European Space Agency lidar development programs for remote sensing of the atmosphere

Science.gov (United States)

Armandillo, Errico

1992-12-01

Active laser remote sensing from space is considered an important step forward in the understanding of the processes which regulate weather and climate changes. The planned launching into polar orbit in the late 1990s of a series of dedicated Earth observation satellites offer new possibilities for flying lidar in space. Among the various lidar candidates, ESA has recognized in the backscattering lidar and Doppler wind lidar the instruments which can most contribute to the Earth observation program. To meet the schedule of the on-coming flight opportunities, ESA has been engaged over the past years in a preparatory program aimed to define the instruments and ensure timely availability of the critical components. This paper reviews the status of the ongoing developments and highlights the critical issues addressed.

Advancing Atmosphere-Ocean Remote Sensing with Spaceborne High Spectral Resolution Lidar

Science.gov (United States)

Hostetler, C. A.; Behrenfeld, M. J.; Chepfer, H.; Hu, Y.; Hair, J. W.; Trepte, C. R.; Winker, D. M.; Ferrare, R. A.; Burton, S. P.; Scarino, A. J.; Powell, K. A.; Michaud, J.

2016-12-01

More than 1600 publications employing observations from the CALIOP lidar on CALIPSO testify to the value of spaceborne lidar for aerosol and cloud remote sensing. Recent publications have shown the value of CALIOP data for retrievals of key ocean carbon cycle stocks. In this presentation we focus on the advantages of a more advanced technique, High Spectral Resolution Lidar (HSRL), for aerosol, cloud, and ocean remote sensing. An atmosphere-ocean optimized HSRL achieves greater accuracy over the standard backscatter lidar technique for retrievals of aerosol and cloud extinction and backscatter profiles, provides additional capability to retrieve aerosol and cloud microphysical parameters, and enables vertically-resolved characterization of scattering and absorption properties of suspended and dissolved materials in the ocean. Numerous publications highlight the synergy of coincident CALIOP and passive A-train observations for studies of aerosol-cloud radiative effects and cloud-climate feedback. Less appreciated is the complementarity that would exist between an optimized spaceborne lidar and passive ocean color. An optimized HSRL flown in formation with the Plankton, Aerosol, and ocean Ecosystem (PACE) mission would provide phytoplankton vertical distribution, which is needed for accurately estimating net primary productivity but absent in the PACE ocean color data. The HSRL would also provide data needed to improve atmospheric correction schemes in ocean color retrievals. Because lidar provides measurements both night and day, through tenuous clouds and aerosol layers, and in holes between clouds, the sampling achieved is highly complementary to passive radiometry, providing data in important high latitude regions where ocean color data are sparse or nonexistent. In this presentation we will discuss 1) relevant aerosol, cloud, and ocean retrievals from airborne HSRL field missions; 2) the advantages of an optimized spaceborne HSRL for aerosol, cloud, and ocean

Remote measurement of atmospheric temperature profiles in clouds with rotational Raman lidar; Fernmessung atmosphaerischer Temperaturprofile in Wolken mit Rotations-Raman-Lidar

Energy Technology Data Exchange (ETDEWEB)

Behrendt, A. [GKSS-Forschungszentrum Geesthacht GmbH (Germany). Inst. fuer Physikalische und Chemische Analytik

2000-07-01

The development of a lidar receiver for remote measurements of atmospheric temperature profiles with the rotational Raman method is described. By a new receiver concept, this instrument allowed for the first time remote temperature measurements without any perturbation by the presence of clouds up to a backscatter ratio of 45. In addition, high efficiency of the spectral separation of atmospheric backscatter signals leads to improved measurement resolution: the minimum integration time needed for a statistical uncertainty < {+-}1 K at, e.g., 10 km height and 960 m height resolution is only 5 minutes. The measurement range extends to over 45 km altitude. Results of field campaigns obtained with the instrument are presented and discussed. In winter 1997/98, the instrument was transferred with the GKSS Raman lidar to Esrange (67.9 N, 21.1 E) in northern Sweden, where pioneering remote measurements of local temperatures in orographically induced polar stratospheric clouds could be carried out. (orig.)

SURFACE FITTING FILTERING OF LIDAR POINT CLOUD WITH WAVEFORM INFORMATION

Directory of Open Access Journals (Sweden)

S. Xing

2017-09-01

Full Text Available Full-waveform LiDAR is an active technology of photogrammetry and remote sensing. It provides more detailed information about objects along the path of a laser pulse than discrete-return topographic LiDAR. The point cloud and waveform information with high quality can be obtained by waveform decomposition, which could make contributions to accurate filtering. The surface fitting filtering method with waveform information is proposed to present such advantage. Firstly, discrete point cloud and waveform parameters are resolved by global convergent Levenberg Marquardt decomposition. Secondly, the ground seed points are selected, of which the abnormal ones are detected by waveform parameters and robust estimation. Thirdly, the terrain surface is fitted and the height difference threshold is determined in consideration of window size and mean square error. Finally, the points are classified gradually with the rising of window size. The filtering process is finished until window size is larger than threshold. The waveform data in urban, farmland and mountain areas from “WATER (Watershed Allied Telemetry Experimental Research” are selected for experiments. Results prove that compared with traditional method, the accuracy of point cloud filtering is further improved and the proposed method has highly practical value.

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

Science.gov (United States)

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

2000-01-01

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

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...

Remote sensing of methane emissions by combining optical similitude absorption spectroscopy (OSAS) and lidar

Science.gov (United States)

Galtier, Sandrine; Anselmo, Christophe; Welschinger, Jean-Yves; Cariou, Jean-Pierre; Sivignon, Jean-François; Miffre, Alain; Rairoux, Patrick

2018-04-01

Monitoring the emission of gases is difficult to achieve in industrial sites and in environments presenting poor infrastructures. Hence, robust methodologies should be developed and coupled to Lidar technology to allow remote sensing of gas emission. OSAS is a new methodology to evaluate gas concentration emission from spectrally integrated differential absorption measurements. Proof of concept of OSAS-Lidar for CH4 emission monitoring is here presented.

Characterization of the EPRI Differential Absorption Lidar (DIAL) System. Final report. [For remote sensing of air pollutants

Energy Technology Data Exchange (ETDEWEB)

Baumgartner, R.A.; Depp, J.G.; Evans, W.E.; Grant, W.B.; Hawley, J.G.; March, R.G.; Murray, E.R.; Proctor, E.K.

1979-12-01

SRI International designed and constructed a DIfferential Absorption Lidar (DIAL) to provide EPRI with a mobile field system for remote measurements of SO/sub 2/, NO/sub 3/, and O/sub 3/. After field testing the lidar was prepared for the sytem calibration testing where lidar measurements were compared to in situ profiles of SO/sub 2/, NO/sub 2/, and O/sub 3/. This two-week field program determined overall system accuracy and reliability in measuring varying ambient gas concentrations. The lidar was then returned to SRI for detailed subsystem performance evaluations. Improvements were made wherever possible, and the lidar was prepared for further systems tests. Tests were made using an NO/sub 2/ sample chamber to simulate a calibrated NO/sub 2/ plume, and ambient measured NO/sub 2/ concentrations were compared with values from a regional air pollutant monitoring station. Following the local calibration and the systems field tests, SRI evaluated the performance and reliability of the EPRI lidar. Based on that evaluation, SRI undertook a major analysis of possible system improvements. Although the remote measuring capability had been successfully demonstrated in the field program, SRI makes several recommendations for systems improvements which would increase the lidar accuracy and reliability.

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

Science.gov (United States)

Popescu, Sorin C.; Nelson, Ross F.

2011-01-01

The Silvilaser 2009 conference held in College Station, Texas, USA, was the ninth conference in the Silvilaser series, which started in 2002 with the international workshop on using lidar (Light Detection and Ranging) for analyzing forest structure, held in Victoria, British Columbia, Canada. Following the Canadian workshop, subsequent forestry-lidar conferences took place in Australia, Sweden, Germany, USA, Japan, Finland, and the United Kingdom (UK). By the time this Silvilaser 2009 special issue of PE&RS is published, the 10th international conference will have been held in Freiburg, Germany, and planning will be ongoing for the 11th meeting to take place in Tasmania, Australia, in October 2011. Papers presented at the 2005 conference held in Blacksburg, Virginia, USA, were assembled in a special issue of PE&RS published in December 2006. Other special issues resulting from previous conferences were published in journals such as the Canadian Journal of Remote Sensing (2003), the Scandinavian Journal of Forest Research (2004), and Japan s Journal of Forest Planning (2008). Given the conference history and the much longer record of publications on lidar applications for estimating forest biophysical parameters, which dates back to the early 1980s, we may consider lidar an established remote sensing technology for characterizing forest canopy structure and estimating forest biophysical parameters. Randy Wynne, a professor at Virginia Tech and the final keynote speaker at Silvilaser 2009, made the case that it was time to push 30 years of research into operations, along the lines of what has already been done to good effect in the Scandinavian countries. In Randy s words, it s time to "Just do it!" This special issue includes a selection of papers presented during the 2009 Silvilaser conference, which consisted of eight sections as follows: (1) biomass and carbon stock estimates, (2) tree species and forest type classification, (3) data fusion and integration, (4, 5

Assessing Surface Fuel Hazard in Coastal Conifer Forests through the Use of LiDAR Remote Sensing

Science.gov (United States)

Koulas, Christos

The research problem that this thesis seeks to examine is a method of predicting conventional fire hazards using data drawn from specific regions, namely the Sooke and Goldstream watershed regions in coastal British Columbia. This thesis investigates whether LiDAR data can be used to describe conventional forest stand fire hazard classes. Three objectives guided this thesis: to discuss the variables associated with fire hazard, specifically the distribution and makeup of fuel; to examine the relationship between derived LiDAR biometrics and forest attributes related to hazard assessment factors defined by the Capitol Regional District (CRD); and to assess the viability of the LiDAR biometric decision tree in the CRD based on current frameworks for use. The research method uses quantitative datasets to assess the optimal generalization of these types of fire hazard data through discriminant analysis. Findings illustrate significant LiDAR-derived data limitations, and reflect the literature in that flawed field application of data modelling techniques has led to a disconnect between the ways in which fire hazard models have been intended to be used by scholars and the ways in which they are used by those tasked with prevention of forest fires. It can be concluded that a significant trade-off exists between computational requirements for wildfire simulation models and the algorithms commonly used by field teams to apply these models with remote sensing data, and that CRD forest management practices would need to change to incorporate a decision tree model in order to decrease risk.

Remote sensing of methane emissions by combining optical similitude absorption spectroscopy (OSAS and lidar

Directory of Open Access Journals (Sweden)

Galtier Sandrine

2018-01-01

Full Text Available Monitoring the emission of gases is difficult to achieve in industrial sites and in environments presenting poor infrastructures. Hence, robust methodologies should be developed and coupled to Lidar technology to allow remote sensing of gas emission. OSAS is a new methodology to evaluate gas concentration emission from spectrally integrated differential absorption measurements. Proof of concept of OSAS-Lidar for CH4 emission monitoring is here presented.

Remote sensing of coastal area near Bari : results of marine campaign performed with lidar fluorosensor; Rapporto sulla campagna di misura con LIDAR fluorosensore effettuate sul mare di Bari

Energy Technology Data Exchange (ETDEWEB)

Barbini, R.; Colao, F.; Fantoni, R.; Palucci, A.; Ribezzo, S. [ENEA, Centro Ricerche Frascati, Rome (Italy). Dip. Innovazione

1995-12-01

The lidar fluorosensor, built at ENEA Frascati to remotely monitor the sea-water quality by collecting the water Raman back scattering and induced fluorescence from dispersed oils, suspended matter and chlorophyll, has been employed in a marine campaign in the southern Adriatic sea. To this aim, the lidar fluorosensor has been installed on a coastal guard boat and operated during the cruise. Extensive calibration measurements have been undertaken by using this system, both in laboratory and during the campaigns, to analyze sea water samples taken at several places along the Italian coasts. Absolute values of organic matter, chlorophyll concentrations have been obtained by calibrating the locally and remotely sensed lidar data with standard physical-chemical methods.

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.

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

Science.gov (United States)

Saenz, Edward J.

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

Performance Simulations for a Spaceborne Methane Lidar Mission

Science.gov (United States)

Kiemle, C.; Kawa, Stephan Randolph; Quatrevalet, Mathieu; Browell, Edward V.

2014-01-01

Future spaceborne lidar measurements of key anthropogenic greenhouse gases are expected to close current observational gaps particularly over remote, polar, and aerosol-contaminated regions, where actual in situ and passive remote sensing observation techniques have difficulties. For methane, a "Methane Remote Lidar Mission" was proposed by Deutsches Zentrum fuer Luft- und Raumfahrt and Centre National d'Etudes Spatiales in the frame of a German-French climate monitoring initiative. Simulations assess the performance of this mission with the help of Moderate Resolution Imaging Spectroradiometer and Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations of the earth's surface albedo and atmospheric optical depth. These are key environmental parameters for integrated path differential absorption lidar which uses the surface backscatter to measure the total atmospheric methane column. Results showthat a lidar with an average optical power of 0.45W at 1.6 µm wavelength and a telescope diameter of 0.55 m, installed on a low Earth orbit platform(506 km), will measure methane columns at precisions of 1.2%, 1.7%, and 2.1% over land, water, and snow or ice surfaces, respectively, for monthly aggregated measurement samples within areas of 50 × 50 km2. Globally, the mean precision for the simulated year 2007 is 1.6%, with a standard deviation of 0.7%. At high latitudes, a lower reflectance due to snow and ice is compensated by denser measurements, owing to the orbital pattern. Over key methane source regions such as densely populated areas, boreal and tropical wetlands, or permafrost, our simulations show that the measurement precision will be between 1 and 2%.

Current Research in Lidar Technology Used for the Remote Sensing of Atmospheric Aerosols

Science.gov (United States)

Comerón, Adolfo; Muñoz-Porcar, Constantino; Rocadenbosch, Francesc; Rodríguez-Gómez, Alejandro; Sicard, Michaël

2017-01-01

Lidars are active optical remote sensing instruments with unique capabilities for atmospheric sounding. A manifold of atmospheric variables can be profiled using different types of lidar: concentration of species, wind speed, temperature, etc. Among them, measurement of the properties of aerosol particles, whose influence in many atmospheric processes is important but is still poorly stated, stands as one of the main fields of application of current lidar systems. This paper presents a review on fundamentals, technology, methodologies and state-of-the art of the lidar systems used to obtain aerosol information. Retrieval of structural (aerosol layers profiling), optical (backscatter and extinction coefficients) and microphysical (size, shape and type) properties requires however different levels of instrumental complexity; this general outlook is structured following a classification that attends these criteria. Thus, elastic systems (detection only of emitted frequencies), Raman systems (detection also of Raman frequency-shifted spectral lines), high spectral resolution lidars, systems with depolarization measurement capabilities and multi-wavelength instruments are described, and the fundamentals in which the retrieval of aerosol parameters is based is in each case detailed. PMID:28632170

Dimensionless parameterization of lidar for laser remote sensing of the atmosphere and its application to systems with SiPM and PMT detectors.

Science.gov (United States)

Agishev, Ravil; Comerón, Adolfo; Rodriguez, Alejandro; Sicard, Michaël

2014-05-20

In this paper, we show a renewed approach to the generalized methodology for atmospheric lidar assessment, which uses the dimensionless parameterization as a core component. It is based on a series of our previous works where the problem of universal parameterization over many lidar technologies were described and analyzed from different points of view. The modernized dimensionless parameterization concept applied to relatively new silicon photomultiplier detectors (SiPMs) and traditional photomultiplier (PMT) detectors for remote-sensing instruments allowed predicting the lidar receiver performance with sky background available. The renewed approach can be widely used to evaluate a broad range of lidar system capabilities for a variety of lidar remote-sensing applications as well as to serve as a basis for selection of appropriate lidar system parameters for a specific application. Such a modernized methodology provides a generalized, uniform, and objective approach for evaluation of a broad range of lidar types and systems (aerosol, Raman, DIAL) operating on different targets (backscatter or topographic) and under intense sky background conditions. It can be used within the lidar community to compare different lidar instruments.

Innovative Technique for High-Accuracy Remote Monitoring of Surface Water

Science.gov (United States)

Gisler, A.; Barton-Grimley, R. A.; Thayer, J. P.; Crowley, G.

2016-12-01

Lidar (light detection and ranging) provides absolute depth and topographic mapping capability compared to other remote sensing methods, which is useful for mapping rapidly changing environments such as riverine systems and agricultural waterways. Effectiveness of current lidar bathymetric systems is limited by the difficulty in unambiguously identifying backscattered lidar signals from the water surface versus the bottom, limiting their depth resolution to 0.3-0.5 m. Additionally these are large, bulky systems that are constrained to expensive aircraft-mounted platforms and use waveform-processing techniques requiring substantial computation time. These restrictions are prohibitive for many potential users. A novel lidar device has been developed that allows for non-contact measurements of water depth down to 1 cm with an accuracy and precision of shallow to deep water allowing for shoreline charting, measuring water volume, mapping bottom topology, and identifying submerged objects. The scalability of the technique opens up the ability for handheld or UAS-mounted lidar bathymetric systems, which provides for potential applications currently unavailable to the community. The high laser pulse repetition rate allows for very fine horizontal resolution while the photon-counting technique permits real-time depth measurement and object detection. The enhanced measurement capability, portability, scalability, and relatively low-cost creates the opportunity to perform frequent high-accuracy monitoring and measuring of aquatic environments which is crucial for monitoring water resources on fast timescales. Results from recent campaigns measuring water depth in flowing creeks and murky ponds will be presented which demonstrate that the method is not limited by rough water surfaces and can map underwater topology through moderately turbid water.

Scanning lidar fluorosensor for remote diagnostic of surfaces

Science.gov (United States)

Caneve, Luisa; Colao, Francesco; Fantoni, Roberta; Fiorani, Luca

2013-08-01

Scanning hyperspectral systems based on laser induced fluorescence (LIF) have been developed and realized at the ENEA allowing to obtain information of analytical and qualitative interest on different materials by the study of the emission of fluorescence. This technique, for a surface analysis, is fast, remote, not invasive and specific. A new compact setup capable of fast 2D monochromatic images acquisition on up to 90 different spectral channels in the visible/UV range will be presented. It has been recently built with the aim to increase the performances in terms of space resolution, time resolved capabilities and data acquisition speed. Major achievements have been reached by a critical review of the optical design. The results recently obtained with in-situ measurements of interest for applications in the field of cultural heritage will be shown. 2001 Elsevier Science. All rights reserved

Remote sensing of Sonoran Desert vegetation structure and phenology with ground-based LiDAR

Science.gov (United States)

Sankey, Joel B.; Munson, Seth M.; Webb, Robert H.; Wallace, Cynthia S.A.; Duran, Cesar M.

2015-01-01

Long-term vegetation monitoring efforts have become increasingly important for understanding ecosystem response to global change. Many traditional methods for monitoring can be infrequent and limited in scope. Ground-based LiDAR is one remote sensing method that offers a clear advancement to monitor vegetation dynamics at high spatial and temporal resolution. We determined the effectiveness of LiDAR to detect intra-annual variability in vegetation structure at a long-term Sonoran Desert monitoring plot dominated by cacti, deciduous and evergreen shrubs. Monthly repeat LiDAR scans of perennial plant canopies over the course of one year had high precision. LiDAR measurements of canopy height and area were accurate with respect to total station survey measurements of individual plants. We found an increase in the number of LiDAR vegetation returns following the wet North American Monsoon season. This intra-annual variability in vegetation structure detected by LiDAR was attributable to a drought deciduous shrub Ambrosia deltoidea, whereas the evergreen shrub Larrea tridentata and cactus Opuntia engelmannii had low variability. Benefits of using LiDAR over traditional methods to census desert plants are more rapid, consistent, and cost-effective data acquisition in a high-resolution, 3-dimensional context. We conclude that repeat LiDAR measurements can be an effective method for documenting ecosystem response to desert climatology and drought over short time intervals and at detailed-local spatial scale.

Remote sensing systems – Platforms and sensors: Aerial, satellites, UAVs, optical, radar, and LiDAR: Chapter 1

Science.gov (United States)

Panda, Sudhanshu S.; Rao, Mahesh N.; Thenkabail, Prasad S.; Fitzerald, James E.

2015-01-01

The American Society of Photogrammetry and Remote Sensing defined remote sensing as the measurement or acquisition of information of some property of an object or phenomenon, by a recording device that is not in physical or intimate contact with the object or phenomenon under study (Colwell et al., 1983). Environmental Systems Research Institute (ESRI) in its geographic information system (GIS) dictionary defines remote sensing as “collecting and interpreting information about the environment and the surface of the earth from a distance, primarily by sensing radiation that is naturally emitted or reflected by the earth’s surface or from the atmosphere, or by sending signals transmitted from a device and reflected back to it (ESRI, 2014).” The usual source of passive remote sensing data is the measurement of reflected or transmitted electromagnetic radiation (EMR) from the sun across the electromagnetic spectrum (EMS); this can also include acoustic or sound energy, gravity, or the magnetic field from or of the objects under consideration. In this context, the simple act of reading this text is considered remote sensing. In this case, the eye acts as a sensor and senses the light reflected from the object to obtain information about the object. It is the same technology used by a handheld camera to take a photograph of a person or a distant scenic view. Active remote sensing, however, involves sending a pulse of energy and then measuring the returned energy through a sensor (e.g., Radio Detection and Ranging [RADAR], Light Detection and Ranging [LiDAR]). Thermal sensors measure emitted energy by different objects. Thus, in general, passive remote sensing involves the measurement of solar energy reflected from the Earth’s surface, while active remote sensing involves synthetic (man-made) energy pulsed at the environment and the return signals are measured and recorded.

