Lidar-based estimates of aboveground biomass in the continental US and Mexico using ground, airborne, and satellite observations

Science.gov (United States)

Ross Nelson; Hank Margolis; Paul Montesano; Guoqing Sun; Bruce Cook; Larry Corp; Hans-Erik Andersen; Ben deJong; Fernando Paz Pellat; Thaddeus Fickel; Jobriath Kauffman; Stephen Prisley

2017-01-01

Existing national forest inventory plots, an airborne lidar scanning (ALS) system, and a space profiling lidar system (ICESat-GLAS) are used to generate circa 2005 estimates of total aboveground dry biomass (AGB) in forest strata, by state, in the continental United States (CONUS) and Mexico. The airborne lidar is used to link ground observations of AGB to space lidar...

Depolarization ratio of polar stratospheric clouds in coastal Antarctica: comparison analysis between ground-based Micro Pulse Lidar and space-borne CALIOP observations

Directory of Open Access Journals (Sweden)

C. Córdoba-Jabonero

2013-03-01

Full Text Available Polar stratospheric clouds (PSCs play an important role in polar ozone depletion, since they are involved in diverse ozone destruction processes (chlorine activation, denitrification. The degree of that ozone reduction is depending on the type of PSCs, and hence on their occurrence. Therefore PSC characterization, mainly focused on PSC-type discrimination, is widely demanded. The backscattering (R and volume linear depolarization (δV ratios are the parameters usually used in lidar measurements for PSC detection and identification. In this work, an improved version of the standard NASA/Micro Pulse Lidar (MPL-4, which includes a built-in depolarization detection module, has been used for PSC observations above the coastal Antarctic Belgrano II station (Argentina, 77.9° S 34.6° W, 256 m a.s.l. since 2009. Examination of the MPL-4 δV feature as a suitable index for PSC-type discrimination is based on the analysis of the two-channel data, i.e., the parallel (p- and perpendicular (s- polarized MPL signals. This study focuses on the comparison of coincident δV-profiles as obtained from ground-based MPL-4 measurements during three Antarctic winters with those reported from the space-borne lidar CALIOP (Cloud-Aerosol Lidar with Orthogonal Polarization aboard the CALIPSO (Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation satellite in the same period (83 simultaneous cases are analysed for 2009–2011 austral winter times. Three different approaches are considered for the comparison analysis between both lidar profile data sets in order to test the degree of agreement: the correlation coefficient (CC, as a measure of the relationship between both PSC vertical structures; the mean differences together with their root mean square (RMS values found between data sets; and the percentage differences (BIAS, parameter also used in profiling comparisons between CALIOP and other ground-based lidar systems. All of them are examined as a function

Investigation of tropical cirrus cloud properties using ground based lidar measurements

Science.gov (United States)

Dhaman, Reji K.; Satyanarayana, Malladi; Krishnakumar, V.; Mahadevan Pillai, V. P.; Jayeshlal, G. S.; Raghunath, K.; Venkat Ratnam, M.

2016-05-01

Cirrus clouds play a significant role in the Earths radiation budget. Therefore, knowledge of geometrical and optical properties of cirrus cloud is essential for the climate modeling. In this paper, the cirrus clouds microphysical and optical properties are made by using a ground based lidar measurements over an inland tropical station Gadanki (13.5°N, 79.2°E), Andhra Pradesh, India. The variation of cirrus microphysical and optical properties with mid cloud temperature is also studied. The cirrus clouds mean height is generally observed in the range of 9-17km with a peak occurrence at 13- 14km. The cirrus mid cloud temperature ranges from -81°C to -46°C. The cirrus geometrical thickness ranges from 0.9- 4.5km. During the cirrus occurrence days sub-visual, thin and dense cirrus were at 37.5%, 50% and 12.5% respectively. The monthly cirrus optical depth ranges from 0.01-0.47, but most (<80%) of the cirrus have values less than 0.1. Optical depth shows a strong dependence with cirrus geometrical thickness and mid-cloud height. The monthly mean cirrus extinction ranges from 2.8E-06 to 8E-05 and depolarization ratio and lidar ratio varies from 0.13 to 0.77 and 2 to 52 sr respectively. A positive correlation exists for both optical depth and extinction with the mid-cloud temperature. The lidar ratio shows a scattered behavior with mid-cloud temperature.

Aerosol characteristics inversion based on the improved lidar ratio profile with the ground-based rotational Raman-Mie lidar

Science.gov (United States)

Ji, Hongzhu; Zhang, Yinchao; Chen, Siying; Chen, He; Guo, Pan

2018-06-01

An iterative method, based on a derived inverse relationship between atmospheric backscatter coefficient and aerosol lidar ratio, is proposed to invert the lidar ratio profile and aerosol extinction coefficient. The feasibility of this method is investigated theoretically and experimentally. Simulation results show the inversion accuracy of aerosol optical properties for iterative method can be improved in the near-surface aerosol layer and the optical thick layer. Experimentally, as a result of the reduced insufficiency error and incoherence error, the aerosol optical properties with higher accuracy can be obtained in the near-surface region and the region of numerical derivative distortion. In addition, the particle component can be distinguished roughly based on this improved lidar ratio profile.

Seasonal variation of spherical aerosols distribution in East Asia based on ground and space Lidar observation and a Chemical transport model

Science.gov (United States)

Hara, Y.; Yumimoto, K.; Uno, I.; Shimizu, A.; Sugimoto, N.; Ohara, T.

2009-12-01

The anthropogenic aerosols largely impact on not only human health but also global climate system, therefore air pollution in East Asia due to a rapid economic growth has been recognized as a significant environmental problem. Several international field campaigns had been conducted to elucidate pollutant gases, aerosols characteristics and radiative forcing in East Asia. (e.g., ACE-Asia, TRACE-P, ADEC, EAREX 2005). However, these experiments were mainly conducted in springtime, therefore seasonal variation of aerosols distribution has not been clarified well yet. National Institute for Environmental Studies (NIES) has been constructing a lidar networks by automated dual wavelength / polarization Mie-lidar systems to observe the atmospheric environment in Asian region since 2001. Furthermore, from June 2006, space-borne backscatter lidar, Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), onboard NASA/CALIPSO satellite, measures continuous global aerosol and cloud vertical distribution with very high spatial resolution. In this paper, we will show the seasonal variation of aerosols distribution in East Asia based on the NIES lidar network observation, Community Multi-scale Air Quality Modeling System (CMAQ) chemical transport model simulation and CALIOP observation over the period from July 2006 to December 2008. We found that CMAQ result explains the typical seasonal aerosol characteristics by lidar observations. For example, CMAQ and ground lidar showed a summertime peak of aerosol optical thickness (AOT) at Beijing, an autumn AOT peak at Guangzhou and summertime AOT trough at Hedo, Okinawa. These characteristics are mainly controlled by seasonal variations of Asian summer/winter monsoon system. We also examined the CMAQ seasonal average aerosol extinction profiles with ground lidar and CALIOP extinction data. These comparisons clarified that the CMAQ reproduced the observed aerosol layer depth well in the downwind region. Ground lidar and CALIOP seasonal

Lidar-based Research and Innovation at DTU Wind Energy - a Review

Science.gov (United States)

Mikkelsen, T.

2014-06-01

As wind turbines during the past decade have increased in size so have the challenges met by the atmospheric boundary-layer meteorologists and the wind energy society to measure and characterize the huge-volume wind fields surpassing and driving them. At the DTU Wind Energy test site "Østerild" for huge wind turbines, the hub-height of a recently installed 8 MW Vestas V164 turbine soars 143 meters up above the ground, and its rotor of amazing 164 meters in diameter make the turbine tips flicker 225 meters into the sky. Following the revolution in photonics-based telecommunication at the turn of the Millennium new fibre-based wind lidar technologies emerged and DTU Wind Energy, at that time embedded within Rise National Laboratory, began in collaboration with researchers from wind lidar companies to measure remote sensed wind profiles and turbulence structures within the atmospheric boundary layer with the emerging, at that time new, all-fibre-based 1.55 μ coherent detection wind lidars. Today, ten years later, DTU Wind Energy routinely deploys ground-based vertical profilers instead of met masts for high-precision measurements of mean wind profiles and turbulence profiles. At the departments test site "Høvsøre" DTU Wind Energy also routinely calibrate and accredit wind lidar manufactures wind lidars. Meanwhile however, new methodologies for power curve assessment based on ground-based and nacelle based lidars have also emerged. For improving the turbines power curve assessments and for advancing their control with feed-forward wind measurements experience has also been gained with wind lidars installed on turbine nacelles and integrated into the turbines rotating spinners. A new mobile research infrastructure WindScanner.dk has also emerged at DTU Wind Energy. Wind and turbulence fields are today scanned from sets of three simultaneously in space and time synchronized scanning lidars. One set consists of three fast scanning continuous-wave based wind lidars

Calibrating a ground-based backscatter lidar for continuous measurements of PM2.5

Science.gov (United States)

Pesch, Markus; Oderbolz, Daniel

2007-10-01

One of the main issues of atmospheric research and air quality control is the reduction of harmful particulate matter (PM) in the atmosphere. Small particles can enter the human airways and cause serious health problems such as COPD (Chronic Obstructive Pulmonary Disease), asthma or even lung cancer. Recently, interest has shifted from PM10 to finer fractions of particulate matter, e.g. PM2.5, because the health impact of finer particles is considered to be more severe. Up to now measurements of particulate matter were carried out mainly at ground level. However important atmospheric processes, i.e. particle formation, transport and vertical mixing processes, take place predominantly at higher altitudes in the planetary boundary layer. Lidar in principle provides the ability to observe these processes where they occur. The new method outlined in this paper demonstrates the use of a small sized and quite inexpensive lidar in stand-alone operation to investigate transport processes of particulate matter, and PM2.5 in particular. Continuous measurements of PM2.5 as a reference are gained with a conventional in-situ monitor, installed on a tower at an altitude of 325 m in the North of Berlin (Frohnauer Turm). These PM2.5 measurements will be compared with backscatter Lidar data (1064 nm) taken from approx. 60 m over ground up to an altitude of 15 km with a spatial resolution of 15 m. The vertical backscatter profiles at 325 m will be correlated to the concentrations obtained by the PM2,5 monitor on the tower. Both measurements have a time resolution of 180 s to observe also processes that take place at short time scales. The objective is to gain correlation functions for estimating PM2.5 concentrations from backscatter Lidar data. Such a calibrated Lidar system is a valuable instrument for environmental agencies and atmospheric research groups to observe and investigate causes of high level PM concentrations. First results show a reasonably good linear correlation

Comparison of lidar-derived PM10 with regional modeling and ground-based observations in the frame of MEGAPOLI experiment

Directory of Open Access Journals (Sweden)

J.-C. Raut

2011-10-01

Full Text Available An innovative approach using mobile lidar measurements was implemented to test the performances of chemistry-transport models in simulating mass concentrations (PM10 predicted by chemistry-transport models. A ground-based mobile lidar (GBML was deployed around Paris onboard a van during the MEGAPOLI (Megacities: Emissions, urban, regional and Global Atmospheric POLlution and climate effects, and Integrated tools for assessment and mitigation summer experiment in July 2009. The measurements performed with this Rayleigh-Mie lidar are converted into PM10 profiles using optical-to-mass relationships previously established from in situ measurements performed around Paris for urban and peri-urban aerosols. The method is described here and applied to the 10 measurements days (MD. MD of 1, 15, 16 and 26 July 2009, corresponding to different levels of pollution and atmospheric conditions, are analyzed here in more details. Lidar-derived PM10 are compared with results of simulations from POLYPHEMUS and CHIMERE chemistry-transport models (CTM and with ground-based observations from the AIRPARIF network. GBML-derived and AIRPARIF in situ measurements have been found to be in good agreement with a mean Root Mean Square Error RMSE (and a Mean Absolute Percentage Error MAPE of 7.2 μg m−3 (26.0% and 8.8 μg m−3 (25.2% with relationships assuming peri-urban and urban-type particles, respectively. The comparisons between CTMs and lidar at ~200 m height have shown that CTMs tend to underestimate wet PM10 concentrations as revealed by the mean wet PM10 observed during the 10 MD of 22.4, 20.0 and 17.5 μg m−3 for lidar with peri-urban relationship, and POLYPHEMUS and CHIMERE models, respectively. This leads to a RMSE (and a MAPE of 6.4 μg m−3 (29.6% and 6.4 μg m−3 (27.6% when considering POLYPHEMUS and CHIMERE CTMs, respectively. Wet integrated PM10 computed (between the ground and 1 km above the ground level from lidar, POLYPHEMUS and CHIMERE results

Lidar-based Research and Innovation at DTU Wind Energy – a Review

International Nuclear Information System (INIS)

Mikkelsen, T

2014-01-01

As wind turbines during the past decade have increased in size so have the challenges met by the atmospheric boundary-layer meteorologists and the wind energy society to measure and characterize the huge-volume wind fields surpassing and driving them. At the DTU Wind Energy test site ''Østerild'' for huge wind turbines, the hub-height of a recently installed 8 MW Vestas V164 turbine soars 143 meters up above the ground, and its rotor of amazing 164 meters in diameter make the turbine tips flicker 225 meters into the sky. Following the revolution in photonics-based telecommunication at the turn of the Millennium new fibre-based wind lidar technologies emerged and DTU Wind Energy, at that time embedded within Rise National Laboratory, began in collaboration with researchers from wind lidar companies to measure remote sensed wind profiles and turbulence structures within the atmospheric boundary layer with the emerging, at that time new, all-fibre-based 1.55 μ coherent detection wind lidars. Today, ten years later, DTU Wind Energy routinely deploys ground-based vertical profilers instead of met masts for high-precision measurements of mean wind profiles and turbulence profiles. At the departments test site ''Høvsøre'' DTU Wind Energy also routinely calibrate and accredit wind lidar manufactures wind lidars. Meanwhile however, new methodologies for power curve assessment based on ground-based and nacelle based lidars have also emerged. For improving the turbines power curve assessments and for advancing their control with feed-forward wind measurements experience has also been gained with wind lidars installed on turbine nacelles and integrated into the turbines rotating spinners. A new mobile research infrastructure WindScanner.dk has also emerged at DTU Wind Energy. Wind and turbulence fields are today scanned from sets of three simultaneously in space and time synchronized scanning lidars. One set consists of three fast

The impact of forest structure and spatial scale on the relationship between ground plot above ground biomass and GEDI lidar waveforms

Science.gov (United States)

Armston, J.; Marselis, S.; Hancock, S.; Duncanson, L.; Tang, H.; Kellner, J. R.; Calders, K.; Disney, M.; Dubayah, R.

2017-12-01

The NASA Global Ecosystem Dynamics Investigation (GEDI) will place a multi-beam waveform lidar instrument on the International Space Station (ISS) to provide measurements of forest vertical structure globally. These measurements of structure will underpin empirical modelling of above ground biomass density (AGBD) at the scale of individual GEDI lidar footprints (25m diameter). The GEDI pre-launch calibration strategy for footprint level models relies on linking AGBD estimates from ground plots with GEDI lidar waveforms simulated from coincident discrete return airborne laser scanning data. Currently available ground plot data have variable and often large uncertainty at the spatial resolution of GEDI footprints due to poor colocation, allometric model error, sample size and plot edge effects. The relative importance of these sources of uncertainty partly depends on the quality of ground measurements and region. It is usually difficult to know the magnitude of these uncertainties a priori so a common approach to mitigate their influence on model training is to aggregate ground plot and waveform lidar data to a coarser spatial scale (0.25-1ha). Here we examine the impacts of these principal sources of uncertainty using a 3D simulation approach. Sets of realistic tree models generated from terrestrial laser scanning (TLS) data or parametric modelling matched to tree inventory data were assembled from four contrasting forest plots across tropical rainforest, deciduous temperate forest, and sclerophyll eucalypt woodland sites. These tree models were used to simulate geometrically explicit 3D scenes with variable tree density, size class and spatial distribution. GEDI lidar waveforms are simulated over ground plots within these scenes using monte carlo ray tracing, allowing the impact of varying ground plot and waveform colocation error, forest structure and edge effects on the relationship between ground plot AGBD and GEDI lidar waveforms to be directly assessed. We

Characteristics of Volcanic Stratospheric Aerosol Layer Observed by CALIOP and Ground Based Lidar at Equatorial Atmosphere Radar Site

Science.gov (United States)

Abo, Makoto; Shibata, Yasukuni; Nagasawa, Chikao

2018-04-01

We investigated the relation between major tropical volcanic eruptions in the equatorial region and the stratospheric aerosol data, which have been collected by the ground based lidar observations at at Equatorial Atmosphere Radar site between 2004 and 2015 and the CALIOP observations in low latitude between 2006 and 2015. We found characteristic dynamic behavior of volcanic stratospheric aerosol layers over equatorial region.

Relativity effects for space-based coherent lidar experiments

Science.gov (United States)

Gudimetla, V. S. Rao

1996-01-01

An effort was initiated last year in the Astrionics Laboratory at Marshall Space Flight Center to examine and incorporate, if necessary, the effects of relativity in the design of space-based lidar systems. A space-based lidar system, named AEOLUS, is under development at Marshall Space Flight Center and it will be used to accurately measure atmospheric wind profiles. Effects of relativity were also observed in the performance of space-based systems, for example in case of global positioning systems, and corrections were incorporated into the design of instruments. During the last summer, the effects of special relativity on the design of space-based lidar systems were studied in detail, by analyzing the problem of laser scattering off a fixed target when the source and a co-located receiver are moving on a spacecraft. Since the proposed lidar system uses a coherent detection system, errors even in the order of a few microradians must be corrected to achieve a good signal-to-noise ratio. Previous analysis assumed that the ground is flat and the spacecraft is moving parallel to the ground, and developed analytical expressions for the location, direction and Doppler shift of the returning radiation. Because of the assumptions used in that analysis, only special relativity effects were involved. In this report, that analysis is extended to include general relativity and calculate its effects on the design.

Lidar-based Research and Innovation at DTU Wind Energy – a Review

DEFF Research Database (Denmark)

Mikkelsen, Torben

2014-01-01

" for huge wind turbines, the hub-height of a recently installed 8 MW Vestas V164 turbine soars 143 meters up above the ground, and its rotor of amazing 164 meters in diameter make the turbine tips flicker 225 meters into the sky. Following the revolution in photonics-based telecommunication at the turn...... "Høvsøre" DTU Wind Energy also routinely calibrate and accredit wind lidar manufactures wind lidars. Meanwhile however, new methodologies for power curve assessment based on ground-based and nacelle based lidars have also emerged. For improving the turbines power curve assessments and for advancing...... their control with feed-forward wind measurements experience has also been gained with wind lidars installed on turbine nacelles and integrated into the turbines rotating spinners. A new mobile research infrastructure WindScanner.dk has also emerged at DTU Wind Energy. Wind and turbulence fields are today...

Lidar technologies for airborne and space-based applications

International Nuclear Information System (INIS)

Henson, T.D.; Schmitt, R.L.; Sobering, T.J.; Raymond, T.D.; Stephenson, D.A.

1994-10-01

This study identifies technologies required to extend the capabilities of airborne light detection and ranging (lidar) systems and establish the feasibility of autonomous space-based lidars. Work focused on technologies that enable the development of a lightweight, low power, rugged and autonomous Differential Absorption Lidar (DIAL) instruments. Applications for airborne or space-based DIAL include the measurement of water vapor profiles in support of climate research and processing-plant emissions signatures for environmental and nonproliferation monitoring. A computer-based lidar performance model was developed to allow trade studies to be performed on various technologies and system configurations. It combines input from the physics (absorption line strengths and locations) of the problem, the system requirements (weight, power, volume, accuracy), and the critical technologies available (detectors, lasers, filters) to produce the best conceptual design. Conceptual designs for an airborne and space-based water vapor DIAL, and a detailed design of a ground-based water vapor DIAL demonstration system were completed. Future work planned includes the final testing, integration, and operation of the demonstration system to prove the capability of the critical enabling technologies identified

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....

Ground-based lidar and microwave radiometry synergy for high vertical resolution absolute humidity profiling

Science.gov (United States)

Barrera-Verdejo, María; Crewell, Susanne; Löhnert, Ulrich; Orlandi, Emiliano; Di Girolamo, Paolo

2016-08-01

Continuous monitoring of atmospheric humidity profiles is important for many applications, e.g., assessment of atmospheric stability and cloud formation. Nowadays there are a wide variety of ground-based sensors for atmospheric humidity profiling. Unfortunately there is no single instrument able to provide a measurement with complete vertical coverage, high vertical and temporal resolution and good performance under all weather conditions, simultaneously. For example, Raman lidar (RL) measurements can provide water vapor with a high vertical resolution, albeit with limited vertical coverage, due to sunlight contamination and the presence of clouds. Microwave radiometers (MWRs) receive water vapor information throughout the troposphere, though their vertical resolution is poor. In this work, we present an MWR and RL system synergy, which aims to overcome the specific sensor limitations. The retrieval algorithm combining these two instruments is an optimal estimation method (OEM), which allows for an uncertainty analysis of the retrieved profiles. The OEM combines measurements and a priori information, taking the uncertainty of both into account. The measurement vector consists of a set of MWR brightness temperatures and RL water vapor profiles. The method is applied to a 2-month field campaign around Jülich (Germany), focusing on clear sky periods. Different experiments are performed to analyze the improvements achieved via the synergy compared to the individual retrievals. When applying the combined retrieval, on average the theoretically determined absolute humidity uncertainty is reduced above the last usable lidar range by a factor of ˜ 2 with respect to the case where only RL measurements are used. The analysis in terms of degrees of freedom per signal reveal that most information is gained above the usable lidar range, especially important during daytime when the lidar vertical coverage is limited. The retrieved profiles are further evaluated using

Mapping Above- and Below-Ground Carbon Pools in Boreal Forests: The Case for Airborne Lidar.

Science.gov (United States)

Kristensen, Terje; Næsset, Erik; Ohlson, Mikael; Bolstad, Paul V; Kolka, Randall

2015-01-01

A large and growing body of evidence has demonstrated that airborne scanning light detection and ranging (lidar) systems can be an effective tool in measuring and monitoring above-ground forest tree biomass. However, the potential of lidar as an all-round tool for assisting in assessment of carbon (C) stocks in soil and non-tree vegetation components of the forest ecosystem has been given much less attention. Here we combine the use airborne small footprint scanning lidar with fine-scale spatial C data relating to vegetation and the soil surface to describe and contrast the size and spatial distribution of C pools within and among multilayered Norway spruce (Picea abies) stands. Predictor variables from lidar derived metrics delivered precise models of above- and below-ground tree C, which comprised the largest C pool in our study stands. We also found evidence that lidar canopy data correlated well with the variation in field layer C stock, consisting mainly of ericaceous dwarf shrubs and herbaceous plants. However, lidar metrics derived directly from understory echoes did not yield significant models. Furthermore, our results indicate that the variation in both the mosses and soil organic layer C stock plots appears less influenced by differences in stand structure properties than topographical gradients. By using topographical models from lidar ground returns we were able to establish a strong correlation between lidar data and the organic layer C stock at a stand level. Increasing the topographical resolution from plot averages (~2000 m2) towards individual grid cells (1 m2) did not yield consistent models. Our study demonstrates a connection between the size and distribution of different forest C pools and models derived from airborne lidar data, providing a foundation for future research concerning the use of lidar for assessing and monitoring boreal forest C.

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.

Ground level and Lidar monitoring of volcanic dust and dust from Patagonia

Science.gov (United States)

Otero, L. A.; Losno, R.; Salvador, J. O.; Journet, E.; Qu, Z.; Triquet, S.; Monna, F.; Balkanski, Y.; Bulnes, D.; Ristori, P. R.; Quel, E. J.

2013-05-01

A combined approach including ground level aerosol sampling, lidar and sunphotometer measurements is used to monitor suspended particles in the atmosphere at several sites in Patagonia. Motivated by the Puyehue volcanic eruption in June 2011 two aerosol monitoring stations with several passive and active instruments were installed in Bariloche and Comodoro Rivadavia. The main goal which is to monitor ground lifted and transported ashes and dust involving danger to civil aviation, is achieved by measuring continuously aerosol concentration at ground level and aerosol vertical distribution using lidar. In addition, starting from December 2011, continuous series of weekly accumulated aerosol concentrations at Rio Gallegos are being measured to study the impact of Patagonian dust over the open ocean on phytoplankton primary productivity and CO2 removal. These measurements are going to be coupled with LIDAR monitoring and a dust optical response models to test if aerosol extrapolation can be done from the ground to the top of the layer. Laboratory chemical analysis of the aerosols will include elemental composition, solubilisation kinetic and mineralogical determination. Expected deliverables for this study is the estimation of the amount of dust exported from Patagonia towards the South Atlantic, its chemical properties, including bioavailability simulation, from model and comparison to experimental measurements.

Optical and geometrical properties of cirrus clouds in Amazonia derived from 1 year of ground-based lidar measurements

Science.gov (United States)

Gouveia, Diego A.; Barja, Boris; Barbosa, Henrique M. J.; Seifert, Patric; Baars, Holger; Pauliquevis, Theotonio; Artaxo, Paulo

2017-03-01

Cirrus clouds cover a large fraction of tropical latitudes and play an important role in Earth's radiation budget. Their optical properties, altitude, vertical and horizontal coverage control their radiative forcing, and hence detailed cirrus measurements at different geographical locations are of utmost importance. Studies reporting cirrus properties over tropical rain forests like the Amazon, however, are scarce. Studies with satellite profilers do not give information on the diurnal cycle, and the satellite imagers do not report on the cloud vertical structure. At the same time, ground-based lidar studies are restricted to a few case studies. In this paper, we derive the first comprehensive statistics of optical and geometrical properties of upper-tropospheric cirrus clouds in Amazonia. We used 1 year (July 2011 to June 2012) of ground-based lidar atmospheric observations north of Manaus, Brazil. This dataset was processed by an automatic cloud detection and optical properties retrieval algorithm. Upper-tropospheric cirrus clouds were observed more frequently than reported previously for tropical regions. The frequency of occurrence was found to be as high as 88 % during the wet season and not lower than 50 % during the dry season. The diurnal cycle shows a minimum around local noon and maximum during late afternoon, associated with the diurnal cycle of precipitation. The mean values of cirrus cloud top and base heights, cloud thickness, and cloud optical depth were 14.3 ± 1.9 (SD) km, 12.9 ± 2.2 km, 1.4 ± 1.1 km, and 0.25 ± 0.46, respectively. Cirrus clouds were found at temperatures down to -90 °C. Frequently cirrus were observed within the tropical tropopause layer (TTL), which are likely associated to slow mesoscale uplifting or to the remnants of overshooting convection. The vertical distribution was not uniform, and thin and subvisible cirrus occurred more frequently closer to the tropopause. The mean lidar ratio was 23.3 ± 8.0 sr. However, for

Ground-Truthing of Airborne LiDAR Using RTK-GPS Surveyed Data in Coastal Louisiana's Wetlands

Science.gov (United States)

Lauve, R. M.; Alizad, K.; Hagen, S. C.

2017-12-01

Airborne LiDAR (Light Detection and Ranging) data are used by engineers and scientists to create bare earth digital elevation models (DEM), which are essential to modeling complex coastal, ecological, and hydrological systems. However, acquiring accurate bare earth elevations in coastal wetlands is difficult due to the density of marsh grasses that prevent the sensors reflection off the true ground surface. Previous work by Medeiros et al. [2015] developed a technique to assess LiDAR error and adjust elevations according to marsh vegetation density and index. The aim of this study is the collection of ground truth points and the investigation on the range of potential errors found in existing LiDAR datasets within coastal Louisiana's wetlands. Survey grids were mapped out in an area dominated by Spartina alterniflora and a survey-grade Trimble Real Time Kinematic (RTK) GPS device was employed to measure bare earth ground elevations in the marsh system adjacent to Terrebonne Bay, LA. Elevations were obtained for 20 meter-spaced surveyed grid points and were used to generate a DEM. The comparison between LiDAR derived and surveyed data DEMs yield an average difference of 23 cm with a maximum difference of 68 cm. Considering the local tidal range of 45 cm, these differences can introduce substantial error when the DEM is used for ecological modeling [Alizad et al., 2016]. Results from this study will be further analyzed and implemented in order to adjust LiDAR-derived DEMs closer to their true elevation across Louisiana's coastal wetlands. ReferencesAlizad, K., S. C. Hagen, J. T. Morris, S. C. Medeiros, M. V. Bilskie, and J. F. Weishampel (2016), Coastal wetland response to sea-level rise in a fluvial estuarine system, Earth's Future, 4(11), 483-497, 10.1002/2016EF000385. Medeiros, S., S. Hagen, J. Weishampel, and J. Angelo (2015), Adjusting Lidar-Derived Digital Terrain Models in Coastal Marshes Based on Estimated Aboveground Biomass Density, Remote Sensing, 7

Ground-based lidar measurements from Ny-Ålesund during ASTAR 2007

Directory of Open Access Journals (Sweden)

A. Herber

2009-11-01

Full Text Available During the Arctic Study of Tropospheric Aerosol, Clouds and Radiation (ASTAR in March and April 2007, measurements obtained at the AWIPEV Arctic Research Base in Ny-Ålesund, Spitsbergen at 78.9° N, 11.9° E (operated by the Alfred Wegener Institute for Polar and Marine Research – AWI and the Institut polaire français Paul-Emile Victor – IPEV, supported the airborne campaign. This included lidar data from the Koldewey Aerosol Raman Lidar (KARL and the Micro Pulse Lidar (MPL, located in the atmospheric observatory as well as photometer data and the daily launched radiosonde. The MPL features nearly continuous measurements; the KARL was switched on whenever weather conditions allowed observations (145 h in 61 days. From 1 March to 30 April, 71 meteorological balloon soundings were performed and compared with the concurrent MPL measurements; photometer measurements are available from 18 March. For the KARL data, a statistical overview of particle detection based on their optical properties backscatter ratio and volume depolarization can be given. The altitudes of the occurrence of the named features (subvisible and visible ice and water as well as mixed-phase clouds, aerosol layers as well as their dependence on different air mass origins are analyzed. Although the spring 2007 was characterized by rather clean conditions, diverse case studies of cloud and aerosol occurrence during March and April 2007 are presented in more detail, including temporal development and main optical properties as depolarization, backscatter and extinction coefficients. Links between air mass origins and optical properties can be presumed but need further evidence.

Detection of large above-ground biomass variability in lowland forest ecosystems by airborne LiDAR

Directory of Open Access Journals (Sweden)

J. Jubanski

2013-06-01

Full Text Available Quantification of tropical forest above-ground biomass (AGB over large areas as input for Reduced Emissions from Deforestation and forest Degradation (REDD+ projects and climate change models is challenging. This is the first study which attempts to estimate AGB and its variability across large areas of tropical lowland forests in Central Kalimantan (Indonesia through correlating airborne light detection and ranging (LiDAR to forest inventory data. Two LiDAR height metrics were analysed, and regression models could be improved through the use of LiDAR point densities as input (R2 = 0.88; n = 52. Surveying with a LiDAR point density per square metre of about 4 resulted in the best cost / benefit ratio. We estimated AGB for 600 km of LiDAR tracks and showed that there exists a considerable variability of up to 140% within the same forest type due to varying environmental conditions. Impact from logging operations and the associated AGB losses dating back more than 10 yr could be assessed by LiDAR but not by multispectral satellite imagery. Comparison with a Landsat classification for a 1 million ha study area where AGB values were based on site-specific field inventory data, regional literature estimates, and default values by the Intergovernmental Panel on Climate Change (IPCC showed an overestimation of 43%, 102%, and 137%, respectively. The results show that AGB overestimation may lead to wrong greenhouse gas (GHG emission estimates due to deforestation in climate models. For REDD+ projects this leads to inaccurate carbon stock estimates and consequently to significantly wrong REDD+ based compensation payments.

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...

Multiscale influence of woody riparian vegetation on fluvial topography quantified with ground-based and airborne lidar

Science.gov (United States)

Bywater-Reyes, Sharon; Wilcox, Andrew C.; Diehl, Rebecca M.

2017-06-01

Coupling between riparian vegetation and river processes can result in the coevolution of plant communities and channel morphology. Quantifying biotic-abiotic interactions remains difficult because of the challenges in making and analyzing appropriately scaled observations. We measure the influence of woody vegetation on channel topography at the patch and reach scales in a sand bed, dryland river system (Santa Maria River, Arizona) with native Populus and invasive Tamarix. At the patch scale, we use ground-based lidar to relate plant morphology to "tail bars" formed in the lee of vegetation. We find vegetation roughness density (λf) to most influence tail-bar shape and size, suggesting coherent flow structures associated with roughness density are responsible for sediment deposition at this scale. Using airborne lidar, we test whether relationships between topography and vegetation morphology observed at the patch scale are persistent at the reach scale. We find that elevation of the channel (relative to the local mean) covaries with a metric of vegetation density, indicating analogous influences of vegetation density on topography across spatial scales. While these results are expected, our approach provides insight regarding interactions between woody riparian vegetation and channel topography at multiple scales, and a means to quantify such interactions for use in other field settings.

Retrieval method of aerosol extinction coefficient profile based on backscattering, side-scattering and Raman-scattering lidar

Science.gov (United States)

Shan, Huihui; Zhang, Hui; Liu, Junjian; Tao, Zongming; Wang, Shenhao; Ma, Xiaomin; Zhou, Pucheng; Yao, Ling; Liu, Dong; Xie, Chenbo; Wang, Yingjian

2018-03-01

Aerosol extinction coefficient profile is an essential parameter for atmospheric radiation model. It is difficult to get higher signal to noise ratio (SNR) of backscattering lidar from the ground to the tropopause especially in near range. Higher SNR problem can be solved by combining side-scattering and backscattering lidar. Using Raman-scattering lidar, aerosol extinction to backscatter ratio (lidar ratio) can be got. Based on side-scattering, backscattering and Raman-scattering lidar system, aerosol extinction coefficient is retrieved precisely from the earth's surface to the tropopause. Case studies show this method is reasonable and feasible.

Helicopter-based lidar system for monitoring the upper ocean and terrain surface

International Nuclear Information System (INIS)

Lee, Kwi Joo; Park, Youngsik; Bunkin, Alexey; Pershin, Serguei; Voliak, Konstantin; Nunes, Raul

2002-01-01

A compact helicopter-based lidar system is developed and tested under laboratory and field conditions. It is shown that the lidar can measure concentrations of chlorophyll a and dissolved organic matter at the surface of water bodies, detect fluorescence spectra of ground vegetation at a distance of up to 530 m, and determine the vertical profile of light-scattering particle concentration in the upper ocean. The possibilities of the lidar system are demonstrated by detection of polluted areas at the ocean surface, by online monitoring of three-dimensional distribution of light-scattering layers, and by recognition of plant types and physiological states

Advances in High Energy Solid-State Pulsed 2-Micron Lidar Development for Ground and Airborne Wind, Water Vapor and CO2 Measurements

Science.gov (United States)

Singh, Upendra N.; Yu, Jirong; Petros, Mulugeta; Refaat, Tamer; Kavaya, Michael J.; Remus, Ruben

2015-01-01

NASA Langley Research Center has a long history of developing 2-micron lasers. From fundamental spectroscopy research, theoretical prediction of new materials, laser demonstration and engineering of lidar systems, it has been a very successful program spanning around two decades. Successful development of 2-micron lasers has led to development of a state-of-the-art compact lidar transceiver for a pulsed coherent Doppler lidar system for wind measurement with an unprecedented laser pulse energy of 250 millijoules in a rugged package. This high pulse energy is produced by a Ho:Tm:LuLiF laser with an optical amplifier. While the lidar is meant for use as an airborne instrument, ground-based tests were carried out to characterize performance of the lidar. Atmospheric measurements will be presented, showing the lidar's capability for wind measurement in the atmospheric boundary layer and free troposphere. Lidar wind measurements are compared to a balloon sonde, showing good agreement between the two sensors. Similar architecture has been used to develop a high energy, Ho:Tm:YLF double-pulsed 2-micron Integrated Differential Absorption Lidar (IPDA) instrument based on direct detection technique that provides atmospheric column CO2 measurements. This instrument has been successfully used to measure atmospheric CO2 column density initially from a ground mobile lidar trailer, and then it was integrated on B-200 plane and 20 hours of flight measurement were made from an altitude ranging 1500 meters to 8000 meters. These measurements were compared to in-situ measurements and National Oceanic and Atmospheric Administration (NOAA) airborne flask measurement to derive the dry mixing ratio of the column CO2 by reflecting the signal by various reflecting surfaces such as land, vegetation, ocean surface, snow and sand. The lidar measurements when compared showed a very agreement with in-situ and airborne flask measurement. NASA Langley Research Center is currently developing a

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.

In-situ Calibration of Ground -based Lidar instrument

DEFF Research Database (Denmark)

Georgieva Yankova, Ginka; Villanueva, Héctor

This report presents the result of the lidar in-situ calibration performed at DTU’s test site for large wind turbine at Østerild, Denmark. Calibration is here understood as the establishment of a relation between the reference wind speed measurements with measurement uncertainties provided by mea...

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.

Further Studies of Forest Structure Parameter Retrievals Using the Echidna® Ground-Based Lidar

Science.gov (United States)

Strahler, A. H.; Yao, T.; Zhao, F.; Yang, X.; Schaaf, C.; Wang, Z.; Li, Z.; Woodcock, C. E.; Culvenor, D.; Jupp, D.; Newnham, G.; Lovell, J.

2012-12-01

Ongoing work with the Echidna® Validation Instrument (EVI), a full-waveform, ground-based scanning lidar (1064 nm) developed by Australia's CSIRO and deployed by Boston University in California conifers (2008) and New England hardwood and softwood (conifer) stands (2007, 2009, 2010), confirms the importance of slope correction in forest structural parameter retrieval; detects growth and disturbance over periods of 2-3 years; provides a new way to measure the between-crown clumping factor in leaf area index retrieval using lidar range; and retrieves foliage profiles with more lower-canopy detail than a large-footprint aircraft scanner (LVIS), while simulating LVIS foliage profiles accurately from a nadir viewpoint using a 3-D point cloud. Slope correction is important for accurate retrieval of forest canopy structural parameters, such as mean diameter at breast height (DBH), stem count density, basal area, and above-ground biomass. Topographic slope can induce errors in parameter retrievals because the horizontal plane of the instrument scan, which is used to identify, measure, and count tree trunks, will intersect trunks below breast height in the uphill direction and above breast height in the downhill direction. A test of three methods at southern Sierra Nevada conifer sites improved the range of correlations of these EVI-retrieved parameters with field measurements from 0.53-0.68 to 0.85-0.93 for the best method. EVI scans can detect change, including both growth and disturbance, in periods of two to three years. We revisited three New England forest sites scanned in 2007-2009 or 2007-2010. A shelterwood stand at the Howland Experimental Forest, Howland, Maine, showed increased mean DBH, above-ground biomass and leaf area index between 2007 and 2009. Two stands at the Harvard Forest, Petersham, Massachusetts, suffered reduced leaf area index and reduced stem count density as the result of an ice storm that damaged the stands. At one stand, broken tops were

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...

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.

LiDAR and Orthophoto Synergy to optimize Object-Based Landscape Change: Analysis of an Active Landslide

Directory of Open Access Journals (Sweden)

Martijn Kamps

2017-08-01

Full Text Available Active landslides have three major effects on landscapes: (1 land cover change, (2 topographical change, and (3 above ground biomass change. Data derived from multi-temporal Light Detection and Ranging technology (LiDAR are used in combination with multi-temporal orthophotos to quantify these changes between 2006 and 2012, caused by an active deep-seated landslide near the village of Doren in Austria. Land-cover is classified by applying membership-based classification and contextual improvements based on the synergy of orthophotos and LiDAR-based elevation data. Topographical change is calculated by differencing of LiDAR derived digital terrain models. The above ground biomass is quantified by applying a local-maximum algorithm for tree top detection, in combination with allometric equations. The land cover classification accuracies were improved from 65% (using only LiDAR and 76% (using only orthophotos to 90% (using data synergy for 2006. A similar increase from respectively 64% and 75% to 91% was established for 2012. The increased accuracies demonstrate the effectiveness of using data synergy of LiDAR and orthophotos using object-based image analysis to quantify landscape changes, caused by an active landslide. The method has great potential to be transferred to larger areas for use in landscape change analyses.

Potential of ALOS2 and NDVI to Estimate Forest Above-Ground Biomass, and Comparison with Lidar-Derived Estimates

Directory of Open Access Journals (Sweden)

Gaia Vaglio Laurin

2016-12-01

Full Text Available Remote sensing supports carbon estimation, allowing the upscaling of field measurements to large extents. Lidar is considered the premier instrument to estimate above ground biomass, but data are expensive and collected on-demand, with limited spatial and temporal coverage. The previous JERS and ALOS SAR satellites data were extensively employed to model forest biomass, with literature suggesting signal saturation at low-moderate biomass values, and an influence of plot size on estimates accuracy. The ALOS2 continuity mission since May 2014 produces data with improved features with respect to the former ALOS, such as increased spatial resolution and reduced revisit time. We used ALOS2 backscatter data, testing also the integration with additional features (SAR textures and NDVI from Landsat 8 data together with ground truth, to model and map above ground biomass in two mixed forest sites: Tahoe (California and Asiago (Alps. While texture was useful to improve the model performance, the best model was obtained using joined SAR and NDVI (R2 equal to 0.66. In this model, only a slight saturation was observed, at higher levels than what usually reported in literature for SAR; the trend requires further investigation but the model confirmed the complementarity of optical and SAR datatypes. For comparison purposes, we also generated a biomass map for Asiago using lidar data, and considered a previous lidar-based study for Tahoe; in these areas, the observed R2 were 0.92 for Tahoe and 0.75 for Asiago, respectively. The quantitative comparison of the carbon stocks obtained with the two methods allows discussion of sensor suitability. The range of local variation captured by lidar is higher than those by SAR and NDVI, with the latter showing overestimation. However, this overestimation is very limited for one of the study areas, suggesting that when the purpose is the overall quantification of the stored carbon, especially in areas with high carbon

Coastal change analysis of Lovells Island using high resolution ground based LiDAR imagery

Science.gov (United States)

Ly, Jennifer K.

Many methods have been employed to study coastline change. These methods range from historical map analysis to GPS surveys to modern airborne LiDAR and satellite imagery. These previously used methods can be time consuming, labor intensive, and expensive and have varying degrees of accuracy and temporal coverage. Additionally, it is often difficult to apply such techniques in direct response to an isolated event within an appropriate temporal framework. Here we utilize a new ground based Canopy Biomass LiDAR (CBL) system built at The University of Massachusetts Boston (in collaboration with the Rochester Institute of Technology) in order to identify and analyze coastal change on Lovells Island, Boston Harbor. Surveys of a bluff developing in an eroding drumlin and beach cusps on a high-energy cobble beach on Lovells Island were conducted in June, September and December of 2013. At each site for each survey, the CBL was set up and multiple scans of each feature were taken on a predetermined transect that was established parallel to the high-water mark at distances relative to the scale of the bluff and cusps. The scans from each feature were compiled, integrated and visualized using Meshlab. Results from our surveys indicate that the highly portable and easy to deploy CBL system produces images of exceptional clarity, with the capacity to resolve small-scale changes to coastal features and systems. The CBL, while still under development (and coastal surveying protocols with it are just being established), appears to be an ideal tool for analyzing coastal geological features and is anticipated to prove to be a useful tool for the observation and analysis of coastal change. Furthermore, there is significant potential for utilizing the low cost ultra-portable CBL in frequent deployments to develop small-scale erosion rate and sediment budget analyses.

A new air quality modelling approach at the regional scale using lidar data assimilation

International Nuclear Information System (INIS)

Wang, Y.

2013-01-01

Assimilation of lidar observations for air quality modelling is investigated via the development of a new model, which assimilates ground-based lidar network measurements using optimal interpolation (OI) in a chemistry transport model. First, a tool for assimilating PM 10 (particulate matter with a diameter lower than 10 μm) concentration measurements on the vertical is developed in the air quality modelling platform POLYPHEMUS. It is applied to western Europe for one month from 15 July to 15 August 2001 to investigate the potential impact of future ground-based lidar networks on analysis and short-term forecasts (the description of the future) of PM 10 . The efficiency of assimilating lidar network measurements is compared to the efficiency of assimilating concentration measurements from the AirBase ground network, which includes about 500 stations in western Europe. A sensitivity study on the number and location of required lidars is also performed to help define an optimal lidar network for PM 10 forecasts. Secondly, a new model for simulating normalised lidar signals (PR 2 ) is developed and integrated in POLYPHEMUS. Simulated lidar signals are compared to hourly ground-based mobile and in-situ lidar observations performed during the MEGAPOLI (Mega-cities: Emissions, urban, regional and Global Atmospheric Pollution and climate effects, and Integrated tools for assessment and mitigation) summer experiment in July 2009. It is found that the model correctly reproduces the vertical distribution of aerosol optical properties and their temporal variability. Additionally, two new algorithms for assimilating lidar signals are presented and evaluated during MEGAPOLI. The aerosol simulations without and with lidar data assimilation are evaluated using the AIRPARIF (a regional operational network in charge of air quality survey around the Paris area) database to demonstrate the feasibility and the usefulness of assimilating lidar profiles for aerosol forecasts. Finally

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.

IEA Wind Task 32: Wind Lidar Identifying and Mitigating Barriers to the Adoption of Wind Lidar

Directory of Open Access Journals (Sweden)

Andrew Clifton

2018-03-01

Full Text Available 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 taken to confirm or mitigate the barriers. Task 32 will continue to be a meeting point for the international wind lidar community until at least 2020 and welcomes old and new participants.

Test of ground-based Lidar instrument WLS7-106

DEFF Research Database (Denmark)

Gómez Arranz, Paula

This report presents the result of the test performed for the given Windcube at DTU’s test site for large wind turbine at Høvsøre, Denmark. The test aims at establishing a relation between the reference wind measurements and corresponding lidar wind indications, and evaluating a set of quality...

Test of ground-based lidar instrument WLS7-159

DEFF Research Database (Denmark)

Gómez Arranz, Paula; Wagner, Rozenn

This report presents the result of the test performed for the given Windcube at DTU’s test site for large wind turbine at Høvsøre, Denmark. The test aims at establishing a relation between the reference wind measurements and corresponding lidar wind indications, and evaluating a set of quality...

Calibration of ground-based Lidar instrument WLS7-73

DEFF Research Database (Denmark)

Yordanova, Ginka; Gómez Arranz, Paula

This report presents the result of the lidar calibration performed for the given WLS7 Windcube 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 uncertain...

Airborne LIDAR borsight error calibration based on surface coincide

International Nuclear Information System (INIS)

Yuan, Fangyan; Li, Guoqing; Zuo, Zhengli; Li, Dong; Qi, Zengying; Qiu, Wen; Tan, Junxiang

2014-01-01

Light Detection and Ranging (LIDAR) is a system which can directly collect three-dimensional coordinate information of ground point and laser reflection strength information. With the wide application of LIDAR system, users hope to get more accurate results. Boresight error has an important effect on data accuracy and thus, it is thought that eliminating the error is very important. In recent years, many methods have been proposed to eliminate the error. Generally, they can be categorized into tie point method and surface matching method. In this paper, we propose another method called try value method based on surface coincide that is used in actual production by many companies. The method is simple and operable. Further, the efficacy of the method was demonstrated by analyzing the data from Zhangye city

Ground-based mobile scanning LIDAR for remote sensing of contrails

Directory of Open Access Journals (Sweden)

F. Homburg

Full Text Available Air traffic is a source of trace gases in the upper troposphere and lower stratosphere. Contrails readily form from water vapor exhausts under favorable meteorological conditions. Since contrails are ice crystal clouds like natural cirrus clouds, they bear a greenhouse potential which has to be investigated. The IFU has built a scanning lidar system employing a pulsed Nd:YAG laser as the emitter and a 52-cm diameter telescope as the receiver. Signals are processed in several channels to investigate depolarization and wavelength dependencies of the light backscattered from ice crystals. These investigations are aimed at the formation and life cycles of contrails, their optical properties, and their climatological consequences in areas of dense air traffic. The experimental lidar setup is described and a sample measurement is shown.

Ground-based mobile scanning LIDAR for remote sensing of contrails

Directory of Open Access Journals (Sweden)

V. Freudenthaler

1994-08-01

Full Text Available Air traffic is a source of trace gases in the upper troposphere and lower stratosphere. Contrails readily form from water vapor exhausts under favorable meteorological conditions. Since contrails are ice crystal clouds like natural cirrus clouds, they bear a greenhouse potential which has to be investigated. The IFU has built a scanning lidar system employing a pulsed Nd:YAG laser as the emitter and a 52-cm diameter telescope as the receiver. Signals are processed in several channels to investigate depolarization and wavelength dependencies of the light backscattered from ice crystals. These investigations are aimed at the formation and life cycles of contrails, their optical properties, and their climatological consequences in areas of dense air traffic. The experimental lidar setup is described and a sample measurement is shown.

