlled rockfall hazards. The scientific research conducted between the years of 2006-2010, as presented in this thesis, are divided into five chapters, each of which has been published by or is under review by an international journal. The five research foci are: (i) geomechanical feature extraction and analysis using LiDAR data in active mining environments; (ii) engineered monitoring of rockfall hazards along transportation corridors: using mobile terrestrial LiDAR; (iii) optimization of LiDAR scanning and processing for automated structural evaluation of discontinuities in rockmasses; (iv) location orientation bias when using static LiDAR data for geomechanical analysis; and (v) evaluating roadside rockmasses for rockfall hazards from LiDAR data: optimizing data collection and processing protocols. The research conducted pertaining to this thesis has direct and significant implications with

  20. Histories of terrestrial planets

    International Nuclear Information System (INIS)

    Benes, K.

    1981-01-01

    The uneven historical development of terrestrial planets - Mercury, Venus, Earth, Moon and Mars - is probably due to the differences in their size, weight and rotational dynamics in association with the internal planet structure, their distance from the Sun, etc. A systematic study of extraterrestrial planets showed that the time span of internal activity was not the same for all bodies. It is assumed that the initial history of all terrestrial planets was marked with catastrophic events connected with the overall dynamic development of the solar system. In view of the fact that the cores of small terrestrial bodies cooled quicker, their geological development almost stagnated after two or three thousand million years. This is what probably happened to the Mercury and the Moon as well as the Mars. Therefore, traces of previous catastrophic events were preserved on the surface of the planets. On the other hand, the Earth is the most metamorphosed terrestrial planet and compared to the other planets appears to be atypical. Its biosphere is significantly developed as well as the other shell components, its hydrosphere and atmosphere, and its crust is considerably differentiated. (J.P.)

  1. Terrestrial planet formation.

    Science.gov (United States)

    Righter, K; O'Brien, D P

    2011-11-29

    Advances in our understanding of terrestrial planet formation have come from a multidisciplinary approach. Studies of the ages and compositions of primitive meteorites with compositions similar to the Sun have helped to constrain the nature of the building blocks of planets. This information helps to guide numerical models for the three stages of planet formation from dust to planetesimals (~10(6) y), followed by planetesimals to embryos (lunar to Mars-sized objects; few 10(6) y), and finally embryos to planets (10(7)-10(8) y). Defining the role of turbulence in the early nebula is a key to understanding the growth of solids larger than meter size. The initiation of runaway growth of embryos from planetesimals ultimately leads to the growth of large terrestrial planets via large impacts. Dynamical models can produce inner Solar System configurations that closely resemble our Solar System, especially when the orbital effects of large planets (Jupiter and Saturn) and damping mechanisms, such as gas drag, are included. Experimental studies of terrestrial planet interiors provide additional constraints on the conditions of differentiation and, therefore, origin. A more complete understanding of terrestrial planet formation might be possible via a combination of chemical and physical modeling, as well as obtaining samples and new geophysical data from other planets (Venus, Mars, or Mercury) and asteroids.

  2. Radionuclides in terrestrial ecosystems

    International Nuclear Information System (INIS)

    Bocock, K.L.

    1981-01-01

    This report summarizes information on the distribution and movement of radionuclides in semi-natural terrestrial ecosystems in north-west England with particular emphasis on inputs to, and outputs from ecosystems; on plant and soil aspects; and on radionuclides in fallout and in discharges by the nuclear industry. (author)

  3. The OptD-multi method in LiDAR processing

    International Nuclear Information System (INIS)

    Błaszczak-Bąk, Wioleta; Sobieraj-Żłobińska, Anna; Kowalik, Michał

    2017-01-01

    New and constantly developing technology for acquiring spatial data, such as LiDAR (light detection and ranging), is a source for large volume of data. However, such amount of data is not always needed for developing the most popular LiDAR products: digital terrain model (DTM) or digital surface model. Therefore, in many cases, the number of contained points are reduced in the pre-processing stage. The degree of reduction is determined by the algorithm used, which should enable the user to obtain a dataset appropriate and optimal for the planned purpose. The aim of this article is to propose a new Optimum Dataset method (OptD method) in the processing of LiDAR point clouds. The OptD method can reduce the number of points in a dataset for the specified optimization criteria concerning the characteristics of generated DTM. The OptD method can be used in two variants: OptD-single (one criterion for optimization) and OptD-multi (two or more optimization criteria). The OptD-single method has been thoroughly tested and presented by Błaszczak-Bąk (2016 Acta Geodyn. Geomater . 13/4 379–86). In this paper the authors discussed the OptD-multi method. (paper)

  4. Evaluation of landslide susceptibility mapping techniques using lidar-derived conditioning factors (Oregon case study

    Directory of Open Access Journals (Sweden)

    Rubini Mahalingam

    2016-11-01

    Full Text Available Landslides are a significant geohazard, which frequently result in significant human, infrastructure, and economic losses. Landslide susceptibility mapping using GIS and remote sensing can help communities prepare for these damaging events. Current mapping efforts utilize a wide variety of techniques and consider multiple factors. Unfortunately, each study is relatively independent of others in the applied technique and factors considered, resulting in inconsistencies. Further, input data quality often varies in terms of source, data collection, and generation, leading to uncertainty. This paper investigates if lidar-derived data-sets (slope, slope roughness, terrain roughness, stream power index, and compound topographic index can be used for predictive mapping without other landslide conditioning factors. This paper also assesses the differences in landslide susceptibility mapping using several, widely used statistical techniques. Landslide susceptibility maps were produced from the aforementioned lidar-derived data-sets for a small study area in Oregon using six representative statistical techniques. Most notably, results show that only a few factors were necessary to produce satisfactory maps with high predictive capability (area under the curve >0.7. The sole use of lidar digital elevation models and their derivatives can be used for landslide mapping using most statistical techniques without requiring additional detailed data-sets that are often difficult to obtain or of lower quality.

  5. Lidar investigations of atmospheric aerosols over Sofia

    International Nuclear Information System (INIS)

    Dreischuh, T.; Deleva, A.; Peshev, Z.; Grigorov, I.; Kolarov, G.; Stoyanov, D.

    2016-01-01

    An overview is given of the laser remote sensing of atmospheric aerosols and related processes over the Sofia area performed in the Institute of Electronics, Bulgarian Academy of Sciences, during the last three years. Results from lidar investigations of the optical characteristics of atmospheric aerosols obtained in the frame of the European Aerosol Research Lidar Network, as well as from the lidar mapping of near-surface aerosol fields for remote monitoring of atmospheric pollutants are presented and discussed in this paper.

  6. Lidar data used in the COFIN project

    DEFF Research Database (Denmark)

    Ejsing Jørgensen, Hans; Nielsen, Morten

    1999-01-01

    This report presents the Lidar data used in the COFIN project. The Lidar data have been obtained from several ground level dispersion experiments over flat and complex terrain. The method for treating the data and the conditons under which the data wereobtained are described in detail. Finally we...... describe the Tools to extract and visualize the Lidar data. Data, report, and visualisation tools are available on the Risø FTP server....

  7. NAMMA LIDAR ATMOSPHERIC SENSING EXPERIMENT (LASE) V1

    Data.gov (United States)

    National Aeronautics and Space Administration — NASA's Lidar Atmospheric Sensing Experiment (LASE) system using the DIAL (Differential Absorption Lidar) system was operated during the NASA African Monsoon...

  8. Systematic variations in multi-spectral lidar representations of canopy height profiles and gap probability

    Science.gov (United States)

    Chasmer, L.; Hopkinson, C.; Gynan, C.; Mahoney, C.; Sitar, M.

    2015-12-01

    Airborne and terrestrial lidar are increasingly used in forest attribute modeling for carbon, ecosystem and resource monitoring. The near infra-red wavelength at 1064nm has been utilised most in airborne applications due to, for example, diode manufacture costs, surface reflectance and eye safety. Foliage reflects well at 1064nm and most of the literature on airborne lidar forest structure is based on data from this wavelength. However, lidar systems also operate at wavelengths further from the visible spectrum (e.g. 1550nm) for eye safety reasons. This corresponds to a water absorption band and can be sensitive to attenuation if surfaces contain moisture. Alternatively, some systems operate in the visible range (e.g. 532nm) for specialised applications requiring simultaneous mapping of terrestrial and bathymetric surfaces. All these wavelengths provide analogous 3D canopy structure reconstructions and thus offer the potential to be combined for spatial comparisons or temporal monitoring. However, a systematic comparison of wavelength-dependent foliage profile and gap probability (index of transmittance) is needed. Here we report on two multispectral lidar missions carried out in 2013 and 2015 over conifer, deciduous and mixed stands in Ontario, Canada. The first used separate lidar sensors acquiring comparable data at three wavelengths, while the second used a single sensor with 3 integrated laser systems. In both cases, wavelenegths sampled were 532nm, 1064nm and 1550nm. The experiment revealed significant differences in proportions of returns at ground level, the vertical foliage distribution and gap probability across wavelengths. Canopy attenuation was greatest at 532nm due to photosynthetic plant tissue absorption. Relative to 1064nm, foliage was systematically undersampled at the 10% to 60% height percentiles at both 1550nm and 532nm (this was confirmed with coincident terrestrial lidar data). When using all returns to calculate gap probability, all

  9. Querying Large Biological Network Datasets

    Science.gov (United States)

    Gulsoy, Gunhan

    2013-01-01

    New experimental methods has resulted in increasing amount of genetic interaction data to be generated every day. Biological networks are used to store genetic interaction data gathered. Increasing amount of data available requires fast large scale analysis methods. Therefore, we address the problem of querying large biological network datasets.…

  10. Fluxnet Synthesis Dataset Collaboration Infrastructure

    Energy Technology Data Exchange (ETDEWEB)

    Agarwal, Deborah A. [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Humphrey, Marty [Univ. of Virginia, Charlottesville, VA (United States); van Ingen, Catharine [Microsoft. San Francisco, CA (United States); Beekwilder, Norm [Univ. of Virginia, Charlottesville, VA (United States); Goode, Monte [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Jackson, Keith [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Rodriguez, Matt [Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Weber, Robin [Univ. of California, Berkeley, CA (United States)

    2008-02-06

    The Fluxnet synthesis dataset originally compiled for the La Thuile workshop contained approximately 600 site years. Since the workshop, several additional site years have been added and the dataset now contains over 920 site years from over 240 sites. A data refresh update is expected to increase those numbers in the next few months. The ancillary data describing the sites continues to evolve as well. There are on the order of 120 site contacts and 60proposals have been approved to use thedata. These proposals involve around 120 researchers. The size and complexity of the dataset and collaboration has led to a new approach to providing access to the data and collaboration support and the support team attended the workshop and worked closely with the attendees and the Fluxnet project office to define the requirements for the support infrastructure. As a result of this effort, a new website (http://www.fluxdata.org) has been created to provide access to the Fluxnet synthesis dataset. This new web site is based on a scientific data server which enables browsing of the data on-line, data download, and version tracking. We leverage database and data analysis tools such as OLAP data cubes and web reports to enable browser and Excel pivot table access to the data.

  11. Break Lines, This data was produced for the USGS according to specific project requirements. The Lidar derived breaklines cover Somerset County and the Western portion of Wicomico County, Maryland. Inland streams, rivers, lakes, ponds and tidal features are present., Published in 2012, Not Applicable scale, Eastern Shore Regional GIS Cooperative.

    Data.gov (United States)

    NSGIC Regional | GIS Inventory — Break Lines dataset current as of 2012. This data was produced for the USGS according to specific project requirements. The Lidar derived breaklines cover Somerset...

  12. Contours, 2 foot contours automatically generated from 2008 LIDAR for the purpose of supporting FEMA floodplain mapping. Limited manual editing, breaklines for waterbodies greater than 5 acres created and use.10' index contours labeled., Published in 2008, 1:1200 (1in=100ft) scale, City of Portage Government.

    Data.gov (United States)

    NSGIC Local Govt | GIS Inventory — Contours dataset current as of 2008. 2 foot contours automatically generated from 2008 LIDAR for the purpose of supporting FEMA floodplain mapping. Limited manual...

  13. SAR and LIDAR fusion: experiments and applications

    Science.gov (United States)

    Edwards, Matthew C.; Zaugg, Evan C.; Bradley, Joshua P.; Bowden, Ryan D.

    2013-05-01

    In recent years ARTEMIS, Inc. has developed a series of compact, versatile Synthetic Aperture Radar (SAR) systems which have been operated on a variety of small manned and unmanned aircraft. The multi-frequency-band SlimSAR has demonstrated a variety of capabilities including maritime and littoral target detection, ground moving target indication, polarimetry, interferometry, change detection, and foliage penetration. ARTEMIS also continues to build upon the radar's capabilities through fusion with other sensors, such as electro-optical and infrared camera gimbals and light detection and ranging (LIDAR) devices. In this paper we focus on experiments and applications employing SAR and LIDAR fusion. LIDAR is similar to radar in that it transmits a signal which, after being reflected or scattered by a target area, is recorded by the sensor. The differences are that a LIDAR uses a laser as a transmitter and optical sensors as a receiver, and the wavelengths used exhibit a very different scattering phenomenology than the microwaves used in radar, making SAR and LIDAR good complementary technologies. LIDAR is used in many applications including agriculture, archeology, geo-science, and surveying. Some typical data products include digital elevation maps of a target area and features and shapes extracted from the data. A set of experiments conducted to demonstrate the fusion of SAR and LIDAR data include a LIDAR DEM used in accurately processing the SAR data of a high relief area (mountainous, urban). Also, feature extraction is used in improving geolocation accuracy of the SAR and LIDAR data.

  14. First Airborne IPDA Lidar Measurements of Methane and Carbon Dioxide Applying the DLR Greenhouse Gas Sounder CHARM-F

    Science.gov (United States)

    Amediek, A.; Ehret, G.; Fix, A.; Wirth, M.; Quatrevalet, M.; Büdenbender, C.; Kiemle, C.; Loehring, J.; Gerbig, C.

    2015-12-01

    First airborne measurement using CHARM-F, the four-wavelengths lidar for simultaneous soundings of atmospheric CO2 and CH4, were performed in Spring 2015 onboard the German research aircraft HALO. The lidar is designed in the IPDA (integrated path differential absorption) configuration using short double pulses, which gives column averaged gas mixing ratios between aircraft and ground. HALO's maximum flight altitude of 15 km and special features of the lidar, such as a relatively large laser ground spot, enable the CHARM-F system to be an airborne demonstrator for future spaceborne greenhouse gas lidars. Due to a high technological conformity this applies in particular to the French-German satellite mission MERLIN, the spaceborne methane IPDA lidar. The successfully completed flight measurements provide a valuable dataset, which supports the retrieval algorithm development for MERLIN notably. The flights covered different ground cover types, different orography types as well as the sea. Additionally, we captured different cloud conditions, at which the broken cloud case is a matter of particular interest. This dataset allows detailed analyses of measurement sensitivities, general studies on the IPDA principle and on technical details of the system. These activities are supported by another instrument onboard: a cavity ring down spectrometer, providing in-situ data of carbon dioxide, methane and water vapor with high accuracy and precision, which is ideal for validation purposes of the lidar. Additionally the onboard instrumentation of HALO gives information about pressure and temperature for cross-checking the ECMWF data, which are intended to be used for calculating the weighting function, the key quantity for the retrieval of gas column mixing ratios from the measured gas optical depths. In combination with dedicated descents into the boundary layer and subsequent ascents, a self-contained dataset for characterizations of CHARM-F is available.

  15. Three-dimension imaging lidar

    Science.gov (United States)

    Degnan, John J. (Inventor)

    2007-01-01

    This invention is directed to a 3-dimensional imaging lidar, which utilizes modest power kHz rate lasers, array detectors, photon-counting multi-channel timing receivers, and dual wedge optical scanners with transmitter point-ahead correction to provide contiguous high spatial resolution mapping of surface features including ground, water, man-made objects, vegetation and submerged surfaces from an aircraft or a spacecraft.

  16. High Spectral Resolution Lidar and MPLNET Micro Pulse Lidar Aerosol Optical Property Retrieval Intercomparison During the 2012 7-SEAS Field Campaign at Singapore

    Science.gov (United States)

    Lolli, Simone; Welton, Ellsworth J.; Campbell, James R.; Eloranta, Edwin; Holben, Brent N.; Chew, Boon Ning; Salinas, Santo V.

    2014-01-01

    From August 2012 to February 2013 a High Resolution Spectral Lidar (HSRL; 532 nm) was deployed at that National University of Singapore near a NASA Micro Pulse Lidar NETwork (MPLNET; 527 nm) site. A primary objective of the MPLNET lidar project is the production and dissemination of reliable Level 1 measurements and Level 2 retrieval products. This paper characterizes and quantifies error in Level 2 aerosol optical property retrievals conducted through inversion techniques that derive backscattering and extinction coefficients from MPLNET elastic single-wavelength datasets. MPLNET Level 2 retrievals for aerosol optical depth and extinction/backscatter coefficient profiles are compared with corresponding HSRL datasets, for which the instrument collects direct measurements of each using a unique optical configuration that segregates aerosol and cloud backscattered signal from molecular signal. The intercomparison is performed, and error matrices reported, for lower (0-5km) and the upper (>5km) troposphere, respectively, to distinguish uncertainties observed within and above the MPLNET instrument optical overlap regime.

  17. KML-Based Access and Visualization of High Resolution LiDAR Topography

    Science.gov (United States)

    Crosby, C. J.; Blair, J. L.; Nandigam, V.; Memon, A.; Baru, C.; Arrowsmith, J. R.

    2008-12-01

    Over the past decade, there has been dramatic growth in the acquisition of LiDAR (Light Detection And Ranging) high-resolution topographic data for earth science studies. Capable of providing digital elevation models (DEMs) more than an order of magnitude higher resolution than those currently available, LiDAR data allow earth scientists to study the processes that contribute to landscape evolution at resolutions not previously possible yet essential for their appropriate representation. These datasets also have significant implications for earth science education and outreach because they provide an accurate representation of landforms and geologic hazards. Unfortunately, the massive volume of data produced by LiDAR mapping technology can be a barrier to their use. To make these data available to a larger user community, we have been exploring the use of Keyhole Markup Language (KML) and Google Earth to provide access to LiDAR data products and visualizations. LiDAR digital elevation models are typically delivered in a tiled format that lends itself well to a KML-based distribution system. For LiDAR datasets hosted in the GEON OpenTopography Portal (www.opentopography.org) we have developed KML files that show the extent of available LiDAR DEMs and provide direct access to the data products. Users interact with these KML files to explore the extent of the available data and are able to select DEMs that correspond to their area of interest. Selection of a tile loads a download that the user can then save locally for analysis in their software of choice. The GEON topography system also has tools available that allow users to generate custom DEMs from LiDAR point cloud data. This system is powerful because it enables users to access massive volumes of raw LiDAR data and to produce DEM products that are optimized to their science applications. We have developed a web service that converts the custom DEM models produced by the system to a hillshade that is delivered to

  18. New Visualization Techniques to Analyze Ultra-High Resolution Four-dimensional Surface Deformation Imagery Collected With Ground-based Tripod LiDAR

    Science.gov (United States)

    Kreylos, O.; Bawden, G. W.; Kellogg, L. H.