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.

Multi-Beam Surface Lidar for Lunar and Planetary Mapping

Science.gov (United States)

Bufton, Jack L.; Garvin, James B.

1998-01-01

Surface lidar techniques are now being demonstrated in low Earth orbit with a single beam of pulsed laser radiation at 1064 nm that profiles the vertical structure of Earth surface landforms along the nadir track of a spacecraft. In addition, a profiling laser altimeter, called MOLA, is operating in elliptical Martian orbit and returning surface topography data. These instruments form the basis for suggesting an improved lidar instrument that employs multiple beams for extension of sensor capabilities toward the goal of true, 3-dimensional mapping of the Moon or other similar planetary surfaces. In general the lidar waveform acquired with digitization of a laser echo can be used for laser distance measurement (i.e. range-to-the-surface) by time-of-flight measurement and for surface slope and shape measurements by examining the detailed lidar waveform. This is particularly effective when the intended target is the lunar surface or another planetary body free of any atmosphere. The width of the distorted return pulse is a first order measure of the surface incidence angle, a combination of surface slope and laser beam pointing. Assuming an independent and absolute (with respect to inertial space) measurement of laser beam pointing on the spacecraft, it is possible to derive a surface slope with-respect-to the mean planetary surface or its equipotential gravity surface. Higher-order laser pulse distortions can be interpreted in terms of the vertical relief of the surface or reflectivity variations within the area of the laser beam footprint on the surface.

SF6 laser remote sensing by CO2 laser DIAL lidar

International Nuclear Information System (INIS)

Parvin, P.; Basam, Z.; Zamanipour, Z.; Kariminezhad, H.; Boyook, N.; Borna, F.; Azari, T.; Eshragi, N.; Ataran, A.; Ghods Ahmad Zadeh, R.

2004-01-01

A DIAL system using tunable CO 2 laser has been demonstrated practically for remote sensing of SF 6 components in Mashad Shahid Motahhari Research Complex. Non toxic components of SF 6 as a rare isotope is studied to calibrate the lidar function in several conditions. The whole system enables us to detect ppm amounts of chemical gases as well as pollutants and poisonous species

Modeling plant composition as community continua in a forest landscape with LiDAR and hyperspectral remote sensing.

Science.gov (United States)

Hakkenberg, C R; Peet, R K; Urban, D L; Song, C

2018-01-01

In light of the need to operationalize the mapping of forest composition at landscape scales, this study uses multi-scale nested vegetation sampling in conjunction with LiDAR-hyperspectral remotely sensed data from the G-LiHT airborne sensor to map vascular plant compositional turnover in a compositionally and structurally complex North Carolina Piedmont forest. Reflecting a shift in emphasis from remotely sensing individual crowns to detecting aggregate optical-structural properties of forest stands, predictive maps reflect the composition of entire vascular plant communities, inclusive of those species smaller than the resolution of the remotely sensed imagery, intertwined with proximate taxa, or otherwise obscured from optical sensors by dense upper canopies. Stand-scale vascular plant composition is modeled as community continua: where discrete community-unit classes at different compositional resolutions provide interpretable context for continuous gradient maps that depict n-dimensional compositional complexity as a single, consistent RGB color combination. In total, derived remotely sensed predictors explain 71%, 54%, and 48% of the variation in the first three components of vascular plant composition, respectively. Among all remotely sensed environmental gradients, topography derived from LiDAR ground returns, forest structure estimated from LiDAR all returns, and morphological-biochemical traits determined from hyperspectral imagery each significantly correspond to the three primary axes of floristic composition in the study site. Results confirm the complementarity of LiDAR and hyperspectral sensors for modeling the environmental gradients constraining landscape turnover in vascular plant composition and hold promise for predictive mapping applications spanning local land management to global ecosystem modeling. © 2017 by the Ecological Society of America.

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...

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

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

Sustained high-quality column CO2 measurements from space are required to improve estimates of regional and global scale sources and sinks to attribute them to specific biogeochemical processes for improving models of carbon-climate interactions and to reduce uncertainties in projecting future change. Several studies show that space-borne CO2 measurements offer many advantages particularly over high altitudes, tropics and southern oceans. Current satellite-based sensing provides rapid CO2 monitoring with global-scale coverage and high spatial resolution. However, these sensors are based on passive remote sensing, which involves limitations such as full seasonal and high latitude coverage, poor sensitivity to the lower atmosphere, retrieval complexities and radiation path length uncertainties. CO2 active optical remote sensing is an alternative technique that has the potential to overcome these limitations. The need for space-based CO2 active optical remote sensing using the Integrated Path Differential Absorption (IPDA) lidar has been advocated by the Advanced Space Carbon and Climate Observation of Planet Earth (A-Scope) and Active Sensing of CO2 Emission over Nights, Days, and Seasons (ASCENDS) studies in Europe and the USA. Space-based IPDA systems can provide sustained, high precision and low-bias column CO2 in presence of thin clouds and aerosols while covering critical regions such as high latitude ecosystems, tropical ecosystems, southern ocean, managed ecosystems, urban and industrial systems and coastal systems. At NASA Langley Research Center, technology developments are in progress to provide high pulse energy 2-μm IPDA that enables optimum, lower troposphere weighted column CO2 measurements from space. This system provides simultaneous ranging; information on aerosol and cloud distributions; measurements over region of broken clouds; and reduces influences of surface complexities. Through the continual support from NASA Earth Science Technology Office

IEA Task 32: Wind Lidar Systems for Wind Energy Deployment (LIDAR)

Energy Technology Data Exchange (ETDEWEB)

Kuhn, Martin; Trabucchi, Davide; Clifton, Andrew; Courtney, Mike; Rettenmeier, Andreas

2016-05-25

Under the International Energy Agency Wind Implementing Agreement (IEA Wind) Task 11, researchers started examining novel applications for remote sensing and the issues around them during the 51st topical expert meeting about remote sensing in January 2007. The 59th topical expert meeting organized by Task 11 in October 2009 was also dedicated to remote sensing, and the first draft of the Task's recommended practices on remote sensing was published in January 2013. The results of the Task 11 topical expert meetings provided solid groundwork for a new IEA Wind Task 32 on wind lidar technologies. Members of the wind community identified the need to consolidate the knowledge about wind lidar systems to facilitate their use, and to investigate how to exploit the advantages offered by this technology. This was the motivation that led to the start of IEA Wind Task 32 'Lidar Application for Wind Energy Deployment' in November 2011. The kick-off was meeting was held in May 2012.

Remote sensing of methane with OSAS-lidar on the 2ν3 band Q-branch: Experimental proof

Science.gov (United States)

Galtier, Sandrine; Anselmo, Christophe; Welschinger, Jean-Yves; Sivignon, J. F.; Cariou, Jean-Pierre; Miffre, Alain; Rairoux, Patrick

2018-06-01

Optical sensors based on absorption spectroscopy play a central role in the detection and monitoring of atmospheric trace gases. We here present for the first time the experimental demonstration of OSAS-Lidar on the remote sensing of CH4 in the atmosphere. This new methodology, the OSAS-Lidar, couples the Optical Similitude Absorption Spectroscopy (OSAS) methodology with a light detection and ranging device. It is based on the differential absorption of spectrally integrated signals following Beer Lambert-Bouguer law, which are range-resolved. Its novelty originates from the use of broadband laser spectroscopy and from the mathematical approach used to retrieve the trace gas concentration. We previously applied the OSAS methodology in laboratory on the 2ν3 methane absorption band, centered at the 1665 nm wavelength and demonstrated that the OSAS-methodology is almost independent from atmospheric temperature and pressure. In this paper, we achieve an OSAS-Lidar device capable of observing large concentrations of CH4 released from a methane source directly into the atmosphere. Comparison with a standard in-situ measurement device shows that the path-integrated concentrations retrieved from OSAS-Lidar methodology exhibit sufficient sensitivity (2 000 ppm m) and observational time resolution (1 s) to remotely sense methane leaks in the atmosphere. The coupling of OSAS-lidar with a wind measurement device opens the way to monitor time-resolved methane flux emissions, which is important in regards to future climate mitigation involving regional reduction of CH4 flux emissions.

Remote Sensing of Sonoran Desert Vegetation Structure and Phenology with Ground-Based LiDAR

Directory of Open Access Journals (Sweden)

Joel B. Sankey

2014-12-01

Full Text Available Long-term vegetation monitoring efforts have become increasingly important for understanding ecosystem response to global change. Many traditional methods for monitoring can be infrequent and limited in scope. Ground-based LiDAR is one remote sensing method that offers a clear advancement to monitor vegetation dynamics at high spatial and temporal resolution. We determined the effectiveness of LiDAR to detect intra-annual variability in vegetation structure at a long-term Sonoran Desert monitoring plot dominated by cacti, deciduous and evergreen shrubs. Monthly repeat LiDAR scans of perennial plant canopies over the course of one year had high precision. LiDAR measurements of canopy height and area were accurate with respect to total station survey measurements of individual plants. We found an increase in the number of LiDAR vegetation returns following the wet North American Monsoon season. This intra-annual variability in vegetation structure detected by LiDAR was attributable to a drought deciduous shrub Ambrosia deltoidea, whereas the evergreen shrub Larrea tridentata and cactus Opuntia engelmannii had low variability. Benefits of using LiDAR over traditional methods to census desert plants are more rapid, consistent, and cost-effective data acquisition in a high-resolution, 3-dimensional context. We conclude that repeat LiDAR measurements can be an effective method for documenting ecosystem response to desert climatology and drought over short time intervals and at detailed-local spatial scale.

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

Data.gov (United States)

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

Airborne Lidar Surface Topography (LIST) Simulator

Science.gov (United States)

Yu, Anthony W.; Krainak, Michael A.; Harding, David J.; Abshire, James B.; Sun, Xiaoli; Cavanaugh, John; Valett, Susan; Ramos-Izquierdo, Luis; Winkert, Tom; Plants, Michael;

Developing a portable, autonomous aerosol backscatter lidar for network or remote operations

Science.gov (United States)

Strawbridge, K. B.

2013-03-01

Lidar has the ability to detect the complex vertical structure of the atmosphere and can therefore identify the existence and extent of aerosols with high spatial and temporal resolution, making it well suited for understanding atmospheric dynamics and transport processes. Environment Canada has developed a portable, autonomous lidar system that can be monitored remotely and operated continuously except during precipitation events. The lidar, housed in a small trailer, simultaneously emits two wavelengths of laser light (1064 nm and 532 nm) at energies of approximately 150 mJ/pulse/wavelength and detects the backscatter signal at 1064 nm and both polarizations at 532 nm. For laser energies of this magnitude, the challenge resides in designing a system that meets the airspace safety requirements for autonomous operations. Through the combination of radar technology, beam divergence, laser cavity interlocks and using computer log files, this risk was mitigated. A Continuum Inlite small footprint laser is the backbone of the system because of three design criteria: requiring infrequent flash lamp changes compared to previous Nd : YAG Q-switch lasers, complete software control capability and a built-in laser energy monitoring system. A computer-controlled interface was designed to monitor the health of the system, adjust operational parameters and maintain a climate-controlled environment. Through an Internet connection, it also transmitted the vital performance indicators and data stream to allow the lidar profile data for multiple instruments from near ground to 15 km, every 10 s, to be viewed, in near real-time via a website. The details of the system design and calibration will be discussed and the success of the instrument as tested within the framework of a national lidar network dubbed CORALNet (Canadian Operational Research Aerosol Lidar Network). In addition, the transport of a forest fire plume across the country will be shown as evidenced by the lidar

Developing a portable, autonomous aerosol backscatter lidar for network or remote operations

Directory of Open Access Journals (Sweden)

K. B. Strawbridge

2013-03-01

Full Text Available Lidar has the ability to detect the complex vertical structure of the atmosphere and can therefore identify the existence and extent of aerosols with high spatial and temporal resolution, making it well suited for understanding atmospheric dynamics and transport processes. Environment Canada has developed a portable, autonomous lidar system that can be monitored remotely and operated continuously except during precipitation events. The lidar, housed in a small trailer, simultaneously emits two wavelengths of laser light (1064 nm and 532 nm at energies of approximately 150 mJ/pulse/wavelength and detects the backscatter signal at 1064 nm and both polarizations at 532 nm. For laser energies of this magnitude, the challenge resides in designing a system that meets the airspace safety requirements for autonomous operations. Through the combination of radar technology, beam divergence, laser cavity interlocks and using computer log files, this risk was mitigated. A Continuum Inlite small footprint laser is the backbone of the system because of three design criteria: requiring infrequent flash lamp changes compared to previous Nd : YAG Q-switch lasers, complete software control capability and a built-in laser energy monitoring system. A computer-controlled interface was designed to monitor the health of the system, adjust operational parameters and maintain a climate-controlled environment. Through an Internet connection, it also transmitted the vital performance indicators and data stream to allow the lidar profile data for multiple instruments from near ground to 15 km, every 10 s, to be viewed, in near real-time via a website. The details of the system design and calibration will be discussed and the success of the instrument as tested within the framework of a national lidar network dubbed CORALNet (Canadian Operational Research Aerosol Lidar Network. In addition, the transport of a forest fire plume across the country will be shown as evidenced

Remote detection and recognition of bio-aerosols by laser-induced fluorescense lidar: practical implementation and field tests

Science.gov (United States)

Boreysho, Anatoly; Savin, Andrey; Morozov, Alexey; Konyaev, Maxim; Konovalov, Konstantin

2007-06-01

Recognition of aerosol clouds material at some significant distance is now a key requirement for the wide range of applications. The elastic backscatter lidar have demonstrated high capabilities in aerosol remote detection, cloud real-time mapping at very long distances for low-concentration natural aerosols as well as artificial ones [1]. However, recognition ability is required to make them more relevant. Laser-induced fluorescence (LIF) looks very promising with respect to the recognition problem. New approach based on mobile lidar complex [2] equipped by spectrally-and range-resolved LIF-sensor is described as well as some results of field tests. The LIF-sensor consists of four-harmonics Nd:YAG laser equipped by an output expander to provide final beam divergence camera collimated with the lidar scanning direction. The LIF-lidar is mounted on a truck-based platform (20-feet container) as a part of multi-purpose mobile lidar complex and adjusted for field conditions.

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

Science.gov (United States)

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

2010-01-01

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

A classical model wind turbine wake “blind test” revisited by remote sensing lidars

DEFF Research Database (Denmark)

Sjöholm, Mikael; Angelou, Nikolas; Nielsen, Morten Busk

2017-01-01

One of the classical model wind turbine wake “blind test” experiments1 conducted in the boundary-layer wind tunnel at NTNU in Trondheim and used for benchmarking of numerical flow models has been revisited by remote sensing lidars in a joint experiment called “Lidars For Wind Tunnels” (L4WT) under...... was D=0.894 m and it was designed for a tip speed ratio (TSR) of 6. However, the TSRs used were 3, 6, and 10 at a free-stream velocity of 10 m/s. Due to geometrical constraints imposed by for instance the locations of the wind tunnel windows, all measurements were performed in the very same vertical...... cross-section of the tunnel and the various down-stream distances of the wake, i.e. 1D, 3D, and 5D were achieved by re-positioning the turbine. The approach used allows for unique studies of the influence of the inherent lidar spatial filtering on previously both experimentally and numerically well...

A New Framework for Quantifying Lidar Uncertainty

Energy Technology Data Exchange (ETDEWEB)

Newman, Jennifer, F.; Clifton, Andrew; Bonin, Timothy A.; Churchfield, Matthew J.

2017-03-24

As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards discuss uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device. However, real-world experience has shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we propose the development of a new lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from an operational wind farm to assess the ability of the framework to predict errors in lidar-measured wind speed.

A COMPARISON OF LIDAR REFLECTANCE AND RADIOMETRICALLY CALIBRATED HYPERSPECTRAL IMAGERY

Directory of Open Access Journals (Sweden)

A. Roncat

2016-06-01

Full Text Available In order to retrieve results comparable under different flight parameters and among different flight campaigns, passive remote sensing data such as hyperspectral imagery need to undergo a radiometric calibration. While this calibration, aiming at the derivation of physically meaningful surface attributes such as a reflectance value, is quite cumbersome for passively sensed data and relies on a number of external parameters, the situation is by far less complicated for active remote sensing techniques such as lidar. This fact motivates the investigation of the suitability of full-waveform lidar as a “single-wavelength reflectometer” to support radiometric calibration of hyperspectral imagery. In this paper, this suitability was investigated by means of an airborne hyperspectral imagery campaign and an airborne lidar campaign recorded over the same area. Criteria are given to assess diffuse reflectance behaviour; the distribution of reflectance derived by the two techniques were found comparable in four test areas where these criteria were met. This is a promising result especially in the context of current developments of multi-spectral lidar systems.

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.

Remote Sensing of Vegetation Species Diversity: The Utility of Integrated Airborne Hyperspectral and Lidar Data

Science.gov (United States)

Krause, Keith Stuart

The change, reduction, or extinction of species is a major issue currently facing the Earth. Efforts are underway to measure, monitor, and protect habitats that contain high species diversity. Remote sensing technology shows extreme value for monitoring species diversity by mapping ecosystems and using those land cover maps or other derived data as proxies to species number and distribution. The National Ecological Observatory Network (NEON) Airborne Observation Platform (AOP) consists of remote sensing instruments such as an imaging spectrometer, a full-waveform lidar, and a high-resolution color camera. AOP collected data over the Ordway-Swisher Biological Station (OSBS) in May 2014. A majority of the OSBS site is covered by the Sandhill ecosystem, which contains a very high diversity of vegetation species and is a native habitat for several threatened fauna species. The research presented here investigates ways to analyze the AOP data to map ecosystems at the OSBS site. The research attempts to leverage the high spatial resolution data and study the variability of the data within a ground plot scale along with integrating data from the different sensors. Mathematical features are derived from the data and brought into a decision tree classification algorithm (rpart), in order to create an ecosystem map for the site. The hyperspectral and lidar features serve as proxies for chemical, functional, and structural differences in the vegetation types for each of the ecosystems. K-folds cross validation shows a training accuracy of 91%, a validation accuracy of 78%, and a 66% accuracy using independent ground validation. The results presented here represent an important contribution to utilizing integrated hyperspectral and lidar remote sensing data for ecosystem mapping, by relating the spatial variability of the data within a ground plot scale to a collection of vegetation types that make up a given ecosystem.

Hyperspectral and LiDAR remote sensing of fire fuels in Hawaii Volcanoes National Park.

Science.gov (United States)

Varga, Timothy A; Asner, Gregory P

2008-04-01

Alien invasive grasses threaten to transform Hawaiian ecosystems through the alteration of ecosystem dynamics, especially the creation or intensification of a fire cycle. Across sub-montane ecosystems of Hawaii Volcanoes National Park on Hawaii Island, we quantified fine fuels and fire spread potential of invasive grasses using a combination of airborne hyperspectral and light detection and ranging (LiDAR) measurements. Across a gradient from forest to savanna to shrubland, automated mixture analysis of hyperspectral data provided spatially explicit fractional cover estimates of photosynthetic vegetation, non-photosynthetic vegetation, and bare substrate and shade. Small-footprint LiDAR provided measurements of vegetation height along this gradient of ecosystems. Through the fusion of hyperspectral and LiDAR data, a new fire fuel index (FFI) was developed to model the three-dimensional volume of grass fuels. Regionally, savanna ecosystems had the highest volumes of fire fuels, averaging 20% across the ecosystem and frequently filling all of the three-dimensional space represented by each image pixel. The forest and shrubland ecosystems had lower FFI values, averaging 4.4% and 8.4%, respectively. The results indicate that the fusion of hyperspectral and LiDAR remote sensing can provide unique information on the three-dimensional properties of ecosystems, their flammability, and the potential for fire spread.

Mineralogy and Astrobiology Detection Using Laser Remote Sensing Instrument

Science.gov (United States)

Abedin, M. Nurul; Bradley, Arthur T.; Sharma, Shiv K.; Misra, Anupam K.; Lucey, Paul G.; Mckay, Chistopher P.; Ismail, Syed; Sandford, Stephen P.

2015-01-01

A multispectral instrument based on Raman, laser-induced fluorescence (LIF), laser-induced breakdown spectroscopy (LIBS), and a lidar system provides high-fidelity scientific investigations, scientific input, and science operation constraints in the context of planetary field campaigns with the Jupiter Europa Robotic Lander and Mars Sample Return mission opportunities. This instrument conducts scientific investigations analogous to investigations anticipated for missions to Mars and Jupiter's icy moons. This combined multispectral instrument is capable of performing Raman and fluorescence spectroscopy out to a >100 m target distance from the rover system and provides single-wavelength atmospheric profiling over long ranges (>20 km). In this article, we will reveal integrated remote Raman, LIF, and lidar technologies for use in robotic and lander-based planetary remote sensing applications. Discussions are focused on recently developed Raman, LIF, and lidar systems in addition to emphasizing surface water ice, surface and subsurface minerals, organics, biogenic, biomarker identification, atmospheric aerosols and clouds distributions, i.e., near-field atmospheric thin layers detection for next robotic-lander based instruments to measure all the above-mentioned parameters. OCIS codes: (120.0280) Remote sensing and sensors; (130.0250) Optoelectronics; (280.3640) Lidar; (300.2530) Fluorescence, laser-induced; (300.6450) Spectroscopy, Raman; (300.6365) Spectroscopy, laser induced breakdown

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.