A Ground-Based Doppler Radar and Micropulse Lidar Forward Simulator for GCM Evaluation of Arctic Mixed-Phase Clouds: Moving Forward Towards an Apples-to-apples Comparison of Hydrometeor Phase

Science.gov (United States)

Lamer, K.; Fridlind, A. M.; Ackerman, A. S.; Kollias, P.; Clothiaux, E. E.

2017-12-01

An important aspect of evaluating Artic cloud representation in a general circulation model (GCM) consists of using observational benchmarks which are as equivalent as possible to model output in order to avoid methodological bias and focus on correctly diagnosing model dynamical and microphysical misrepresentations. However, current cloud observing systems are known to suffer from biases such as limited sensitivity, and stronger response to large or small hydrometeors. Fortunately, while these observational biases cannot be corrected, they are often well understood and can be reproduced in forward simulations. Here a ground-based millimeter wavelength Doppler radar and micropulse lidar forward simulator able to interface with output from the Goddard Institute for Space Studies (GISS) ModelE GCM is presented. ModelE stratiform hydrometeor fraction, mixing ratio, mass-weighted fall speed and effective radius are forward simulated to vertically-resolved profiles of radar reflectivity, Doppler velocity and spectrum width as well as lidar backscatter and depolarization ratio. These forward simulated fields are then compared to Atmospheric Radiation Measurement (ARM) North Slope of Alaska (NSA) ground-based observations to assess cloud vertical structure (CVS). Model evalution of Arctic mixed-phase cloud would also benefit from hydrometeor phase evaluation. While phase retrieval from synergetic observations often generates large uncertainties, the same retrieval algorithm can be applied to observed and forward-simulated radar-lidar fields, thereby producing retrieved hydrometeor properties with potentially the same uncertainties. Comparing hydrometeor properties retrieved in exactly the same way aims to produce the best apples-to-apples comparisons between GCM ouputs and observations. The use of a comprenhensive ground-based forward simulator coupled with a hydrometeor classification retrieval algorithm provides a new perspective for GCM evaluation of Arctic mixed

Assessment of NASA airborne laser altimetry data using ground-based GPS data near Summit Station, Greenland

Science.gov (United States)

Brunt, Kelly M.; Hawley, Robert L.; Lutz, Eric R.; Studinger, Michael; Sonntag, John G.; Hofton, Michelle A.; Andrews, Lauren C.; Neumann, Thomas A.

2017-03-01

A series of NASA airborne lidars have been used in support of satellite laser altimetry missions. These airborne laser altimeters have been deployed for satellite instrument development, for spaceborne data validation, and to bridge the data gap between satellite missions. We used data from ground-based Global Positioning System (GPS) surveys of an 11 km long track near Summit Station, Greenland, to assess the surface-elevation bias and measurement precision of three airborne laser altimeters including the Airborne Topographic Mapper (ATM), the Land, Vegetation, and Ice Sensor (LVIS), and the Multiple Altimeter Beam Experimental Lidar (MABEL). Ground-based GPS data from the monthly ground-based traverses, which commenced in 2006, allowed for the assessment of nine airborne lidar surveys associated with ATM and LVIS between 2007 and 2016. Surface-elevation biases for these altimeters - over the flat, ice-sheet interior - are less than 0.12 m, while assessments of measurement precision are 0.09 m or better. Ground-based GPS positions determined both with and without differential post-processing techniques provided internally consistent solutions. Results from the analyses of ground-based and airborne data provide validation strategy guidance for the Ice, Cloud, and land Elevation Satellite 2 (ICESat-2) elevation and elevation-change data products.

Reconciling Ground-Based and Space-Based Estimates of the Frequency of Occurrence and Radiative Effect of Clouds around Darwin, Australia

Energy Technology Data Exchange (ETDEWEB)

Protat, Alain; Young, Stuart; McFarlane, Sally A.; L' Ecuyer, Tristan; Mace, Gerald G.; Comstock, Jennifer M.; Long, Charles N.; Berry, Elizabeth; Delanoe, Julien

2014-02-01

The objective of this paper is to investigate whether estimates of the cloud frequency of occurrence and associated cloud radiative forcing as derived from ground-based and satellite active remote sensing and radiative transfer calculations can be reconciled over a well instrumented active remote sensing site located in Darwin, Australia, despite the very different viewing geometry and instrument characteristics. It is found that the ground-based radar-lidar combination at Darwin does not detect most of the cirrus clouds above 10 km (due to limited lidar detection capability and signal obscuration by low-level clouds) and that the CloudSat radar - Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) combination underreports the hydrometeor frequency of occurrence below 2 km height, due to instrument limitations at these heights. The radiative impact associated with these differences in cloud frequency of occurrence is large on the surface downwelling shortwave fluxes (ground and satellite) and the top-of atmosphere upwelling shortwave and longwave fluxes (ground). Good agreement is found for other radiative fluxes. Large differences in radiative heating rate as derived from ground and satellite radar-lidar instruments and RT calculations are also found above 10 km (up to 0.35 Kday-1 for the shortwave and 0.8 Kday-1 for the longwave). Given that the ground-based and satellite estimates of cloud frequency of occurrence and radiative impact cannot be fully reconciled over Darwin, caution should be exercised when evaluating the representation of clouds and cloud-radiation interactions in large-scale models and limitations of each set of instrumentation should be considered when interpreting model-observations differences.

Mapping the spatial pattern of temperate forest above ground biomass by integrating airborne lidar with Radarsat-2 imagery via geostatistical models

Science.gov (United States)

Li, Wang; Niu, Zheng; Gao, Shuai; Wang, Cheng

2014-11-01

Light Detection and Ranging (LiDAR) and Synthetic Aperture Radar (SAR) are two competitive active remote sensing techniques in forest above ground biomass estimation, which is important for forest management and global climate change study. This study aims to further explore their capabilities in temperate forest above ground biomass (AGB) estimation by emphasizing the spatial auto-correlation of variables obtained from these two remote sensing tools, which is a usually overlooked aspect in remote sensing applications to vegetation studies. Remote sensing variables including airborne LiDAR metrics, backscattering coefficient for different SAR polarizations and their ratio variables for Radarsat-2 imagery were calculated. First, simple linear regression models (SLR) was established between the field-estimated above ground biomass and the remote sensing variables. Pearson's correlation coefficient (R2) was used to find which LiDAR metric showed the most significant correlation with the regression residuals and could be selected as co-variable in regression co-kriging (RCoKrig). Second, regression co-kriging was conducted by choosing the regression residuals as dependent variable and the LiDAR metric (Hmean) with highest R2 as co-variable. Third, above ground biomass over the study area was estimated using SLR model and RCoKrig model, respectively. The results for these two models were validated using the same ground points. Results showed that both of these two methods achieved satisfactory prediction accuracy, while regression co-kriging showed the lower estimation error. It is proved that regression co-kriging model is feasible and effective in mapping the spatial pattern of AGB in the temperate forest using Radarsat-2 data calibrated by airborne LiDAR metrics.

Section-Based Tree Species Identification Using Airborne LIDAR Point Cloud

Science.gov (United States)

Yao, C.; Zhang, X.; Liu, H.

2017-09-01

The application of LiDAR data in forestry initially focused on mapping forest community, particularly and primarily intended for largescale forest management and planning. Then with the smaller footprint and higher sampling density LiDAR data available, detecting individual tree overstory, estimating crowns parameters and identifying tree species are demonstrated practicable. This paper proposes a section-based protocol of tree species identification taking palm tree as an example. Section-based method is to detect objects through certain profile among different direction, basically along X-axis or Y-axis. And this method improve the utilization of spatial information to generate accurate results. Firstly, separate the tree points from manmade-object points by decision-tree-based rules, and create Crown Height Mode (CHM) by subtracting the Digital Terrain Model (DTM) from the digital surface model (DSM). Then calculate and extract key points to locate individual trees, thus estimate specific tree parameters related to species information, such as crown height, crown radius, and cross point etc. Finally, with parameters we are able to identify certain tree species. Comparing to species information measured on ground, the portion correctly identified trees on all plots could reach up to 90.65 %. The identification result in this research demonstrate the ability to distinguish palm tree using LiDAR point cloud. Furthermore, with more prior knowledge, section-based method enable the process to classify trees into different classes.

Fusion of LIDAR Data and Multispectral Imagery for Effective Building Detection Based on Graph and Connected Component Analysis

Science.gov (United States)

Gilani, S. A. N.; Awrangjeb, M.; Lu, G.

2015-03-01

Building detection in complex scenes is a non-trivial exercise due to building shape variability, irregular terrain, shadows, and occlusion by highly dense vegetation. In this research, we present a graph based algorithm, which combines multispectral imagery and airborne LiDAR information to completely delineate the building boundaries in urban and densely vegetated area. In the first phase, LiDAR data is divided into two groups: ground and non-ground data, using ground height from a bare-earth DEM. A mask, known as the primary building mask, is generated from the non-ground LiDAR points where the black region represents the elevated area (buildings and trees), while the white region describes the ground (earth). The second phase begins with the process of Connected Component Analysis (CCA) where the number of objects present in the test scene are identified followed by initial boundary detection and labelling. Additionally, a graph from the connected components is generated, where each black pixel corresponds to a node. An edge of a unit distance is defined between a black pixel and a neighbouring black pixel, if any. An edge does not exist from a black pixel to a neighbouring white pixel, if any. This phenomenon produces a disconnected components graph, where each component represents a prospective building or a dense vegetation (a contiguous block of black pixels from the primary mask). In the third phase, a clustering process clusters the segmented lines, extracted from multispectral imagery, around the graph components, if possible. In the fourth step, NDVI, image entropy, and LiDAR data are utilised to discriminate between vegetation, buildings, and isolated building's occluded parts. Finally, the initially extracted building boundary is extended pixel-wise using NDVI, entropy, and LiDAR data to completely delineate the building and to maximise the boundary reach towards building edges. The proposed technique is evaluated using two Australian data sets

Determination of the smoke-plume heights and their dynamics with ground-based scanning LIDAR

Science.gov (United States)

V. Kovalev; A. Petkov; C. Wold; S. Urbanski; W. M. Hao

2015-01-01

Lidar-data processing techniques are analyzed, which allow determining smoke-plume heights and their dynamics and can be helpful for the improvement of smoke dispersion and air quality models. The data processing algorithms considered in the paper are based on the analysis of two alternative characteristics related to the smoke dispersion process: the regularized...

Assessment of cirrus cloud and aerosol radiative effect in South-East Asia by ground-based NASA MPLNET lidar network data and CALIPSO satellite measurements

Science.gov (United States)

Lolli, Simone; Campbell, James R.; Lewis, Jasper R.; Welton, Ellsworth J.; Di Girolamo, Paolo; Fatkhuroyan, Fatkhuroyan; Gu, Yu; Marquis, Jared W.

2017-10-01

Aerosol, together with cirrus clouds, play a fundamental role in the earth-atmosphere system radiation budget, especially at tropical latitudes, where the Earth surface coverage by cirrus cloud can easily reach 70%. In this study we evaluate the combined aerosol and cirrus cloud net radiative effects in a wild and barren region like South East Asia. This part of the world is extremely vulnerable to climate change and it is source of important anthropogenic and natural aerosol emissions. The analysis has been carried out by computing cirrus cloud and aerosol net radiative effects through the Fu-Liou-Gu atmospheric radiative transfer model, adequately adapted to input lidar measurements, at surface and top-of-the atmosphere. The aerosol radiative effects were computed respectively using the retrieved lidar extinction from Cloud-Aerosol Lidar with Orthogonal Polarization in 2011 and 2012 and the lidar on-board of Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations for the South East Asia Region (27N-12S, 77E-132E) with 5° x 5° spatial resolution. To assess the cirrus cloud radiative effect, we used the ground-based Micro Pulse Lidar Network measurements at Singapore permanent observational site. Results put in evidence that strong aerosol emission areas are related on average to a net surface cooling. On the contrary, cirrus cloud radiative effect shows a net daytime positive warming of the system earth-atmosphere. This effect is weak over the ocean where the albedo is lower and never counter-balances the net cooling produced by aerosols. The net cooling is stronger in 2011, with an associated reduction in precipitations by the four of the five rain-gauges stations deployed in three regions as Sumatra, Kalimantan and Java with respect to 2012. We can speculate that aerosol emissions may be associated with lower rainfall, however some very important phenomena as El Nino Southern Oscillation , Madden-Julian Oscillation, Monsoon and Indian Dipole are not

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.

Test of ground-based Lidar instrument WLS200S-10

DEFF Research Database (Denmark)

Gómez Arranz, Paula

This report presents the result of the test performed for the given Windcube at DTU’s test site for large wind turbine at Høvsøre, Denmark. The test aims at establishing a relation between the reference wind measurements and corresponding lidar wind indications, and evaluating a set of quality...

Test of ground-based Lidar instrument WLS200S-11

DEFF Research Database (Denmark)

Gómez Arranz, Paula

This report presents the result of the test performed for the given Windcube at DTU’s test site for large wind turbine at Høvsøre, Denmark. The test aims at establishing a relation between the reference wind measurements and corresponding lidar wind indications, and evaluating a set of quality...

GROUND DEFORMATION EXTRACTION USING VISIBLE IMAGES AND LIDAR DATA IN MINING AREA

Directory of Open Access Journals (Sweden)

W. Hu

2016-06-01

Full Text Available Recognition and extraction of mining ground deformation can help us understand the deformation process and space distribution, and estimate the deformation laws and trends. This study focuses on the application of ground deformation detection and extraction combining with high resolution visible stereo imagery, LiDAR observation point cloud data and historical data. The DEM in large mining area is generated using high-resolution satellite stereo images, and ground deformation is obtained through time series analysis combined with historical DEM data. Ground deformation caused by mining activities are detected and analyzed to explain the link between the regional ground deformation and local deformation. A district of covering 200 km2 around the West Open Pit Mine in Fushun of Liaoning province, a city located in the Northeast China is chosen as the test area for example. Regional and local ground deformation from 2010 to 2015 time series are detected and extracted with DEMs derived from ZY-3 images and LiDAR point DEMs in the case study. Results show that the mean regional deformation is 7.1 m of rising elevation with RMS 9.6 m. Deformation of rising elevation and deformation of declining elevation couple together in local area. The area of higher elevation variation is 16.3 km2 and the mean rising value is 35.8 m with RMS 15.7 m, while the deformation area of lower elevation variation is 6.8 km2 and the mean declining value is 17.6 m with RMS 9.3 m. Moreover, local large deformation and regional slow deformation couple together, the deformation in local mining activities has expanded to the surrounding area, a large ground fracture with declining elevation has been detected and extracted in the south of West Open Pit Mine, the mean declining elevation of which is 23.1 m and covering about 2.3 km2 till 2015. The results in this paper are preliminary currently; we are making efforts to improve more precision results with

Biomass burning aerosols characterization from ground based and profiling measurements

Science.gov (United States)

Marin, Cristina; Vasilescu, Jeni; Marmureanu, Luminita; Ene, Dragos; Preda, Liliana; Mihailescu, Mona

2018-04-01

The study goal is to assess the chemical and optical properties of aerosols present in the lofted layers and at the ground. The biomass burning aerosols were evaluated in low level layers from multi-wavelength lidar measurements, while chemical composition at ground was assessed using an Aerosol Chemical Speciation Monitor (ACSM) and an Aethalometer. Classification of aerosol type and specific organic markers were used to explore the potential to sense the particles from the same origin at ground base and on profiles.

Filtering Airborne LIDAR Data by AN Improved Morphological Method Based on Multi-Gradient Analysis

Science.gov (United States)

Li, Y.

2013-05-01

The technology of airborne Light Detection And Ranging (LIDAR) is capable of acquiring dense and accurate 3D geospatial data. Although many related efforts have been made by a lot of researchers in the last few years, LIDAR data filtering is still a challenging task, especially for area with high relief or hybrid geographic features. In order to address the bare-ground extraction from LIDAR point clouds of complex landscapes, a novel morphological filtering algorithm is proposed based on multi-gradient analysis in terms of the characteristic of LIDAR data distribution in this paper. Firstly, point clouds are organized by an index mesh. Then, the multigradient of each point is calculated using the morphological method. And, objects are removed gradually by choosing some points to carry on an improved opening operation constrained by multi-gradient iteratively. 15 sample data provided by ISPRS Working Group III/3 are employed to test the filtering algorithm proposed. These sample data include those environments that may lead to filtering difficulty. Experimental results show that filtering algorithm proposed by this paper is of high adaptability to various scenes including urban and rural areas. Omission error, commission error and total error can be simultaneously controlled in a relatively small interval. This algorithm can efficiently remove object points while preserves ground points to a great degree.

CALIPSO-Inferred Aerosol Direct Radiative Effects: Bias Estimates Using Ground-Based Raman Lidars

Science.gov (United States)

Thorsen, Tyler; Fu, Qiang

2016-01-01

Observational constraints on the change in the radiative energy budget caused by the presence of aerosols, i.e. the aerosol direct radiative effect (DRE), have recently been made using observations from the Cloud- Aerosol Lidar and Infrared Pathfinder Satellite (CALIPSO). CALIPSO observations have the potential to provide improved global estimates of aerosol DRE compared to passive sensor-derived estimates due to CALIPSO's ability to perform vertically-resolved aerosol retrievals over all surface types and over cloud. In this study we estimate the uncertainties in CALIPSO-inferred aerosol DRE using multiple years of observations from the Atmospheric Radiation Measurement (ARM) program's Raman lidars (RL) at midlatitude and tropical sites. Examined are assumptions about the ratio of extinction-to-backscatter (i.e. the lidar ratio) made by the CALIPSO retrievals, which are needed to retrieve the aerosol extinction profile. The lidar ratio is shown to introduce minimal error in the mean aerosol DRE at the top-of-atmosphere and surface. It is also shown that CALIPSO is unable to detect all radiatively-significant aerosol, resulting in an underestimate in the magnitude of the aerosol DRE by 30-50%. Therefore, global estimates of the aerosol DRE inferred from CALIPSO observations are likely too weak.

Where’s the Ground Surface? – Elevation Bias in LIDAR-derived Digital Elevation Models Due to Dense Vegetation in Oregon Tidal Marshes

Science.gov (United States)

Light Detection and Ranging (LIDAR) is a powerful resource for coastal and wetland managers and its use is increasing. Vegetation density and other land cover characteristics influence the accuracy of LIDAR-derived ground surface digital elevation models; however the degree to wh...

Helicopter-borne observations of the continental background aerosol in combination with remote sensing and ground-based measurements

Science.gov (United States)

Düsing, Sebastian; Wehner, Birgit; Seifert, Patric; Ansmann, Albert; Baars, Holger; Ditas, Florian; Henning, Silvia; Ma, Nan; Poulain, Laurent; Siebert, Holger; Wiedensohler, Alfred; Macke, Andreas

2018-01-01

This paper examines the representativeness of ground-based in situ measurements for the planetary boundary layer (PBL) and conducts a closure study between airborne in situ and ground-based lidar measurements up to an altitude of 2300 m. The related measurements were carried out in a field campaign within the framework of the High-Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP)2) Observational Prototype Experiment (HOPE) in September 2013 in a rural background area of central Europe.The helicopter-borne probe ACTOS (Airborne Cloud and Turbulence Observation System) provided measurements of the aerosol particle number size distribution (PNSD), the aerosol particle number concentration (PNC), the number concentration of cloud condensation nuclei (CCN-NC), and meteorological atmospheric parameters (e.g., temperature and relative humidity). These measurements were supported by the ground-based 3+2 wavelength polarization lidar system PollyXT, which provided profiles of the particle backscatter coefficient (σbsc) for three wavelengths (355, 532, and 1064 nm). Particle extinction coefficient (σext) profiles were obtained by using a fixed backscatter-to-extinction ratio (also lidar ratio, LR). A new approach was used to determine profiles of CCN-NC for continental aerosol. The results of this new approach were consistent with the airborne in situ measurements within the uncertainties.In terms of representativeness, the PNSD measurements on the ground showed a good agreement with the measurements provided with ACTOS for lower altitudes. The ground-based measurements of PNC and CCN-NC are representative of the PBL when the PBL is well mixed. Locally isolated new particle formation events on the ground or at the top of the PBL led to vertical variability in the cases presented here and ground-based measurements are not entirely representative of the PBL. Based on Mie theory (Mie, 1908), optical aerosol properties under ambient conditions for

Helicopter-borne observations of the continental background aerosol in combination with remote sensing and ground-based measurements

Directory of Open Access Journals (Sweden)

S. Düsing

2018-01-01

Full Text Available This paper examines the representativeness of ground-based in situ measurements for the planetary boundary layer (PBL and conducts a closure study between airborne in situ and ground-based lidar measurements up to an altitude of 2300 m. The related measurements were carried out in a field campaign within the framework of the High-Definition Clouds and Precipitation for Advancing Climate Prediction (HD(CP2 Observational Prototype Experiment (HOPE in September 2013 in a rural background area of central Europe.The helicopter-borne probe ACTOS (Airborne Cloud and Turbulence Observation System provided measurements of the aerosol particle number size distribution (PNSD, the aerosol particle number concentration (PNC, the number concentration of cloud condensation nuclei (CCN-NC, and meteorological atmospheric parameters (e.g., temperature and relative humidity. These measurements were supported by the ground-based 3+2 wavelength polarization lidar system PollyXT, which provided profiles of the particle backscatter coefficient (σbsc for three wavelengths (355, 532, and 1064 nm. Particle extinction coefficient (σext profiles were obtained by using a fixed backscatter-to-extinction ratio (also lidar ratio, LR. A new approach was used to determine profiles of CCN-NC for continental aerosol. The results of this new approach were consistent with the airborne in situ measurements within the uncertainties.In terms of representativeness, the PNSD measurements on the ground showed a good agreement with the measurements provided with ACTOS for lower altitudes. The ground-based measurements of PNC and CCN-NC are representative of the PBL when the PBL is well mixed. Locally isolated new particle formation events on the ground or at the top of the PBL led to vertical variability in the cases presented here and ground-based measurements are not entirely representative of the PBL. Based on Mie theory (Mie, 1908, optical aerosol properties under ambient

Ground-based eye-safe networkable micro-pulse differential absorption and high spectral resolution lidar for water vapor and aerosol profiling in the lower troposphere

Science.gov (United States)

Repasky, K. S.; Spuler, S.; Hayman, M. M.; Bunn, C. E.

2017-12-01

Atmospheric water vapor is a greenhouse gas that is known to be a significant driver of weather and climate. Several National Research Council (NRC) reports have highlighted the need for improved water vapor measurements that can capture its spatial and temporal variability as a means to improve weather predictions. Researchers at Montana State University (MSU) and the National Center for Atmospheric Research (NCAR) have developed an eye-safe diode laser based micro-pulse differential absorption lidar (MP-DIAL) for water vapor profiling in the lower troposphere. The MP-DIAL is capable of long term unattended operation and is capable of monitoring water vapor in the lower troposphere in most weather conditions. Two MP-DIAL instruments are currently operational and have been deployed at the Front Range Air Pollution and Photochemistry Experiment (FRAPPE), the Plains elevated Convection at Night (PECAN) experiment, the Perdigão experiment, and the Land Atmosphere Feedback Experiment (LAFE). For each of these field experiments, the MP-DIAL was run unattended and provided near-continuous water vapor profiles, including periods of bright daytime clouds, from 300 m above the ground level to 4 km (or the cloud base) with 150 m vertical resolution and 5 minute temporal resolution. Three additional MP-DIAL instruments are currently under construction and will result in a network of five eye-safe MP-DIAL instruments for ground based weather and climate research experiments. Taking advantage of the broad spectral coverage and modularity or the diode based architecture, a high spectral resolution lidar (HSRL) measurement capabilities was added to the second MP-DIAL instrument. The HSRL capabilities will be operational during the deployment at the LAFE field experiment. The instrument architecture will be presented along with examples of data collected during recent field experiments.

Nighttime Aerosol Optical Depth Measurements Using a Ground-based Lunar Photometer

Science.gov (United States)

Berkoff, Tim; Omar, Ali; Haggard, Charles; Pippin, Margaret; Tasaddaq, Aasam; Stone, Tom; Rodriguez, Jon; Slutsker, Ilya; Eck, Tom; Holben, Brent;

High-Throughput Phenotyping of Plant Height: Comparing Unmanned Aerial Vehicles and Ground LiDAR Estimates.

Science.gov (United States)

Madec, Simon; Baret, Fred; de Solan, Benoît; Thomas, Samuel; Dutartre, Dan; Jezequel, Stéphane; Hemmerlé, Matthieu; Colombeau, Gallian; Comar, Alexis

2017-01-01

The capacity of LiDAR and Unmanned Aerial Vehicles (UAVs) to provide plant height estimates as a high-throughput plant phenotyping trait was explored. An experiment over wheat genotypes conducted under well watered and water stress modalities was conducted. Frequent LiDAR measurements were performed along the growth cycle using a phénomobile unmanned ground vehicle. UAV equipped with a high resolution RGB camera was flying the experiment several times to retrieve the digital surface model from structure from motion techniques. Both techniques provide a 3D dense point cloud from which the plant height can be estimated. Plant height first defined as the z -value for which 99.5% of the points of the dense cloud are below. This provides good consistency with manual measurements of plant height (RMSE = 3.5 cm) while minimizing the variability along each microplot. Results show that LiDAR and structure from motion plant height values are always consistent. However, a slight under-estimation is observed for structure from motion techniques, in relation with the coarser spatial resolution of UAV imagery and the limited penetration capacity of structure from motion as compared to LiDAR. Very high heritability values ( H 2 > 0.90) were found for both techniques when lodging was not present. The dynamics of plant height shows that it carries pertinent information regarding the period and magnitude of the plant stress. Further, the date when the maximum plant height is reached was found to be very heritable ( H 2 > 0.88) and a good proxy of the flowering stage. Finally, the capacity of plant height as a proxy for total above ground biomass and yield is discussed.

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

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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.

Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches

Directory of Open Access Journals (Sweden)

Maggi Kelly

2013-08-01

Full Text Available Light detection and ranging (lidar data is increasingly being used for ecosystem monitoring across geographic scales. This work concentrates on delineating individual trees in topographically-complex, mixed conifer forest across the California’s Sierra Nevada. We delineated individual trees using vector data and a 3D lidar point cloud segmentation algorithm, and using raster data with an object-based image analysis (OBIA of a canopy height model (CHM. The two approaches are compared to each other and to ground reference data. We used high density (9 pulses/m2, discreet lidar data and WorldView-2 imagery to delineate individual trees, and to classify them by species or species types. We also identified a new method to correct artifacts in a high-resolution CHM. Our main focus was to determine the difference between the two types of approaches and to identify the one that produces more realistic results. We compared the delineations via tree detection, tree heights, and the shape of the generated polygons. The tree height agreement was high between the two approaches and the ground data (r2: 0.93–0.96. Tree detection rates increased for more dominant trees (8–100 percent. The two approaches delineated tree boundaries that differed in shape: the lidar-approach produced fewer, more complex, and larger polygons that more closely resembled real forest structure.

Spatial and optical parameters of contrails in the vortex and dispersion regime determined by means of a ground-based scanning lidar

Energy Technology Data Exchange (ETDEWEB)

Freudenthaler, V; Homburg, F; Jaeger, H [Fraunhofer-Inst. fuer Atmosphaerische Umweltforschung (IFU), Garmisch-Partenkirchen (Germany)

1998-12-31

The spatial growth of individual condensation trails (contrails) of commercial aircrafts in the time range from 15 s to 60 min behind the aircraft is investigated by means of a ground-based scanning backscatter lidar. The growth in width is mainly governed by wind shear and varies between 18 m/min and 140 m/min. The growth of the cross-section varies between 3500 m{sup 2}/min and 25000 m{sup 2}/min. These values are in agreement with results of model calculations and former field measurements. The vertical growth is often limited by boundaries of the humid layer at flight level, but values up to 18 m/min were observed. Optical parameters like depolarization, optical depth and lidar ratio, i.e. the extinction-to-backscatter ratio, have been retrieved from the measurements at a wavelength of 532 nm. The linear depolarization rises from values as low as 0.06 for a young contrail (10 s old) to values around 0.5, typical for aged contrails. The latter indicates the transition from non-crystalline to crystalline particles in persistent contrails within a few minutes. The scatter of depolarization values measured in individual contrails is narrow, independent of the contrails age, and suggests a rather uniform growth of the particles inside a contrail. (author) 18 refs.

Spatial and optical parameters of contrails in the vortex and dispersion regime determined by means of a ground-based scanning lidar

Energy Technology Data Exchange (ETDEWEB)

Freudenthaler, V.; Homburg, F.; Jaeger, H. [Fraunhofer-Inst. fuer Atmosphaerische Umweltforschung (IFU), Garmisch-Partenkirchen (Germany)

1997-12-31

The spatial growth of individual condensation trails (contrails) of commercial aircrafts in the time range from 15 s to 60 min behind the aircraft is investigated by means of a ground-based scanning backscatter lidar. The growth in width is mainly governed by wind shear and varies between 18 m/min and 140 m/min. The growth of the cross-section varies between 3500 m{sup 2}/min and 25000 m{sup 2}/min. These values are in agreement with results of model calculations and former field measurements. The vertical growth is often limited by boundaries of the humid layer at flight level, but values up to 18 m/min were observed. Optical parameters like depolarization, optical depth and lidar ratio, i.e. the extinction-to-backscatter ratio, have been retrieved from the measurements at a wavelength of 532 nm. The linear depolarization rises from values as low as 0.06 for a young contrail (10 s old) to values around 0.5, typical for aged contrails. The latter indicates the transition from non-crystalline to crystalline particles in persistent contrails within a few minutes. The scatter of depolarization values measured in individual contrails is narrow, independent of the contrails age, and suggests a rather uniform growth of the particles inside a contrail. (author) 18 refs.

Estimating Stand Volume and Above-Ground Biomass of Urban Forests Using LiDAR

Directory of Open Access Journals (Sweden)

Vincenzo Giannico

2016-04-01

Full Text Available Assessing forest stand conditions in urban and peri-urban areas is essential to support ecosystem service planning and management, as most of the ecosystem services provided are a consequence of forest stand characteristics. However, collecting data for assessing forest stand conditions is time consuming and labor intensive. A plausible approach for addressing this issue is to establish a relationship between in situ measurements of stand characteristics and data from airborne laser scanning (LiDAR. In this study we assessed forest stand volume and above-ground biomass (AGB in a broadleaved urban forest, using a combination of LiDAR-derived metrics, which takes the form of a forest allometric model. We tested various methods for extracting proxies of basal area (BA and mean stand height (H from the LiDAR point-cloud distribution and evaluated the performance of different models in estimating forest stand volume and AGB. The best predictors for both models were the scale parameters of the Weibull distribution of all returns (except the first (proxy of BA and the 95th percentile of the distribution of all first returns (proxy of H. The R2 were 0.81 (p < 0.01 for the stand volume model and 0.77 (p < 0.01 for the AGB model with a RMSE of 23.66 m3·ha−1 (23.3% and 19.59 Mg·ha−1 (23.9%, respectively. We found that a combination of two LiDAR-derived variables (i.e., proxy of BA and proxy of H, which take the form of a forest allometric model, can be used to estimate stand volume and above-ground biomass in broadleaved urban forest areas. Our results can be compared to other studies conducted using LiDAR in broadleaved forests with similar methods.

Validation of POLDER/ADEOS data using a ground-based lidar network: Preliminary results for semi-transparent and cirrus clouds

Science.gov (United States)

Chepfer, H.; Sauvage, L.; Flamant, P. H.; Pelon, J.; Goloub, P.; Brogniez, G.; spinhirne, J.; Lavorato, M.; Sugimoto, N.

1998-01-01

At mid and tropical latitudes, cirrus clouds are present more than 50% of the time in satellites observations. Due to their large spatial and temporal coverage, and associated low temperatures, cirrus clouds have a major influence on the Earth-Ocean-Atmosphere energy balance through their effects on the incoming solar radiation and outgoing infrared radiation. At present the impact of cirrus clouds on climate is well recognized but remains to be asserted more precisely, for their optical and radiative properties are not very well known. In order to understand the effects of cirrus clouds on climate, their optical and radiative characteristics of these clouds need to be determined accurately at different scales in different locations i.e. latitude. Lidars are well suited to observe cirrus clouds, they can detect very thin and semi-transparent layers, and retrieve the clouds geometrical properties i.e. altitude and multilayers, as well as radiative properties i.e. optical depth, backscattering phase functions of ice crystals. Moreover the linear depolarization ratio can give information on the ice crystal shape. In addition, the data collected with an airborne version of POLDER (POLarization and Directionality of Earth Reflectances) instrument have shown that bidirectional polarized measurements can provide information on cirrus cloud microphysical properties (crystal shapes, preferred orientation in space). The spaceborne version of POLDER-1 has been flown on ADEOS-1 platform during 8 months (October 96 - June 97), and the next POLDER-2 instrument will be launched in 2000 on ADEOS-2. The POLDER-1 cloud inversion algorithms are currently under validation. For cirrus clouds, a validation based on comparisons between cloud properties retrieved from POLDER-1 data and cloud properties inferred from a ground-based lidar network is currently under consideration. We present the first results of the validation.

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.

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

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...

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

Assessing LiDAR elevation data for KDOT applications.

Science.gov (United States)

2013-02-01

LiDAR-based elevation surveys are a cost-effective means for mapping topography over large areas. LiDAR : surveys use an airplane-mounted or ground-based laser radar unit to scan terrain. Post-processing techniques are : applied to remove vegetation ...

The Escompte - Marseille 2001 International Field Experiment: Ground Based and Lidar Results Obtained At St. Chamas By The Epfl Mobile Laboratory

Science.gov (United States)

Balin, I.; Jimenez, R.; Simeonov, V.; Ristori, P.; Navarette, M.; van den Bergh, H.; Calpini, B.

The assessment of the air pollution problems in term of understanding of the non- linear chemical mechanisms, the transport or the meteorological processes, and the choice of the abatement strategies could be based on the air pollution models. Nowa- days, very few of these models were validated due to the lack of 3D measurements. The goal of the ESCOMPTE experiment was to provide such of 3D database in order to constrain the air pollution models. The EPFL-LPA mobile laboratory was part of the ESCOMPTE extensive network and was located on the northern side of the Berre Lake at St.Chamas. In this framework, measurements of the air pollutants (O3, SO2, NOx, polycyclic aromatic hydrocarbons, black carbon and particulate matter of less than 10 microns mean diameter) and meteorological parameters (wind, temperature, pressure and relative humidity) were continuously performed from June 10 to July 13, 2001. They were combined with ground based lidar observations for ozone and aerosol estimation from 100m above ground level up to the free troposphere at ca.7 km agl. This paper will present an overview of the results obtained and will highlight one of the intensive observation period (IOP) during which clean air conditions were initially observed followed by highly polluted air masses during the second half of the IOP.

Relative drifts and stability of satellite and ground-based stratospheric ozone profiles at NDACC lidar stations

Directory of Open Access Journals (Sweden)

P. J. Nair

2012-06-01

Full Text Available The long-term evolution of stratospheric ozone at different stations in the low and mid-latitudes is investigated. The analysis is performed by comparing the collocated profiles of ozone lidars, at the northern mid-latitudes (Meteorological Observatory Hohenpeißenberg, Haute-Provence Observatory, Tsukuba and Table Mountain Facility, tropics (Mauna Loa Observatory and southern mid-latitudes (Lauder, with ozonesondes and space-borne sensors (SBUV(/2, SAGE II, HALOE, UARS MLS and Aura MLS, extracted around the stations. Relative differences are calculated to find biases and temporal drifts in the measurements. All measurement techniques show their best agreement with respect to the lidar at 20–40 km, where the differences and drifts are generally within ±5% and ±0.5% yr⁻¹, respectively, at most stations. In addition, the stability of the long-term ozone observations (lidar, SBUV(/2, SAGE II and HALOE is evaluated by the cross-comparison of each data set. In general, all lidars and SBUV(/2 exhibit near-zero drifts and the comparison between SAGE II and HALOE shows larger, but insignificant drifts. The RMS of the drifts of lidar and SBUV(/2 is 0.22 and 0.27% yr⁻¹, respectively at 20–40 km. The average drifts of the long-term data sets, derived from various comparisons, are less than ±0.3% yr⁻¹ in the 20–40 km altitude at all stations. A combined time series of the relative differences between SAGE II, HALOE and Aura MLS with respect to lidar data at six sites is constructed, to obtain long-term data sets lasting up to 27 years. The relative drifts derived from these combined data are very small, within ±0.2% yr⁻¹.

A DIMENSION REDUCTION-BASED METHOD FOR CLASSIFICATION OF HYPERSPECTRAL AND LIDAR DATA

Directory of Open Access Journals (Sweden)

B. Abbasi

2015-12-01

Full Text Available The existence of various natural objects such as grass, trees, and rivers along with artificial manmade features such as buildings and roads, make it difficult to classify ground objects. Consequently using single data or simple classification approach cannot improve classification results in object identification. Also, using of a variety of data from different sensors; increase the accuracy of spatial and spectral information. In this paper, we proposed a classification algorithm on joint use of hyperspectral and Lidar (Light Detection and Ranging data based on dimension reduction. First, some feature extraction techniques are applied to achieve more information from Lidar and hyperspectral data. Also Principal component analysis (PCA and Minimum Noise Fraction (MNF have been utilized to reduce the dimension of spectral features. The number of 30 features containing the most information of the hyperspectral images is considered for both PCA and MNF. In addition, Normalized Difference Vegetation Index (NDVI has been measured to highlight the vegetation. Furthermore, the extracted features from Lidar data calculated based on relation between every pixel of data and surrounding pixels in local neighbourhood windows. The extracted features are based on the Grey Level Co-occurrence Matrix (GLCM matrix. In second step, classification is operated in all features which obtained by MNF, PCA, NDVI and GLCM and trained by class samples. After this step, two classification maps are obtained by SVM classifier with MNF+NDVI+GLCM features and PCA+NDVI+GLCM features, respectively. Finally, the classified images are fused together to create final classification map by decision fusion based majority voting strategy.

Lidar-based biomass assessment for the Yukon River Basin

Science.gov (United States)

Peterson, B.; Wylie, B. K.; Stoker, J.; Nossov, D.

2010-12-01

Climate change is expected to have a significant impact on high-latitude forests in terms of their ability to sequester carbon as expressed as pools of standing total biomass and soil organic matter. Above ground biomass is an important driver in ecosystem process models used to assess, predict, and understand climate change impacts. Therefore, it is of compelling interest to acquire accurate assessments of current biomass levels for these high-latitude forests, a particular challenge because of their vastness and remoteness. At this time, remote sensing is the only feasible method through which to acquire such assessments. In this study, the use of lidar data for estimating shrub and tree biomass for the Yukon Flats region of Alaska’s Yukon River Basin (YRB) is demonstrated. The lidar data were acquired in the late summer and fall of 2009 as were an initial set of field sampling data collected for training and validation purposes. The 2009 field campaigns were located near Canvasback Lake and Boot Lake in the YRB. Various tallies of biomass were calculated from the field data using allometric equations (Bond-Lamberty et al. 2002, Yarie et al. 2007, Mack et al. 2008). Additional field data were also collected during two 2010 field campaigns at different locations in the Yukon Flats. Linear regressions have been developed based on field-based shrub and tree biomass and various lidar metrics of canopy height calculated for the plots (900 m^2). A multiple linear regression performed at the plot level resulted in a strong relationship (R^2=0.88) between observed and predicted biomass at the plot level. The coefficients for this regression were used to generate a shrub and tree biomass map for the entire Yukon Flats study area covered by lidar. This biomass map will be evaluated using additional field data collected in 2010 as well as other remote sensing data sources. Furthermore, additional lidar metrics (e.g. height of median energy) are being derived from the raw

Software design of control system of CCD side-scatter lidar

Science.gov (United States)

Kuang, Zhiqiang; Liu, Dong; Deng, Qian; Zhang, Zhanye; Wang, Zhenzhu; Yu, Siqi; Tao, Zongming; Xie, Chenbo; Wang, Yingjian

2018-03-01

Because of the existence of blind zone and transition zone, the application of backscattering lidar in near-ground is limited. The side-scatter lidar equipped with the Charge Coupled Devices (CCD) can separate the transmitting and receiving devices to avoid the impact of the geometric factors which is exited in the backscattering lidar and, detect the more precise near-ground aerosol signals continuously. Theories of CCD side-scatter lidar and the design of control system are introduced. The visible control of laser and CCD and automatic data processing method of the side-scatter lidar are developed by using the software of Visual C #. The results which are compared with the calibration of the atmospheric aerosol lidar data show that signals from the CCD side- scatter lidar are convincible.

Tracking atmospheric boundary layer in tehran using combined lidar remote sensing and ground base measurements

Science.gov (United States)

Panahifar, Hossein; Khalesifard, Hamid

2018-04-01

The vertical structure of the atmospheric boundary layer (ABL) has been studied by use of a depolarized LiDAR over Tehran, Iran. The boundary layer height (BLH) remains under 1km, and its retrieval from LiDAR have been compared with sonding measurements and meteorological model outputs. It is also shown that the wind speed and direction as well as topography lead to the persistence of air pollution in Tehran. The situation aggravate in fall and winter due to temperature inversion.

Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology

Science.gov (United States)

Chase, Arlen F.; Fisher, Christopher T.; Leisz, Stephen J.; Weishampel, John F.

2012-01-01

The application of light detection and ranging (LiDAR), a laser-based remote-sensing technology that is capable of penetrating overlying vegetation and forest canopies, is generating a fundamental shift in Mesoamerican archaeology and has the potential to transform research in forested areas world-wide. Much as radiocarbon dating that half a century ago moved archaeology forward by grounding archaeological remains in time, LiDAR is proving to be a catalyst for an improved spatial understanding of the past. With LiDAR, ancient societies can be contextualized within a fully defined landscape. Interpretations about the scale and organization of densely forested sites no longer are constrained by sample size, as they were when mapping required laborious on-ground survey. The ability to articulate ancient landscapes fully permits a better understanding of the complexity of ancient Mesoamerican urbanism and also aids in modern conservation efforts. The importance of this geospatial innovation is demonstrated with newly acquired LiDAR data from the archaeological sites of Caracol, Cayo, Belize and Angamuco, Michoacán, Mexico. These data illustrate the potential of technology to act as a catalytic enabler of rapid transformational change in archaeological research and interpretation and also underscore the value of on-the-ground archaeological investigation in validating and contextualizing results. PMID:22802623

Geospatial revolution and remote sensing LiDAR in Mesoamerican archaeology.

Science.gov (United States)

Chase, Arlen F; Chase, Diane Z; Fisher, Christopher T; Leisz, Stephen J; Weishampel, John F

2012-08-07

The application of light detection and ranging (LiDAR), a laser-based remote-sensing technology that is capable of penetrating overlying vegetation and forest canopies, is generating a fundamental shift in Mesoamerican archaeology and has the potential to transform research in forested areas world-wide. Much as radiocarbon dating that half a century ago moved archaeology forward by grounding archaeological remains in time, LiDAR is proving to be a catalyst for an improved spatial understanding of the past. With LiDAR, ancient societies can be contextualized within a fully defined landscape. Interpretations about the scale and organization of densely forested sites no longer are constrained by sample size, as they were when mapping required laborious on-ground survey. The ability to articulate ancient landscapes fully permits a better understanding of the complexity of ancient Mesoamerican urbanism and also aids in modern conservation efforts. The importance of this geospatial innovation is demonstrated with newly acquired LiDAR data from the archaeological sites of Caracol, Cayo, Belize and Angamuco, Michoacán, Mexico. These data illustrate the potential of technology to act as a catalytic enabler of rapid transformational change in archaeological research and interpretation and also underscore the value of on-the-ground archaeological investigation in validating and contextualizing results.

Terrain Classification and Identification of Tree Stems Using Ground-Based Lidar

Science.gov (United States)

2012-12-01

diameters using lidar data (e.g. Henning & Radtke , 2006; Maas et al., 2008) with RMS errors of 1.0 cm, but this has been done with little or no understory...occlusion or data sparsity. Here, the range is selected to balance these two competing effects. In the literature (Aschoff et al., 2004; Henning & Radtke ...restrictions in the assumed fits. While the dbh estimates are not as accurate as some previously reported (e.g. Henning & Radtke (2006)), this is to be

UV Lidar Receiver Analysis for Tropospheric Sensing of Ozone

Science.gov (United States)

Pliutau, Denis; DeYoung, Russell J.

2013-01-01

A simulation of a ground based Ultra-Violet Differential Absorption Lidar (UV-DIAL) receiver system was performed under realistic daytime conditions to understand how range and lidar performance can be improved for a given UV pulse laser energy. Calculations were also performed for an aerosol channel transmitting at 3 W. The lidar receiver simulation studies were optimized for the purpose of tropospheric ozone measurements. The transmitted lidar UV measurements were from 285 to 295 nm and the aerosol channel was 527-nm. The calculations are based on atmospheric transmission given by the HITRAN database and the Modern Era Retrospective Analysis for Research and Applications (MERRA) meteorological data. The aerosol attenuation is estimated using both the BACKSCAT 4.0 code as well as data collected during the CALIPSO mission. The lidar performance is estimated for both diffuseirradiance free cases corresponding to nighttime operation as well as the daytime diffuse scattered radiation component based on previously reported experimental data. This analysis presets calculations of the UV-DIAL receiver ozone and aerosol measurement range as a function of sky irradiance, filter bandwidth and laser transmitted UV and 527-nm energy

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

Predictive modeling of hazardous waste landfill total above-ground biomass using passive optical and LIDAR remotely sensed data

Science.gov (United States)

Hadley, Brian Christopher

This dissertation assessed remotely sensed data and geospatial modeling technique(s) to map the spatial distribution of total above-ground biomass present on the surface of the Savannah River National Laboratory's (SRNL) Mixed Waste Management Facility (MWMF) hazardous waste landfill. Ordinary least squares (OLS) regression, regression kriging, and tree-structured regression were employed to model the empirical relationship between in-situ measured Bahia (Paspalum notatum Flugge) and Centipede [Eremochloa ophiuroides (Munro) Hack.] grass biomass against an assortment of explanatory variables extracted from fine spatial resolution passive optical and LIDAR remotely sensed data. Explanatory variables included: (1) discrete channels of visible, near-infrared (NIR), and short-wave infrared (SWIR) reflectance, (2) spectral vegetation indices (SVI), (3) spectral mixture analysis (SMA) modeled fractions, (4) narrow-band derivative-based vegetation indices, and (5) LIDAR derived topographic variables (i.e. elevation, slope, and aspect). Results showed that a linear combination of the first- (1DZ_DGVI), second- (2DZ_DGVI), and third-derivative of green vegetation indices (3DZ_DGVI) calculated from hyperspectral data recorded over the 400--960 nm wavelengths of the electromagnetic spectrum explained the largest percentage of statistical variation (R2 = 0.5184) in the total above-ground biomass measurements. In general, the topographic variables did not correlate well with the MWMF biomass data, accounting for less than five percent of the statistical variation. It was concluded that tree-structured regression represented the optimum geospatial modeling technique due to a combination of model performance and efficiency/flexibility factors.

Physical and optical properties of 2010 Eyjafjallajökull volcanic eruption aerosol: ground-based, Lidar and airborne measurements in France

Directory of Open Access Journals (Sweden)

M. Hervo

2012-02-01

Full Text Available During the Eyjafjallajökull eruption (14 April to 24 May 2010, the volcanic aerosol cloud was observed across Europe by several airborne in situ and ground-based remote-sensing instruments. On 18 and 19 May, layers of depolarizing particles (i.e. non-spherical particles were detected in the free troposphere above the Puy de Dôme station, (PdD, France with a Rayleigh-Mie LIDAR emitting at a wavelength of 355 nm, with parallel and crossed polarization channels. These layers in the free troposphere (FT were also well captured by simulations with the Lagrangian particle dispersion model FLEXPART, which furthermore showed that the ash was eventually entrained into the planetary boundary layer (PBL. Indeed, the ash cloud was then detected and characterized with a comprehensive set of in situ instruments at the Puy de Dôme station (PdD. In agreement with the FLEXPART simulation, up to 65 μg m⁻³ of particle mass and 2.2 ppb of SO₂ were measured at PdD, corresponding to concentrations higher than the 95 percentile of 2 yr of measurements at PdD. Moreover, the number concentration of particles increased to 24 000 cm⁻³, mainly in the submicronic mode, but a supermicronic mode was also detected with a modal diameter of 2 μm. The resulting optical properties of the ash aerosol were characterized by a low scattering Ångström exponent (0.98, showing the presence of supermicronic particles. For the first time to our knowledge, the combination of in situ optical and physical characterization of the volcanic ash allowed the calculation of the mass-to-extinction ratio (η with no assumptions on the aerosol density. The mass-to-extinction ratio was found to be significantly different from the background boundary layer aerosol (max: 1.57 g m⁻² as opposed to 0.33 ± 0.03 g m⁻². Using this ratio, ash mass concentration in the volcanic plume derived from LIDAR measurements was found to be 655 ± 23 �

Lidar and airborne investigation of smoke plume characteristics: Kootenai Creek Fire case study

Science.gov (United States)

S. Urbanski; V. Kovalev; W. M. Hao; C. Wold; A. Petkov

2010-01-01

A ground-based scanning lidar was utilized with a set of airborne instruments to acquire measurements of smoke plume dynamics, smoke aerosol distribution and chemical composition in the vicinity of active wildfires in the western U.S. A new retrieval technique was used for processing lidar multiangle measurements. The technique determines the location of...