    2005-12-01

    We are developing a visualization application to display and interact with very large (tens of millions of points) four-dimensional point position datasets in an immersive environment such that point groups from repeated Tripod LiDAR (Light Detection And Ranging) surveys can be selected, measured, and analyzed for land surface change using 3D~interactions. Ground-based tripod or terrestrial LiDAR (T-LiDAR) can remotely collect ultra-high resolution (centimeter to subcentimeter) and accurate (± 4 mm) digital imagery of the scanned target, and at scanning rates of 2,000 (x, y, z, i) (3D~position~+ intensity) points per second over 7~million points can be collected for a given target in an hour. We developed a multiresolution point set data representation based on octrees to display large T-LiDAR point cloud datasets at the frame rates required for immersive display (between 60 Hz and 120 Hz). Data inside an observer's region of interest is shown in full detail, whereas data outside the field of view or far away from the observer is shown at reduced resolution to provide context. Using 3D input devices at the University of California Davis KeckCAVES, users can navigate large point sets, accurately select related point groups in two or more point sets by sweeping regions of space, and guide the software in deriving positional information from point groups to compute their displacements between surveys. We used this new software application in the KeckCAVES to analyze 4D T-LiDAR imagery from the June~1, 2005 Blue Bird Canyon landslide in Laguna Beach, southern California. Over 50~million (x, y, z, i) data points were collected between 10 and 21~days after the landslide to evaluate T-LiDAR as a natural hazards response tool. The visualization of the T-LiDAR scans within the immediate landslide showed minor readjustments in the weeks following the primarily landslide with no observable continued motion on the primary landslide. Recovery and demolition efforts across the

  19. Airborne lidar-based estimates of tropical forest structure in complex terrain: opportunities and trade-offs for REDD+

    Science.gov (United States)

    Leitold, Veronika; Keller, Michael; Morton, Douglas C; Cook, Bruce D; Shimabukuro, Yosio E

    2015-12-01

    Carbon stocks and fluxes in tropical forests remain large sources of uncertainty in the global carbon budget. Airborne lidar remote sensing is a powerful tool for estimating aboveground biomass, provided that lidar measurements penetrate dense forest vegetation to generate accurate estimates of surface topography and canopy heights. Tropical forest areas with complex topography present a challenge for lidar remote sensing. We compared digital terrain models (DTM) derived from airborne lidar data from a mountainous region of the Atlantic Forest in Brazil to 35 ground control points measured with survey grade GNSS receivers. The terrain model generated from full-density (~20 returns m -2 ) data was highly accurate (mean signed error of 0.19 ± 0.97 m), while those derived from reduced-density datasets (8 m -2 , 4 m -2 , 2 m -2 and 1 m -2 ) were increasingly less accurate. Canopy heights calculated from reduced-density lidar data declined as data density decreased due to the inability to accurately model the terrain surface. For lidar return densities below 4 m -2 , the bias in height estimates translated into errors of 80-125 Mg ha -1 in predicted aboveground biomass. Given the growing emphasis on the use of airborne lidar for forest management, carbon monitoring, and conservation efforts, the results of this study highlight the importance of careful survey planning and consistent sampling for accurate quantification of aboveground biomass stocks and dynamics. Approaches that rely primarily on canopy height to estimate aboveground biomass are sensitive to DTM errors from variability in lidar sampling density.

  20. Voxel-Based Spatial Filtering Method for Canopy Height Retrieval from Airborne Single-Photon Lidar

    Directory of Open Access Journals (Sweden)

    Hao Tang

    2016-09-01

    Full Text Available Airborne single-photon lidar (SPL is a new technology that holds considerable potential for forest structure and carbon monitoring at large spatial scales because it acquires 3D measurements of vegetation faster and more efficiently than conventional lidar instruments. However, SPL instruments use green wavelength (532 nm lasers, which are sensitive to background solar noise, and therefore SPL point clouds require more elaborate noise filtering than other lidar instruments to determine canopy heights, particularly in daytime acquisitions. Histogram-based aggregation is a commonly used approach for removing noise from photon counting lidar data, but it reduces the resolution of the dataset. Here we present an alternate voxel-based spatial filtering method that filters noise points efficiently while largely preserving the spatial integrity of SPL data. We develop and test our algorithms on an experimental SPL dataset acquired over Garrett County in Maryland, USA. We then compare canopy attributes retrieved using our new algorithm with those obtained from the conventional histogram binning approach. Our results show that canopy heights derived using the new algorithm have a strong agreement with field-measured heights (r2 = 0.69, bias = 0.42 m, RMSE = 4.85 m and discrete return lidar heights (r2 = 0.94, bias = 1.07 m, RMSE = 2.42 m. Results are consistently better than height accuracies from the histogram method (field data: r2 = 0.59, bias = 0.00 m, RMSE = 6.25 m; DRL: r2 = 0.78, bias = −0.06 m and RMSE = 4.88 m. Furthermore, we find that the spatial-filtering method retains fine-scale canopy structure detail and has lower errors over steep slopes. We therefore believe that automated spatial filtering algorithms such as the one presented here can support large-scale, canopy structure mapping from airborne SPL data.

  1. Working group 4: Terrestrial

    International Nuclear Information System (INIS)

    Anon.

    1993-01-01

    A working group at a Canada/USA symposium on climate change and the Arctic identified major concerns and issues related to terrestrial resources. The group examined the need for, and the means of, involving resource managers and users at local and territorial levels in the process of identifying and examining the impacts and consequences of climatic change. Climatic change will be important to the Arctic because of the magnitude of the change projected for northern latitudes; the apparent sensitivity of its terrestrial ecosystems, natural resources, and human support systems; and the dependence of the social, cultural, and economic welfare of Arctic communities, businesses, and industries on the health and quality of their environment. Impacts of climatic change on the physical, biological, and associated socio-economic environment are outlined. Gaps in knowledge needed to quantify these impacts are listed along with their relationships with resource management. Finally, potential actions for response and adaptation are presented

  2. Phytopharmacology of Tribulus terrestris.

    Science.gov (United States)

    Shahid, M; Riaz, M; Talpur, M M A; Pirzada, T

    2016-01-01

    Tribulus terrestris is an annual herb which belongs to the Zygophyllaceae family. This plant has been used in traditional medicine for the treatment of various diseases for hundreds of decades. The main active phytoconstituents of this plant include flavonoids, alkaloids, saponins, lignin, amides, and glycosides. The plant parts have different pharmacological activities including aphrodisiac, antiinflammatory, antimicrobial and antioxidant potential. T. terrestris is most often used for infertility and loss of libido. It has potential application as immunomodulatory, hepatoprotective, hypolipidemic, anthelmintic and anticarcinogenic activities. The aim of the present article is to create a database for further investigation of the phytopharmacological properties of this plant to promote research. This study will definitely help to confirm its traditional use along with its value-added utility, eventually leading to higher revenues from the plant.

  3. Terrestrial plant methane production

    DEFF Research Database (Denmark)

    Mikkelsen, Teis Nørgaard; Bruhn, Dan; Møller, Ian M.

    We evaluate all experimental work published on the phenomenon of aerobic methane (CH4) generation in terrestrial plants. We conclude that the phenomenon is true. Four stimulating factors have been observed to induce aerobic plant CH4 production, i.e. cutting injuries, increasing temperature...... the aerobic methane emission in plants. Future work is needed for establishing the relative contribution of several proven potential CH4 precursors in plant material....

  4. Comparison of Surface Flow Features from Lidar-Derived Digital Elevation Models with Historical Elevation and Hydrography Data for Minnehaha County, South Dakota

    Science.gov (United States)

    Poppenga, Sandra K.; Worstell, Bruce B.; Stoker, Jason M.; Greenlee, Susan K.

    2009-01-01

    The U.S. Geological Survey (USGS) has taken the lead in the creation of a valuable remote sensing product by incorporating digital elevation models (DEMs) derived from Light Detection and Ranging (lidar) into the National Elevation Dataset (NED), the elevation layer of 'The National Map'. High-resolution lidar-derived DEMs provide the accuracy needed to systematically quantify and fully integrate surface flow including flow direction, flow accumulation, sinks, slope, and a dense drainage network. In 2008, 1-meter resolution lidar data were acquired in Minnehaha County, South Dakota. The acquisition was a collaborative effort between Minnehaha County, the city of Sioux Falls, and the USGS Earth Resources Observation and Science (EROS) Center. With the newly acquired lidar data, USGS scientists generated high-resolution DEMs and surface flow features. This report compares lidar-derived surface flow features in Minnehaha County to 30- and 10-meter elevation data previously incorporated in the NED and ancillary hydrography datasets. Surface flow features generated from lidar-derived DEMs are consistently integrated with elevation and are important in understanding surface-water movement to better detect surface-water runoff, flood inundation, and erosion. Many topographic and hydrologic applications will benefit from the increased availability of accurate, high-quality, and high-resolution surface-water data. The remotely sensed data provide topographic information and data integration capabilities needed for meeting current and future human and environmental needs.

  5. Tropospheric ozone climatology at two Southern Hemisphere tropical/subtropical sites, (Reunion Island and Irene, South Africa from ozonesondes, LIDAR, and in situ aircraft measurements

    Directory of Open Access Journals (Sweden)

    G. Clain

    2009-03-01

    Full Text Available This paper presents a climatology and trends of tropospheric ozone in the Southwestern Indian Ocean (Reunion Island and South Africa (Irene and Johannesburg. This study is based on a multi-instrumental dataset: PTU-O3 ozonesondes, DIAL LIDAR and MOZAIC airborne instrumentation.

    The seasonal profiles of tropospheric ozone at Reunion Island have been calculated from two different data sets: ozonesondes and LIDAR. The two climatological profiles are similar, except in austral summer when the LIDAR profiles show greater values in the free troposphere, and in the upper troposphere when the LIDAR profiles show lower values during all seasons. These results show that the climatological value of LIDAR profiles must be discussed with care since LIDAR measurements can be performed only under clear sky conditions, and the upper limit of the profile depends on the signal strength.

    In addition, linear trends have been calculated from ozonesonde data at Reunion and Irene. Considering the whole tropospheric column, the trend is slightly positive for Reunion, and more clearly positive for Irene. Trend calculations have also been made separating the troposphere into three layers, and separating the dataset into seasons. Results show that the positive trend for Irene is governed by the lower layer that is affected by industrial pollution and biomass burning. On the contrary, for Reunion Island, the strongest trends are observed in the upper troposphere, and in winter when stratosphere-troposphere exchange is more frequently expected.

  6. CERC Dataset (Full Hadza Data)

    DEFF Research Database (Denmark)

    2016-01-01

    The dataset includes demographic, behavioral, and religiosity data from eight different populations from around the world. The samples were drawn from: (1) Coastal and (2) Inland Tanna, Vanuatu; (3) Hadzaland, Tanzania; (4) Lovu, Fiji; (5) Pointe aux Piment, Mauritius; (6) Pesqueiro, Brazil; (7......) Kyzyl, Tyva Republic; and (8) Yasawa, Fiji. Related publication: Purzycki, et al. (2016). Moralistic Gods, Supernatural Punishment and the Expansion of Human Sociality. Nature, 530(7590): 327-330....

  7. Viking Seismometer PDS Archive Dataset

    Science.gov (United States)

    Lorenz, R. D.

    2016-12-01

    The Viking Lander 2 seismometer operated successfully for over 500 Sols on the Martian surface, recording at least one likely candidate Marsquake. The Viking mission, in an era when data handling hardware (both on board and on the ground) was limited in capability, predated modern planetary data archiving, and ad-hoc repositories of the data, and the very low-level record at NSSDC, were neither convenient to process nor well-known. In an effort supported by the NASA Mars Data Analysis Program, we have converted the bulk of the Viking dataset (namely the 49,000 and 270,000 records made in High- and Event- modes at 20 and 1 Hz respectively) into a simple ASCII table format. Additionally, since wind-generated lander motion is a major component of the signal, contemporaneous meteorological data are included in summary records to facilitate correlation. These datasets are being archived at the PDS Geosciences Node. In addition to brief instrument and dataset descriptions, the archive includes code snippets in the freely-available language 'R' to demonstrate plotting and analysis. Further, we present examples of lander-generated noise, associated with the sampler arm, instrument dumps and other mechanical operations.

  8. PHYSICS PERFORMANCE AND DATASET (PPD)

    CERN Multimedia

    L. Silvestris

    2013-01-01

    The first part of the Long Shutdown period has been dedicated to the preparation of the samples for the analysis targeting the summer conferences. In particular, the 8 TeV data acquired in 2012, including most of the “parked datasets”, have been reconstructed profiting from improved alignment and calibration conditions for all the sub-detectors. A careful planning of the resources was essential in order to deliver the datasets well in time to the analysts, and to schedule the update of all the conditions and calibrations needed at the analysis level. The newly reprocessed data have undergone detailed scrutiny by the Dataset Certification team allowing to recover some of the data for analysis usage and further improving the certification efficiency, which is now at 91% of the recorded luminosity. With the aim of delivering a consistent dataset for 2011 and 2012, both in terms of conditions and release (53X), the PPD team is now working to set up a data re-reconstruction and a new MC pro...

  9. A Robust Gold Deconvolution Approach for LiDAR Waveform Data Processing to Characterize Vegetation Structure

    Science.gov (United States)

    Zhou, T.; Popescu, S. C.; Krause, K.; Sheridan, R.; Ku, N. W.

    2014-12-01

    Increasing attention has been paid in the remote sensing community to the next generation Light Detection and Ranging (lidar) waveform data systems for extracting information on topography and the vertical structure of vegetation. However, processing waveform lidar data raises some challenges compared to analyzing discrete return data. The overall goal of this study was to present a robust de-convolution algorithm- Gold algorithm used to de-convolve waveforms in a lidar dataset acquired within a 60 x 60m study area located in the Harvard Forest in Massachusetts. The waveform lidar data was collected by the National Ecological Observatory Network (NEON). Specific objectives were to: (1) explore advantages and limitations of various waveform processing techniques to derive topography and canopy height information; (2) develop and implement a novel de-convolution algorithm, the Gold algorithm, to extract elevation and canopy metrics; and (3) compare results and assess accuracy. We modeled lidar waveforms with a mixture of Gaussian functions using the Non-least squares (NLS) algorithm implemented in R and derived a Digital Terrain Model (DTM) and canopy height. We compared our waveform-derived topography and canopy height measurements using the Gold de-convolution algorithm to results using the Richardson-Lucy algorithm. Our findings show that the Gold algorithm performed better than the Richardson-Lucy algorithm in terms of recovering the hidden echoes and detecting false echoes for generating a DTM, which indicates that the Gold algorithm could potentially be applied to processing of waveform lidar data to derive information on terrain elevation and canopy characteristics.

  10. Internationally coordinated glacier monitoring: strategy and datasets

    Science.gov (United States)

    Hoelzle, Martin; Armstrong, Richard; Fetterer, Florence; Gärtner-Roer, Isabelle; Haeberli, Wilfried; Kääb, Andreas; Kargel, Jeff; Nussbaumer, Samuel; Paul, Frank; Raup, Bruce; Zemp, Michael

    2014-05-01

    Internationally coordinated monitoring of long-term glacier changes provide key indicator data about global climate change and began in the year 1894 as an internationally coordinated effort to establish standardized observations. Today, world-wide monitoring of glaciers and ice caps is embedded within the Global Climate Observing System (GCOS) in support of the United Nations Framework Convention on Climate Change (UNFCCC) as an important Essential Climate Variable (ECV). The Global Terrestrial Network for Glaciers (GTN-G) was established in 1999 with the task of coordinating measurements and to ensure the continuous development and adaptation of the international strategies to the long-term needs of users in science and policy. The basic monitoring principles must be relevant, feasible, comprehensive and understandable to a wider scientific community as well as to policy makers and the general public. Data access has to be free and unrestricted, the quality of the standardized and calibrated data must be high and a combination of detailed process studies at selected field sites with global coverage by satellite remote sensing is envisaged. Recently a GTN-G Steering Committee was established to guide and advise the operational bodies responsible for the international glacier monitoring, which are the World Glacier Monitoring Service (WGMS), the US National Snow and Ice Data Center (NSIDC), and the Global Land Ice Measurements from Space (GLIMS) initiative. Several online databases containing a wealth of diverse data types having different levels of detail and global coverage provide fast access to continuously updated information on glacier fluctuation and inventory data. For world-wide inventories, data are now available through (a) the World Glacier Inventory containing tabular information of about 130,000 glaciers covering an area of around 240,000 km2, (b) the GLIMS-database containing digital outlines of around 118,000 glaciers with different time stamps and

  11. Development of lidar techniques for environmental studies

    Energy Technology Data Exchange (ETDEWEB)

    Andersson, Mats

    1996-09-01

    The lidar group in Lund has performed many DIAL measurements with a mobile lidar system that was first described in 1987. The lidar system is based on a Nd:YAG-pumped dye laser. During the last few years the lidar group has focused on fluorescence imaging and mercury measurements in the troposphere. In 1994 we performed two campaigns: one fluorescence imaging measurement campaign outside Avignon, France and one unique lidar campaign at a mercury mine in Almaden, Spain. Both campaigns are described in this thesis. This thesis also describes how the mobile lidar system was updated with the graphical programming language LabVIEW to obtain a user friendly lidar system. The software controls the lidar system and analyses measured data. The measurement results are shown as maps of species concentration. All electronics and the major parts of the program are described. A new graphical technique to estimate wind speed from plumes is also discussed. First measurements have been performed with the new system. 31 refs, 19 figs, 1 tab

  12. 2013 NRCS-USGS Lidar: Lauderdale (MS)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME:NRCS LAUDERDALE MS 0.7M NPS LIDAR. LiDAR Data Acquisition and Processing Production Task. USGS Contract No. G10PC00057. Task Order No. G12PD000125 Woolpert...