Development of a pulsed 9.5 micron lidar for regional scale O3 measurement

Science.gov (United States)

Stewart, R. W.

1980-01-01

A pulsed infrared lidar system designed for application to the remote sensing of atmospheric trace gases from an airborne platform is described. The system is also capable of measuring the infrared backscatter characteristics of the ocean surface, terrain, cloud, and aerosol targets. The lidar employed is based on dual wavelength pulse energy measurements in the 9-11 micrometer wavelength region.

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

Science.gov (United States)

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

2015-01-01

Background: 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...

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

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

Data.gov (United States)

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

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

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

Science.gov (United States)

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

2006-12-01

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

Development of a Dynamic Lidar Uncertainty Framework

Energy Technology Data Exchange (ETDEWEB)

Newman, Jennifer [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Clifton, Andrew [WindForS; Bonin, Timothy [CIRES/NOAA ESRL; Choukulkar, Aditya [CIRES/NOAA ESRL; Brewer, W. Alan [NOAA ESRL; Delgado, Ruben [University of Maryland Baltimore County

2017-08-07

As wind turbine sizes increase and wind energy expands to more complex and remote sites, remote-sensing devices such as lidars are expected to play a key role in wind resource assessment and power performance testing. The switch to remote-sensing devices represents a paradigm shift in the way the wind industry typically obtains and interprets measurement data for wind energy. For example, the measurement techniques and sources of uncertainty for a remote-sensing device are vastly different from those associated with a cup anemometer on a meteorological tower. Current IEC standards for quantifying remote sensing device uncertainty for power performance testing consider uncertainty due to mounting, calibration, and classification of the remote sensing device, among other parameters. Values of the uncertainty are typically given as a function of the mean wind speed measured by a reference device and are generally fixed, leading to climatic uncertainty values that apply to the entire measurement campaign. However, real-world experience and a consideration of the fundamentals of the measurement process have shown that lidar performance is highly dependent on atmospheric conditions, such as wind shear, turbulence, and aerosol content. At present, these conditions are not directly incorporated into the estimated uncertainty of a lidar device. In this presentation, we describe the development of a new dynamic lidar uncertainty framework that adapts to current flow conditions and more accurately represents the actual uncertainty inherent in lidar measurements under different conditions. In this new framework, sources of uncertainty are identified for estimation of the line-of-sight wind speed and reconstruction of the three-dimensional wind field. These sources are then related to physical processes caused by the atmosphere and lidar operating conditions. The framework is applied to lidar data from a field measurement site to assess the ability of the framework to predict

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

In developing a national energy strategy, the United States has a number of objectives, including increasing economic growth, improving environmental quality, and enhancing national energy security. Wind power contributes to these objectives through the deployment of clean, affordable and reliable domestic energy. To achieve U.S. wind generation objectives, the Wind and Water Power Program within the Department of Energy’s (DOE) Office of Energy Efficiency and Renewable Energy (EERE) instituted the U.S. Offshore Wind: Removing Market Barriers Program in FY 2011. Accurate and comprehensive information on offshore wind resource characteristics across a range of spatial and temporal scales is one market barrier that needs to be addressed through advanced research in remote sensing technologies. There is a pressing need for reliable offshore wind-speed measurements to assess the availability of the potential wind energy resource in terms of power production and to identify any frequently occurring spatial variability in the offshore wind resource that may impact the operational reliability and lifetime of wind turbines and their components and to provide a verification program to validate the “bankability” of the output of these alternative technologies for use by finance institutions for the financing of offshore wind farm construction. The application of emerging remote sensing technologies is viewed as a means to cost-effectively meet the data needs of the offshore wind industry. In particular, scanning and buoy mounted LIDAR have been proposed as a means to obtain accurate offshore wind data at multiple locations without the high cost and regulatory hurdles associated with the construction of offshore meteorological towers. However; before these remote sensing technologies can be accepted the validity of the measured data must be evaluated to ensure their accuracy. The proposed research will establish a unique coastal ocean test-bed in the Mid-Atlantic for

Fluorescence lidar measurements at the archaeological site House of Augustus at Palatino, Rome

Science.gov (United States)

Raimondi, Valentina; Alisi, Chiara; Barup, Kerstin; Bracciale, Maria Paola; Broggi, Alessandra; Conti, Cinzia; Hällström, Jenny; Lognoli, David; Palombi, Lorenzo; Santarelli, Maria Laura; Sprocati, Anna Rosa

2013-10-01

Early diagnostics and documentation fulfill an essential role for an effective planning of conservation and restoration of cultural heritage assets. In particular, remote sensing techniques that do not require the use of scaffolds or lifts, such as fluoresence lidar, can provide useful information to obtain an overall assessment of the status of the investigated surfaces and can be exploited to address analytical studies in selected areas. Here we present the results of a joint Italian-Swedish project focused on documenting and recording the status of some sections of the part closed to the public by using fluorescence hyperspectral imaging lidar. The lidar used a tripled-frequency Nd:YAG laser emitting at 355 nm as excitation source and an intensified, gated 512x512-pixel CCD as detector. The lidar had imaging capabilities thanks to a computer-controlled scanning mirror. The fluorescence characteristics of fresco wall paintings were compared to those of fresco fragments found at the same archaeological site and separately examined in the lab using FT-IR and Raman techniques for the identification of pigments. The fluorescence lidar was also used to remotely detect the growth of phototrophic biodeteriogens on the walls. The fluorescence lidar data were compared with results from biological sampling, cultivation and laboratory analysis by molecular techniques.

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

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

Science.gov (United States)

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

2012-11-01

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

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

Directory of Open Access Journals (Sweden)

A. Roncat

2017-09-01

Full Text Available While airborne lidar has confirmed its leading role in delivering high-resolution 3D topographic information during the last decade, its radiometric potential has not yet been fully exploited. However, with the increasing availability of commercial lidar systems which (a make use of full-waveform information and (b operate at several wavelengths simultaneously, this potential is increasing as well. Radiometric calibration of the full-waveform information mentioned before allows for the derivation of physical target surface parameters such as the backscatter coefficient and a diffuse reflectance value at bottom of atmosphere (BOA, i.e. the target surface. With lidar being an active remote sensing technique, these parameters can be derived from lidar data itself, accompanied by the measurement or estimation of reference data for diffuse reflectance. In contrast to this, such a radiometric calibration for passive hyperspectral imagery (HSI requires the knowledge and/or estimation of much more unknowns. However, in case of corresponding wavelength(s radiometrically calibrated lidar datasets can deliver an areawide reference for BOA reflectance. This paper presents criteria to check where the assumption of diffuse BOA reflectance behaviour is fulfilled and how these criteria are assessed in lidar data; the assessment is illustrated by an extended lidar dataset. Moreover, for this lidar dataset and an HSI dataset recorded over the same area, the corresponding reflectance values are compared for different surface types.

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

Science.gov (United States)

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

2012-12-01

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

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.

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.

Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data

Science.gov (United States)

Pitkänen, T. P.; Käyhkö, N.

2017-08-01

Mapping structural changes in vegetation dynamics has, for a long time, been carried out using satellite images, orthophotos and, more recently, airborne lidar acquisitions. Lidar has established its position as providing accurate material for structure-based analyses but its limited availability, relatively short history, and lack of spectral information, however, are generally impeding the use of lidar data for change detection purposes. A potential solution in respect of detecting both contemporary vegetation structures and their previous trajectories is to combine lidar acquisitions with optical remote sensing data, which can substantially extend the coverage, span and spectral range needed for vegetation mapping. In this study, we tested the simultaneous use of a single low-density lidar data set, a series of Landsat satellite frames and two high-resolution orthophotos to detect vegetation succession related to grassland overgrowth, i.e. encroachment of woody plants into semi-natural grasslands. We built several alternative Random Forest models with different sets of variables and tested the applicability of respective data sources for change detection purposes, aiming at distinguishing unchanged grassland and woodland areas from overgrown grasslands. Our results show that while lidar alone provides a solid basis for indicating structural differences between grassland and woodland vegetation, and orthophoto-generated variables alone are better in detecting successional changes, their combination works considerably better than its respective parts. More specifically, a model combining all the used data sets reduces the total error from 17.0% to 11.0% and omission error of detecting overgrown grasslands from 56.9% to 31.2%, when compared to model constructed solely based on lidar data. This pinpoints the efficiency of the approach where lidar-generated structural metrics are combined with optical and multitemporal observations, providing a workable framework to

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

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

Forest inventory with LiDAR and stereo DSM on Washington department of natural resources lands

Science.gov (United States)

Jacob L. Strunk; Peter J. Gould

2015-01-01

DNR’s forest inventory group has completed its first version of a new remote-sensing based forest inventory system covering 1.4 million acres of DNR forest lands. We use a combination of field plots, lidar, NAIP, and a NAIP-derived canopy surface DSM. Given that height drives many key inventory variables (e.g. height, volume, biomass, carbon), remote-sensing derived...

2012 NRCS-USGS Tupelo, MS Lidar Survey

Data.gov (United States)

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

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.

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

Science.gov (United States)

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

2016-06-01

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

Underwater lidar system: design challenges and application in pollution detection

Science.gov (United States)

Gupta, Pradip; Sankolli, Swati; Chakraborty, A.

2016-05-01

The present remote sensing techniques have imposed limitations in the applications of LIDAR Technology. The fundamental sampling inadequacy of the remote sensing data obtained from satellites is that they cannot resolve in the third spatial dimension, the vertical. This limits our possibilities of measuring any vertical variability in the water column. Also the interaction between the physical and biological process in the oceans and their effects at subsequent depths cannot be modeled with present techniques. The idea behind this paper is to introduce underwater LIDAR measurement system by using a LIDAR mounted on an Autonomous Underwater Vehicle (AUV). The paper introduces working principles and design parameters for the LIDAR mounted AUV (AUV-LIDAR). Among several applications the papers discusses the possible use and advantages of AUV-LIDAR in water pollution detection through profiling of Dissolved Organic Matter (DOM) in water bodies.

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.

Evaluation of Airborne Lidar Elevation Surfaces for Propagation of Coastal Inundation: The Importance of Hydrologic Connectivity

Directory of Open Access Journals (Sweden)

Sandra Poppenga

2015-09-01

Full Text Available Detailed information about coastal inundation is vital to understanding dynamic and populated areas that are impacted by storm surge and flooding. To understand these natural hazard risks, lidar elevation surfaces are frequently used to model inundation in coastal areas. A single-value surface method is sometimes used to inundate areas in lidar elevation surfaces that are below a specified elevation value. However, such an approach does not take into consideration hydrologic connectivity between elevation grids cells resulting in inland areas that should be hydrologically connected to the ocean, but are not. Because inland areas that should drain to the ocean are hydrologically disconnected by raised features in a lidar elevation surface, simply raising the water level to propagate coastal inundation will lead to inundation uncertainties. We took advantage of this problem to identify hydrologically disconnected inland areas to point out that they should be considered for coastal inundation, and that a lidar-based hydrologic surface should be developed with hydrologic connectivity prior to inundation analysis. The process of achieving hydrologic connectivity with hydrologic-enforcement is not new, however, the application of hydrologically-enforced lidar elevation surfaces for improved coastal inundation mapping as approached in this research is innovative. In this article, we propagated a high-resolution lidar elevation surface in coastal Staten Island, New York to demonstrate that inland areas lacking hydrologic connectivity to the ocean could potentially be included in inundation delineations. For inland areas that were hydrologically disconnected, we evaluated if drainage to the ocean was evident, and calculated an area exceeding 11 ha (~0.11 km2 that could be considered in inundation delineations. We also assessed land cover for each inland area to determine the type of physical surfaces that would be potentially impacted if the inland areas

Evaluation of airborne lidar elevation surfaces for propagation of coastal inundation: the importance of hydrologic connectivity

Science.gov (United States)

Poppenga, Sandra K.; Worstell, Bruce B.

2015-01-01

Detailed information about coastal inundation is vital to understanding dynamic and populated areas that are impacted by storm surge and flooding. To understand these natural hazard risks, lidar elevation surfaces are frequently used to model inundation in coastal areas. A single-value surface method is sometimes used to inundate areas in lidar elevation surfaces that are below a specified elevation value. However, such an approach does not take into consideration hydrologic connectivity between elevation grids cells resulting in inland areas that should be hydrologically connected to the ocean, but are not. Because inland areas that should drain to the ocean are hydrologically disconnected by raised features in a lidar elevation surface, simply raising the water level to propagate coastal inundation will lead to inundation uncertainties. We took advantage of this problem to identify hydrologically disconnected inland areas to point out that they should be considered for coastal inundation, and that a lidar-based hydrologic surface should be developed with hydrologic connectivity prior to inundation analysis. The process of achieving hydrologic connectivity with hydrologic-enforcement is not new, however, the application of hydrologically-enforced lidar elevation surfaces for improved coastal inundation mapping as approached in this research is innovative. In this article, we propagated a high-resolution lidar elevation surface in coastal Staten Island, New York to demonstrate that inland areas lacking hydrologic connectivity to the ocean could potentially be included in inundation delineations. For inland areas that were hydrologically disconnected, we evaluated if drainage to the ocean was evident, and calculated an area exceeding 11 ha (~0.11 km2) that could be considered in inundation delineations. We also assessed land cover for each inland area to determine the type of physical surfaces that would be potentially impacted if the inland areas were considered as

2009 - 2011 CA Coastal Conservancy Coastal Lidar Project

Data.gov (United States)

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

Opo lidar sounding of trace atmospheric gases in the 3 - 4 μm spectral range

Science.gov (United States)

Romanovskii, Oleg A.; Sadovnikov, Sergey A.; Kharchenko, Olga V.; Yakovlev, Semen V.

2018-04-01

The applicability of a KTA crystal-based laser system with optical parametric oscillators (OPO) generation to lidar sounding of the atmosphere in the spectral range 3-4 μm is studied in this work. A technique developed for lidar sounding of trace atmospheric gases (TAG) is based on differential absorption lidar (DIAL) method and differential optical absorption spectroscopy (DOAS). The DIAL-DOAS technique is tested to estimate its efficiency for lidar sounding of atmospheric trace gases. The numerical simulation performed shows that a KTA-based OPO laser is a promising source of radiation for remote DIAL-DOAS sounding of the TAGs under study along surface tropospheric paths. A possibility of using a PD38-03-PR photodiode for the DIAL gas analysis of the atmosphere is shown.

Integration of TerraSAR-X, RapidEye and airborne lidar for remote sensing of intertidal bedforms on the upper flats of Norderney (German Wadden Sea)

Science.gov (United States)

Adolph, Winny; Jung, Richard; Schmidt, Alena; Ehlers, Manfred; Heipke, Christian; Bartholomä, Alexander; Farke, Hubert

2017-04-01

The Wadden Sea is a large coastal transition area adjoining the southern North Sea uniting ecological key functions with an important role in coastal protection. The region is strictly protected by EU directives and national law and is a UNESCO World Heritage Site, requiring frequent quality assessments and regular monitoring. In 2014 an intertidal bedform area characterised by alternating crests and water-covered troughs on the tidal flats of the island of Norderney (German Wadden Sea sector) was chosen to test different remote sensing methods for habitat mapping: airborne lidar, satellite-based radar (TerraSAR-X) and electro-optical sensors (RapidEye). The results revealed that, although sensitive to different surface qualities, all sensors were able to image the bedforms. A digital terrain model generated from the lidar data shows crests and slopes of the bedforms with high geometric accuracy in the centimetre range, but high costs limit the operation area. TerraSAR-X data enabled identifying the positions of the bedforms reflecting the residual water in the troughs also with a high resolution of up to 1.1 m, but with larger footprints and much higher temporal availability. RapidEye data are sensitive to differences in sediment moisture employed to identify crest areas, slopes and troughs, with high spatial coverage but the lowest resolution (6.5 m). Monitoring concepts may differ in their remote sensing requirements regarding areal coverage, spatial and temporal resolution, sensitivity and geometric accuracy. Also financial budgets limit the selection of sensors. Thus, combining differing assets into an integrated concept of remote sensing contributes to solving these issues.

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.

Analysis of inflow parameters using LiDARs

NARCIS (Netherlands)

Giyanani, A.H.; Bierbooms, W.A.A.M.; Van Bussel, G.J.W.

2014-01-01

Remote sensing of the atmospheric variables with the use of LiDAR is a relatively new technique for wind resource assessment and oncoming wind prediction in wind energy. The validation of LiDAR measurements and comparisons with other sensing elements thus, is of high importance for further

2003 Oahu Coastline Lidar

Data.gov (United States)

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

2006 FEMA New Jersey Flood Mitigation Lidar: Highlands Area

Data.gov (United States)

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

Lidar system for air-pollution monitoring over urban areas

Science.gov (United States)

Moskalenko, Irina V.; Shcheglov, Djolinard A.; Molodtsov, Nikolai A.

1997-05-01

The atmospheric environmental situation over the urban area of a large city is determined by a complex combination of anthropogenic pollution and meteorological factors. The efficient way to provide three-dimensional mapping of gaseous pollutants over wide areas is utilization of lidar systems employing tunable narrowband transmitters. The paper presented describes activity of RRC 'Kurchatov Institute' in the field of lidar atmospheric monitoring. The project 'mobile remote sensing system based on tunable laser transmitter for environmental monitoring' is developed under financial support of International Scientific and Technology Center (Moscow). The objective of the project is design, construction and field testing of a DIAL-technique system. The lidar transmitter consists of an excimer laser pumping dye laser, BBO crystal frequency doubler, and scanning flat mirror. Sulfur dioxide and atomic mercury have been selected as pollutants for field tests of the lidar system under development. A recent large increase in Moscow traffic stimulated taking into consideration also the remote sensing of lower troposphere ozone because of the photochemical smog problem. The status of the project is briefly discussed. The current activity includes also collecting of environmental data relevant to lidar remote sensing. Main attention is paid to pollutant concentration levels over Moscow city and Moscow district areas.

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.

Estimating Ladder Fuels: A New Approach Combining Field Photography with LiDAR

Directory of Open Access Journals (Sweden)

Heather A. Kramer

2016-09-01

Full Text Available Forests historically associated with frequent fire have changed dramatically due to fire suppression and past harvesting over the last century. The buildup of ladder fuels, which carry fire from the surface of the forest floor to tree crowns, is one of the critical changes, and it has contributed to uncharacteristically large and severe fires. The abundance of ladder fuels makes it difficult to return these forests to their natural fire regime or to meet management objectives. Despite the importance of ladder fuels, methods for quantifying them are limited and imprecise. LiDAR (Light Detection and Ranging, a form of active remote sensing, is able to estimate many aspects of forest structure across a landscape. This study investigates a new method for quantifying ladder fuel in the field (using photographs with a calibration banner and remotely (using LiDAR data. We apply these new techniques in the Klamath Mountains of Northern California to predict ladder fuel levels across the study area. Our results demonstrate a new utility of LiDAR data to identify fire hazard and areas in need of fuels reduction.

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.

a New Approach for Accuracy Improvement of Pulsed LIDAR Remote Sensing Data

Science.gov (United States)

Zhou, G.; Huang, W.; Zhou, X.; He, C.; Li, X.; Huang, Y.; Zhang, L.

2018-05-01

In remote sensing applications, the accuracy of time interval measurement is one of the most important parameters that affect the quality of pulsed lidar data. The traditional time interval measurement technique has the disadvantages of low measurement accuracy, complicated circuit structure and large error. A high-precision time interval data cannot be obtained in these traditional methods. In order to obtain higher quality of remote sensing cloud images based on the time interval measurement, a higher accuracy time interval measurement method is proposed. The method is based on charging the capacitance and sampling the change of capacitor voltage at the same time. Firstly, the approximate model of the capacitance voltage curve in the time of flight of pulse is fitted based on the sampled data. Then, the whole charging time is obtained with the fitting function. In this method, only a high-speed A/D sampler and capacitor are required in a single receiving channel, and the collected data is processed directly in the main control unit. The experimental results show that the proposed method can get error less than 3 ps. Compared with other methods, the proposed method improves the time interval accuracy by at least 20 %.

Aerodynamic roughness length estimation from very high-resolution imaging LIDAR observations over the Heihe basin in China

Directory of Open Access Journals (Sweden)

J. Colin

2010-12-01

Full Text Available Roughness length of land surfaces is an essential variable for the parameterisation of momentum and heat exchanges. The growing interest in the estimation of the surface turbulent flux parameterisation from passive remote sensing leads to an increasing development of models, and the common use of simple semi-empirical formulations to estimate surface roughness. Over complex surface land cover, these approaches would benefit from the combined use of passive remote sensing and land surface structure measurements from Light Detection And Ranging (LIDAR techniques. Following early studies based on LIDAR profile data, this paper explores the use of imaging LIDAR measurements for the estimation of the aerodynamic roughness length over a heterogeneous landscape of the Heihe river basin, a typical inland river basin in the northwest of China. The point cloud obtained from multiple flight passes over an irrigated farmland area were used to separate the land surface topography and the vegetation canopy into a Digital Elevation Model (DEM and a Digital Surface Model (DSM respectively. These two models were then incorporated in two approaches: (i a strictly geometrical approach based on the calculation of the plan surface density and the frontal surface density to derive a geometrical surface roughness; (ii a more aerodynamic approach where both the DEM and DSM are introduced in a Computational Fluid Dynamics model (CFD. The inversion of the resulting 3-D wind field leads to a fine representation of the aerodynamic surface roughness. Examples of the use of these three approaches are presented for various wind directions together with a cross-comparison of results on heterogeneous land cover and complex roughness element structures.