Generic Methodology for Field Calibration of Nacelle-Based Wind Lidars

DEFF Research Database (Denmark)

Borraccino, Antoine; Courtney, Michael; Wagner, Rozenn

2016-01-01

Nacelle-based Doppler wind lidars have shown promising capabilities to assess power performance, detect yaw misalignment or perform feed-forward control. The power curve application requires uncertainty assessment. Traceable measurements and uncertainties of nacelle-based wind lidars can be obtai...

Comparison of Two Independent LIDAR-Based Pitch Control Designs

Energy Technology Data Exchange (ETDEWEB)

Dunne, F.; Schlipf, D.; Pao, L. Y.

2012-08-01

Two different lidar-based feedforward controllers have previously been designed for the NREL 5 MW wind turbine model under separate studies. Feedforward controller A uses a finite-impulse-response design, with 5 seconds of preview, and three rotating lidar measurements. Feedforward controller B uses a static-gain design, with the preview time defined by the pitch actuator dynamics, a simulation of a real nacelle-based scanning lidar system, and a lowpass filter defined by the lidar configuration. These controllers are now directly compared under the same lidar configuration, in terms of fatigue load reduction, rotor speed regulation, and power capture. The various differences in design choices are discussed and compared. We also compare frequency plots of individual pitch feedforward and collective pitch feedforward load reductions, and we see that individual pitch feedforward is effective mainly at the once-per-revolution and twice-per-revolution frequencies. We also explain how to determine the required preview time by breaking it down into separate parts, and we then compare it to the expected preview time available.

Landslides Mapped from LIDAR Imagery, Kitsap County, Washington

Science.gov (United States)

McKenna, Jonathan P.; Lidke, David J.; Coe, Jeffrey A.

2008-01-01

Landslides are a recurring problem on hillslopes throughout the Puget Lowland, Washington, but can be difficult to identify in the densely forested terrain. However, digital terrain models of the bare-earth surface derived from LIght Detection And Ranging (LIDAR) data express topographic details sufficiently well to identify landslides. Landslides and escarpments were mapped using LIDAR imagery and field checked (when permissible and accessible) throughout Kitsap County. We relied almost entirely on derivatives of LIDAR data for our mapping, including topographic-contour, slope, and hill-shaded relief maps. Each mapped landslide was assigned a level of 'high' or 'moderate' confidence based on the LIDAR characteristics and on field observations. A total of 231 landslides were identified representing 0.8 percent of the land area of Kitsap County. Shallow debris topples along the coastal bluffs and large (>10,000 m2) landslide complexes are the most common types of landslides. The smallest deposit mapped covers an area of 252 m2, while the largest covers 0.5 km2. Previous mapping efforts that relied solely on field and photogrammetric methods identified only 57 percent of the landslides mapped by LIDAR (61 percent high confidence and 39 percent moderate confidence), although nine landslides previously identified were not mapped during this study. The remaining 43 percent identified using LIDAR have 13 percent high confidence and 87 percent moderate confidence. Coastal areas are especially susceptible to landsliding; 67 percent of the landslide area that we mapped lies within 500 meters of the present coastline. The remaining 33 percent are located along drainages farther inland. The LIDAR data we used for mapping have some limitations including (1) rounding of the interface area between low slope surfaces and vertical faces (that is, along the edges of steep escarpments) which results in scarps being mapped too far headward (one or two meters), (2) incorrect laser

A 3D radiative transfer model based on lidar data and its application on hydrological and ecosystem modeling

Science.gov (United States)

Li, W.; Su, Y.; Harmon, T. C.; Guo, Q.

2013-12-01

Light Detection and Ranging (lidar) is an optical remote sensing technology that measures properties of scattered light to find range and/or other information of a distant object. Due to its ability to generate 3-dimensional data with high spatial resolution and accuracy, lidar technology is being increasingly used in ecology, geography, geology, geomorphology, seismology, remote sensing, and atmospheric physics. In this study we construct a 3-dimentional (3D) radiative transfer model (RTM) using lidar data to simulate the spatial distribution of solar radiation (direct and diffuse) on the surface of water and mountain forests. The model includes three sub-models: a light model simulating the light source, a sensor model simulating the camera, and a scene model simulating the landscape. We use ground-based and airborne lidar data to characterize the 3D structure of the study area, and generate a detailed 3D scene model. The interactions between light and object are simulated using the Monte Carlo Ray Tracing (MCRT) method. A large number of rays are generated from the light source. For each individual ray, the full traveling path is traced until it is absorbed or escapes from the scene boundary. By locating the sensor at different positions and directions, we can simulate the spatial distribution of solar energy at the ground, vegetation and water surfaces. These outputs can then be incorporated into meteorological drivers for hydrologic and energy balance models to improve our understanding of hydrologic processes and ecosystem functions.

Csf Based Non-Ground Points Extraction from LIDAR Data

Science.gov (United States)

Shen, A.; Zhang, W.; Shi, H.

2017-09-01

Region growing is a classical method of point cloud segmentation. Based on the idea of collecting the pixels with similar properties to form regions, region growing is widely used in many fields such as medicine, forestry and remote sensing. In this algorithm, there are two core problems. One is the selection of seed points, the other is the setting of the growth constraints, in which the selection of the seed points is the foundation. In this paper, we propose a CSF (Cloth Simulation Filtering) based method to extract the non-ground seed points effectively. The experiments have shown that this method can obtain a group of seed spots compared with the traditional methods. It is a new attempt to extract seed points

Special Relativity Corrections for Space-Based Lidars

Science.gov (United States)

RaoGudimetla, Venkata S.; Kavaya, Michael J.

1999-01-01

The theory of special relativity is used to analyze some of the physical phenomena associated with space-based coherent Doppler lidars aimed at Earth and the atmosphere. Two important cases of diffuse scattering and retroreflection by lidar targets are treated. For the case of diffuse scattering, we show that for a coaligned transmitter and receiver on the moving satellite, there is no angle between transmitted and returned radiation. However, the ray that enters the receiver does not correspond to a retroreflected ray by the target. For the retroreflection case there is misalignment between the transmitted ray and the received ray. In addition, the Doppler shift in the frequency and the amount of tip for the receiver aperture when needed are calculated, The error in estimating wind because of the Doppler shift in the frequency due to special relativity effects is examined. The results are then applied to a proposed space-based pulsed coherent Doppler lidar at NASA's Marshall Space Flight Center for wind and aerosol backscatter measurements. The lidar uses an orbiting spacecraft with a pulsed laser source and measures the Doppler shift between the transmitted and the received frequencies to determine the atmospheric wind velocities. We show that the special relativity effects are small for the proposed system.

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

TENSOR MODELING BASED FOR AIRBORNE LiDAR DATA CLASSIFICATION

Directory of Open Access Journals (Sweden)

N. Li

2016-06-01

Full Text Available Feature selection and description is a key factor in classification of Earth observation data. In this paper a classification method based on tensor decomposition is proposed. First, multiple features are extracted from raw LiDAR point cloud, and raster LiDAR images are derived by accumulating features or the “raw” data attributes. Then, the feature rasters of LiDAR data are stored as a tensor, and tensor decomposition is used to select component features. This tensor representation could keep the initial spatial structure and insure the consideration of the neighborhood. Based on a small number of component features a k nearest neighborhood classification is applied.

Tropospheric Ozone Source Attribution in Southern California during Summer 2014 Based on Lidar Measurements and Model Simulations

Science.gov (United States)

Granados Munoz, Maria Jose; Johnson, Matthew S.; Leblanc, Thierry

2016-01-01

In the past decades, significant efforts have been made to increase tropospheric ozone long-term monitoring. A large number of ground-based, airborne and space-borne instruments are currently providing valuable data to contribute to better understand tropospheric ozone budget and variability. Nonetheless, most of these instruments provide in-situ surface and column-integrated data, whereas vertically resolved measurements are still scarce. Besides ozonesondes and aircraft, lidar measurements have proven to be valuable tropospheric ozone profilers. Using the measurements from the tropospheric ozone differential absorption lidar (DIAL) located at the JPL Table Mountain Facility, California, and the GEOS-Chem and GEOS-5 model outputs, the impact of the North American monsoon on tropospheric ozone during summer 2014 is investigated. The influence of the Monsoon lightning-induced NOx will be evaluated against other sources (e.g. local anthropogenic emissions and the stratosphere) using also complementary data such as backward-trajectories analysis, coincident water vapor lidar measurements, and surface ozone in-situ measurements.

Combining Lidar and Synthetic Aperture Radar Data to Estimate Forest Biomass: Status and Prospects

Directory of Open Access Journals (Sweden)

Sanna Kaasalainen

2015-01-01

Full Text Available Research activities combining lidar and radar remote sensing have increased in recent years. The main focus in combining lidar-radar forest remote sensing has been on the retrieval of the aboveground biomass (AGB, which is a primary variable related to carbon cycle in land ecosystems, and has therefore been identified as an essential climate variable. In this review, we summarize the studies combining lidar and radar in estimating forest AGB. We discuss the complementary use of lidar and radar according to the relevance of the added value. The most promising prospects for combining lidar and radar data are in the use of lidar-derived ground elevations for improving large-area biomass estimates from radar, and in upscaling of lidar-based AGB data across large areas covered by spaceborne radar missions.

A multiscale curvature algorithm for classifying discrete return LiDAR in forested environments

Science.gov (United States)

Jeffrey S. Evans; Andrew T. Hudak

2007-01-01

One prerequisite to the use of light detection and ranging (LiDAR) across disciplines is differentiating ground from nonground returns. The objective was to automatically and objectively classify points within unclassified LiDAR point clouds, with few model parameters and minimal postprocessing. Presented is an automated method for classifying LiDAR returns as ground...

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....

Measurements of CO2 Column Abundance in the Low Atmosphere Using Ground Based 1.6 μm CO2 DIAL

Science.gov (United States)

Abo, M.; Shibata, Y.; Nagasawa, C.

2017-12-01

Changes in atmospheric carbon dioxide (CO2) concentration are believed to produce the largest radiative forcing for the current climate system. Accurate predictions of atmospheric CO2 concentration rely on the knowledge of its sinks and sources, transports, and its variability with time. Although this knowledge is currently unsatisfactory, numerical models use it as a way in simulating CO2 fluxes. Validating and improving the global atmospheric transport model, therefore, requires precise measurement of the CO2 concentration profile. There are two further variations on Lidar: the differential absorption Lidar (DIAL) and the integrated path differential absorption (IPDA) Lidar. DIAL/IPDA are basically for profile/total column measurement, respectively. IPDA is a special case of DIAL and can measure the total column-averaged mixing ratio of trace gases using return signals from the Earth's surface or from thick clouds based on an airborne or a satellite. We have developed a ground based 1.6 μm DIAL to measure vertical CO2 mixing ratio profiles from 0.4 to 2.5 km altitude. The goals of the CO2 DIAL are to produce atmospheric CO2 mixing ratio measurements with much smaller seasonal and diurnal biases from the ground surface. But, in the ground based lidar, return signals from around ground surface are usually suppressed in order to handle the large dynamic range. To receive the return signals as near as possible from ground surface, namely, the field of view (FOV) of the telescope must be wide enough to reduce the blind range of the lidar. While the return signals from the far distance are very weak, to enhance the sensitivity and heighten the detecting distance, the FOV must be narrow enough to suppress the sky background light, especially during the daytime measurements. To solve this problem, we propose a total column measurement method from the ground surface to 0.4 km altitude. Instead of strong signals from thick clouds such as the IPDA, the proposed method uses

A Compact Mobile Ozone Lidar for Atmospheric Ozone and Aerosol Profiling

Science.gov (United States)

De Young, Russell; Carrion, William; Pliutau, Denis

2014-01-01

A compact mobile differential absorption lidar (DIAL) system has been developed at NASA Langley Research Center to provide ozone, aerosol and cloud atmospheric measurements in a mobile trailer for ground-based atmospheric ozone air quality campaigns. This lidar is integrated into the Tropospheric Ozone Lidar Network (TOLNet) currently made up of four other ozone lidars across the country. The lidar system consists of a UV and green laser transmitter, a telescope and an optical signal receiver with associated Licel photon counting and analog channels. The laser transmitter consist of a Q-switched Nd:YLF inter-cavity doubled laser pumping a Ce:LiCAF tunable UV laser with all the associated power and lidar control support units on a single system rack. The system has been configured to enable mobile operation from a trailer and was deployed to Denver, CO July 15-August 15, 2014 supporting the DISCOVER-AQ campaign. Ozone curtain plots and the resulting science are presented.

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.

Automated Extraction of 3D Trees from Mobile LiDAR Point Clouds

Directory of Open Access Journals (Sweden)

Y. Yu

2014-06-01

Full Text Available This paper presents an automated algorithm for extracting 3D trees directly from 3D mobile light detection and ranging (LiDAR data. To reduce both computational and spatial complexities, ground points are first filtered out from a raw 3D point cloud via blockbased elevation filtering. Off-ground points are then grouped into clusters representing individual objects through Euclidean distance clustering and voxel-based normalized cut segmentation. Finally, a model-driven method is proposed to achieve the extraction of 3D trees based on a pairwise 3D shape descriptor. The proposed algorithm is tested using a set of mobile LiDAR point clouds acquired by a RIEGL VMX-450 system. The results demonstrate the feasibility and effectiveness of the proposed algorithm.

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...

Wide-angle imaging LIDAR (WAIL): a ground-based instrument for monitoring the thickness and density of optically thick clouds

International Nuclear Information System (INIS)

Love, Steven P.; Davis, A.B.; Rohde, C.A.; Ho, Cheng

2001-01-01

Traditional lidar provides little information on dense clouds beyond the range to their base (ceilometry), due to their extreme opacity. At most optical wavelengths, however, laser photons are not absorbed but merely scattered out of the beam, and thus eventually escape the cloud via multiple scattering, producing distinctive extended space- and time-dependent patterns which are, in essence, the cloud's radiative Green functions. These Green functions, essentially 'movies' of the time evolution of the spatial distribution of escaping light, are the primary data products of a new type of lidar: Wide Angle Imaging Lidar (WAIL). WAIL data can be used to infer both optical depth and physical thickness of clouds, and hence the cloud liquid water content. The instrumental challenge is to accommodate a radiance field varying over many orders of magnitude and changing over widely varying time-scales. Our implementation uses a high-speed microchannel plate/crossed delay line imaging detector system with a 60-degree full-angle field of view, and a 532 nm doubled Nd:YAG laser. Nighttime field experiments testing various solutions to this problem show excellent agreement with diffusion theory, and retrievals yield plausible values for the optical and geometrical parameters of the observed cloud decks.

Development of LiDAR measurements for the German offshore test site

International Nuclear Information System (INIS)

Rettenmeier, A; Kuehn, M; Waechter, M; Rahm, S; Mellinghoff, H; Siegmeier, B; Reeder, L

2008-01-01

The paper introduces the content of the recently started joint research project 'Development of LiDAR measurements for the German Offshore Test Site' which has the objective to support other research projects at the German offshore test site 'alpha ventus'. The project has started before the erection of the offshore wind farm and one aim is to give recommendations concerning LiDAR technology useable for offshore measurement campaigns and data analysis. The work is organized in four work packages. The work package LiDAR technology deals with the specification, acquisition and calibration of a commercial LiDAR system for the measurement campaigns. Power curve measurements are dedicated to power curve assessment with ground-based LiDAR using standard statistical methods. Additionally, it deals with the development of new methods for the measurement of non-steady short-term power curves. Wind field research aims at the development of wake loading simulation methods of wind turbines and the exploration of loading control strategies and nacelle-based wind field measurement techniques. Finally, dissemination of results to the industry takes place in work package Technology transfer

Imaging of Ground Ice with Surface-Based Geophysics

Science.gov (United States)

2015-10-01

terrains. Electrical Resistivity Tomography (ERT), in particular, has been effective for imaging ground ice. ERT measures the ability of materials to...13 2.2.1 Electrical resistivity tomography (ERT...Engineer Research and Development Center ERT Electrical Resistivity Tomography GPS Global Positioning System LiDAR Light Detection and Ranging SIPRE

A review of the mobile LIDAR system developed at the CSIR and a proposed improvement of the system

CSIR Research Space (South Africa)

Shikwambana, L

2012-07-01

Full Text Available or cloud of pollutants) and (3) To study the plume (say smoke, biomass burning and etc), Haze and Aerosol/pollutant dispersion. Fig. 5. A schematic view of the modified LIDAR system with Scanner. Fig. 4. (a) Ground-based zenith-pointing lidars...

All-Fiber Airborne Coherent Doppler Lidar to Measure Wind Profiles

Directory of Open Access Journals (Sweden)

Liu Jiqiao

2016-01-01

Full Text Available An all-fiber airborne pulsed coherent Doppler lidar (CDL prototype at 1.54μm is developed to measure wind profiles in the lower troposphere layer. The all-fiber single frequency pulsed laser is operated with pulse energy of 300μJ, pulse width of 400ns and pulse repetition rate of 10kHz. To the best of our knowledge, it is the highest pulse energy of all-fiber eye-safe single frequency laser that is used in airborne coherent wind lidar. The telescope optical diameter of monostatic lidar is 100 mm. Velocity-Azimuth-Display (VAD scanning is implemented with 20 degrees elevation angle in 8 different azimuths. Real-time signal processing board is developed to acquire and process the heterodyne mixing signal with 10000 pulses spectra accumulated every second. Wind profiles are obtained every 20 seconds. Several experiments are implemented to evaluate the performance of the lidar. We have carried out airborne wind lidar experiments successfully, and the wind profiles are compared with aerological theodolite and ground based wind lidar. Wind speed standard error of less than 0.4m/s is shown between airborne wind lidar and balloon aerological theodolite.

INTERACT-II campaign:comparison of commercial lidars and ceilometers with advanced multi-wavelength Raman lidars

Science.gov (United States)

Rosoldi, Marco; Madonna, Fabio; Pappalardo, Gelsomina; Vande Hey, Joshua; Zheng, Yunhui; Vaisala Team

2017-04-01

Knowledge of aerosol spatio-temporal distribution in troposphere is essential for the study of climate and air quality. For this purpose, global scale high resolution continuous measurements of tropospheric aerosols are needed. Global coverage high resolution networks of ground-based low-cost and low-maintenance remote sensing instruments, such as commercial automatic lidars and ceilometers, can strongly contribute to this scientific mission. Therefore, it is very interesting for scientific community to understand to which extent these instruments are able to provide reliable aerosol measurements and fill in the geographical gaps of existing networks of the advanced lidars, like EARLINET (European Aerosol Research LIdar NETwork). The INTERACT-II (INTERcomparison of Aerosol and Cloud Tracking) campaign, carried out at CIAO (CNR-IMAA Atmospheric Observatory) in Tito Scalo, Potenza, Italy (760m a.s.l., 40.60°N, 15.72°E), aims to evaluate the performances of commercial automatic lidars and ceilometers for tropospheric aerosol profiling. The campaign has been performed in the period from July 2016 to January 2017 in the framework of ACTRIS-2 (Aerosol Clouds Trace gases Research InfraStructure) H2020 research infrastructure project. Besides the commercial ceilometers operational at CIAO (VAISALA CT25K and Luftt CHM15k), the performance of a CL51 VAISALA ceilometer, a Campbell CS135 ceilometer and a mini-Micro Pulse Lidar (MPL) have been assessed using the EARLINET multi-wavelengths Raman lidars operative at CIAO as reference. Following a similar approach used in the first INTERACT campaign (Madonna et al., AMT 2015), attenuated backscatter coefficient profiles and signals obtained from all the instruments have been compared, over a vertical resolution of 60 meters and a temporal integration ranging between 1 and 2 hours, depending on the observed atmospheric scenario. CIAO lidars signals have been processed using the EARLINET Single Calculus Chain (SCC) also with the

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.

A Study on Factors Affecting Airborne LiDAR Penetration

Directory of Open Access Journals (Sweden)

Wei-Chen Hsu

2015-01-01

Full Text Available This study uses data from different periods, areas and parameters of airborne LiDAR (light detection and ranging surveys to understand the factors that influence airborne LiDAR penetration rate. A discussion is presented on the relationships between these factors and LiDAR penetration rate. The results show that the flight height above ground level (AGL does not have any relationship with the penetration rate. There are some factors that should have larger influence. For example, the laser is affected by a wet ground surface by reducing the number of return echoes. The field of view (FOV has a slightly negative correlation with the penetration rate, which indicates that the laser incidence angle close to zero should achieve the best penetration. The vegetation cover rate also shows a negative correlation with the penetration rate, thus bare ground and reduced vegetation in the aftermath of a typhoon also cause high penetration rate. More return echoes could be extracted from the full-waveform system, thereby effectively improving the penetration rate. This study shows that full-waveform LiDAR is an effective method for increasing the number of surface reflected echoes. This study suggests avoiding LiDAR survey employment directly following precipitation to prevent laser echo reduction.

16-year Climatology of Cirrus cloud properties using ground-based Lidar over Gadanki (13.45˚N, 79.18˚E)

Science.gov (United States)

Pandit, Amit Kumar; Raghunath, Karnam; Jayaraman, Achuthan; Venkat Ratnam, Madineni; Gadhavi, Harish

Cirrus clouds are ubiquitous high level cold clouds predominantly consisting of ice-crystals. With their highest coverage over the tropics, these are one of the most vital and complex components of Tropical Tropopause Layer (TTL) due to their strong radiative feedback and dehydration in upper troposphere and lower stratosphere (UTLS) regions. The continuous changes in their coverage, position, thickness, and ice-crystal size and shape distributions bring uncertainties in the estimates of cirrus cloud radiative forcing. Long-term changes in the distribution of aerosols and water vapour in the TTL can influence cirrus properties. This necessitates long-term studies of tropical cirrus clouds, which are only few. The present study provides 16-year climatology of physical and optical properties of cirrus clouds observed using a ground-based Lidar located at Gadanki (13.45(°) N, 79.18(°) ˚E and 375 m amsl) in south-India. In general, cirrus clouds occurred for about 44% of the total Lidar observation time. Owing to the increased convective activities, the occurrence of cirrus clouds during the southwest-monsoon season is highest while it is lowest during the winter. Altitude distribution of cirrus clouds reveals that the peak occurrence was about 25% at 14.5 km. The most probable base and top height of cirrus clouds are 14 and 15.5 km, respectively. This is also reflected in the bulk extinction coefficient profile (at 532 nm) of cirrus clouds. These results are compared with the CALIPSO observations. Most of the time cirrus clouds are located within the TTL bounded by convective outflow level and cold-point tropopause. Cirrus clouds are thick during the monsoon season as compared to that during winter. An inverse relation between the thickness of cirrus clouds and TTL thickness is found. The occurrence of cirrus clouds at an altitude close to the tropopause (16 km) showed an increase of 8.4% in the last 16 years. Base and top heights of cirrus clouds also showed

Improving correlations between MODIS aerosol optical thickness and ground-based PM 2.5 observations through 3D spatial analyses

Science.gov (United States)

Hutchison, Keith D.; Faruqui, Shazia J.; Smith, Solar

The Center for Space Research (CSR) continues to focus on developing methods to improve correlations between satellite-based aerosol optical thickness (AOT) values and ground-based, air pollution observations made at continuous ambient monitoring sites (CAMS) operated by the Texas commission on environmental quality (TCEQ). Strong correlations and improved understanding of the relationships between satellite and ground observations are needed to formulate reliable real-time predictions of air quality using data accessed from the moderate resolution imaging spectroradiometer (MODIS) at the CSR direct-broadcast ground station. In this paper, improvements in these correlations are demonstrated first as a result of the evolution in the MODIS retrieval algorithms. Further improvement is then shown using procedures that compensate for differences in horizontal spatial scales between the nominal 10-km MODIS AOT products and CAMS point measurements. Finally, airborne light detection and ranging (lidar) observations, collected during the Texas Air Quality Study of 2000, are used to examine aerosol profile concentrations, which may vary greatly between aerosol classes as a result of the sources, chemical composition, and meteorological conditions that govern transport processes. Further improvement in correlations is demonstrated with this limited dataset using insights into aerosol profile information inferred from the vertical motion vectors in a trajectory-based forecast model. Analyses are ongoing to verify these procedures on a variety of aerosol classes using data collected by the Cloud-Aerosol Lidar and Infrared Pathfinder Satellite (Calipso) lidar.

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

Improving salt marsh digital elevation model accuracy with full-waveform lidar and nonparametric predictive modeling

Science.gov (United States)

Rogers, Jeffrey N.; Parrish, Christopher E.; Ward, Larry G.; Burdick, David M.

2018-03-01

Salt marsh vegetation tends to increase vertical uncertainty in light detection and ranging (lidar) derived elevation data, often causing the data to become ineffective for analysis of topographic features governing tidal inundation or vegetation zonation. Previous attempts at improving lidar data collected in salt marsh environments range from simply computing and subtracting the global elevation bias to more complex methods such as computing vegetation-specific, constant correction factors. The vegetation specific corrections can be used along with an existing habitat map to apply separate corrections to different areas within a study site. It is hypothesized here that correcting salt marsh lidar data by applying location-specific, point-by-point corrections, which are computed from lidar waveform-derived features, tidal-datum based elevation, distance from shoreline and other lidar digital elevation model based variables, using nonparametric regression will produce better results. The methods were developed and tested using full-waveform lidar and ground truth for three marshes in Cape Cod, Massachusetts, U.S.A. Five different model algorithms for nonparametric regression were evaluated, with TreeNet's stochastic gradient boosting algorithm consistently producing better regression and classification results. Additionally, models were constructed to predict the vegetative zone (high marsh and low marsh). The predictive modeling methods used in this study estimated ground elevation with a mean bias of 0.00 m and a standard deviation of 0.07 m (0.07 m root mean square error). These methods appear very promising for correction of salt marsh lidar data and, importantly, do not require an existing habitat map, biomass measurements, or image based remote sensing data such as multi/hyperspectral imagery.

a Voxel-Based Filtering Algorithm for Mobile LIDAR Data

Science.gov (United States)

Qin, H.; Guan, G.; Yu, Y.; Zhong, L.

2018-04-01

This paper presents a stepwise voxel-based filtering algorithm for mobile LiDAR data. In the first step, to improve computational efficiency, mobile LiDAR points, in xy-plane, are first partitioned into a set of two-dimensional (2-D) blocks with a given block size, in each of which all laser points are further organized into an octree partition structure with a set of three-dimensional (3-D) voxels. Then, a voxel-based upward growing processing is performed to roughly separate terrain from non-terrain points with global and local terrain thresholds. In the second step, the extracted terrain points are refined by computing voxel curvatures. This voxel-based filtering algorithm is comprehensively discussed in the analyses of parameter sensitivity and overall performance. An experimental study performed on multiple point cloud samples, collected by different commercial mobile LiDAR systems, showed that the proposed algorithm provides a promising solution to terrain point extraction from mobile point clouds.

Raster Vs. Point Cloud LiDAR Data Classification

Science.gov (United States)

El-Ashmawy, N.; Shaker, A.

2014-09-01

Airborne Laser Scanning systems with light detection and ranging (LiDAR) technology is one of the fast and accurate 3D point data acquisition techniques. Generating accurate digital terrain and/or surface models (DTM/DSM) is the main application of collecting LiDAR range data. Recently, LiDAR range and intensity data have been used for land cover classification applications. Data range and Intensity, (strength of the backscattered signals measured by the LiDAR systems), are affected by the flying height, the ground elevation, scanning angle and the physical characteristics of the objects surface. These effects may lead to uneven distribution of point cloud or some gaps that may affect the classification process. Researchers have investigated the conversion of LiDAR range point data to raster image for terrain modelling. Interpolation techniques have been used to achieve the best representation of surfaces, and to fill the gaps between the LiDAR footprints. Interpolation methods are also investigated to generate LiDAR range and intensity image data for land cover classification applications. In this paper, different approach has been followed to classifying the LiDAR data (range and intensity) for land cover mapping. The methodology relies on the classification of the point cloud data based on their range and intensity and then converted the classified points into raster image. The gaps in the data are filled based on the classes of the nearest neighbour. Land cover maps are produced using two approaches using: (a) the conventional raster image data based on point interpolation; and (b) the proposed point data classification. A study area covering an urban district in Burnaby, British Colombia, Canada, is selected to compare the results of the two approaches. Five different land cover classes can be distinguished in that area: buildings, roads and parking areas, trees, low vegetation (grass), and bare soil. The results show that an improvement of around 10 % in the

Aerosol backscatter measurements at 10.6 microns with airborne and ground-based CO2 Doppler lidars over the Colorado High Plains. II - Backscatter structure

Science.gov (United States)

Bowdle, David A.; Rothermel, Jeffry; Vaughan, J. Michael; Post, Madison J.

1991-01-01

Measurements of tropospheric aerosol volume backscatter coefficients at 10.6-microns wavelength were obtained with airborne continuous wave and ground-based pulsed CO2 Doppler lidars over the Colorado High Plains during a 20-day period in summer 1982. A persistent 'background' layer was found between 6- and 10-km altitude, with a generally uniform backscatter mixing ratio of about 10 to the -10th sq m/kg per sr. The upper boundary of this background layer varied with the tropopause height; the lower boundary varied with the strength and diurnal cycle of convective mixing in the planetary boundary layer (PBL). For quiescent meteorological conditions, the transition from the PBL to the background layer was usually very sharp, with backscatter decreases sometimes as large as 3 decades in about 70 m. Sharp gradients were also found at the boundaries of shallow (tens of meters) subvisible cirrus clouds. For less stable conditions, associated with vertical aerosol transport by deep cumuliform clouds, backscatter tended to decrease exponentially with altitude.

Strategies for lidar characterization of particulates from point and area sources

Science.gov (United States)

Wojcik, Michael D.; Moore, Kori D.; Martin, Randal S.; Hatfield, Jerry

2010-10-01

Use of ground based remote sensing technologies such as scanning lidar systems (light detection and ranging) has gained traction in characterizing ambient aerosols due to some key advantages such as wide area of regard (10 km2), fast response time, high spatial resolution (University, in conjunction with the USDA-ARS, has developed a three-wavelength scanning lidar system called Aglite that has been successfully deployed to characterize particle motion, concentration, and size distribution at both point and diffuse area sources in agricultural and industrial settings. A suite of massbased and size distribution point sensors are used to locally calibrate the lidar. Generating meaningful particle size distribution, mass concentration, and emission rate results based on lidar data is dependent on strategic onsite deployment of these point sensors with successful local meteorological measurements. Deployment strategies learned from field use of this entire measurement system over five years include the characterization of local meteorology and its predictability prior to deployment, the placement of point sensors to prevent contamination and overloading, the positioning of the lidar and beam plane to avoid hard target interferences, and the usefulness of photographic and written observational data.

AN EFFICIENT METHOD FOR AUTOMATIC ROAD EXTRACTION BASED ON MULTIPLE FEATURES FROM LiDAR DATA

Directory of Open Access Journals (Sweden)

Y. Li

2016-06-01

Full Text Available The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1 road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2 local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3 hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for “Urban Classification and 3D Building Reconstruction” project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.

An Efficient Method for Automatic Road Extraction Based on Multiple Features from LiDAR Data

Science.gov (United States)

Li, Y.; Hu, X.; Guan, H.; Liu, P.

2016-06-01

The road extraction in urban areas is difficult task due to the complicated patterns and many contextual objects. LiDAR data directly provides three dimensional (3D) points with less occlusions and smaller shadows. The elevation information and surface roughness are distinguishing features to separate roads. However, LiDAR data has some disadvantages are not beneficial to object extraction, such as the irregular distribution of point clouds and lack of clear edges of roads. For these problems, this paper proposes an automatic road centerlines extraction method which has three major steps: (1) road center point detection based on multiple feature spatial clustering for separating road points from ground points, (2) local principal component analysis with least squares fitting for extracting the primitives of road centerlines, and (3) hierarchical grouping for connecting primitives into complete roads network. Compared with MTH (consist of Mean shift algorithm, Tensor voting, and Hough transform) proposed in our previous article, this method greatly reduced the computational cost. To evaluate the proposed method, the Vaihingen data set, a benchmark testing data provided by ISPRS for "Urban Classification and 3D Building Reconstruction" project, was selected. The experimental results show that our method achieve the same performance by less time in road extraction using LiDAR data.

Lidar observation of Eyjafjallajoekull ash layer evolution above the Swiss Plateau

Science.gov (United States)

Simeonov, Valentin; Dinoev, Todor; Parlange, Mark; Serikov, Ilya; Calpini, Bertrand; Wienhold, F.; Engel, I.; Brabec, M.; Crisian, A.; Peter, T.; Mitev, Valentin; Matthey, R.

2010-05-01

The Iceland volcano Eyjafjallajökull started to emit significant amounts of volcanic ash and SO2 on 15th April 2010, following the initial eruption on 20th March 2010. In the next days, the ash was dispersed over large parts of Europe resulting in the closure of the major part of the European airspace. Information about spatial and temporal evolution of the cloud was needed urgently to define the conditions for opening the airspace. Satellite, airborne and ground observations together with meteorological models were used to evaluate the cloud propagation and evolution. While the horizontal extents of the volcanic cloud were accurately captured by satellite images, it remained difficult to obtain accurate information about the cloud base and top height, density and dynamics. During this event lidars demonstrated that they were the only ground based instruments allowing monitoring of the vertical distribution of the volcanic ash. Here we present observational results showing the evolution of the volcanic layer over the Swiss plateau. The measurements were carried out by one Raman lidar located in Payerne, two elastic lidars located in Neuchatel and Zurich, and a backscatter sonde launched from Zurich. The observations by the lidars have shown very similar time evolution, coherent with the backscatter sonde profiles and characterized by the appearance of the ash layer on the evening of 16th, followed by descend to 2-3 km during the next day and final mixing with the ABL on 19th. Simultaneous water vapor data from the Payerne lidar show low water content of the ash layer. The CSEM and EPFL gratefully acknowledge the financial support by the European Commission under grant RICA-025991.

Light Detection and Ranging (LIDAR) From Space - Laser Altimeters

Science.gov (United States)

Sun, Xiaoli

2016-01-01

Light detection and ranging, or lidar, is like radar but atoptical wavelengths. The principle of operation and theirapplications in remote sensing are similar. Lidars havemany advantages over radars in instrument designs andapplications because of the much shorter laser wavelengthsand narrower beams. The lidar transmitters and receiveroptics are much smaller than radar antenna dishes. Thespatial resolution of lidar measurement is much finer thanthat of radar because of the much smaller footprint size onground. Lidar measurements usually give a better temporalresolution because the laser pulses can be much narrowerthan radio frequency (RF) signals. The major limitation oflidar is the ability to penetrate clouds and ground surfaces.

Small Imaging Depth LIDAR and DCNN-Based Localization for Automated Guided Vehicle.

Science.gov (United States)

Ito, Seigo; Hiratsuka, Shigeyoshi; Ohta, Mitsuhiko; Matsubara, Hiroyuki; Ogawa, Masaru

2018-01-10

We present our third prototype sensor and a localization method for Automated Guided Vehicles (AGVs), for which small imaging LIght Detection and Ranging (LIDAR) and fusion-based localization are fundamentally important. Our small imaging LIDAR, named the Single-Photon Avalanche Diode (SPAD) LIDAR, uses a time-of-flight method and SPAD arrays. A SPAD is a highly sensitive photodetector capable of detecting at the single-photon level, and the SPAD LIDAR has two SPAD arrays on the same chip for detection of laser light and environmental light. Therefore, the SPAD LIDAR simultaneously outputs range image data and monocular image data with the same coordinate system and does not require external calibration among outputs. As AGVs travel both indoors and outdoors with vibration, this calibration-less structure is particularly useful for AGV applications. We also introduce a fusion-based localization method, named SPAD DCNN, which uses the SPAD LIDAR and employs a Deep Convolutional Neural Network (DCNN). SPAD DCNN can fuse the outputs of the SPAD LIDAR: range image data, monocular image data and peak intensity image data. The SPAD DCNN has two outputs: the regression result of the position of the SPAD LIDAR and the classification result of the existence of a target to be approached. Our third prototype sensor and the localization method are evaluated in an indoor environment by assuming various AGV trajectories. The results show that the sensor and localization method improve the localization accuracy.

Development of wavelength locking circuit for 1.53 micron water vapor monitoring coherent differential absorption LIDAR

Science.gov (United States)

Imaki, Masaharu; Kojima, Ryota; Kameyama, Shumpei

2018-04-01

We have studied a ground based coherent differential absorption LIDAR (DIAL) for vertical profiling of water vapor density using a 1.5μm laser wavelength. A coherent LIDAR has an advantage in daytime measurement compared with incoherent LIDAR because the influence of background light is greatly suppressed. In addition, the LIDAR can simultaneously measure wind speed and water vapor density. We had developed a wavelength locking circuit using the phase modulation technique and offset locking technique, and wavelength stabilities of 0.123 pm which corresponds to 16 MHz are realized. In this paper, we report the wavelength locking circuits for the 1.5 um wavelength.

(DCT-FY08) Target Detection Using Multiple Modality Airborne and Ground Based Sensors

Science.gov (United States)

2013-03-01

resolution SIFT grids in metric-topological SLAM ,” in Proc. of the IEEE Conference on Computer Vision and Pattern Recognition, 2009. [4] M. Bosse and R...single camera SLAM ,” IEEE Trans. Pattern Anal. Mach. Intell., vol. 29, no. 6, pp. 1052–1067, 2007. [7] D. Nister, O. Naroditsky, and J. Bergen...segmentation with ground-based and airborne LIDAR range data,” in Proceedings of the Fourth International Symposium on 3D Data Processing

Independent evaluation of the SNODAS snow depth product using regional-scale lidar-derived measurements

Science.gov (United States)

Hedrick, A.; Marshall, H.-P.; Winstral, A.; Elder, K.; Yueh, S.; Cline, D.

2015-01-01

Repeated light detection and ranging (lidar) surveys are quickly becoming the de facto method for measuring spatial variability of montane snowpacks at high resolution. This study examines the potential of a 750 km2 lidar-derived data set of snow depths, collected during the 2007 northern Colorado Cold Lands Processes Experiment (CLPX-2), as a validation source for an operational hydrologic snow model. The SNOw Data Assimilation System (SNODAS) model framework, operated by the US National Weather Service, combines a physically based energy-and-mass-balance snow model with satellite, airborne and automated ground-based observations to provide daily estimates of snowpack properties at nominally 1 km resolution over the conterminous United States. Independent validation data are scarce due to the assimilating nature of SNODAS, compelling the need for an independent validation data set with substantial geographic coverage. Within 12 distinctive 500 × 500 m study areas located throughout the survey swath, ground crews performed approximately 600 manual snow depth measurements during each of the CLPX-2 lidar acquisitions. This supplied a data set for constraining the uncertainty of upscaled lidar estimates of snow depth at the 1 km SNODAS resolution, resulting in a root-mean-square difference of 13 cm. Upscaled lidar snow depths were then compared to the SNODAS estimates over the entire study area for the dates of the lidar flights. The remotely sensed snow depths provided a more spatially continuous comparison data set and agreed more closely to the model estimates than that of the in situ measurements alone. Finally, the results revealed three distinct areas where the differences between lidar observations and SNODAS estimates were most drastic, providing insight into the causal influences of natural processes on model uncertainty.

Development of semiconductor laser based Doppler lidars for wind-sensing applications

DEFF Research Database (Denmark)

Rodrigo, Peter John; Hu, Qi; Pedersen, Christian

2015-01-01

We summarize the progress we have made in the development of semiconductor laser (SL) based Doppler lidar systems for remote wind speed and direction measurements. The SL emitter used in our wind-sensing lidar is an integrated diode laser with a tapered (semiconductor) amplifier. The laser source...

Towards Linking 3D SAR and Lidar Models with a Spatially Explicit Individual Based Forest Model

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Osmanoglu, B.; Ranson, J.; Sun, G.; Armstrong, A. H.; Fischer, R.; Huth, A.

2017-12-01

In this study, we present a parameterization of the FORMIND individual-based gap model (IBGM)for old growth Atlantic lowland rainforest in La Selva, Costa Rica for the purpose of informing multisensor remote sensing techniques for above ground biomass techniques. The model was successfully parameterized and calibrated for the study site; results show that the simulated forest reproduces the structural complexity of Costa Rican rainforest based on comparisons with CARBONO inventory plot data. Though the simulated stem numbers (378) slightly underestimated the plot data (418), particularly for canopy dominant intermediate shade tolerant trees and shade tolerant understory trees, overall there was a 9.7% difference. Aboveground biomass (kg/ha) showed a 0.1% difference between the simulated forest and inventory plot dataset. The Costa Rica FORMIND simulation was then used to parameterize a spatially explicit (3D) SAR and lidar backscatter models. The simulated forest stands were used to generate a Look Up Table as a tractable means to estimate aboveground forest biomass for these complex forests. Various combinations of lidar and radar variables were evaluated in the LUT inversion. To test the capability of future data for estimation of forest height and biomass, we considered data of 1) L- (or P-) band polarimetric data (backscattering coefficients of HH, HV and VV); 2) L-band dual-pol repeat-pass InSAR data (HH/HV backscattering coefficients and coherences, height of scattering phase center at HH and HV using DEM or surface height from lidar data as reference); 3) P-band polarimetric InSAR data (canopy height from inversion of PolInSAR data or use the coherences and height of scattering phase center at HH, HV and VV); 4) various height indices from waveform lidar data); and 5) surface and canopy top height from photon-counting lidar data. The methods for parameterizing the remote sensing models with the IBGM and developing Look Up Tables will be discussed. Results

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.

Scanning Raman lidar for tropospheric water vapor profiling and GPS path delay correction

Science.gov (United States)

Tarniewicz, Jerome; Bock, Olivier; Pelon, Jacques R.; Thom, Christian

2002-01-01

The design of a ground based and transportable combined Raman elastic-backscatter lidar for the remote sensing of lower tropospheric water vapor and nitrogen concentration is described. This lidar is intended to be used for an external calibration of the wet path delay of GPS signals. A description of the method used to derive water vapor and nitrogen profiles in the lower troposphere is given. The instrument has been tested during the ESCOMPTE campaign in June 2001 and first measurements are presented.

The 1996 Leonid shower as studied with a potassium lidar: Observations and inferred meteoroid sizes

Science.gov (United States)

Höffner, Josef; von Zahn, Ulf; McNeil, William J.; Murad, Edmond

1999-02-01

We report on the observation and analysis of meteor trails that are detected by ground-based lidar tuned to the D1 fine structure line of K. The lidar is located at Kühlungsborn, Germany. The echo profiles are analyzed with a temporal resolution of about 1 s and altitude resolution of 200 m. Identification of meteor trails in the large archive of raw data is performed with help of an automated computer search code. During the peak of the Lenoid meteor shower on the morning of November 17, 1996, we observed seven meteor trails between 0245 and 0445 UT. Their mean altitude was 89.0 km. The duration of observation of individual trails ranges from 3 s to ~30 min. We model the probability of observing a meteor trail by ground-based lidar as a function of both altitude distribution and duration of the trails. These distributions depend on the mass distribution, entry velocity, and entry angle of the meteoroids, on the altitude-dependent chemical and dynamical lifetimes of the released K atom, and on the absolute detection sensitivity of our lidar experiment. From the modeling, we derive the statistical likelihood of detection of trails from meteoroids of a particular size. These bracket quite well the observed trails. The model also gives estimates of the probable size of the meteoroids based on characteristics of individual trails.

Hardware in the Loop Performance Assessment of LIDAR-Based Spacecraft Pose Determination.

Science.gov (United States)

Opromolla, Roberto; Fasano, Giancarmine; Rufino, Giancarlo; Grassi, Michele

2017-09-24

In this paper an original, easy to reproduce, semi-analytic calibration approach is developed for hardware-in-the-loop performance assessment of pose determination algorithms processing point cloud data, collected by imaging a non-cooperative target with LIDARs. The laboratory setup includes a scanning LIDAR, a monocular camera, a scaled-replica of a satellite-like target, and a set of calibration tools. The point clouds are processed by uncooperative model-based algorithms to estimate the target relative position and attitude with respect to the LIDAR. Target images, acquired by a monocular camera operated simultaneously with the LIDAR, are processed applying standard solutions to the Perspective- n -Points problem to get high-accuracy pose estimates which can be used as a benchmark to evaluate the accuracy attained by the LIDAR-based techniques. To this aim, a precise knowledge of the extrinsic relative calibration between the camera and the LIDAR is essential, and it is obtained by implementing an original calibration approach which does not need ad-hoc homologous targets (e.g., retro-reflectors) easily recognizable by the two sensors. The pose determination techniques investigated by this work are of interest to space applications involving close-proximity maneuvers between non-cooperative platforms, e.g., on-orbit servicing and active debris removal.

CALIPSO satellite validation using an elastic backscattering Lidar system and the AERONET sun photometer data

International Nuclear Information System (INIS)

Lopes, Fabio Juliano da Silva

2011-01-01

Aerosol and clouds play an important role in the Earth's climate process through their direct and indirect contributions to the radiation budget. The largest difficulty in predicting the climate change processes is associated with uncertainties in the distribution and properties of aerosols and clouds, as well as their interactions on a global scale. The CALIPSO mission was developed as part of the NASA program, in collaboration with the French space agency CNES, with the main goal to develop studies that will help to quantify the uncertainties about aerosols and clouds. The CALIPSO satellite carried a Lidar system on board, named CALIOP, as a primary instrument, able to provide the aerosol and cloud vertical profiles and distribution, as well as their interactions. Once the optical properties measured by CALIOP are retrieved, using a complex set of algorithms, it is necessary to study and develop methodologies in order to assess the accuracy of the CALIOP products. In this context, a validation methodology was developed in order to verify the assumed values of the Lidar Ratio selected by the CALIOP algorithms, using two ground-based remote sensing instruments, an elastic backscatter Lidar system (MSP) installed at IPEN in Sao Paulo and the AERONET sun photometers operating at five different locations in Brazil, Rio Branco - Acre (RB), Alta Floresta - Mato Grosso (AF), Cuiaba - Mato Grosso (CB), Campo Grande - Mato Grosso do Sul (CG) e Sao Paulo - Sao Paulo (SP). Those days when the CALIOP system and ground-based instruments spatially coincided, were selected and analyzed under cloud-free conditions, as well as days when the trajectories of air masses indicated the transport of air parcels from the CALIOP track towards the ground-based sensors. The Lidar Ratio values from the Aeronet/Caliop proposed model was determined and showed good consistency with those initially assumed by the CALIOP Algorithm. Based on the quantitative comparison, a mean difference of -2

Registration of vehicle based panoramic image and LiDAR point cloud

Science.gov (United States)

Chen, Changjun; Cao, Liang; Xie, Hong; Zhuo, Xiangyu

2013-10-01

Higher quality surface information would be got when data from optical images and LiDAR were integrated, owing to the fact that optical images and LiDAR point cloud have unique characteristics that make them preferable in many applications. While most previous works focus on registration of pinhole perspective cameras to 2D or 3D LiDAR data. In this paper, a method for the registration of vehicle based panoramic image and LiDAR point cloud is proposed. Using the translation among panoramic image, single CCD image, laser scanner and Position and Orientation System (POS) along with the GPS/IMU data, precise co-registration between the panoramic image and the LiDAR point cloud in the world system is achieved. Results are presented under a real world data set collected by a new developed Mobile Mapping System (MMS) integrated with a high resolution panoramic camera, two laser scanners and a POS.

An Aerosol Extinction-to-Backscatter Ratio Database Derived from the NASA Micro-Pulse Lidar Network: Applications for Space-based Lidar Observations

Science.gov (United States)

Welton, Ellsworth J.; Campbell, James R.; Spinhime, James D.; Berkoff, Timothy A.; Holben, Brent; Tsay, Si-Chee; Bucholtz, Anthony

2004-01-01

Backscatter lidar signals are a function of both backscatter and extinction. Hence, these lidar observations alone cannot separate the two quantities. The aerosol extinction-to-backscatter ratio, S, is the key parameter required to accurately retrieve extinction and optical depth from backscatter lidar observations of aerosol layers. S is commonly defined as 4*pi divided by the product of the single scatter albedo and the phase function at 180-degree scattering angle. Values of S for different aerosol types are not well known, and are even more difficult to determine when aerosols become mixed. Here we present a new lidar-sunphotometer S database derived from Observations of the NASA Micro-Pulse Lidar Network (MPLNET). MPLNET is a growing worldwide network of eye-safe backscatter lidars co-located with sunphotometers in the NASA Aerosol Robotic Network (AERONET). Values of S for different aerosol species and geographic regions will be presented. A framework for constructing an S look-up table will be shown. Look-up tables of S are needed to calculate aerosol extinction and optical depth from space-based lidar observations in the absence of co-located AOD data. Applications for using the new S look-up table to reprocess aerosol products from NASA's Geoscience Laser Altimeter System (GLAS) will be discussed.