  13. Infrastructure Investment Protection with LiDAR

    Science.gov (United States)

    2012-10-15

    The primary goal of this research effort was to explore the wide variety of uses of LiDAR technology and to evaluate their : applicability to NCDOT practices. NCDOT can use this information about LiDAR in determining how and when the : technology can...

  14. The ITER Thomson scattering core LIDAR diagnostic

    NARCIS (Netherlands)

    Naylor, G.A.; Scannell, R.; Beurskens, M.; Walsh, M.J.; Pastor, I.; Donné, A.J.H.; Snijders, B.; Biel, W.; Meszaros, B.; Giudicotti, L.; Pasqualotto, R.; Marot, L.

    2012-01-01

    The central electron temperature and density of the ITER plasma may be determined by Thomson scattering. A LIDAR topology is proposed in order to minimize the port access required of the ITER vacuum vessel. By using a LIDAR technique, a profile of the electron temperature and density can be

  15. Saginaw Bay, MI LiDAR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME:(NRCS) Saginaw Bay, MI LiDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G11PD01254 Woolpert Order...

  16. 2012 USGS Lidar: Elwha River (WA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Elwha River, WA LiDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G11PD01088 Woolpert Order No....

  17. Calibration of Ground -based Lidar instrument

    DEFF Research Database (Denmark)

    Villanueva, Héctor; Yordanova, Ginka

    This report presents the result of the lidar calibration performed for the given Ground-based Lidar at DTU’s test site for large wind turbines at Høvsøre, Denmark. Calibration is here understood as the establishment of a relation between the reference wind speed measurements with measurement...

  18. 2006 South Carolina DNR Lidar: Aiken County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The LiDAR data acquisition was executed in five sessions, on March 15, 16 & 17, 2006, using a Leica ALS50 LiDAR System. Specific details about the ALS50 system...

  19. 2014 USGS/NRCS Lidar: Central MS

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: USGS-NRCS Laurel MS 0.7m NPS LIDAR Lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G13PD01086 Woolpert...

  20. The long term stability of lidar calibrations

    DEFF Research Database (Denmark)

    Courtney, Michael; Gayle Nygaard, Nicolai

    Wind lidars are now used extensively for wind resource measurements. One of the requirements for the data to be accepted in support of project financing (so-called ‘banka-bility’) is to demonstrate the long-term stability of lidar cali-brations. Calibration results for six Leosphere WindCube li...

  1. RARD: The Related-Article Recommendation Dataset

    OpenAIRE

    Beel, Joeran; Carevic, Zeljko; Schaible, Johann; Neusch, Gabor

    2017-01-01

    Recommender-system datasets are used for recommender-system evaluations, training machine-learning algorithms, and exploring user behavior. While there are many datasets for recommender systems in the domains of movies, books, and music, there are rather few datasets from research-paper recommender systems. In this paper, we introduce RARD, the Related-Article Recommendation Dataset, from the digital library Sowiport and the recommendation-as-a-service provider Mr. DLib. The dataset contains ...

  2. Airborne Lidar Simulator for the Lidar Surface Topography (LIST) Mission

    Science.gov (United States)

    Yu, Anthony W.; Krainak, Michael A.; Abshire, James B.; Cavanaugh, John; Valett, Susan; Ramos-Izquierdo, Luis

    2010-01-01

    In 2007, the National Research Council (NRC) completed its first decadal survey for Earth science at the request of NASA, NOAA, and USGS. The Lidar Surface Topography (LIST) mission is one of fifteen missions recommended by NRC, whose primary objectives are to map global topography and vegetation structure at 5 m spatial resolution, and to acquire global surface height mapping within a few years. NASA Goddard conducted an initial mission concept study for the LIST mission in 2007, and developed the initial measurement requirements for the mission.

  3. Pointing Verification Method for Spaceborne Lidars

    Directory of Open Access Journals (Sweden)

    Axel Amediek

    2017-01-01

    Full Text Available High precision acquisition of atmospheric parameters from the air or space by means of lidar requires accurate knowledge of laser pointing. Discrepancies between the assumed and actual pointing can introduce large errors due to the Doppler effect or a wrongly assumed air pressure at ground level. In this paper, a method for precisely quantifying these discrepancies for airborne and spaceborne lidar systems is presented. The method is based on the comparison of ground elevations derived from the lidar ranging data with high-resolution topography data obtained from a digital elevation model and allows for the derivation of the lateral and longitudinal deviation of the laser beam propagation direction. The applicability of the technique is demonstrated by using experimental data from an airborne lidar system, confirming that geo-referencing of the lidar ground spot trace with an uncertainty of less than 10 m with respect to the used digital elevation model (DEM can be obtained.

  4. Calibration Methods for a Space Borne Backscatter Lidar

    NARCIS (Netherlands)

    Kunz, G.J.

    1996-01-01

    Lidar returns from cloud decks and from the Earth's surface are useful for calibrating single scatter lidar signals from space. To this end analytical methods (forward and backward) are presented for inverting lidar waveforms in terms of the path integrated lidar retum and the transmission losses

  5. Mapping Forest Edge Using Aerial Lidar

    Science.gov (United States)

    MacLean, M. G.

    2014-12-01

    Slightly more than 60% of Massachusetts is covered with forest and this land cover type is invaluable for the protection and maintenance of our natural resources and is a carbon sink for the state. However, Massachusetts is currently experiencing a decline in forested lands, primarily due to the expansion of human development (Thompson et al., 2011). Of particular concern is the loss of "core areas" or the areas within forests that are not influenced by other land cover types. These areas are of significant importance to native flora and fauna, since they generally are not subject to invasion by exotic species and are more resilient to the effects of climate change (Campbell et al., 2009). However, the expansion of development has reduced the amount of this core area, but the exact amount is still unknown. Current methods of estimating core area are not particularly precise, since edge, or the area of the forest that is most influenced by other land cover types, is quite variable and situation dependent. Therefore, the purpose of this study is to devise a new method for identifying areas that could qualify as "edge" within the Harvard Forest, in Petersham MA, using new remote sensing techniques. We sampled along eight transects perpendicular to the edge of an abandoned golf course within the Harvard Forest property. Vegetation inventories as well as Photosynthetically Active Radiation (PAR) at different heights within the canopy were used to determine edge depth. These measurements were then compared with small-footprint waveform aerial LiDAR datasets and imagery to model edge depths within Harvard Forest.

  6. Increasing the Impact of High-Resolution Lidar Topography Through Online Data Access and Processing

    Science.gov (United States)

    Crosby, C. J.; Nandigam, V.; Baru, C.; Arrowsmith, R.

    2013-12-01

    Topography data acquired with lidar (light detection and ranging) technology are revolutionizing the way we study the Earth's surface and overlying vegetation. These data, collected from satellite, airborne, tripod, or mobile-mounted scanners have emerged as a fundamental tool for research on topics including earthquake hazards, hillslope processes, and cyrosphere change. The U.S. National Science Foundation-funded OpenTopography (OT) Facility (http://www.opentopography.org) is a web-based system designed to democratize access to earth science-oriented lidar topography data. OT provides free, online access to lidar data in a number of forms, including the point cloud and associated geospatial-processing tools for customized analysis. The point cloud data are co-located with on-demand processing tools to generate digital elevation models, and derived products and visualizations which allow users to quickly access data in a format appropriate for their scientific application. The OT system is built using a service-oriented architecture (SOA) that leverages cyberinfrastructure resources at the San Diego Supercomputer Center at the University of California San Diego to allow users, regardless of expertise, to access these massive lidar datasets and derived raster data products for use in research and teaching. OT hosts over 600 billion lidar returns covering more than 120,000 km2. These data are provided by a variety of partners under joint agreements and memoranda of understanding with OT. Partners include national facilities such as the NSF-funded National Center for Airborne Lidar Mapping (NCALM), as well as non-governmental organizations and local, state, and federal agencies. OT has become a hub for high-resolution topography resources. Datasets hosted by other organizations, as well as lidar-specific software, can be registered into the OT catalog, providing users a 'one-stop shop' for such information. OT is also a partner on the NASA Lidar Access System (NLAS

  7. Measurement and Study of Lidar Ratio by Using a Raman Lidar in Central China

    Directory of Open Access Journals (Sweden)

    Wei Wang

    2016-05-01

    Full Text Available We comprehensively evaluated particle lidar ratios (i.e., particle extinction to backscatter ratio at 532 nm over Wuhan in Central China by using a Raman lidar from July 2013 to May 2015. We utilized the Raman lidar data to obtain homogeneous aerosol lidar ratios near the surface through the Raman method during no-rain nights. The lidar ratios were approximately 57 ± 7 sr, 50 ± 5 sr, and 22 ± 4 sr under the three cases with obviously different pollution levels. The haze layer below 1.8 km has a large particle extinction coefficient (from 5.4e-4 m−1 to 1.6e-4 m−1 and particle backscatter coefficient (between 1.1e-05 m−1sr−1 and 1.7e-06 m−1sr−1 in the heavily polluted case. Furthermore, the particle lidar ratios varied according to season, especially between winter (57 ± 13 sr and summer (33 ± 10 sr. The seasonal variation in lidar ratios at Wuhan suggests that the East Asian monsoon significantly affects the primary aerosol types and aerosol optical properties in this region. The relationships between particle lidar ratios and wind indicate that large lidar ratio values correspond well with weak winds and strong northerly winds, whereas significantly low lidar ratio values are associated with prevailing southwesterly and southerly wind.

  8. The design, development, and test of balloonborne and groundbased lidar systems. Volume 3: Groundbased lidar systems

    Science.gov (United States)

    Shepherd, O.; Aurilio, G.; Bucknam, R. D.; Hurd, A. G.; Robertie, N. F.

    1991-06-01

    This is Volume 3 of a three volume final report on the design, development and test of balloonborne and groundbased lidar systems. Volume 1 describes the design and fabrication of a balloonborne CO2 coherent payload to measure the 10.6 micrometers backscatter from atmospheric aerosols as a function of altitude. Volume 2 describes the August 1987 flight test of Atmospheric Balloonborne Lidar Experiment, ABLE 2. In this volume we describe groundbased lidar development and measurements. A design was developed for installation of the ABLE lidar in the GL rooftop dome. A transportable shed was designed to house the ABLE lidar at the various remote measurement sites. Refurbishment and modification of the ABLE lidar were completed to permit groundbased lidar measurements of clouds and aerosols. Lidar field measurements were made at Ascension Island during SABLE 89. Lidar field measurements were made at Terciera, Azores during GABLE 90. These tasks have been successfully completed, and recommendations for further lidar measurements and data analysis have been made.

  9. Measurement and Study of Lidar Ratio by Using a Raman Lidar in Central China.

    Science.gov (United States)

    Wang, Wei; Gong, Wei; Mao, Feiyue; Pan, Zengxin; Liu, Boming

    2016-05-18

    We comprehensively evaluated particle lidar ratios (i.e., particle extinction to backscatter ratio) at 532 nm over Wuhan in Central China by using a Raman lidar from July 2013 to May 2015. We utilized the Raman lidar data to obtain homogeneous aerosol lidar ratios near the surface through the Raman method during no-rain nights. The lidar ratios were approximately 57 ± 7 sr, 50 ± 5 sr, and 22 ± 4 sr under the three cases with obviously different pollution levels. The haze layer below 1.8 km has a large particle extinction coefficient (from 5.4e-4 m(-1) to 1.6e-4 m(-1)) and particle backscatter coefficient (between 1.1e-05 m(-1)sr(-1) and 1.7e-06 m(-1)sr(-1)) in the heavily polluted case. Furthermore, the particle lidar ratios varied according to season, especially between winter (57 ± 13 sr) and summer (33 ± 10 sr). The seasonal variation in lidar ratios at Wuhan suggests that the East Asian monsoon significantly affects the primary aerosol types and aerosol optical properties in this region. The relationships between particle lidar ratios and wind indicate that large lidar ratio values correspond well with weak winds and strong northerly winds, whereas significantly low lidar ratio values are associated with prevailing southwesterly and southerly wind.

  10. Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies.

    Science.gov (United States)

    Ferraz, A.; Painter, T. H.; Saatchi, S.; Bormann, K. J.

    2016-12-01

    Fusion of multi-temporal Airborne Snow Observatory (ASO) lidar data for mountainous vegetation ecosystems studies The NASA Jet Propulsion Laboratory developed the Airborne Snow Observatory (ASO), a coupled scanning lidar system and imaging spectrometer, to quantify the spatial distribution of snow volume and dynamics over mountains watersheds (Painter et al., 2015). To do this, ASO weekly over-flights mountainous areas during snowfall and snowmelt seasons. In addition, there are additional flights in snow-off conditions to calculate Digital Terrain Models (DTM). In this study, we focus on the reliability of ASO lidar data to characterize the 3D forest vegetation structure. The density of a single point cloud acquisition is of nearly 1 pt/m2, which is not optimal to properly characterize vegetation. However, ASO covers a given study site up to 14 times a year that enables computing a high-resolution point cloud by merging single acquisitions. In this study, we present a method to automatically register ASO multi-temporal lidar 3D point clouds. Although flight specifications do not change between acquisition dates, lidar datasets might have significant planimetric shifts due to inaccuracies in platform trajectory estimation introduced by the GPS system and drifts of the IMU. There are a large number of methodologies that address the problem of 3D data registration (Gressin et al., 2013). Briefly, they look for common primitive features in both datasets such as buildings corners, structures like electric poles, DTM breaklines or deformations. However, they are not suited for our experiment. First, single acquisition point clouds have low density that makes the extraction of primitive features difficult. Second, the landscape significantly changes between flights due to snowfall and snowmelt. Therefore, we developed a method to automatically register point clouds using tree apexes as keypoints because they are features that are supposed to experience little change

  11. Passive Containment DataSet

    Science.gov (United States)

    This data is for Figures 6 and 7 in the journal article. The data also includes the two EPANET input files used for the analysis described in the paper, one for the looped system and one for the block system.This dataset is associated with the following publication:Grayman, W., R. Murray , and D. Savic. Redesign of Water Distribution Systems for Passive Containment of Contamination. JOURNAL OF THE AMERICAN WATER WORKS ASSOCIATION. American Water Works Association, Denver, CO, USA, 108(7): 381-391, (2016).

  12. Multispectral LiDAR Data for Land Cover Classification of Urban Areas

    Directory of Open Access Journals (Sweden)

    Salem Morsy

    2017-04-01

    Full Text Available Airborne Light Detection And Ranging (LiDAR systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

  13. INTEGRATING SMARTPHONE IMAGES AND AIRBORNE LIDAR DATA FOR COMPLETE URBAN BUILDING MODELLING

    Directory of Open Access Journals (Sweden)

    S. Zhang

    2016-06-01

    Full Text Available A complete building model reconstruction needs data collected from both air and ground. The former often has sparse coverage on building façades, while the latter usually is unable to observe the building rooftops. Attempting to solve the missing data issues in building reconstruction from single data source, we describe an approach for complete building reconstruction that integrates airborne LiDAR data and ground smartphone imagery. First, by taking advantages of GPS and digital compass information embedded in the image metadata of smartphones, we are able to find airborne LiDAR point clouds for the corresponding buildings in the images. In the next step, Structure-from-Motion and dense multi-view stereo algorithms are applied to generate building point cloud from multiple ground images. The third step extracts building outlines respectively from the LiDAR point cloud and the ground image point cloud. An automated correspondence between these two sets of building outlines allows us to achieve a precise registration and combination of the two point clouds, which ultimately results in a complete and full resolution building model. The developed approach overcomes the problem of sparse points on building façades in airborne LiDAR and the deficiency of rooftops in ground images such that the merits of both datasets are utilized.

  14. Modeling habitat for Marbled Murrelets on the Siuslaw National Forest, Oregon, using lidar data

    Science.gov (United States)

    Hagar, Joan C.; Aragon, Ramiro; Haggerty, Patricia; Hollenbeck, Jeff P.

    2018-03-28

    Habitat models using lidar-derived variables that quantify fine-scale variation in vegetation structure can improve the accuracy of occupancy estimates for canopy-dwelling species over models that use variables derived from other remote sensing techniques. However, the ability of models developed at such a fine spatial scale to maintain accuracy at regional or larger spatial scales has not been tested. We tested the transferability of a lidar-based habitat model for the threatened Marbled Murrelet (Brachyramphus marmoratus) between two management districts within a larger regional conservation zone in coastal western Oregon. We compared the performance of the transferred model against models developed with data from the application location. The transferred model had good discrimination (AUC = 0.73) at the application location, and model performance was further improved by fitting the original model with coefficients from the application location dataset (AUC = 0.79). However, the model selection procedure indicated that neither of these transferred models were considered competitive with a model trained on local data. The new model trained on data from the application location resulted in the selection of a slightly different set of lidar metrics from the original model, but both transferred and locally trained models consistently indicated positive relationships between the probability of occupancy and lidar measures of canopy structural complexity. We conclude that while the locally trained model had superior performance for local application, the transferred model could reasonably be applied to the entire conservation zone.

  15. Multispectral LiDAR Data for Land Cover Classification of Urban Areas.

    Science.gov (United States)

    Morsy, Salem; Shaker, Ahmed; El-Rabbany, Ahmed

    2017-04-26

    Airborne Light Detection And Ranging (LiDAR) systems usually operate at a monochromatic wavelength measuring the range and the strength of the reflected energy (intensity) from objects. Recently, multispectral LiDAR sensors, which acquire data at different wavelengths, have emerged. This allows for recording of a diversity of spectral reflectance from objects. In this context, we aim to investigate the use of multispectral LiDAR data in land cover classification using two different techniques. The first is image-based classification, where intensity and height images are created from LiDAR points and then a maximum likelihood classifier is applied. The second is point-based classification, where ground filtering and Normalized Difference Vegetation Indices (NDVIs) computation are conducted. A dataset of an urban area located in Oshawa, Ontario, Canada, is classified into four classes: buildings, trees, roads and grass. An overall accuracy of up to 89.9% and 92.7% is achieved from image classification and 3D point classification, respectively. A radiometric correction model is also applied to the intensity data in order to remove the attenuation due to the system distortion and terrain height variation. The classification process is then repeated, and the results demonstrate that there are no significant improvements achieved in the overall accuracy.