Semiconductor Laser Wind Lidar for Turbine Control

DEFF Research Database (Denmark)

Hu, Qi

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

DEM Development from Ground-Based LiDAR Data: A Method to Remove Non-Surface Objects

Directory of Open Access Journals (Sweden)

Maneesh Sharma

2010-11-01

Full Text Available Topography and land cover characteristics can have significant effects on infiltration, runoff, and erosion processes on watersheds. The ability to model the timing and routing of surface water and erosion is affected by the resolution of the digital elevation model (DEM. High resolution ground-based Light Detecting and Ranging (LiDAR technology can be used to collect detailed topographic and land cover characteristic data. In this study, a method was developed to remove vegetation from ground-based LiDAR data to create high resolution DEMs. Research was conducted on intensively studied rainfall–runoff plots on the USDA-ARS Walnut Gulch Experimental Watershed in Southeast Arizona. LiDAR data were used to generate 1 cm resolution digital surface models (DSM for 5 plots. DSMs created directly from LiDAR data contain non-surface objects such as vegetation cover. A vegetation removal method was developed which used a slope threshold and a focal mean filter method to remove vegetation and create bare earth DEMs. The method was validated on a synthetic plot, where rocks and vegetation were added incrementally. Results of the validation showed a vertical error of ±7.5 mm in the final DEM.

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.

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.

Opo lidar sounding of trace atmospheric gases in the 3 – 4 μm spectral range

Directory of Open Access Journals (Sweden)

Romanovskii Oleg A.

2018-01-01

Full Text Available The applicability of a KTA crystal-based laser system with optical parametric oscillators (OPO generation to lidar sounding of the atmosphere in the spectral range 3–4 μm is studied in this work. A technique developed for lidar sounding of trace atmospheric gases (TAG is based on differential absorption lidar (DIAL method and differential optical absorption spectroscopy (DOAS. The DIAL-DOAS technique is tested to estimate its efficiency for lidar sounding of atmospheric trace gases. The numerical simulation performed shows that a KTA-based OPO laser is a promising source of radiation for remote DIAL-DOAS sounding of the TAGs under study along surface tropospheric paths. A possibility of using a PD38-03-PR photodiode for the DIAL gas analysis of the atmosphere is shown.

CLASSIFICATION OF WATER SURFACES USING AIRBORNE TOPOGRAPHIC LIDAR DATA

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J. Smeeckaert

2013-05-01

Full Text Available Accurate Digital Terrain Models (DTM are inevitable inputs for mapping areas subject to natural hazards. Topographic airborne laser scanning has become an established technique to characterize the Earth surface: lidar provides 3D point clouds allowing a fine reconstruction of the topography. For flood hazard modeling, the key step before terrain modeling is the discrimination of land and water surfaces within the delivered point clouds. Therefore, instantaneous shoreline, river borders, inland waters can be extracted as a basis for more reliable DTM generation. This paper presents an automatic, efficient, and versatile workflow for land/water classification of airborne topographic lidar data. For that purpose, a classification framework based on Support Vector Machines (SVM is designed. First, a restricted set of features, based only 3D lidar point coordinates and flightline information, is defined. Then, the SVM learning step is performed on small but well-targeted areas thanks to an automatic region growing strategy. Finally, label probabilities given by the SVM are merged during a probabilistic relaxation step in order to remove pixel-wise misclassification. Results show that survey of millions of points are labelled with high accuracy (>95% in most cases for coastal areas, and >89% for rivers and that small natural and anthropic features of interest are still well classified though we work at low point densities (0.5–4 pts/m2. Our approach is valid for coasts and rivers, and provides a strong basis for further discrimination of land-cover classes and coastal habitats.

Atmospheric lidar: Legal, scientific and technological aspects

International Nuclear Information System (INIS)

Barbini, R.; Colao, F.; Fiorani, L.; Palucci, A.

2000-01-01

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 [it

Application of Earth Sciencés Technology in Mapping the of Brazilian Coast: Localization, Analysis & Monitoring of the Archaeological Sites with Remote Sensing & LiDAR

Science.gov (United States)

Thompson Alves de Souza, Carlos Eduardo

Application of Earth Sciencés Technology in Mapping the of Brazilian Coast: Localization, Analysis & Monitoring of the Archaeological Sites with Remote Sensing & LiDAR Carlos Eduardo Thompson Alves de Souza cethompsoniii@hotmail.com Archaeologist Member of the European Association of Archaeologists B.A.Archaeology MA.Remote Sensing Abstract The Archaeological Research in Urban Environment with the Air Light Detection and Ranging is problematic for the Overlay Layers mixed with contexts concerning the Interpretation of Archaeological Data. However, in the Underwater Archaeology the results are excellent. This paper considers the application of Remote Sensing and Air Light Detection and Ranging (LIDAR) as separate things as well as Land Archaeology and the Underwater Archaeology. European Archaeologists know very little about Brazil and the article presents an Overview of Research in Brazil with Remote Sensing in Archaeology and Light Detection and Ranging in Land Archaeology and Underwater Archaeology, because Brazil has Continental Dimensions. Braziliańs Methodology for Location, Analysis and Monitoring of Archaeological Sites is necessarily more Complex and Innovative and therefore can serve as a New Paradigm for other archaeologists involved in the Advanced Management Heritage.

Nitrogen concentration estimation with hyperspectral LiDAR

Directory of Open Access Journals (Sweden)

O. Nevalainen

2013-10-01

Full Text Available Agricultural lands have strong impact on global carbon dynamics and nitrogen availability. Monitoring changes in agricultural lands require more efficient and accurate methods. The first prototype of a full waveform hyperspectral Light Detection and Ranging (LiDAR instrument has been developed at the Finnish Geodetic Institute (FGI. The instrument efficiently combines the benefits of passive and active remote sensing sensors. It is able to produce 3D point clouds with spectral information included for every point which offers great potential in the field of remote sensing of environment. This study investigates the performance of the hyperspectral LiDAR instrument in nitrogen estimation. The investigation was conducted by finding vegetation indices sensitive to nitrogen concentration using hyperspectral LiDAR data and validating their performance in nitrogen estimation. The nitrogen estimation was performed by calculating 28 published vegetation indices to ten oat samples grown in different fertilization conditions. Reference data was acquired by laboratory nitrogen concentration analysis. The performance of the indices in nitrogen estimation was determined by linear regression and leave-one-out cross-validation. The results indicate that the hyperspectral LiDAR instrument holds a good capability to estimate plant biochemical parameters such as nitrogen concentration. The instrument holds much potential in various environmental applications and provides a significant improvement to the remote sensing of environment.

LiDAR Relative Reflectivity Surface (2011) for Coral Bay, St. John

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) 0.3x0.3 meter resolution relative seafloor reflectivity surface for Coral Bay, St. John in the U.S....

LiDAR Relative Reflectivity Surface (2011) for Fish Bay, St. John

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) 0.3x0.3 meter resolution relative seafloor reflectivity surface for Fish Bay, St. John in the U.S....

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

Science.gov (United States)

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

2010-12-01

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

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

LiDAR utility for natural resource managers

Science.gov (United States)

Andrew Thomas Hudak; Jeffrey Scott Evans; Alistair Mattthew Stuart. Smith

2009-01-01

Applications of LiDAR remote sensing are exploding, while moving from the research to the operational realm. Increasingly, natural resource managers are recognizing the tremendous utility of LiDAR-derived information to make improved decisions. This review provides a cross-section of studies, many recent, that demonstrate the relevance of LiDAR across a suite of...

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

Science.gov (United States)

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

Modelling the Carbon Stocks Estimation of the Tropical Lowland Dipterocarp Forest Using LIDAR and Remotely Sensed Data

Science.gov (United States)

Zaki, N. A. M.; Latif, Z. A.; Suratman, M. N.; Zainal, M. Z.

2016-06-01

Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR) is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3). This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland Dipterocarp forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r) between Crown projection area (CPA) and Carbon stocks (CS); height from LiDAR (H_LDR) and Carbon stocks (CS); and Crown projection area (CPA) and height from LiDAR (H_LDR) were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH) and carbon stocks which is Pearson Correlation p = 0.000 (p using multiple linear regression method. The study concluded that the integration of WV-3 imagery with the CHM raster based LiDAR were useful in order to quantify the AGB and carbon stocks for a larger sample area of the Lowland Dipterocarp forest.

Search-Lidar Demonstrator for Detection of Small Sea-Surface Targets

NARCIS (Netherlands)

Heuvel, J.C. van den; Bekman, H.H.P.T.; Putten, F.J.M. van; Cohen, L.H.; Schleijpen, H.M.A.

2008-01-01

Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC’s, and speedboats. Lidar

The design, development, and test of balloonborne and groundbased lidar systems. Volume 2: Flight test of Atmospheric Balloon Lidar Experiment, ABLE 2

Science.gov (United States)

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

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 Aug. 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 were successfully completed, and recommendations for further lidar measurements and data analysis were made.

Remote imaging laser-induced breakdown spectroscopy and laser-induced fluorescence spectroscopy using nanosecond pulses from a mobile lidar system.

Science.gov (United States)

Grönlund, Rasmus; Lundqvist, Mats; Svanberg, Sune

2006-08-01

A mobile lidar system was used in remote imaging laser-induced breakdown spectroscopy (LIBS) and laser-induced fluorescence (LIF) experiments. Also, computer-controlled remote ablation of a chosen area was demonstrated, relevant to cleaning of cultural heritage items. Nanosecond frequency-tripled Nd:YAG laser pulses at 355 nm were employed in experiments with a stand-off distance of 60 meters using pulse energies of up to 170 mJ. By coaxial transmission and common folding of the transmission and reception optical paths using a large computer-controlled mirror, full elemental imaging capability was achieved on composite targets. Different spectral identification algorithms were compared in producing thematic data based on plasma or fluorescence light.

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.

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...

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.

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

MODELLING THE CARBON STOCKS ESTIMATION OF THE TROPICAL LOWLAND DIPTEROCARP FOREST USING LIDAR AND REMOTELY SENSED DATA

Directory of Open Access Journals (Sweden)

N. A. M. Zaki

2016-06-01

Full Text Available Tropical forest embraces a large stock of carbon in the global carbon cycle and contributes to the enormous amount of above and below ground biomass. The carbon kept in the aboveground living biomass of trees is typically the largest pool and the most directly impacted by the anthropogenic factor such as deforestation and forest degradation. However, fewer studies had been proposed to model the carbon for tropical rain forest and the quantification still remain uncertainties. A multiple linear regression (MLR is one of the methods to define the relationship between the field inventory measurements and the statistical extracted from the remotely sensed data which is LiDAR and WorldView-3 imagery (WV-3. This paper highlight the model development from fusion of multispectral WV-3 with the LIDAR metrics to model the carbon estimation of the tropical lowland Dipterocarp forest of the study area. The result shown the over segmentation and under segmentation value for this output is 0.19 and 0.11 respectively, thus D-value for the classification is 0.19 which is 81%. Overall, this study produce a significant correlation coefficient (r between Crown projection area (CPA and Carbon stocks (CS; height from LiDAR (H_LDR and Carbon stocks (CS; and Crown projection area (CPA and height from LiDAR (H_LDR were shown 0.671, 0.709 and 0.549 respectively. The CPA of the segmentation found to be representative spatially with higher correlation of relationship between diameter at the breast height (DBH and carbon stocks which is Pearson Correlation p = 0.000 (p Dipterocarp forest.

The design, development, and test of balloonborne and groundbased lidar systems. Volume 1: Balloonborne coherent CO2 lidar system

Science.gov (United States)

Shepherd, O.; Aurilio, G.; Bucknam, R. D.; Hurd, A. G.; Rappaport, S. A.

1991-06-01

This is Volume 1 of a three volume final report on the design, development, and test of balloonborne and groundbased lidar systems. Volume 2 describes the flight test of Atmospheric Balloonborne Lidar Experiment, ABLE 2, which successfully made atmospheric density backscatter measurements during a flight over White Sands Missile Range. Volume 3 describes groundbased lidar development and measurements, including the design of a telescope dome lidar installation, the design of a transportable lidar shed for remote field sites, and field measurements of atmospheric and cloud backscatter from Ascension Island during SABLE 89 and Terciera, Azores during GABLE 90. In this volume, Volume 1, the design and fabrication of a balloonborne CO2 coherent lidar payload are described. The purpose of this payload is to measure, from altitudes greater than 20 km, the 10.6 micrometers backscatter from atmospheric aerosols as a function of altitude. Minor modifications to the lidar would provide for aerosol velocity measurements to be made. The lidar and payload system design was completed, and major components were fabricated and assembled. These tasks have been successfully completed, and recommendations for further lidar measurements and data analysis have been made.

2005 Oahu/Maui Lidar Mapping Project

Data.gov (United States)

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

Demystifying LiDAR technologies for temperate rainforest in the Pacific Northwest

Science.gov (United States)

Rhonda Mazza; Demetrios Gatziolis

2013-01-01

Light detection and ranging (LiDAR), also known as airborne laser scanning, is a rapidly emerging technology for remote sensing. Used to help map, monitor, and assess natural resources, LiDAR data were first embraced by forestry professionals in Scandinavia as a tool for conducting forest inventories in the mid to late 1990s. Thus early LiDAR theory and applications...

An Innovative Concept for Spacebased Lidar Measurement of Ocean Carbon Biomass

Science.gov (United States)

Hu, Yongxiang; Behrenfeld, Michael; Hostetler, Chris; Pelon, Jacques; Trepte, Charles; Hair, John; Slade, Wayne; Cetinic, Ivona; Vaughan, Mark; Lu, Xiaomei;

An evaluation of the WindEye wind lidar

DEFF Research Database (Denmark)

Dellwik, Ebba; Sjöholm, Mikael; Mann, Jakob

Prevision of the wind field by remote sensing wind lidars has the potential to improve the performance of wind turbines. The functionality of a WindEye lidar developed by Windar Photonics A/S (Denmark) for the wind energy market was tested in a two months long field experiment. The WindEye sensor...... with a high accuracy during the whole campaign....

High Spectral Resolution LIDAR as a Tool for Air Quality Research

Science.gov (United States)

Eloranta, E. W.; Spuler, S.; Hayman, M. M.

2017-12-01

Many aspects of air quality research require information on the vertical distribution of pollution. Traditional measurements, obtained from surface based samplers, or passive satellite remote sensing, do not provide vertical profiles. Lidar can provide profiles of aerosol properties. However traditional backscatter lidar suffers from uncertain calibrations with poorly constrained algorithms. These problems are avoided using High Spectral Resolution Lidar (HSRL) which provides absolutely calibrated vertical profiles of aerosol properties. The University of Wisconsin HSRL systems measure 532 nm wavelength aerosol backscatter cross-sections, extinction cross-sections, depolarization, and attenuated 1064 nm backscatter. These instruments are designed for long-term deployment at remote sites with minimal local support. Processed data is provided for public viewing and download in real-time on our web site "http://hsrl.ssec.wisc.edu". Air pollution applications of HSRL data will be illustrated with examples acquired during air quality field programs including; KORUS-AQ, DISCOVER-AQ, LAMOS and FRAPPE. Observations include 1) long range transport of dust, air pollution and smoke. 2) Fumigation episodes where elevated pollution is mixed down to the surface. 3) visibility restrictions by aerosols and 4) diurnal variations in atmospheric optical depth. While HSRL is powerful air quality research tool, its application in routine measurement networks is hindered by the high cost of current systems. Recent technical advances promise a next generation HSRL using telcom components to greatly reduce system cost. This paper will present data generated by a prototype low cost system constructed at NCAR. In addition to lower cost, operation at a non-visible near 780 nm infrared wavelength removes all FAA restrictions on the operation.

Application of Lidar remote sensing to the estimation of forest canopy and stand structure

Science.gov (United States)

Lefsky, Michael Andrew

A new remote sensing instrument, SLICER (Scanning Lidar Imager of Canopies by Echo Recovery), has been applied to the problem of remote sensing the canopy and stand structure of two groups of deciduous forests, Tulip Poplar-Oak stands in the vicinity of Annapolis, MD. and bottomland hardwood stands near Williamston, NC. The ability of the SLICER instrument to remotely sense the vertical distribution of canopy structure (Canopy Height Profile), bulk canopy transmittance, and several indices of canopy height has been successfully validated using twelve stands with coincident field and SLICER estimates of canopy structure. Principal components analysis has been applied to canopy height profiles from both field sites, and three significant factors were identified, each closely related to the amount of foliage in a recognizable layer of the forest, either understory, midstory, or overstory. The distribution of canopy structure to these layers is significantly correlated with the size and number of stems supporting them. The same layered structure was shown to apply to both field and SLICER remotely sensed canopy height profiles, and to apply to SLICER remotely sensed canopy profiles from both the bottomland hardwood stands in the coastal plain of North Carolina, and to mesic Tulip-Poplars stands in the upland coastal plain of Maryland. Linear regressions have demonstrated that canopy and stand structure are correlated to both a statistically significant and useful degree. Stand age and stem density is more highly correlated to stand height, while stand basal area and aboveground biomass are more closely related to a new measure of canopy structure, the quadratic mean canopy height. A geometric model of canopy structure has been shown to explain the differing relationships between canopy structure and stand basal area for stands of Eastern Deciduous Forest and Douglas Fir Forest.

Charactering lidar optical subsystem using four quadrants method

Science.gov (United States)

Tian, Xiaomin; Liu, Dong; Xu, Jiwei; Wang, Zhenzhu; Wang, Bangxin; Wu, Decheng; Zhong, Zhiqing; Xie, Chenbo; Wang, Yingjian

2018-02-01

Lidar is a kind of active optical remote sensing instruments , can be applied to sound atmosphere with a high spatial and temporal resolution. Many parameter of atmosphere can be get by using different inverse algorithm with lidar backscatter signal. The basic setup of a lidar consist of a transmitter and a receiver. To make sure the quality of lidar signal data, the lidar must be calibrated before being used to measure the atmospheric variables. It is really significant to character and analyze lidar optical subsystem because a well equiped lidar optical subsystem contributes to high quality lidar signal data. we pay close attention to telecover test to character and analyze lidar optical subsystem.The telecover test is called four quadrants method consisting in dividing the telescope aperture in four quarants. when a lidar is well configured with lidar optical subsystem, the normalized signal from four qudrants will agree with each other on some level. Testing our WARL-II lidar by four quadrants method ,we find the signals of the four basically consistent with each other both in near range and in far range. But in detail, the signals in near range have some slight distinctions resulting from overlap function, some signals distinctions are induced by atmospheric instability.

2011 USGS Lidar: Orange County (CA)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR (Light Detection and Ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format....

2006 FEMA Lidar: Rhode Island Coastline

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

Modelling Forest α-Diversity and Floristic Composition — On the Added Value of LiDAR plus Hyperspectral Remote Sensing

Directory of Open Access Journals (Sweden)

Martin Wegmann

2012-09-01

Full Text Available The decline of biodiversity is one of the major current global issues. Still, there is a widespread lack of information about the spatial distribution of individual species and biodiversity as a whole. Remote sensing techniques are increasingly used for biodiversity monitoring and especially the combination of LiDAR and hyperspectral data is expected to deliver valuable information. In this study spatial patterns of vascular plant community composition and alpha-diversity of a temperate montane forest in Germany were analysed for different forest strata. The predictive power of LiDAR (LiD and hyperspectral (MNF datasets alone and combined (MNF+LiD was compared using random forest regression in a ten-fold cross-validation scheme that included feature selection and model tuning. The final models were used for spatial predictions. Species richness could be predicted with varying accuracy (R2 = 0.26 to 0.55 depending on the forest layer. In contrast, community composition of the different layers, obtained by multivariate ordination, could in part be modelled with high accuracies for the first ordination axis (R2 = 0.39 to 0.78, but poor accuracies for the second axis (R2 ≤ 0.3. LiDAR variables were the best predictors for total species richness across all forest layers (R2 LiD = 0.3, R2 MNF = 0.08, R2 MNF+LiD = 0.2, while for community composition across all forest layers both hyperspectral and LiDAR predictors achieved similar performances (R2 LiD = 0.75, R2 MNF = 0.76, R2 MNF+LiD = 0.78. The improvement in R2 was small (≤0.07—if any—when using both LiDAR and hyperspectral data as compared to using only the best single predictor set. This study shows the high potential of LiDAR and hyperspectral data for plant biodiversity modelling, but also calls for a critical evaluation of the added value of combining both with respect to acquisition costs.

Estimating tropical forest structure using LIDAR AND X-BAND INSAR

Science.gov (United States)

Palace, M. W.; Treuhaft, R. N.; Keller, M. M.; Sullivan, F.; Roberto dos Santos, J.; Goncalves, F. G.; Shimbo, J.; Neumann, M.; Madsen, S. N.; Hensley, S.