Aerosol observation using multi-wavelength Mie-Raman lidars of the Ad-Net and aerosol component analysis

Directory of Open Access Journals (Sweden)

Nishizawa Tomoaki

2018-01-01

Full Text Available We deployed multi-wavelength Mie-Raman lidars (MMRL at three sites of the AD-Net and have conducted continuous measurements using them since 2013. To analyze the MMRL data and better understand the externally mixing state of main aerosol components (e.g., dust, sea-salt, and black carbon in the atmosphere, we developed an integrated package of aerosol component retrieval algorithms, which have already been developed or are being developed, to estimate vertical profiles of the aerosol components. This package applies to the other ground-based lidar network data (e.g., EARLINET and satellite-borne lidar data (e.g., CALIOP/CALIPSO and ATLID/EarthCARE as well as the other lidar data of the AD-Net.

Aerosol observation using multi-wavelength Mie-Raman lidars of the Ad-Net and aerosol component analysis

Science.gov (United States)

Nishizawa, Tomoaki; Sugimoto, Nobuo; Shimizu, Atsushi; Uno, Itsushi; Hara, Yukari; Kudo, Rei

2018-04-01

We deployed multi-wavelength Mie-Raman lidars (MMRL) at three sites of the AD-Net and have conducted continuous measurements using them since 2013. To analyze the MMRL data and better understand the externally mixing state of main aerosol components (e.g., dust, sea-salt, and black carbon) in the atmosphere, we developed an integrated package of aerosol component retrieval algorithms, which have already been developed or are being developed, to estimate vertical profiles of the aerosol components. This package applies to the other ground-based lidar network data (e.g., EARLINET) and satellite-borne lidar data (e.g., CALIOP/CALIPSO and ATLID/EarthCARE) as well as the other lidar data of the AD-Net.

Estimating Aboveground Forest Carbon Stock of Major Tropical Forest Land Uses Using Airborne Lidar and Field Measurement Data in Central Sumatra

Science.gov (United States)

Thapa, R. B.; Watanabe, M.; Motohka, T.; Shiraishi, T.; shimada, M.

2013-12-01

Tropical forests are providing environmental goods and services including carbon sequestration, energy regulation, water fluxes, wildlife habitats, fuel, and building materials. Despite the policy attention, the tropical forest reserve in Southeast Asian region is releasing vast amount of carbon to the atmosphere due to deforestation. Establishing quality forest statistics and documenting aboveground forest carbon stocks (AFCS) are emerging in the region. Airborne and satellite based large area monitoring methods are developed to compliment conventional plot based field measurement methods as they are costly, time consuming, and difficult to implement for large regions. But these methods still require adequate ground measurements for calibrating accurate AFCS model. Furthermore, tropical region comprised of varieties of natural and plantation forests capping higher variability of forest structures and biomass volumes. To address this issue and the needs for ground data, we propose the systematic collection of ground data integrated with airborne light detection and ranging (LiDAR) data. Airborne LiDAR enables accurate measures of vertical forest structure, including canopy height and volume demanding less ground measurement plots. Using an appropriate forest type based LiDAR sampling framework, structural properties of forest can be quantified and treated similar to ground measurement plots, producing locally relevant information to use independently with satellite data sources including synthetic aperture radar (SAR). In this study, we examined LiDAR derived forest parameters with field measured data and developed general and specific AFCS models for tropical forests in central Sumatra. The general model is fitted for all types of natural and plantation forests while the specific model is fitted to the specific forest type. The study region consists of natural forests including peat swamp and dry moist forests, regrowth, and mangrove and plantation forests

First measurements of a carbon dioxide plume from an industrial source using a ground based mobile differential absorption lidar.

Science.gov (United States)

Robinson, R A; Gardiner, T D; Innocenti, F; Finlayson, A; Woods, P T; Few, J F M

2014-08-01

The emission of carbon dioxide (CO2) from industrial sources is one of the main anthropogenic contributors to the greenhouse effect. Direct remote sensing of CO2 emissions using optical methods offers the potential for the identification and quantification of CO2 emissions. We report the development and demonstration of a ground based mobile differential absorption lidar (DIAL) able to measure the mass emission rate of CO2 in the plume from a power station. To our knowledge DIAL has not previously been successfully applied to the measurement of emission plumes of CO2 from industrial sources. A significant challenge in observing industrial CO2 emission plumes is the ability to discriminate and observe localised concentrations of CO2 above the locally observed background level. The objectives of the study were to modify our existing mobile infrared DIAL system to enable CO2 measurements and to demonstrate the system at a power plant to assess the feasibility of the technique for the identification and quantification of CO2 emissions. The results of this preliminary study showed very good agreement with the expected emissions calculated by the site. The detection limit obtained from the measurements, however, requires further improvement to provide quantification of smaller emitters of CO2, for example for the detection of fugitive emissions. This study has shown that in principle, remote optical sensing technology will have the potential to provide useful direct data on CO2 mass emission rates.

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...

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.

Airborne LIDAR and high resolution satellite data for rapid 3D feature extraction

Science.gov (United States)

Jawak, S. D.; Panditrao, S. N.; Luis, A. J.

2014-11-01

This work uses the canopy height model (CHM) based workflow for individual tree crown delineation and 3D feature extraction approach (Overwatch Geospatial's proprietary algorithm) for building feature delineation from high-density light detection and ranging (LiDAR) point cloud data in an urban environment and evaluates its accuracy by using very high-resolution panchromatic (PAN) (spatial) and 8-band (multispectral) WorldView-2 (WV-2) imagery. LiDAR point cloud data over San Francisco, California, USA, recorded in June 2010, was used to detect tree and building features by classifying point elevation values. The workflow employed includes resampling of LiDAR point cloud to generate a raster surface or digital terrain model (DTM), generation of a hill-shade image and an intensity image, extraction of digital surface model, generation of bare earth digital elevation model (DEM) and extraction of tree and building features. First, the optical WV-2 data and the LiDAR intensity image were co-registered using ground control points (GCPs). The WV-2 rational polynomial coefficients model (RPC) was executed in ERDAS Leica Photogrammetry Suite (LPS) using supplementary *.RPB file. In the second stage, ortho-rectification was carried out using ERDAS LPS by incorporating well-distributed GCPs. The root mean square error (RMSE) for the WV-2 was estimated to be 0.25 m by using more than 10 well-distributed GCPs. In the second stage, we generated the bare earth DEM from LiDAR point cloud data. In most of the cases, bare earth DEM does not represent true ground elevation. Hence, the model was edited to get the most accurate DEM/ DTM possible and normalized the LiDAR point cloud data based on DTM in order to reduce the effect of undulating terrain. We normalized the vegetation point cloud values by subtracting the ground points (DEM) from the LiDAR point cloud. A normalized digital surface model (nDSM) or CHM was calculated from the LiDAR data by subtracting the DEM from the DSM

Surface Signature Characterization at SPE through Ground-Proximal Methods: Methodology Change and Technical Justification

Energy Technology Data Exchange (ETDEWEB)

Schultz-Fellenz, Emily S. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2015-09-09

A portion of LANL’s FY15 SPE objectives includes initial ground-based or ground-proximal investigations at the SPE Phase 2 site. The area of interest is the U2ez location in Yucca Flat. This collection serves as a baseline for discrimination of surface features and acquisition of topographic signatures prior to any development or pre-shot activities associated with SPE Phase 2. Our team originally intended to perform our field investigations using previously vetted ground-based (GB) LIDAR methodologies. However, the extended proposed time frame of the GB LIDAR data collection, and associated data processing time and delivery date, were unacceptable. After technical consultation and careful literature research, LANL identified an alternative methodology to achieve our technical objectives and fully support critical model parameterization. Very-low-altitude unmanned aerial systems (UAS) photogrammetry appeared to satisfy our objectives in lieu of GB LIDAR. The SPE Phase 2 baseline collection was used as a test of this UAS photogrammetric methodology.

On the factors governing water vapor turbulence mixing in the convective boundary layer over land: Concept and data analysis technique using ground-based lidar measurements

International Nuclear Information System (INIS)

Pal, Sandip

2016-01-01

The convective boundary layer (CBL) turbulence is the key process for exchanging heat, momentum, moisture and trace gases between the earth's surface and the lower part of the troposphere. The turbulence parameterization of the CBL is a challenging but important component in numerical models. In particular, correct estimation of CBL turbulence features, parameterization, and the determination of the contribution of eddy diffusivity are important for simulating convection initiation, and the dispersion of health hazardous air pollutants and Greenhouse gases. In general, measurements of higher-order moments of water vapor mixing ratio (q) variability yield unique estimates of turbulence in the CBL. Using the high-resolution lidar-derived profiles of q variance, third-order moment, and skewness and analyzing concurrent profiles of vertical velocity, potential temperature, horizontal wind and time series of near-surface measurements of surface flux and meteorological parameters, a conceptual framework based on bottom up approach is proposed here for the first time for a robust characterization of the turbulent structure of CBL over land so that our understanding on the processes governing CBL q turbulence could be improved. Finally, principal component analyses will be applied on the lidar-derived long-term data sets of q turbulence statistics to identify the meteorological factors and the dominant physical mechanisms governing the CBL turbulence features. - Highlights: • Lidar based study for CBL turbulence features • Water vapor and aerosol turbulence profiles • Processes governing boundary layer turbulence profiles using lidars

On the factors governing water vapor turbulence mixing in the convective boundary layer over land: Concept and data analysis technique using ground-based lidar measurements

Energy Technology Data Exchange (ETDEWEB)

Pal, Sandip, E-mail: sup252@PSU.EDU

2016-06-01

The convective boundary layer (CBL) turbulence is the key process for exchanging heat, momentum, moisture and trace gases between the earth's surface and the lower part of the troposphere. The turbulence parameterization of the CBL is a challenging but important component in numerical models. In particular, correct estimation of CBL turbulence features, parameterization, and the determination of the contribution of eddy diffusivity are important for simulating convection initiation, and the dispersion of health hazardous air pollutants and Greenhouse gases. In general, measurements of higher-order moments of water vapor mixing ratio (q) variability yield unique estimates of turbulence in the CBL. Using the high-resolution lidar-derived profiles of q variance, third-order moment, and skewness and analyzing concurrent profiles of vertical velocity, potential temperature, horizontal wind and time series of near-surface measurements of surface flux and meteorological parameters, a conceptual framework based on bottom up approach is proposed here for the first time for a robust characterization of the turbulent structure of CBL over land so that our understanding on the processes governing CBL q turbulence could be improved. Finally, principal component analyses will be applied on the lidar-derived long-term data sets of q turbulence statistics to identify the meteorological factors and the dominant physical mechanisms governing the CBL turbulence features. - Highlights: • Lidar based study for CBL turbulence features • Water vapor and aerosol turbulence profiles • Processes governing boundary layer turbulence profiles using lidars.

Observation of Asian dust properties by using multi-wavelength LIDAR system at anmyeon island, Korea

International Nuclear Information System (INIS)

Choi, Sung Chul; Ko, Do Kyeoung; Lee, Jong Min; Kim, Young Joon; Noh, Young Min

2004-01-01

The Asian dust affect climate both directly and indirectly because they act as effective ice nuclei and forms ice cloud. However, little is known about spatial distribution and trajectory because few measurement data are available in the free troposphere over East Asia, where a large amount of Asian dust are transported form desert regions in Asian continent. LIDAR system is an effective tool for remotely measuring the vertical distribution of aerosol optical properties. For measurement of Asian dust optical properties, a multi-wavelength LIDAR system developed by the Advanced Environment Monitoring Research Center (ADEMRC), Gwangju Institute Science and Technology (GIST), Korea. This paper presents the results of ground-based multi-wavelength LIDAR measurements of the Asian dust aerosol over Anmyeon Island (36.40N, 126.10E) during the spring of 2004. To discriminate between Asian dust and cloud, depolarization ratio is useful for the detection of these particles and the LIDAR ratio. Also, we discuss the relationship between LIDAR ratio and other optical properties from LIDAR measurement, i.e., the depolarization ratio, aerosol extinction coefficient and LIDAR ratio

Ground-based LiDAR application to characterize sea cliff instability processes along a densely populated coastline in Southern Italy

Science.gov (United States)

Esposito, Giuseppe; Semaan, Fouad; Salvini, Riccardo; Troise, Claudia; Somma, Renato; Matano, Fabio; Sacchi, Marco

2017-04-01

Sea cliff retreatment along the coastline of the Campi Flegrei volcanic area (Southern Italy) is becoming a threat for public and private structures due to the massive urbanization occurred in the last few decades. In this area, geological features of the outcropping rocks represent one of the most important factors conditioning the sea cliff retreatment. In fact, pyroclastic deposits formed by pumices, scoria, ashes and lapilli are arranged in weakly to moderately welded layers of variable thicknesses, resulting very erodible and prone to landslide processes. Available methods to evaluate topographic changes and retreat rates of sea cliffs include a variety of geomatic techniques, like terrestrial and aerial photogrammetry and LiDAR (Light Detection And Ranging). By means of such techniques, it is in fact possible to obtain high resolution topography of sea cliffs and perform multi-temporal change detection analysis. In this contribution, we present an application of Terrestrial Laser Scanning (TLS or ground-based LiDAR) aimed to identify and quantify instability processes acting along the Torrefumo coastal cliff, in the Campi Flegrei area. Specifically, we acquired a series of 3D point clouds on the years 2013 and 2016, and compared them through a cloud-to-cloud distance computation. Furthermore, a statistical analysis was applied to the change detection results. In this way, an inventory of the cliff failures occurred along the Torrefumo cliff in the 2013-2016 time span was created, as well as the spatial and volumetric distribution of these failures was evaluated. The volumetric analysis shows that large collapses occurred rarely, whereas the spatial analysis shows that the majority of failures occurred in the middle and upper parts of the cliff face. Results also show that both rock fall and surficial erosion processes contribute to the cliff retreatment, acting in turn according to the geological properties of the involved pyroclastic deposits. The presented

Development of a Regional Lidar-Derived Above-Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA

Directory of Open Access Journals (Sweden)

Karis Tenneson

2018-03-01

Full Text Available Historical forest management practices in the southwestern US have left forests prone to high-severity, stand-replacement fires. Reducing the cost of forest-fire management and reintroducing fire to the landscape without negative impact depends on detailed knowledge of stand composition, in particular, above-ground biomass (AGB. Lidar-based modeling techniques provide opportunities to increase ability of managers to monitor AGB and other forest metrics at reduced cost. We developed a regional lidar-based statistical model to estimate AGB for Ponderosa pine and mixed conifer forest systems of the southwestern USA, using previously collected field data. Model selection was performed using Bayesian model averaging (BMA to reduce researcher bias, fully explore the model space, and avoid overfitting. The selected model includes measures of canopy height, canopy density, and height distribution. The model selected with BMA explains 71% of the variability in field-estimates of AGB, and the RMSE of the two independent validation data sets are 23.25 and 32.82 Mg/ha. The regional model is structured in accordance with previously described local models, and performs equivalently to these smaller scale models. We have demonstrated the effectiveness of lidar for developing cost-effective, robust regional AGB models for monitoring and planning adaptively at the landscape scale.

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.

Topographic lidar survey of the Chandeleur Islands, Louisiana, February 6, 2012

Science.gov (United States)

Guy, Kristy K.; Plant, Nathaniel G.; Bonisteel-Cormier, Jamie M.

2014-01-01

This Data Series Report contains lidar elevation data collected February 6, 2012, for Chandeleur Islands, Louisiana. Point cloud data in lidar data exchange format (LAS) and bare earth digital elevation models (DEMs) in ERDAS Imagine raster format (IMG) are available as downloadable files. The point cloud data—data points described in three dimensions—were processed to extract bare earth data; therefore, the point cloud data are organized into the following classes: 1– and 17–unclassified, 2–ground, 9–water, and 10–breakline proximity. Digital Aerial Solutions, LLC, (DAS) was contracted by the U.S. Geological Survey (USGS) to collect and process these data. The lidar data were acquired at a horizontal spacing (or nominal pulse spacing) of 0.5 meters (m) or less. The USGS conducted two ground surveys in small areas on the Chandeleur Islands on February 5, 2012. DAS calculated a root mean square error (RMSEz) of 0.034 m by comparing the USGS ground survey point data to triangulated irregular network (TIN) models built from the lidar elevation data. This lidar survey was conducted to document the topography and topographic change of the Chandeleur Islands. The survey supports detailed studies of Louisiana, Mississippi and Alabama barrier islands that resolve annual and episodic changes in beaches, berms and dunes associated with processes driven by storms, sea-level rise, and even human restoration activities. These lidar data are available to Federal, State and local governments, emergency-response officials, resource managers, and the general public.

Synchronous Adversarial Feature Learning for LiDAR based Loop Closure Detection

OpenAIRE

Yin, Peng; He, Yuqing; Xu, Lingyun; Peng, Yan; Han, Jianda; Xu, Weiliang

2018-01-01

Loop Closure Detection (LCD) is the essential module in the simultaneous localization and mapping (SLAM) task. In the current appearance-based SLAM methods, the visual inputs are usually affected by illumination, appearance and viewpoints changes. Comparing to the visual inputs, with the active property, light detection and ranging (LiDAR) based point-cloud inputs are invariant to the illumination and appearance changes. In this paper, we extract 3D voxel maps and 2D top view maps from LiDAR ...

The Effect of Wind-Turbine Wakes on Summertime US Midwest Atmospheric Wind Profiles as Observed with Ground-Based Doppler Lidar

Science.gov (United States)

Rhodes, Michael E.; Lundquist, Julie K.

2013-07-01

We examine the influence of a modern multi-megawatt wind turbine on wind and turbulence profiles three rotor diameters (D) downwind of the turbine. Light detection and ranging (lidar) wind-profile observations were collected during summer 2011 in an operating wind farm in central Iowa at 20-m vertical intervals from 40 to 220 m above the surface. After a calibration period during which two lidars were operated next to each other, one lidar was located approximately 2D directly south of a wind turbine; the other lidar was moved approximately 3D north of the same wind turbine. Data from the two lidars during southerly flow conditions enabled the simultaneous capture of inflow and wake conditions. The inflow wind and turbulence profiles exhibit strong variability with atmospheric stability: daytime profiles are well-mixed with little shear and strong turbulence, while nighttime profiles exhibit minimal turbulence and considerable shear across the rotor disk region and above. Consistent with the observations available from other studies and with wind-tunnel and large-eddy simulation studies, measurable reductions in wake wind-speeds occur at heights spanning the wind turbine rotor (43-117 m), and turbulent quantities increase in the wake. In generalizing these results as a function of inflow wind speed, we find the wind-speed deficit in the wake is largest at hub height or just above, and the maximum deficit occurs when wind speeds are below the rated speed for the turbine. Similarly, the maximum enhancement of turbulence kinetic energy and turbulence intensity occurs at hub height, although observations at the top of the rotor disk do not allow assessment of turbulence in that region. The wind shear below turbine hub height (quantified here with the power-law coefficient) is found to be a useful parameter to identify whether a downwind lidar observes turbine wake or free-flow conditions. These field observations provide data for validating turbine-wake models and wind

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.

Validation of double-pulse 1572 nm integrated path differential absorption lidar measurement of carbon dioxide

Science.gov (United States)

Du, Juan; Liu, Jiqiao; Bi, Decang; Ma, Xiuhua; Hou, Xia; Zhu, Xiaolei; Chen, Weibiao

2018-04-01

A ground-based double-pulse 1572 nm integrated path differential absorption (IPDA) lidar was developed for carbon dioxide (CO2) column concentrations measurement. The lidar measured the CO2 concentrations continuously by receiving the scattered echo signal from a building about 1300 m away. The other two instruments of TDLAS and in-situ CO2 analyzer measured the CO2 concentrations on the same time. A CO2 concentration measurement of 430 ppm with 1.637 ppm standard error was achieved.

Progress on Development of an Airborne Two-Micron IPDA Lidar for Water Vapor and Carbon Dioxide Column Measurements

Science.gov (United States)

Singh, Upendra N.; Petros, Mulugeta; Refaat, Tamer F.; Yu, Jirong; Antill, Charles W.; Taylor, Bryant D.; Bowen, Stephen C.; Welters, Angela M.; Remus, Ruben G.; Wong, Teh-Hwa;

a Threshold-Free Filtering Algorithm for Airborne LIDAR Point Clouds Based on Expectation-Maximization

Science.gov (United States)

Hui, Z.; Cheng, P.; Ziggah, Y. Y.; Nie, Y.

2018-04-01

Filtering is a key step for most applications of airborne LiDAR point clouds. Although lots of filtering algorithms have been put forward in recent years, most of them suffer from parameters setting or thresholds adjusting, which will be time-consuming and reduce the degree of automation of the algorithm. To overcome this problem, this paper proposed a threshold-free filtering algorithm based on expectation-maximization. The proposed algorithm is developed based on an assumption that point clouds are seen as a mixture of Gaussian models. The separation of ground points and non-ground points from point clouds can be replaced as a separation of a mixed Gaussian model. Expectation-maximization (EM) is applied for realizing the separation. EM is used to calculate maximum likelihood estimates of the mixture parameters. Using the estimated parameters, the likelihoods of each point belonging to ground or object can be computed. After several iterations, point clouds can be labelled as the component with a larger likelihood. Furthermore, intensity information was also utilized to optimize the filtering results acquired using the EM method. The proposed algorithm was tested using two different datasets used in practice. Experimental results showed that the proposed method can filter non-ground points effectively. To quantitatively evaluate the proposed method, this paper adopted the dataset provided by the ISPRS for the test. The proposed algorithm can obtain a 4.48 % total error which is much lower than most of the eight classical filtering algorithms reported by the ISPRS.

Airborne Lidar Measurements of Aerosol Optical Properties During SAFARI-2000

Science.gov (United States)

McGill, M. J.; Hlavka, D. L.; Hart, W. D.; Welton, E. J.; Campbell, J. R.; Starr, David OC. (Technical Monitor)

2002-01-01

The Cloud Physics Lidar (CPL) operated onboard the NASA ER-2 high altitude aircraft during the SAFARI-2000 field campaign. The CPL provided high spatial resolution measurements of aerosol optical properties at both 1064 nm and 532 nm. We present here results of planetary boundary layer (PBL) aerosol optical depth analysis and profiles of aerosol extinction. Variation of optical depth and extinction are examined as a function of regional location. The wide-scale aerosol mapping obtained by the CPL is a unique data set that will aid in future studies of aerosol transport. Comparisons between the airborne CPL and ground-based MicroPulse Lidar Network (MPL-Net) sites are shown to have good agreement.

Special relativity effects for space-based coherent lidar experiments

Science.gov (United States)

Raogudimetla, V. S.

1994-01-01

case of the space-based coherent lidar, assuming flat ground. Here an interest in developing analytical expression for the location of the receiving point for the return with respect to the satellite, receiving angle and Doppler shift in frequency and amount of tip, all as measured in the satellite moving coordinate system and the diffuse scattering angle at the ground which does not require any compensation. All the three cases of retro-reflection, specular reflection and diffuse scattering by the ground should be treated though retro-reflection and diffuse scattering are more important.

Coupling Fine-Scale Root and Canopy Structure Using Ground-Based Remote Sensing

Directory of Open Access Journals (Sweden)

Brady S. Hardiman

2017-02-01

Full Text Available Ecosystem physical structure, defined by the quantity and spatial distribution of biomass, influences a range of ecosystem functions. Remote sensing tools permit the non-destructive characterization of canopy and root features, potentially providing opportunities to link above- and belowground structure at fine spatial resolution in functionally meaningful ways. To test this possibility, we employed ground-based portable canopy LiDAR (PCL and ground penetrating radar (GPR along co-located transects in forested sites spanning multiple stages of ecosystem development and, consequently, of structural complexity. We examined canopy and root structural data for coherence (i.e., correlation in the frequency of spatial variation at multiple spatial scales ≤10 m within each site using wavelet analysis. Forest sites varied substantially in vertical canopy and root structure, with leaf area index and root mass more becoming even vertically as forests aged. In all sites, above- and belowground structure, characterized as mean maximum canopy height and root mass, exhibited significant coherence at a scale of 3.5–4 m, and results suggest that the scale of coherence may increase with stand age. Our findings demonstrate that canopy and root structure are linked at characteristic spatial scales, which provides the basis to optimize scales of observation. Our study highlights the potential, and limitations, for fusing LiDAR and radar technologies to quantitatively couple above- and belowground ecosystem structure.

Simultaneous Rayleigh lidar and airglow measurements of middle atmospheric waves over low latitudes in India

Science.gov (United States)

Taori, A.; Kamalakar, V.; Raghunath, K.; Rao, S. V. B.; Russell, J. M.

2012-04-01

We utilize simultaneous Rayleigh lidar and mesospheric OH and O2 airglow measurements to identify the dominant and propagating waves within 40-95 km altitude regions over a low latitude station Gadanki (13.8° N, 79.2 °E). It is found that waves with 0.4-0.6 h periodicity are common throughout the altitude range of 40-95 km with significant amplitudes. The ground based temperature measurements with lidar and airglow monitoring are found to compare well with SABER data. With simultaneous Rayleigh lidar (temperature) and mesospheric airglow (emission intensity and temperature) measurements, we estimate the amplitude growth and Krassovsky parameters to characterize the propagation and dissipation of these upward propagating waves.

The Micro-Pulse Lidar Network (MPLNET): A Federated Network of Micro-pulse Lidars and AERONET Sunphotometers

Science.gov (United States)

Welton, Ellsworth J.; Campbell, James R.; Spinhirne, James D.; Berkoff, Timothy A.; Holben, Brent; Tsay, Si-Chee

2004-01-01

We present the formation of a new global-ground based eye-safe lidar network, the NASA Micro-Pulse Lidar Network (MPLNET). The aim of MPLNET is to acquire long- term observations of aerosol and cloud vertical profiles at unique geographic sites within the NASA Aerosol Robotic Network (AERONET). MPLNET utilizes standard instrumentation and data processing algorithms for efficient network operations and direct comparison of data between each site. The micro-pulse lidar is eye-safe, compact, and commercially available, and most easily allows growth of the network without sacrificing standardized instrumentation goals. Network growth follows a federated approach, pioneered by AERONET, wherein independent research groups may join MPLNET with their own instrument and site. MPLNET sites produce not only vertical profile data, but also column-averaged products already available from AERONET (aerosol optical depth, sky radiance, size distributions). Algorithms are presented for each MPLNET data product. Real-time Level 1 data products (next-day) include daily lidar signal images from the surface to -2Okm, and Level 1.5 aerosol extinction profiles at times co-incident with AERONET observations. Quality assured Level 2 aerosol extinction profiles are generated after screening the Level 1.5 results and removing bad data. Level 3 products include continuous day/night aerosol extinction profiles, and are produced using Level 2 calibration data. Rigorous uncertainty calculations are presented for all data products. Analysis of MPLNET data show the MPL and our analysis routines are capable of successfully retrieving aerosol profiles, with the strenuous accounting of uncertainty necessary for accurate interpretation of the results.

MSFC Doppler Lidar Science experiments and operations plans for 1981 airborne test flight

Science.gov (United States)

Fichtl, G. H.; Bilbro, J. W.; Kaufman, J. W.

1981-01-01

The flight experiment and operations plans for the Doppler Lidar System (DLS) are provided. Application of DLS to the study of severe storms and local weather penomena is addressed. Test plans involve 66 hours of flight time. Plans also include ground based severe storm and local weather data acquisition.

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.

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.

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.

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.

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)

Retrieval method of aerosol extinction coefficient profile by an integral lidar system and case study

Science.gov (United States)

Shan, Huihui; Zhang, Hui; Liu, Junjian; Wang, Shenhao; Ma, Xiaomin; Zhang, Lianqing; Liu, Dong; Xie, Chenbo; Tao, Zongming

2018-02-01

Aerosol extinction coefficient profile is an essential parameter for atmospheric radiation model. But it is difficult to get the full aerosol extinction profile from the ground to the tropopause especially in near ground precisely using backscattering lidar. A combined measurement of side-scattering, backscattering and Raman-scattering lidar is proposed to retrieve the aerosol extinction coefficient profile from the surface to the tropopause which covered a dynamic range of 5 orders. The side-scattering technique solves the dead zone and the overlap problem caused by the traditional lidar in the near range. Using the Raman-scattering the aerosol lidar ratio (extinction to backscatter ratio) can be obtained. The cases studies in this paper show the proposed method is reasonable and feasible.

A user friendly Lidar system based on LabVIEW

Energy Technology Data Exchange (ETDEWEB)

Andersson, Mats; Weibring, P.

1996-09-01

Mobile differential absorption lidar (DIAL) systems have been used for the last two decades. The lidar group in Lund has performed many DIAL measurements with a mobile lidar system which was first described in 1987. This report describes how that system was updated with the graphical programming language LabVIEW in order to get a user friendly system. The software controls the lidar system and analyses measurement data. The measurement results are shown as maps of species concentration. New electronics to support the new lidar program have also been installed. The report describes how all supporting electronics and the program work. A user manual for the new program is also given. 19 refs, 79 figs, 23 charts

Generic calibration procedures for nacelle-based profiling lidars

DEFF Research Database (Denmark)

Borraccino, Antoine; Courtney, Michael; Wagner, Rozenn

In power performance testing, it has been demonstrated that the effects of wind speed and direction variations over the rotor disk can no longer be neglected for large wind turbines [1]. A new generation of commercial nacelle-based lidars is now available, offering wind profiling capabilities. De...

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

High-energy, 2µm laser transmitter for coherent wind LIDAR

Science.gov (United States)

Singh, Upendra N.; Yu, Jirong; Kavaya, Michael J.; Koch, Grady J.

2017-11-01

A coherent Doppler lidar at 2μm wavelength has been built with higher output energy (300 mJ) than previously available. The laser transmitter is based on the solid-state Ho:Tm:LuLiF, a NASA Langley Research Center invented laser material for higher extraction efficiency. This diode pumped injection seeded MOPA has a transform limited line width and diffraction limited beam quality. NASA Langley Research Center is developing coherent wind lidar transmitter technology at eye-safe wavelength for satellite-based observation of wind on a global scale. The ability to profile wind is a key measurement for understanding and predicting atmospheric dynamics and is a critical measurement for improving weather forecasting and climate modeling. We would describe the development and performance of an engineering hardened 2μm laser transmitter for coherent Doppler wind measurement from ground/aircraft/space platform.

Combining satellite photographs and raster lidar data for channel connectivity in tidal marshes.

Science.gov (United States)

Li, Zhi; Hodges, Ben

2017-04-01

High resolution airborne lidar is capable of providing topographic detail down to the 1 x 1 m scale or finer over large tidal marshes of a river delta. Such data sets can be challenging to develop and ground-truth due to the inherent complexities of the environment, the relatively small changes in elevation throughout a marsh, and practical difficulties in accessing the variety of flooded, dry, and muddy regions. Standard lidar point-cloud processing techniques (as typically applied in large lidar data collection program) have a tendency to mis-identify narrow channels and water connectivity in a marsh, which makes it difficult to directly use such data for modeling marsh flows. Unfortunately, it is not always practical, or even possible, to access the point cloud and re-analyze the raw lidar data when discrepancies have been found in a raster work product. Faced with this problem in preparing a model of the Trinity River delta (Texas, USA), we developed an approach to integrating analysis of a lidar-based raster with satellite images. Our primary goal was to identify the clear land/water boundaries needed to identify channelization in the available rasterized lidar data. The channel extraction method uses pixelized satellite photographs that are stretched/distorted with image-processing techniques to match identifiable control features in both lidar and photographic data sets. A kmeans clustering algorithm was applied cluster pixels based on their colors, which is effective in separating land and water in a satellite photograph. The clustered image was matched to the lidar data such that the combination shows the channel network. In effect, we are able to use the fact that the satellite photograph is higher resolution than the lidar data, and thus provides connectivity in the clustering at a finer scale. The principal limitation of the method is the where the satellite image and lidar suffer from similar problems For example, vegetation overhanging a narrow

a Point Cloud Classification Approach Based on Vertical Structures of Ground Objects

Science.gov (United States)

Zhao, Y.; Hu, Q.; Hu, W.

2018-04-01

This paper proposes a novel method for point cloud classification using vertical structural characteristics of ground objects. Since urbanization develops rapidly nowadays, urban ground objects also change frequently. Conventional photogrammetric methods cannot satisfy the requirements of updating the ground objects' information efficiently, so LiDAR (Light Detection and Ranging) technology is employed to accomplish this task. LiDAR data, namely point cloud data, can obtain detailed three-dimensional coordinates of ground objects, but this kind of data is discrete and unorganized. To accomplish ground objects classification with point cloud, we first construct horizontal grids and vertical layers to organize point cloud data, and then calculate vertical characteristics, including density and measures of dispersion, and form characteristic curves for each grids. With the help of PCA processing and K-means algorithm, we analyze the similarities and differences of characteristic curves. Curves that have similar features will be classified into the same class and point cloud correspond to these curves will be classified as well. The whole process is simple but effective, and this approach does not need assistance of other data sources. In this study, point cloud data are classified into three classes, which are vegetation, buildings, and roads. When horizontal grid spacing and vertical layer spacing are 3 m and 1 m respectively, vertical characteristic is set as density, and the number of dimensions after PCA processing is 11, the overall precision of classification result is about 86.31 %. The result can help us quickly understand the distribution of various ground objects.

EFFICIENT LIDAR POINT CLOUD DATA MANAGING AND PROCESSING IN A HADOOP-BASED DISTRIBUTED FRAMEWORK

Directory of Open Access Journals (Sweden)

C. Wang

2017-10-01

Full Text Available Light Detection and Ranging (LiDAR is one of the most promising technologies in surveying and mapping，city management, forestry, object recognition, computer vision engineer and others. However, it is challenging to efficiently storage, query and analyze the high-resolution 3D LiDAR data due to its volume and complexity. In order to improve the productivity of Lidar data processing, this study proposes a Hadoop-based framework to efficiently manage and process LiDAR data in a distributed and parallel manner, which takes advantage of Hadoop’s storage and computing ability. At the same time, the Point Cloud Library (PCL, an open-source project for 2D/3D image and point cloud processing, is integrated with HDFS and MapReduce to conduct the Lidar data analysis algorithms provided by PCL in a parallel fashion. The experiment results show that the proposed framework can efficiently manage and process big LiDAR data.

Efficient LIDAR Point Cloud Data Managing and Processing in a Hadoop-Based Distributed Framework

Science.gov (United States)

Wang, C.; Hu, F.; Sha, D.; Han, X.

2017-10-01

Light Detection and Ranging (LiDAR) is one of the most promising technologies in surveying and mapping city management, forestry, object recognition, computer vision engineer and others. However, it is challenging to efficiently storage, query and analyze the high-resolution 3D LiDAR data due to its volume and complexity. In order to improve the productivity of Lidar data processing, this study proposes a Hadoop-based framework to efficiently manage and process LiDAR data in a distributed and parallel manner, which takes advantage of Hadoop's storage and computing ability. At the same time, the Point Cloud Library (PCL), an open-source project for 2D/3D image and point cloud processing, is integrated with HDFS and MapReduce to conduct the Lidar data analysis algorithms provided by PCL in a parallel fashion. The experiment results show that the proposed framework can efficiently manage and process big LiDAR data.

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....

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.

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

UAV-borne lidar with MEMS mirror-based scanning capability

Science.gov (United States)

Kasturi, Abhishek; Milanovic, Veljko; Atwood, Bryan H.; Yang, James

2016-05-01

Firstly, we demonstrated a wirelessly controlled MEMS scan module with imaging and laser tracking capability which can be mounted and flown on a small UAV quadcopter. The MEMS scan module was reduced down to a small volume of smartphone via Bluetooth while flying on a drone, and could project vector content, text, and perform laser based tracking. Also, a "point-and-range" LiDAR module was developed for UAV applications based on low SWaP (Size, Weight and Power) gimbal-less MEMS mirror beam-steering technology and off-the-shelf OEM LRF modules. For demonstration purposes of an integrated laser range finder module, we used a simple off-the-shelf OEM laser range finder (LRF) with a 100m range, +/-1.5mm accuracy, and 4Hz ranging capability. The LRFs receiver optics were modified to accept 20° of angle, matching the transmitter's FoR. A relatively large (5.0mm) diameter MEMS mirror with +/-10° optical scanning angle was utilized in the demonstration to maintain the small beam divergence of the module. The complete LiDAR prototype can fit into a small volume of battery. The MEMS mirror based LiDAR system allows for ondemand ranging of points or areas within the FoR without altering the UAV's position. Increasing the LRF ranging frequency and stabilizing the pointing of the laser beam by utilizing the onboard inertial sensors and the camera are additional goals of the next design.

Cloud fraction and cloud base measurements from scanning Doppler lidar during WFIP-2

Science.gov (United States)

Bonin, T.; Long, C.; Lantz, K. O.; Choukulkar, A.; Pichugina, Y. L.; McCarty, B.; Banta, R. M.; Brewer, A.; Marquis, M.

2017-12-01

The second Wind Forecast Improvement Project (WFIP-2) consisted of an 18-month field deployment of a variety of instrumentation with the principle objective of validating and improving NWP forecasts for wind energy applications in complex terrain. As a part of the set of instrumentation, several scanning Doppler lidars were installed across the study domain to primarily measure profiles of the mean wind and turbulence at high-resolution within the planetary boundary layer. In addition to these measurements, Doppler lidar observations can be used to directly quantify the cloud fraction and cloud base, since clouds appear as a high backscatter return. These supplementary measurements of clouds can then be used to validate cloud cover and other properties in NWP output. Herein, statistics of the cloud fraction and cloud base height from the duration of WFIP-2 are presented. Additionally, these cloud fraction estimates from Doppler lidar are compared with similar measurements from a Total Sky Imager and Radiative Flux Analysis (RadFlux) retrievals at the Wasco site. During mostly cloudy to overcast conditions, estimates of the cloud radiating temperature from the RadFlux methodology are also compared with Doppler lidar measured cloud base height.

3D Maize Plant Reconstruction Based on Georeferenced Overlapping LiDAR Point Clouds

Directory of Open Access Journals (Sweden)

Miguel Garrido

2015-12-01

Full Text Available 3D crop reconstruction with a high temporal resolution and by the use of non-destructive measuring technologies can support the automation of plant phenotyping processes. Thereby, the availability of such 3D data can give valuable information about the plant development and the interaction of the plant genotype with the environment. This article presents a new methodology for georeferenced 3D reconstruction of maize plant structure. For this purpose a total station, an IMU, and several 2D LiDARs with different orientations were mounted on an autonomous vehicle. By the multistep methodology presented, based on the application of the ICP algorithm for point cloud fusion, it was possible to perform the georeferenced point clouds overlapping. The overlapping point cloud algorithm showed that the aerial points (corresponding mainly to plant parts were reduced to 1.5%–9% of the total registered data. The remaining were redundant or ground points. Through the inclusion of different LiDAR point of views of the scene, a more realistic representation of the surrounding is obtained by the incorporation of new useful information but also of noise. The use of georeferenced 3D maize plant reconstruction at different growth stages, combined with the total station accuracy could be highly useful when performing precision agriculture at the crop plant level.

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...

2012 USACE Topobathy Lidar: Post Sandy (NJ & NY)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These files contain classified topographic and bathymetric lidar data as unclassified valid topographic data (1) and valid topographic data classified as ground (2),...

Statistical properties of mean stand biomass estimators in a LIDAR-based double sampling forest survey design.

Science.gov (United States)

H.E. Anderson; J. Breidenbach

2007-01-01

Airborne laser scanning (LIDAR) can be a valuable tool in double-sampling forest survey designs. LIDAR-derived forest structure metrics are often highly correlated with important forest inventory variables, such as mean stand biomass, and LIDAR-based synthetic regression estimators have the potential to be highly efficient compared to single-stage estimators, which...

Three Dimensional Dynamic Model Based Wind Field Reconstruction from Lidar Data

International Nuclear Information System (INIS)

Raach, Steffen; Schlipf, David; Haizmann, Florian; Cheng, Po Wen

2014-01-01

Using the inflowing horizontal and vertical wind shears for individual pitch controller is a promising method if blade bending measurements are not available. Due to the limited information provided by a lidar system the reconstruction of shears in real-time is a challenging task especially for the horizontal shear in the presence of changing wind direction. The internal model principle has shown to be a promising approach to estimate the shears and directions in 10 minutes averages with real measurement data. The static model based wind vector field reconstruction is extended in this work taking into account a dynamic reconstruction model based on Taylor's Frozen Turbulence Hypothesis. The presented method provides time series over several seconds of the wind speed, shears and direction, which can be directly used in advanced optimal preview control. Therefore, this work is an important step towards the application of preview individual blade pitch control under realistic wind conditions. The method is tested using a turbulent wind field and a detailed lidar simulator. For the simulation, the turbulent wind field structure is flowing towards the lidar system and is continuously misaligned with respect to the horizontal axis of the wind turbine. Taylor's Frozen Turbulence Hypothesis is taken into account to model the wind evolution. For the reconstruction, the structure is discretized into several stages where each stage is reduced to an effective wind speed, superposed with a linear horizontal and vertical wind shear. Previous lidar measurements are shifted using again Taylor's Hypothesis. The wind field reconstruction problem is then formulated as a nonlinear optimization problem, which minimizes the residual between the assumed wind model and the lidar measurements to obtain the misalignment angle and the effective wind speed and the wind shears for each stage. This method shows good results in reconstructing the wind characteristics of a three

Monitoring CO2 Intrusion in shallow aquifer using complex electrical methods and a novel CO2 sensitive Lidar-based sensor

Science.gov (United States)

Leger, E.; Dafflon, B.; Thorpe, M.; Kreitinger, A.; Laura, D.; Haivala, J.; Peterson, J.; Spangler, L.; Hubbard, S. S.

2016-12-01

While subsurface storage of CO2 in geological formations offers significant potential to mitigate atmospheric greenhouse gasses, approaches are needed to monitor the efficacy of the strategy as well as possible negative consequences, such as leakage of CO2 or brine into groundwater or release of fugitive gaseous CO2. Groundwater leakages can cause subsequent reactions that may also be deleterious. For example, a release of dissolved CO2 into shallow groundwatersystems can decrease groundwater pH which can potentiallymobilize naturally occurring trace metals and ions. In this perspective, detecting and assessing potential leak requires development of novel monitoring techniques.We present the results of using surface electrical resistivity tomography (ERT) and a novel CO2 sensitive Lidar-based sensor to monitor a controlled CO2 release at the ZeroEmission Research and Technology Center (Bozeman, Montana). Soil temperature and moisture sensors, wellbore water quality measurements as well as chamber-based CO2 flux measurements were used in addition to the ERT and a novel Lidar-based sensor to detect and assess potential leakage into groundwater, vadose zone and atmosphere. The three-week release wascarried out in the vadose and the saturated zones. Well sampling of pH and conductivity and surface CO2 fluxes and concentrations measurements were acquired during the release and are compared with complex electricalresistivity time-lapse measurements. The novel Lidar-based image of the CO2 plume were compared to chamber-based CO2 flux and concentration measurements. While a continuous increase in subsurface ERT and above ground CO2 was documented, joint analysis of the above and below ground data revealed distinct transport behavior in the vadose and saturated zones. Two type of transport were observed, one in the vadoze zone, monitored by CO2 flux chamber and ERT, and the other one in the saturated zone, were ERT and wellsampling were carried. The experiment suggests how

Individual tree detection based on densities of high points of high resolution airborne lidar

NARCIS (Netherlands)

Abd Rahman, M.Z.; Gorte, B.G.H.

2008-01-01

The retrieval of individual tree location from Airborne LiDAR has focused largely on utilizing canopy height. However, high resolution Airborne LiDAR offers another source of information for tree detection. This paper presents a new method for tree detection based on high points’ densities from a

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

Monitoring individual tree-based change with airborne lidar.

Science.gov (United States)

Duncanson, Laura; Dubayah, Ralph

2018-05-01

Understanding the carbon flux of forests is critical for constraining the global carbon cycle and managing forests to mitigate climate change. Monitoring forest growth and mortality rates is critical to this effort, but has been limited in the past, with estimates relying primarily on field surveys. Advances in remote sensing enable the potential to monitor tree growth and mortality across landscapes. This work presents an approach to measure tree growth and loss using multidate lidar campaigns in a high-biomass forest in California, USA. Individual tree crowns were delineated in 2008 and again in 2013 using a 3D crown segmentation algorithm, with derived heights and crown radii extracted and used to estimate individual tree aboveground biomass. Tree growth, loss, and aboveground biomass were analyzed with respect to tree height and crown radius. Both tree growth and loss rates decrease with increasing tree height, following the expectation that trees slow in growth rate as they age. Additionally, our aboveground biomass analysis suggests that, while the system is a net source of aboveground carbon, these carbon dynamics are governed by size class with the largest sources coming from the loss of a relatively small number of large individuals. This study demonstrates that monitoring individual tree-based growth and loss can be conducted with multidate airborne lidar, but these methods remain relatively immature. Disparities between lidar acquisitions were particularly difficult to overcome and decreased the sample of trees analyzed for growth rate in this study to 21% of the full number of delineated crowns. However, this study illuminates the potential of airborne remote sensing for ecologically meaningful forest monitoring at an individual tree level. As methods continue to improve, airborne multidate lidar will enable a richer understanding of the drivers of tree growth, loss, and aboveground carbon flux.

COHERENT LIDAR SYSTEM BASED ON A SEMICONDUCTOR LASER AND AMPLIFIER

DEFF Research Database (Denmark)

2009-01-01

The present invention relates to a compact, reliable and low-cost coherent LIDAR (Light Detection And Ranging) system for remote wind-speed determination, determination of particle concentration, and/or temperature based on an all semiconductor light source and related methods. The present...... invention provides a coherent LIDAR system comprising a semiconductor laser for emission of a measurement beam of electromagnetic radiation directed towards a measurement volume for illumination of particles in the measurement volume, a reference beam generator for generation of a reference beam, a detector...... for generation of a detector signal by mixing of the reference beam with light emitted from the particles in the measurement volume illuminated by the measurement beam, and a signal processor for generating a velocity signal corresponding to the velocity of the particles based on the detector signal....

Integrating forest inventory and analysis data into a LIDAR-based carbon monitoring system

Science.gov (United States)

Kristofer D. Johnson; Richard Birdsey; Andrew O Finley; Anu Swantaran; Ralph Dubayah; Craig Wayson; Rachel. Riemann

2014-01-01

Forest Inventory and Analysis (FIA) data may be a valuable component of a LIDAR-based carbon monitoring system, but integration of the two observation systems is not without challenges. To explore integration methods, two wall-to-wall LIDAR-derived biomass maps were compared to FIA data at both the plot and county levels in Anne Arundel and Howard Counties in Maryland...

Demonstration of measuring sea fog with an SNSPD-based Lidar system.

Science.gov (United States)

Zhu, Jiang; Chen, Yajun; Zhang, Labao; Jia, Xiaoqing; Feng, Zhijun; Wu, Ganhua; Yan, Xiachao; Zhai, Jiquan; Wu, Yang; Chen, Qi; Zhou, Xiaoying; Wang, Zhizhong; Zhang, Chi; Kang, Lin; Chen, Jian; Wu, Peiheng

2017-11-08

The monitor of sea fogs become more important with the rapid development of marine activities. Remote sensing through laser is an effective tool for monitoring sea fogs, but still challengeable for large distance. We demonstrated a Long-distance Lidar for sea fog with superconducting nanowire single-photon detector (SNSPD), which extended the ranging area to a 180-km diameter area. The system, which was verified by using a benchmark distance measurement of a known island, is applied to the Mie scattering weather prediction Lidar system. The fog echo signal distribution in the range of 42.3∼63.5 km and 53.2∼74.2 km was obtained by the Lidar system. Then the fog concentration and the velocity of the fog were deduced from the distribution, which is consistent with the weather prediction. The height of the sea fog is about two hundred meter while the visibility at this height is about 90 km due to the Earth's radius of curvature. Therefore, the capability of this SNSPD-based Lidar was close to the theoretical limit for sea fog measurements for extremely high signal-to-noise ratio of SNSPD.

Long-term trend analysis and climatology of tropical cirrus clouds using 16 years of lidar data set over Southern India

Science.gov (United States)

Pandit, A. K.; Gadhavi, H. S.; Venkat Ratnam, M.; Raghunath, K.; Rao, S. V. B.; Jayaraman, A.