  16. Retrievals of Aerosol Microphysics from Simulations of Spaceborne Multiwavelength Lidar Measurements

    Science.gov (United States)

    Whiteman, David N.; Perez-Ramírez, Daniel; Veselovskii, Igor; Colarco, Peter; Buchard, Virginie

    2017-01-01

    In support of the Aerosol, Clouds, Ecosystems mission, simulations of a spaceborne multiwavelength lidar are performed based on global model simulations of the atmosphere along a satellite orbit track. The yield for aerosol microphysical inversions is quantified and comparisons are made between the aerosol microphysics inherent in the global model and those inverted from both the model's optical data and the simulated three backscatter and two extinction lidar measurements, which are based on the model's optical data. We find that yield can be significantly increased if inversions based on a reduced optical dataset of three backscatter and one extinction are acceptable. In general, retrieval performance is better for cases where the aerosol fine mode dominates although a lack of sensitivity to particles with sizes less than 0.1 microns is found. Lack of sensitivity to coarse mode cases is also found, in agreement with earlier studies. Surface area is generally the most robustly retrieved quantity. The work here points toward the need for ancillary data to aid in the constraints of the lidar inversions and also for joint inversions involving lidar and polarimeter measurements.

  17. DECISION LEVEL FUSION OF ORTHOPHOTO AND LIDAR DATA USING CONFUSION MATRIX INFORMATION FOR LNAD COVER CLASSIFICATION

    Directory of Open Access Journals (Sweden)

    S. Daneshtalab

    2017-09-01

    Full Text Available Automatic urban objects extraction from airborne remote sensing data is essential to process and efficiently interpret the vast amount of airborne imagery and Lidar data available today. The aim of this study is to propose a new approach for the integration of high-resolution aerial imagery and Lidar data to improve the accuracy of classification in the city complications. In the proposed method, first, the classification of each data is separately performed using Support Vector Machine algorithm. In this case, extracted Normalized Digital Surface Model (nDSM and pulse intensity are used in classification of LiDAR data, and three spectral visible bands (Red, Green, Blue are considered as feature vector for the orthoimage classification. Moreover, combining the extracted features of the image and Lidar data another classification is also performed using all the features. The outputs of these classifications are integrated in a decision level fusion system according to the their confusion matrices to find the final classification result. The proposed method was evaluated using an urban area of Zeebruges, Belgium. The obtained results represented several advantages of image fusion with respect to a single shot dataset. With the capabilities of the proposed decision level fusion method, most of the object extraction difficulties and uncertainty were decreased and, the overall accuracy and the kappa values were improved 7% and 10%, respectively.

  18. Line-Based Registration of Panoramic Images and LiDAR Point Clouds for Mobile Mapping

    Directory of Open Access Journals (Sweden)

    Tingting Cui

    2016-12-01

    Full Text Available For multi-sensor integrated systems, such as the mobile mapping system (MMS, data fusion at sensor-level, i.e., the 2D-3D registration between an optical camera and LiDAR, is a prerequisite for higher level fusion and further applications. This paper proposes a line-based registration method for panoramic images and a LiDAR point cloud collected by a MMS. We first introduce the system configuration and specification, including the coordinate systems of the MMS, the 3D LiDAR scanners, and the two panoramic camera models. We then establish the line-based transformation model for the panoramic camera. Finally, the proposed registration method is evaluated for two types of camera models by visual inspection and quantitative comparison. The results demonstrate that the line-based registration method can significantly improve the alignment of the panoramic image and the LiDAR datasets under either the ideal spherical or the rigorous panoramic camera model, with the latter being more reliable.

  19. ASSESSING TEMPORAL BEHAVIOR IN LIDAR POINT CLOUDS OF URBAN ENVIRONMENTS

    Directory of Open Access Journals (Sweden)

    J. Schachtschneider

    2017-05-01

    Full Text Available Self-driving cars and robots that run autonomously over long periods of time need high-precision and up-to-date models of the changing environment. The main challenge for creating long term maps of dynamic environments is to identify changes and adapt the map continuously. Changes can occur abruptly, gradually, or even periodically. In this work, we investigate how dense mapping data of several epochs can be used to identify the temporal behavior of the environment. This approach anticipates possible future scenarios where a large fleet of vehicles is equipped with sensors which continuously capture the environment. This data is then being sent to a cloud based infrastructure, which aligns all datasets geometrically and subsequently runs scene analysis on it, among these being the analysis for temporal changes of the environment. Our experiments are based on a LiDAR mobile mapping dataset which consists of 150 scan strips (a total of about 1 billion points, which were obtained in multiple epochs. Parts of the scene are covered by up to 28 scan strips. The time difference between the first and last epoch is about one year. In order to process the data, the scan strips are aligned using an overall bundle adjustment, which estimates the surface (about one billion surface element unknowns as well as 270,000 unknowns for the adjustment of the exterior orientation parameters. After this, the surface misalignment is usually below one centimeter. In the next step, we perform a segmentation of the point clouds using a region growing algorithm. The segmented objects and the aligned data are then used to compute an occupancy grid which is filled by tracing each individual LiDAR ray from the scan head to every point of a segment. As a result, we can assess the behavior of each segment in the scene and remove voxels from temporal objects from the global occupancy grid.

  20. Assessing Temporal Behavior in LIDAR Point Clouds of Urban Environments

    Science.gov (United States)

    Schachtschneider, J.; Schlichting, A.; Brenner, C.

    2017-05-01

    Self-driving cars and robots that run autonomously over long periods of time need high-precision and up-to-date models of the changing environment. The main challenge for creating long term maps of dynamic environments is to identify changes and adapt the map continuously. Changes can occur abruptly, gradually, or even periodically. In this work, we investigate how dense mapping data of several epochs can be used to identify the temporal behavior of the environment. This approach anticipates possible future scenarios where a large fleet of vehicles is equipped with sensors which continuously capture the environment. This data is then being sent to a cloud based infrastructure, which aligns all datasets geometrically and subsequently runs scene analysis on it, among these being the analysis for temporal changes of the environment. Our experiments are based on a LiDAR mobile mapping dataset which consists of 150 scan strips (a total of about 1 billion points), which were obtained in multiple epochs. Parts of the scene are covered by up to 28 scan strips. The time difference between the first and last epoch is about one year. In order to process the data, the scan strips are aligned using an overall bundle adjustment, which estimates the surface (about one billion surface element unknowns) as well as 270,000 unknowns for the adjustment of the exterior orientation parameters. After this, the surface misalignment is usually below one centimeter. In the next step, we perform a segmentation of the point clouds using a region growing algorithm. The segmented objects and the aligned data are then used to compute an occupancy grid which is filled by tracing each individual LiDAR ray from the scan head to every point of a segment. As a result, we can assess the behavior of each segment in the scene and remove voxels from temporal objects from the global occupancy grid.

  1. FULLY CONVOLUTIONAL NETWORKS FOR GROUND CLASSIFICATION FROM LIDAR POINT CLOUDS

    Directory of Open Access Journals (Sweden)

    A. Rizaldy

    2018-05-01

    Full Text Available Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs. In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN, a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher. The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.

  2. Fully Convolutional Networks for Ground Classification from LIDAR Point Clouds

    Science.gov (United States)

    Rizaldy, A.; Persello, C.; Gevaert, C. M.; Oude Elberink, S. J.

    2018-05-01

    Deep Learning has been massively used for image classification in recent years. The use of deep learning for ground classification from LIDAR point clouds has also been recently studied. However, point clouds need to be converted into an image in order to use Convolutional Neural Networks (CNNs). In state-of-the-art techniques, this conversion is slow because each point is converted into a separate image. This approach leads to highly redundant computation during conversion and classification. The goal of this study is to design a more efficient data conversion and ground classification. This goal is achieved by first converting the whole point cloud into a single image. The classification is then performed by a Fully Convolutional Network (FCN), a modified version of CNN designed for pixel-wise image classification. The proposed method is significantly faster than state-of-the-art techniques. On the ISPRS Filter Test dataset, it is 78 times faster for conversion and 16 times faster for classification. Our experimental analysis on the same dataset shows that the proposed method results in 5.22 % of total error, 4.10 % of type I error, and 15.07 % of type II error. Compared to the previous CNN-based technique and LAStools software, the proposed method reduces the total error and type I error (while type II error is slightly higher). The method was also tested on a very high point density LIDAR point clouds resulting in 4.02 % of total error, 2.15 % of type I error and 6.14 % of type II error.

  3. Measurement Axis Searching Model for Terrestrial Laser Scans Registration

    Directory of Open Access Journals (Sweden)

    Shaoxing Hu

    2016-01-01

    Full Text Available Nowadays, terrestrial Lidar scans can cover rather a large area; the point densities are strongly varied because of the line-of-sight measurement principle in potential overlaps with scans taken from different viewpoints. Most of the traditional methods focus on registration algorithm and ignore searching model. Sometimes the traditional methods are directly used to align two point clouds; a large critically unsolved problem of the large biases will be created in areas distant from the overlaps while the local overlaps are often aligned well. So a novel measurement axis searching model (MASM has been proposed in this paper. The method includes four steps: (1 the principal axis fitting, (2 the measurement axis generation, (3 low-high-precision search, and (4 result generation. The principal axis gives an orientation to the point cloud; the search scope is limited by the measurement axis. The point cloud orientation can be adjusted gradually until the achievement of the global optimum using low- and high-precision search. We perform some experiments with simulated point clouds and real terrestrial laser scans. The results of simulated point clouds have shown the processing steps of our method, and the results of real terrestrial laser scans have shown the sensitivity of the approach with respect to the indoor and outdoor scenes.

  4. Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest

    Directory of Open Access Journals (Sweden)

    Carlos Alberto Silva

    2017-10-01

    Full Text Available Airborne lidar is a technology well-suited for mapping many forest attributes, including aboveground biomass (AGB stocks and changes in selective logging in tropical forests. However, trade-offs still exist between lidar pulse density and accuracy of AGB estimates. We assessed the impacts of lidar pulse density on the estimation of AGB stocks and changes using airborne lidar and field plot data in a selectively logged tropical forest located near Paragominas, Pará, Brazil. Field-derived AGB was computed at 85 square 50 × 50 m plots in 2014. Lidar data were acquired in 2012 and 2014, and for each dataset the pulse density was subsampled from its original density of 13.8 and 37.5 pulses·m−2 to lower densities of 12, 10, 8, 6, 4, 2, 0.8, 0.6, 0.4 and 0.2 pulses·m−2. For each pulse density dataset, a power-law model was developed to estimate AGB stocks from lidar-derived mean height and corresponding changes between the years 2012 and 2014. We found that AGB change estimates at the plot level were only slightly affected by pulse density. However, at the landscape level we observed differences in estimated AGB change of >20 Mg·ha−1 when pulse density decreased from 12 to 0.2 pulses·m−2. The effects of pulse density were more pronounced in areas of steep slope, especially when the digital terrain models (DTMs used in the lidar derived forest height were created from reduced pulse density data. In particular, when the DTM from high pulse density in 2014 was used to derive the forest height from both years, the effects on forest height and the estimated AGB stock and changes did not exceed 20 Mg·ha−1. The results suggest that AGB change can be monitored in selective logging in tropical forests with reasonable accuracy and low cost with low pulse density lidar surveys if a baseline high-quality DTM is available from at least one lidar survey. We recommend the results of this study to be considered in developing projects and national

  5. The CMS dataset bookkeeping service

    Science.gov (United States)

    Afaq, A.; Dolgert, A.; Guo, Y.; Jones, C.; Kosyakov, S.; Kuznetsov, V.; Lueking, L.; Riley, D.; Sekhri, V.

    2008-07-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems.

  6. The CMS dataset bookkeeping service

    Energy Technology Data Exchange (ETDEWEB)

    Afaq, A; Guo, Y; Kosyakov, S; Lueking, L; Sekhri, V [Fermilab, Batavia, Illinois 60510 (United States); Dolgert, A; Jones, C; Kuznetsov, V; Riley, D [Cornell University, Ithaca, New York 14850 (United States)

    2008-07-15

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems.

  7. The CMS dataset bookkeeping service

    International Nuclear Information System (INIS)

    Afaq, A; Guo, Y; Kosyakov, S; Lueking, L; Sekhri, V; Dolgert, A; Jones, C; Kuznetsov, V; Riley, D

    2008-01-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems

  8. The CMS dataset bookkeeping service

    International Nuclear Information System (INIS)

    Afaq, Anzar; Dolgert, Andrew; Guo, Yuyi; Jones, Chris; Kosyakov, Sergey; Kuznetsov, Valentin; Lueking, Lee; Riley, Dan; Sekhri, Vijay

    2007-01-01

    The CMS Dataset Bookkeeping Service (DBS) has been developed to catalog all CMS event data from Monte Carlo and Detector sources. It provides the ability to identify MC or trigger source, track data provenance, construct datasets for analysis, and discover interesting data. CMS requires processing and analysis activities at various service levels and the DBS system provides support for localized processing or private analysis, as well as global access for CMS users at large. Catalog entries can be moved among the various service levels with a simple set of migration tools, thus forming a loose federation of databases. DBS is available to CMS users via a Python API, Command Line, and a Discovery web page interfaces. The system is built as a multi-tier web application with Java servlets running under Tomcat, with connections via JDBC to Oracle or MySQL database backends. Clients connect to the service through HTTP or HTTPS with authentication provided by GRID certificates and authorization through VOMS. DBS is an integral part of the overall CMS Data Management and Workflow Management systems

  9. Lidar Remote Sensing for Industry and Environment Monitoring

    Science.gov (United States)

    Singh, Upendra N. (Editor); Itabe, Toshikazu (Editor); Sugimoto, Nobuo (Editor)

    2000-01-01

    Contents include the following: 1. Keynote paper: Overview of lidar technology for industrial and environmental monitoring in Japan. 2. lidar technology I: NASA's future active remote sensing mission for earth science. Geometrical detector consideration s in laser sensing application (invited paper). 3. Lidar technology II: High-power femtosecond light strings as novel atmospheric probes (invited paper). Design of a compact high-sensitivity aerosol profiling lidar. 4. Lasers for lidars: High-energy 2 microns laser for multiple lidar applications. New submount requirement of conductively cooled laser diodes for lidar applications. 5. Tropospheric aerosols and clouds I: Lidar monitoring of clouds and aerosols at the facility for atmospheric remote sensing (invited paper). Measurement of asian dust by using multiwavelength lidar. Global monitoring of clouds and aerosols using a network of micropulse lidar systems. 6. Troposphere aerosols and clouds II: Scanning lidar measurements of marine aerosol fields at a coastal site in Hawaii. 7. Tropospheric aerosols and clouds III: Formation of ice cloud from asian dust particles in the upper troposphere. Atmospheric boundary layer observation by ground-based lidar at KMITL, Thailand (13 deg N, 100 deg. E). 8. Boundary layer, urban pollution: Studies of the spatial correlation between urban aerosols and local traffic congestion using a slant angle scanning on the research vessel Mirai. 9. Middle atmosphere: Lidar-observed arctic PSC's over Svalbard (invited paper). Sodium temperature lidar measurements of the mesopause region over Syowa Station. 10. Differential absorption lidar (dIAL) and DOAS: Airborne UV DIAL measurements of ozone and aerosols (invited paper). Measurement of water vapor, surface ozone, and ethylene using differential absorption lidar. 12. Space lidar I: Lightweight lidar telescopes for space applications (invited paper). Coherent lidar development for Doppler wind measurement from the International Space

  10. Arctic Terrestrial Biodiversity Monitoring Plan

    DEFF Research Database (Denmark)

    Christensen, Tom; Payne, J.; Doyle, M.

    The Conservation of Arctic Flora and Fauna (CAFF), the biodiversity working group of the Arctic Council, established the Circumpolar Biodiversity Monitoring Program (CBMP) to address the need for coordinated and standardized monitoring of Arctic environments. The CBMP includes an international...... on developing and implementing long-term plans for monitoring the integrity of Arctic biomes: terrestrial, marine, freshwater, and coastal (under development) environments. The CBMP Terrestrial Expert Monitoring Group (CBMP-TEMG) has developed the Arctic Terrestrial Biodiversity Monitoring Plan (CBMP......-Terrestrial Plan/the Plan) as the framework for coordinated, long-term Arctic terrestrial biodiversity monitoring. The goal of the CBMP-Terrestrial Plan is to improve the collective ability of Arctic traditional knowledge (TK) holders, northern communities, and scientists to detect, understand and report on long...

  11. 4D Near Real-Time Environmental Monitoring Using Highly Temporal LiDAR

    Science.gov (United States)

    Höfle, Bernhard; Canli, Ekrem; Schmitz, Evelyn; Crommelinck, Sophie; Hoffmeister, Dirk; Glade, Thomas

    2016-04-01

    The last decade has witnessed extensive applications of 3D environmental monitoring with the LiDAR technology, also referred to as laser scanning. Although several automatic methods were developed to extract environmental parameters from LiDAR point clouds, only little research has focused on highly multitemporal near real-time LiDAR (4D-LiDAR) for environmental monitoring. Large potential of applying 4D-LiDAR is given for landscape objects with high and varying rates of change (e.g. plant growth) and also for phenomena with sudden unpredictable changes (e.g. geomorphological processes). In this presentation we will report on the most recent findings of the research projects 4DEMON (http://uni-heidelberg.de/4demon) and NoeSLIDE (https://geomorph.univie.ac.at/forschung/projekte/aktuell/noeslide/). The method development in both projects is based on two real-world use cases: i) Surface parameter derivation of agricultural crops (e.g. crop height) and ii) change detection of landslides. Both projects exploit the "full history" contained in the LiDAR point cloud time series. One crucial initial step of 4D-LiDAR analysis is the co-registration over time, 3D-georeferencing and time-dependent quality assessment of the LiDAR point cloud time series. Due to the high amount of datasets (e.g. one full LiDAR scan per day), the procedure needs to be performed fully automatically. Furthermore, the online near real-time 4D monitoring system requires to set triggers that can detect removal or moving of tie reflectors (used for co-registration) or the scanner itself. This guarantees long-term data acquisition with high quality. We will present results from a georeferencing experiment for 4D-LiDAR monitoring, which performs benchmarking of co-registration, 3D-georeferencing and also fully automatic detection of events (e.g. removal/moving of reflectors or scanner). Secondly, we will show our empirical findings of an ongoing permanent LiDAR observation of a landslide (Gresten

  12. Land Cover Segmentation of Airborne LiDAR Data Using Stochastic Atrous Network

    Directory of Open Access Journals (Sweden)

    Hasan Asy’ari Arief

    2018-06-01

    Full Text Available Inspired by the success of deep learning techniques in dense-label prediction and the increasing availability of high precision airborne light detection and ranging (LiDAR data, we present a research process that compares a collection of well-proven semantic segmentation architectures based on the deep learning approach. Our investigation concludes with the proposition of some novel deep learning architectures for generating detailed land resource maps by employing a semantic segmentation approach. The contribution of our work is threefold. (1 First, we implement the multiclass version of the intersection-over-union (IoU loss function that contributes to handling highly imbalanced datasets and preventing overfitting. (2 Thereafter, we propose a novel deep learning architecture integrating the deep atrous network architecture with the stochastic depth approach for speeding up the learning process, and impose a regularization effect. (3 Finally, we introduce an early fusion deep layer that combines image-based and LiDAR-derived features. In a benchmark study carried out using the Follo 2014 LiDAR data and the NIBIO AR5 land resources dataset, we compare our proposals to other deep learning architectures. A quantitative comparison shows that our best proposal provides more than 5% relative improvement in terms of mean intersection-over-union over the atrous network, providing a basis for a more frequent and improved use of LiDAR data for automatic land cover segmentation.