2013-12-01

Tropical forests are considered the most structurally complex of all forests and are experiencing rapid change due to anthropogenic and climatic factors. The high carbon stocks and fluxes make understanding tropical forests highly important to both regional and global studies involving ecosystems and climate. Large and remote areas in the tropics are prime targets for the use of remotely sensed data. Radar and lidar have previously been used to estimate forest structure, with an emphasis on biomass. These two remote sensing methods have the potential to yield much more information about forest structure, specifically through the use of X-band radar and waveform lidar data. We examined forest structure using both field-based and remotely sensed data in the Tapajos National Forest, Para, Brazil. We measured multiple structural parameters for about 70 plots in the field within a 25 x 15 km area that have TanDEM-X single-pass horizontally and vertically polarized radar interferometric data. High resolution airborne lidar were collected over a 22 sq km portion of the same area, within which 33 plots were co-located. Preliminary analyses suggest that X-band interferometric coherence decreases by about a factor of 2 (from 0.95 to 0.45) with increasing field-measured vertical extent (average heights of 7-25 m) and biomass (10-430 Mg/ha) for a vertical wavelength of 39 m, further suggesting, as has been observed at C-band, that interferometric synthetic aperture radar (InSAR) is substantially more sensitive to forest structure/biomass than SAR. Unlike InSAR coherence versus biomass, SAR power at X-band versus biomass shows no trend. Moreover, airborne lidar coherence at the same vertical wavenumbers as InSAR is also shown to decrease as a function of biomass, as well. Although the lidar coherence decrease is about 15% more than the InSAR, implying that lidar penetrates more than InSAR, these preliminary results suggest that X-band InSAR may be useful for structure and

Aerosol and cloud observations from the Lidar In-space Technology Experiment

Science.gov (United States)

Winker, D. M.

1995-01-01

The Lidar In-Space Technology Experiment (LITE) is a backscatter lidar built by NASA Langley Research Center to fly on the Space Shuttle. The purpose of the program was to develop the engineering processes required for space lidar and to demonstrate applications of space lidar to remote sensing of the atmosphere. The instrument was flown on Discovery in September 1994. Global observations of clouds and aerosols were made between the latitudes of 57 deg N and 57 deg S during 10 days of the mission.

Lidar sounding of volcanic plumes

Science.gov (United States)

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

2013-10-01

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

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

Data.gov (United States)

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

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...

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....

2004 Federal Emergency Management Agency (FEMA) Bare Earth Topographic LiDAR: Connecticut River

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LiDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. The LiDAR files were converted from .PTS format to LAS...

Economic and environmental assessment of rooftops regarding suitability for photovoltaic systems installation based on remote sensing data

International Nuclear Information System (INIS)

Lukač, Niko; Seme, Sebastijan; Dežan, Katarina; Žalik, Borut; Štumberger, Gorazd

2016-01-01

Within the last few years, the increase of the world's energy consumption has substantially impacted the environment. Solar energy initiative is more than ever involved to tackle this issue, especially when deploying PV (photovoltaic) systems over large-scale residential areas. However, not all surfaces in these areas are economically suitable, while some surfaces have low CO_2 mitigation. With the availability of high-resolution remote sensing data, the estimation of suitable rooftops for PV systems installation can be performed automatically by estimating the PV potential. This paper presents a novel method for estimating NPV (net present value) of the potential PV systems installed on rooftops by using LiDAR (Light Detection And Ranging) data and PV systems' nonlinear efficiency characteristics. More importantly, the environmental impact is estimated for each rooftop through EPBT (energy payback time) and GGER (greenhouse gas emission rate), based on the life-cycle of a specific PV system. This is combined with NPV in order to find rooftops that are both economically and environmentally viable candidates for PV systems deployment. Results demonstrate a case study LiDAR data for predicting each building's economical and environmental impact, as well as providing an overall view of resulting cumulative CO_2 mitigation over large residential area. - Highlights: • The method relies on PV potential estimation over LiDAR remote sensing data. • Novel economic assessment of PV systems using remote sensing data is proposed. • Environmental analysis of PV systems based on EPBT and GGER is performed. • Estimation of CO_2 mitigation over LiDAR data by considering national energy network.

Robust remote-pumping sodium laser for advanced LIDAR and guide star applications

Science.gov (United States)

Ernstberger, Bernhard; Enderlein, Martin; Friedenauer, Axel; Schwerdt, Robin; Wei, Daoping; Karpov, Vladimir; Leisching, Patrick; Clements, Wallace R. L.; Kaenders, Wilhelm G.

2015-10-01

The performance of large ground-based optical telescopes is limited due to wavefront distortions induced by atmospheric turbulence. Adaptive optics systems using natural guide stars with sufficient brightness provide a practical way for correcting the wavefront errors by means of deformable mirrors. Unfortunately, the sky coverage of bright stars is poor and therefore the concept of laser guide stars was invented, creating an artificial star by exciting resonance fluorescence from the mesospheric sodium layer about 90 km above the earth's surface. Until now, mainly dye lasers or sumfrequency mixing of solid state lasers were used to generate laser guide stars. However, these kinds of lasers require a stationary laser clean room for operation and are extremely demanding in maintenance. Under a development contract with the European Southern Observatory (ESO) and W. M. Keck Observatory (WMKO), TOPTICA Photonics AG and its partner MPB Communications have finalized the development of a next-generation sodium guide star laser system which is available now as a commercial off-the-shelf product. The laser is based on a narrow-band diode laser, Raman fiber amplifier (RFA) technology and resonant second-harmonic generation (SHG), thus highly reliable and simple to operate and maintain. It emits > 22 W of narrow-linewidth (≈ 5 MHz) continuous-wave radiation at sodium resonance and includes a re-pumping scheme for boosting sodium return flux. Due to the SHG resonator acting as spatial mode filter and polarizer, the output is diffraction-limited with RMS wavefront error concept of line-replaceable units (LRU). A comprehensive system software, as well as an intuitive service GUI, allow for remote control and error tracking down to at least the LRU level. In case of a failure, any LRU can be easily replaced. With these fiber-based guide star lasers, TOPTICA for the first time offers a fully engineered, off-the-shelf guide star laser system for groundbased optical telescopes

2004 USGS Lidar: San Francisco Bay (CA)

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — Lidar (Light detection and ranging) discrete-return point cloud data are available in the American Society for Photogrammetry and Remote Sensing (ASPRS) LAS format....

Essentials of LIDAR multiangle data processing methodology for smoke polluted atmospheres

Science.gov (United States)

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

2009-01-01

Mobile scanning lidar is the most appropriate tool for monitoring wildfire smoke-plume dynamics and optical properties. Lidar is the only remote sensing instrument capable of obtaining detailed three-dimensional range-resolved information for smoke distributions and optical properties over ranges of 10+ km at different wavelengths simultaneously.

Innovative High-Accuracy Lidar Bathymetric Technique for the Frequent Measurement of River Systems

Science.gov (United States)

Gisler, A.; Crowley, G.; Thayer, J. P.; Thompson, G. S.; Barton-Grimley, R. A.

2015-12-01

Lidar (light detection and ranging) provides absolute depth and topographic mapping capability compared to other remote sensing methods, which is useful for mapping rapidly changing environments such as riverine systems. Effectiveness of current lidar bathymetric systems is limited by the difficulty in unambiguously identifying backscattered lidar signals from the water surface versus the bottom, limiting their depth resolution to 0.3-0.5 m. Additionally these are large, bulky systems that are constrained to expensive aircraft-mounted platforms and use waveform-processing techniques requiring substantial computation time. These restrictions are prohibitive for many potential users. A novel lidar device has been developed that allows for non-contact measurements of water depth down to 1 cm with an accuracy and precision of shallow to deep water allowing for shoreline charting, measuring water volume, mapping bottom topology, and identifying submerged objects. The scalability of the technique opens up the ability for handheld or UAS-mounted lidar bathymetric systems, which provides for potential applications currently unavailable to the community. The high laser pulse repetition rate allows for very fine horizontal resolution while the photon-counting technique permits real-time depth measurement and object detection. The enhanced measurement capability, portability, scalability, and relatively low-cost creates the opportunity to perform frequent high-accuracy monitoring and measuring of aquatic environments which is crucial for understanding how rivers evolve over many timescales. Results from recent campaigns measuring water depth in flowing creeks and murky ponds will be presented which demonstrate that the method is not limited by rough water surfaces and can map underwater topology through moderately turbid water.

Assessment of vertically-resolved PM10 from mobile lidar observations

Directory of Open Access Journals (Sweden)

J.-C. Raut

2009-11-01

Full Text Available We investigate in this study the vertical PM10 distributions from mobile measurements carried out from locations along the Paris Peripherique (highly trafficked beltway around Paris, examine distinctions in terms of aerosol concentrations between the outlying regions of Paris and the inner city and eventually discuss the influence of aerosol sources, meteorology, and dynamics on the retrieved PM10 distributions. To achieve these purposes, we combine in situ surface measurements with active remote sensing observations obtained from a great number of research programs in Paris area since 1999. Two approaches, devoted to the conversion of vertical profiles of lidar-derived extinction coefficients into PM10, have been set up. A very good agreement is found between the theoretical and empirical methods with a discrepancy of 3%. Hence, specific extinction cross-sections at 355 nm are provided with a reasonable relative uncertainty lower than 12% for urban (4.5 m2 g−1 and periurban (5.9 m2 g−1 aersols, lower than 26% for rural (7.1 m2 g−1 aerosols, biomass burning (2.6 m2 g−1 and dust (1.1 m2 g−1 aerosols The high spatial and temporal resolutions of the mobile lidar (respectively 1.5 m and 1 min enable to follow the spatiotemporal variability of various layers trapping aerosols in the troposphere. Appropriate specific extinction cross-sections are applied in each layer detected in the vertical heterogeneities from the lidar profiles. The standard deviation (rms between lidar-derived PM10 at 200 m above ground and surface network stations measurements was ~14μg m−3. This difference is particularly ascribed to a decorrelation of mass concentrations in the first meters of the boundary layer, as highlighted through multiangular lidar observations. Lidar signals can be used to follow mass concentrations with an uncertainty lower than 25% above urban areas and provide useful information on PM10 peak forecasting that affect air quality.

Fast Occlusion and Shadow Detection for High Resolution Remote Sensing Image Combined with LIDAR Point Cloud

Science.gov (United States)

Hu, X.; Li, X.

2012-08-01

The orthophoto is an important component of GIS database and has been applied in many fields. But occlusion and shadow causes the loss of feature information which has a great effect on the quality of images. One of the critical steps in true orthophoto generation is the detection of occlusion and shadow. Nowadays LiDAR can obtain the digital surface model (DSM) directly. Combined with this technology, image occlusion and shadow can be detected automatically. In this paper, the Z-Buffer is applied for occlusion detection. The shadow detection can be regarded as a same problem with occlusion detection considering the angle between the sun and the camera. However, the Z-Buffer algorithm is computationally expensive. And the volume of scanned data and remote sensing images is very large. Efficient algorithm is another challenge. Modern graphics processing unit (GPU) is much more powerful than central processing unit (CPU). We introduce this technology to speed up the Z-Buffer algorithm and get 7 times increase in speed compared with CPU. The results of experiments demonstrate that Z-Buffer algorithm plays well in occlusion and shadow detection combined with high density of point cloud and GPU can speed up the computation significantly.

FAST OCCLUSION AND SHADOW DETECTION FOR HIGH RESOLUTION REMOTE SENSING IMAGE COMBINED WITH LIDAR POINT CLOUD

Directory of Open Access Journals (Sweden)

X. Hu

2012-08-01

Full Text Available The orthophoto is an important component of GIS database and has been applied in many fields. But occlusion and shadow causes the loss of feature information which has a great effect on the quality of images. One of the critical steps in true orthophoto generation is the detection of occlusion and shadow. Nowadays LiDAR can obtain the digital surface model (DSM directly. Combined with this technology, image occlusion and shadow can be detected automatically. In this paper, the Z-Buffer is applied for occlusion detection. The shadow detection can be regarded as a same problem with occlusion detection considering the angle between the sun and the camera. However, the Z-Buffer algorithm is computationally expensive. And the volume of scanned data and remote sensing images is very large. Efficient algorithm is another challenge. Modern graphics processing unit (GPU is much more powerful than central processing unit (CPU. We introduce this technology to speed up the Z-Buffer algorithm and get 7 times increase in speed compared with CPU. The results of experiments demonstrate that Z-Buffer algorithm plays well in occlusion and shadow detection combined with high density of point cloud and GPU can speed up the computation significantly.

Investigating the relationship between tree heights derived from SIBBORK forest model and remote sensing measurements

Science.gov (United States)

Osmanoglu, B.; Feliciano, E. A.; Armstrong, A. H.; Sun, G.; Montesano, P.; Ranson, K.

2017-12-01

Tree heights are one of the most commonly used remote sensing parameters to measure biomass of a forest. In this project, we investigate the relationship between remotely sensed tree heights (e.g. G-LiHT lidar and commercially available high resolution satellite imagery, HRSI) and the SIBBORK modeled tree heights. G-LiHT is a portable, airborne imaging system that simultaneously maps the composition, structure, and function of terrestrial ecosystems using lidar, imaging spectroscopy and thermal mapping. Ground elevation and canopy height models were generated using the lidar data acquired in 2012. A digital surface model was also generated using the HRSI technique from the commercially available WorldView data in 2016. The HRSI derived height and biomass products are available at the plot (10x10m) level. For this study, we parameterized the SIBBORK individual-based gap model for Howland forest, Maine. The parameterization was calibrated using field data for the study site and results show that the simulated forest reproduces the structural complexity of Howland old growth forest, based on comparisons of key variables including, aboveground biomass, forest height and basal area. Furthermore carbon cycle and ecosystem observational capabilities will be enhanced over the next 6 years via the launch of two LiDAR (NASA's GEDI and ICESAT 2) and two SAR (NASA's ISRO NiSAR and ESA's Biomass) systems. Our aim is to present the comparison of canopy height models obtained with SIBBORK forest model and remote sensing techniques, highlighting the synergy between individual-based forest modeling and high-resolution remote sensing.

Lidar to lidar calibration of Ground-based Lidar

DEFF Research Database (Denmark)

Fernandez Garcia, Sergio; Courtney, Michael

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

Remote wind sensing with a CW diode laser lidar beyond the coherence regime.

Science.gov (United States)

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

2014-08-15

We experimentally demonstrate for the first time (to our knowledge) a coherent CW lidar system capable of wind speed measurement at a probing distance beyond the coherence regime of the light source. A side-by-side wind measurement was conducted on the field using two lidar systems with identical optical designs but different laser linewidths. While one system was operating within the coherence regime, the other was measuring at least 2.4 times the coherence range. The probing distance of both lidars is 85 m and the radial wind speed correlation was measured to be r2=0.965 between the two lidars at a sampling rate of 2 Hz. Based on our experimental results, we describe a practical guideline for designing a wind lidar operating beyond the coherence regime.

Tropospheric ozone seasonal and long-term variability as seen by lidar and surface measurements at the JPL-Table Mountain Facility, California

Directory of Open Access Journals (Sweden)

M. J. Granados-Muñoz

2016-07-01

Full Text Available A combined surface and tropospheric ozone climatology and interannual variability study was performed for the first time using co-located ozone photometer measurements (2013–2015 and tropospheric ozone differential absorption lidar measurements (2000–2015 at the Jet Propulsion Laboratory Table Mountain Facility (TMF; elev. 2285 m, in California. The surface time series were investigated both in terms of seasonal and diurnal variability. The observed surface ozone is typical of high-elevation remote sites, with small amplitude of the seasonal and diurnal cycles, and high ozone values, compared to neighboring lower altitude stations representative of urban boundary layer conditions. The ozone mixing ratio ranges from 45 ppbv in the winter morning hours to 65 ppbv in the spring and summer afternoon hours. At the time of the lidar measurements (early night, the seasonal cycle observed at the surface is similar to that observed by lidar between 3.5 and 9 km. Above 9 km, the local tropopause height variation with time and season impacts significantly the ozone lidar observations. The frequent tropopause folds found in the vicinity of TMF (27 % of the time, mostly in winter and spring produce a dual-peak vertical structure in ozone within the fold layer, characterized by higher-than-average values in the bottom half of the fold (12–14 km, and lower-than-averaged values in the top half of the fold (14–18 km. This structure is consistent with the expected origin of the air parcels within the fold, i.e., mid-latitude stratospheric air folding down below the upper tropospheric sub-tropical air. The influence of the tropopause folds extends down to 5 km, increasing the ozone content in the troposphere. No significant signature of interannual variability could be observed on the 2000–2015 de-seasonalized lidar time series, with only a statistically non-significant positive anomaly during the years 2003–2007. Our trend analysis

Optimizing Lidar Scanning Strategies for Wind Energy Measurements (Invited)

Science.gov (United States)

Newman, J. F.; Bonin, T. A.; Klein, P.; Wharton, S.; Chilson, P. B.

2013-12-01

Environmental concerns and rising fossil fuel prices have prompted rapid development in the renewable energy sector. Wind energy, in particular, has become increasingly popular in the United States. However, the intermittency of available wind energy makes it difficult to integrate wind energy into the power grid. Thus, the expansion and successful implementation of wind energy requires accurate wind resource assessments and wind power forecasts. The actual power produced by a turbine is affected by the wind speeds and turbulence levels experienced across the turbine rotor disk. Because of the range of measurement heights required for wind power estimation, remote sensing devices (e.g., lidar) are ideally suited for these purposes. However, the volume averaging inherent in remote sensing technology produces turbulence estimates that are different from those estimated by a sonic anemometer mounted on a standard meteorological tower. In addition, most lidars intended for wind energy purposes utilize a standard Doppler beam-swinging or Velocity-Azimuth Display technique to estimate the three-dimensional wind vector. These scanning strategies are ideal for measuring mean wind speeds but are likely inadequate for measuring turbulence. In order to examine the impact of different lidar scanning strategies on turbulence measurements, a WindCube lidar, a scanning Halo lidar, and a scanning Galion lidar were deployed at the Southern Great Plains Atmospheric Radiation Measurement (ARM) site in Summer 2013. Existing instrumentation at the ARM site, including a 60-m meteorological tower and an additional scanning Halo lidar, were used in conjunction with the deployed lidars to evaluate several user-defined scanning strategies. For part of the experiment, all three scanning lidars were pointed at approximately the same point in space and a tri-Doppler analysis was completed to calculate the three-dimensional wind vector every 1 second. In another part of the experiment, one of

Remote wind sensing with a CW diode laser lidar beyond the coherence regime

DEFF Research Database (Denmark)

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

2014-01-01

We experimentally demonstrate for the first time (to our knowledge) a coherent CW lidar system capable of wind speed measurement at a probing distance beyond the coherence regime of the light source. A side-by-side wind measurement was conducted on the field using two lidar systems with identical...... optical designs but different laser linewidths. While one system was operating within the coherence regime, the other was measuring at least 2.4 times the coherence range. The probing distance of both lidars is 85 m and the radial wind speed correlation was measured to be r2=0.965 between the two lidars...

Lidar to lidar calibration

DEFF Research Database (Denmark)

Fernandez Garcia, Sergio; Villanueva, Héctor

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

2008 USGS New Jersey Lidar: Somerset County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These data support the general geospatial needs of the USGS and other federal agencies. LiDAR data is remotely sensed high-resolution elevation data collected by an...

Crown-Level Tree Species Classification Using Integrated Airborne Hyperspectral and LIDAR Remote Sensing Data

Science.gov (United States)

Wang, Z.; Wu, J.; Wang, Y.; Kong, X.; Bao, H.; Ni, Y.; Ma, L.; Jin, J.

2018-05-01

Mapping tree species is essential for sustainable planning as well as to improve our understanding of the role of different trees as different ecological service. However, crown-level tree species automatic classification is a challenging task due to the spectral similarity among diversified tree species, fine-scale spatial variation, shadow, and underlying objects within a crown. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR) and hyperspectral imagery offer a great potential opportunity to derive crown spectral, structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, an innovative approach was developed for tree species classification at the crown level. The method utilized LiDAR data for individual tree crown delineation and morphological structure extraction, and Compact Airborne Spectrographic Imager (CASI) hyperspectral imagery for pure crown-scale spectral extraction. Specifically, four steps were include: 1) A weighted mean filtering method was developed to improve the accuracy of the smoothed Canopy Height Model (CHM) derived from LiDAR data; 2) The marker-controlled watershed segmentation algorithm was, therefore, also employed to delineate the tree-level canopy from the CHM image in this study, and then individual tree height and tree crown were calculated according to the delineated crown; 3) Spectral features within 3 × 3 neighborhood regions centered on the treetops detected by the treetop detection algorithm were derived from the spectrally normalized CASI imagery; 4) The shape characteristics related to their crown diameters and heights were established, and different crown-level tree species were classified using the combination of spectral and shape characteristics. Analysis of results suggests that the developed classification strategy in this paper (OA = 85.12 %, Kc = 0.90) performed better than LiDAR-metrics method (OA = 79

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

Remote sensing of land surface phenology

Science.gov (United States)

Meier, G.A.; Brown, Jesslyn F.

2014-01-01

Remote sensing of land-surface phenology is an important method for studying the patterns of plant and animal growth cycles. Phenological events are sensitive to climate variation; therefore phenology data provide important baseline information documenting trends in ecology and detecting the impacts of climate change on multiple scales. The USGS Remote sensing of land surface phenology program produces annually, nine phenology indicator variables at 250 m and 1,000 m resolution for the contiguous U.S. The 12 year archive is available at http://phenology.cr.usgs.gov/index.php.

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.