2015-12-01

Sixteen-year (1998-2013) climatology of cirrus clouds and their macrophysical (base height, top height and geometrical thickness) and optical properties (cloud optical thickness) observed using a ground-based lidar over Gadanki (13.5° N, 79.2° E), India, is presented. The climatology obtained from the ground-based lidar is compared with the climatology obtained from 7 and a half years (June 2006-December 2013) of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations. A very good agreement is found between the two climatologies in spite of their opposite viewing geometries and the differences in sampling frequencies. Nearly 50-55 % of cirrus clouds were found to possess geometrical thickness less than 2 km. Ground-based lidar is found to detect a higher number of sub-visible clouds than CALIOP which has implications for global warming studies as sub-visible cirrus clouds have significant positive radiative forcing. Cirrus clouds with mid-cloud temperatures between -50 to -70 °C have a mean geometrical thickness greater than 2 km in contrast to the earlier reported value of 1.7 km. Trend analyses reveal a statistically significant increase in the altitude of sub-visible cirrus clouds which is consistent with the recent climate model simulations. The mid-cloud altitude of sub-visible cirrus clouds is found to be increasing at the rate of 41 ± 21 m year-1. Statistically significant decrease in optical thickness of sub-visible and thick cirrus clouds is observed. Also, the fraction of sub-visible cirrus cloud is found to have increased by 9 % in the last 16 years (1998 to 2013). This increase is mainly compensated by a 7 % decrease in thin cirrus cloud fraction. This has implications for the temperature and water vapour budget in the tropical tropopause layer.

Linear LIDAR versus Geiger-mode LIDAR: impact on data properties and data quality

Science.gov (United States)

Ullrich, A.; Pfennigbauer, M.

2016-05-01

LIDAR has become the inevitable technology to provide accurate 3D data fast and reliably even in adverse measurement situations and harsh environments. It provides highly accurate point clouds with a significant number of additional valuable attributes per point. LIDAR systems based on Geiger-mode avalanche photo diode arrays, also called single photon avalanche photo diode arrays, earlier employed for military applications, now seek to enter the commercial market of 3D data acquisition, advertising higher point acquisition speeds from longer ranges compared to conventional techniques. Publications pointing out the advantages of these new systems refer to the other category of LIDAR as "linear LIDAR", as the prime receiver element for detecting the laser echo pulses - avalanche photo diodes - are used in a linear mode of operation. We analyze the differences between the two LIDAR technologies and the fundamental differences in the data they provide. The limitations imposed by physics on both approaches to LIDAR are also addressed and advantages of linear LIDAR over the photon counting approach are discussed.

Specular and diffuse object extraction from a LiDAR derived Digital Surface Model (DSM)

International Nuclear Information System (INIS)

Saraf, N M; Hamid, J R A; Kamaruddin, M H

2014-01-01

This paper intents to investigate the indifferent behaviour quantitatively of target objects of interest due to specular and diffuse reflectivity based on generated LiDAR DSM of the study site in Ampang, Kuala Lumpur. The LiDAR data to be used was initially checked for its reliability and accuracy. The point cloud LiDAR data was converted to raster to allow grid analysis of the next process of generating the DSM and DTM. Filtering and masking were made removing the features of interest (i.e. building and tree) and other unwanted above surface features. A normalised DSM and object segmentation approach were conducted on the trees and buildings separately. Error assessment and findings attained were highlighted and documented. The result of LiDAR verification certified that the data is reliable and useable. The RMSE obtained is within the tolerance value of horizontal and vertical accuracy (x, y, z) i.e. 0.159 m, 0.211 m 0.091 m respectively. Building extraction inclusive of roof top based on slope and contour analysis undertaken indicate the capability of the approach while single tree extraction through aspect analysis appears to preserve the accuracy of the extraction accordingly. The paper has evaluated the suitable methods of extracting non-ground features and the effective segmentation of the LiDAR data

EARLINET: towards an advanced sustainable European aerosol lidar network

Science.gov (United States)

Pappalardo, G.; Amodeo, A.; Apituley, A.; Comeron, A.; Freudenthaler, V.; Linné, H.; Ansmann, A.; Bösenberg, J.; D'Amico, G.; Mattis, I.; Mona, L.; Wandinger, U.; Amiridis, V.; Alados-Arboledas, L.; Nicolae, D.; Wiegner, M.

2014-03-01

The European Aerosol Research Lidar Network, EARLINET was founded in 2000 as a research project for establishing a quantitative, comprehensive and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET is continuing to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EARLINET special issue which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last thirteen years. Since 2000, EARLINET has strongly developed in terms of number of stations and spatial distribution, from 17 stations in 10 countries in 2000, to 27 stations in 16 countries in 2013. EARLINET has strongly developed also in terms of technological advances with the spread of advanced multi-wavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing and dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase of the observing capability and a reduction of operational costs. Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions and for model evaluation and satellite data validation and integration. Future plans are in the direction of continuous measurements and near real time data delivery in close cooperation with other ground-based networks, as in the ACTRIS research infrastructure, and with the modelling and satellite community, bridging the research community with the

Real-time surveillance system for marine environment based on HLIF LiDAR

Science.gov (United States)

Babichenko, Sergey; Sobolev, Innokenti; Aleksejev, Valeri; Sõro, Oliver

2017-10-01

The operational monitoring of the risk areas of marine environment requires cost-effective solutions. One of the options is the use of sensor networks based on fixed installations and moving platforms (coastal boats, supply-, cargo-, and passenger vessels). Such network allows to gather environmental data in time and space with direct links to operational activities in the controlled area for further environmental risk assessment. Among many remote sensing techniques the LiDAR (Light Detection And Ranging) based on Light Induced Fluorescence (LIF) is the tool of direct assessment of water quality variations caused by chemical pollution, colored dissolved organic matter, and phytoplankton composition. The Hyperspectral LIF (HLIF) LiDAR acquires comprehensive LIF spectra and analyses them by spectral pattern recognition technique to detect and classify the substances in water remotely. Combined use of HLIF LiDARs with Real-Time Data Management System (RTDMS) provides the economically effective solution for the regular monitoring in the controlled area. OCEAN VISUALS in cooperation with LDI INNOVATION has developed Oil in Water Locator (OWL™) with RTDMS (OWL MAP™) based on HLIF LiDAR technique. This is a novel technical solution for monitoring of marine environment providing continuous unattended operations. OWL™ has been extensively tested on board of various vessels in the North Sea, Norwegian Sea, Barents Sea, Baltic Sea and Caribbean Sea. This paper describes the technology features, the results of its operational use in 2014-2017, and outlook for the technology development.

Evaluation of single photon and Geiger mode Lidar for the 3D Elevation Program

Science.gov (United States)

Stoker, Jason M.; Abdullah, Qassim; Nayegandhi, Amar; Winehouse, Jayna

2016-01-01

Data acquired by Harris Corporation’s (Melbourne, FL, USA) Geiger-mode IntelliEarth™ sensor and Sigma Space Corporation’s (Lanham-Seabrook, MD, USA) Single Photon HRQLS sensor were evaluated and compared to accepted 3D Elevation Program (3DEP) data and survey ground control to assess the suitability of these new technologies for the 3DEP. While not able to collect data currently to meet USGS lidar base specification, this is partially due to the fact that the specification was written for linear-mode systems specifically. With little effort on part of the manufacturers of the new lidar systems and the USGS Lidar specifications team, data from these systems could soon serve the 3DEP program and its users. Many of the shortcomings noted in this study have been reported to have been corrected or improved upon in the next generation sensors.

MERGING AIRBORNE LIDAR DATA AND SATELLITE SAR DATA FOR BUILDING CLASSIFICATION

Directory of Open Access Journals (Sweden)

T. Yamamoto

2015-05-01

Full Text Available A frequent map revision is required in GIS applications, such as disaster prevention and urban planning. In general, airborne photogrammetry and LIDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, attribute data acquisition and classification depend on manual editing works including ground surveys. In general, airborne photogrammetry and LiDAR measurements are applied to geometrical data acquisition for automated map generation and revision. However, these approaches classify geometrical attributes. Moreover, ground survey and manual editing works are finally required in attribute data classification. On the other hand, although geometrical data extraction is difficult, SAR data have a possibility to automate the attribute data acquisition and classification. The SAR data represent microwave reflections on various surfaces of ground and buildings. There are many researches related to monitoring activities of disaster, vegetation, and urban. Moreover, we have an opportunity to acquire higher resolution data in urban areas with new sensors, such as ALOS2 PALSAR2. Therefore, in this study, we focus on an integration of airborne LIDAR data and satellite SAR data for building extraction and classification.

Three-dimensional reconstruction of indoor whole elements based on mobile LiDAR point cloud data

Science.gov (United States)

Gong, Yuejian; Mao, Wenbo; Bi, Jiantao; Ji, Wei; He, Zhanjun

2014-11-01

Ground-based LiDAR is one of the most effective city modeling tools at present, which has been widely used for three-dimensional reconstruction of outdoor objects. However, as for indoor objects, there are some technical bottlenecks due to lack of GPS signal. In this paper, based on the high-precision indoor point cloud data which was obtained by LiDAR, an international advanced indoor mobile measuring equipment, high -precision model was fulfilled for all indoor ancillary facilities. The point cloud data we employed also contain color feature, which is extracted by fusion with CCD images. Thus, it has both space geometric feature and spectral information which can be used for constructing objects' surface and restoring color and texture of the geometric model. Based on Autodesk CAD platform and with help of PointSence plug, three-dimensional reconstruction of indoor whole elements was realized. Specifically, Pointools Edit Pro was adopted to edit the point cloud, then different types of indoor point cloud data was processed, including data format conversion, outline extracting and texture mapping of the point cloud model. Finally, three-dimensional visualization of the real-world indoor was completed. Experiment results showed that high-precision 3D point cloud data obtained by indoor mobile measuring equipment can be used for indoor whole elements' 3-d reconstruction and that methods proposed in this paper can efficiently realize the 3 -d construction of indoor whole elements. Moreover, the modeling precision could be controlled within 5 cm, which was proved to be a satisfactory result.

Ground-based remote sensing observation of the complex behaviour of the Marseille boundary layer during ESCOMPTE

Science.gov (United States)

Delbarre, H.; Augustin, P.; Saïd, F.; Campistron, B.; Bénech, B.; Lohou, F.; Puygrenier, V.; Moppert, C.; Cousin, F.; Fréville, P.; Fréjafon, E.

2005-03-01

Ground-based remote sensing systems have been used during the ESCOMPTE campaign, to continuously characterize the boundary-layer behaviour through many atmospheric parameters (wind, extinction and ozone concentration distribution, reflectivity, turbulence). This analysis is focused on the comparison of the atmospheric stratification retrieved from a UV angular ozone lidar, an Ultra High Frequency wind profiler and a sodar, above the area of Marseille, on June 26th 2001 (Intensive Observation Period 2b). The atmospheric stratification is shown to be very complex including two superimposed sea breezes, with an important contribution of advection. The temporal and spatial evolution of the stratification observed by the UV lidar and by the UHF radar are in good agreement although the origin of the echoes of these systems is quite different. The complexity of the dynamic situation has only partially been retrieved by a non-hydrostatic mesoscale model used with a 3 km resolution.

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.

Sensitivity studies for a space-based methane lidar mission

Directory of Open Access Journals (Sweden)

C. Kiemle

2011-10-01

Full Text Available Methane is the third most important greenhouse gas in the atmosphere after water vapour and carbon dioxide. A major handicap to quantify the emissions at the Earth's surface in order to better understand biosphere-atmosphere exchange processes and potential climate feedbacks is the lack of accurate and global observations of methane. Space-based integrated path differential absorption (IPDA lidar has potential to fill this gap, and a Methane Remote Lidar Mission (MERLIN on a small satellite in polar orbit was proposed by DLR and CNES in the frame of a German-French climate monitoring initiative. System simulations are used to identify key performance parameters and to find an advantageous instrument configuration, given the environmental, technological, and budget constraints. The sensitivity studies use representative averages of the atmospheric and surface state to estimate the measurement precision, i.e. the random uncertainty due to instrument noise. Key performance parameters for MERLIN are average laser power, telescope size, orbit height, surface reflectance, and detector noise. A modest-size lidar instrument with 0.45 W average laser power and 0.55 m telescope diameter on a 506 km orbit could provide 50-km averaged methane column measurement along the sub-satellite track with a precision of about 1% over vegetation. The use of a methane absorption trough at 1.65 μm improves the near-surface measurement sensitivity and vastly relaxes the wavelength stability requirement that was identified as one of the major technological risks in the pre-phase A studies for A-SCOPE, a space-based IPDA lidar for carbon dioxide at the European Space Agency. Minimal humidity and temperature sensitivity at this wavelength position will enable accurate measurements in tropical wetlands, key regions with largely uncertain methane emissions. In contrast to actual passive remote sensors, measurements in Polar Regions will be possible and biases due to aerosol

Verification test for three WindCube WLS7 LiDARs at the Høvsøre test site

DEFF Research Database (Denmark)

Gottschall, Julia; Courtney, Michael

The report describes the procedure of testing ground-based WindCube lidars (manufactured by the French company Leosphere) at the Høvsøre test site in comparison to reference sensors mounted at a meteorological mast. Results are presented for three tested units – in detail for unit WLS7-0062, and ......-0062, and in a summary for units WLS7-0064 and WLS7-0066. The verification test covers the evaluation of measured mean wind speeds, wind directions and wind speed standard deviations. The data analysis is basically performed in terms of different kinds of regression analyses.......The report describes the procedure of testing ground-based WindCube lidars (manufactured by the French company Leosphere) at the Høvsøre test site in comparison to reference sensors mounted at a meteorological mast. Results are presented for three tested units – in detail for unit WLS7...

Object-Based Crop Species Classification Based on the Combination of Airborne Hyperspectral Images and LiDAR Data

Directory of Open Access Journals (Sweden)

Xiaolong Liu

2015-01-01

Full Text Available Identification of crop species is an important issue in agricultural management. In recent years, many studies have explored this topic using multi-spectral and hyperspectral remote sensing data. In this study, we perform dedicated research to propose a framework for mapping crop species by combining hyperspectral and Light Detection and Ranging (LiDAR data in an object-based image analysis (OBIA paradigm. The aims of this work were the following: (i to understand the performances of different spectral dimension-reduced features from hyperspectral data and their combination with LiDAR derived height information in image segmentation; (ii to understand what classification accuracies of crop species can be achieved by combining hyperspectral and LiDAR data in an OBIA paradigm, especially in regions that have fragmented agricultural landscape and complicated crop planting structure; and (iii to understand the contributions of the crop height that is derived from LiDAR data, as well as the geometric and textural features of image objects, to the crop species’ separabilities. The study region was an irrigated agricultural area in the central Heihe river basin, which is characterized by many crop species, complicated crop planting structures, and fragmented landscape. The airborne hyperspectral data acquired by the Compact Airborne Spectrographic Imager (CASI with a 1 m spatial resolution and the Canopy Height Model (CHM data derived from the LiDAR data acquired by the airborne Leica ALS70 LiDAR system were used for this study. The image segmentation accuracies of different feature combination schemes (very high-resolution imagery (VHR, VHR/CHM, and minimum noise fractional transformed data (MNF/CHM were evaluated and analyzed. The results showed that VHR/CHM outperformed the other two combination schemes with a segmentation accuracy of 84.8%. The object-based crop species classification results of different feature integrations indicated that

Augmented Reality Based Doppler Lidar Data Visualization: Promises and Challenges

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Cherukuru N. W.

2016-01-01

As a proof of concept, we used the lidar data from a recent field campaign and developed a smartphone application to view the lidar scan in augmented reality. In this paper, we give a brief methodology of this feasibility study, present the challenges and promises of using AR technology in conjunction with Doppler wind lidars.

Advanced signal processing based on support vector regression for lidar applications

Science.gov (United States)

Gelfusa, M.; Murari, A.; Malizia, A.; Lungaroni, M.; Peluso, E.; Parracino, S.; Talebzadeh, S.; Vega, J.; Gaudio, P.

2015-10-01

The LIDAR technique has recently found many applications in atmospheric physics and remote sensing. One of the main issues, in the deployment of systems based on LIDAR, is the filtering of the backscattered signal to alleviate the problems generated by noise. Improvement in the signal to noise ratio is typically achieved by averaging a quite large number (of the order of hundreds) of successive laser pulses. This approach can be effective but presents significant limitations. First of all, it implies a great stress on the laser source, particularly in the case of systems for automatic monitoring of large areas for long periods. Secondly, this solution can become difficult to implement in applications characterised by rapid variations of the atmosphere, for example in the case of pollutant emissions, or by abrupt changes in the noise. In this contribution, a new method for the software filtering and denoising of LIDAR signals is presented. The technique is based on support vector regression. The proposed new method is insensitive to the statistics of the noise and is therefore fully general and quite robust. The developed numerical tool has been systematically compared with the most powerful techniques available, using both synthetic and experimental data. Its performances have been tested for various statistical distributions of the noise and also for other disturbances of the acquired signal such as outliers. The competitive advantages of the proposed method are fully documented. The potential of the proposed approach to widen the capability of the LIDAR technique, particularly in the detection of widespread smoke, is discussed in detail.

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

Cloud properties derived from two lidars over the ARM SGP site

Energy Technology Data Exchange (ETDEWEB)

Dupont, Jean-Charles; Haeffelin, Martial; Morille, Y.; Comstock, Jennifer M.; Flynn, Connor J.; Long, Charles N.; Sivaraman, Chitra; Newsom, Rob K.

2011-02-16

biased low, especially for daylight periods, compared with those derived from the RL data, which detects 5 cloud base ranging from 7.5 km in winter to 9.5 km in summer (and tops ranging from 8.6 to 10.5 km). The optically thickest cirrus clouds (COT>0.3) reach 50% of the total population for the Raman lidar and only 20% for the Micropulse lidar due to the difference of pulse energy and the effect of solar irradiance contamination. A complementary study using the cloud fraction 10 derived from the Micropulse lidar for clouds below 5 km and from the Raman lidar for cloud above 5 km allows for better estimation of the total cloud fraction between the ground and the top of the atmosphere. This study presents the diurnal cycle of cloud fraction for each season in comparisons with the Long et al. (2006) cloud fraction calculation derived from radiative flux analysis.

Three-dimensional mapping of light transmittance and foliage distribution using lidar

International Nuclear Information System (INIS)

Todd, K.W.; Csillag, F.; Atkinson, P.M.

2003-01-01

The horizontal and vertical distributions of light transmittance were evaluated as a function of foliage distribution using lidar (light detection and ranging) observations for a sugar maple (Acer saccharum) stand in the Turkey Lakes Watershed. Along the vertical profile of vegetation, horizontal slices of probability of light transmittance were derived from an Optech ALTM 1225 instrument's return pulses (two discrete, 15-cm diameter returns) using indicator kriging. These predictions were compared with (i) below canopy (1-cm spatial resolution) transect measurements of the fraction of photosynthetically active radiation (FPAR) and (ii) measurements of tree height. A first-order trend was initially removed from the lidar returns. The vertical distribution of vegetation height was then sliced into nine percentiles and indicator variograms were fitted to them. Variogram parameters were found to vary as a function of foliage height above ground. In this paper, we show that the relationship between ground measurements of FPAR and kriged estimates of vegetation cover becomes stronger and tighter at coarser spatial resolutions. Three-dimensional maps of foliage distribution were computed as stacks of the percentile probability surfaces. These probability surfaces showed correspondence with individual tree-based observations and provided a much more detailed characterization of quasi-continuous foliage distribution. These results suggest that discrete-return lidar provides a promising technology to capture variations of foliage characteristics in forests to support the development of functional linkages between biophysical and ecological studies. (author)

Project ABLE: (Atmospheric Balloonborne Lidar Experiment)

Science.gov (United States)

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

1985-03-01

Project ABLE (Atmospheric Balloonborne Lidar Experiment) is part of the A.F. Geophysics Laboratory's continuing interest in developing techniques for making remote measurements of atmospheric quantities such as density, pressure, temperatures, and wind motions. The system consists of a balloonborne lidar payload designed to measure neutral molecular density as a function of altitude from ground level to 70 km. The lidar provides backscatter data at the doubled and tripled frequencies of a Nd:YAG laser, which will assist in the separation of the molecular and aerosol contributions and subsequent determination of molecular and aerosol contributions and subsequent determination of molecular density vs altitude. The object of this contract was to fabricate and operate in a field test a balloonborne lidar experiment capable of performing nighttime atmospheric density measurements up to 70 km altitude with a resolution of 150 meters. The payload included a frequency-doubled and -tripled Nd:YAG laser with outputs at 355 and 532 nm; a telescoped receiver with PMT detectors; a command-controlled optical pointing system; and support system, including thermal control, telmetry, command, and power. Successful backscatter measurements were made during field operations which included a balloon launch from Roswell, NM and a flight over the White Sands Missile Range.

Lidar remote sensing of above-ground biomass in three biomes.

Science.gov (United States)

Michael A. Lefsky; Warren B. Cohen; David J. Harding; Geoffrey G. Parkers; Steven A. Acker; S. Thomas. Gower

2002-01-01

Estimation of the amount of carbon stored in forests is a key challenge for understanding the global carbon cycle, one which remote sensing is expected to help address. However, estimation of carbon storage in moderate to high biomass forests is difficult for conventional optical and radar sensors. Lidar (light detection and ranging) instruments measure the vertical...

Airborne Measurements of Atmospheric Pressure made Using an IPDA Lidar Operating in the Oxygen A-Band

Science.gov (United States)

Riris, Haris; Abshire, James B.; Stephen, Mark; Rodriquez, Michael; Allan, Graham; Hasselbrack, William; Mao, Jianping

2012-01-01

We report airborne measurements of atmospheric pressure made using an integrated path differential absorption (IPDA) lidar that operates in the oxygen A-band near 765 nm. Remote measurements of atmospheric temperature and pressure are needed for NASA s Active Sensing of CO2 Emissions Over Nights, Days, and Seasons (ASCENDS) mission to measure atmospheric CO2. Accurate measurements of tropospheric CO2 on a global scale are very important in order to better understand its sources and sinks and to improve our predictions of climate change. The goal of ASCENDS is to determine the CO2 dry mixing ratio with lidar measurements from space at a level of 1 ppm. Analysis to date shows that with current weather models, measurements of both the CO2 column density and the column density of dry air are needed. Since O2 is a stable molecule that uniformly mixed in the atmosphere, measuring O2 absorption in the atmosphere can be used to infer the dry air density. We have developed an airborne (IPDA) lidar for Oxygen, with support from the NASA ESTO IIP program. Our lidar uses DFB-based seed laser diodes, a pulsed modulator, a fiber laser amplifier, and a non-linear crystal to generate wavelength tunable 765 nm laser pulses with a few uJ/pulse energy. The laser pulse rate is 10 KHz, and average transmitted laser power is 20 mW. Our lidar steps laser pulses across a selected line O2 doublet near 764.7 nm in the Oxygen A-band. The direct detection lidar receiver uses a 20 cm diameter telescope, a Si APD detector in Geiger mode, and a multi-channel scalar to detect and record the time resolved laser backscatter in 40 separate wavelength channels. Subsequent analysis is used to estimate the transmission line shape of the doublet for the laser pulses reflected from the ground. Ground based data analysis allows averaging from 1 to 60 seconds to increase SNR in the transmission line shape of the doublet. Our retrieval algorithm fits the expected O2 lineshapes against the measurements and

Statistical-uncertainty-based adaptive filtering of lidar signals

International Nuclear Information System (INIS)

Fuehrer, P. L.; Friehe, C. A.; Hristov, T. S.; Cooper, D. I.; Eichinger, W. E.

2000-01-01

An adaptive filter signal processing technique is developed to overcome the problem of Raman lidar water-vapor mixing ratio (the ratio of the water-vapor density to the dry-air density) with a highly variable statistical uncertainty that increases with decreasing photomultiplier-tube signal strength and masks the true desired water-vapor structure. The technique, applied to horizontal scans, assumes only statistical horizontal homogeneity. The result is a variable spatial resolution water-vapor signal with a constant variance out to a range limit set by a specified signal-to-noise ratio. The technique was applied to Raman water-vapor lidar data obtained at a coastal pier site together with in situ instruments located 320 m from the lidar. The micrometerological humidity data were used to calibrate the ratio of the lidar gains of the H 2 O and the N 2 photomultiplier tubes and set the water-vapor mixing ratio variance for the adaptive filter. For the coastal experiment the effective limit of the lidar range was found to be approximately 200 m for a maximum noise-to-signal variance ratio of 0.1 with the implemented data-reduction procedure. The technique can be adapted to off-horizontal scans with a small reduction in the constraints and is also applicable to other remote-sensing devices that exhibit the same inherent range-dependent signal-to-noise ratio problem. (c) 2000 Optical Society of America

The Extraction of Vegetation Points from LiDAR Using 3D Fractal Dimension Analyses

Directory of Open Access Journals (Sweden)

Haiquan Yang

2015-08-01

Full Text Available Light Detection and Ranging (LiDAR, a high-precision technique used for acquiring three-dimensional (3D surface information, is widely used to study surface vegetation information. Moreover, the extraction of a vegetation point set from the LiDAR point cloud is a basic starting-point for vegetation information analysis, and an important part of its further processing. To extract the vegetation point set completely and to describe the different spatial morphological characteristics of various features in a LiDAR point cloud, we have used 3D fractal dimensions. We discovered that every feature has its own distinctive 3D fractal dimension interval. Based on the 3D fractal dimensions of tall trees, we propose a new method for the extraction of vegetation using airborne LiDAR. According to this method, target features can be distinguished based on their morphological characteristics. The non-ground points acquired by filtering are processed by region growing segmentation and the morphological characteristics are evaluated by 3D fractal dimensions to determine the features required for the determination of the point set for tall trees. Avon, New York, USA was selected as the study area to test the method and the result proves the method’s efficiency. Thus, this approach is feasible. Additionally, the method uses the 3D coordinate properties of the LiDAR point cloud and does not require additional information, such as return intensity, giving it a larger scope of application.

Atmospheric Turbulence Estimates from a Pulsed Lidar

Science.gov (United States)

Pruis, Matthew J.; Delisi, Donald P.; Ahmad, Nash'at N.; Proctor, Fred H.

2013-01-01

Estimates of the eddy dissipation rate (EDR) were obtained from measurements made by a coherent pulsed lidar and compared with estimates from mesoscale model simulations and measurements from an in situ sonic anemometer at the Denver International Airport and with EDR estimates from the last observation time of the trailing vortex pair. The estimates of EDR from the lidar were obtained using two different methodologies. The two methodologies show consistent estimates of the vertical profiles. Comparison of EDR derived from the Weather Research and Forecast (WRF) mesoscale model with the in situ lidar estimates show good agreement during the daytime convective boundary layer, but the WRF simulations tend to overestimate EDR during the nighttime. The EDR estimates from a sonic anemometer located at 7.3 meters above ground level are approximately one order of magnitude greater than both the WRF and lidar estimates - which are from greater heights - during the daytime convective boundary layer and substantially greater during the nighttime stable boundary layer. The consistency of the EDR estimates from different methods suggests a reasonable ability to predict the temporal evolution of a spatially averaged vertical profile of EDR in an airport terminal area using a mesoscale model during the daytime convective boundary layer. In the stable nighttime boundary layer, there may be added value to EDR estimates provided by in situ lidar measurements.

2006 Texas Water Development Board (TWDB) Lidar: Brazoria County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, flight lines of standard density (1.4 meter ground sample distance) data were collected over...

2006 Texas Water Development Board (TWDB) Lidar: Galveston County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, flight lines of standard density (1.4 meter ground sample distance) data were collected over...

2006 Texas Water Development Board (TWDB) Lidar: Jackson County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, flight lines of standard density (1.4 meter ground sample distance) data were collected over...

2006 Texas Water Development Board (TWDB) Lidar: Orange County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, 43 flight lines of standard density (1.4 meter ground sample distance) data were collected over...

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.

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.

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...

Comparing Individual Tree Segmentation Based on High Resolution Multispectral Image and Lidar Data

Science.gov (United States)

Xiao, P.; Kelly, M.; Guo, Q.

2014-12-01

This study compares the use of high-resolution multispectral WorldView images and high density Lidar data for individual tree segmentation. The application focuses on coniferous and deciduous forests in the Sierra Nevada Mountains. The tree objects are obtained in two ways: a hybrid region-merging segmentation method with multispectral images, and a top-down and bottom-up region-growing method with Lidar data. The hybrid region-merging method is used to segment individual tree from multispectral images. It integrates the advantages of global-oriented and local-oriented region-merging strategies into a unified framework. The globally most-similar pair of regions is used to determine the starting point of a growing region. The merging iterations are constrained within the local vicinity, thus the segmentation is accelerated and can reflect the local context. The top-down region-growing method is adopted in coniferous forest to delineate individual tree from Lidar data. It exploits the spacing between the tops of trees to identify and group points into a single tree based on simple rules of proximity and likely tree shape. The bottom-up region-growing method based on the intensity and 3D structure of Lidar data is applied in deciduous forest. It segments tree trunks based on the intensity and topological relationships of the points, and then allocate other points to exact tree crowns according to distance. The accuracies for each method are evaluated with field survey data in several test sites, covering dense and sparse canopy. Three types of segmentation results are produced: true positive represents a correctly segmented individual tree, false negative represents a tree that is not detected and assigned to a nearby tree, and false positive represents that a point or pixel cluster is segmented as a tree that does not in fact exist. They respectively represent correct-, under-, and over-segmentation. Three types of index are compared for segmenting individual tree

Aerosol and cloud sensing with the Lidar In-space Technology Experiment (LITE)

Science.gov (United States)

Winker, D. M.; McCormick, M. P.

1994-01-01

The Lidar In-space Technology Experiment (LITE) is a multi-wavelength backscatter lidar developed by NASA Langley Research Center to fly on the Space Shuttle. The LITE instrument is built around a three-wavelength ND:YAG laser and a 1-meter diameter telescope. The laser operates at 10 Hz and produces about 500 mJ per pulse at 1064 nm and 532 nm, and 150 mJ per pulse at 355 nm. The objective of the LITE program is to develop the engineering processes required for space lidar and to demonstrate applications of space-based lidar to remote sensing of the atmosphere. The LITE instrument was designed to study a wide range of cloud and aerosol phenomena. To this end, a comprehensive program of scientific investigations has been planned for the upcoming mission. Simulations of on-orbit performance show the instrument has sufficient sensitivity to detect even thin cirrus on a single-shot basis. Signal averaging provides the capability of measuring the height and structure of the planetary boundary layer, aerosols in the free troposphere, the stratospheric aerosol layer, and density profiles to an altitude of 40 km. The instrument has successfully completed a ground-test phase and is scheduled to fly on the Space Shuttle Discovery for a 9-day mission in September 1994.

Comparing LiDAR-Generated to ground- surveyed channel cross-sectional profiles in a forested mountain stream

Science.gov (United States)

Brian C. Dietterick; Russell White; Ryan Hilburn

2012-01-01

Airborne Light Detection and Ranging (LiDAR) holds promise to provide an alternative to traditional ground-based survey methods for stream channel characterization and some change detection purposes, even under challenging landscape conditions. This study compared channel characteristics measured at 53 ground-surveyed and LiDAR-derived crosssectional profiles located...

A Multi-temporal Analysis of Logging Impacts on Tropical Forest Structure Using Airborne Lidar Data

Science.gov (United States)

Keller, M. M.; Pinagé, E. R.; Duffy, P.; Longo, M.; dos-Santos, M. N.; Leitold, V.; Morton, D. C.

2017-12-01

The long-term impacts of selective logging on carbon cycling and ecosystem function in tropical-forests are still uncertain. Despite improvements in selective logging detection using satellite data, quantifying changes in forest structure from logging and recovery following logging is difficult using orbital data. We analyzed the dynamics of forest structure comparing logged and unlogged forests in the Eastern Brazilian Amazon (Paragominas Municipality, Pará State) using small footprint discrete return airborne lidar data acquired in 2012 and 2014. Logging operations were conducted at the 1200 ha study site from 2006 through 2013 using reduced impact logging techniques—management practices that minimize canopy and ground damage compared to more common conventional logging. Nevertheless, logging still reduced aboveground biomass by 10% to 20% in logged areas compared to intact forests. We aggregated lidar point-cloud data at spatial scales ranging from 50 m to 250 m and developed a binomial classification model based on the height distribution of lidar returns in 2012 and validated the model against the 2014 lidar acquisition. We accurately classified intact and logged forest classes compared with field data. Classification performance improved as spatial resolution increased (AUC = 0.974 at 250 m). We analyzed the differences in canopy gaps, understory damage (based on a relative density model), and biomass (estimated from total canopy height) of intact and logged classes. As expected, logging greatly increased both canopy gap formation and understory damage. However, while the area identified as canopy gap persisted for at least 8 years (from the oldest logging treatments in 2006 to the most recent lidar acquisition in 2014), the effects of ground damage were mostly erased by vigorous understory regrowth after about 5 years. The rate of new gap formation was 6 to 7 times greater in recently logged forests compared to undisturbed forests. New gaps opened at a

Progress report of FY 1997 activities: The application of Kalman filtering to derive water vapor profiles from combined ground-based sensors: Raman lidar, microwave radiometers, GPS, and radiosondes

International Nuclear Information System (INIS)

Edgeworth R. Westwater; Yong Han

1997-01-01

Previously, the proposers have delivered to ARM a documented algorithm, that is now applied operationally, and which derives water vapor profiles from combined remote sensor measurements of water vapor radiometers, cloud-base ceilometers, and radio acoustic sounding systems (RASS). With the expanded deployment of a Raman lidar at the CART Central Facility, high quality, high vertical-resolution, water vapor profiles will be provided during nighttime clear conditions, and during clear daytime conditions, to somewhat lower altitudes. The object of this proposal was to use Kalman Filtering, previously applied to the combination of nighttime Raman lidar and microwave radiometer data, to derive high-quality water vapor profiles, during non-precipitating conditions, from data routinely available at the CART site. Input data to the algorithm would include: Raman lidar data, highly quality-controlled data of integrated moisture from microwave radiometers and GPS, RASS, and radiosondes. The algorithm will include recently-developed quality control procedures for radiometers. The focus of this years activities has been on the intercomparison of data obtained during an intensive operating period at the SGP CART site in central Oklahoma

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.

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.

A multiresolution hierarchical classification algorithm for filtering airborne LiDAR data

Science.gov (United States)

Chen, Chuanfa; Li, Yanyan; Li, Wei; Dai, Honglei

2013-08-01

We presented a multiresolution hierarchical classification (MHC) algorithm for differentiating ground from non-ground LiDAR point cloud based on point residuals from the interpolated raster surface. MHC includes three levels of hierarchy, with the simultaneous increase of cell resolution and residual threshold from the low to the high level of the hierarchy. At each level, the surface is iteratively interpolated towards the ground using thin plate spline (TPS) until no ground points are classified, and the classified ground points are used to update the surface in the next iteration. 15 groups of benchmark dataset, provided by the International Society for Photogrammetry and Remote Sensing (ISPRS) commission, were used to compare the performance of MHC with those of the 17 other publicized filtering methods. Results indicated that MHC with the average total error and average Cohen’s kappa coefficient of 4.11% and 86.27% performs better than all other filtering methods.

Using Lidar and color infrared imagery to successfully measure stand characteristics on the William B. Bankhead National Forest, Alabama

Science.gov (United States)

Jeffrey Stephens; Luben Dimov; Callie Schweitzer; Wubishet Tadesse

2008-01-01

Light detection and ranging (Lidar) and color infrared imagery (CIR) were used to quantify forest structure and to distinguish deciduous from coniferous trees for selected stands on the William B. Bankhead National Forest in Alabama. Lidar bare ground and vegetation point clouds were used to determine tree heights and tree locations. Lidar accuracy was assessed by...

Raman lidars for a better understanding of pollution in the Arctic System (PARCS)

Science.gov (United States)

Patrick, Chazette; Jean-Christophe, Raut; Julien, Totems; Xiaoxia, Shang; Christophe, Caudoux; Julien, Delanoë; Kathy, Law

2018-04-01

The development of oil and gas drilling and the opening of new shipping routes, in the Barents and Norway seas, poses new challenges for the Arctic environment due to the impact of air pollution emissions on climate and air quality. To improve our knowledge of the interactions between aerosols, water vapor and cloud cover, within the French PARCS (Pollution in the ARCtic System) project, Raman lidar observations were performed from the ground and from an ultra-light aircraft near the North Cape in northern Norway, and coupled with measurements from a 95 GHz ground-based Doppler radar.

Aerosols Observations with a new lidar station in Punta Arenas, Chile

Science.gov (United States)

Barja, Boris; Zamorano, Felix; Ristori, Pablo; Otero, Lidia; Quel, Eduardo; Sugimoto, Nobuo; Shimizu, Atsushi; Santana, Jorge

2018-04-01

A tropospheric lidar system was installed in Punta Arenas, Chile (53.13°S, 70.88°W) in September 2016 under the collaboration project SAVERNET (Chile, Japan and Argentina) to monitor the atmosphere. Statistical analyses of the clouds and aerosols behavior and some cases of dust detected with lidar, at these high southern latitude and cold environment regions during three months (austral spring) are discussed using information from satellite, modelling and solar radiation ground measurements.

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.

Registration of Aerial Image with Airborne LiDAR Data Based on Plücker Line

Directory of Open Access Journals (Sweden)

SHENG Qinghong

2015-07-01

Full Text Available Registration of aerial image with airborne LiDAR data is a key to feature extraction. A registration model based on Plücker line is proposed. The relative position and attitude relationship between the conjugate lines in LiDAR and image is determined based on Plücker linear equation, which describes line transformation in space, then coplanarity condition equation is established. Finally, coordinate transformation between image point and corresponding LiDAR point is achieved by the spiral movement of Plücker lines in the image. The registration model of Plücker linear coplanarity condition equation is simple, and jointly describes the rotation and translation to avoid coupling error between them, so the accuracy is approved. This research provides technical support for high-quality earth spatial information acquisition.

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

Estimation of Above Ground Biomass in a Tropical Mountain Forest in Southern Ecuador Using Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Víctor González-Jaramillo

2018-04-01

Full Text Available A reliable estimation of Above Ground Biomass (AGB in Tropical Mountain Forest (TMF is still complicated, due to fast-changing climate and topographic conditions, which modifies the forest structure within fine scales. The variations in vertical and horizontal forest structure are hardly detectable by small field plots, especially in natural TMF due to the high tree diversity and the inaccessibility of remote areas. Therefore, the present approach used remotely sensed data from a Light Detection and Ranging (LiDAR sensor in combination with field measurements to estimate AGB accurately for a catchment in the Andes of south-eastern Ecuador. From the LiDAR data, information about horizontal and vertical structure of the TMF could be derived and the vegetation at tree level classified, differentiated between the prevailing forest types (ravine forest, ridge forest and Elfin Forest. Furthermore, topographical variables (Topographic Position Index, TPI; Morphometric Protection Index, MPI were calculated by means of the high-resolution LiDAR data to analyse the AGB distribution within the catchment. The field measurements included different tree parameters of the species present in the plots, which were used to determine the local mean Wood Density (WD as well as the specific height-diameter relationship to calculate AGB, applying regional scale modelling at tree level. The results confirmed that field plot measurements alone cannot capture completely the forest structure in TMF but in combination with high resolution LiDAR data, applying a classification at tree level, the AGB amount (Mg ha−1 and its distribution in the entire catchment could be estimated adequately (model accuracy at tree level: R2 > 0.91. It was found that the AGB distribution is strongly related to ridges and depressions (TPI and to the protection of the site (MPI, because high AGB was also detected at higher elevations (up to 196.6 Mg ha−1, above 2700 m, if the site is

Retrieval of aerosol complex refractive index from a synergy between lidar, sun photometer and in situ measurements during LISAIR experiment

International Nuclear Information System (INIS)

Raut, J.C.; Chazette, P.

2007-01-01

Particulate pollutant exchanges between the streets and the Planetary Boundary Layer (PBL), and their daily evolution linked to human activity were studied in the framework of the Lidar pour la Surveillance de l'AIR (LISAIR) experiment. This program lasted from 10 to 30 May 2005. A synergetic approach combining dedicated active (lidar) and passive (sun photometer) remote sensors as well as ground based in situ instrumentation (nephelometer, aethalometer and particle sizers) was used to investigate urban aerosol optical properties within Paris. Aerosol complex refractive indices were assessed to be 1.56-0.034 i at 355 nm and 1.59-0.040 i at 532 nm, thus leading to single-scattering albedo values between 0.80 and 0.88. These retrievals are consistent with soot components in the aerosol arising from traffic exhausts indicating that these pollutants have a radiative impact on climate. We also discussed the influence of relative humidity on aerosol properties. A good agreement was found between vertical extinction profile derived from lidar backscattering signal and retrieved from the coupling between radio sounding and ground in situ measurements. (authors)

A cloud masking algorithm for EARLINET lidar systems

Science.gov (United States)

Binietoglou, Ioannis; Baars, Holger; D'Amico, Giuseppe; Nicolae, Doina

2015-04-01

Cloud masking is an important first step in any aerosol lidar processing chain as most data processing algorithms can only be applied on cloud free observations. Up to now, the selection of a cloud-free time interval for data processing is typically performed manually, and this is one of the outstanding problems for automatic processing of lidar data in networks such as EARLINET. In this contribution we present initial developments of a cloud masking algorithm that permits the selection of the appropriate time intervals for lidar data processing based on uncalibrated lidar signals. The algorithm is based on a signal normalization procedure using the range of observed values of lidar returns, designed to work with different lidar systems with minimal user input. This normalization procedure can be applied to measurement periods of only few hours, even if no suitable cloud-free interval exists, and thus can be used even when only a short period of lidar measurements is available. Clouds are detected based on a combination of criteria including the magnitude of the normalized lidar signal and time-space edge detection performed using the Sobel operator. In this way the algorithm avoids misclassification of strong aerosol layers as clouds. Cloud detection is performed using the highest available time and vertical resolution of the lidar signals, allowing the effective detection of low-level clouds (e.g. cumulus humilis). Special attention is given to suppress false cloud detection due to signal noise that can affect the algorithm's performance, especially during day-time. In this contribution we present the details of algorithm, the effect of lidar characteristics (space-time resolution, available wavelengths, signal-to-noise ratio) to detection performance, and highlight the current strengths and limitations of the algorithm using lidar scenes from different lidar systems in different locations across Europe.

Urban forest topographical mapping using UAV LIDAR

Science.gov (United States)

Putut Ash Shidiq, Iqbal; Wibowo, Adi; Kusratmoko, Eko; Indratmoko, Satria; Ardhianto, Ronni; Prasetyo Nugroho, Budi

2017-12-01

Topographical data is highly needed by many parties, such as government institution, mining companies and agricultural sectors. It is not just about the precision, the acquisition time and data processing are also carefully considered. In relation with forest management, a high accuracy topographic map is necessary for planning, close monitoring and evaluating forest changes. One of the solution to quickly and precisely mapped topography is using remote sensing system. In this study, we test high-resolution data using Light Detection and Ranging (LiDAR) collected from unmanned aerial vehicles (UAV) to map topography and differentiate vegetation classes based on height in urban forest area of University of Indonesia (UI). The semi-automatic and manual classifications were applied to divide point clouds into two main classes, namely ground and vegetation. There were 15,806,380 point clouds obtained during the post-process, in which 2.39% of it were detected as ground.

Arrange and average algorithm for the retrieval of aerosol parameters from multiwavelength high-spectral-resolution lidar/Raman lidar data.

Science.gov (United States)

Chemyakin, Eduard; Müller, Detlef; Burton, Sharon; Kolgotin, Alexei; Hostetler, Chris; Ferrare, Richard

2014-11-01

We present the results of a feasibility study in which a simple, automated, and unsupervised algorithm, which we call the arrange and average algorithm, is used to infer microphysical parameters (complex refractive index, effective radius, total number, surface area, and volume concentrations) of atmospheric aerosol particles. The algorithm uses backscatter coefficients at 355, 532, and 1064 nm and extinction coefficients at 355 and 532 nm as input information. Testing of the algorithm is based on synthetic optical data that are computed from prescribed monomodal particle size distributions and complex refractive indices that describe spherical, primarily fine mode pollution particles. We tested the performance of the algorithm for the "3 backscatter (β)+2 extinction (α)" configuration of a multiwavelength aerosol high-spectral-resolution lidar (HSRL) or Raman lidar. We investigated the degree to which the microphysical results retrieved by this algorithm depends on the number of input backscatter and extinction coefficients. For example, we tested "3β+1α," "2β+1α," and "3β" lidar configurations. This arrange and average algorithm can be used in two ways. First, it can be applied for quick data processing of experimental data acquired with lidar. Fast automated retrievals of microphysical particle properties are needed in view of the enormous amount of data that can be acquired by the NASA Langley Research Center's airborne "3β+2α" High-Spectral-Resolution Lidar (HSRL-2). It would prove useful for the growing number of ground-based multiwavelength lidar networks, and it would provide an option for analyzing the vast amount of optical data acquired with a future spaceborne multiwavelength lidar. The second potential application is to improve the microphysical particle characterization with our existing inversion algorithm that uses Tikhonov's inversion with regularization. This advanced algorithm has recently undergone development to allow automated and

Lidar Cloud Detection with Fully Convolutional Networks

Science.gov (United States)

Cromwell, E.; Flynn, D.

2017-12-01

The vertical distribution of clouds from active remote sensing instrumentation is a widely used data product from global atmospheric measuring sites. The presence of clouds can be expressed as a binary cloud mask and is a primary input for climate modeling efforts and cloud formation studies. Current cloud detection algorithms producing these masks do not accurately identify the cloud boundaries and tend to oversample or over-represent the cloud. This translates as uncertainty for assessing the radiative impact of clouds and tracking changes in cloud climatologies. The Atmospheric Radiation Measurement (ARM) program has over 20 years of micro-pulse lidar (MPL) and High Spectral Resolution Lidar (HSRL) instrument data and companion automated cloud mask product at the mid-latitude Southern Great Plains (SGP) and the polar North Slope of Alaska (NSA) atmospheric observatory. Using this data, we train a fully convolutional network (FCN) with semi-supervised learning to segment lidar imagery into geometric time-height cloud locations for the SGP site and MPL instrument. We then use transfer learning to train a FCN for (1) the MPL instrument at the NSA site and (2) for the HSRL. In our semi-supervised approach, we pre-train the classification layers of the FCN with weakly labeled lidar data. Then, we facilitate end-to-end unsupervised pre-training and transition to fully supervised learning with ground truth labeled data. Our goal is to improve the cloud mask accuracy and precision for the MPL instrument to 95% and 80%, respectively, compared to the current cloud mask algorithms of 89% and 50%. For the transfer learning based FCN for the HSRL instrument, our goal is to achieve a cloud mask accuracy of 90% and a precision of 80%.

Coherent lidar wind measurements from the Space Station base using 1.5 m all-reflective optics

Science.gov (United States)

Bilbro, J. W.; Beranek, R. G.

1987-01-01

This paper discusses the space-based measurement of atmospheric winds from the point of view of the requirements of the optical system of a coherent CO2 lidar. A brief description of the measurement technique is given and a discussion of previous study results provided. The telescope requirements for a Space Station based lidar are arrived at through discussions of the desired system sensitivity and the need for lag angle compensation.

New Results from the NOAA CREST Lidar Network (CLN Observations in the US Eastcoast

Directory of Open Access Journals (Sweden)

Moshary Fred

2016-01-01

Full Text Available This paper presents coordinated ground-based observations by the NOAA-CREST Lidar Network (CLN for profiling of aerosols, cloud, water vapor, and wind along the US east coast including Caribbean region at Puerto Rico. The instrumentation, methodology and observation capability are reviewed. The applications to continental and intercontinental-scale transport of smoke and dust plumes, and their large scale regional impact are discussed.

EARLINET: towards an advanced sustainable European aerosol lidar network

Science.gov (United States)

Pappalardo, G.; Amodeo, A.; Apituley, A.; Comeron, A.; Freudenthaler, V.; Linné, H.; Ansmann, A.; Bösenberg, J.; D'Amico, G.; Mattis, I.; Mona, L.; Wandinger, U.; Amiridis, V.; Alados-Arboledas, L.; Nicolae, D.; Wiegner, M.