  13. Radar and Lidar Radar DEM

    Science.gov (United States)

    Liskovich, Diana; Simard, Marc

    2011-01-01

    Using radar and lidar data, the aim is to improve 3D rendering of terrain, including digital elevation models (DEM) and estimates of vegetation height and biomass in a variety of forest types and terrains. The 3D mapping of vegetation structure and the analysis are useful to determine the role of forest in climate change (carbon cycle), in providing habitat and as a provider of socio-economic services. This in turn will lead to potential for development of more effective land-use management. The first part of the project was to characterize the Shuttle Radar Topography Mission DEM error with respect to ICESat/GLAS point estimates of elevation. We investigated potential trends with latitude, canopy height, signal to noise ratio (SNR), number of LiDAR waveform peaks, and maximum peak width. Scatter plots were produced for each variable and were fitted with 1st and 2nd degree polynomials. Higher order trends were visually inspected through filtering with a mean and median filter. We also assessed trends in the DEM error variance. Finally, a map showing how DEM error was geographically distributed globally was created.

  14. IEA Wind Task 32: Wind lidar identifying and mitigating barriers to the adoption of wind lidar

    DEFF Research Database (Denmark)

    Clifton, Andrew; Clive, Peter; Gottschall, Julia

    2018-01-01

    IEA Wind Task 32 exists to identify and mitigate barriers to the adoption of lidar for wind energy applications. It leverages ongoing international research and development activities in academia and industry to investigate site assessment, power performance testing, controls and loads, and complex...... flows. Since its initiation in 2011, Task 32 has been responsible for several recommended practices and expert reports that have contributed to the adoption of ground-based, nacelle-based, and floating lidar by the wind industry. Future challenges include the development of lidar uncertainty models......, best practices for data management, and developing community-based tools for data analysis, planning of lidar measurements and lidar configuration. This paper describes the barriers that Task 32 identified to the deployment of wind lidar in each of these application areas, and the steps that have been...

  15. Contaminant exposure in terrestrial vertebrates

    International Nuclear Information System (INIS)

    Smith, Philip N.; Cobb, George P.; Godard-Codding, Celine; Hoff, Dale; McMurry, Scott T.; Rainwater, Thomas R.; Reynolds, Kevin D.

    2007-01-01

    Here we review mechanisms and factors influencing contaminant exposure among terrestrial vertebrate wildlife. There exists a complex mixture of biotic and abiotic factors that dictate potential for contaminant exposure among terrestrial and semi-terrestrial vertebrates. Chemical fate and transport in the environment determine contaminant bioaccessibility. Species-specific natural history characteristics and behavioral traits then play significant roles in the likelihood that exposure pathways, from source to receptor, are complete. Detailed knowledge of natural history traits of receptors considered in conjunction with the knowledge of contaminant behavior and distribution on a site are critical when assessing and quantifying exposure. We review limitations in our understanding of elements of exposure and the unique aspects of exposure associated with terrestrial and semi-terrestrial taxa. We provide insight on taxa-specific traits that contribute, or limit exposure to, transport phenomenon that influence exposure throughout terrestrial systems, novel contaminants, bioavailability, exposure data analysis, and uncertainty associated with exposure in wildlife risk assessments. Lastly, we identify areas related to exposure among terrestrial and semi-terrestrial organisms that warrant additional research. - Both biotic and abiotic factors determine chemical exposure for terrestrial vertebrates

  16. Three-dimensional imaging, change detection, and stability assessment during the centerline trench levee seepage experiment using terrestrial light detection and ranging technology, Twitchell Island, California, 2012

    Science.gov (United States)

    Bawden, Gerald W.; Howle, James; Bond, Sandra; Shriro, Michelle; Buck, Peter

    2014-01-01

    region that has a maximum subsidence of 3.5 cm over an area 0.75 m wide and 8.1 m long and is associated with a number of small fractures in the pavement that are predominately north-south-trending and parallel to the trench. We determined that there was no significant motion of the levee flank during the last week of the seepage test. We also determined biomorphic parameters for the landside tree, such as the 3D positioning on the levee, tree height, levee parallel/perpendicular cross sectional area, and canopy centroid. These biomorphic parameters were requested to support a University of California Berkeley team studying seepage and stability on the levee. A gridded, 2-cm bare-earth digital elevation model of the levee crown and the landside levee flank from the final terrestrial lidar (T-Lidar) survey provided detailed topographic data for future assessment. Because the T-Lidar was not integrated into the project design, other than an initial courtesy dataset to help characterize the levee surface, our ability to contribute to the overall science goals of the seepage test was limited. Therefore, our analysis focused on developing data collection and processing methodology necessary to align ultra high-resolution T-Lidar data (with an average spot spacing 2–3 millimeters on the levee crown) from several instrument setup locations to detect, measure, and characterize dynamic centimeter-scale deformation and surface changes during the seepage test.

  17. Fusion of LiDAR and aerial imagery for the estimation of downed tree volume using Support Vector Machines classification and region based object fitting

    Science.gov (United States)

    Selvarajan, Sowmya

    The study classifies 3D small footprint full waveform digitized LiDAR fused with aerial imagery to downed trees using Support Vector Machines (SVM) algorithm. Using small footprint waveform LiDAR, airborne LiDAR systems can provide better canopy penetration and very high spatial resolution. The small footprint waveform scanner system Riegl LMS-Q680 is addition with an UltraCamX aerial camera are used to measure and map downed trees in a forest. The various data preprocessing steps helped in the identification of ground points from the dense LiDAR dataset and segment the LiDAR data to help reduce the complexity of the algorithm. The haze filtering process helped to differentiate the spectral signatures of the various classes within the aerial image. Such processes, helped to better select the features from both sensor data. The six features: LiDAR height, LiDAR intensity, LiDAR echo, and three image intensities are utilized. To do so, LiDAR derived, aerial image derived and fused LiDAR-aerial image derived features are used to organize the data for the SVM hypothesis formulation. Several variations of the SVM algorithm with different kernels and soft margin parameter C are experimented. The algorithm is implemented to classify downed trees over a pine trees zone. The LiDAR derived features provided an overall accuracy of 98% of downed trees but with no classification error of 86%. The image derived features provided an overall accuracy of 65% and fusion derived features resulted in an overall accuracy of 88%. The results are observed to be stable and robust. The SVM accuracies were accompanied by high false alarm rates, with the LiDAR classification producing 58.45%, image classification producing 95.74% and finally the fused classification producing 93% false alarm rates The Canny edge correction filter helped control the LiDAR false alarm to 35.99%, image false alarm to 48.56% and fused false alarm to 37.69% The implemented classifiers provided a powerful tool for

  18. Clear-air lidar dark band

    Science.gov (United States)

    Girolamo, Paolo Di; Scoccione, Andrea; Cacciani, Marco; Summa, Donato; Schween, Jan H.

    2018-04-01

    This paper illustrates measurements carried out by the Raman lidar BASIL in the frame of HOPE, revealing the presence of a clear-air dark band phenomenon (i.e. the appearance of a minimum in lidar backscatter echoes) in the upper portion of the convective boundary layer. The phenomenon is clearly distinguishable in the lidar backscatter echoes at 1064 nm. This phenomenon is attributed to the presence of lignite aerosol particles advected from the surrounding open pit mines in the vicinity of the measuring site.

  19. What Good is Raman Water Vapor Lidar?

    Science.gov (United States)

    Whitman, David

    2011-01-01

    Raman lidar has been used to quantify water vapor in the atmosphere for various scientific studies including mesoscale meteorology and satellite validation. Now the international networks of NDACC and GRUAN have interest in using Raman water vapor lidar for detecting trends in atmospheric water vapor concentrations. What are the data needs for addressing these very different measurement challenges. We will review briefly the scientific needs for water vapor accuracy for each of these three applications and attempt to translate that into performance specifications for Raman lidar in an effort to address the question in the title of "What good is Raman water vapor Iidar."

  20. Multiangle lidar observations of the Atmosphere

    Science.gov (United States)

    Lalitkumar Prakash, Pawar; Choukiker, Yogesh Kumar; Raghunath, K.

    2018-04-01

    Atmospheric Lidars are used extensively to get aerosol parameters like backscatter coefficient, backscatter ratio etc. National Atmospheric Research Laboratory, Gadanki (13°N, 79°E), India has a powerful lidar which has alt-azimuth capability. Inversion method is applied to data from observations of lidar system at different azimuth and elevation angles. Data Analysis is described and Observations in 2D and 3D format are discussed. Presence of Cloud and the variation of backscatter parameters are seen in an interesting manner.

  1. Multiangle lidar observations of the Atmosphere

    Directory of Open Access Journals (Sweden)

    Lalitkumar Prakash Pawar

    2018-01-01

    Full Text Available Atmospheric Lidars are used extensively to get aerosol parameters like backscatter coefficient, backscatter ratio etc. National Atmospheric Research Laboratory, Gadanki (13°N, 79°E, India has a powerful lidar which has alt-azimuth capability. Inversion method is applied to data from observations of lidar system at different azimuth and elevation angles. Data Analysis is described and Observations in 2D and 3D format are discussed. Presence of Cloud and the variation of backscatter parameters are seen in an interesting manner.

  2. New Generation Lidar Technology and Applications

    Science.gov (United States)

    Spinhirne, James D.

    1999-01-01

    Lidar has been a tool for atmospheric research for several decades. Until recently routine operational use of lidar was not known. Problems have involved a lack of appropriate technology rather than a lack of applications. Within the last few years, lidar based on a new generation of solid state lasers and detectors have changed the situation. Operational applications for cloud and aerosol research applications are now well established. In these research applications, the direct height profiling capability of lidar is typically an adjunct to other types of sensing, both passive and active. Compact eye safe lidar with the sensitivity for ground based monitoring of all significant cloud and aerosol structure and the reliability to operate full time for several years is now in routine use. The approach is known as micro pulse lidar (MPL). For MPL the laser pulse repetition rate is in the kilohertz range and the pulse energies are in the micro-Joule range. The low pulse energy permits the systems to be eye safe and reliable with solid state lasers. A number of MPL systems have been deployed since 1992 at atmospheric research sites at a variety of global locations. Accurate monitoring of cloud and aerosol vertical distribution is a critical measurement for atmospheric radiation. An airborne application of lidar cloud and aerosol profiling is retrievals of parameters from combined lidar and passive sensing involving visible, infrared and microwave frequencies. A lidar based on a large pulse, solid state diode pumped ND:YAG laser has been deployed on the NASA ER-2 high altitude research aircraft along with multi-spectral visible/IR and microwave imaging radiometers since 1993. The system has shown high reliability in an extensive series of experimental projects for cloud remote sensing. The retrieval of cirrus radiation parameters is an effective application for combined lidar and passive sensing. An approved NASA mission will soon begin long term lidar observation of

  3. Wind measurement via direct detection lidar

    Science.gov (United States)

    Afek, I.; Sela, N.; Narkiss, N.; Shamai, G.; Tsadka, S.

    2013-10-01

    Wind sensing Lidar is considered a promising technology for high quality wind measurements required for various applications such as hub height wind resource assessment, power curve measurements and advanced, real time, forward looking turbine control. Until recently, the only available Lidar technology was based on coherent Doppler shift detection, whose market acceptance has been slow primarily due to its exuberant price. Direct detection Lidar technology provides an alternative to remote sensing of wind by incorporating high precision measurement, a robust design and an affordable price tag.

  4. Detectors for LIDAR type Thomson scattering diagnostics

    International Nuclear Information System (INIS)

    Hirsch, K.

    1991-04-01

    A report on the capability of the microchannel plate photomultiplier type (ITT F4128) presently used at the JET LIDAR Thomson Scattering System is given. Detailed investigation on time response, low noise amplification, shutter ratio, gating behaviour, linear mode of operation and saturation pulse recovery carried out during the design phase for LIDAR are presented. New investigation with respect to dc- and gated operation showed no measurable changes in sensitivity of this MCP photomultiplier. Comparing this type of detector with other MCP photomultipliers and with streak cameras some detection schemes for future LIDAR type diagnostic are proposed. (orig.)

  5. Detecting wind turbine wakes with nacelle lidars

    DEFF Research Database (Denmark)

    Held, D. P.; Larvol, A.; Mann, Jakob

    2017-01-01

    variance is used as a detection parameter for wakes. A one month long measurement campaign, where a continuous-wave lidar on a turbine has been exposed to multiple wake situations, is used to test the detection capabilities. The results show that it is possible to identify situation where a downstream...... turbine is in wake by comparing the peak widths. The used lidar is inexpensive and brings instalments on every turbine within economical reach. Thus, the information gathered by the lidars can be used for improved control at wind farm level....

  6. LIDAR for atmosphere research over Africa

    CSIR Research Space (South Africa)

    Sivakumar, V

    2008-11-01

    Full Text Available d’aéronomie, CNRS, Paris, France 1Email: SVenkataraman@csir.co.za – www.csir.co.za K-6665 [www.kashangroup.com] Lidar for atmospheric studies: The CSIR’s laser research into monitoring various pollutants in the lower atmosphere via... to lidar applications for atmosphere studies including pollutant monitoring. The following salient features emanated from the survey: • Around 80% of the lidars are in the northern hemisphere • Of the 20% in the southern hemisphere region...

  7. 2008 TIGER/Line Nationwide Dataset

    Data.gov (United States)

    California Natural Resource Agency — This dataset contains a nationwide build of the 2008 TIGER/Line datasets from the US Census Bureau downloaded in April 2009. The TIGER/Line Shapefiles are an extract...

  8. Unveiling topographical changes using LiDAR mapping capability: case study of Belaga in Sarawak, East-Malaysia

    Science.gov (United States)

    Ganendra, T. R.; Khan, N. M.; Razak, W. J.; Kouame, Y.; Mobarakeh, E. T.

    2016-06-01

    The use of Light Detection and Ranging (LiDAR) remote sensing technology to scan and map landscapes has proven to be one of the most popular techniques to accurately map topography. Thus, LiDAR technology is the ultimate method of unveiling the surface feature under dense vegetation, and, this paper intends to emphasize the diverse techniques that can be utilized to elucidate topographical changes over the study area, using multi-temporal airborne full waveform LiDAR datasets collected in 2012 and 2014. Full waveform LiDAR data offers access to an almost unlimited number of returns per shot, which enables the user to explore in detail topographical changes, such as vegetation growth measurement. The study also found out topography changes at the study area due to earthwork activities contributing to soil consolidation, soil erosion and runoff, requiring cautious monitoring. The implications of this study not only concurs with numerous investigations undertaken by prominent researchers to improve decision making, but also corroborates once again that investigations employing multi-temporal LiDAR data to unveil topography changes in vegetated terrains, produce more detailed and accurate results than most other remote sensing data.

  9. Handling Low-Density LiDAR Data: Calculating the Heights of Civil Constructions and the Accuracy Expected

    Directory of Open Access Journals (Sweden)

    Rubén Martínez Marín

    2013-01-01

    Full Text Available During the last years, in many developed countries, administrations and private companies have devoted considerable amounts of money to obtain mapping data using airborne LiDAR. For many civil activities, we can take advantage of it, since those data are available with no cost. Some important questions arise: Are those data good enough to be used for determining the heights of the civil constructions with the accuracy we need in some civil work? What accuracy can we expect when using low-density LiDAR data (0.5 pts/m2? In order to answer those questions, we have developed a specific methodology based on establishing a set of control points on the top of several constructions and calculating the elevation of each one using postprocessing GPS. Those results have been taken as correct values and the comparison between those values and the elevations obtained, assigning values to the control points by the interpolation of the LiDAR dataset, has been carried out. This paper shows the results obtained using low-density airborne LiDAR data and the accuracy obtained. Results have shown that LiDAR can be accurate enough (10–25 cm to determine the height of civil constructions and apply those data in many civil engineering activities.

  10. Satellite-Based Precipitation Datasets

    Science.gov (United States)

    Munchak, S. J.; Huffman, G. J.

    2017-12-01

    Of the possible sources of precipitation data, those based on satellites provide the greatest spatial coverage. There is a wide selection of datasets, algorithms, and versions from which to choose, which can be confusing to non-specialists wishing to use the data. The International Precipitation Working Group (IPWG) maintains tables of the major publicly available, long-term, quasi-global precipitation data sets (http://www.isac.cnr.it/ ipwg/data/datasets.html), and this talk briefly reviews the various categories. As examples, NASA provides two sets of quasi-global precipitation data sets: the older Tropical Rainfall Measuring Mission (TRMM) Multi-satellite Precipitation Analysis (TMPA) and current Integrated Multi-satellitE Retrievals for Global Precipitation Measurement (GPM) mission (IMERG). Both provide near-real-time and post-real-time products that are uniformly gridded in space and time. The TMPA products are 3-hourly 0.25°x0.25° on the latitude band 50°N-S for about 16 years, while the IMERG products are half-hourly 0.1°x0.1° on 60°N-S for over 3 years (with plans to go to 16+ years in Spring 2018). In addition to the precipitation estimates, each data set provides fields of other variables, such as the satellite sensor providing estimates and estimated random error. The discussion concludes with advice about determining suitability for use, the necessity of being clear about product names and versions, and the need for continued support for satellite- and surface-based observation.

  11. Extensive Sampling of Forest Carbon using High Density Power Line Lidar

    Science.gov (United States)

    Hampton, H. M.; Chen, Q.; Dye, D. G.; Hungate, B. A.