Development of Prototype Micro-Lidar using Narrow Linewidth Semiconductor Lasers for Mars Boundary Layer Wind and Dust Opacity Profiles

Science.gov (United States)

Menzies, Robert T.; Cardell, Greg; Chiao, Meng; Esproles, Carlos; Forouhar, Siamak; Hemmati, Hamid; Tratt, David

1999-01-01

We have developed a compact Doppler lidar concept which utilizes recent developments in semiconductor diode laser technology in order to be considered suitable for wind and dust opacity profiling in the Mars lower atmosphere from a surface location. The current understanding of the Mars global climate and meteorology is very limited, with only sparse, near-surface data available from the Viking and Mars Pathfinder landers, supplemented by long-range remote sensing of the Martian atmosphere. The in situ measurements from a lander-based Doppler lidar would provide a unique dataset particularly for the boundary layer. The coupling of the radiative properties of the lower atmosphere with the dynamics involves the radiative absorption and scattering effects of the wind-driven dust. Variability in solar irradiance, on diurnal and seasonal time scales, drives vertical mixing and PBL (planetary boundary layer) thickness. The lidar data will also contribute to an understanding of the impact of wind-driven dust on lander and rover operations and lifetime through an improvement in our understanding of Mars climatology. In this paper we discuss the Mars lidar concept, and the development of a laboratory prototype for performance studies, using, local boundary layer and topographic target measurements.

Using LiDAR to Estimate Surface Erosion Volumes within the Post-storm 2012 Bagley Fire

Science.gov (United States)

Mikulovsky, R. P.; De La Fuente, J. A.; Mondry, Z. J.

2014-12-01

The total post-storm 2012 Bagley fire sediment budget of the Squaw Creek watershed in the Shasta-Trinity National Forest was estimated using many methods. A portion of the budget was quantitatively estimated using LiDAR. Simple workflows were designed to estimate the eroded volume's of debris slides, fill failures, gullies, altered channels and streams. LiDAR was also used to estimate depositional volumes. Thorough manual mapping of large erosional features using the ArcGIS 10.1 Geographic Information System was required as these mapped features determined the eroded volume boundaries in 3D space. The 3D pre-erosional surface for each mapped feature was interpolated based on the boundary elevations. A surface difference calculation was run using the estimated pre-erosional surfaces and LiDAR surfaces to determine volume of sediment potentially delivered into the stream system. In addition, cross sections of altered channels and streams were taken using stratified random selection based on channel gradient and stream order respectively. The original pre-storm surfaces of channel features were estimated using the cross sections and erosion depth criteria. Open source software Inkscape was used to estimate cross sectional areas for randomly selected channel features and then averaged for each channel gradient and stream order classes. The average areas were then multiplied by the length of each class to estimate total eroded altered channel and stream volume. Finally, reservoir and in-channel depositional volumes were estimated by mapping channel forms and generating specific reservoir elevation zones associated with depositional events. The in-channel areas and zones within the reservoir were multiplied by estimated and field observed sediment thicknesses to attain a best guess sediment volume. In channel estimates included re-occupying stream channel cross sections established before the fire. Once volumes were calculated, other erosion processes of the Bagley

Development of atmospheric polarization LIDAR System

International Nuclear Information System (INIS)

Ghalumyan, A.S.; Ghazaryan, V.R.

2016-01-01

LIDAR (Light Detection And Ranging) system sensitive to the polarization of the backscattered signal is being developed in Yerevan Physics Institute. The system is designed primarily for remote sensing of the atmospheric electric fields. At present, the system is being tuned for measuring vertical atmospheric backscatter profiles of aerosols and hydrometeors, analyze the depolarization ratio of elastic backscattered laser beams and investigate the influence of external factors on the beam polarization. In this paper, we describe the complete LIDAR system – the laser transmitter, receiving telescope and the polarization separator. The data acquisition and processing techniques are also described. (author)

Microwave Remote Sensing Modeling of Ocean Surface Salinity and Winds Using an Empirical Sea Surface Spectrum

Science.gov (United States)

Yueh, Simon H.

2004-01-01

Active and passive microwave remote sensing techniques have been investigated for the remote sensing of ocean surface wind and salinity. We revised an ocean surface spectrum using the CMOD-5 geophysical model function (GMF) for the European Remote Sensing (ERS) C-band scatterometer and the Ku-band GMF for the NASA SeaWinds scatterometer. The predictions of microwave brightness temperatures from this model agree well with satellite, aircraft and tower-based microwave radiometer data. This suggests that the impact of surface roughness on microwave brightness temperatures and radar scattering coefficients of sea surfaces can be consistently characterized by a roughness spectrum, providing physical basis for using combined active and passive remote sensing techniques for ocean surface wind and salinity remote sensing.

Lidar: range-resolved optical remote sensing of the atmosphere

National Research Council Canada - National Science Library

Weitkamp, Claus; Walther, Herbert

2005-01-01

"Written by leading experts in optical radar, or lidar, this book brings all the recent practices up-to-date and covers a multitude of applications, from atmospheric sciences to environmental protection...

Capability of Raman lidar for monitoring the variation of atmospheric CO2 profile

International Nuclear Information System (INIS)

Zhao Peitao; Hu Shunxing; Su Jia; Cao Kaifa; Hu Huanling; Zhang Yinchao; Wang Lian; Zhao Yuefeng

2008-01-01

Lidar (Light detection and ranging) has special capabilities for remote sensing of many different behaviours of the atmosphere. One of the techniques which show a great deal of promise for several applications is Raman scattering. The detecting capability, including maximum operation range and minimum detectable gas concentration is one of the most significant parameters for lidar remote sensing of pollutants. In this paper, based on the new method for evaluating the capabilities of a Raman lidar system, we present an evaluation of detecting capability of Raman lidar for monitoring atmospheric CO 2 in Hefei. Numerical simulations about the influence of atmospheric conditions on lidar detecting capability were carried out, and a conclusion can be drawn that the maximum difference of the operation ranges caused by the weather conditions alone can reach about 0.4 to 0.5km with a measuring precision within 30ppmv. The range of minimum detectable concentration caused by the weather conditions alone can reach about 20 to 35 ppmv in vertical direction for 20000 shots at a distance of 1 km on the assumption that other parameters are kept constant. The other corresponding parameters under different conditions are also given. The capability of Raman lidar operated in vertical direction was found to be superior to that operated in horizontal direction. During practical measurement with the Raman lidar whose hardware components were fixed, aerosol scattering extinction effect would be a significant factor that influenced the capability of Raman lidar. This work may be a valuable reference for lidar system designing, measurement accuracy improving and data processing

Calibration Methods for a Space Borne Backscatter Lidar

NARCIS (Netherlands)

Kunz, G.J.

1996-01-01

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

Non-Topographic Space-Based Laser Remote Sensing

Science.gov (United States)

Yu, Anthony W.; Abshire, James B.; Riris, Haris; Purucker, Michael; Janches, Diego; Getty, Stephanie; Krainak, Michael A.; Stephen, Mark A.; Chen, Jeffrey R.; Li, Steve X.;

PROCESSING UAV AND LIDAR POINT CLOUDS IN GRASS GIS

Directory of Open Access Journals (Sweden)

V. Petras

2016-06-01

Full Text Available Today’s methods of acquiring Earth surface data, namely lidar and unmanned aerial vehicle (UAV imagery, non-selectively collect or generate large amounts of points. Point clouds from different sources vary in their properties such as number of returns, density, or quality. We present a set of tools with applications for different types of points clouds obtained by a lidar scanner, structure from motion technique (SfM, and a low-cost 3D scanner. To take advantage of the vertical structure of multiple return lidar point clouds, we demonstrate tools to process them using 3D raster techniques which allow, for example, the development of custom vegetation classification methods. Dense point clouds obtained from UAV imagery, often containing redundant points, can be decimated using various techniques before further processing. We implemented and compared several decimation techniques in regard to their performance and the final digital surface model (DSM. Finally, we will describe the processing of a point cloud from a low-cost 3D scanner, namely Microsoft Kinect, and its application for interaction with physical models. All the presented tools are open source and integrated in GRASS GIS, a multi-purpose open source GIS with remote sensing capabilities. The tools integrate with other open source projects, specifically Point Data Abstraction Library (PDAL, Point Cloud Library (PCL, and OpenKinect libfreenect2 library to benefit from the open source point cloud ecosystem. The implementation in GRASS GIS ensures long term maintenance and reproducibility by the scientific community but also by the original authors themselves.

LiDAR Relative Reflectivity Surface (2011) for the St. Thomas East End Reserve, St. Thomas

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — This image represents a LiDAR (Light Detection & Ranging) 0.3x0.3 meter resolution relative seafloor reflectivity surface for the St. Thomas East End Reserve...

Remotely measuring the wind using turbine-mounted lidars: Application to power performance testing

DEFF Research Database (Denmark)

Borraccino, Antoine

the so-called whitebox approach. It consists mainly in calibrating the lidar primary measurementsof line-of-sight velocities. The line-of-sight velocity is the projection of the wind vector onto the laser beam propagation path. The calibration is performed in situ, by comparing the lidar velocity...... measurements to a reference quantity itself traceable to the international standards of units. The uncertainty of the line-ofsight velocity measurements was assessed using a normative methodology (GUM) which is based on the law of propagation of uncertainties. The generic calibration procedure was applied...... to two commercially developed nacelle lidars systems, the Avent 5-beam Demonstrator and the ZephIR Dual Mode lidars. Further, the lineof-sight positioning quantities such as inclination angles or beam trajectory werealso calibrated and their uncertainties assessed. Calibration results were of high...

Airborne Instrument Simulator for the Lidar Surface Topography (LIST) Mission

Science.gov (United States)

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

2010-01-01

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

Telescope aperture optimization for spacebased coherent wind lidar

Science.gov (United States)

Ge, Xian-ying; Zhu, Jun; Cao, Qipeng; Zhang, Yinchao; Yin, Huan; Dong, Xiaojing; Wang, Chao; Zhang, Yongchao; Zhang, Ning

2015-08-01

Many studies have indicated that the optimum measurement approach for winds from space is a pulsed coherent wind lidar, which is an active remote sensing tool with the characteristics that high spatial and temporal resolutions, real-time detection, high mobility, facilitated control and so on. Because of the significant eye safety, efficiency, size, and lifetime advantage, 2μm wavelength solid-state laser lidar systems have attracted much attention in spacebased wind lidar plans. In this paper, the theory of coherent detection is presented and a 2μm wavelength solid-state laser lidar system is introduced, then the ideal aperture is calculated from signal-to-noise(SNR) view at orbit 400km. However, considering real application, even if the lidar hardware is perfectly aligned, the directional jitter of laser beam, the attitude change of the lidar in the long round trip time of the light from the atmosphere and other factors can bring misalignment angle. So the influence of misalignment angle is considered and calculated, and the optimum telescope diameter(0.45m) is obtained as the misalignment angle is 4 μrad. By the analysis of the optimum aperture required for spacebased coherent wind lidar system, we try to present the design guidance for the telescope.

Future Plans in US Flight Missions: Using Laser Remote Sensing for Climate Science Observations

Science.gov (United States)

Callahan, Lisa W.

2010-01-01

Laser Remote Sensing provides critical climate science observations necessary to better measure, understand, model and predict the Earth's water, carbon and energy cycles. Laser Remote Sensing applications for studying the Earth and other planets include three dimensional mapping of surface topography, canopy height and density, atmospheric measurement of aerosols and trace gases, plume and cloud profiles, and winds measurements. Beyond the science, data from these missions will produce new data products and applications for a multitude of end users including policy makers and urban planners on local, national and global levels. NASA Missions in formulation including Ice, Cloud, and land Elevation Satellite (ICESat 2) and the Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI), and future missions such as the Active Sensing of CO2 Emissions over Nights, Days and Seasons (ASCENDS), will incorporate the next generation of LIght Detection And Ranging (lidar) instruments to measure changes in the surface elevation of the ice, quantify ecosystem carbon storage due to biomass and its change, and provide critical data on CO 2 in the atmosphere. Goddard's plans for these instruments and potential uses for the resulting data are described below. For the ICESat 2 mission, GSFC is developing a micro-pulse multi-beam lidar. This instrument will provide improved ice elevation estimates over high slope and very rough areas and result in improved lead detection for sea ice estimates. Data about the sea ice and predictions related to sea levels will continue to help inform urban planners as the changes in the polar ice accelerate. DESDynI is planned to be launched in 2017 and includes both lidar and radar instruments. GSFC is responsible for the lidar portion of the DESDynI mission and is developing a scanning laser altimeter that will measure the Earth's topography, the structure of tree canopies, biomass, and surface roughness. The DESDynI lidar will also measure and

Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys

Science.gov (United States)

Andrew T. Hudak; Eva K. Strand; Lee A. Vierling; John C. Byrne; Jan U. H. Eitel; Sebastian Martinuzzi; Michael J. Falkowski

2012-01-01

Sound forest policy and management decisions to mitigate rising atmospheric CO2 depend upon accurate methodologies to quantify forest carbon pools and fluxes over large tracts of land. LiDAR remote sensing is a rapidly evolving technology for quantifying aboveground biomass and thereby carbon pools; however, little work has evaluated the efficacy of repeat LiDAR...

Optical Backscattering Measured by Airborne Lidar and Underwater Glider

Directory of Open Access Journals (Sweden)

James H. Churnside

2017-04-01

Full Text Available The optical backscattering from particles in the ocean is an important quantity that has been measured by remote sensing techniques and in situ instruments. In this paper, we compare estimates of this quantity from airborne lidar with those from an in situ instrument on an underwater glider. Both of these technologies allow much denser sampling of backscatter profiles than traditional ship surveys. We found a moderate correlation (R = 0.28, p < 10−5, with differences that are partially explained by spatial and temporal sampling mismatches, variability in particle composition, and lidar retrieval errors. The data suggest that there are two different regimes with different scattering properties. For backscattering coefficients below about 0.001 m−1, the lidar values were generally greater than the glider values. For larger values, the lidar was generally lower than the glider. Overall, the results are promising and suggest that airborne lidar and gliders provide comparable and complementary information on optical particulate backscattering.

Effect of remote clouds on surface UV irradiance

Energy Technology Data Exchange (ETDEWEB)

Deguenther, M.; Meerkoetter, R. [Deutsche Forschungsanstalt fuer Luft- und Raumfahrt e.V. (DLR), Wessling (Germany). Inst. fuer Physik der Atmosphaere

2000-06-01

Clouds affect local surface UV irradiance, even if the horizontal distance from the radiation observation site amounts to several kilometers. In order to investigate this effect, which we call remote clouds effect, a 3-dimensional radiative transfer model is applied. Assuming the atmosphere is subdivided into a quadratic based sector and its surrounding, we quantify the influence of changing cloud coverage within this surrounding from 0% to 100% on surface UV irradiance at the sector center. To work out this remote clouds influence as a function of sector base size, we made some calculations for different sizes between 10 km x 10 km and 100 km x 100 km. It appears that in the case of small sectors (base size {<=}20 km x 20 km) the remote clouds effect is highly variable: Depending on cloud structure, solar zenith angle and wavelength, the surface UV irradiance may be enhanced up to 15% as well as reduced by more than 50%. In contrast, for larger sectors it is always the case that enhancements become smaller by 5% if sector base size exceeds 60 km x 60 km. However, these values are upper estimates of the remote cloud effects and they are found only for special cloud structures. Since these structures might occur but cannot be regarded as typical, different satellite observed cloud formations (horizontal resolution about 1 km x 1 km) have also been investigated. For these more common cloud distributions we find remote cloud effects to be distinctly smaller than the corresponding upper estimates, e.g., for a sector with base size of 25 km x 25 km the surface UV irradiance error due to ignoring the actual remote clouds and replacing their influence with periodic horizontal boundary conditions is less than 3%, whereas the upper estimate of remote clouds effect would suggest an error close to 10%. (orig.)

CROWN-LEVEL TREE SPECIES CLASSIFICATION USING INTEGRATED AIRBORNE HYPERSPECTRAL AND LIDAR REMOTE SENSING DATA

Directory of Open Access Journals (Sweden)

Z. Wang

2018-05-01

Full Text Available Mapping tree species is essential for sustainable planning as well as to improve our understanding of the role of different trees as different ecological service. However, crown-level tree species automatic classification is a challenging task due to the spectral similarity among diversified tree species, fine-scale spatial variation, shadow, and underlying objects within a crown. Advanced remote sensing data such as airborne Light Detection and Ranging (LiDAR and hyperspectral imagery offer a great potential opportunity to derive crown spectral, structure and canopy physiological information at the individual crown scale, which can be useful for mapping tree species. In this paper, an innovative approach was developed for tree species classification at the crown level. The method utilized LiDAR data for individual tree crown delineation and morphological structure extraction, and Compact Airborne Spectrographic Imager (CASI hyperspectral imagery for pure crown-scale spectral extraction. Specifically, four steps were include: 1 A weighted mean filtering method was developed to improve the accuracy of the smoothed Canopy Height Model (CHM derived from LiDAR data; 2 The marker-controlled watershed segmentation algorithm was, therefore, also employed to delineate the tree-level canopy from the CHM image in this study, and then individual tree height and tree crown were calculated according to the delineated crown; 3 Spectral features within 3 × 3 neighborhood regions centered on the treetops detected by the treetop detection algorithm were derived from the spectrally normalized CASI imagery; 4 The shape characteristics related to their crown diameters and heights were established, and different crown-level tree species were classified using the combination of spectral and shape characteristics. Analysis of results suggests that the developed classification strategy in this paper (OA = 85.12 %, Kc = 0.90 performed better than Li

2007 FEMA New Jersey Flood Mitigation Lidar: Gloucester County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

2006 FEMA New Jersey Flood Mitigation Lidar: Middlesex County

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

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

Data.gov (United States)

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

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.

Field test of a lidar wind profiler

NARCIS (Netherlands)

Kunz, G.J.

1996-01-01

Wind speeds and wind directions are measured remotely using an incoherent backscatter lidar system operating at a wavelength of 1.06 mm with a maximum repetition rate of 13 Hz. The principle of the measurements is based on following detectable atmospheric structures, which are transported by the

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...

Autonomous Alignment Advancements for Eye-safe Coherent Lidar, Phase I

Data.gov (United States)

National Aeronautics and Space Administration — Eye-safe coherent lidar technology holds increasing promise of meeting NASA's demanding remote 3D space winds goal near term. Highly autonomous, long-range coherent...

Measurements of stratospheric Pinatubo aerosol extinction profiles by a Raman lidar

International Nuclear Information System (INIS)

Abo, Makoto; Nagasawa, Chikao.

1992-01-01

The Raman lidar has been used for remote measurements of water vapor, ozone and atmospheric temperature in the lower troposphere because the Raman cross section is three orders smaller than the Rayleigh cross section. The authors estimated the extinction coefficients of the Pinatubo volcanic aerosol in the stratosphere using a Raman lidar. If the precise aerosol extinction coefficients are derived, the backscatter coefficient of a Mie scattering lidar will be more accurately estimated. The Raman lidar has performed to measure density profiles of some species using Raman scattering. Here the authors used a frequency-doubled Nd:YAG laser for transmitter and received nitrogen vibrational Q-branch Raman scattering signal. Ansmann et al. (1990) derived tropospherical aerosol extinction profiles with a Raman lidar. The authors think that this method can apply to dense stratospheric aerosols such as Pinatubo volcanic aerosols. As dense aerosols are now accumulated in the stratosphere by Pinatubo volcanic eruption, the error of Ramen lidar signal regarding the fluctuation of air density can be ignored

Results from the search-lidar demonstrator project for detection of small Sea-Surface targets

NARCIS (Netherlands)

Heuvel, J.C. van den; Putten, F.J.M. van; Cohen, L.H.; Kemp, R.A.W.; Franssen, G.C.

2009-01-01

Coastal surveillance and naval operations in the littoral both have to deal with the threat of small sea-surface targets. These targets have a low radar cross-section and a low velocity that makes them hard to detect by radar. Typical threats include jet skis, FIAC's, and speedboats. Previous lidar

A study of a dual polarization laser backscatter system for remote identification and measurement of water pollution

Science.gov (United States)

Sheives, T. C.

1974-01-01

Remote identification and measurement of subsurface water turbidity and oil on water was accomplished with analytical models which describe the backscatter from smooth surface turbid water, including single scatter and multiple scatter effects. Lidar measurements from natural waterways are also presented and compared with ground observations of several physical water quality parameters.

a Universal De-Noising Algorithm for Ground-Based LIDAR Signal

Science.gov (United States)

Ma, Xin; Xiang, Chengzhi; Gong, Wei

2016-06-01

Ground-based lidar, working as an effective remote sensing tool, plays an irreplaceable role in the study of atmosphere, since it has the ability to provide the atmospheric vertical profile. However, the appearance of noise in a lidar signal is unavoidable, which leads to difficulties and complexities when searching for more information. Every de-noising method has its own characteristic but with a certain limitation, since the lidar signal will vary with the atmosphere changes. In this paper, a universal de-noising algorithm is proposed to enhance the SNR of a ground-based lidar signal, which is based on signal segmentation and reconstruction. The signal segmentation serving as the keystone of the algorithm, segments the lidar signal into three different parts, which are processed by different de-noising method according to their own characteristics. The signal reconstruction is a relatively simple procedure that is to splice the signal sections end to end. Finally, a series of simulation signal tests and real dual field-of-view lidar signal shows the feasibility of the universal de-noising algorithm.

Lidar: air pollution applications

International Nuclear Information System (INIS)

Collis, R.T.H.