2014-08-01

The European Aerosol Research Lidar Network, EARLINET, was founded in 2000 as a research project for establishing a quantitative, comprehensive, and statistically significant database for the horizontal, vertical, and temporal distribution of aerosols on a continental scale. Since then EARLINET has continued to provide the most extensive collection of ground-based data for the aerosol vertical distribution over Europe. This paper gives an overview of the network's main developments since 2000 and introduces the dedicated EARLINET special issue, which reports on the present innovative and comprehensive technical solutions and scientific results related to the use of advanced lidar remote sensing techniques for the study of aerosol properties as developed within the network in the last 13 years. Since 2000, EARLINET has developed greatly in terms of number of stations and spatial distribution: from 17 stations in 10 countries in 2000 to 27 stations in 16 countries in 2013. EARLINET has developed greatly also in terms of technological advances with the spread of advanced multiwavelength Raman lidar stations in Europe. The developments for the quality assurance strategy, the optimization of instruments and data processing, and the dissemination of data have contributed to a significant improvement of the network towards a more sustainable observing system, with an increase in the observing capability and a reduction of operational costs. Consequently, EARLINET data have already been extensively used for many climatological studies, long-range transport events, Saharan dust outbreaks, plumes from volcanic eruptions, and for model evaluation and satellite data validation and integration. Future plans are aimed at continuous measurements and near-real-time data delivery in close cooperation with other ground-based networks, such as in the ACTRIS (Aerosols, Clouds, and Trace gases Research InfraStructure Network) www.actris.net, and with the modeling and satellite

Airborne lidar reflectance measurements at 1.57 μm in support of the A-SCOPE mission for atmospheric CO2

Directory of Open Access Journals (Sweden)

J. Caron

2009-11-01

Full Text Available The characteristics of the lidar reflectance of the Earth's surface is an important issue for the IPDA lidar technique (integrated path differential absorption lidar which is the proposed method for the spaceborne measurement of atmospheric carbon dioxide within the framework of ESA's A-SCOPE project. Both, the absolute reflectance of the ground and its variations have an impact on the measurement sensitivity. The first aspect influences the instrument's signal to noise ratio, the second one can lead to retrieval errors, if the ground reflectance changes are strong on small scales. The investigation of the latter is the main purpose of this study. Airborne measurements of the lidar ground reflectance at 1.57 μm wavelength were performed in Central and Western Europe, including many typical land surface coverages as well as the open sea. The analyses of the data show, that the lidar ground reflectance is highly variable on a wide range of spatial scales. However, by means of the assumption of laser footprints in the order of several tens of meters, as planned for spaceborne systems, and by means of an averaging of the data it was shown, that this specific retrieval error is well below 1 ppm (CO2 column mixing ratio, and so compatible with the sensitivity requirements of spaceborne CO2 measurements. Several approaches for upscaling the data in terms of the consideration of larger laser footprints, compared to the one used here, are shown and discussed. Furthermore, the collected data are compared to MODIS ground reflectance data.

A Comparison of sector-scan and dual Doppler wind measurements at Høvsøre Test Station – one lidar or two?

DEFF Research Database (Denmark)

Simon, Elliot; Courtney, Michael

from the coast). Ground based remote sensing has numerous advantages over traditional in-situ (offshore met mast) and buoy based installations, mainly in terms or cost, complexity, and failure/delay risk. Since each lidar can only measure a portion of the wind vector, it is necessary to either deploy...

Investigating the influence of LiDAR ground surface errors on the utility of derived forest inventories

Science.gov (United States)

Wade T. Tinkham; Alistair M. S. Smith; Chad Hoffman; Andrew T. Hudak; Michael J. Falkowski; Mark E. Swanson; Paul E. Gessler

2012-01-01

Light detection and ranging, or LiDAR, effectively produces products spatially characterizing both terrain and vegetation structure; however, development and use of those products has outpaced our understanding of the errors within them. LiDAR's ability to capture three-dimensional structure has led to interest in conducting or augmenting forest inventories with...

Augmented Reality Based Doppler Lidar Data Visualization: Promises and Challenges

Science.gov (United States)

Cherukuru, N. W.; Calhoun, R.

2016-06-01

Augmented reality (AR) is a technology in which the enables the user to view virtual content as if it existed in real world. We are exploring the possibility of using this technology to view radial velocities or processed wind vectors from a Doppler wind lidar, thus giving the user an ability to see the wind in a literal sense. This approach could find possible applications in aviation safety, atmospheric data visualization as well as in weather education and public outreach. As a proof of concept, we used the lidar data from a recent field campaign and developed a smartphone application to view the lidar scan in augmented reality. In this paper, we give a brief methodology of this feasibility study, present the challenges and promises of using AR technology in conjunction with Doppler wind lidars.

Demonstration of coherent Doppler lidar for navigation in GPS-denied environments

Science.gov (United States)

Amzajerdian, Farzin; Hines, Glenn D.; Pierrottet, Diego F.; Barnes, Bruce W.; Petway, Larry B.; Carson, John M.

2017-05-01

A coherent Doppler lidar has been developed to address NASA's need for a high-performance, compact, and cost-effective velocity and altitude sensor onboard its landing vehicles. Future robotic and manned missions to solar system bodies require precise ground-relative velocity vector and altitude data to execute complex descent maneuvers and safe, soft landing at a pre-designated site. This lidar sensor, referred to as a Navigation Doppler Lidar (NDL), meets the required performance of the landing missions while complying with vehicle size, mass, and power constraints. Operating from up to four kilometers altitude, the NDL obtains velocity and range precision measurements reaching 2 cm/sec and 2 meters, respectively, dominated by the vehicle motion. Terrestrial aerial vehicles will also benefit from NDL data products as enhancement or replacement to GPS systems when GPS is unavailable or redundancy is needed. The NDL offers a viable option to aircraft navigation in areas where the GPS signal can be blocked or jammed by intentional or unintentional interference. The NDL transmits three laser beams at different pointing angles toward the ground to measure range and velocity along each beam using a frequency modulated continuous wave (FMCW) technique. The three line-of-sight measurements are then combined in order to determine the three components of the vehicle velocity vector and its altitude relative to the ground. This paper describes the performance and capabilities that the NDL demonstrated through extensive ground tests, helicopter flight tests, and onboard an autonomous rocket-powered test vehicle while operating in closedloop with a guidance, navigation, and control (GN and C) system.

AUTOMATIC PARKING OF SELF-DRIVING CAR BASED ON LIDAR

OpenAIRE

B. Lee; Y. Wei; I. Y. Guo

2017-01-01

To overcome the deficiency of ultrasonic sensor and camera, this paper proposed a method of autonomous parking based on the self-driving car, using HDL-32E LiDAR. First the 3-D point cloud data was preprocessed. Then we calculated the minimum size of parking space according to the dynamic theories of vehicle. Second the rapidly-exploring random tree algorithm (RRT) algorithm was improved in two aspects based on the moving characteristic of autonomous car. And we calculated the parking path on...

A Thin Plate Spline-Based Feature-Preserving Method for Reducing Elevation Points Derived from LiDAR

Directory of Open Access Journals (Sweden)

Chuanfa Chen

2015-09-01

Full Text Available Light detection and ranging (LiDAR technique is currently one of the most important tools for collecting elevation points with a high density in the context of digital elevation model (DEM construction. However, the high density data always leads to serious time and memory consumption problems in data processing. In this paper, we have developed a thin plate spline (TPS-based feature-preserving (TPS-F method for LiDAR-derived ground data reduction by selecting a certain amount of significant terrain points and by extracting geomorphological features from the raw dataset to maintain the accuracy of constructed DEMs as high as possible, while maximally keeping terrain features. We employed four study sites with different topographies (i.e., flat, undulating, hilly and mountainous terrains to analyze the performance of TPS-F for LiDAR data reduction in the context of DEM construction. These results were compared with those of the TPS-based algorithm without features (TPS-W and two classical data selection methods including maximum z-tolerance (Max-Z and the random method. Results show that irrespective of terrain characteristic, the two versions of TPS-based approaches (i.e., TPS-F and TPS-W are always more accurate than the classical methods in terms of error range and root means square error. Moreover, in terms of streamline matching rate (SMR, TPS-F has a better ability of preserving geomorphological features, especially for the mountainous terrain. For example, the average SMR of TPS-F is 89.2% in the mountainous area, while those of TPS-W, max-Z and the random method are 56.6%, 34.7% and 35.3%, respectively.

Laser remote sensing of water vapor: Raman lidar development

International Nuclear Information System (INIS)

Goldsmith, J.E.M.; Lapp, M.; Bisson, S.E.; Melfi, S.H.; Whiteman, D.N.; Ferrare, R.A.; Evans, K.D.

1994-01-01

The goal of this research is the development of a critical design for a Raman lidar system optimized to match ARM Program needs for profiling atmospheric water vapor at CART sites. This work has emphasized the development of enhanced daytime capabilities using Raman lidar techniques. This abstract touches briefly on the main components of the research program, summarizing results of the efforts. A detailed Raman lidar instrument model has been developed to predict the daytime and nighttime performance capabilities of Raman lidar systems. The model simulates key characteristics of the lidar system, using realistic atmospheric profiles, modeled background sky radiance, and lidar system parameters based on current instrument capabilities. The model is used to guide development of lidar systems based on both the solar-blind concept and the narrowband, narrow field-of-view concept for daytime optimization

2005 Maryland Department of Natural Resources LiDAR: Cecil County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LIDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

Extracting More Data from LiDAR in Forested Areas by Analyzing Waveform Shape

Directory of Open Access Journals (Sweden)

Peter Beets

2012-03-01

Full Text Available Light Detection And Ranging (LiDAR in forested areas is used for constructing Digital Terrain Models (DTMs, estimating biomass carbon and timber volume and estimating foliage distribution as an indicator of tree growth and health. All of these purposes are hindered by the inability to distinguish the source of returns as foliage, stems, understorey and the ground except by their relative positions. The ability to separate these returns would improve all analyses significantly. Furthermore, waveform metrics providing information on foliage density could improve forest health and growth estimates. In this study, the potential to use waveform LiDAR was investigated. Aerial waveform LiDAR data were acquired for a New Zealand radiata pine plantation forest, and Leaf Area Density (LAD was measured in the field. Waveform peaks with a good signal-to-noise ratio were analyzed and each described with a Gaussian peak height, half-height width, and an exponential decay constant. All parameters varied substantially across all surface types, ruling out the potential to determine source characteristics for individual returns, particularly those with a lower signal-to-noise ratio. However, pulses on the ground on average had a greater intensity, decay constant and a narrower peak than returns from coniferous foliage. When spatially averaged, canopy foliage density (measured as LAD varied significantly, and was found to be most highly correlated with the volume-average exponential decay rate. A simple model based on the Beer-Lambert law is proposed to explain this relationship, and proposes waveform decay rates as a new metric that is less affected by shadowing than intensity-based metrics. This correlation began to fail when peaks with poorer curve fits were included.

Algorithm for Extracting Digital Terrain Models under Forest Canopy from Airborne LiDAR Data

Directory of Open Access Journals (Sweden)

Almasi S. Maguya

2014-07-01

Full Text Available Extracting digital elevationmodels (DTMs from LiDAR data under forest canopy is a challenging task. This is because the forest canopy tends to block a portion of the LiDAR pulses from reaching the ground, hence introducing gaps in the data. This paper presents an algorithm for DTM extraction from LiDAR data under forest canopy. The algorithm copes with the challenge of low data density by generating a series of coarse DTMs by using the few ground points available and using trend surfaces to interpolate missing elevation values in the vicinity of the available points. This process generates a cloud of ground points from which the final DTM is generated. The algorithm has been compared to two other algorithms proposed in the literature in three different test sites with varying degrees of difficulty. Results show that the algorithm presented in this paper is more tolerant to low data density compared to the other two algorithms. The results further show that with decreasing point density, the differences between the three algorithms dramatically increased from about 0.5m to over 10m.

Progress in diode-pumped alexandrite lasers as a new resource for future space lidar missions

Science.gov (United States)

Damzen, M. J.; Thomas, G. M.; Teppitaksak, A.; Minassian, A.

2017-11-01

Satellite-based remote sensing using laser-based lidar techniques provides a powerful tool for global 3-D mapping of atmospheric species (e.g. CO2, ozone, clouds, aerosols), physical attributes of the atmosphere (e.g. temperature, wind speed), and spectral indicators of Earth features (e.g. vegetation, water). Such information provides a valuable source for weather prediction, understanding of climate change, atmospheric science and health of the Earth eco-system. Similarly, laser-based altimetry can provide high precision ground topography mapping and more complex 3-D mapping (e.g. canopy height profiling). The lidar technique requires use of cutting-edge laser technologies and engineered designs that are capable of enduring the space environment over the mission lifetime. The laser must operate with suitably high electrical-to-optical efficiency and risk reduction strategy adopted to mitigate against laser failure or excessive operational degradation of laser performance.

DECISION LEVEL FUSION OF LIDAR DATA AND AERIAL COLOR IMAGERY BASED ON BAYESIAN THEORY FOR URBAN AREA CLASSIFICATION

Directory of Open Access Journals (Sweden)

H. Rastiveis

2015-12-01

Full Text Available Airborne Light Detection and Ranging (LiDAR generates high-density 3D point clouds to provide a comprehensive information from object surfaces. Combining this data with aerial/satellite imagery is quite promising for improving land cover classification. In this study, fusion of LiDAR data and aerial imagery based on Bayesian theory in a three-level fusion algorithm is presented. In the first level, pixel-level fusion, the proper descriptors for both LiDAR and image data are extracted. In the next level of fusion, feature-level, using extracted features the area are classified into six classes of “Buildings”, “Trees”, “Asphalt Roads”, “Concrete roads”, “Grass” and “Cars” using Naïve Bayes classification algorithm. This classification is performed in three different strategies: (1 using merely LiDAR data, (2 using merely image data, and (3 using all extracted features from LiDAR and image. The results of three classifiers are integrated in the last phase, decision level fusion, based on Naïve Bayes algorithm. To evaluate the proposed algorithm, a high resolution color orthophoto and LiDAR data over the urban areas of Zeebruges, Belgium were applied. Obtained results from the decision level fusion phase revealed an improvement in overall accuracy and kappa coefficient.

Field evaluation of remote wind sensing technologies: Shore-based and buoy mounted LIDAR systems

Energy Technology Data Exchange (ETDEWEB)

Herrington, Thomas [Stevens Inst. of Technology, Hoboken, NJ (United States)

2017-11-03

the evaluation of LIDAR-based wind measurement systems to validate the accuracy of remotely measured wind data in marine applications. Specifically, the test-bed will be utilized to systematically evaluate the capability of emerging scanning LIDAR and buoy mounted vertically profiling LIDAR by: (1) Evaluating a fixed scanning LIDAR against land-based 50 and 60 meter high meteorological masts fitted with research quality cup-vane and/or sonic anemometers; (2) Evaluating a buoy mounted vertically profiling LIDAR fixed on land and floating in a sheltered bay against a co-located 60 meter high meteorological mast fitted with a research quality cup-vane and/or sonic anemometers and the fixed scanning LIDAR; and (3) Offshore field evaluation of both LIDAR platforms through a comparison of the fixed scanning LIDAR data and data obtained by the buoy mounted LIDAR located 10 miles offshore. The proposed research will systematically validate Light Detection and Ranging (LIDAR) based wind measurement systems and assess the temporal and spatial variability of the offshore wind resource in the Mid-Atlantic east of New Jersey. The goal of the proposed project is to address the technical and commercial challenges of the offshore wind energy industry by validating and assessing cost-effective, over ocean wind resource characterization technologies. The objective is to systematically evaluate the capability of both scanning and vertically profiling LIDARs to accurately measure 3D wind fields through comparison with fixed met masts and intercomparison among LIDAR platforms. Once validated, data collected by both buoy mounted vertically profiling LIDARs and shore-based, pulsed horizontally scanning LIDARs can be used to accurately assess offshore wind resources and to quantify the spatial and temporal variability in the offshore wind fields. One of the fundamental research questions to be addressed in phase 1 is the assessment of various measurement and data processing schemes to

Development of ground-based lidars for measuring H2O and O3 profiles in the troposphere

Science.gov (United States)

Sakai, T.; Abo, M.; Pham, L. H. P.; Uchino, O.; Nagai, T.; Izumi, T.; Morino, I.; Ohyama, H.; Nagasawa, C.

2015-12-01

Water vapor is the strongest natural greenhouse gas and a highly variable atmospheric constituent. It plays an important role of the energy transfer and the meteorological phenomena such as evaporation, vapor transport, cloud formation, and rainfall in the troposphere. Ozone is an important air pollutant that at high concentrations impacts on human health and ecosystem including crops and also a greenhouse gas that plays an important role in climate change. Aerosol is an important climate parameter and also one of the largest error sources (causes) in retrieval from solar reflected short wavelength infrared radiances observed with greenhouse gases observing satellites such as the GOSAT and OCO-2. Therefore, we have been developing ground-based differential absorption lidars (DIALs) for measuring the tropospheric water vapor, ozone and aerosols.The water vapor DIAL employs two distributed Bragg reflector (DBR) lasers operating at 829.054 nm for the online wavelength and 829.124 nm for the offline wavelength with tapered semiconductor optical amplifier (TSOA) in a master oscillator power amplifier (MOPA) configuration, and utilizes pseudorandom coded pulse modulation technique.It has started to measure the vertical distribution of lower tropospheric water vapor in order to improve accuracy and lead time of numerical weather prediction of local heavy rainfalls. Well-organized and regularly spaced convective cells of which vertical thickness were 200 m and the periods were 10 minutes were observed in the top of planetary boundary layer at 2.5 km altitude over Tokyo (35.66°N, 139.37°E) on 22 June 2015.The ozone DIAL employs a Nd:YAG laser and a 2 m long Raman cell filled with CO2 gas which generates four Stokes lines (276.2, 287.2, 299.1, and 312.0 nm) of stimulated Raman scattering, and two receiving telescopes with diameters of 49 and 10 cm.It has started to measure the vertical distributions of the tropospheric ozone as well as aerosols and thin cirrus cloud in

A fast approach to generate large-scale topographic maps based on new Chinese vehicle-borne Lidar system

International Nuclear Information System (INIS)

Youmei, Han; Bogang, Yang

2014-01-01

Large -scale topographic maps are important basic information for city and regional planning and management. Traditional large- scale mapping methods are mostly based on artificial mapping and photogrammetry. The traditional mapping method is inefficient and limited by the environments. While the photogrammetry methods(such as low-altitude aerial mapping) is an economical and effective way to map wide and regulate range of large scale topographic map but doesn't work well in the small area due to the high cost of manpower and resources. Recent years, the vehicle-borne LIDAR technology has a rapid development, and its application in surveying and mapping is becoming a new topic. The main objective of this investigation is to explore the potential of vehicle-borne LIDAR technology to be used to fast mapping large scale topographic maps based on new Chinese vehicle-borne LIDAR system. It studied how to use the new Chinese vehicle-borne LIDAR system measurement technology to map large scale topographic maps. After the field data capture, it can be mapped in the office based on the LIDAR data (point cloud) by software which programmed by ourselves. In addition, the detailed process and accuracy analysis were proposed by an actual case. The result show that this new technology provides a new fast method to generate large scale topographic maps, which is high efficient and accuracy compared to traditional methods

Self-Tuning Method for Increased Obstacle Detection Reliability Based on Internet of Things LiDAR Sensor Models.

Science.gov (United States)

Castaño, Fernando; Beruvides, Gerardo; Villalonga, Alberto; Haber, Rodolfo E

2018-05-10

On-chip LiDAR sensors for vehicle collision avoidance are a rapidly expanding area of research and development. The assessment of reliable obstacle detection using data collected by LiDAR sensors has become a key issue that the scientific community is actively exploring. The design of a self-tuning methodology and its implementation are presented in this paper, to maximize the reliability of LiDAR sensors network for obstacle detection in the 'Internet of Things' (IoT) mobility scenarios. The Webots Automobile 3D simulation tool for emulating sensor interaction in complex driving environments is selected in order to achieve that objective. Furthermore, a model-based framework is defined that employs a point-cloud clustering technique, and an error-based prediction model library that is composed of a multilayer perceptron neural network, and k-nearest neighbors and linear regression models. Finally, a reinforcement learning technique, specifically a Q-learning method, is implemented to determine the number of LiDAR sensors that are required to increase sensor reliability for obstacle localization tasks. In addition, a IoT driving assistance user scenario, connecting a five LiDAR sensor network is designed and implemented to validate the accuracy of the computational intelligence-based framework. The results demonstrated that the self-tuning method is an appropriate strategy to increase the reliability of the sensor network while minimizing detection thresholds.

LiDAR based prediction of forest biomass using hierarchical models with spatially varying coefficients

Science.gov (United States)

Babcock, Chad; Finley, Andrew O.; Bradford, John B.; Kolka, Randall K.; Birdsey, Richard A.; Ryan, Michael G.

2015-01-01

Many studies and production inventory systems have shown the utility of coupling covariates derived from Light Detection and Ranging (LiDAR) data with forest variables measured on georeferenced inventory plots through regression models. The objective of this study was to propose and assess the use of a Bayesian hierarchical modeling framework that accommodates both residual spatial dependence and non-stationarity of model covariates through the introduction of spatial random effects. We explored this objective using four forest inventory datasets that are part of the North American Carbon Program, each comprising point-referenced measures of above-ground forest biomass and discrete LiDAR. For each dataset, we considered at least five regression model specifications of varying complexity. Models were assessed based on goodness of fit criteria and predictive performance using a 10-fold cross-validation procedure. Results showed that the addition of spatial random effects to the regression model intercept improved fit and predictive performance in the presence of substantial residual spatial dependence. Additionally, in some cases, allowing either some or all regression slope parameters to vary spatially, via the addition of spatial random effects, further improved model fit and predictive performance. In other instances, models showed improved fit but decreased predictive performance—indicating over-fitting and underscoring the need for cross-validation to assess predictive ability. The proposed Bayesian modeling framework provided access to pixel-level posterior predictive distributions that were useful for uncertainty mapping, diagnosing spatial extrapolation issues, revealing missing model covariates, and discovering locally significant parameters.

2002 Maryland Department of Natural Resources LiDAR: Worcester County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Light Detection and Ranging (LiDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

LESTO: an Open Source GIS-based toolbox for LiDAR analysis

Science.gov (United States)

Franceschi, Silvia; Antonello, Andrea; Tonon, Giustino

2015-04-01

During the last five years different research institutes and private companies stared to implement new algorithms to analyze and extract features from LiDAR data but only a few of them also created a public available software. In the field of forestry there are different examples of software that can be used to extract the vegetation parameters from LiDAR data, unfortunately most of them are closed source (even if free), which means that the source code is not shared with the public for anyone to look at or make changes to. In 2014 we started the development of the library LESTO (LiDAR Empowered Sciences Toolbox Opensource): a set of modules for the analysis of LiDAR point cloud with an Open Source approach with the aim of improving the performance of the extraction of the volume of biomass and other vegetation parameters on large areas for mixed forest structures. LESTO contains a set of modules for data handling and analysis implemented within the JGrassTools spatial processing library. The main subsections are dedicated to 1) preprocessing of LiDAR raw data mainly in LAS format (utilities and filtering); 2) creation of raster derived products; 3) flight-lines identification and normalization of the intensity values; 4) tools for extraction of vegetation and buildings. The core of the LESTO library is the extraction of the vegetation parameters. We decided to follow the single tree based approach starting with the implementation of some of the most used algorithms in literature. These have been tweaked and applied on LiDAR derived raster datasets (DTM, DSM) as well as point clouds of raw data. The methods range between the simple extraction of tops and crowns from local maxima, the region growing method, the watershed method and individual tree segmentation on point clouds. The validation procedure consists in finding the matching between field and LiDAR-derived measurements at individual tree and plot level. An automatic validation procedure has been developed

LIDAR-based characterization and conservation of the first theropod dinosaur trackways from Arkansas, USA.

Directory of Open Access Journals (Sweden)

Brian F Platt

Full Text Available LIDAR-based analyses of the first theropod dinosaur trackways known from the state of Arkansas, USA are reported. The trackways were found on a limestone bedding plane in the Albian De Queen Formation in an active gypsum quarry. Because limited access precluded thorough field study, fieldwork focused on preserving the entire site digitally with ground-based LIDAR, and detailed measurements were later taken digitally from point cloud data. The site contains eight tridactyl trackways associated with sauropod trackways and numerous isolated tracks. Although there appear to be two different tridactyl morphotypes, we show that the tracks are all likely from a single species of trackmaker. We apply a simple method of estimating substrate consistency by comparing the differences between true track dimensions and apparent track dimensions. The tridactyl tracks at the southern end of the site are preserved with significantly greater differences in true vs. apparent dimensions and are shallower than the rest of the tridactyl tracks at the site, which we interpret as the result of outward expansion of the soft tissues of the foot upon contact with a firm substrate. We interpret the firm substrate as having high bulk density and high shear strength, which also explain associated manus-only sauropod tracks. We show that the tridactyl tracks are likely from theropod trackmakers and that footprint lengths, trackway paces, stride lengths, and pace angulations of the De Queen trackways are statistically indistinguishable from equivalent measurements of theropod trackways in the Glen Rose Formation. The Glen Rose tracks are attributed to the large-bodied theropod, Acrocanthosaurus and we likewise attribute the De Queen tracks to Acrocanthosaurus, which is known from skeletal remains in temporally equivalent units and from the mine itself.

LIDAR-based characterization and conservation of the first theropod dinosaur trackways from Arkansas, USA.

Science.gov (United States)

Platt, Brian F; Suarez, Celina A; Boss, Stephen K; Williamson, Malcolm; Cothren, Jackson; Kvamme, Jo Ann C

2018-01-01

LIDAR-based analyses of the first theropod dinosaur trackways known from the state of Arkansas, USA are reported. The trackways were found on a limestone bedding plane in the Albian De Queen Formation in an active gypsum quarry. Because limited access precluded thorough field study, fieldwork focused on preserving the entire site digitally with ground-based LIDAR, and detailed measurements were later taken digitally from point cloud data. The site contains eight tridactyl trackways associated with sauropod trackways and numerous isolated tracks. Although there appear to be two different tridactyl morphotypes, we show that the tracks are all likely from a single species of trackmaker. We apply a simple method of estimating substrate consistency by comparing the differences between true track dimensions and apparent track dimensions. The tridactyl tracks at the southern end of the site are preserved with significantly greater differences in true vs. apparent dimensions and are shallower than the rest of the tridactyl tracks at the site, which we interpret as the result of outward expansion of the soft tissues of the foot upon contact with a firm substrate. We interpret the firm substrate as having high bulk density and high shear strength, which also explain associated manus-only sauropod tracks. We show that the tridactyl tracks are likely from theropod trackmakers and that footprint lengths, trackway paces, stride lengths, and pace angulations of the De Queen trackways are statistically indistinguishable from equivalent measurements of theropod trackways in the Glen Rose Formation. The Glen Rose tracks are attributed to the large-bodied theropod, Acrocanthosaurus and we likewise attribute the De Queen tracks to Acrocanthosaurus, which is known from skeletal remains in temporally equivalent units and from the mine itself.

A LIDAR-Based Tree Canopy Characterization under Simulated Uneven Road Condition: Advance in Tree Orchard Canopy Profile Measurement

Directory of Open Access Journals (Sweden)

Yue Shen

2017-01-01

Full Text Available In real outdoor canopy profile detection, the accuracy of a LIDAR scanner to measure canopy structure is affected by a potentially uneven road condition. The level of error associated with attitude angles from undulations in the ground surface can be reduced by developing appropriate correction algorithm. This paper proposes an offline attitude angle offset correction algorithm based on a 3D affine coordinate transformation. The validity of the correction algorithm is verified by conducting an indoor experiment. The experiment was conducted on an especially designed canopy profile measurement platform. During the experiment, an artificial tree and a tree-shaped carved board were continuously scanned at constant laser scanner travel speed and detection distances under simulated bumpy road conditions. Acquired LIDAR laser scanner raw data was processed offline by exceptionally developed MATLAB program. The obtained results before and after correction method show that the single attitude angle offset correction method is able to correct the distorted data points in tree-shaped carved board profile measurement, with a relative error of 5%, while the compound attitude angle offset correction method is effective to reduce the error associated with compound attitude angle deviation from the ideal scanner pose, with relative error of 7%.

Turbulence estimation from a continuous-wave scanning lidar (SpinnerLidar)

DEFF Research Database (Denmark)

Barnhoorn, J.G.; Sjöholm, Mikael; Mikkelsen, Torben Krogh

2017-01-01

out, and 2) the mixing of velocity covariances from other components into the line-of-sight variance measurements. However, turbulence measurements based on upwind horizontal rotor plane scanning of the line-of-sight variance measurements combined with ensemble-averaged Doppler spectra width...... deviations averaged over 10-min sampling periods are compared. Lidar variances are inherently more prone to noise which always yields a positive bias. The 5.3 % higher turbulence level measured by the SpinnerLidar relative to the cup anemometer may equally well be attributed to truncation of turbulent...

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

Interrelationship of Cn2 & Eddy Dissipation rate based on Scintillometer and Doppler Lidar observations in complex terrain during the Perdigao Campaign 2017

Science.gov (United States)

Creegan, E. D.; Krishnamurthy, R.; Hocut, C. M.; Pattantyus, A.; Leo, L. S.; Wang, Y.; Fernando, H. J.; Bariteau, L.

2017-12-01

The Perdigao campaign is a joint EU/US science project designed to provide information on flow field(s) over complex terrain and through wind turbines at unprecedented high spatial and temporal resolution. The goal is to improve wind energy physics and overcome the current deficiencies of wind resource models. Topographically the Perdigao location is an expansion of the "double hill in crossflow", consisting of two parallel ridges along the NW-SE direction. The site was heavily instrumented with an array of towers (with multiple transects along the valley and across two ridges) and a large suite of ground based and aerial remote sensing platforms. On the outflow side of the NW ridge a scintillometer was emplaced with the line-of-sight (LOS) running adjacent to the towers comprising the NE transect from the ridgetop down to the base. Scanning lidars were placed at both ends of this LOS. Other instruments included a tethered lifting system (TLS), sodar, microwave radiometer, an energy budget flux tower and radiosonde releases. Scintillomoter data provides a quantitative measure of the intensity of optical turbulence, through the refractive index structure parameter, Cn2, where averaged Cn2 is often determined as a function of local differences in temperature, moisture, and wind velocity at discrete points. The refractive index structure parameter is also a function of the inner (dissipation) and outer (energy producing) turbulent scales. The scintillometer directly gives path averaged Cn2 and Eddy Dissipation rate along the LOS. Coplanar scans along the same path were synchronized using two scanning coherent Doppler lidars. Algorithms have been developed to estimate both eddy dissipation rate and Cn2 from Doppler lidar data effectively creating a new lidar data product. Additionally, from TLS measurements, Cn2 and dissipation rate are calculated using the high frequency spectra of the hot-wire sensor. In this work, measurements of Cn2 and Eddy Dissipation rate

Volumetric visualization of multiple-return LIDAR data: Using voxels

Science.gov (United States)

Stoker, Jason M.

2009-01-01

Elevation data are an important component in the visualization and analysis of geographic information. The creation and display of 3D models representing bare earth, vegetation, and surface structures have become a major focus of light detection and ranging (lidar) remote sensing research in the past few years. Lidar is an active sensor that records the distance, or range, of a laser usually fi red from an airplane, helicopter, or satellite. By converting the millions of 3D lidar returns from a system into bare ground, vegetation, or structural elevation information, extremely accurate, high-resolution elevation models can be derived and produced to visualize and quantify scenes in three dimensions. These data can be used to produce high-resolution bare-earth digital elevation models; quantitative estimates of vegetative features such as canopy height, canopy closure, and biomass; and models of urban areas such as building footprints and 3D city models.

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

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.

The ground based plan

International Nuclear Information System (INIS)

1989-01-01

The paper presents a report of ''The Ground Based Plan'' of the United Kingdom Science and Engineering Research Council. The ground based plan is a plan for research in astronomy and planetary science by ground based techniques. The contents of the report contains a description of:- the scientific objectives and technical requirements (the basis for the Plan), the present organisation and funding for the ground based programme, the Plan, the main scientific features and the further objectives of the Plan. (U.K.)

Space-Based CO2 Active Optical Remote Sensing using 2-μm Triple-Pulse IPDA Lidar

Science.gov (United States)

Singh, Upendra; Refaat, Tamer; Ismail, Syed; Petros, Mulugeta

2017-04-01

, current efforts are focused on developing an aircraft-based 2-μm triple-pulse IPDA lidar for independent and simultaneous monitoring of CO2 and water vapor (H2O). Triple-pulse IPDA design, development and integration is based on the knowledge gathered from the successful demonstration of the airborne CO2 2-μm double-pulse IPDA lidar. IPDA transmitter enhancements include generating high-energy (80 mJ) and high repetition rate (50Hz) three successive pulses using a single pump pulse. IPDA receiver enhancement include an advanced, low noise (1 fW/Hz1/2) MCT e-APD detection system for improved measurement sensitivity. In place of H2O sensing, the triple-pulse IPDA can be tuned to measure CO2 with two different weighting functions using two on-lines and a common off-line. Modeling of a space-based high-energy 2-µm triple-pulse IPDA lidar was conducted to demonstrate CO2 measurement capability and to evaluate random and systematic errors. Projected performance shows reference surface using US Standard atmospheric model. In addition, measurements can be optimized by tuning on-lines based upon ground target scenarios, environment and science objectives. With 10 MHz detection bandwidth, surface ranging with an uncertainty of <3 m can be achieved as demonstrated from earlier airborne flights.

Measurement of phase function of aerosol at different altitudes by CCD Lidar

Science.gov (United States)

Sun, Peiyu; Yuan, Ke'e.; Yang, Jie; Hu, Shunxing

2018-02-01

The aerosols near the ground are closely related to human health and climate change, the study on which has important significance. As we all know, the aerosol is inhomogeneous at different altitudes, of which the phase function is also different. In order to simplify the retrieval algorithm, it is usually assumed that the aerosol is uniform at different altitudes, which will bring measurement error. In this work, an experimental approach is demonstrated to measure the scattering phase function of atmospheric aerosol particles at different heights by CCD lidar system, which could solve the problem of the traditional CCD lidar system in assumption of phase function. The phase functions obtained by the new experimental approach are used to retrieve the aerosol extinction coefficient profiles. By comparison of the aerosol extinction coefficient retrieved by Mie-scattering aerosol lidar and CCD lidar at night, the reliability of new experimental approach is verified.

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

Accuracy Assessment of Lidar-Derived Digital Terrain Model (dtm) with Different Slope and Canopy Cover in Tropical Forest Region

Science.gov (United States)

Salleh, M. R. M.; Ismail, Z.; Rahman, M. Z. A.

2015-10-01

Airborne Light Detection and Ranging (LiDAR) technology has been widely used recent years especially in generating high accuracy of Digital Terrain Model (DTM). High density and good quality of airborne LiDAR data promises a high quality of DTM. This study focussing on the analysing the error associated with the density of vegetation cover (canopy cover) and terrain slope in a LiDAR derived-DTM value in a tropical forest environment in Bentong, State of Pahang, Malaysia. Airborne LiDAR data were collected can be consider as low density captured by Reigl system mounted on an aircraft. The ground filtering procedure use adaptive triangulation irregular network (ATIN) algorithm technique in producing ground points. Next, the ground control points (GCPs) used in generating the reference DTM and these DTM was used for slope classification and the point clouds belong to non-ground are then used in determining the relative percentage of canopy cover. The results show that terrain slope has high correlation for both study area (0.993 and 0.870) with the RMSE of the LiDAR-derived DTM. This is similar to canopy cover where high value of correlation (0.989 and 0.924) obtained. This indicates that the accuracy of airborne LiDAR-derived DTM is significantly affected by terrain slope and canopy caver of study area.

ACCURACY ASSESSMENT OF LIDAR-DERIVED DIGITAL TERRAIN MODEL (DTM WITH DIFFERENT SLOPE AND CANOPY COVER IN TROPICAL FOREST REGION

Directory of Open Access Journals (Sweden)

M. R. M. Salleh

2015-10-01

Full Text Available Airborne Light Detection and Ranging (LiDAR technology has been widely used recent years especially in generating high accuracy of Digital Terrain Model (DTM. High density and good quality of airborne LiDAR data promises a high quality of DTM. This study focussing on the analysing the error associated with the density of vegetation cover (canopy cover and terrain slope in a LiDAR derived-DTM value in a tropical forest environment in Bentong, State of Pahang, Malaysia. Airborne LiDAR data were collected can be consider as low density captured by Reigl system mounted on an aircraft. The ground filtering procedure use adaptive triangulation irregular network (ATIN algorithm technique in producing ground points. Next, the ground control points (GCPs used in generating the reference DTM and these DTM was used for slope classification and the point clouds belong to non-ground are then used in determining the relative percentage of canopy cover. The results show that terrain slope has high correlation for both study area (0.993 and 0.870 with the RMSE of the LiDAR-derived DTM. This is similar to canopy cover where high value of correlation (0.989 and 0.924 obtained. This indicates that the accuracy of airborne LiDAR-derived DTM is significantly affected by terrain slope and canopy caver of study area.

First Simultaneous and Common-Volume Lidar Observations of Na and Fe Metals, Temperatures, and Vertical Winds in Antarctica

Science.gov (United States)

Chu, X.

2017-12-01

A new STAR Na Doppler lidar will be installed to Arrival Heights near McMurdo Station, Antarctica in October 2017. This new lidar will be operated next to an existing Fe Boltzmann lidar to make simultaneous and common-volume measurements of metal Na and Fe layers, neutral temperatures, and vertical winds in the mesosphere and thermosphere, up to nearly 200 km. These measurements will be used to study a variety of science topics, e.g., the meteoric metal layers, wave dynamics, polar mesospheric clouds, constituent and heat fluxes, and cosmic dust. The discoveries of thermospheric neutral Fe layers and persistent gravity waves by the Fe Boltzmann lidar observations has opened a new door to explore the space-atmosphere interactions with ground-based instruments, especially in the least understood but crucially important altitude range of 100-200 km. These neutral metal layers provide excellent tracers for modern resonance lidars to measure the neutral wind and temperature directly. Even more exciting, the neutral metal layers in the thermosphere provide a natural laboratory to test our fundamental understandings of the atmosphere-ionosphere-magnetosphere coupling and processes. This paper will report the first summer results from the simultaneous Na and Fe lidar observations from Antarctica, and highlight important discoveries made by the Fe lidar during its first seven years of campaign at McMurdo. A thermosphere-ionosphere Fe/Fe+ (TIFe) model will be introduced to explain the TIFe layers in Antarctica.

COMPREHENSIVE COMPARISON OF TWO IMAGE-BASED POINT CLOUDS FROM AERIAL PHOTOS WITH AIRBORNE LIDAR FOR LARGE-SCALE MAPPING

Directory of Open Access Journals (Sweden)

E. Widyaningrum

2017-09-01

Full Text Available The integration of computer vision and photogrammetry to generate three-dimensional (3D information from images has contributed to a wider use of point clouds, for mapping purposes. Large-scale topographic map production requires 3D data with high precision and accuracy to represent the real conditions of the earth surface. Apart from LiDAR point clouds, the image-based matching is also believed to have the ability to generate reliable and detailed point clouds from multiple-view images. In order to examine and analyze possible fusion of LiDAR and image-based matching for large-scale detailed mapping purposes, point clouds are generated by Semi Global Matching (SGM and by Structure from Motion (SfM. In order to conduct comprehensive and fair comparison, this study uses aerial photos and LiDAR data that were acquired at the same time. Qualitative and quantitative assessments have been applied to evaluate LiDAR and image-matching point clouds data in terms of visualization, geometric accuracy, and classification result. The comparison results conclude that LiDAR is the best data for large-scale mapping.

2012 Post-Superstorm Sandy Lidar Elevation Data, USACE National Coastal Mapping Program

Data.gov (United States)

Army Corps of Engineers, Department of the Army, Department of Defense — These files contain classified topographic and bathymetric lidar data as unclassified valid topographic data (1), and valid topographic data classified as ground...

A novel EMD selecting thresholding method based on multiple iteration for denoising LIDAR signal

Science.gov (United States)

Li, Meng; Jiang, Li-hui; Xiong, Xing-long

2015-06-01

Empirical mode decomposition (EMD) approach has been believed to be potentially useful for processing the nonlinear and non-stationary LIDAR signals. To shed further light on its performance, we proposed the EMD selecting thresholding method based on multiple iteration, which essentially acts as a development of EMD interval thresholding (EMD-IT), and randomly alters the samples of noisy parts of all the corrupted intrinsic mode functions to generate a better effect of iteration. Simulations on both synthetic signals and LIDAR signals from real world support this method.

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.

2004 Anne Arundel, Charles, Howard & St. Mary's Counties LiDAR Mapping

Data.gov (United States)

Federal Emergency Management Agency, Department of Homeland Security — Light Detection and Ranging (LIDAR) is a method of locating objects on the ground using aerial-borne equipment. It is similar to RADAR or SONAR in that the two-way...

Retrieval of Aerosol Components Using Multi-Wavelength Mie-Raman Lidar and Comparison with Ground Aerosol Sampling

Directory of Open Access Journals (Sweden)

Yukari Hara

2018-06-01

Full Text Available We verified an algorithm using multi-wavelength Mie-Raman lidar (MMRL observations to retrieve four aerosol components (black carbon (BC, sea salt (SS, air pollution (AP, and mineral dust (DS with in-situ aerosol measurements, and determined the seasonal variation of aerosol components in Fukuoka, in the western region of Japan. PM2.5, PM10, and mass concentrations of BC and SS components are derived from in-situ measurements. MMRL provides the aerosol extinction coefficient (α, particle linear depolarization ratio (δ, backscatter coefficient (β, and lidar ratio (S at 355 and 532 nm, and the attenuated backscatter coefficient (βatt at 1064 nm. We retrieved vertical distributions of extinction coefficients at 532 nm for four aerosol components (BC, SS, AP, and DS using 1α532 + 1β532 + 1βatt,1064 + 1δ532 data of MMRL. The retrieved extinction coefficients of the four aerosol components at 532 nm were converted to mass concentrations using the theoretical computed conversion factor assuming the prescribed size distribution, particle shape, and refractive index for each aerosol component. MMRL and in-situ measurements confirmed that seasonal variation of aerosol optical properties was affected by internal/external mixing of various aerosol components, in addition to hygroscopic growth of water-soluble aerosols. MMRL overestimates BC mass concentration compared to in-situ observation using the pure BC model. This overestimation was reduced drastically by introducing the internal mixture model of BC and water-soluble substances (Core-Gray Shell (CGS model. This result suggests that considering the internal mixture of BC and water-soluble substances is essential for evaluating BC mass concentration in this area. Systematic overestimation of BC mass concentration was found during summer, even when we applied the CGS model. The observational facts based on in-situ and MMRL measurements suggested that misclassification of AP as CGS particles was

Space-borne clear air lidar measurements in the presence of broken cloud

Directory of Open Access Journals (Sweden)

I. Astin

Full Text Available A number of proposed lidar systems, such as ESA’s AEOLUS (formerly ADM and DIAL missions (e.g. WALES are to make use of lidar returns in clear air. However, on average, two-thirds of the globe is covered in cloud. Hence, there is a strong likelihood that data from these instruments may be contaminated by cloud. Similarly, optically thick cloud may not be penetrated by a lidar pulse, resulting in unobservable regions that are overshadowed by the cloud. To address this, it is suggested, for example, in AEOLUS, that a number of consecutive short sections of lidar data (between 1 and 3.5 km in length be tested for cloud contamination or for overshadowing and only those that are unaffected by cloud be used to derive atmospheric profiles. The prob-ability of obtaining profiles to near ground level using this technique is investigated both analytically and using UV air-borne lidar data recorded during the CLARE’98 campaign. These data were measured in the presence of broken cloud on a number of flights over southern England over a four-day period and were chosen because the lidar used has the same wavelength, footprint and could match the along-track spacing of the proposed AEOLUS lidar.

Key words. Atmospheric composition and structure (aerosols and particles Meteorology and atmospheric dynamics (instruments and techniques; general circulation

Extinction effects of atmospheric compositions on return signals of space-based lidar from numerical simulation

Science.gov (United States)

Yao, Lilin; Wang, Fu; Min, Min; Zhang, Ying; Guo, Jianping; Yu, Xiao; Chen, Binglong; Zhao, Yiming; Wang, Lidong

2018-05-01

The atmospheric composition induced extinction effect on return signals of space-based lidar remains incomprehensively understood, especially around 355 nm and 2051 nm channels. Here we simulated the extinction effects of atmospheric gases (e.g., H2O, CO2, and O3) and six types of aerosols (clean continental, clean marine, dust, polluted continental, polluted dust, and smoke) on return signals of space-based lidar system at 355 nm, 532 nm, 1064 nm, and 2051 nm channels, based on a robust lidar return signal simulator in combination with radiative transfer model (LBLRTM). Results show significant Rayleigh (molecular) scattering effects in the return signals at 355 nm and 532 nm channels, which markedly decays with increases in wavelength. The spectral transmittance of CO2 is nearly 0, yet the transmittance of H2O is approximately 100% at 2051 nm, which verifies this 2051 nm channel is suitable for CO2 retrieval. The spectral transmittance also reveals another possible window for CO2 and H2O detection at 2051.6 nm, since their transmittance both near 0.5. Moreover the corresponding Doppler return signals at 2051.6 nm channel can be used to retrieve wind field. Thus we suggest 2051 nm channel may better be centered at 2051.6 nm. Using the threshold for the signal-to-noise ratio (SNR) of return signals, the detection ranges for three representative distribution scenarios for the six types of aerosols at four typical lidar channels are determined. The results clearly show that high SNR values can be seen ubiquitously in the atmosphere ranging from the height of aerosol layer top to 25 km at 355 nm, and can been found at 2051.6 nm in the lower troposphere that highly depends on aerosol distribution scenario in the vertical. This indicates that the Doppler space-based lidar system with a double-channel joint detection mode is able to retrieve atmospheric wind field or profile from 0 to 25 km.

Portable and Airborne Small Footprint LiDAR: Forest Canopy Structure Estimation of Fire Managed Plots

Directory of Open Access Journals (Sweden)

Claudia M.C.S. Listopad

2011-06-01

Full Text Available This study used an affordable ground-based portable LiDAR system to provide an understanding of the structural differences between old-growth and secondary-growth Southeastern pine. It provided insight into the strengths and weaknesses in the structural determination of portable systems in contrast to airborne LiDAR systems. Portable LiDAR height profiles and derived metrics and indices (e.g., canopy cover, canopy height were compared among plots with different fire frequency and fire season treatments within secondary forest and old growth plots. The treatments consisted of transitional season fire with four different return intervals: 1-yr, 2-yr, 3-yr fire return intervals, and fire suppressed plots. The remaining secondary plots were treated using a 2-yr late dormant season fire cycle. The old growth plots were treated using a 2-yr growing season fire cycle. Airborne and portable LiDAR derived canopy cover were consistent throughout the plots, with significantly higher canopy cover values found in 3-yr and fire suppressed plots. Portable LiDAR height profile and metrics presented a higher sensitivity in capturing subcanopy elements than the airborne system, particularly in dense canopy plots. The 3-dimensional structures of the secondary plots with varying fire return intervals were dramatically different to old-growth plots, where a symmetrical distribution with clear recruitment was visible. Portable LiDAR, even though limited to finer spatial scales and specific biases, is a low-cost investment with clear value for the management of forest canopy structure.

Towards 4d Virtual City Reconstruction from LIDAR Point Cloud Sequences

Science.gov (United States)

Józsa, O.; Börcs, A.; Benedek, C.

2013-05-01

In this paper we propose a joint approach on virtual city reconstruction and dynamic scene analysis based on point cloud sequences of a single car-mounted Rotating Multi-Beam (RMB) Lidar sensor. The aim of the addressed work is to create 4D spatio-temporal models of large dynamic urban scenes containing various moving and static objects. Standalone RMB Lidar devices have been frequently applied in robot navigation tasks and proved to be efficient in moving object detection and recognition. However, they have not been widely exploited yet for geometric approximation of ground surfaces and building facades due to the sparseness and inhomogeneous density of the individual point cloud scans. In our approach we propose an automatic registration method of the consecutive scans without any additional sensor information such as IMU, and introduce a process for simultaneously extracting reconstructed surfaces, motion information and objects from the registered dense point cloud completed with point time stamp information.

Forest Biomass Mapping From Lidar and Radar Synergies

Science.gov (United States)

Sun, Guoqing; Ranson, K. Jon; Guo, Z.; Zhang, Z.; Montesano, P.; Kimes, D.

2011-01-01

The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R(exp 2) of 0.71 and RMSE of 31.33 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI Mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R2 of 0.63-0.71, RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar- SAR synergy 63 was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the

Comparisons of Simultaneously Acquired Airborne Sfm Photogrammetry and Lidar

Science.gov (United States)

Larsen, C. F.