    2013-12-01

    unmanaged areas, using high point density lidar collected over transmission line corridors. The lidar metric of quadratic mean height guided our selection of field plots spanning the full range from low to high levels of aboveground biomass across the study region. Before model selection, we minimized two of the major sources of errors in lidar calibration: variance in tree allometry across landscapes and plot edge effects (spatial mismatch between field measurements and lidar points). We tested an assortment of model selection techniques and goodness of fit measures for deriving forest structural metrics of interest. For example, we obtained an R-squared value for aboveground biomass (Mg/ha) of 0.9 using stepwise regression. The forest metrics obtained are being used in the next stage of the project to parameterize biogeochemical models linking terrestrial carbon pools and atmospheric greenhouse gas exchanges.

  12. Terrestrial Water Storage

    Science.gov (United States)

    Rodell, M.; Chambers, D. P.; Famiglietti, J. S.

    2015-01-01

    During 2014 dryness continued in the Northern Hemisphere and relative wetness continued in the Southern Hemisphere (Fig. 2.21; Plate 2.1g). These largely canceled out such that the global land surface began and ended the year with a terrestrial water storage (TWS) anomaly slightly below 0 cm (equivalent height of water; Fig. 2.22). TWS is the sum of groundwater, soil moisture, surface water, snow, and ice. Groundwater responds more slowly to meteorological phenomena than the other components because the overlying soil acts as a low pass filter, but often it has a larger range of variability on multiannual timescales (Rodell and Famiglietti 2001; Alley et al. 2002).In situ groundwater data are only archived and made and Tanzania. The rest of the continent experienced mixed to dry conditions. Significant reductions in TWS in Greenland, Antarctica, and southern coastal Alaska reflect ongoing ice sheet and glacier ablation, not groundwater depletion.

  13. Introduction of a simple-model-based land surface dataset for Europe

    Science.gov (United States)

    Orth, Rene; Seneviratne, Sonia I.

    2015-04-01

    Land surface hydrology can play a crucial role during extreme events such as droughts, floods and even heat waves. We introduce in this study a new hydrological dataset for Europe that consists of soil moisture, runoff and evapotranspiration (ET). It is derived with a simple water balance model (SWBM) forced with precipitation, temperature and net radiation. The SWBM dataset extends over the period 1984-2013 with a daily time step and 0.5° × 0.5° resolution. We employ a novel calibration approach, in which we consider 300 random parameter sets chosen from an observation-based range. Using several independent validation datasets representing soil moisture (or terrestrial water content), ET and streamflow, we identify the best performing parameter set and hence the new dataset. To illustrate its usefulness, the SWBM dataset is compared against several state-of-the-art datasets (ERA-Interim/Land, MERRA-Land, GLDAS-2-Noah, simulations of the Community Land Model Version 4), using all validation datasets as reference. For soil moisture dynamics it outperforms the benchmarks. Therefore the SWBM soil moisture dataset constitutes a reasonable alternative to sparse measurements, little validated model results, or proxy data such as precipitation indices. Also in terms of runoff the SWBM dataset performs well, whereas the evaluation of the SWBM ET dataset is overall satisfactory, but the dynamics are less well captured for this variable. This highlights the limitations of the dataset, as it is based on a simple model that uses uniform parameter values. Hence some processes impacting ET dynamics may not be captured, and quality issues may occur in regions with complex terrain. Even though the SWBM is well calibrated, it cannot replace more sophisticated models; but as their calibration is a complex task the present dataset may serve as a benchmark in future. In addition we investigate the sources of skill of the SWBM dataset and find that the parameter set has a similar

  14. Frequency Stepped Pulse Train Modulated Wind Sensing Lidar

    DEFF Research Database (Denmark)

    Olesen, Anders Sig; Pedersen, Anders Tegtmeier; Rottwitt, Karsten

    2011-01-01

    of frequency shifts corresponding to a specific distance. The spatial resolution depends on the repetition rate of the pulses in the pulse train. Directional wind measurements are shown and compared to a CW lidar measurement. The carrier to noise ratio of the FSPT lidar compared to a CW lidar is discussed......In this paper a wind sensing lidar utilizing a Frequency Stepped Pulse Train (FSPT) is demonstrated. One of the advantages in the FSTP lidar is that it enables direct measurement of wind speed as a function of distance from the lidar. Theoretically the FSPT lidar continuously produces measurements...... as is the case with a CW lidar, but at the same time with a spatial resolution, and without the range ambiguity originating from e.g. clouds. The FSPT lidar utilizes a frequency sweeping source for generation of the FSPT. The source generates a pulse train where each pulse has an optical carrier frequency...

  15. System, method, and apparatus for remote measurement of terrestrial biomass

    Science.gov (United States)

    Johnson, Patrick W [Jefferson, MD

    2011-04-12

    A system, method, and/or apparatus for remote measurement of terrestrial biomass contained in vegetative elements, such as large tree boles or trunks present in an area of interest, are provided. The method includes providing an airborne VHF radar system in combination with a LiDAR system, overflying the area of interest while directing energy toward the area of interest, using the VHF radar system to collect backscatter data from the trees as a function of incidence angle and frequency, and determining a magnitude of the biomass from the backscatter data and data from the laser radar system for each radar resolution cell. A biomass map is generated showing the magnitude of the biomass of the vegetative elements as a function of location on the map by using each resolution cell as a unique location thereon. In certain preferred embodiments, a single frequency is used with a linear array antenna.

  16. 2010 Northwestern Hawaiian Islands Lidar - Midway Atoll

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the...

  17. 2010 Northwestern Hawaiian Islands Lidar - Laysan Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the...

  18. 2012 OLC Lidar: West Metro, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has collected Light Detection and Ranging (LiDAR) data of the Oregon West Metro Study Area for the Oregon Department of Geology and Mineral Industries (DOGAMI)....

  19. 2012 OLC Lidar DEM: West Metro, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — WSI has collected Light Detection and Ranging (LiDAR) data of the Oregon West Metro Study Area for the Oregon Department of Geology and Mineral Industries (DOGAMI)....

  20. 2013 South Carolina DNR Lidar: Greenville County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Atlantic Group provided high accuracy, calibrated multiple return LiDAR for roughly 1,510 square miles covering both Greenville and Spartanburg counties, South...

  1. 2006 NOAA Bathymetric Lidar: Puerto Rico (Southwest)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set (Project Number OPR-I305-KRL-06) depicts depth values (mean 5 meter gridded) collected using LiDAR (Light Detection & Ranging) from the shoreline...

  2. 2004 Harrison County, Mississippi Lidar Mapping

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata record describes the topographic mapping of Harrison County, Mississippi in March of 2004. Products generated include lidar point clouds in .LAS format...

  3. 2015 Cook & Tift County (GA) Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: NOAA OCM Tift and Cook Counties GA Lidar Data Acquisition and Processing Production Task NOAA Contract No. EA133C-11-CQ-0010 Woolpert Order No. 75271...

  4. 2010 ARRA Lidar: Golden Gate (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Golden Gate LiDAR Project is a cooperative project sponsored by the US Geological Survey (USGS) and San Francisco State University (SFSU) that has resulted in...

  5. 2012 USGS Lidar: Brooks Camp (AK)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) had a requirement for high resolution Lidar needed for mapping the Brooks Camp region of Katmai National Park in Alaska....

  6. 2005 Oahu/Maui Lidar Mapping Project

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. Using a combination of laser rangefinding, GPS positioning...

  7. 2004 USGS Lidar: San Francisco Bay (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Lidar (Light detection and ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format....

  8. 2010 ARRA Lidar: Eleven County Virginia

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Terrapoint and LMSI collected LiDAR for over 2,572 square miles in Northumberland, Lancaster, Middlesex, King and Queen, Matthews, Gloucester, James City,...

  9. 2012 South Carolina DNR Lidar: Edgefield County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Towill Inc. collected LiDAR for over 3,300 square miles in Calhoun, Aiken, Barnwell, Edgefield, McCormick, and Abbeville counties in South Carolina. This metadata...

  10. 2007 Sumpter Powder River Mine Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. (WS) collected Light Detection and Ranging (LiDAR) data for the USDA Forest Service on September 17, 2007. The project covers an 8-mile...

  11. 2009 - 2011 OLC Lidar DEM: Deschutes (OR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. collected Light Detection and Ranging (LiDAR) data of the Deschutes Study Area for the Oregon Department of Geology and Mineral Industries...

  12. 2008 USGS New Jersey Lidar: Somerset County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These data support the general geospatial needs of the USGS and other federal agencies. LiDAR data is remotely sensed high-resolution elevation data collected by an...

  13. 2016 USGS Lidar: Maine QL2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Product: This lidar data set includes classified LAS files, breaklines, digital elevation models (DEMs), intensity imagery, and contours. Geographic Extent: Four...

  14. 2013 South Carolina DNR Lidar: Beaufort County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LMSI provided high accuracy, calibrated multiple return LiDAR for roughly 785 square miles covering Beaufort County, South Carolina. The nominal point spacing for...

  15. 2004 FEMA Lidar: Blackstone (MA & RI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The LIDAR-derived data was collected in the Blackstone River area. This data supports the Federal Emergency Management Agency's specifications for mapping...

  16. Nonlinear filtering for LIDAR signal processing

    Directory of Open Access Journals (Sweden)

    D. G. Lainiotis

    1996-01-01

    Full Text Available LIDAR (Laser Integrated Radar is an engineering problem of great practical importance in environmental monitoring sciences. Signal processing for LIDAR applications involves highly nonlinear models and consequently nonlinear filtering. Optimal nonlinear filters, however, are practically unrealizable. In this paper, the Lainiotis's multi-model partitioning methodology and the related approximate but effective nonlinear filtering algorithms are reviewed and applied to LIDAR signal processing. Extensive simulation and performance evaluation of the multi-model partitioning approach and its application to LIDAR signal processing shows that the nonlinear partitioning methods are very effective and significantly superior to the nonlinear extended Kalman filter (EKF, which has been the standard nonlinear filter in past engineering applications.

  17. 2011 USGS Lidar: Orange County (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR (Light Detection and Ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format....

  18. 2012 South Carolina DNR Lidar: Calhoun County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Towill Inc. collected LiDAR for over 3,300 square miles in Calhoun, Aiken, Barnwell, Edgefield, McCormick, and Abbeville counties in South Carolina. This metadata...

  19. 2011 FEMA Lidar: Southern Virginia Cities

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Dewberry collected LiDAR for ~3,341 square miles in various Virginia Counties, a part of Worcester County, and Hooper's Island. The acquisition was performed by...

  20. 2013 South Carolina DNR Lidar: Spartanburg County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The Atlantic Group provided high accuracy, calibrated multiple return LiDAR for roughly 1,510 square miles covering both Greenville and Spartanburg counties, South...

  1. 2010 USGS Lidar: Salton Sea (CA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The USGS Salton Sea project encompasses a 5-kilometer buffer around the Salton Sea, California. Dewberry classified LiDAR for a project boundary that touches 623...

  2. 2014 USACE NCMP Topobathy Lidar DEM: Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — These Digital Elevation Model (DEM) files contain rasterized topobathy lidar elevations at a 1 m grid size, generated from data collected by the Coastal Zone Mapping...

  3. 2010 South Carolina DNR Lidar: Sumter County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Provide high density LiDAR elevation data map of Sumter County, SC. Provide Bare Earth DEM (vegetation removal) of Sumter County, SC.

  4. 2010 South Carolina DNR Lidar: Richland County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Provide high density LiDAR elevation data map of Richland County, SC. Provide Bare Earth DEM (vegetation removal) of Richland County, SC.

  5. 2015 City of Portland, Maine, Lidar

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — 2015 City of Portland Maine Lidar Data Acquisition and Processing Woolpert Order No. 75564 Contractor: Woolpert, Inc. This task is for a high resolution data set of...

  6. 2016 Martin County QL2 Lidar (FL)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Martin County FL QL2 Lidar Acquisition and Processing Production Task Task Order No. G14PS00574 Woolpert Order No. 76001 Contractor: Woolpert, Inc. This task is for...

  7. VT Data - Lidar 1ft Contours

    Data.gov (United States)

    Vermont Center for Geographic Information — (Link to Metadata) This metadata applies to contours derived from Quality Level 2 (QL2) Lidar 'collections' with a resolution (RESCLASS) of 0.7m. For an overview of...

  8. 2009 - 2011 OLC Lidar: Deschutes (OR)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Watershed Sciences, Inc. collected Light Detection and Ranging (LiDAR) data of the Deschutes Study Area for the Oregon Department of Geology and Mineral Industries...

  9. 2005 NCFMP Lidar: NC Statewide Phase 3

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Airborne LIDAR terrain mapping data acquired March through April 2005. These data sets may represent a single geographic tile of a larger, county/sub-county data...

  10. 2015 NOAA Lidar: Pelekane Watershed (HI)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This metadata describes the Digital Elevation Model (DEM) 1 meter products derived from the airborne LiDAR data collected in August of 2015 for the Pelekane...

  11. 2006 FEMA Lidar: Rhode Island Coastline

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

  12. 2010 South Carolina DNR Lidar: Kershaw County

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Provide high density LiDAR elevation data map of Kershaw County, SC. Provide Bare Earth DEM (vegetation removal) of Kershaw County, SC.

  13. 2010 Northwestern Hawaiian Islands Lidar - Kure Atoll

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the...

  14. 2010 Northwestern Hawaiian Islands Lidar - Lisianki Island

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — The U.S. Geological Survey (USGS) contracted with Hawaii-based Aerial Surveying, Inc. to collect lidar-derived elevation data over the low-lying areas within the...

  15. 2003 NCFMP Lidar: NC Statewide Phase 2

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Airborne LIDAR terrain mapping data acquired January through March 2003. Point data (XYZ) in ASCII format. Horizontal datum NAD83(1995) North Carolina State Plane...

  16. Lidar instruments for ESA Earth observation missions

    Science.gov (United States)

    Hélière, Arnaud; Armandillo, Errico; Durand, Yannig; Culoma, Alain; Meynart, Roland

    2017-11-01

    The idea of deploying a lidar system on an Earthorbiting satellite stems from the need for continuously providing profiles of our atmospheric structure with high accuracy and resolution and global coverage. Interest in this information for climatology, meteorology and the atmospheric sciences in general is huge. Areas of application range from the determination of global warming and greenhouse effects, to monitoring the transport and accumulation of pollutants in the different atmospheric regions (such as the recent fires in Southeast Asia), to the assessment of the largely unknown microphysical properties and the structural dynamics of the atmosphere itself. Spaceborne lidar systems have been the subject of extensive investigations by the European Space Agency since mid 1970's, resulting in mission and instrument concepts, such as ATLID, the cloud backscatter lidar payload of the EarthCARE mission, ALADIN, the Doppler wind lidar of the Atmospheric Dynamics Mission (ADM) and more recently a water vapour Differential Absorption Lidar considered for the WALES mission. These studies have shown the basic scientific and technical feasibility of spaceborne lidars, but they have also demonstrated their complexity from the instrument viewpoint. As a result, the Agency undertook technology development in order to strengthen the instrument maturity. This is the case for ATLID, which benefited from a decade of technology development and supporting studies and is now studied in the frame of the EarthCARE mission. ALADIN, a Direct Detection Doppler Wind Lidar operating in the Ultra -Violet, will be the 1st European lidar to fly in 2007 as payload of the Earth Explorer Core Mission ADM. WALES currently studied at the level of a phase A, is based upon a lidar operating at 4 wavelengths in near infrared and aims to profile the water vapour in the lower part of the atmosphere with high accuracy and low bias. Lastly, the European Space Agency is extending the lidar instrument field

  17. Evaluation of the Wind Flow Variability Using Scanning Doppler Lidar Measurements

    Science.gov (United States)

    Sand, S. C.; Pichugina, Y. L.; Brewer, A.

    2016-12-01

    Better understanding of the wind flow variability at the heights of the modern turbines is essential to accurately assess of generated wind power and efficient turbine operations. Nowadays the wind energy industry often utilizes scanning Doppler lidar to measure wind-speed profiles at high spatial and temporal resolution.The study presents wind flow features captured by scanning Doppler lidars during the second Wind Forecast and Improvement Project (WFIP 2) sponsored by the Department of Energy (DOE) and National Oceanic and Atmospheric Administration (NOAA). This 18-month long experiment in the Columbia River Basin aims to improve model wind forecasts complicated by mountain terrain, coastal effects, and numerous wind farms.To provide a comprehensive dataset to use for characterizing and predicting meteorological phenomena important to Wind Energy, NOAA deployed scanning, pulsed Doppler lidars to two sites in Oregon, one at Wasco, located upstream of all wind farms relative to the predominant westerly flow in the region, and one at Arlington, located in the middle of several wind farms.In this presentation we will describe lidar scanning patterns capable of providing data in conical, or vertical-slice modes. These individual scans were processed to obtain 15-min averaged profiles of wind speed and direction in real time. Visualization of these profiles as time-height cross sections allows us to analyze variability of these parameters with height, time and location, and reveal periods of rapid changes (ramp events). Examples of wind flow variability between two sites of lidar measurements along with examples of reduced wind velocity downwind of operating turbines (wakes) will be presented.

  18. Effect of multiple scattering on lidar measurements

    International Nuclear Information System (INIS)

    Cohen, A.

    1977-01-01

    The lidar equation in its standard form involves the assumption that the scattered irradiance reaching the lidar receiver has been only singly scattered. However, in the cases of scattering from clouds and thick aerosol layers, it is shown that multiple scattering cannot be neglected. An experimental method for the detection of multiple scattering by depolarization measurement techniques is discussed. One method of theoretical calculations of double-scattering is presented and discussed

  19. A New Framework for Quantifying Lidar Uncertainty

    Energy Technology Data Exchange (ETDEWEB)

    Newman, Jennifer, F.; Clifton, Andrew; Bonin, Timothy A.; Churchfield, Matthew J.

    2017-03-24

    As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards discuss uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device. However, real-world experience has shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we propose the development of a new lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from an operational wind farm to assess the ability of the framework to predict errors in lidar-measured wind speed.