1977-01-01

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

REMOTELY SENSED DATA FUSION IN MODERN AGE ARCHAEOLOGY AND MILITARY HISTORICAL RECONSTRUCTION

Directory of Open Access Journals (Sweden)

A. Juhász

2016-06-01

Full Text Available LiDAR technology has become one of the major remote sensing methods in the last few years. There are several areas, where the scanned 3D point clouds can be used very efficiently. In our study we review the potential applications of LiDAR data in military historical reconstruction. Obviously, the base of this kind of investigation must be the archive data, but it is an interesting challenge to integrate a cutting edge method into such tasks. The LiDAR technology can be very useful, especially in vegetation covered areas, where the conventional remote sensing technologies are mostly inefficient. We review two typical sample projects where we integrated LiDAR data in military historical GIS reconstruction. Finally, we summarize, how laser scanned data can support the different parts of reconstruction work and define the technological steps of LiDAR data processing.

2014 NOAA Post-Sandy Topobathymetric Lidar: Void DEMs Rhode Island

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — These lidar data were collected by the National Oceanic Atmospheric Administration National Geodetic Survey Remote Sensing Division using a Riegl VQ820G system. The...

A graph signal filtering-based approach for detection of different edge types on airborne lidar data

Science.gov (United States)

Bayram, Eda; Vural, Elif; Alatan, Aydin

2017-10-01

Airborne Laser Scanning is a well-known remote sensing technology, which provides a dense and highly accurate, yet unorganized point cloud of earth surface. During the last decade, extracting information from the data generated by airborne LiDAR systems has been addressed by many studies in geo-spatial analysis and urban monitoring applications. However, the processing of LiDAR point clouds is challenging due to their irregular structure and 3D geometry. In this study, we propose a novel framework for the detection of the boundaries of an object or scene captured by LiDAR. Our approach is motivated by edge detection techniques in vision research and it is established on graph signal filtering which is an exciting and promising field of signal processing for irregular data types. Due to the convenient applicability of graph signal processing tools on unstructured point clouds, we achieve the detection of the edge points directly on 3D data by using a graph representation that is constructed exclusively to answer the requirements of the application. Moreover, considering the elevation data as the (graph) signal, we leverage aerial characteristic of the airborne LiDAR data. The proposed method can be employed both for discovering the jump edges on a segmentation problem and for exploring the crease edges on a LiDAR object on a reconstruction/modeling problem, by only adjusting the filter characteristics.

Automatic registration of optical imagery with 3d lidar data using local combined mutual information

Directory of Open Access Journals (Sweden)

E. G. Parmehr

2013-10-01

Full Text Available Automatic registration of multi-sensor data is a basic step in data fusion for photogrammetric and remote sensing applications. The effectiveness of intensity-based methods such as Mutual Information (MI for automated registration of multi-sensor image has been previously reported for medical and remote sensing applications. In this paper, a new multivariable MI approach that exploits complementary information of inherently registered LiDAR DSM and intensity data to improve the robustness of registering optical imagery and LiDAR point cloud, is presented. LiDAR DSM and intensity information has been utilised in measuring the similarity of LiDAR and optical imagery via the Combined MI. An effective histogramming technique is adopted to facilitate estimation of a 3D probability density function (pdf. In addition, a local similarity measure is introduced to decrease the complexity of optimisation at higher dimensions and computation cost. Therefore, the reliability of registration is improved due to the use of redundant observations of similarity. The performance of the proposed method for registration of satellite and aerial images with LiDAR data in urban and rural areas is experimentally evaluated and the results obtained are discussed.

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

[1] Active remote sensors such as lidars or radars can be used with other data to quantify the cloud properties at regional scale and at global scale (Dupont et al., 2009). Relative to radar, lidar remote sensing is sensitive to very thin and high clouds but has a significant limitation due to signal attenuation in the ability to precisely quantify the properties of clouds with a 20 cloud optical thickness larger than 3. In this study, 10-years of backscatter lidar signal data are analysed by a unique algorithm called STRucture of ATmosphere (STRAT, Morille et al., 2007). We apply the STRAT algorithm to data from both the collocated Micropulse lidar (MPL) and a Raman lidar (RL) at the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site between 1998 and 2009. Raw backscatter lidar signal is processed and 25 corrections for detector deadtime, afterpulse, and overlap are applied. (Campbell et al.) The cloud properties for all levels of clouds are derived and distributions of cloud base height (CBH), top height (CTH), physical cloud thickness (CT), and optical thickness (COT) from local statistics are compared. The goal of this study is (1) to establish a climatology of macrophysical and optical properties for all levels of clouds observed over the ARM SGP site 30 and (2) to estimate the discrepancies induced by the two remote sensing systems (pulse energy, sampling, resolution, etc.). Our first results tend to show that the MPLs, which are the primary ARM lidars, have a distinctly limited range where all of these cloud properties are detectable, especially cloud top and cloud thickness, but even actual cloud base especially during summer daytime period. According to the comparisons between RL and MPL, almost 50% of situations show a signal to noise ratio too low (smaller than 3) for the MPL in order to detect clouds higher than 7km during daytime period in summer. Consequently, the MPLderived annual cycle of cirrus cloud base (top) altitude is

Detection of Wind Evolution and Lidar Trajectory Optimization for Lidar-Assisted Wind Turbine Control

Directory of Open Access Journals (Sweden)

David Schlipf

2015-11-01

Full Text Available Recent developments in remote sensing are offering a promising opportunity to rethink conventional control strategies of wind turbines. With technologies such as lidar, the information about the incoming wind field - the main disturbance to the system - can be made available ahead of time. Initial field testing of collective pitch feedforward control shows, that lidar measurements are only beneficial if they are filtered properly to avoid harmful control action. However, commercial lidar systems developed for site assessment are usually unable to provide a usable signal for real time control. Recent research shows, that the correlation between the measurement of rotor effective wind speed and the turbine reaction can be modeled and that the model can be used to optimize a scan pattern. This correlation depends on several criteria such as turbine size, position of the measurements, measurement volume, and how the wind evolves on its way towards the rotor. In this work the longitudinal wind evolution is identified with the line-of-sight measurements of a pulsed lidar system installed on a large commercial wind turbine. This is done by staring directly into the inflowing wind during operation of the turbine and fitting the coherence between the wind at different measurement distances to an exponential model taking into account the yaw misalignment, limitation to line-of-sight measurements and the pulse volume. The identified wind evolution is then used to optimize the scan trajectory of a scanning lidar for lidar-assisted feedforward control in order to get the best correlation possible within the constraints of the system. Further, an adaptive filer is fitted to the modeled correlation to avoid negative impact of feedforward control because of uncorrelated frequencies of the wind measurement. The main results of the presented work are a first estimate of the wind evolution in front of operating wind turbines and an approach which manufacturers of

CoMet: an airborne mission to simultaneously measure CO2 and CH4 using lidar, passive remote sensing, and in-situ techniques

Science.gov (United States)

Fix, Andreas; Amediek, Axel; Bovensmann, Heinrich; Ehret, Gerhard; Gerbig, Christoph; Gerilowski, Konstantin; Pfeilsticker, Klaus; Roiger, Anke; Zöger, Martin

2018-04-01

TIn order to improve our current knowledge on the budgets of the two most important anthropogenic greenhouse gases, CO2 and CH4, an airborne mission on board the German research aircraft HALO in coordination with two smaller Cessna aircraft is going to be conducted in April/May 2017. The goal of CoMet is to combine a suite of the best currently available active (lidar) and passive remote sensors as well as in-situ instruments to provide regional-scale data of greenhouse gases which are urgently required.

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.

Remote sensing of sulphur dioxide emissions of sea-going vessels through lidar; Zwaveldioxide-uitstoot van zeeschepen op afstand gemeten met lidar

Energy Technology Data Exchange (ETDEWEB)

Berkhout, A J.C.; Swart, D P.J.; Van der Hoff, G R; Bergwerff, J B

2011-12-15

RIVM developed an instrument to measure from the shore sulphur dioxide emissions of passing sea-going vessels. This instrument uses the lidar technique (Light Detection And Ranging). The instrument uses a laser beam to scan the exhaust plume from a passing ship and determine the emission, unnoticed. It was used from 2006 to 2008 to measure sulphur dioxide emissions from a large number of ships sailing on the Westerscheldt estuary and on the North Sea Canal. The highest measured emission was 37 gram per second. The total emission of sulphur dioxide in the Netherlands has been declining for many years. Since 2006, emissions from ocean shipping are declining as well, but not as fast as those from other sources. Therefore, the contribution from ocean shipping is gaining importance. In 2010, 55 percent of the Dutch sulphur dioxide emissions originated with sea-going vessels. In 1990, this was 21 percent. Sea-going ships are not allowed to use sulphur-rich fuel in territorial waters and at the North Sea. This relatively cheap fuel may be on board, though, for use elsewhere at sea. To what extent ship owners comply with this ban is not known. Traditional measurement methods involve taking fuel samples on board. This requires someone boarding the ship. The crew therefore knows a measurement is taking place and can adjust the type of fuel used. Moreover, with traditional methods, only a few ships per day can be checked. Lidar is not yet recognised as a law enforcement instrument. Therefore, no fines can be imposed based on lidar measurements only. The lidar may be used, though, to identify possible offenders. A law enforcement official may then board that ship to ascertain that the law was breached. When used in this way, the use of the lidar is cost-effective even now. This is because the lidar can measure almost all passing ships. Expensive patrol ships can then be directed to only visit those ships that are the most likely offenders. Moreover, this greatly increases the

Remote measurement of atmospheric pollutants with laser techniques

Energy Technology Data Exchange (ETDEWEB)

Corio, W; Querzola, B; Zanzottera, E

1979-03-01

Laser techniques for the remote sensing of atmospheric pollutants are reviewed, with attention given to lidars based on Rayleigh and Mie scattering, the Raman effect, or fluorescent scattering. Emphasis is placed on differential absorption lidars, which rely on Rayleigh or Mie scattering for measurements made in the IR or in the visible-UV range, respectively. A comprehensive air pollution monitoring program based on differential absorption lidars, together with systems using fluorescent backscattering and absorption measurements with topographic backscattering, is described.

2009 Bayfield County Lake Superior Lidar Survey

Data.gov (United States)

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

Polar winter cloud depolarization measurements with the CANDAC Rayleigh-Mie-Raman Lidar

Science.gov (United States)

McCullough, E. M.; Nott, G. J.; Duck, T. J.; Sica, R. J.; Doyle, J. G.; Pike-thackray, C.; Drummond, J. R.

2011-12-01

Clouds introduce a significant positive forcing to the Arctic radiation budget and this is strongest during the polar winter when shortwave radiation is absent (Intrieri et al., 2002). The amount of forcing depends on the occurrence probability and optical depth of the clouds as well as the cloud particle phase (Ebert and Curry 1992). Mixed-phase clouds are particularly complex as they involve interactions between three phases of water (vapour, liquid and ice) coexisting in the same cloud. Although significant progress has been made in characterizing wintertime Arctic clouds (de Boer et al., 2009 and 2011), there is considerable variability in the relative abundance of particles of each phase, in the morphology of solid particles, and in precipitation rates depending on the meteorology at the time. The Canadian Network for the Detection of Atmospheric Change (CANDAC) Rayleigh-Mie-Raman Lidar (CRL) was installed in the Canadian High Arctic at Eureka, Nunavut (80°N, 86°W) in 2008-2009. The remotely-operated system began with measurement capabilities for multi-wavelength aerosol extinction, water vapour mixing ratio, and tropospheric temperature profiles, as well as backscatter cross section coefficient and colour ratio. In 2010, a new depolarization channel was added. The capability to measure the polarization state of the return signal allows the characterization of the cloud in terms of liquid and ice water content, enabling the lidar to probe all three phases of water in these clouds. Lidar depolarization results from 2010 and 2011 winter clouds at Eureka will be presented, with a focus on differences in downwelling radiation between mixed phase clouds and ice clouds. de Boer, G., E.W. Eloranta, and M.D. Shupe (2009), Arctic mixed-phase stratiform cloud properties from multiple years of surface-based measurements at two high-latitude locations, Journal of Atmospheric Sciences, 66 (9), 2874-2887. de Boer, G., H. Morrison, M. D. Shupe, and R. Hildner (2011

Characterizing Urban Volumetry Using LIDAR Data

Science.gov (United States)

Santos, T.; Rodrigues, A. M.; Tenedório, J. A.

2013-05-01

Urban indicators are efficient tools designed to simplify, quantify and communicate relevant information for land planners. Since urban data has a strong spatial representation, one can use geographical data as the basis for constructing information regarding urban environments. One important source of information about the land status is imagery collected through remote sensing. Afterwards, using digital image processing techniques, thematic detail can be extracted from those images and used to build urban indicators. Most common metrics are based on area (2D) measurements. These include indicators like impervious area per capita or surface occupied by green areas, having usually as primary source a spectral image obtained through a satellite or airborne camera. More recently, laser scanning data has become available for large-scale applications. Such sensors acquire altimetric information and are used to produce Digital Surface Models (DSM). In this context, LiDAR data available for the city is explored along with demographic information, and a framework to produce volumetric (3D) urban indexes is proposed, and measures like Built Volume per capita, Volumetric Density and Volumetric Homogeneity are computed.

2007 Northwest Florida Water Management District (NWFWMD) Lidar: North Jefferson County

Data.gov (United States)

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

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.

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.

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

Science.gov (United States)

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

2013-12-01

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

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.

Application of backpack Lidar to geological cross-section measurement

Science.gov (United States)

Lin, Jingyu; Wang, Ran; Xiao, Zhouxuan; Li, Lu; Yao, Weihua; Han, Wei; Zhao, Baolin

2017-11-01

As the traditional geological cross section measurement, the artificial traverse method was recently substituted by using point coordinates data. However, it is still the crux of the matter that how to acquire the high-precision point coordinates data quickly and economically. Thereby, the backpack Lidar is presented on the premise of the principle of using point coordinates in this issue. Undoubtedly, Lidar technique, one of booming and international active remote sensing techniques, is a powerful tool in obtaining precise topographic information, high-precision 3-D coordinates and building a real 3-D model. With field practice and date processing indoors, it is essentially accomplished that geological sections maps could be generated simply, accurately and automatically in the support of relevant software such as ArcGIS and LiDAR360.

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.

Mapping migratory bird prevalence using remote sensing data fusion.

Science.gov (United States)

Swatantran, Anu; Dubayah, Ralph; Goetz, Scott; Hofton, Michelle; Betts, Matthew G; Sun, Mindy; Simard, Marc; Holmes, Richard

2012-01-01

Improved maps of species distributions are important for effective management of wildlife under increasing anthropogenic pressures. Recent advances in lidar and radar remote sensing have shown considerable potential for mapping forest structure and habitat characteristics across landscapes. However, their relative efficacies and integrated use in habitat mapping remain largely unexplored. We evaluated the use of lidar, radar and multispectral remote sensing data in predicting multi-year bird detections or prevalence for 8 migratory songbird species in the unfragmented temperate deciduous forests of New Hampshire, USA. A set of 104 predictor variables describing vegetation vertical structure and variability from lidar, phenology from multispectral data and backscatter properties from radar data were derived. We tested the accuracies of these variables in predicting prevalence using Random Forests regression models. All data sets showed more than 30% predictive power with radar models having the lowest and multi-sensor synergy ("fusion") models having highest accuracies. Fusion explained between 54% and 75% variance in prevalence for all the birds considered. Stem density from discrete return lidar and phenology from multispectral data were among the best predictors. Further analysis revealed different relationships between the remote sensing metrics and bird prevalence. Spatial maps of prevalence were consistent with known habitat preferences for the bird species. Our results highlight the potential of integrating multiple remote sensing data sets using machine-learning methods to improve habitat mapping. Multi-dimensional habitat structure maps such as those generated from this study can significantly advance forest management and ecological research by facilitating fine-scale studies at both stand and landscape level.

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....

Lidars for oceanological research: criteria for comparison, main limitations, perspectives

Science.gov (United States)

Feigels, Victor I.

1992-12-01

The paper contains a comparative analysis and discussion of resultant recommendations for the optimization of an airborne lidar's parameters, with application to modern lidar systems as employed in various countries for the ocean and continental shelf research. As criteria for the systems comparison in different remote sensing conditions (aircraft altitude, depth, day/night, zenithal sun angle, sea-water attenuation coefficient, receiver optical system's field of view (FOV), laser wavelength, etc.,) Sakitt's D-index of discriminability is used. We demonstrate the optical signal, as determined by the following process: reflecting from boundary -- backscattering in the atmosphere -- secondary reflecting from boundary, to be the cause for limiting the distance of underwater measurements. Some estimates for the bottom depth values to be achieved by a `super-lidar' are presented.

Time series analysis of continuous-wave coherent Doppler Lidar wind measurements

DEFF Research Database (Denmark)

Sjöholm, Mikael; Mikkelsen, Torben; Mann, Jakob

2008-01-01

The influence of spatial volume averaging of a focused 1.55 mu m continuous-wave coherent Doppler Lidar on observed wind turbulence measured in the atmospheric surface layer over homogeneous terrain is described and analysed. Comparison of Lidar-measured turbulent spectra with spectra simultaneou......The influence of spatial volume averaging of a focused 1.55 mu m continuous-wave coherent Doppler Lidar on observed wind turbulence measured in the atmospheric surface layer over homogeneous terrain is described and analysed. Comparison of Lidar-measured turbulent spectra with spectra...

Lidar Range-Resolved Optical Remote Sensing of the Atmosphere

CERN Document Server

Weitkamp, Claus

2005-01-01

Written by leading experts in optical radar, or lidar, this book brings all the recent practices up-to-date and covers a multitude of applications, from atmospheric sciences to environmental protection. Its broad cross-disciplinary scope should appeal to both the experienced scientist and the novice in the field. The Foreword is by one of the early pioneers in the area, Herbert Walther.

Beyond 3-D: The New Spectrum of Lidar Applications for Earth and Ecological Sciences

Science.gov (United States)

Eitel, Jan U. H.; Hofle, Bernhard; Vierling, Lee A.; Abellan, Antonio; Asner, Gregory P.; Deems, Jeffrey S.; Glennie, Craig L.; Joerg, Phillip C.; LeWinter, Adam L.; Magney, Troy S.;

Lidar cross-sections of soot fractal aggregates: Assessment of equivalent-sphere models

Science.gov (United States)

Ceolato, Romain; Gaudfrin, Florian; Pujol, Olivier; Riviere, Nicolas; Berg, Matthew J.; Sorensen, Christopher M.

2018-06-01

This work assesses the ability of equivalent-sphere models to reproduce the optical properties of soot aggregates relevant for lidar remote sensing, i.e. the backscattering and extinction cross sections. Lidar cross-sections are computed with a spectral discrete dipole approximation model over the visible-to-infrared (400-5000 nm) spectrum and compared with equivalent-sphere approximations. It is shown that the equivalent-sphere approximation, applied to fractal aggregates, has a limited ability to calculate such cross-sections well. The approximation should thus be used with caution for the computation of broadband lidar cross-sections, especially backscattering, at small and intermediate wavelengths (e.g. UV to visible).

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...

Automated integration of lidar into the LANDFIRE product suite

Science.gov (United States)

Peterson, Birgit; Nelson, Kurtis; Seielstad, Carl; Stoker, Jason M.; Jolly, W. Matt; Parsons, Russell

2015-01-01

Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure. Although lidar data are increasingly available, they have rarely been applied to wildland fuels mapping efforts, mostly due to two issues. First, the Landscape Fire and Resource Planning Tools (LANDFIRE) program, which has become the default source of large-scale fire behaviour modelling inputs for the US, does not currently incorporate lidar data into the vegetation and fuel mapping process because spatially continuous lidar data are not available at the national scale. Second, while lidar data are available for many land management units across the US, these data are underutilized for fire behaviour applications. This is partly due to a lack of local personnel trained to process and analyse lidar data. This investigation addresses these issues by developing the Creating Hybrid Structure from LANDFIRE/lidar Combinations (CHISLIC) tool. CHISLIC allows individuals to automatically generate a suite of vegetation structure and wildland fuel parameters from lidar data and infuse them into existing LANDFIRE data sets. CHISLIC will become available for wider distribution to the public through a partnership with the U.S. Forest Service’s Wildland Fire Assessment System (WFAS) and may be incorporated into the Wildland Fire Decision Support System (WFDSS) with additional design and testing. WFAS and WFDSS are the primary systems used to support tactical and strategic wildland fire management decisions.

Lidar Technology at the Goddard Laser and Electro-Optics Branch

Science.gov (United States)

Heaps, William S.; Obenschain, Arthur F. (Technical Monitor)

2000-01-01

Discovery-class orbiters now in the NASA planetary program. The purpose of the lidar is to continuously profile the water vapor and dust in the Mars atmosphere from orbit in order to quantify its dynamics, their relationship in the diurnal cycles, and to infer water vapor exchange with the Mars surface. To remotely measure the water-vapor height profiles, we will use the differential absorption lidar (DIAL) technique. We are also developing a laser sensor for measuring the total column content of CO2 in the atmosphere of the earth. CO2 is the principal greenhouse gas and has increased by roughly 80 ppm in the last century and a half. We will report our efforts in the development of the laser transmitter and photon counting detector components for a Mars Orbiting DIAL system and for the CO2 sounder.

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.