2014-12-01

Digital elevation models (DEMs) created using images from a consumer DSLR camera are compared against simultaneously acquired LiDAR on a number of airborne mapping projects across Alaska, California and Utah. The aircraft used is a Cessna 180, and is equipped with the University of Alaska Geophysical Institute (UAF-GI) scanning airborne LiDAR system. This LiDAR is the same as described in Johnson et al, 2013, and is the principal instrument used for NASA's Operation IceBridge flights in Alaska. The system has been in extensive use since 2009, and is particularly well characterized with dozens of calibration flights and a careful program of boresight angle determination and monitoring. The UAF-GI LiDAR has a precision of +/- 8 cm and accuracy of +/- 15 cm. The photogrammetry DEM simultaneously acquired with the LiDAR relies on precise shutter timing using an event marker input to the IMU associated with the LiDAR system. The photo positions are derived from the fully coupled GPS/IMU processing, which samples at 100 Hz and is able to directly calculate the antenna to image plane offset displacements from the full orientation data. This use of the GPS/IMU solution means that both the LiDAR and Cessna 180 photogrammetry DEM share trajectory input data, however no orientation data nor ground control is used for the photorammetry processing. The photogrammetry DEMs are overlaid on the LiDAR point cloud and analyzed for horizontal shifts or warps relative to the LiDAR. No warping or horizontal shifts have been detectable for a number of photogrammetry DEMs. Vertical offsets range from +/- 30 cm, with a typical standard deviation about that mean of 10 cm or better. LiDAR and photogrammetry function inherently differently over trees and brush, and direct comparisons between the two methods show much larger differences over vegetated areas. Finally, the differences in flight patterns associated with the two methods will be discussed, highlighting the photogrammetry

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...

Object-Based Canopy Gap Segmentation and Classification: Quantifying the Pros and Cons of Integrating Optical and LiDAR Data

Directory of Open Access Journals (Sweden)

Jian Yang

2015-11-01

Full Text Available Delineating canopy gaps and quantifying gap characteristics (e.g., size, shape, and dynamics are essential for understanding regeneration dynamics and understory species diversity in structurally complex forests. Both high spatial resolution optical and light detection and ranging (LiDAR remote sensing data have been used to identify canopy gaps through object-based image analysis, but few studies have quantified the pros and cons of integrating optical and LiDAR for image segmentation and classification. In this study, we investigate whether the synergistic use of optical and LiDAR data improves segmentation quality and classification accuracy. The segmentation results indicate that the LiDAR-based segmentation best delineates canopy gaps, compared to segmentation with optical data alone, and even the integration of optical and LiDAR data. In contrast, the synergistic use of two datasets provides higher classification accuracy than the independent use of optical or LiDAR (overall accuracy of 80.28% ± 6.16% vs. 68.54% ± 9.03% and 64.51% ± 11.32%, separately. High correlations between segmentation quality and object-based classification accuracy indicate that classification accuracy is largely dependent on segmentation quality in the selected experimental area. The outcome of this study provides valuable insights of the usefulness of data integration into segmentation and classification not only for canopy gap identification but also for many other object-based applications.

A METHOD OF EXTRACTING SHORELINE BASED ON SEMANTIC INFORMATION USING DUAL-LENGTH LiDAR DATA

Directory of Open Access Journals (Sweden)

C. Yao

2017-09-01

Full Text Available Shoreline is a spatial varying separation between water and land. By utilizing dual-wavelength LiDAR point data together with semantic information that shoreline often appears beyond water surface profile and is observable on the beach, the paper generates the shoreline and the details are as follows: (1 Gain the water surface profile: first we obtain water surface by roughly selecting water points based on several features of water body, then apply least square fitting method to get the whole water trend surface. Then we get the ground surface connecting the under -water surface by both TIN progressive filtering method and surface interpolation method. After that, we have two fitting surfaces intersected to get water surface profile of the island. (2 Gain the sandy beach: we grid all points and select the water surface profile grids points as seeds, then extract sandy beach points based on eight-neighborhood method and features, then we get all sandy beaches. (3 Get the island shoreline: first we get the sandy beach shoreline based on intensity information, then we get a threshold value to distinguish wet area and dry area, therefore we get the shoreline of several sandy beaches. In some extent, the shoreline has the same height values within a small area, by using all the sandy shoreline points to fit a plane P, and the intersection line of the ground surface and the shoreline plane P can be regarded as the island shoreline. By comparing with the surveying shoreline, the results show that the proposed method can successfully extract shoreline.

Water vapor differential absorption lidar development and evaluation

Science.gov (United States)

Browell, E. V.; Wilkerson, T. D.; Mcllrath, T. J.

1979-01-01

A ground-based differential absorption lidar (DIAL) system is described which has been developed for vertical range-resolved measurements of water vapor. The laser transmitter consists of a ruby-pumped dye laser, which is operated on a water vapor absorption line at 724.372 nm. Part of the ruby laser output is transmitted simultaneously with the dye laser output to determine atmospheric scattering and attenuation characteristics. The dye and ruby laser backscattered light is collected by a 0.5-m diam telescope, optically separated in the receiver package, and independently detected using photomultiplier tubes. Measurements of vertical water vapor concentration profiles using the DIAL system at night are discussed, and comparisons are made between the water vapor DIAL measurements and data obtained from locally launched rawinsondes. Agreement between these measurements was found to be within the uncertainty of the rawinsonde data to an altitude of 3 km. Theoretical simulations of this measurement were found to give reasonably accurate predictions of the random error of the DIAL measurements. Confidence in these calculations will permit the design of aircraft and Shuttle DIAL systems and experiments using simulation results as the basis for defining lidar system performance requirements

The evolution of mapping habitat for northern spotted owls (Strix occidentalis caurina): A comparison of photo-interpreted, Landsat-based, and lidar-based habitat maps

Science.gov (United States)

Ackers, Steven H.; Davis, Raymond J.; Olsen, K.; Dugger, Catherine

2015-01-01

Wildlife habitat mapping has evolved at a rapid pace over the last few decades. Beginning with simple, often subjective, hand-drawn maps, habitat mapping now involves complex species distribution models (SDMs) using mapped predictor variables derived from remotely sensed data. For species that inhabit large geographic areas, remote sensing technology is often essential for producing range wide maps. Habitat monitoring for northern spotted owls (Strix occidentalis caurina), whose geographic covers about 23 million ha, is based on SDMs that use Landsat Thematic Mapper imagery to create forest vegetation data layers using gradient nearest neighbor (GNN) methods. Vegetation data layers derived from GNN are modeled relationships between forest inventory plot data, climate and topographic data, and the spectral signatures acquired by the satellite. When used as predictor variables for SDMs, there is some transference of the GNN modeling error to the final habitat map.Recent increases in the use of light detection and ranging (lidar) data, coupled with the need to produce spatially accurate and detailed forest vegetation maps have spurred interest in its use for SDMs and habitat mapping. Instead of modeling predictor variables from remotely sensed spectral data, lidar provides direct measurements of vegetation height for use in SDMs. We expect a SDM habitat map produced from directly measured predictor variables to be more accurate than one produced from modeled predictors.We used maximum entropy (Maxent) SDM modeling software to compare predictive performance and estimates of habitat area between Landsat-based and lidar-based northern spotted owl SDMs and habitat maps. We explored the differences and similarities between these maps, and to a pre-existing aerial photo-interpreted habitat map produced by local wildlife biologists. The lidar-based map had the highest predictive performance based on 10 bootstrapped replicate models (AUC = 0.809 ± 0.011), but the

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...

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.

BUILDING DAMAGE ASSESSMENT AFTER EARTHQUAKE USING POST-EVENT LiDAR DATA

Directory of Open Access Journals (Sweden)

H. Rastiveis

2015-12-01

Full Text Available After an earthquake, damage assessment plays an important role in leading rescue team to help people and decrease the number of mortality. Damage map is a map that demonstrates collapsed buildings with their degree of damage. With this map, finding destructive buildings can be quickly possible. In this paper, we propose an algorithm for automatic damage map generation after an earthquake using post-event LiDAR Data and pre-event vector map. The framework of the proposed approach has four main steps. To find the location of all buildings on LiDAR data, in the first step, LiDAR data and vector map are registered by using a few number of ground control points. Then, building layer, selected from vector map, are mapped on the LiDAR data and all pixels which belong to the buildings are extracted. After that, through a powerful classifier all the extracted pixels are classified into three classes of “debris”, “intact building” and “unclassified”. Since textural information make better difference between “debris” and “intact building” classes, different textural features are applied during the classification. After that, damage degree for each candidate building is estimated based on the relation between the numbers of pixels labelled as “debris” class to the whole building area. Calculating the damage degree for each candidate building, finally, building damage map is generated. To evaluate the ability proposed method in generating damage map, a data set from Port-au-Prince, Haiti’s capital after the 2010 Haiti earthquake was used. In this case, after calculating of all buildings in the test area using the proposed method, the results were compared to the damage degree which estimated through visual interpretation of post-event satellite image. Obtained results were proved the reliability of the proposed method in damage map generation using LiDAR data.

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...

Processing LiDAR Data to Predict Natural Hazards

Science.gov (United States)

Fairweather, Ian; Crabtree, Robert; Hager, Stacey

2008-01-01

ELF-Base and ELF-Hazards (wherein 'ELF' signifies 'Extract LiDAR Features' and 'LiDAR' signifies 'light detection and ranging') are developmental software modules for processing remote-sensing LiDAR data to identify past natural hazards (principally, landslides) and predict future ones. ELF-Base processes raw LiDAR data, including LiDAR intensity data that are often ignored in other software, to create digital terrain models (DTMs) and digital feature models (DFMs) with sub-meter accuracy. ELF-Hazards fuses raw LiDAR data, data from multispectral and hyperspectral optical images, and DTMs and DFMs generated by ELF-Base to generate hazard risk maps. Advanced algorithms in these software modules include line-enhancement and edge-detection algorithms, surface-characterization algorithms, and algorithms that implement innovative data-fusion techniques. The line-extraction and edge-detection algorithms enable users to locate such features as faults and landslide headwall scarps. Also implemented in this software are improved methodologies for identification and mapping of past landslide events by use of (1) accurate, ELF-derived surface characterizations and (2) three LiDAR/optical-data-fusion techniques: post-classification data fusion, maximum-likelihood estimation modeling, and hierarchical within-class discrimination. This software is expected to enable faster, more accurate forecasting of natural hazards than has previously been possible.

Small-scale Scheimpflug lidar for aerosol extinction coefficient and vertical atmospheric transmittance detection.

Science.gov (United States)

Sun, Guodong; Qin, Laian; Hou, Zaihong; Jing, Xu; He, Feng; Tan, Fengfu; Zhang, Silong

2018-03-19

In this paper, a new prototypical Scheimpflug lidar capable of detecting the aerosol extinction coefficient and vertical atmospheric transmittance at 1 km above the ground is described. The lidar system operates at 532 nm and can be used to detect aerosol extinction coefficients throughout an entire day. Then, the vertical atmospheric transmittance can be determined from the extinction coefficients with the equation of numerical integration in this area. CCD flat fielding of the image data is used to mitigate the effects of pixel sensitivity variation. An efficient method of two-dimensional wavelet transform according to a local threshold value has been proposed to reduce the Gaussian white noise in the lidar signal. Furthermore, a new iteration method of backscattering ratio based on genetic algorithm is presented to calculate the aerosol extinction coefficient and vertical atmospheric transmittance. Some simulations are performed to reduce the different levels of noise in the simulated signal in order to test the precision of the de-noising method and inversion algorithm. The simulation result shows that the root-mean-square errors of extinction coefficients are all less than 0.02 km -1 , and that the relative errors of the atmospheric transmittance between the model and inversion data are below 0.56% for all cases. The feasibility of the instrument and the inversion algorithm have also been verified by an optical experiment. The average relative errors of aerosol extinction coefficients between the Scheimpflug lidar and the conventional backscattering elastic lidar are 3.54% and 2.79% in the full overlap heights of two time points, respectively. This work opens up new possibilities of using a small-scale Scheimpflug lidar system for the remote sensing of atmospheric aerosols.

Power curve measurement with a nacelle mounted lidar

DEFF Research Database (Denmark)

Wagner, Rozenn; Friis Pedersen, Troels; Courtney, Michael

2014-01-01

is tested. A pulsed lidar prototype, measuring horizontally, was installed on the nacelle of a multi-megawatt wind turbine. A met mast with a top-mounted cup anemometer standing at two rotor diameters in front of the turbine was used as a reference. After a data-filtering step, the comparison of the 10 min......Nacelle-based lidars are an attractive alternative to conventional mast base reference wind instrumentation where the erection of a mast is expensive, for example offshore. In this paper, the use of this new technology for the specific application of wind turbine power performance measurement...... in wind speed measurements. A lower scatter in the power curve was observed for the lidar than for the mast. Since the lidar follows the turbine nacelle as it yaws, it always measures upwind. The wind measured by the lidar therefore shows a higher correlation with the turbine power fluctuations than...

UV Raman lidar measurements of relative humidity for the characterization of cirrus cloud microphysical properties

Directory of Open Access Journals (Sweden)

G. Masiello

2009-11-01

Full Text Available Raman lidar measurements performed in Potenza by the Raman lidar system BASIL in the presence of cirrus clouds are discussed. Measurements were performed on 6 September 2004 in the frame of the Italian phase of the EAQUATE Experiment.

The major feature of BASIL is represented by its capability to perform high-resolution and accurate measurements of atmospheric temperature and water vapour, and consequently relative humidity, both in daytime and night-time, based on the application of the rotational and vibrational Raman lidar techniques in the UV. BASIL is also capable to provide measurements of the particle backscatter and extinction coefficient, and consequently lidar ratio (at the time of these measurements, only at one wavelength, which are fundamental to infer geometrical and microphysical properties of clouds.

A case study is discussed in order to assess the capability of Raman lidars to measure humidity in presence of cirrus clouds, both below and inside the cloud. While air inside the cloud layers is observed to be always under-saturated with respect to water, both ice super-saturation and under-saturation conditions are found inside these clouds. Upper tropospheric moistening is observed below the lower cloud layer.

The synergic use of the data derived from the ground based Raman Lidar and of spectral radiances measured by the NAST-I Airborne Spectrometer allows the determination of the temporal evolution of the atmospheric cooling/heating rates due to the presence of the cirrus cloud.

Lidar measurements beneath the cirrus cloud layer have been interpreted using a 1-D cirrus cloud model with explicit microphysics. The 1-D simulations indicate that sedimentation-moistening has contributed significantly to the moist anomaly, but other mechanisms are also contributing. This result supports the hypothesis that the observed mid-tropospheric humidification is a real feature which is

2006 Texas Water Development Board (TWDB) Lidar: Northern Cameron and Willacy Counties

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Using a LH Systems ALS50 Light Detection And Ranging (LiDAR) system, standard density (1.4 meter ground sample distance) data were collected over areas in Northern...

Atmospheric CO2 Concentration Measurements with Clouds from an Airborne Lidar

Science.gov (United States)

Mao, J.; Abshire, J. B.; Kawa, S. R.; Riris, H.; Allan, G. R.; Hasselbrack, W. E.; Numata, K.; Chen, J. R.; Sun, X.; DiGangi, J. P.; Choi, Y.

2017-12-01

Globally distributed atmospheric CO2 concentration measurements with high precision, low bias and full seasonal sampling are crucial to advance carbon cycle sciences. However, two thirds of the Earth's surface is typically covered by clouds, and passive remote sensing approaches from space are limited to cloud-free scenes. NASA Goddard is developing a pulsed, integrated-path differential absorption (IPDA) lidar approach to measure atmospheric column CO2 concentrations, XCO2, from space as a candidate for NASA's ASCENDS mission. Measurements of time-resolved laser backscatter profiles from the atmosphere also allow this technique to estimate XCO2 and range to cloud tops in addition to those to the ground with precise knowledge of the photon path-length. We demonstrate this measurement capability using airborne lidar measurements from summer 2017 ASCENDS airborne science campaign in Alaska. We show retrievals of XCO2 to ground and to a variety of cloud tops. We will also demonstrate how the partial column XCO2 to cloud tops and cloud slicing approach help resolving vertical and horizontal gradient of CO2 in cloudy conditions. The XCO2 retrievals from the lidar are validated against in situ measurements and compared to the Goddard Parameterized Chemistry Transport Model (PCTM) simulations. Adding this measurement capability to the future lidar mission for XCO2 will provide full global and seasonal data coverage and some information about vertical structure of CO2. This unique facility is expected to benefit atmospheric transport process studies, carbon data assimilation in models, and global and regional carbon flux estimation.

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.

Cyclops: single-pixel imaging lidar system based on compressive sensing

Science.gov (United States)

Magalhães, F.; Correia, M. V.; Farahi, F.; Pereira do Carmo, J.; Araújo, F. M.

2017-11-01

Mars and the Moon are envisaged as major destinations of future space exploration missions in the upcoming decades. Imaging LIDARs are seen as a key enabling technology in the support of autonomous guidance, navigation and control operations, as they can provide very accurate, wide range, high-resolution distance measurements as required for the exploration missions. Imaging LIDARs can be used at critical stages of these exploration missions, such as descent and selection of safe landing sites, rendezvous and docking manoeuvres, or robotic surface navigation and exploration. Despite these devices have been commercially available and used for long in diverse metrology and ranging applications, their size, mass and power consumption are still far from being suitable and attractive for space exploratory missions. Here, we describe a compact Single-Pixel Imaging LIDAR System that is based on a compressive sensing technique. The application of the compressive codes to a DMD array enables compression of the spatial information, while the collection of timing histograms correlated to the pulsed laser source ensures image reconstruction at the ranged distances. Single-pixel cameras have been compared with raster scanning and array based counterparts in terms of noise performance, and proved to be superior. Since a single photodetector is used, a better SNR and higher reliability is expected in contrast with systems using large format photodetector arrays. Furthermore, the event of failure of one or more micromirror elements in the DMD does not prevent full reconstruction of the images. This brings additional robustness to the proposed 3D imaging LIDAR. The prototype that was implemented has three modes of operation. Range Finder: outputs the average distance between the system and the area of the target under illumination; Attitude Meter: provides the slope of the target surface based on distance measurements in three areas of the target; 3D Imager: produces 3D ranged

Macrophysical and optical properties of mid-latitude cirrus clouds over a semi-arid area observed by micro-pulse lidar

International Nuclear Information System (INIS)

Wang, Jin; Zhang, Lei; Huang, Jianping; Cao, Xianjie; Liu, Ruijin; Zhou, Bi; Wang, Hongbin; Huang, Zhongwei; Bi, Jianrong; Zhou, Tian; Zhang, Beidou; Wang, Tengjiao

2013-01-01

Macrophysical and optical characteristics of cirrus clouds were investigated at the Semi-Arid Climate Observatory and Laboratory (SACOL; 35.95°N, 104.14°E) of Lanzhou University in northwest China during April to December 2007 using micro-pulse lidar data and profiling radiometer measurements. Analysis of the measurements allowed the determination of macrophysical properties such as cirrus cloud height, ambient temperature, and geometrical depth, and optical characteristics were determined in terms of optical depth, extinction coefficient, and lidar ratio. Cirrus clouds were generally observed at heights ranging from 5.8 to 12.7 km, with a mean of 9.0±1.0 km. The mean cloud geometrical depth and optical depth were found to be 2.0±0.6 km and 0.350±0.311, respectively. Optical depth increased linearly with increasing geometrical depth. The results derived from lidar signals showed that cirrus over SACOL consisted of thin cirrus and opaque cirrus which occurred frequently in the height of 8–10 km. The lidar ratio varied from 5 to 70 sr, with a mean value of 26±16 sr, after taking into account multiple scattering effects. The mean lidar ratio of thin cirrus was greater than that of opaque cirrus. The maximum lidar ratio appeared between 0.058 and 0.3 when plotted against optical depth. The lidar ratio increased exponentially as the optical depth increased. The maximum lidar ratio fell between 11 and 12 km when plotted against cloud mid-height. The lidar ratio first increased and then decreased with increasing mid-height. -- Highlights: ► Cirrus clouds over semi-arid area were firstly observed by ground-based lidar. ► Macrophysical and optical characteristics of cirrus clouds were discussed. ► Thin cirrus and opaque cirrus occurred most frequently over SACOL. ► Thin cirrus often occurred above 10 km

2010 Federal Emergency Management Agency (FEMA) Topographic Lidar: Concord River Watershed, Massachusetts

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Concord AOI consists of one area. Ground Control is collected throughout the AOI for use in the processing of LiDAR data to ensure data accurately represents the...

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).

Progress report of FY 1999 activities: The application of Kalman filtering to derive water vapor profiles from combined ground-based sensors: Raman lidar, microwave radiometers, GPS, and radiosondes

International Nuclear Information System (INIS)

Edgeworth R. Westwater; Yong Han

1999-01-01

Previously, the proposers have delivered to ARM a documented algorithm, that is now applied operationally, and which derives water vapor profiles from combined remote sensor measurements of water vapor radiometers, cloud-base ceilometers, and radio acoustic sounding systems (RASS). With the expanded deployment of a Raman lidar at the CART Central Facility, high quality, high vertical-resolution, water vapor profiles will be provided during nighttime clear conditions, and during clear daytime conditions, to somewhat lower altitudes. The object of this effort is to use Kalman Filtering, previously applied to the combination of nighttime Raman lidar and microwave radiometer data, to derive high-quality water vapor profiles, during non-precipitating conditions, from data routinely available at the CART site. Input data to the algorithm would include: Raman lidar data, highly quality-controlled data of integrated moisture from microwave radiometers and GPS, RASS, and radiosondes. While analyzing data obtained during the Water Vapor Intensive Operating Period'97 at the SGP CART site in central Oklahoma, several questions arose about the calibration of the ARM microwave radiometers (MWR). A large portion of this years effort was a thorough analysis of the many factors that are important for the calibration of this instrument through the tip calibration method and the development of algorithms to correct this procedure. An open literature publication describing this analysis has been accepted

UAS-Borne Photogrammetry for Surface Topographic Characterization: A Ground-Truth Baseline for Future Change Detection and Refinement of Scaled Remotely-Sensed Datasets

Science.gov (United States)

Coppersmith, R.; Schultz-Fellenz, E. S.; Sussman, A. J.; Vigil, S.; Dzur, R.; Norskog, K.; Kelley, R.; Miller, L.

2015-12-01

While long-term objectives of monitoring and verification regimes include remote characterization and discrimination of surficial geologic and topographic features at sites of interest, ground truth data is required to advance development of remote sensing techniques. Increasingly, it is desirable for these ground-based or ground-proximal characterization methodologies to be as nimble, efficient, non-invasive, and non-destructive as their higher-altitude airborne counterparts while ideally providing superior resolution. For this study, the area of interest is an alluvial site at the Nevada National Security Site intended for use in the Source Physics Experiment's (Snelson et al., 2013) second phase. Ground-truth surface topographic characterization was performed using a DJI Inspire 1 unmanned aerial system (UAS), at very low altitude (clouds. Within the area of interest, careful installation of surveyed ground control fiducial markers supplied necessary targets for field collection, and information for model georectification. The resulting model includes a Digital Elevation Model derived from 2D imagery. It is anticipated that this flexible and versatile characterization process will provide point cloud data resolution equivalent to a purely ground-based LiDAR scanning deployment (e.g., 1-2cm horizontal and vertical resolution; e.g., Sussman et al., 2012; Schultz-Fellenz et al., 2013). In addition to drastically increasing time efficiency in the field, the UAS method also allows for more complete coverage of the study area when compared to ground-based LiDAR. Comparison and integration of these data with conventionally-acquired airborne LiDAR data from a higher-altitude (~ 450m) platform will aid significantly in the refinement of technologies and detection capabilities of remote optical systems to identify and detect surface geologic and topographic signatures of interest. This work includes a preliminary comparison of surface signatures detected from varying

Analysis and validation of ozone variability observed by lidar during the ESCOMPTE-2001 campaign

Science.gov (United States)

Ancellet, G.; Ravetta, F.

2005-03-01

An ozone lidar was successfully operated as a ground-based instrument during the ESCOMPTE experiment in June/July 2001. Ozone profiles were measured between 0.5 and 5 km. Moreover, simultaneous measurements of the lidar scattering ratio (SR) at 316 nm diagnosed the diurnal evolution of the PBL top. Comparison of this data set with in-situ measurements by ultralight aircraft (ULM) and balloon soundings supports the existence of well-defined layers over the whole altitude range. Differences between measurements techniques are not due to instrumental inaccuracies but point towards the existence of ozone plumes with sharp horizontal gradients. This is indeed supported by aircraft horizontal cross-section available twice a day at two different levels in the planetary boundary layer (PBL) and the free troposphere. Analysis of the ozone data set has shown a good correlation between surface meteorological conditions, surface ozone measurements and lidar ozone profiles in the PBL. Observed ozone maxima or minima are linked either to sea breeze circulation bringing polluted air masses over the lidar or synoptic flows bringing air with background O 3 values into the region. The observed variability of the ozone field is very large over the whole altitude range. Although it is the result of local temporal variability and advection of spatial inhomogenities, the latter proved to be an important contribution.

Wind observations above an urban river using a new lidar technique, scintillometry and anemometry

Energy Technology Data Exchange (ETDEWEB)

Wood, C.R. [Department of Meteorology, University of Reading, Reading, RG6 6BB (United Kingdom); Finnish Meteorological Institute, Erik Palmenin aukio 1, Helsinki, 00101 (Finland); Pauscher, L. [King' s College London, Department of Geography, London, WC2R 2LS (United Kingdom); Ward, H.C. [King' s College London, Department of Geography, London, WC2R 2LS (United Kingdom); Centre for Ecology and Hydrology, Wallingford, Oxfordshire, OX10 8BB (United Kingdom); Kotthaus, S. [King' s College London, Department of Geography, London, WC2R 2LS (United Kingdom); Barlow, J.F., E-mail: j.f.barlow@reading.ac.uk [Department of Meteorology, University of Reading, Reading, RG6 6BB (United Kingdom); Gouvea, M. [King' s College London, Department of Geography, London, WC2R 2LS (United Kingdom); Lane, S.E. [Department of Meteorology, University of Reading, Reading, RG6 6BB (United Kingdom); Grimmond, C.S.B. [King' s College London, Department of Geography, London, WC2R 2LS (United Kingdom)

2013-01-01

Airflow along rivers might provide a key mechanism for ventilation in cities: important for air quality and thermal comfort. Airflow varies in space and time in the vicinity of rivers. Consequently, there is limited utility in point measurements. Ground-based remote sensing offers the opportunity to study 3D airflow in locations which are difficult to observe with conventional approaches. For three months in the winter and spring of 2011, the airflow above the River Thames in central London was observed using a scanning Doppler lidar, a scintillometer and sonic anemometers. First, an inter-comparison showed that lidar-derived mean wind-speed estimates compare almost as well to sonic anemometers (root-mean-square error (rmse) 0.65-0.68 m s{sup -1}) as comparisons between sonic anemometers (0.35-0.73 m s{sup -1}). Second, the lidar duo-beam operating strategy provided horizontal transects of wind vectors (comparison with scintillometer rmse 1.12-1.63 m s{sup -1}) which revealed mean and turbulent airflow across the river and surrounds; in particular, channelled airflow along the river and changes in turbulence quantities consistent with the roughness changes between built and river environments. The results have important consequences for air quality and dispersion around urban rivers, especially given that many cities have high traffic rates on roads located on riverbanks. -- Highlights: Black-Right-Pointing-Pointer An inter-comparison was made between lidar-derived winds and regular anemometry. Black-Right-Pointing-Pointer A new lidar operating technique was developed. Black-Right-Pointing-Pointer Airflow features above an urban river included channelling of wind.

Wind observations above an urban river using a new lidar technique, scintillometry and anemometry

International Nuclear Information System (INIS)

Wood, C.R.; Pauscher, L.; Ward, H.C.; Kotthaus, S.; Barlow, J.F.; Gouvea, M.; Lane, S.E.; Grimmond, C.S.B.

2013-01-01

Airflow along rivers might provide a key mechanism for ventilation in cities: important for air quality and thermal comfort. Airflow varies in space and time in the vicinity of rivers. Consequently, there is limited utility in point measurements. Ground-based remote sensing offers the opportunity to study 3D airflow in locations which are difficult to observe with conventional approaches. For three months in the winter and spring of 2011, the airflow above the River Thames in central London was observed using a scanning Doppler lidar, a scintillometer and sonic anemometers. First, an inter-comparison showed that lidar-derived mean wind-speed estimates compare almost as well to sonic anemometers (root-mean-square error (rmse) 0.65–0.68 m s −1 ) as comparisons between sonic anemometers (0.35–0.73 m s −1 ). Second, the lidar duo-beam operating strategy provided horizontal transects of wind vectors (comparison with scintillometer rmse 1.12–1.63 m s −1 ) which revealed mean and turbulent airflow across the river and surrounds; in particular, channelled airflow along the river and changes in turbulence quantities consistent with the roughness changes between built and river environments. The results have important consequences for air quality and dispersion around urban rivers, especially given that many cities have high traffic rates on roads located on riverbanks. -- Highlights: ► An inter-comparison was made between lidar-derived winds and regular anemometry. ► A new lidar operating technique was developed. ► Airflow features above an urban river included channelling of wind.

2014 U.S. Geological Survey CMGP LiDAR: Post Sandy (National Capital Region)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — USGS Contract No. G10PC00025 CONTRACTOR: Quantum Spatial, Inc Ground Control Points were acquired and calibrated by Compass Data, Inc. All Lidar data acquisition,...

A comparison of mixing depths observed by ground-based wind profilers and an airborne lidar

Energy Technology Data Exchange (ETDEWEB)

White, A.B.; Senff, C. [Univ. of Colorado/NOAA Environmental Technology Lab., Cooperative Inst. for Research in Environmental Sciences, Boulder, CO (United States); Banta, R.M. [NOAA Environmental Technology Lab., Boulder, CO (United States)

1997-10-01

The mixing depth is one of the most important parameters in air pollution studies because it determines the vertical extent of the `box` in which pollutants are mixed and dispersed. During the 1995 Southern Oxidants Study (SOS95), scientists from the National Oceanic and Atmospheric Administration Environmental Technology Laboratory (NOAA/ETL) deployed four 915-MHz boundary-layer radar/wind profilers (hereafter radars) in and around the Nashville, Tennessee metropolitan area. Scientists from NOAA/ETL also operated an ultraviolet differential absorption lidar (DIAL) onboard a CASA-212 aircraft. Profiles from radar and DIAL can be used to derive estimates of the mixing depth. The methods used for both instruments are similar in that they depend on information derived from the backscattered power. However, different scattering mechanisms for the radar and DIAL mean that different tracers of mixing depth are measured. In this paper we compare the mixing depth estimates obtained from the radar and DIAL and discuss the similarities and differences that occur. (au)

Forest Canopy LAI and Vertical FAVD Profile Inversion from Airborne Full-Waveform LiDAR Data Based on a Radiative Transfer Model

Directory of Open Access Journals (Sweden)

Han Ma

2015-02-01

Full Text Available Forest canopy leaf area index (LAI is a critical variable for the modeling of climates and ecosystems over both regional and global scales. This paper proposes a physically based method to retrieve LAI and foliage area volume density (FAVD profile directly from full-waveform Light Detection And Ranging (LiDAR data using a radiative transfer (RT model. First, a physical interaction model between LiDAR and a forest scene was built on the basis of radiative transfer theories. Next, FAVD profile of each laser shot of full-waveform LiDAR was inverted using the physical model. In addition, the missing LiDAR data, caused by high-density forest and LiDAR system limitations, were filled in based on the inverted FAVD and the ancillary CHM data. Finally, LAI of the study area was retrieved from the inverted FAVD at a 10-m resolution. CHM derived LAI based on the Beer-Lambert law was compared with the LAI derived from full-waveform data. Also, we compared the results with the field measured LAI. The values of correlation coefficient r and RMSE of the estimated LAI were 0.73 and 0.67, respectively. The results indicate that full-waveform LiDAR data is a reliable data source and represent a useful tool for retrieving forest LAI.

AUTOMATED RECONSTRUCTION OF WALLS FROM AIRBORNE LIDAR DATA FOR COMPLETE 3D BUILDING MODELLING

Directory of Open Access Journals (Sweden)

Y. He

2012-07-01

Full Text Available Automated 3D building model generation continues to attract research interests in photogrammetry and computer vision. Airborne Light Detection and Ranging (LIDAR data with increasing point density and accuracy has been recognized as a valuable source for automated 3D building reconstruction. While considerable achievements have been made in roof extraction, limited research has been carried out in modelling and reconstruction of walls, which constitute important components of a full building model. Low point density and irregular point distribution of LIDAR observations on vertical walls render this task complex. This paper develops a novel approach for wall reconstruction from airborne LIDAR data. The developed method commences with point cloud segmentation using a region growing approach. Seed points for planar segments are selected through principle component analysis, and points in the neighbourhood are collected and examined to form planar segments. Afterwards, segment-based classification is performed to identify roofs, walls and planar ground surfaces. For walls with sparse LIDAR observations, a search is conducted in the neighbourhood of each individual roof segment to collect wall points, and the walls are then reconstructed using geometrical and topological constraints. Finally, walls which were not illuminated by the LIDAR sensor are determined via both reconstructed roof data and neighbouring walls. This leads to the generation of topologically consistent and geometrically accurate and complete 3D building models. Experiments have been conducted in two test sites in the Netherlands and Australia to evaluate the performance of the proposed method. Results show that planar segments can be reliably extracted in the two reported test sites, which have different point density, and the building walls can be correctly reconstructed if the walls are illuminated by the LIDAR sensor.

A comparison of two open source LiDAR surface classification algorithms

Science.gov (United States)

With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are op...

Coherent Lidar Turbulence Measurement for Gust Load Alleviation

Science.gov (United States)

Bogue, Rodney K.; Ehernberger, L. J.; Soreide, David; Bagley, Hal

1996-01-01

Atmospheric turbulence adversely affects operation of commercial and military aircraft and is a design constraint. The airplane structure must be designed to survive the loads imposed by turbulence. Reducing these loads allows the airplane structure to be lighter, a substantial advantage for a commercial airplane. Gust alleviation systems based on accelerometers mounted in the airplane can reduce the maximum gust loads by a small fraction. These systems still represent an economic advantage. The ability to reduce the gust load increases tremendously if the turbulent gust can be measured before the airplane encounters it. A lidar system can make measurements of turbulent gusts ahead of the airplane, and the NASA Airborne Coherent Lidar for Advanced In-Flight Measurements (ACLAIM) program is developing such a lidar. The ACLAIM program is intended to develop a prototype lidar system for use in feasibility testing of gust load alleviation systems and other airborne lidar applications, to define applications of lidar with the potential for improving airplane performance, and to determine the feasibility and benefits of these applications. This paper gives an overview of the ACLAIM program, describes the lidar architecture for a gust alleviation system, and describes the prototype ACLAIM lidar system.

Lidar-Radiometer Inversion Code (LIRIC) for the Retrieval of Vertical Aerosol Properties from Combined Lidar Radiometer Data: Development and Distribution in EARLINET

Science.gov (United States)

Chaikovsky, A.; Dubovik, O.; Holben, Brent N.; Bril, A.; Goloub, P.; Tanre, D.; Pappalardo, G.; Wandinger, U.; Chaikovskaya, L.; Denisov, S.;

Compact, High Energy 2-micron Coherent Doppler Wind Lidar Development for NASA's Future 3-D Winds Measurement from Space

Science.gov (United States)

Singh, Upendra N.; Koch, Grady; Yu, Jirong; Petros, Mulugeta; Beyon, Jeffrey; Kavaya, Michael J.; Trieu, Bo; Chen, Songsheng; Bai, Yingxin; Petzar, paul;

Scanning, Multibeam, Single Photon Lidars for Rapid, Large Scale, High Resolution, Topographic and Bathymetric Mapping

Directory of Open Access Journals (Sweden)

John J. Degnan

2016-11-01

Full Text Available Several scanning, single photon sensitive, 3D imaging lidars are herein described that operate at aircraft above ground levels (AGLs between 1 and 11 km, and speeds in excess of 200 knots. With 100 beamlets and laser fire rates up to 60 kHz, we, at the Sigma Space Corporation (Lanham, MD, USA, have interrogated up to 6 million ground pixels per second, all of which can record multiple returns from volumetric scatterers such as tree canopies. High range resolution has been achieved through the use of subnanosecond laser pulsewidths, detectors and timing receivers. The systems are presently being deployed on a variety of aircraft to demonstrate their utility in multiple applications including large scale surveying, bathymetry, forestry, etc. Efficient noise filters, suitable for near realtime imaging, have been shown to effectively eliminate the solar background during daytime operations. Geolocation elevation errors measured to date are at the subdecimeter level. Key differences between our Single Photon Lidars, and competing Geiger Mode lidars are also discussed.

Column CO2 Measurement From an Airborne Solid-State Double-Pulsed 2-Micron Integrated Path Differential Absorption Lidar

Science.gov (United States)

Singh, U. N.; Yu, J.; Petros, M.; Refaat, T. F.; Remus, R.; Fay, J.; Reithmaier, K.

2014-01-01

NASA LaRC is developing and integrating a double-Pulsed 2-micron direct detection IPDA lidar for CO2 column measurement from an airborne platform. The presentation will describe the development of the 2-micrometers IPDA lidar system and present the airborne measurement of column CO2 and will compare to in-situ measurement for various ground target of different reflectivity.

Column carbon dioxide and water vapor measurements by an airborne triple-pulse integrated path differential absorption lidar: novel lidar technologies and techniques with path to space

Science.gov (United States)

Singh, U. N.; Petros, M.; Refaat, T. F.; Yu, J.; Ismail, S.

2017-09-01

The 2-micron wavelength region is suitable for atmospheric carbon dioxide (CO2) measurements due to the existence of distinct absorption features for the gas at this wavelength region [1]. For more than 20 years, researchers at NASA Langley Research Center (LaRC) have developed several high-energy and high repetition rate 2-micron pulsed lasers [2]. Currently, LaRC team is engaged in designing, developing and demonstrating a triple-pulsed 2-micron direct detection Integrated Path Differential Absorption (IPDA) lidar to measure the weighted-average column dry-air mixing ratios of carbon dioxide (XCO2) and water vapor (XH2O) from an airborne platform [1, 3-5]. This novel technique allows measurement of the two most dominant greenhouse gases, simultaneously and independently, using a single instrument. This paper will provide status and details of the development of this airborne 2-micron triple-pulse IPDA lidar. The presented work will focus on the advancement of critical IPDA lidar components. Updates on the state-of-the-art triple-pulse laser transmitter will be presented including the status of seed laser locking, wavelength control, receiver and detector upgrades, laser packaging and lidar integration. Future plans for IPDA lidar ground integration, testing and flight validation will also be discussed. This work enables new Earth observation measurements, while reducing risk, cost, size, volume, mass and development time of required instruments.

Aggregating pixel-level basal area predictions derived from LiDAR data to industrial forest stands in North-Central Idaho

Science.gov (United States)

Andrew T. Hudak; Jeffrey S. Evans; Nicholas L. Crookston; Michael J. Falkowski; Brant K. Steigers; Rob Taylor; Halli Hemingway

2008-01-01

Stand exams are the principal means by which timber companies monitor and manage their forested lands. Airborne LiDAR surveys sample forest stands at much finer spatial resolution and broader spatial extent than is practical on the ground. In this paper, we developed models that leverage spatially intensive and extensive LiDAR data and a stratified random sample of...

Registration of Urban Aerial Image and LiDAR Based on Line Vectors

Directory of Open Access Journals (Sweden)

Qinghong Sheng

2017-09-01

Full Text Available In a traditional registration of a single aerial image with airborne light detection and ranging (LiDAR data using linear features that regard line direction as a control or linear features as constraints in the solution, lacking the constraint of linear position leads to the error propagation of the adjustment model. To solve this problem, this paper presents a line vector-based registration mode (LVR in which image rays and LiDAR lines are expressed by a line vector that integrates the line direction and the line position. A registration equation of line vector is set up by coplanar imaging rays and corresponding control lines. Three types of datasets consisting of synthetic, theInternational Society for Photogrammetry and Remote Sensing (ISPRS test project, and real aerial data are used. A group of progressive experiments is undertaken to evaluate the robustness of the LVR. Experimental results demonstrate that the integrated line direction and the line position contributes a great deal to the theoretical and real accuracies of the unknowns, as well as the stability of the adjustment model. This paper provides a new suggestion that, for a single image and LiDAR data, registration in urban areas can be accomplished by accommodating rich line features.

2011 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Quinnipiac River Watershed, Connecticut

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — The Quinnipiac AOI consists of one 443 square mile area. Ground Control is collected throughout the AOI for use in the processing of LiDAR data to ensure data...

Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects

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S. Lolli

2018-03-01

Full Text Available In the past 2 decades, ground-based lidar networks have drastically increased in scope and relevance, thanks primarily to the advent of lidar observations from space and their need for validation. Lidar observations of aerosol and cloud geometrical, optical and microphysical atmospheric properties are subsequently used to evaluate their direct radiative effects on climate. However, the retrievals are strongly dependent on the lidar instrument measurement technique and subsequent data processing methodologies. In this paper, we evaluate the discrepancies between the use of Raman and elastic lidar measurement techniques and corresponding data processing methods for two aerosol layers in the free troposphere and for two cirrus clouds with different optical depths. Results show that the different lidar techniques are responsible for discrepancies in the model-derived direct radiative effects for biomass burning (0.05 W m−2 at surface and 0.007 W m−2 at top of the atmosphere and dust aerosol layers (0.7 W m−2 at surface and 0.85 W m−2 at top of the atmosphere. Data processing is further responsible for discrepancies in both thin (0.55 W m−2 at surface and 2.7 W m−2 at top of the atmosphere and opaque (7.7 W m−2 at surface and 11.8 W m−2 at top of the atmosphere cirrus clouds. Direct radiative effect discrepancies can be attributed to the larger variability of the lidar ratio for aerosols (20–150 sr than for clouds (20–35 sr. For this reason, the influence of the applied lidar technique plays a more fundamental role in aerosol monitoring because the lidar ratio must be retrieved with relatively high accuracy. In contrast, for cirrus clouds, with the lidar ratio being much less variable, the data processing is critical because smoothing it modifies the aerosol and cloud vertically resolved extinction profile that is used as input to compute direct radiative effect calculations.

Impact of varying lidar measurement and data processing techniques in evaluating cirrus cloud and aerosol direct radiative effects

Science.gov (United States)

Lolli, Simone; Madonna, Fabio; Rosoldi, Marco; Campbell, James R.; Welton, Ellsworth J.; Lewis, Jasper R.; Gu, Yu; Pappalardo, Gelsomina

2018-03-01

In the past 2 decades, ground-based lidar networks have drastically increased in scope and relevance, thanks primarily to the advent of lidar observations from space and their need for validation. Lidar observations of aerosol and cloud geometrical, optical and microphysical atmospheric properties are subsequently used to evaluate their direct radiative effects on climate. However, the retrievals are strongly dependent on the lidar instrument measurement technique and subsequent data processing methodologies. In this paper, we evaluate the discrepancies between the use of Raman and elastic lidar measurement techniques and corresponding data processing methods for two aerosol layers in the free troposphere and for two cirrus clouds with different optical depths. Results show that the different lidar techniques are responsible for discrepancies in the model-derived direct radiative effects for biomass burning (0.05 W m-2 at surface and 0.007 W m-2 at top of the atmosphere) and dust aerosol layers (0.7 W m-2 at surface and 0.85 W m-2 at top of the atmosphere). Data processing is further responsible for discrepancies in both thin (0.55 W m-2 at surface and 2.7 W m-2 at top of the atmosphere) and opaque (7.7 W m-2 at surface and 11.8 W m-2 at top of the atmosphere) cirrus clouds. Direct radiative effect discrepancies can be attributed to the larger variability of the lidar ratio for aerosols (20-150 sr) than for clouds (20-35 sr). For this reason, the influence of the applied lidar technique plays a more fundamental role in aerosol monitoring because the lidar ratio must be retrieved with relatively high accuracy. In contrast, for cirrus clouds, with the lidar ratio being much less variable, the data processing is critical because smoothing it modifies the aerosol and cloud vertically resolved extinction profile that is used as input to compute direct radiative effect calculations.

Design and implementation of 3D LIDAR based on pixel-by-pixel scanning and DS-OCDMA

Science.gov (United States)

Kim, Gunzung; Eom, Jeongsook; Park, Yongwan

2017-02-01

We designed a prototype for testing feasibility of a proposed light detection and ranging (LIDAR) system, which was designed to encode pixel location information in its laser pulses using the direct-sequence optical code division multiple access method in conjunction with a scanning-based microelectromechanical system (MEMS) mirror. The prototype was built using commercial o -the-shelf optical components and development kits. It comprised of an optical modulator, an amplified photodetector, an MEMS mirror development kit, an analog-to-digital converter evaluation module, a digital signal processor with ARM evaluation kit and a Windows personal computer. The prototype LIDAR system has capable of acquiring 120 x 32-pixel images at 5 frames/s. We measured a watering pot to demonstrate the imaging performance of the prototype LIDAR system.

A Graph-Based Approach for 3D Building Model Reconstruction from Airborne LiDAR Point Clouds

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Bin Wu

2017-01-01

Full Text Available 3D building model reconstruction is of great importance for environmental and urban applications. Airborne light detection and ranging (LiDAR is a very useful data source for acquiring detailed geometric and topological information of building objects. In this study, we employed a graph-based method based on hierarchical structure analysis of building contours derived from LiDAR data to reconstruct urban building models. The proposed approach first uses a graph theory-based localized contour tree method to represent the topological structure of buildings, then separates the buildings into different parts by analyzing their topological relationships, and finally reconstructs the building model by integrating all the individual models established through the bipartite graph matching process. Our approach provides a more complete topological and geometrical description of building contours than existing approaches. We evaluated the proposed method by applying it to the Lujiazui region in Shanghai, China, a complex and large urban scene with various types of buildings. The results revealed that complex buildings could be reconstructed successfully with a mean modeling error of 0.32 m. Our proposed method offers a promising solution for 3D building model reconstruction from airborne LiDAR point clouds.

Automated Detection of Selective Logging in Amazon Forests Using Airborne Lidar Data and Pattern Recognition Algorithms

Science.gov (United States)

Keller, M. M.; d'Oliveira, M. N.; Takemura, C. M.; Vitoria, D.; Araujo, L. S.; Morton, D. C.

2012-12-01

Selective logging, the removal of several valuable timber trees per hectare, is an important land use in the Brazilian Amazon and may degrade forests through long term changes in structure, loss of forest carbon and species diversity. Similar to deforestation, the annual area affected by selected logging has declined significantly in the past decade. Nonetheless, this land use affects several thousand km2 per year in Brazil. We studied a 1000 ha area of the Antimary State Forest (FEA) in the State of Acre, Brazil (9.304 ○S, 68.281 ○W) that has a basal area of 22.5 m2 ha-1 and an above-ground biomass of 231 Mg ha-1. Logging intensity was low, approximately 10 to 15 m3 ha-1. We collected small-footprint airborne lidar data using an Optech ALTM 3100EA over the study area once each in 2010 and 2011. The study area contained both recent and older logging that used both conventional and technologically advanced logging techniques. Lidar return density averaged over 20 m-2 for both collection periods with estimated horizontal and vertical precision of 0.30 and 0.15 m. A relative density model comparing returns from 0 to 1 m elevation to returns in 1-5 m elevation range revealed the pattern of roads and skid trails. These patterns were confirmed by ground-based GPS survey. A GIS model of the road and skid network was built using lidar and ground data. We tested and compared two pattern recognition approaches used to automate logging detection. Both segmentation using commercial eCognition segmentation and a Frangi filter algorithm identified the road and skid trail network compared to the GIS model. We report on the effectiveness of these two techniques.

2011 U.S. Army Corps of Engineers (USACE) Topographic LiDAR: Massachusetts and New Hampshire

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These files contain classified topographic and bathymetric lidar data as unclassified valid topographic data (1), valid topographic data classified as ground (2),...

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

Demonstration of a diode-laser-based high spectral resolution lidar (HSRL) for quantitative profiling of clouds and aerosols.

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Hayman, Matthew; Spuler, Scott

2017-11-27

We present a demonstration of a diode-laser-based high spectral resolution lidar. It is capable of performing calibrated retrievals of aerosol and cloud optical properties at a 150 m range resolution with less than 1 minute integration time over an approximate range of 12 km during day and night. This instrument operates at 780 nm, a wavelength that is well established for reliable semiconductor lasers and detectors, and was chosen because it corresponds to the D2 rubidium absorption line. A heated vapor reference cell of isotopic rubidium 87 is used as an effective and reliable aerosol signal blocking filter in the instrument. In principle, the diode-laser-based high spectral resolution lidar can be made cost competitive with elastic backscatter lidar systems, yet delivers a significant improvement in data quality through direct retrieval of quantitative optical properties of clouds and aerosols.

Quantifying spatial distribution of snow depth errors from LiDAR using Random Forests

Science.gov (United States)

Tinkham, W.; Smith, A. M.; Marshall, H.; Link, T. E.; Falkowski, M. J.; Winstral, A. H.