  20. Heterodyne lidar for chemical sensing

    International Nuclear Information System (INIS)

    Oldenborg, Richard C.; Tiee, Joe J.; Shimada, Tsutomu; Wilson, Carl W.; Remelius, Dennis K.; Fox, Jay; Swim, Cynthia

    2004-01-01

    The overall objective is to assess the detection performance of LWIR (long wavelength infrared) coherent Lidar systems that potentially possess enhanced effluent detection capabilities. Previous work conducted by Los Alamos has demonstrated that infrared DIfferential Absorption Lidar (DIAL) is capable of detecting chemicals in plumes from long standoff ranges. Our DIAL approach relied on the reflectivity of topographical targets to provide a strong return signal. With the inherent advantage of applying heterodyne transceivers to approach single-photon detection in LWIR, it is projected that marked improvements in detection range or in spatial coverage can be attained. In some cases, the added photon detection sensitivity could be utilized for sensing 'soft targets', such as atmospheric and threat aerosols where return signal strength is drastically reduced, as opposed to topographical targets. This would allow range resolved measurements and could lead to the mitigation of the limiting source of noise due to spectral/spatial/temporal variability of the ground scene. The ability to distinguish normal variations in the background from true chemical signatures is crucial to the further development of sensitive remote chemical sensing technologies. One main difficulty in demonstrating coherent DIAL detection is the development of suitable heterodyne transceivers that can achieve rapid multi-wavelength tuning required for obtaining spectral signature information. LANL has recently devised a novel multi-wavelength heterodyne transceiver concept that addresses this issue. A 5-KHz prototype coherent CO 2 transceiver has been constructed and is being now used to help address important issues in remote CBW agent standoff detection. Laboratory measurements of signal-to-noise ratio (SNR) will be reported. Since the heterodyne detection scheme fundamentally has poor shot-to-shot signal statistics, in order to achieve sensitive detection limits, favorable averaging statistics

  1. PHYSICS PERFORMANCE AND DATASET (PPD)

    CERN Multimedia

    L. Silvestris

    2012-01-01

      Introduction The first part of the year presented an important test for the new Physics Performance and Dataset (PPD) group (cf. its mandate: http://cern.ch/go/8f77). The activity was focused on the validation of the new releases meant for the Monte Carlo (MC) production and the data-processing in 2012 (CMSSW 50X and 52X), and on the preparation of the 2012 operations. In view of the Chamonix meeting, the PPD and physics groups worked to understand the impact of the higher pile-up scenario on some of the flagship Higgs analyses to better quantify the impact of the high luminosity on the CMS physics potential. A task force is working on the optimisation of the reconstruction algorithms and on the code to cope with the performance requirements imposed by the higher event occupancy as foreseen for 2012. Concerning the preparation for the analysis of the new data, a new MC production has been prepared. The new samples, simulated at 8 TeV, are already being produced and the digitisation and recons...

  2. Pattern Analysis On Banking Dataset

    Directory of Open Access Journals (Sweden)

    Amritpal Singh

    2015-06-01

    Full Text Available Abstract Everyday refinement and development of technology has led to an increase in the competition between the Tech companies and their going out of way to crack the system andbreak down. Thus providing Data mining a strategically and security-wise important area for many business organizations including banking sector. It allows the analyzes of important information in the data warehouse and assists the banks to look for obscure patterns in a group and discover unknown relationship in the data.Banking systems needs to process ample amount of data on daily basis related to customer information their credit card details limit and collateral details transaction details risk profiles Anti Money Laundering related information trade finance data. Thousands of decisionsbased on the related data are taken in a bank daily. This paper analyzes the banking dataset in the weka environment for the detection of interesting patterns based on its applications ofcustomer acquisition customer retention management and marketing and management of risk fraudulence detections.

  3. PHYSICS PERFORMANCE AND DATASET (PPD)

    CERN Multimedia

    L. Silvestris

    2013-01-01

    The PPD activities, in the first part of 2013, have been focused mostly on the final physics validation and preparation for the data reprocessing of the full 8 TeV datasets with the latest calibrations. These samples will be the basis for the preliminary results for summer 2013 but most importantly for the final publications on the 8 TeV Run 1 data. The reprocessing involves also the reconstruction of a significant fraction of “parked data” that will allow CMS to perform a whole new set of precision analyses and searches. In this way the CMSSW release 53X is becoming the legacy release for the 8 TeV Run 1 data. The regular operation activities have included taking care of the prolonged proton-proton data taking and the run with proton-lead collisions that ended in February. The DQM and Data Certification team has deployed a continuous effort to promptly certify the quality of the data. The luminosity-weighted certification efficiency (requiring all sub-detectors to be certified as usab...

  4. Comparison of stratospheric temperature profiles from a ground-based microwave radiometer with lidar, radiosonde and satellite data

    Science.gov (United States)

    Navas-Guzmán, Francisco; Kämpfer, Niklaus; Haefele, Alexander; Keckhut, Philippe; Hauchecorne, Alain

    2015-04-01

    The importance of the knowledge of the temperature structure in the atmosphere has been widely recognized. Temperature is a key parameter for dynamical, chemical and radiative processes in the atmosphere. The cooling of the stratosphere is an indicator for climate change as it provides evidence of natural and anthropogenic climate forcing just like surface warming ( [1] and references therein). However, our understanding of the observed stratospheric temperature trend and our ability to test simulations of the stratospheric response to emissions of greenhouse gases and ozone depleting substances remains limited. Stratospheric long-term datasets are sparse and obtained trends differ from one another [1]. Therefore it is important that in the future such datasets are generated. Different techniques allow to measure stratospheric temperature profiles as radiosonde, lidar or satellite. The main advantage of microwave radiometers against these other instruments is a high temporal resolution with a reasonable good spatial resolution. Moreover, the measurement at a fixed location allows to observe local atmospheric dynamics over a long time period, which is crucial for climate research. TEMPERA (TEMPERature RAdiometer) is a newly developed ground-based microwave radiometer designed, built and operated at the University of Bern. The instrument and the retrieval of temperature profiles has been described in detail in [2]. TEMPERA is measuring a pressure broadened oxygen line at 53.1 GHz in order to determine stratospheric temperature profiles. The retrieved profiles of TEMPERA cover an altitude range of approximately 20 to 45 km with a vertical resolution in the order of 15 km. The lower limit is given by the instrumental baseline and the bandwidth of the measured spectrum. The upper limit is given by the fact that above 50 km the oxygen lines are splitted by the Zeeman effect in the terrestrial magnetic field. In this study we present a comparison of stratospheric

  5. Establishing macroecological trait datasets: digitalisation, extrapolation and validation of diet preferences in terrestrial mammals worldwide

    NARCIS (Netherlands)

    Kissling, W.D.; Dalby, L.; Fløjgaard, C.; Lenoir, J.; Sandel, B.; Sandom, C.; Trøjelsgaard, K.; Svenning, J.-C.

    2014-01-01

    Ecological trait data are essential for understanding the broad-scale distribution of biodiversity and its response to global change. For animals, diet represents a fundamental aspect of species’ evolutionary adaptations, ecological and functional roles, and trophic interactions. However, the

  6. Detection and classification of pole-like road objects from mobile LiDAR data in motorway environment

    Science.gov (United States)

    Yan, Li; Li, Zan; Liu, Hua; Tan, Junxiang; Zhao, Sainan; Chen, Changjun

    2017-12-01

    Mobile LiDAR Scanning (MLS) can collect 3-dimensional (3D) road and road-related geospatial information accurately and efficiently. Pole-like objects located in road environment are important street furniture and they are necessary information in road inventory and road mapping. The automatic detection and classification of pole-like road objects from mobile LiDAR data can greatly reduce the cost and improve the efficiency. This paper provides a complete workflow for the detection and classification of pole-like road objects from mobile LiDAR data in motorway environment. The major workflow includes three steps: data preprocessing, pole-like road objects detection and pole-like road objects classification. In data preprocessing step, ground points are removed by an automatic ground filtering algorithm, and then off-ground points are clustered into segments and the overlapped segments containing pole-like road objects are further separated through an iterative min-cut based segmentation approach. In detection step, filters utilizing both prior and shape information are used to detect the target objects. In classification step, features of objects are calculated and classified using Random Forest classifier. Our method was tested on two datasets scanned in motorway environment, and the results showed that the Matthews correlation coefficient of the two datasets in detection step was 93.7% and 95.9% respectively and the overall accuracy of the two datasets in classification step was 96.5% and 97.9% respectively.

  7. Comparison of the filtering models for airborne LiDAR data by three classifiers with exploration on model transfer

    Science.gov (United States)

    Ma, Hongchao; Cai, Zhan; Zhang, Liang

    2018-01-01

    This paper discusses airborne light detection and ranging (LiDAR) point cloud filtering (a binary classification problem) from the machine learning point of view. We compared three supervised classifiers for point cloud filtering, namely, Adaptive Boosting, support vector machine, and random forest (RF). Nineteen features were generated from raw LiDAR point cloud based on height and other geometric information within a given neighborhood. The test datasets issued by the International Society for Photogrammetry and Remote Sensing (ISPRS) were used to evaluate the performance of the three filtering algorithms; RF showed the best results with an average total error of 5.50%. The paper also makes tentative exploration in the application of transfer learning theory to point cloud filtering, which has not been introduced into the LiDAR field to the authors' knowledge. We performed filtering of three datasets from real projects carried out in China with RF models constructed by learning from the 15 ISPRS datasets and then transferred with little to no change of the parameters. Reliable results were achieved, especially in rural area (overall accuracy achieved 95.64%), indicating the feasibility of model transfer in the context of point cloud filtering for both easy automation and acceptable accuracy.

  8. Tidally Heated Terrestrial Exoplanets

    Science.gov (United States)

    Henning, Wade Garrett

    This work models the surface and internal temperatures for hypothetical terrestrial planets in situations involving extreme tidal heating. The feasibility of such planets is evaluated in terms of the orbital perturbations that may give rise to them, their required proximity to a hoststar, and the potential for the input tidal heating to cause significant partial melting of the mantle. Trapping terrestrial planets into 2:1 resonances with migrating Hot Jupiters is considered as a reasonable way for Earth-like worlds to both maintain high eccentricities and to move to short enough orbital periods (1-20 days) for extreme tidal heating to occur. Secular resonance and secular orbital perturbations may support moderate tidal heating at a low equilibrium eccentricity. At orbital periods below 10-30 days, with eccentricities from 0.01 to 0.1, tidal heat may greatly exceed radiogenic heat production. It is unlikely to exceed insolation, except when orbiting very low luminosity hosts, and thus will have limited surface temperature expression. Observations of such bodies many not be able to detect tidal surface enhancements given a few percent uncertainty in albedo, except on the nightside of spin synchronous airless objects. Otherwise detection may occur via spectral detection of hotspots or high volcanic gas concentrations including sulfur dioxide and hydrogen sulfide. The most extreme cases may be able to produce magma oceans, or magma slush mantles with up to 40-60% melt fractions. Tides may alter the habitable zones for smaller red dwarf stars, but are generally detrimental. Multiple viscoelastic models, including the Maxwell, Voigt-Kelvin, Standard Anelastic Solid, and Burgers rheologies are explored and applied to objects such as Io and the super-Earth planet GJ 876d. The complex valued Love number for the Burgers rheology is derived and found to be a useful improvement when modeling the low temperature behavior of tidal bodies, particularly during low eccentricity

  9. Automatic building extraction from LiDAR data fusion of point and grid-based features

    Science.gov (United States)

    Du, Shouji; Zhang, Yunsheng; Zou, Zhengrong; Xu, Shenghua; He, Xue; Chen, Siyang

    2017-08-01

    This paper proposes a method for extracting buildings from LiDAR point cloud data by combining point-based and grid-based features. To accurately discriminate buildings from vegetation, a point feature based on the variance of normal vectors is proposed. For a robust building extraction, a graph cuts algorithm is employed to combine the used features and consider the neighbor contexture information. As grid feature computing and a graph cuts algorithm are performed on a grid structure, a feature-retained DSM interpolation method is proposed in this paper. The proposed method is validated by the benchmark ISPRS Test Project on Urban Classification and 3D Building Reconstruction and compared to the state-art-of-the methods. The evaluation shows that the proposed method can obtain a promising result both at area-level and at object-level. The method is further applied to the entire ISPRS dataset and to a real dataset of the Wuhan City. The results show a completeness of 94.9% and a correctness of 92.2% at the per-area level for the former dataset and a completeness of 94.4% and a correctness of 95.8% for the latter one. The proposed method has a good potential for large-size LiDAR data.

  10. Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

    Science.gov (United States)

    Vierling, Lee A.; Vierling, Kerri T.; Adam, Patrick; Hudak, Andrew T.

    2013-01-01

    Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2

  11. Doppler lidar sensor for precision navigation in GPS-deprived environment

    Science.gov (United States)

    Amzajerdian, F.; Pierrottet, D. F.; Hines, G. D.; Petway, L. B.; Barnes, B. W.

    2013-05-01

    Landing mission concepts that are being developed for exploration of solar system bodies are increasingly ambitious in their implementations and objectives. Most of these missions require accurate position and velocity data during their descent phase in order to ensure safe, soft landing at the pre-designated sites. Data from the vehicle's Inertial Measurement Unit will not be sufficient due to significant drift error after extended travel time in space. Therefore, an onboard sensor is required to provide the necessary data for landing in the GPS-deprived environment of space. For this reason, NASA Langley Research Center has been developing an advanced Doppler lidar sensor capable of providing accurate and reliable data suitable for operation in the highly constrained environment of space. The Doppler lidar transmits three laser beams in different directions toward the ground. The signal from each beam provides the platform velocity and range to the ground along the laser line-of-sight (LOS). The six LOS measurements are then combined in order to determine the three components of the vehicle velocity vector, and to accurately measure altitude and attitude angles relative to the local ground. These measurements are used by an autonomous Guidance, Navigation, and Control system to accurately navigate the vehicle from a few kilometers above the ground to the designated location and to execute a gentle touchdown. A prototype version of our lidar sensor has been completed for a closed-loop demonstration onboard a rocket-powered terrestrial free-flyer vehicle.

  12. Capability Assessment and Performance Metrics for the Titan Multispectral Mapping Lidar

    Directory of Open Access Journals (Sweden)

    Juan Carlos Fernandez-Diaz

    2016-11-01

    Full Text Available In this paper we present a description of a new multispectral airborne mapping light detection and ranging (lidar along with performance results obtained from two years of data collection and test campaigns. The Titan multiwave lidar is manufactured by Teledyne Optech Inc. (Toronto, ON, Canada and emits laser pulses in the 1550, 1064 and 532 nm wavelengths simultaneously through a single oscillating mirror scanner at pulse repetition frequencies (PRF that range from 50 to 300 kHz per wavelength (max combined PRF of 900 kHz. The Titan system can perform simultaneous mapping in terrestrial and very shallow water environments and its multispectral capability enables new applications, such as the production of false color active imagery derived from the lidar return intensities and the automated classification of target and land covers. Field tests and mapping projects performed over the past two years demonstrate capabilities to classify five land covers in urban environments with an accuracy of 90%, map bathymetry under more than 15 m of water, and map thick vegetation canopies at sub-meter vertical resolutions. In addition to its multispectral and performance characteristics, the Titan system is designed with several redundancies and diversity schemes that have proven to be beneficial for both operations and the improvement of data quality.

  13. Towards lidar-based mapping of tree age at the Arctic forest tundra ecotone.

    Science.gov (United States)

    Jensen, J.; Maguire, A.; Oelkers, R.; Andreu-Hayles, L.; Boelman, N.; D'Arrigo, R.; Griffin, K. L.; Jennewein, J. S.; Hiers, E.; Meddens, A. J.; Russell, M.; Vierling, L. A.; Eitel, J.

    2017-12-01

    Climate change may cause spatial shifts in the forest-tundra ecotone (FTE). To improve our ability to study these spatial shifts, information on tree demography along the FTE is needed. The objective of this study was to assess the suitability of lidar derived tree heights as a surrogate for tree age. We calculated individual tree age from 48 tree cores collected at basal height from white spruce (Picea glauca) within the FTE in northern Alaska. Tree height was obtained from terrestrial lidar scans (= 3 m), yielding strong predictive relationships between height and age (R2 = 0.86, RMSE 12.21 years, and R2 = 0.93, RMSE = 25.16 years, respectively). The slope coefficient for small and large tree models (16.83 and 12.98 years/m, respectively) indicate that small trees grow 1.3 times faster than large trees at these FTE study sites. Although a strong, predictive relationship between age and height is uncommon in light-limited forest environments, our findings suggest that the sparseness of trees within the FTE may explain the strong tree height-age relationships found herein. Further analysis of 36 additional tree cores recently collected within the FTE near Inuvik, Canada will be performed. Our preliminary analysis suggests that lidar derived tree height could be a reliable proxy for tree age at the FTE, thereby establishing a new technique for scaling tree structure and demographics across larger portions of this sensitive ecotone.

  14. Ecological transfer mechanisms - Terrestrial

    International Nuclear Information System (INIS)

    Martin, W.E.; Raines, Gilbert E.; Bloom, S.G.; Levin, A.A.

    1969-01-01

    Radionuclides produced by nuclear excavation detonations and released to the environment may enter a variety of biogeochemical cycles and follow essentially the same transfer pathways as their stable-element counterparts. Estimation of potential internal radiation doses to individuals and/or populations living in or near fallout-contaminated areas requires analysis of the food-chain and other ecological pathways by which radionuclides released to the environment may be returned to man. A generalized materials transfer diagram, applicable to the forest, agricultural, freshwater and marine ecosystems providing food and water to the indigenous population of Panama and Colombia in regions that could be affected by nuclear excavation of a sea-level canal between the Atlantic and Pacific Oceans, is presented. Transfer mechanisms effecting the movement of stable elements and radionuclides in terrestrial ecosystems are discussed, and methods used to simulate these processes by means of mathematical models are described to show how intake values are calculated for different radionuclides in the major ecological pathways leading to man. These data provide a basis for estimating potential internal radiation doses for comparison with the radiation protection criteria established by recognized authorities; and this, in turn, provides a basis for recommending measures to insure the radiological safety of the nuclear operation plan. (author)

  15. Solar-terrestrial physics

    International Nuclear Information System (INIS)

    Patel, V.L.

    1977-01-01

    The Glossary is designed to be a technical dictionary that will provide solar workers of various specialties, students, other astronomers and theoreticians with concise information on the nature and the properties of phenomena of solar and solar-terrestrial physics. Each term, or group of related terms, is given a concise phenomenological and quantitative description, including the relationship to other phenomena and an interpretation in terms of physical processes. The references are intended to lead the non-specialist reader into the literature. This section deals with: geomagnetic field; coordinate systems; geomagnetic indices; Dst index; auroral electrojet index AE; daily, 27-day and semi-annual variations of geomagnetic field; micropulsation; geomagnetic storms; storm sudden commencement (SSC) or sudden commencement (SC); initial phase; ring current; sudden impulses; ionosphere; D region; polar cap absorption; sudden ionospheric disturbance; E region; sporadic E; equatorial electrojet; solar flare effect; F 1 and F 2 regions; spread F; travelling ionospheric disturbances; magnetosphere; magnetospheric coordinate systems; plasmasphere; magnetosheath; magnetospheric tail; substorm; radiation belts or Van Allen belts; whistlers; VLF emissions; aurora; auroral forms; auroral oval and auroral zones; auroral intensity; stable auroral red arcs; pulsing aurora; polar glow aurora; and airglow. (B.R.H.)

  16. Ecological transfer mechanisms - Terrestrial

    Energy Technology Data Exchange (ETDEWEB)

    Martin, W E; Raines, Gilbert E; Bloom, S G; Levin, A A [Battelle Memorial Institute, CoIumbus, OH (United States)

    1969-07-01

    Radionuclides produced by nuclear excavation detonations and released to the environment may enter a variety of biogeochemical cycles and follow essentially the same transfer pathways as their stable-element counterparts. Estimation of potential internal radiation doses to individuals and/or populations living in or near fallout-contaminated areas requires analysis of the food-chain and other ecological pathways by which radionuclides released to the environment may be returned to man. A generalized materials transfer diagram, applicable to the forest, agricultural, freshwater and marine ecosystems providing food and water to the indigenous population of Panama and Colombia in regions that could be affected by nuclear excavation of a sea-level canal between the Atlantic and Pacific Oceans, is presented. Transfer mechanisms effecting the movement of stable elements and radionuclides in terrestrial ecosystems are discussed, and methods used to simulate these processes by means of mathematical models are described to show how intake values are calculated for different radionuclides in the major ecological pathways leading to man. These data provide a basis for estimating potential internal radiation doses for comparison with the radiation protection criteria established by recognized authorities; and this, in turn, provides a basis for recommending measures to insure the radiological safety of the nuclear operation plan. (author)

  17. Model of the Correlation between Lidar Systems and Wind Turbines for Lidar-Assisted Control

    DEFF Research Database (Denmark)

    Schlipf, David; Cheng, Po Wen; Mann, Jakob

    2013-01-01

    - or spinner-based lidar system. If on the one hand, the assumed correlation is overestimated, then the uncorrelated frequencies of the preview will cause unnecessary control action, inducing undesired loads. On the other hand, the benefits of the lidar-assisted controller will not be fully exhausted......, if correlated frequencies are filtered out. To avoid these miscalculations, this work presents a method to model the correlation between lidar systems and wind turbines using Kaimal wind spectra. The derived model accounts for different measurement configurations and spatial averaging of the lidar system......Investigations of lidar-assisted control to optimize the energy yield and to reduce loads of wind turbines have increased significantly in recent years. For this kind of control, it is crucial to know the correlation between the rotor effective wind speed and the wind preview provided by a nacelle...

  18. Application of LiDAR to hydrologic flux estimation in Australian eucalypt forests (Invited)

    Science.gov (United States)

    Lane, P. N.; Mitchell, P. J.; Jaskierniak, D.; Hawthorne, S. N.; Griebel, A.

    2013-12-01

    inventory methods.These models can be used to parameterize hydrologic models to explore disturbance and age-related ET changes, and develop spatial-temporal maps of ET based on accurate representation of sapwood areas in complex terrain. The third example involves analyses of stand growth and long term streamflow response to thinning treatments in eucalyptus regnans forests. These forests have a strong age-streamflow relationship that can lead to streamflow declines as disturbed stands regrow. A set of thinning treatments in small experimental catchments (uniform, strip and understorey removal) were implemented in 1978-1982. The streamflow analysis supported early findings that flows increase and then relaxed, but also detected a flow decline below expected undisturbed levels for most catchments. Airborne LiDAR was used to analyse the structural recovery of treated stands, estimate LAI and canopy coverage via gap-fraction analysis, and scale ET measurements. The LiDAR data revealed the association of treatment type and regrowth and demonstrated that despite a net reduction in overstorey stem density, stand LAI had recovered and may explain the flow response. Finally, new terrestrial LiDAR instruments are being used in conjunction with eddy-covariance flux tower and sapflow measurement to measure fine temporal scale carbon-water dynamics. These instruments can be combined with airborne derived data to produce 3 dimensional canopy profile for linkage with ET processes.

  19. Noctilucent clouds in the polar sumer mesopause: Investigations using the ALOMAR Rayleigh/Mie/Raman Lidar; Leuchtende Nachtwolken an der polaren Sommermesopause: Untersuchungen mit dem ALOMAR Rayleigh/Mie/Raman Lidar

    Energy Technology Data Exchange (ETDEWEB)

    Baumgarten, G.

    2001-09-01

    Noctilucent clouds (NLC) are rare, tenuous clouds in the terrestrial atmosphere that occur at polar latitudes in summer near 83 km altitude. These clouds where studied using the ALOMAR Rayleigh/Mie/Raman lidar located at 69 N, 16 E. The depolarization of light, which was backscattered on NLC particles was measured for the first time by the ALOMAR RMR-Lidar. Considering the small ratio of particle size over wavelength an unexpectedly large depolarization of 1.7% was observed. Comparing this result to T-matrix calculations for scattering on randomly oriented aspherical particles implies that the shape of the NLC particles is needle like. The ALOMAR RMR-Lidar is a twin-lidar equipped with two steerable telescopes which were used to observe a single NLC layer in two separate measurement volumes about 50 km apart at NLC altitudes. Cross correlation technique reveal the layer to be tilted with imbedded periodic horizontal structures showing wavelengths of about 30 to 50 km. These structures drift horizontally through the measurement volumes rather than being microphysically formed during the observation period. (orig.)

  20. Ensemble classification of individual Pinus crowns from multispectral satellite imagery and airborne LiDAR

    Science.gov (United States)

    Kukunda, Collins B.; Duque-Lazo, Joaquín; González-Ferreiro, Eduardo; Thaden, Hauke; Kleinn, Christoph

    2018-03-01

    Distinguishing tree species is relevant in many contexts of remote sensing assisted forest inventory. Accurate tree species maps support management and conservation planning, pest and disease control and biomass estimation. This study evaluated the performance of applying ensemble techniques with the goal of automatically distinguishing Pinus sylvestris L. and Pinus uncinata Mill. Ex Mirb within a 1.3 km2 mountainous area in Barcelonnette (France). Three modelling schemes were examined, based on: (1) high-density LiDAR data (160 returns m-2), (2) Worldview-2 multispectral imagery, and (3) Worldview-2 and LiDAR in combination. Variables related to the crown structure and height of individual trees were extracted from the normalized LiDAR point cloud at individual-tree level, after performing individual tree crown (ITC) delineation. Vegetation indices and the Haralick texture indices were derived from Worldview-2 images and served as independent spectral variables. Selection of the best predictor subset was done after a comparison of three variable selection procedures: (1) Random Forests with cross validation (AUCRFcv), (2) Akaike Information Criterion (AIC) and (3) Bayesian Information Criterion (BIC). To classify the species, 9 regression techniques were combined using ensemble models. Predictions were evaluated using cross validation and an independent dataset. Integration of datasets and models improved individual tree species classification (True Skills Statistic, TSS; from 0.67 to 0.81) over individual techniques and maintained strong predictive power (Relative Operating Characteristic, ROC = 0.91). Assemblage of regression models and integration of the datasets provided more reliable species distribution maps and associated tree-scale mapping uncertainties. Our study highlights the potential of model and data assemblage at improving species classifications needed in present-day forest planning and management.

  1. Aquatic and Terrestrial Environment 2004

    DEFF Research Database (Denmark)

    Andersen, J. M.; Boutrup, S.; Bijl, L. van der

    This report presents the 2004 results of the Danish National Monitoring and Assess-ment Programme for the Aquatic and Terrestrial Environments (NOVANA). 2004 was the first year in which terrestrial nature was included in the monitoring pro-gramme. The report reviews the state of the groundwater......, watercourses, lakes and marine waters and the pressures upon them and reviews the monitoring of terrestrial natural habitats and selected plants and animals. The report is based on the annual reports prepared for each subprogramme by the Topic Centres. The latter reports are mainly based on data collected...

  2. Differential absorption lidar measurements of atmospheric water vapor using a pseudonoise code modulated AlGaAs laser. Thesis

    Science.gov (United States)

    Rall, Jonathan A. R.

    1994-01-01

    Lidar measurements using pseudonoise code modulated AlGaAs lasers are reported. Horizontal path lidar measurements were made at night to terrestrial targets at ranges of 5 and 13 km with 35 mW of average power and integration times of one second. Cloud and aerosol lidar measurements were made to thin cirrus clouds at 13 km altitude with Rayleigh (molecular) backscatter evident up to 9 km. Average transmitter power was 35 mW and measurement integration time was 20 minutes. An AlGaAs laser was used to characterize spectral properties of water vapor absorption lines at 811.617, 816.024, and 815.769 nm in a multipass absorption cell using derivative spectroscopy techniques. Frequency locking of an AlGaAs laser to a water vapor absorption line was achieved with a laser center frequency stability measured to better than one-fifth of the water vapor Doppler linewidth over several minutes. Differential absorption lidar measurements of atmospheric water vapor were made in both integrated path and range-resolved modes using an externally modulated AlGaAs laser. Mean water vapor number density was estimated from both integrated path and range-resolved DIAL measurements and agreed with measured humidity values to within 6.5 percent and 20 percent, respectively. Error sources were identified and their effects on estimates of water vapor number density calculated.

  3. 2013-2014 USGS Lidar: Olympic Peninsula (WA)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: USGS Olympic Peninsula Washington LIDAR LiDAR Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G13PD00849...

  4. 2015 OLC FEMA Lidar DEM: Snake River, ID

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Quantum Spatial has collected Light Detection and Ranging (LiDAR) data for the Oregon LiDAR Consortium (OLC) Snake River FEMA study area. This study area is located...

  5. Elevation - LiDAR Survey - Roseau County, Minnesota

    Data.gov (United States)

    Army Corps of Engineers, Department of the Army, Department of Defense — LIDAR Data for Roseau County Minnesota. This project consists of approximately 87 square miles of LIDAR mapping in Roseau County, Minnesota at two sites: area 1,...

  6. 2014 USGS CMGP Lidar: Post Sandy (Long Island, NY)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Long Island New York Sandy LIDAR lidar Data Acquisition and Processing Production Task USGS Contract No. G10PC00057 Task Order No. G14PD00296 Woolpert...

  7. Multi-wavelength Ocean Profiling and Atmospheric Lidar

    Data.gov (United States)

    National Aeronautics and Space Administration — We propose to build and demonstrate the world's first multi-wavelength ocean-profiling high spectral resolution lidar (HSRL). The lidar will provide profiles of...

  8. Occurrence and characteristics of mutual interference between LIDAR scanners

    Science.gov (United States)

    Kim, Gunzung; Eom, Jeongsook; Park, Seonghyeon; Park, Yongwan

    2015-05-01

    The LIDAR scanner is at the heart of object detection of the self-driving car. Mutual interference between LIDAR scanners has not been regarded as a problem because the percentage of vehicles equipped with LIDAR scanners was very rare. With the growing number of autonomous vehicle equipped with LIDAR scanner operated close to each other at the same time, the LIDAR scanner may receive laser pulses from other LIDAR scanners. In this paper, three types of experiments and their results are shown, according to the arrangement of two LIDAR scanners. We will show the probability that any LIDAR scanner will interfere mutually by considering spatial and temporal overlaps. It will present some typical mutual interference scenario and report an analysis of the interference mechanism.

  9. 2006 FEMA New Jersey Flood Mitigation Lidar: Highlands Area

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) data is remotely sensed high-resolution elevation data collected by an airborne collection platform. LiDAR was flown for...

  10. 2012 NOAA Fisheries Topographic Lidar: Bridge Creek, Oregon

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — This data set is an LAZ (compressed LAS) format file containing LIDAR point cloud data. This data set is an LAZ (compressed LAS) format file containing LIDAR point...

  11. 2010 USGS Lidar: Southeastern Michigan (Hillsdale, Jackson, Lenawee Counties)

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — TASK NAME: Lake Erie LiDAR Priority Area 1 LiDAR Data Acquisition and Processing Production Task- Jackson, Hillsdale, and Lenawee Counties USGS Contract No....

  12. 2012 NRCS-USGS Tupelo, MS Lidar Survey

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is a remotely sensed high resolution elevation data collected by an airborne platform. The LiDAR sensor uses a combination of laser range finding, GPS...

  13. 2008 Florida Division of Emergency Management Lidar: Middle Suwannee River

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR Survey for the Suwannee River Water Management District (SRWMD), Florida. The LiDAR aerial acquisition was conducted in January of 2008, and the breaklines and...

  14. 2015 Oregon Department Forestry Lidar DEM: Northwest OR

    Data.gov (United States)

    National Oceanic and Atmospheric Administration, Department of Commerce — GeoTerra, Inc. was selected by Oregon Department of Forestry to provide Lidar remote sensing data including LAZ files of the classified Lidar points and surface...

  15. The Geometry of Finite Equilibrium Datasets

    DEFF Research Database (Denmark)

    Balasko, Yves; Tvede, Mich

    We investigate the geometry of finite datasets defined by equilibrium prices, income distributions, and total resources. We show that the equilibrium condition imposes no restrictions if total resources are collinear, a property that is robust to small perturbations. We also show that the set...... of equilibrium datasets is pathconnected when the equilibrium condition does impose restrictions on datasets, as for example when total resources are widely non collinear....

  16. Analysis of lidar elevation data for improved identification and delineation of lands vulnerable to sea-level rise

    Science.gov (United States)

    Gesch, Dean B.

    2009-01-01

    The importance of sea-level rise in shaping coastal landscapes is well recognized within the earth science community, but as with many natural hazards, communicating the risks associated with sea-level rise remains a challenge. Topography is a key parameter that influences many of the processes involved in coastal change, and thus, up-to-date, high-resolution, high-accuracy elevation data are required to model the coastal environment. Maps of areas subject to potential inundation have great utility to planners and managers concerned with the effects of sea-level rise. However, most of the maps produced to date are simplistic representations derived from older, coarse elevation data. In the last several years, vast amounts of high quality elevation data derived from lidar have become available. Because of their high vertical accuracy and spatial resolution, these lidar data are an excellent source of up-to-date information from which to improve identification and delineation of vulnerable lands. Four elevation datasets of varying resolution and accuracy were processed to demonstrate that the improved quality of lidar data leads to more precise delineation of coastal lands vulnerable to inundation. A key component of the comparison was to calculate and account for the vertical uncertainty of the elevation datasets. This comparison shows that lidar allows for a much more detailed delineation of the potential inundation zone when compared to other types of elevation models. It also shows how the certainty of the delineation of lands vulnerable to a given sea-level rise scenario is much improved when derived from higher resolution lidar data.

  17. Enhancing Conservation with High Resolution Productivity Datasets for the Conterminous United States

    Science.gov (United States)

    Robinson, Nathaniel Paul

    Human driven alteration of the earth's terrestrial surface is accelerating through land use changes, intensification of human activity, climate change, and other anthropogenic pressures. These changes occur at broad spatio-temporal scales, challenging our ability to effectively monitor and assess the impacts and subsequent conservation strategies. While satellite remote sensing (SRS) products enable monitoring of the earth's terrestrial surface continuously across space and time, the practical applications for conservation and management of these products are limited. Often the processes driving ecological change occur at fine spatial resolutions and are undetectable given the resolution of available datasets. Additionally, the links between SRS data and ecologically meaningful metrics are weak. Recent advances in cloud computing technology along with the growing record of high resolution SRS data enable the development of SRS products that quantify ecologically meaningful variables at relevant scales applicable for conservation and management. The focus of my dissertation is to improve the applicability of terrestrial gross and net primary productivity (GPP/NPP) datasets for the conterminous United States (CONUS). In chapter one, I develop a framework for creating high resolution datasets of vegetation dynamics. I use the entire archive of Landsat 5, 7, and 8 surface reflectance data and a novel gap filling approach to create spatially continuous 30 m, 16-day composites of the normalized difference vegetation index (NDVI) from 1986 to 2016. In chapter two, I integrate this with other high resolution datasets and the MOD17 algorithm to create the first high resolution GPP and NPP datasets for CONUS. I demonstrate the applicability of these products for conservation and management, showing the improvements beyond currently available products. In chapter three, I utilize this dataset to evaluate the relationships between land ownership and terrestrial production

  18. THE BENEFITS OF TERRESTRIAL LASER SCANNING AND HYPERSPECTRAL DATA FUSION PRODUCTS

    Directory of Open Access Journals (Sweden)

    S. J. Buckley

    2012-10-01

    Full Text Available Close range hyperspectral imaging is a developing method for the analysis and identification of material composition in many applications, such as in within the earth sciences. Using compact imaging devices in the field allows near-vertical topography to be imaged, thus bypassing the key limitations of viewing angle and resolution that preclude the use of airborne and spaceborne platforms. Terrestrial laser scanning allows 3D topography to be captured with high precision and spatial resolution. The combination of 3D geometry from laser scanning, and material properties from hyperspectral imaging allows new fusion products to be created, adding new information for solving application problems. This paper highlights the advantages of terrestrial lidar and hyperspectral integration, focussing on the qualitative and quantitative aspects, with examples from a geological field application. Accurate co-registration of the two data types is required. This allows 2D pixels to be linked to the 3D lidar geometry, giving increased quantitative analysis as classified material vectors are projected to 3D space for calculation of areas and examination of spatial relationships. User interpretation of hyperspectral results in a spatially-meaningful manner is facilitated using visual methods that combine the geometric and mineralogical products in a 3D environment. Point cloud classification and the use of photorealistic modelling enhance qualitative validation and interpretation, and allow image registration accuracy to be checked. A method for texture mapping of lidar meshes with multiple image textures, both conventional digital photos and hyperspectral results, is described. The integration of terrestrial laser scanning and hyperspectral imaging is a valuable means of providing new analysis methods, suitable for many applications requiring linked geometric and chemical information.

  19. IPCC Socio-Economic Baseline Dataset

    Data.gov (United States)

    National Aeronautics and Space Administration — The Intergovernmental Panel on Climate Change (IPCC) Socio-Economic Baseline Dataset consists of population, human development, economic, water resources, land...

  20. Veterans Affairs Suicide Prevention Synthetic Dataset

    Data.gov (United States)

    Department of Veterans Affairs — The VA's Veteran Health Administration, in support of the Open Data Initiative, is providing the Veterans Affairs Suicide Prevention Synthetic Dataset (VASPSD). The...