2013-12-01

There is increasing need to characterize the distribution of snow in complex terrain using remote sensing approaches, especially in isolated mountainous regions that are often water-limited, the principal source of terrestrial freshwater, and sensitive to climatic shifts and variations. We apply intensive topographic surveys, multi-temporal LiDAR, and Random Forest modeling to quantify snow volume and characterize associated errors across seven land cover types in a semi-arid mountainous catchment at a 1 and 4 m spatial resolution. The LiDAR-based estimates of both snow-off surface topology and snow depths were validated against ground-based measurements across the catchment. Comparison of LiDAR-derived snow depths to manual snow depth surveys revealed that LiDAR based estimates were more accurate in areas of low lying vegetation such as shrubs (RMSE = 0.14 m) as compared to areas consisting of tree cover (RMSE = 0.20-0.35 m). The highest errors were found along the edge of conifer forests (RMSE = 0.35 m), however a second conifer transect outside the catchment had much lower errors (RMSE = 0.21 m). This difference is attributed to the wind exposure of the first site that led to highly variable snow depths at short spatial distances. The Random Forest modeled errors deviated from the field measured errors with a RMSE of 0.09-0.34 m across the different cover types. Results show that snow drifts, which are important for maintaining spring and summer stream flows and establishing and sustaining water-limited plant species, contained 30 × 5-6% of the snow volume while only occupying 10% of the catchment area similar to findings by prior physically-based modeling approaches. This study demonstrates the potential utility of combining multi-temporal LiDAR with Random Forest modeling to quantify the distribution of snow depth with a reasonable degree of accuracy. Future work could explore the utility of Terrestrial LiDAR Scanners to produce validation of snow-on surface

A Concealed Car Extraction Method Based on Full-Waveform LiDAR Data

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Chuanrong Li

2016-01-01

Full Text Available Concealed cars extraction from point clouds data acquired by airborne laser scanning has gained its popularity in recent years. However, due to the occlusion effect, the number of laser points for concealed cars under trees is not enough. Thus, the concealed cars extraction is difficult and unreliable. In this paper, 3D point cloud segmentation and classification approach based on full-waveform LiDAR was presented. This approach first employed the autocorrelation G coefficient and the echo ratio to determine concealed cars areas. Then the points in the concealed cars areas were segmented with regard to elevation distribution of concealed cars. Based on the previous steps, a strategy integrating backscattered waveform features and the view histogram descriptor was developed to train sample data of concealed cars and generate the feature pattern. Finally concealed cars were classified by pattern matching. The approach was validated by full-waveform LiDAR data and experimental results demonstrated that the presented approach can extract concealed cars with accuracy more than 78.6% in the experiment areas.

Incremental and Enhanced Scanline-Based Segmentation Method for Surface Reconstruction of Sparse LiDAR Data

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Weimin Wang

2016-11-01

Full Text Available The segmentation of point clouds is an important aspect of automated processing tasks such as semantic extraction. However, the sparsity and non-uniformity of the point clouds gathered by the popular 3D mobile LiDAR devices pose many challenges for existing segmentation methods. To improve the segmentation results of point clouds from mobile LiDAR devices, we propose an optimized segmentation method based on Scanline Continuity Constraint (SLCC in this work. Unlike conventional scanline-based segmentation methods, SLCC clusters scanlines using the continuity constraints in terms of the distance as well as the direction of two consecutive points. In addition, scanline clusters are agglomerated not only into primitive geometrical shapes but also irregular shapes. Another downside to existing segmentation methods is that they are not capable of incremental processing. This causes unnecessary memory and time consumption for applications that require frame-wise segmentation or when new point clouds are added. In order to address this, we propose an incremental scheme—the Incremental Recursive Segmentation (IRIS, that can be easily applied to any segmentation method. IRIS is achieved by combining the segments of newly added point clouds and the previously segmented results. Furthermore, as an example application, we construct a processing pipeline consisting of plane fitting and surface reconstruction using the segmentation results. Finally, we evaluate the proposed methods on three datasets acquired from a handheld Velodyne HDL-32E LiDAR device. The experimental results verify the efficiency of IRIS for any segmentation method and the advantages of SLCC for processing mobile LiDAR data.

In-field High Throughput Phenotyping and Cotton Plant Growth Analysis Using LiDAR.

Science.gov (United States)

Sun, Shangpeng; Li, Changying; Paterson, Andrew H; Jiang, Yu; Xu, Rui; Robertson, Jon S; Snider, John L; Chee, Peng W

2018-01-01

Plant breeding programs and a wide range of plant science applications would greatly benefit from the development of in-field high throughput phenotyping technologies. In this study, a terrestrial LiDAR-based high throughput phenotyping system was developed. A 2D LiDAR was applied to scan plants from overhead in the field, and an RTK-GPS was used to provide spatial coordinates. Precise 3D models of scanned plants were reconstructed based on the LiDAR and RTK-GPS data. The ground plane of the 3D model was separated by RANSAC algorithm and a Euclidean clustering algorithm was applied to remove noise generated by weeds. After that, clean 3D surface models of cotton plants were obtained, from which three plot-level morphologic traits including canopy height, projected canopy area, and plant volume were derived. Canopy height ranging from 85th percentile to the maximum height were computed based on the histogram of the z coordinate for all measured points; projected canopy area was derived by projecting all points on a ground plane; and a Trapezoidal rule based algorithm was proposed to estimate plant volume. Results of validation experiments showed good agreement between LiDAR measurements and manual measurements for maximum canopy height, projected canopy area, and plant volume, with R 2 -values of 0.97, 0.97, and 0.98, respectively. The developed system was used to scan the whole field repeatedly over the period from 43 to 109 days after planting. Growth trends and growth rate curves for all three derived morphologic traits were established over the monitoring period for each cultivar. Overall, four different cultivars showed similar growth trends and growth rate patterns. Each cultivar continued to grow until ~88 days after planting, and from then on varied little. However, the actual values were cultivar specific. Correlation analysis between morphologic traits and final yield was conducted over the monitoring period. When considering each cultivar individually

Crop 3D-a LiDAR based platform for 3D high-throughput crop phenotyping.

Science.gov (United States)

Guo, Qinghua; Wu, Fangfang; Pang, Shuxin; Zhao, Xiaoqian; Chen, Linhai; Liu, Jin; Xue, Baolin; Xu, Guangcai; Li, Le; Jing, Haichun; Chu, Chengcai

2018-03-01

With the growing population and the reducing arable land, breeding has been considered as an effective way to solve the food crisis. As an important part in breeding, high-throughput phenotyping can accelerate the breeding process effectively. Light detection and ranging (LiDAR) is an active remote sensing technology that is capable of acquiring three-dimensional (3D) data accurately, and has a great potential in crop phenotyping. Given that crop phenotyping based on LiDAR technology is not common in China, we developed a high-throughput crop phenotyping platform, named Crop 3D, which integrated LiDAR sensor, high-resolution camera, thermal camera and hyperspectral imager. Compared with traditional crop phenotyping techniques, Crop 3D can acquire multi-source phenotypic data in the whole crop growing period and extract plant height, plant width, leaf length, leaf width, leaf area, leaf inclination angle and other parameters for plant biology and genomics analysis. In this paper, we described the designs, functions and testing results of the Crop 3D platform, and briefly discussed the potential applications and future development of the platform in phenotyping. We concluded that platforms integrating LiDAR and traditional remote sensing techniques might be the future trend of crop high-throughput phenotyping.

Quantitative study of tectonic geomorphology along Haiyuan fault based on airborne LiDAR

Science.gov (United States)

Chen, Tao; Zhang, Pei Zhen; Liu, Jing; Li, Chuan You; Ren, Zhi Kun; Hudnut, Kenneth W.

2014-01-01

High-precision and high-resolution topography are the fundamental data for active fault research. Light detection and ranging (LiDAR) presents a new approach to build detailed digital elevation models effectively. We take the Haiyuan fault in Gansu Province as an example of how LiDAR data may be used to improve the study of active faults and the risk assessment of related hazards. In the eastern segment of the Haiyuan fault, the Shaomayin site has been comprehensively investigated in previous research because of its exemplary tectonic topographic features. Based on unprecedented LiDAR data, the horizontal and vertical coseismic offsets at the Shaomayin site are described. The measured horizontal value is about 8.6 m, and the vertical value is about 0.8 m. Using prior dating ages sampled from the same location, we estimate the horizontal slip rate as 4.0 ± 1.0 mm/a with high confidence and define that the lower bound of the vertical slip rate is 0.4 ± 0.1 mm/a since the Holocene. LiDAR data can repeat the measurements of field work on quantifying offsets of tectonic landform features quite well. The offset landforms are visualized on an office computer workstation easily, and specialized software may be used to obtain displacement quantitatively. By combining precious chronological results, the fundamental link between fault activity and large earthquakes is better recognized, as well as the potential risk for future earthquake hazards.

Atmospheric aerosol and gas sensing using Scheimpflug lidar

Science.gov (United States)

Mei, Liang; Brydegaard, Mikkel

2015-04-01

This work presents a new lidar technique for atmospheric remote sensing based on Scheimpflug principle, which describes the relationship between nonparallel image- and object-planes[1]. When a laser beam is transmitted into the atmosphere, the implication is that the backscattering echo of the entire illuminated probe volume can be in focus simultaneously without diminishing the aperture. The range-resolved backscattering echo can be retrieved by using a tilted line scan or two-dimensional CCD/CMOS camera. Rather than employing nanosecond-pulsed lasers, cascade detectors, and MHz signal sampling, all of high cost and complexity, we have developed a robust and inexpensive atmospheric lidar system based on compact laser diodes and array detectors. We present initial applications of the Scheimpflug lidar for atmospheric aerosol monitoring in bright sunlight, with a 3 W, 808 nm CW laser diode. Kilohertz sampling rates are also achieved with applications for wind speed and entomology [2]. Further, a proof-of-principle demonstration of differential absorption lidar (DIAL) based on the Scheimpflug lidar technique is presented [3]. By utilizing a 30 mW narrow band CW laser diode emitting at around 760 nm, the detailed shape of an oxygen absorption line can be resolved remotely with an integration time of 6 s and measurement cycle of 1 minute during night time. The promising results demonstrated in this work show potential for the Scheimpflug lidar technique for remote atmospheric aerosol and gas sensing, and renews hope for robust and realistic instrumentation for atmospheric lidar sensing. [1] F. Blais, "Review of 20 years of range sensor development," Journal of Electronic Imaging, vol. 13, pp. 231-243, Jan 2004. [2] M. Brydegaard, A. Gebru, and S. Svanberg, "Super resolution laser radar with blinking atmospheric particles - application to interacting flying insects " Progress In Electromagnetics Research, vol. 147, pp. 141-151, 2014. [3] L. Mei and M. Brydegaard

Triple-Pulse Integrated Path Differential Absorption Lidar for Carbon Dioxide Measurement - Novel Lidar Technologies and Techniques with Path to Space

Science.gov (United States)

Singh, Upendra N.; Refaat, Tamer F.; Petros, Mulugeta

2017-01-01

The societal benefits of understanding climate change through identification of global carbon dioxide sources and sinks led to the desired NASA's active sensing of carbon dioxide emissions over nights, days, and seasons (ASCENDS) space-based missions of global carbon dioxide measurements. For more than 15 years, NASA Langley Research Center (LaRC) have developed several carbon dioxide active remote sensors using the differential absorption lidar (DIAL) technique operating at the two-micron wavelength. Currently, an airborne two-micron triple-pulse integrated path differential absorption (IPDA) lidar is under development. This IPDA lidar measures carbon dioxide as well as water vapor, the dominant interfering molecule on carbon dioxide remote sensing. Advancement of this triple-pulse IPDA lidar development is presented.

Buildings classification from airborne LiDAR point clouds through OBIA and ontology driven approach

Science.gov (United States)

Tomljenovic, Ivan; Belgiu, Mariana; Lampoltshammer, Thomas J.

2013-04-01

the consistency of the developed ontologies, and logical reasoning is performed to infer implicit relations between defined concepts. The ontology for the definition of building is specified using the Ontology Web Language (OWL). It is the most widely used ontology language that is based on Description Logics (DL). DL allows the description of internal properties of modelled concepts (roof typology, shape, area, height etc.) and relationships between objects (IS_A, MEMBER_OF/INSTANCE_OF). It captures terminological knowledge (TBox) as well as assertional knowledge (ABox) - that represents facts about concept instances, i.e. the buildings in airborne LiDAR data. To assess the classification accuracy, ground truth data generated by visual interpretation and calculated classification results in terms of precision and recall are used. The advantages of this approach are: (i) flexibility, (ii) transferability, and (iii) extendibility - i.e. ontology can be extended with further concepts, data properties and object properties.

Lidar detection of carbon dioxide in volcanic plumes

Science.gov (United States)

Fiorani, Luca; Santoro, Simone; Parracino, Stefano; Maio, Giovanni; Del Franco, Mario; Aiuppa, Alessandro

2015-06-01

Volcanic gases give information on magmatic processes. In particular, anomalous releases of carbon dioxide precede volcanic eruptions. Up to now, this gas has been measured in volcanic plumes with conventional measurements that imply the severe risks of local sampling and can last many hours. For these reasons and for the great advantages of laser sensing, the thorough development of volcanic lidar has been undertaken at the Diagnostics and Metrology Laboratory (UTAPRAD-DIM) of the Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA). In fact, lidar profiling allows one to scan remotely volcanic plumes in a fast and continuous way, and with high spatial and temporal resolution. Two differential absorption lidar instruments will be presented in this paper: BILLI (BrIdge voLcanic LIdar), based on injection seeded Nd:YAG laser, double grating dye laser, difference frequency mixing (DFM) and optical parametric amplifier (OPA), and VULLI (VULcamed Lidar), based on injection seeded Nd:YAG laser and optical parametric oscillator (OPO). The first one is funded by the ERC (European Research Council) project BRIDGE and the second one by the ERDF (European Regional Development Fund) project VULCAMED. While VULLI has not yet been tested in a volcanic site, BILLI scanned the gas emitted by Pozzuoli Solfatara (Campi Flegrei volcanic area, Naples, Italy) during a field campaign carried out from 13 to 17 October 2014. Carbon dioxide concentration maps were retrieved remotely in few minutes in the crater area. Lidar measurements were in good agreement with well-established techniques, based on different operating principles. To our knowledge, it is the first time that carbon dioxide in a volcanic plume is retrieved by lidar, representing the first direct measurement of this kind ever performed on an active volcano and showing the high potential of laser remote sensing in geophysical research.

Atmospheric lidar: legislative, scientific and technological aspects; Lidar atmosferico. Aspetti legislativi, scientifici e tecnologici

Energy Technology Data Exchange (ETDEWEB)

Barbini, R.; Colao, F.; Fiorani, L.; Palucci, A. [ENEA, Divisione Fisica Applicata, Centro Ricerche Frascati, Frascati, RM (Italy)

2000-07-01

The Atmospheric Lidar is one of the systems of the Mobile Laboratory of Laser Remote Sensing under development at the ENEA Research Center of Frascati. This technical report addresses the legislative, scientific and technological aspects that are the basis for the identification of the requirements, the definition of the architecture and the fixation of the specifications of the Atmospheric Lidar. The problems of air pollution are introduced in section 2. A summary of the Italian laws on that topic is then given. Section 4 provides a survey of the atmospheric measurements that can be achieved with the lidar. The sensitivity in the monitoring of pollutants is discussed in section 5. The other systems of the Mobile Laboratory of Laser Remote Sensing are shortly described in section 6. The last section is devoted to conclusions and perspectives. [Italian] Il lidar atmosferico e' uno dei sistemi del Laboratorio Mobile di Telerilevamento Laser in corso di realizzazione presso il Centro Ricerche di Frascati dell'ENEA. Questo rapporto tecnico discute gli aspetti legislativi, scientifici, tecnologici che sono alla base dell'individuazione dei requisiti, della definizione dell'architettura e della fissazione delle specifiche del Lidar atmosferico. La problematica dell'inquinamento dell'aria e' introdotta nella sezione 2. Segue un riassunto della legislazione italiana su tale tematica. La sezione 4 offre una panoramica delle misure atmosferiche realizzabili con il Lidar. La sensibilita' nel monitoraggio di inquinanti e' discussa nella sezione 5. Gli altri sistemi del Laboratorio Mobile di Telerilevamento Laser sono descritti brevemente nella sezione 6. L'ultima sezione e' dedicata alle conclusioni e alle prospettive.

Object Classification Using Airborne Multispectral LiDAR Data

Directory of Open Access Journals (Sweden)

PAN Suoyan

2018-02-01

Full Text Available Airborne multispectral LiDAR system,which obtains surface geometry and spectral data of objects,simultaneously,has become a fast effective,large-scale spatial data acquisition method.Multispectral LiDAR data are characteristics of completeness and consistency of spectrum and spatial geometric information.Support vector machine (SVM,a machine learning method,is capable of classifying objects based on small samples.Therefore,by means of SVM,this paper performs land cover classification using multispectral LiDAR data. First,all independent point cloud with different wavelengths are merged into a single point cloud,where each pixel contains the three-wavelength spectral information.Next,the merged point cloud is converted into range and intensity images.Finally,land-cover classification is performed by means of SVM.All experiments were conducted on the Optech Titan multispectral LiDAR data,containing three individual point cloud collected by 532 nm,1024 nm,and 1550 nm laser beams.Experimental results demonstrate that ①compared to traditional single-wavelength LiDAR data,multispectral LiDAR data provide a promising solution to land use and land cover applications;②SVM is a feasible method for land cover classification of multispectral LiDAR data.

Moving Beyond 2% Uncertainty: A New Framework for Quantifying Lidar Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Newman, Jennifer F.; Clifton, Andrew

2017-03-08

Remote sensing of wind using lidar is revolutionizing wind energy. However, current generations of wind lidar are ascribed a climatic value of uncertainty, which is based on a poor description of lidar sensitivity to external conditions. In this presentation, we show how it is important to consider the complete lidar measurement process to define the measurement uncertainty, which in turn offers the ability to define a much more granular and dynamic measurement uncertainty. This approach is a progression from the 'white box' lidar uncertainty method.

Geomorphological change detection using object-based feature extraction from multi-temporal LIDAR data

NARCIS (Netherlands)

Seijmonsbergen, A.C.; Anders, N.S.; Bouten, W.; Feitosa, R.Q.; da Costa, G.A.O.P.; de Almeida, C.M.; Fonseca, L.M.G.; Kux, H.J.H.

2012-01-01

Multi-temporal LiDAR DTMs are used for the development and testing of a method for geomorphological change analysis in western Austria. Our test area is located on a mountain slope in the Gargellen Valley in western Austria. Six geomorphological features were mapped by using stratified Object-Based

Research on Visualization of Ground Laser Radar Data Based on Osg

Science.gov (United States)

Huang, H.; Hu, C.; Zhang, F.; Xue, H.

2018-04-01

Three-dimensional (3D) laser scanning is a new advanced technology integrating light, machine, electricity, and computer technologies. It can conduct 3D scanning to the whole shape and form of space objects with high precision. With this technology, you can directly collect the point cloud data of a ground object and create the structure of it for rendering. People use excellent 3D rendering engine to optimize and display the 3D model in order to meet the higher requirements of real time realism rendering and the complexity of the scene. OpenSceneGraph (OSG) is an open source 3D graphics engine. Compared with the current mainstream 3D rendering engine, OSG is practical, economical, and easy to expand. Therefore, OSG is widely used in the fields of virtual simulation, virtual reality, science and engineering visualization. In this paper, a dynamic and interactive ground LiDAR data visualization platform is constructed based on the OSG and the cross-platform C++ application development framework Qt. In view of the point cloud data of .txt format and the triangulation network data file of .obj format, the functions of 3D laser point cloud and triangulation network data display are realized. It is proved by experiments that the platform is of strong practical value as it is easy to operate and provides good interaction.

RESEARCH ON VISUALIZATION OF GROUND LASER RADAR DATA BASED ON OSG

Directory of Open Access Journals (Sweden)

H. Huang

2018-04-01

Full Text Available Three-dimensional (3D laser scanning is a new advanced technology integrating light, machine, electricity, and computer technologies. It can conduct 3D scanning to the whole shape and form of space objects with high precision. With this technology, you can directly collect the point cloud data of a ground object and create the structure of it for rendering. People use excellent 3D rendering engine to optimize and display the 3D model in order to meet the higher requirements of real time realism rendering and the complexity of the scene. OpenSceneGraph (OSG is an open source 3D graphics engine. Compared with the current mainstream 3D rendering engine, OSG is practical, economical, and easy to expand. Therefore, OSG is widely used in the fields of virtual simulation, virtual reality, science and engineering visualization. In this paper, a dynamic and interactive ground LiDAR data visualization platform is constructed based on the OSG and the cross-platform C++ application development framework Qt. In view of the point cloud data of .txt format and the triangulation network data file of .obj format, the functions of 3D laser point cloud and triangulation network data display are realized. It is proved by experiments that the platform is of strong practical value as it is easy to operate and provides good interaction.

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.

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.

Microphysical parameters of cirrus clouds using lidar at a tropical station, Gadanki, Tirupati (13.5° N, 79.2°E), India

Science.gov (United States)

Satyanarayana, M.; Radhakrishnan, S.-R.; Krishnakumar, V.; Mahadevan Pillai, V. P.; Raghunath, K.

2008-12-01

Cirrus clouds have been identified as one of the most uncertain component in the atmospheric research. It is known that cirrus clouds modulate the earth's climate through direct and indirect modification of radiation. The role of cirrus clouds depends mainly on their microphysical properties. To understand cirrus clouds better, we must observe and characterize their properties. In-situ observation of such clouds is a challenging experiment, as the clouds are located at high altitudes. Active remote sensing method based on lidar can detect high and thin cirrus clouds with good spatial and temporal resolution. We present the result obtained on the microphysical properties of the cirrus clouds at two Tropical stations namely Gadhanki, Tirupati (13.50 N, 79.20 E), India and Trivandrum (13.50 N, 770 E) Kerala, India from the ground based pulsed Nd: YAG lidar systems installed at the stations. A variant of the widely used Klett's lidar inversion method with range dependent scattering ratio is used for the present study for the retrieval of aerosol extinction and microphysical parameters of cirrus cloud.

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.

Atmospheric pressure and temperature profiling using near IR differential absorption lidar

Science.gov (United States)

Korb, C. L.; Schwemmer, G. K.; Dombrowski, M.; Weng, C. Y.

1983-01-01

The present investigation is concerned with differential absorption lidar techniques for remotely measuring the atmospheric temperature and pressure profile, surface pressure, and cloud top pressure-height. The procedure used in determining the pressure is based on the conduction of high-resolution measurements of absorption in the wings of lines in the oxygen A band. Absorption with respect to these areas is highly pressure sensitive in connection with the mechanism of collisional line broadening. The method of temperature measurement utilizes a determination of the absorption at the center of a selected line in the oxygen A band which originates from a quantum state with high ground state energy.

Application of the Garrlic Algorithm for the Characterization of Dust and Marine Particles Utilizing the Lidar-Sunphotometer Synergy

Directory of Open Access Journals (Sweden)

Tsekeri Alexandra

2016-01-01

Full Text Available The importance of studying the vertical distribution of aerosol plumes is prominent in regional and climate studies. The new Generalized Aerosol Retrieval from Radiometer and Lidar Combined data algorithm (GARRLiC provides this opportunity combining active and passive ground-based remote sensing from lidar and sunphotometer measurements. Here, we utilize GARRLiC capabilities for the characterization of Saharan dust and marine particles at the Eastern Mediterranean region during the Characterization of Aerosol mixtures of Dust And Marine origin Experiment (CHARADMExp. Two different case studies are presented, a dust-dominated case which we managed to characterize successfully in terms of the particle microphysical properties and their vertical distribution and a case of two separate layers of marine and dust particles for which the characterization proved to be more challenging.

Damage Assessment for Disaster Relief Efforts in Urban Areas Using Optical Imagery and LiDAR Data

Science.gov (United States)

Bahr, Thomas

2014-05-01

Imagery combined with LiDAR data and LiDAR-derived products provides a significant source of geospatial data which is of use in disaster mitigation planning. Feature rich building inventories can be constructed from tools with 3D rooftop extraction capabilities, and two dimensional outputs such as DSMs and DTMs can be used to generate layers to support routing efforts in Spatial Analyst and Network Analyst workflows. This allows us to leverage imagery and LiDAR tools for disaster mitigation or other scenarios. Software such as ENVI, ENVI LiDAR, and ArcGIS® Spatial and Network Analyst can therefore be used in conjunction to help emergency responders route ground teams in support of disaster relief efforts. This is exemplified by a case study against the background of the magnitude 7.0 earthquake that struck Haiti's capital city of Port-au-Prince on January 12, 2010. Soon after, both LiDAR data and an 8-band WorldView-2 scene were collected to map the disaster zone. The WorldView-2 scene was orthorectified and atmospherically corrected in ENVI prior to use. ENVI LiDAR was used to extract the DSM, DTM, buildings, and debris from the LiDAR data point cloud. These datasets provide a foundation for the 2D portion of the analysis. As the data was acquired over an area of dense urbanization, the majority of ground surfaces are roads, and standing buildings and debris are actually largely separable on the basis of elevation classes. To extract the road network of Port-au-Prince, the LiDAR-based feature height information was fused with the WorldView-2 scene, using ENVI's object-based feature extraction approach. This road network was converted to a network dataset for further analysis by the ArcGIS Network Analyst. For the specific case of Haiti, the distribution of blue tarps, used as accommodations for refugees, provided a spectrally distinct target. Pure blue tarp pixel spectra were selected from the WorldView-2 scene and input as a reference into ENVI's Spectral Angle

Application of a multiple scattering model to estimate optical depth, lidar ratio and ice crystal effective radius of cirrus clouds observed with lidar.

Science.gov (United States)

Gouveia, Diego; Baars, Holger; Seifert, Patric; Wandinger, Ulla; Barbosa, Henrique; Barja, Boris; Artaxo, Paulo; Lopes, Fabio; Landulfo, Eduardo; Ansmann, Albert

2018-04-01

Lidar measurements of cirrus clouds are highly influenced by multiple scattering (MS). We therefore developed an iterative approach to correct elastic backscatter lidar signals for multiple scattering to obtain best estimates of single-scattering cloud optical depth and lidar ratio as well as of the ice crystal effective radius. The approach is based on the exploration of the effect of MS on the molecular backscatter signal returned from above cloud top.

Laser safety in design of near-infrared scanning LIDARs

Science.gov (United States)

Zhu, X.; Elgin, D.

2015-05-01

3D LIDARs (Light Detection and Ranging) with 1.5μm nanosecond pulse lasers have been increasingly used in different applications. The main reason for their popularity is that these LIDARs have high performance while at the same time can be made eye-safe. Because the laser hazard effect on eyes or skin at this wavelength region (industrial mining applications. We have incorporated the laser safety requirements in the LIDAR design and conducted laser safety analysis for different operational scenarios. While 1.5μm is normally said to be the eye-safe wavelength, in reality a high performance 3D LIDAR needs high pulse energy, small beam size and high pulse repetition frequency (PRF) to achieve long range, high resolution and high density images. The resulting radiant exposure of its stationary beam could be many times higher than the limit for a Class 1 laser device. Without carefully choosing laser and scanning parameters, including field-of-view, scan speed and pattern, a scanning LIDAR can't be eye- or skin-safe based only on its wavelength. This paper discusses the laser safety considerations in the design of eye-safe scanning LIDARs, including laser pulse energy, PRF, beam size and scanning parameters in two basic designs of scanning mechanisms, i.e. galvanometer based scanner and Risley prism based scanner. The laser safety is discussed in terms of device classification, nominal ocular hazard distance (NOHD) and safety glasses optical density (OD).

On the factors governing water vapor turbulence mixing in the convective boundary layer over land: Concept and data analysis technique using ground-based lidar measurements.

Science.gov (United States)

Pal, Sandip

2016-06-01

The convective boundary layer (CBL) turbulence is the key process for exchanging heat, momentum, moisture and trace gases between the earth's surface and the lower part of the troposphere. The turbulence parameterization of the CBL is a challenging but important component in numerical models. In particular, correct estimation of CBL turbulence features, parameterization, and the determination of the contribution of eddy diffusivity are important for simulating convection initiation, and the dispersion of health hazardous air pollutants and Greenhouse gases. In general, measurements of higher-order moments of water vapor mixing ratio (q) variability yield unique estimates of turbulence in the CBL. Using the high-resolution lidar-derived profiles of q variance, third-order moment, and skewness and analyzing concurrent profiles of vertical velocity, potential temperature, horizontal wind and time series of near-surface measurements of surface flux and meteorological parameters, a conceptual framework based on bottom up approach is proposed here for the first time for a robust characterization of the turbulent structure of CBL over land so that our understanding on the processes governing CBL q turbulence could be improved. Finally, principal component analyses will be applied on the lidar-derived long-term data sets of q turbulence statistics to identify the meteorological factors and the dominant physical mechanisms governing the CBL turbulence features. Copyright © 2016 Elsevier B.V. All rights reserved.

Filtering Photogrammetric Point Clouds Using Standard LIDAR Filters Towards DTM Generation

Science.gov (United States)

Zhang, Z.; Gerke, M.; Vosselman, G.; Yang, M. Y.

2018-05-01

Digital Terrain Models (DTMs) can be generated from point clouds acquired by laser scanning or photogrammetric dense matching. During the last two decades, much effort has been paid to developing robust filtering algorithms for the airborne laser scanning (ALS) data. With the point cloud quality from dense image matching (DIM) getting better and better, the research question that arises is whether those standard Lidar filters can be used to filter photogrammetric point clouds as well. Experiments are implemented to filter two dense matching point clouds with different noise levels. Results show that the standard Lidar filter is robust to random noise. However, artefacts and blunders in the DIM points often appear due to low contrast or poor texture in the images. Filtering will be erroneous in these locations. Filtering the DIM points pre-processed by a ranking filter will bring higher Type II error (i.e. non-ground points actually labelled as ground points) but much lower Type I error (i.e. bare ground points labelled as non-ground points). Finally, the potential DTM accuracy that can be achieved by DIM points is evaluated. Two DIM point clouds derived by Pix4Dmapper and SURE are compared. On grassland dense matching generates points higher than the true terrain surface, which will result in incorrectly elevated DTMs. The application of the ranking filter leads to a reduced bias in the DTM height, but a slightly increased noise level.

2008 Northwest Florida Water Management District (NWFWMD) Lidar: Eglin Air Force Base, Walton County, FL

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — In the summer of 2008, the Northwest Florida Water Management District collected lidar data over a portion of Walton County, FL (Eglin Air force Base) to support...

Detection scheme for a partially occluded pedestrian based on occluded depth in lidar-radar sensor fusion

Science.gov (United States)

Kwon, Seong Kyung; Hyun, Eugin; Lee, Jin-Hee; Lee, Jonghun; Son, Sang Hyuk

2017-11-01

Object detections are critical technologies for the safety of pedestrians and drivers in autonomous vehicles. Above all, occluded pedestrian detection is still a challenging topic. We propose a new detection scheme for occluded pedestrian detection by means of lidar-radar sensor fusion. In the proposed method, the lidar and radar regions of interest (RoIs) have been selected based on the respective sensor measurement. Occluded depth is a new means to determine whether an occluded target exists or not. The occluded depth is a region projected out by expanding the longitudinal distance with maintaining the angle formed by the outermost two end points of the lidar RoI. The occlusion RoI is the overlapped region made by superimposing the radar RoI and the occluded depth. The object within the occlusion RoI is detected by the radar measurement information and the occluded object is estimated as a pedestrian based on human Doppler distribution. Additionally, various experiments are performed in detecting a partially occluded pedestrian in outdoor as well as indoor environments. According to experimental results, the proposed sensor fusion scheme has much better detection performance compared to the case without our proposed method.

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

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

A comparison of two open source LiDAR surface classification algorithms

Science.gov (United States)

Wade T. Tinkham; Hongyu Huang; Alistair M.S. Smith; Rupesh Shrestha; Michael J. Falkowski; Andrew T. Hudak; Timothy E. Link; Nancy F. Glenn; Danny G. Marks

2011-01-01

With the progression of LiDAR (Light Detection and Ranging) towards a mainstream resource management tool, it has become necessary to understand how best to process and analyze the data. While most ground surface identification algorithms remain proprietary and have high purchase costs; a few are openly available, free to use, and are supported by published results....

Methodology for obtaining wind gusts using Doppler lidar

DEFF Research Database (Denmark)

Suomi, Irene; Gryning, Sven-Erik; O'Connor, Ewan J.

2017-01-01

reduced the bias in the Doppler lidar gust factors from 0.07 to 0.03 and can be improved further to reduce the bias by using a realistic estimate of turbulence. Wind gust measurements are often prone to outliers in the time series, because they represent the maximum of a (moving-averaged) horizontal wind...... detection also outperformed the traditional Doppler lidar quality assurance method based on carrier-to-noise ratio, by removing additional unrealistic outliers present in the time series.......A new methodology is proposed for scaling Doppler lidar observations of wind gusts to make them comparable with those observed at a meteorological mast. Doppler lidars can then be used to measure wind gusts in regions and heights where traditional meteorological mast measurements are not available...

Application of a multiple scattering model to estimate optical depth, lidar ratio and ice crystal effective radius of cirrus clouds observed with lidar.

Directory of Open Access Journals (Sweden)

Gouveia Diego

2018-01-01

Full Text Available Lidar measurements of cirrus clouds are highly influenced by multiple scattering (MS. We therefore developed an iterative approach to correct elastic backscatter lidar signals for multiple scattering to obtain best estimates of single-scattering cloud optical depth and lidar ratio as well as of the ice crystal effective radius. The approach is based on the exploration of the effect of MS on the molecular backscatter signal returned from above cloud top.

A spinner-integrated wind lidar for enhanced wind turbine control

DEFF Research Database (Denmark)

Mikkelsen, Torben; Angelou, Nikolas; Hansen, Kasper Hjorth

2013-01-01

A field test with a continuous wave wind lidar (ZephIR) installed in the rotating spinner of a wind turbine for unimpeded preview measurements of the upwind approaching wind conditions is described. The experimental setup with the wind lidar on the tip of the rotating spinner of a large 80 m roto...... of the spinner lidar data, is investigated. Finally, the potential for enhancing turbine control and performance based on wind lidar preview measurements in combination with feed-forward enabled turbine controllers is discussed. Copyright © 2012 John Wiley & Sons, Ltd....

Turbulence characterization from a forward-looking nacelle lidar

DEFF Research Database (Denmark)

Peña, Alfredo; Mann, Jakob; Dimitrov, Nikolay Krasimirov

2017-01-01

of lidars were installed on the nacelle of a wind turbine. Comparison of the lidar-based along-wind unfiltered variances with those from a cup anemometer installed on a meteorological mast close to the turbine shows a bias of just 2 %. The ratios of the unfiltered and filtered radial velocity variances...

A New 3D Object Pose Detection Method Using LIDAR Shape Set.

Science.gov (United States)

Kim, Jung-Un; Kang, Hang-Bong

2018-03-16

In object detection systems for autonomous driving, LIDAR sensors provide very useful information. However, problems occur because the object representation is greatly distorted by changes in distance. To solve this problem, we propose a LIDAR shape set that reconstructs the shape surrounding the object more clearly by using the LIDAR point information projected on the object. The LIDAR shape set restores object shape edges from a bird's eye view by filtering LIDAR points projected on a 2D pixel-based front view. In this study, we use this shape set for two purposes. The first is to supplement the shape set with a LIDAR Feature map, and the second is to divide the entire shape set according to the gradient of the depth and density to create a 2D and 3D bounding box proposal for each object. We present a multimodal fusion framework that classifies objects and restores the 3D pose of each object using enhanced feature maps and shape-based proposals. The network structure consists of a VGG -based object classifier that receives multiple inputs and a LIDAR-based Region Proposal Networks (RPN) that identifies object poses. It works in a very intuitive and efficient manner and can be extended to other classes other than vehicles. Our research has outperformed object classification accuracy (Average Precision, AP) and 3D pose restoration accuracy (3D bounding box recall rate) based on the latest studies conducted with KITTI data sets.

Multistatic Aerosol Cloud Lidar in Space: A Theoretical Perspective

Science.gov (United States)

Mishchenko, Michael I.; Alexandrov, Mikhail D.; Cairns, Brian; Travis, Larry D.

2016-01-01

Accurate aerosol and cloud retrievals from space remain quite challenging and typically involve solving a severely ill-posed inverse scattering problem. In this Perspective, we formulate in general terms an aerosol and aerosol-cloud interaction space mission concept intended to provide detailed horizontal and vertical profiles of aerosol physical characteristics as well as identify mutually induced changes in the properties of aerosols and clouds. We argue that a natural and feasible way of addressing the ill-posedness of the inverse scattering problem while having an exquisite vertical-profiling capability is to fly a multistatic (including bistatic) lidar system. We analyze theoretically the capabilities of a formation-flying constellation of a primary satellite equipped with a conventional monostatic (backscattering) lidar and one or more additional platforms each hosting a receiver of the scattered laser light. If successfully implemented, this concept would combine the measurement capabilities of a passive multi-angle multi-spectral polarimeter with the vertical profiling capability of a lidar; address the ill-posedness of the inverse problem caused by the highly limited information content of monostatic lidar measurements; address the ill-posedness of the inverse problem caused by vertical integration and surface reflection in passive photopolarimetric measurements; relax polarization accuracy requirements; eliminate the need for exquisite radiative-transfer modeling of the atmosphere-surface system in data analyses; yield the day-and-night observation capability; provide direct characterization of ground-level aerosols as atmospheric pollutants; and yield direct measurements of polarized bidirectional surface reflectance. We demonstrate, in particular, that supplementing the conventional backscattering lidar with just one additional receiver flown in formation at a scattering angle close to 170deg can dramatically increase the information content of the

Pointing Knowledge for SPARCLE and Space-Based Doppler Wind Lidars in General

Science.gov (United States)

Emmitt, G. D.; Miller, T.; Spiers, G.

1999-01-01

The SPAce Readiness Coherent Lidar Experiment (SPARCLE) will fly on a space shuttle to demonstrate the use of a coherent Doppler wind lidar to accurately measure global tropospheric winds. To achieve the LOS (Line of Sight) accuracy goal of approx. m/s, the lidar system must be able to account for the orbiter's velocity (approx. 7750 m/s) and the rotational component of the earth's surface motion (approx. 450 m/s). For SPARCLE this requires knowledge of the attitude (roll, pitch and yaw) of the laser beam axis within an accuracy of 80 microradians. (approx. 15 arcsec). Since SPARCLE can not use a dedicated star tracker from its earth-viewing orbiter bay location, a dedicated GPS/INS (Global Positioning System/Inertial Navigation System) will be attached to the lidar instrument rack. Since even the GPS/INS has unacceptable drifts in attitude information, the SPARCLE team has developed a way to periodically scan the instrument itself to obtain less than 10 microradian (2 arcsec) attitude knowledge accuracy that can then be used to correct the GPS/INS output on a 30 minute basis.

Lidar observations of low-level wind reversals over the Gulf of Lion and characterization of their impact on the water vapour variability

Science.gov (United States)

Di Girolamo, Paolo; Flamant, Cyrille; Cacciani, Marco; Summa, Donato; Stelitano, Dario; Richard, Evelyne; Ducrocq, Véronique; Fourrie, Nadia; Said, Frédérique

2017-02-01

Water vapour measurements from a ground-based Raman lidar and an airborne differential absorption lidar, complemented by high resolution numerical simulations from two mesoscale models (Arome-WMED and MESO-NH), are considered to investigate transition events from Mistral/Tramontane to southerly marine flow taking place over the Gulf of Lion in Southern France in the time frame September-October 2012, during the Hydrological Cycle in the Mediterranean Experiment (HyMeX) Special Observation Period 1 (SOP1). Low-level wind reversals associated with these transitions are found to have a strong impact on water vapour transport, leading to a large variability of the water vapour vertical and horizontal distribution. The high spatial and temporal resolution of the lidar data allow to monitor the time evolution of the three-dimensional water vapour field during these transitions from predominantly northerly Mistral/Tramontane flow to a predominantly southerly flow, allowing to identify the quite sharp separation between these flows, which is also quite well captured by the mesoscale models.

Lidar for Wind and Optical Turbulence Profiling

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Fastig Shlomo

2018-01-01

Full Text Available A field campaign for the comparison investigation of systems to measure wind and optical turbulence profiles was conducted in northern Germany. The experimental effort was to compare the performance of the LIDAR, SODAR-RASS and ultrasonic anemometers for the measurement of the above mentioned atmospheric parameters. Soreq's LIDAR is a fiber laser based system demonstrator for the vertical profiling of the wind and turbulence, based on the correlation of aerosol density variations. It provides measurements up to 350m with 20m resolution.

Ground-based photo monitoring

Science.gov (United States)

Frederick C. Hall

2000-01-01

Ground-based photo monitoring is repeat photography using ground-based cameras to document change in vegetation or soil. Assume those installing the photo location will not be the ones re-photographing it. This requires a protocol that includes: (1) a map to locate the monitoring area, (2) another map diagramming the photographic layout, (3) type and make of film such...

Raman lidar water vapor profiling over Warsaw, Poland

Science.gov (United States)

Stachlewska, Iwona S.; Costa-Surós, Montserrat; Althausen, Dietrich

2017-09-01

Water vapor mixing ratio and relative humidity profiles were derived from the multi-wavelength Raman PollyXT lidar at the EARLINET site in Warsaw, using the Rayleigh molecular extinction calculation based on atmospheric temperature and pressure from three different sources: i) the standard atmosphere US 62, ii) the Global Data Assimilation System (GDAS) model output, and iii) the WMO 12374 radiosoundings launched at Legionowo. With each method, 136 midnight relative humidity profiles were obtained for lidar observations from July 2013 to August 2015. Comparisons of these profiles showed in favor of the latter method (iii), but it also indicated that the other two data sources could replace it, if necessary. Such use was demonstrated for an automated retrieval of water vapor mixing ratio from dusk until dawn on 19/20 March 2015; a case study related to an advection of biomass burning aerosol from forest fires over Ukraine. Additionally, an algorithm that applies thresholds to the radiosounding relative humidity profiles to estimate macro-physical cloud vertical structure was used for the first time on the Raman lidar relative humidity profiles. The results, based on a subset of 66 profiles, indicate that below 6 km cloud bases/tops can be successfully obtained in 53% and 76% cases from lidar and radiosounding profiles, respectively. Finally, a contribution of the lidar derived mean relative humidity to cloudy conditions within the range of 0.8 to 6.2 km, in comparison to clear-sky conditions, was estimated.

Performances of a HGCDTE APD based direct detection lidar at 2 μm. Application to dial measurements

Science.gov (United States)

Gibert, Fabien; Dumas, Arnaud; Rothman, Johan; Edouart, Dimitri; Cénac, Claire; Pellegrino, Jessica

2018-04-01

A lidar receiver with a direct detection chain adapted to a HgCdTe APD based detector with electric cooling is associated to a 2.05 μm Ho :YLF pulsed dual wavelength single mode transmitter to provide the first atmospheric lidar measurements using this technology. Experiments confirm the outstanding sensitivity of the detector and hightligth its huge potential for DIAL measurements of trace gas (CO2 and H2O) in this spectral domain. Performances of coherent vs direct detection at 2.05 μm is assessed.

Performances of a HGCDTE APD based direct detection lidar at 2 μm. Application to dial measurements

Directory of Open Access Journals (Sweden)

Gibert Fabien

2018-01-01

Full Text Available A lidar receiver with a direct detection chain adapted to a HgCdTe APD based detector with electric cooling is associated to a 2.05 μm Ho :YLF pulsed dual wavelength single mode transmitter to provide the first atmospheric lidar measurements using this technology. Experiments confirm the outstanding sensitivity of the detector and hightligth its huge potential for DIAL measurements of trace gas (CO2 and H2O in this spectral domain. Performances of coherent vs direct detection at 2.05 μm is assessed.

LiDAR Scan Matching Aided Inertial Navigation System in GNSS-Denied Environments.

Science.gov (United States)

Tang, Jian; Chen, Yuwei; Niu, Xiaoji; Wang, Li; Chen, Liang; Liu, Jingbin; Shi, Chuang; Hyyppä, Juha

2015-07-10

A new scan that matches an aided Inertial Navigation System (INS) with a low-cost LiDAR is proposed as an alternative to GNSS-based navigation systems in GNSS-degraded or -denied environments such as indoor areas, dense forests, or urban canyons. In these areas, INS-based Dead Reckoning (DR) and Simultaneous Localization and Mapping (SLAM) technologies are normally used to estimate positions as separate tools. However, there are critical implementation problems with each standalone system. The drift errors of velocity, position, and heading angles in an INS will accumulate over time, and on-line calibration is a must for sustaining positioning accuracy. SLAM performance is poor in featureless environments where the matching errors can significantly increase. Each standalone positioning method cannot offer a sustainable navigation solution with acceptable accuracy. This paper integrates two complementary technologies-INS and LiDAR SLAM-into one navigation frame with a loosely coupled Extended Kalman Filter (EKF) to use the advantages and overcome the drawbacks of each system to establish a stable long-term navigation process. Static and dynamic field tests were carried out with a self-developed Unmanned Ground Vehicle (UGV) platform-NAVIS. The results prove that the proposed approach can provide positioning accuracy at the centimetre level for long-term operations, even in a featureless indoor environment.

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

Virtual Surveyor based Object Extraction from Airborne LiDAR data

Science.gov (United States)

Habib, Md. Ahsan

Topographic feature detection of land cover from LiDAR data is important in various fields - city planning, disaster response and prevention, soil conservation, infrastructure or forestry. In recent years, feature classification, compliant with Object-Based Image Analysis (OBIA) methodology has been gaining traction in remote sensing and geographic information science (GIS). In OBIA, the LiDAR image is first divided into meaningful segments called object candidates. This results, in addition to spectral values, in a plethora of new information such as aggregated spectral pixel values, morphology, texture, context as well as topology. Traditional nonparametric segmentation methods rely on segmentations at different scales to produce a hierarchy of semantically significant objects. Properly tuned scale parameters are, therefore, imperative in these methods for successful subsequent classification. Recently, some progress has been made in the development of methods for tuning the parameters for automatic segmentation. However, researchers found that it is very difficult to automatically refine the tuning with respect to each object class present in the scene. Moreover, due to the relative complexity of real-world objects, the intra-class heterogeneity is very high, which leads to over-segmentation. Therefore, the method fails to deliver correctly many of the new segment features. In this dissertation, a new hierarchical 3D object segmentation algorithm called Automatic Virtual Surveyor based Object Extracted (AVSOE) is presented. AVSOE segments objects based on their distinct geometric concavity/convexity. This is achieved by strategically mapping the sloping surface, which connects the object to its background. Further analysis produces hierarchical decomposition of objects to its sub-objects at a single scale level. Extensive qualitative and qualitative results are presented to demonstrate the efficacy of this hierarchical segmentation approach.

High Spectral Resolution Lidar Based on a Potassium Faraday Dispersive Filter for Daytime Temperature Measurement

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Abo Makoto

2016-01-01

Full Text Available In this paper, a new high-spectral-resolution lidar technique is proposed for measuring the profiles of atmospheric temperature in daytime. Based on the theory of high resolution Rayleigh scattering, the feasibility and advantages of using potassium (K Faraday dispersive optical filters as blocking filters for measuring atmospheric temperature are demonstrated with a numerical simulation. It was found that temperature profiles could be measured within 1K error for the height of 9 km with a 500 m range resolution in 60 min by using laser pulses with 1mJ/pulse and 1 kHz, and a 50 cm diameter telescope. Furthermore, we are developing compact pulsed laser system for temperature lidar transmitter.

The ten-year pattern (1978-1987) of stratospheric aerosol loading using ground-based radiometry

International Nuclear Information System (INIS)

Michalsky, J.J.; Pearson, E.W.; LeBaron, B.A.

1988-09-01

In this paper the procedures used to obtain a stratospheric measurement with ground-based sun radiometry are reviewed briefly. The five-wavelength optical depths are then used to study the evolution of aerosol size during the decade. The time history of loading from the instruments described are compared. Particular emphasis will be placed on the Garmisch-Partenkirchen data because their latitude is very nearly that of the PNL site. The most useful data for this study are those observational records that measure total stratospheric aerosol burden and include the early period and continue throughout the eruption and decay of El Chichon. The lidar data from Langley Research Center and Fraunhofer-Institute for Atmospheric Environmental Research at Garmisch-Partenkirchen, the SAM II satellite data, and the Pacific Northwest Laboratory (PNL) sun radiometry are the published contiguous measurements of the stratosphere aerosol burden during this period. 16 refs., 6 figs

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.

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

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J. F. Newman

2017-02-01

Full Text Available Remote-sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers for the measurement of wind speed and direction. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, vertically profiling lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry. In this work, a new turbulence error reduction algorithm for lidars is described. The Lidar Turbulence Error Reduction Algorithm, L-TERRA, can be applied using only data from a stand-alone vertically profiling lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of physics-based corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. The lessons learned from creating the L-TERRA model for a WINDCUBE v2 lidar can also be applied to other lidar devices. L-TERRA was tested on data from two sites in the Southern Plains region of the United States. The physics-based corrections in L-TERRA brought regression line slopes much closer to 1 at both sites and significantly reduced the sensitivity of lidar turbulence errors to atmospheric stability. The accuracy of machine