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

Data.gov (United States)

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

Investigating impacts of natural and human-induced environmental changes on hydrological processes and flood hazards using a GIS-based hydrological/hydraulic model and remote sensing data

Science.gov (United States)

Wang, Lei

Natural and human-induced environmental changes have been altering the earth's surface and hydrological processes, and thus directly contribute to the severity of flood hazards. To understand these changes and their impacts, this research developed a GIS-based hydrological and hydraulic modeling system, which incorporates state-of-the-art remote sensing data to simulate flood under various scenarios. The conceptual framework and technical issues of incorporating multi-scale remote sensing data have been addressed. This research develops an object-oriented hydrological modeling framework. Compared with traditional lumped or cell-based distributed hydrological modeling frameworks, the object-oriented framework allows basic spatial hydrologic units to have various size and irregular shape. This framework is capable of assimilating various GIS and remotely-sensed data with different spatial resolutions. It ensures the computational efficiency, while preserving sufficient spatial details of input data and model outputs. Sensitivity analysis and comparison of high resolution LIDAR DEM with traditional USGS 30m resolution DEM suggests that the use of LIDAR DEMs can greatly reduce uncertainty in calibration of flow parameters in the hydrologic model and hence increase the reliability of modeling results. In addition, subtle topographic features and hydrologic objects like surface depressions and detention basins can be extracted from the high resolution LiDAR DEMs. An innovative algorithm has been developed to efficiently delineate surface depressions and detention basins from LiDAR DEMs. Using a time series of Landsat images, a retrospective analysis of surface imperviousness has been conducted to assess the hydrologic impact of urbanization. The analysis reveals that with rapid urbanization the impervious surface has been increased from 10.1% to 38.4% for the case study area during 1974--2002. As a result, the peak flow for a 100-year flood event has increased by 20% and

Remote surface testing and inspection vehicle

International Nuclear Information System (INIS)

Hyde, E.A.; Goldsmith, H.A.; Proudlove, M.J.

1981-01-01

A remotely controlled vehicle capable of roving over the outer surface of a nuclear reactor primary vessel carrying inspection instrumentation. The vehicle comprises an elongate bridge having a pair of suction support pads. Each pad carries gas thrusters for acting in opposition to the suction effort thereby to reduce adherence of the pads and enable displacement of the vehicle over the surface. The vehicle is supported by a services conducting umbilical. (author)

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.

Automated integration of lidar into the LANDFIRE product suite

Science.gov (United States)

Birgit Peterson; Kurtis J. Nelson; Carl Seielstad; Jason Stoker; W. Matt Jolly; Russell Parsons

2015-01-01

Accurate information about three-dimensional canopy structure and wildland fuel across the landscape is necessary for fire behaviour modelling system predictions. Remotely sensed data are invaluable for assessing these canopy characteristics over large areas; lidar data, in particular, are uniquely suited for quantifying three-dimensional canopy structure. Although...

NASA Goddards LiDAR, Hyperspectral and Thermal (G-LiHT) Airborne Imager

Science.gov (United States)

Cook, Bruce D.; Corp, Lawrence A.; Nelson, Ross F.; Middleton, Elizabeth M.; Morton, Douglas C.; McCorkel, Joel T.; Masek, Jeffrey G.; Ranson, Kenneth J.; Ly, Vuong; Montesano, Paul M.

2013-01-01

The combination of LiDAR and optical remotely sensed data provides unique information about ecosystem structure and function. Here, we describe the development, validation and application of a new airborne system that integrates commercial off the shelf LiDAR hyperspectral and thermal components in a compact, lightweight and portable system. Goddard's LiDAR, Hyperspectral and Thermal (G-LiHT) airborne imager is a unique system that permits simultaneous measurements of vegetation structure, foliar spectra and surface temperatures at very high spatial resolution (approximately 1 m) on a wide range of airborne platforms. The complementary nature of LiDAR, optical and thermal data provide an analytical framework for the development of new algorithms to map plant species composition, plant functional types, biodiversity, biomass and carbon stocks, and plant growth. In addition, G-LiHT data enhance our ability to validate data from existing satellite missions and support NASA Earth Science research. G-LiHT's data processing and distribution system is designed to give scientists open access to both low- and high-level data products (http://gliht.gsfc.nasa.gov), which will stimulate the community development of synergistic data fusion algorithms. G-LiHT has been used to collect more than 6,500 km2 of data for NASA-sponsored studies across a broad range of ecoregions in the USA and Mexico. In this paper, we document G-LiHT design considerations, physical specifications, instrument performance and calibration and acquisition parameters. In addition, we describe the data processing system and higher-level data products that are freely distributed under NASA's Data and Information policy.

Predicting live and dead tree basal area of bark beetle affected forests from discrete-return lidar

Science.gov (United States)

Benjamin C. Bright; Andrew T. Hudak; Robert McGaughey; Hans-Erik Andersen; Jose Negron

2013-01-01

Bark beetle outbreaks have killed large numbers of trees across North America in recent years. Lidar remote sensing can be used to effectively estimate forest biomass, but prediction of both live and dead standing biomass in beetle-affected forests using lidar alone has not been demonstrated. We developed Random Forest (RF) models predicting total, live, dead, and...

Extrapolating active layer thickness measurements across Arctic polygonal terrain using LiDAR and NDVI data sets.

Science.gov (United States)

Gangodagamage, Chandana; Rowland, Joel C; Hubbard, Susan S; Brumby, Steven P; Liljedahl, Anna K; Wainwright, Haruko; Wilson, Cathy J; Altmann, Garrett L; Dafflon, Baptiste; Peterson, John; Ulrich, Craig; Tweedie, Craig E; Wullschleger, Stan D

2014-08-01

Landscape attributes that vary with microtopography, such as active layer thickness ( ALT ), are labor intensive and difficult to document effectively through in situ methods at kilometer spatial extents, thus rendering remotely sensed methods desirable. Spatially explicit estimates of ALT can provide critically needed data for parameterization, initialization, and evaluation of Arctic terrestrial models. In this work, we demonstrate a new approach using high-resolution remotely sensed data for estimating centimeter-scale ALT in a 5 km 2 area of ice-wedge polygon terrain in Barrow, Alaska. We use a simple regression-based, machine learning data-fusion algorithm that uses topographic and spectral metrics derived from multisensor data (LiDAR and WorldView-2) to estimate ALT (2 m spatial resolution) across the study area. Comparison of the ALT estimates with ground-based measurements, indicates the accuracy (r 2  = 0.76, RMSE ±4.4 cm) of the approach. While it is generally accepted that broad climatic variability associated with increasing air temperature will govern the regional averages of ALT , consistent with prior studies, our findings using high-resolution LiDAR and WorldView-2 data, show that smaller-scale variability in ALT is controlled by local eco-hydro-geomorphic factors. This work demonstrates a path forward for mapping ALT at high spatial resolution and across sufficiently large regions for improved understanding and predictions of coupled dynamics among permafrost, hydrology, and land-surface processes from readily available remote sensing data.

2006 Federal Emergency Management Agency (FEMA) Topographic LiDAR: Connecticut Coastline Survey

Data.gov (United States)

National Oceanic and Atmospheric Administration, Department of Commerce — LIDAR data is remotely sensed high-resolution elevation data collected by an airborne collection platform. By positioning laser range finding with the use of 1...

Cloud Physics Lidar Measurements During the SAFARI-2000 Field Campaign

Science.gov (United States)

McGill, Matthew; Hlavka, Dennis; Hart, William; Spinhirne, James; Scott, Stan; Starr, David OC. (Technical Monitor)

2001-01-01

A new remote sensing instrument, the Cloud Physics Lidar (CPL) has been built for use on the ER-2 aircraft. The first deployment for CPL was the SAFARI-2000 field campaign during August-September 2000. The CPL is a three-wavelength lidar designed for studies of cirrus, subvisual cirrus, and boundary layer aerosols. The CPL utilizes a high repetition rate, low pulse energy laser with photon counting detectors. A brief description of the CPL instrument will be given, followed by examples of CPL data products. In particular, examples of aerosol backscatter, including boundary layer smoke and cirrus clouds will be shown. Resulting optical depth estimates derived from the aerosol measurements will be shown. Comparisons of the CPL optical depth and optical depth derived from microPulse Lidar and the AATS-14 sunphotomer will be shown.

Quantitative determination of optical aerosol properties with lidar at 0.53 and 1.06 mum wavelength

NARCIS (Netherlands)

Salemink H; Schotanus P; Bergwerff J; van der Meulen A

1984-01-01

Beschreven wordt de kwantitatieve detectie van aerosol in de atmosferische grenslaag tot een hoogte van 1,5 km (remote sensing m.b.v. laser-radar). Voor optische aerosol-eigenschappen wordt goede overeenkomst gevonden tussen lidar (remote) en lokale waarnemingen in vliegtuig en op grondniveau.

Twomey effect in subtropical stratocumulus clouds from UV depolarization lidar

NARCIS (Netherlands)

de Graaf, M.; Brown, Jessica; Donovan, D.P.; Nicolae, D.; Makoto, A.; Vassilis, A.; Balis, D.; Behrendt, A.; Comeron, A.; Gibert, F.; Landulfo, E.; McCormick, M.P.; Senff, C.; Veselovskii, I.; Wandinger, U.

2018-01-01

Marine stratocumulus clouds are important climate regulators, reflecting sunlight over a dark ocean background. A UV-depolarization lidar on Ascension, a small remote island in the south Atlantic, measured cloud droplet sizes and number concentration using an inversion method based on Monte Carlo

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.

Typical Applications of Airborne LIDAR Technolagy in Geological Investigation

Science.gov (United States)

Zheng, X.; Xiao, C.

2018-05-01

The technology of airborne light detection and ranging (LiDAR), also referred to as Airborne Laser Scanning, is widely used for high-resolution topographic data acquisition (even under forest cover) with sub-meter planimetric and vertical accuracy. This contribution constructs the real digital terrain model to provide the direct observation data for the landscape analysis in geological domains. Based on the advantage of LiDAR, the authors mainly deal with the applications of LiDAR data to such fields as surface land collapse, landslide and fault structure extraction. The review conclusion shows that airborne LiDAR technology is becoming an indispensable tool for above mentioned issues, especially in the local and large scale investigations of micro-topography. The technology not only can identify the surface collapse, landslide boundary and subtle faulted landform, but also be able to extract the filling parameters of collapsed surface, the geomorphic parameters of landslide stability evaluation and cracks. This technology has extensive prospect of applications in geological investigation.

TYPICAL APPLICATIONS OF AIRBORNE LIDAR TECHNOLAGY IN GEOLOGICAL INVESTIGATION

Directory of Open Access Journals (Sweden)

X. Zheng

2018-05-01

Full Text Available The technology of airborne light detection and ranging (LiDAR, also referred to as Airborne Laser Scanning, is widely used for high-resolution topographic data acquisition (even under forest cover with sub-meter planimetric and vertical accuracy. This contribution constructs the real digital terrain model to provide the direct observation data for the landscape analysis in geological domains. Based on the advantage of LiDAR, the authors mainly deal with the applications of LiDAR data to such fields as surface land collapse, landslide and fault structure extraction. The review conclusion shows that airborne LiDAR technology is becoming an indispensable tool for above mentioned issues, especially in the local and large scale investigations of micro-topography. The technology not only can identify the surface collapse, landslide boundary and subtle faulted landform, but also be able to extract the filling parameters of collapsed surface, the geomorphic parameters of landslide stability evaluation and cracks. This technology has extensive prospect of applications in geological investigation.

Application of lidars for assessment of wind conditions on a bridge site

DEFF Research Database (Denmark)

Jakobsen, J. B.; Cheynet, Etienne; Snæbjörnsson, Jonas

2015-01-01

Wind measurement techniques based on remote optical sensing, extensively applied in wind energy, have been exploited in civil engineering only in a limited number of studies. The present paper introduces a novel application of wind lidars in bridge engineering, and presents the findings from...... characterization. The paper presents a promising comparison of the measurements obtained by the three different sets of instruments, and discusses their complementary value....... the pilot measurement campaign on the Lysefjord Bridge in the South-West Norway. A single long-range pulsed WindScanner lidar and two short-range continuous-wave WindScanner lidars were deployed, in addition to five sonic anemometers installed on the bridge itself, the latter for long-term wind...

TOLNet ozone lidar intercomparison during the discover-aq and frappé campaigns

Science.gov (United States)

Newchurch, Michael J.; Alvarez, Raul J.; Berkoff, Timothy A.; Carrion, William; DeYoung, Russell J.; Ganoe, Rene; Gronoff, Guillaume; Kirgis, Guillaume; Kuang, Shi; Langford, Andy O.; Leblanc, Thierry; McGee, Thomas J.; Pliutau, Denis; Senff, Christoph; Sullivan, John T.; Sumnicht, Grant; Twigg, Laurence W.; Wang, Lihua

2018-04-01

The Tropospheric Ozone Lidar Network (TOLNet) is a unique network of lidar systems that measure atmospheric profiles of ozone and aerosols, to contribute to air-quality studies, atmospheric modeling, and satellite validation efforts. The accurate characterization of these lidars is of critical interest, and is necessary to determine cross-instrument calibration uniformity. From July to August 2014, three lidars, the TROPospheric OZone (TROPOZ) lidar, the Tunable Optical Profiler for Aerosol and oZone (TOPAZ) lidar, and the Langley Mobile Ozone Lidar (LMOL), of TOLNet participated in the "Deriving Information on Surface conditions from Column and Vertically Resolved Observations Relevant to Air Quality" (DISCOVER-AQ) mission and the "Front Range Air Pollution and Photochemistry Éxperiment" (FRAPPÉ) to measure sub-hourly ozone variations from near the surface to the top of the troposphere. Although large differences occur at few individual altitudes in the near field and far field range, the TOLNet lidars agree with each other within ±4%. These results indicate excellent measurement accuracy for the TOLNet lidars that is suitable for use in air-quality and ozone modeling efforts.

Determining Hydroperiod for Boreal and Prairie Pothole Wetlands using SAR, Optical and LiDAR Remote Sensing Data Fusion

Science.gov (United States)

Montgomery, J. S.; Hopkinson, C.; Brisco, B.; Patterson, S.; Chasmer, L.; Mahoney, C.

2017-12-01

Cultivation, irrigation networks, and infrastructure have all greatly impacted the ecology and hydrology of the Prairie Pothole and Boreal regions of western Canada. Due to sub-humid climate and high potential evaporation, many wetlands in these natural regions are seldom continuously occupied by water, and are often confined to local depressions. In the Boreal region, wetlands may be difficult to monitor due to their remote location, whereas prairie wetlands have highly varying degrees of surface water and soil saturation throughout the year. This study examines how high-resolution Lidar, Synthetic Aperture Radar (SAR), and optical data can be utilized in spatial-temporal studies to classify wetlands based on water extent, riparian vegetation, and topographic characteristics. An intensity (dB) threshold routine was used to extract open surface water extent to determine hydroperiod. Digital Elevation Models (DEM) are used with a topographic position index to infer local depressions, while Digital Surface Models (DSMs) are used to characterise vegetation structural characteristics within and proximal to wetlands. The proposed framework provides an index of wetland permanence and wetland class, where permanence varies seasonally and annually. Boreal wetland hydroperiod is less variable than that found in prairie pothole wetlands, most notably the semi-permanent class, varying by only 2%, compared to >50% in prairie pothole wetlands. For years studied, prairie pothole wetlands reached maximum water extent following major rainfall events. Seasonal and semi-permanent wetlands were found to have greater change in surface water between years than temporary wetlands (75.3% and 59.1% from average respectively). The lowest frequency of water pixel inundation for seasonal and semi-permanent wetlands was found to be in the year with the most precipitation during the growing season (2013, 384mm), compared to 2014 (289mm), and 2015 (310mm). A combination of statistical analyses

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.

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

Directory of Open Access Journals (Sweden)

S. Daneshtalab

2017-09-01

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

Automated Tree Crown Delineation and Biomass Estimation from Airborne LiDAR data: A Comparison of Statistical and Machine Learning Methods

Science.gov (United States)

Gleason, C. J.; Im, J.

2011-12-01

Airborne LiDAR remote sensing has been used effectively in assessing forest biomass because of its canopy penetrating effects and its ability to accurately describe the canopy surface. Current research in assessing biomass using airborne LiDAR focuses on either the individual tree as a base unit of study or statistical representations of a small aggregation of trees (i.e., plot level), and both methods usually rely on regression against field data to model the relationship between the LiDAR-derived data (e.g., volume) and biomass. This study estimates biomass for mixed forests and coniferous plantations (Picea Abies) within Heiberg Memorial Forest, Tully, NY, at both the plot and individual tree level. Plots are regularly spaced with a radius of 13m, and field data include diameter at breast height (dbh), tree height, and tree species. Field data collection and LiDAR data acquisition were seasonally coincident and both obtained in August of 2010. Resulting point cloud density was >5pts/m2. LiDAR data were processed to provide a canopy height surface, and a combination of watershed segmentation, active contouring, and genetic algorithm optimization was applied to delineate individual trees from the surface. This updated delineation method was shown to be more accurate than traditional watershed segmentation. Once trees had been delineated, four biomass estimation models were applied and compared: support vector regression (SVR), linear mixed effects regression (LME), random forest (RF), and Cubist regression. Candidate variables to be used in modeling were derived from the LiDAR surface, and include metrics of height, width, and volume per delineated tree footprint. Previously published allometric equations provided field estimates of biomass to inform the regressions and calculate their accuracy via leave-one-out cross validation. This study found that for forests such as found in the study area, aggregation of individual trees to form a plot-based estimate of

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

Directory of Open Access Journals (Sweden)

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.

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

New lidar challenges for gas hazard management in industrial environments

Science.gov (United States)

Cézard, Nicolas; Liméry, Anasthase; Bertrand, Johan; Le Méhauté, Simon; Benoit, Philippe; Fleury, Didier; Goular, Didier; Planchat, Christophe; Valla, Matthieu; Augère, Béatrice; Dolfi-Bouteyre, Agnès.

2017-10-01

The capability of Lidars to perform range-resolved gas profiles makes them an appealing choice for many applications. In order to address new remote sensing challenges, arising from industrial contexts, Onera currently develops two lidar systems, one Raman and one DIAL. On the Raman side, a high spatial-resolution multi-channel Raman Lidar is developed in partnership with the French National Radioactive Waste Management Agency (Andra). This development aims at enabling future monitoring of hydrogen gas and water vapor profiles inside disposal cells containing radioactive wastes. We report on the development and first tests of a three-channel Raman Lidar (H2, H2O, N2) designed to address this issue. Simultaneous hydrogen and water vapor profiles have been successfully performed along a 5m-long gas cell with 1m resolution at a distance of 85 m. On the DIAL side, a new instrumental concept is being explored and developed in partnership with Total E and P. The objective is to perform methane plume monitoring and flux assessment in the vicinity of industrials plants or platforms. For flux assessment, both gas concentration and air speed must be profiled by lidar. Therefore, we started developing a bi-function, all-fiber, coherent DIAL/Doppler Lidar. The first challenge was to design and build an appropriate fiber laser source. The achieved demonstrator delivers 200 W peak power, polarized, spectrally narrow (<15 MHz), 110 ns pulses of light out of a monomode fiber at 1645 nm. It fulfills the requirements for a future implementation in a bi-function Dial/Doppler lidar with km-range expectation. We report on the laser and lidar architecture, and on first lidar tests at 1645 nm.

Field performance of an all-semiconductor laser coherent Doppler lidar

DEFF Research Database (Denmark)

Rodrigo, Peter John; Pedersen, Christian

2012-01-01

We implement and test what, to our knowledge, is the first deployable coherent Doppler lidar (CDL) system based on a compact, inexpensive all-semiconductor laser (SL). To demonstrate the field performance of our SL-CDL remote sensor, we compare a 36 h time series of averaged radial wind speeds...... measured by our instrument at an 80 m distance to those simultaneously obtained from an industry-standard sonic anemometer (SA). An excellent degree of correlation (R2=0.994 and slope=0.996) is achieved from a linear regression analysis of the CDL versus SA wind speed data. The lidar system is capable...

Synergy of VSWIR and LiDAR for Ecosystem Structure, Biomass, and Canopy Diversity

Science.gov (United States)

Cook, Bruce D.; Asner, Gregory P.

2010-01-01

This slide presentation reviews the use of Visible ShortWave InfraRed (VSWIR) Imaging Spectrometer and LiDAR to study ecosystem structure, biomass and canopy diversity. It is shown that the biophysical data from LiDAR and biochemical information from hyperspectral remote sensing provides complementary data for: (1) describing spatial patterns of vegetation and biodiversity, (2) characterizing relationships between ecosystem form and function, and (3) detecting natural and human induced change that affects the biogeochemical cycles.

Derivation of Sky-View Factors from LIDAR Data

Science.gov (United States)

Kidd, Christopher; Chapman, Lee

2013-01-01

The use of Lidar (Light Detection and Ranging), an active light-emitting instrument, is becoming increasingly common for a range of potential applications. Its ability to provide fine resolution spatial and vertical resolution elevation data makes it ideal for a wide range of studies. This paper demonstrates the capability of Lidar data to measure sky view factors (SVF). The Lidar data is used to generate a spatial map of SVFs which are then compared against photographically-derived SVF at selected point locations. At each location three near-surface elevations measurements were taken and compared with collocated Lidar-derived estimated. It was found that there was generally good agreement between the two methodologies, although with decreasing SVF the Lidar-derived technique tended to overestimate the SVF: this can be attributed in part to the spatial resolution of the Lidar sampling. Nevertheless, airborne Lidar systems can map sky view factors over a large area easily, improving the utility of such data in atmospheric and meteorological models.

Combined Lidar-Radar Remote Sensing: Initial Results from CRYSTAL-FACE and Implications for Future Spaceflight Missions

Science.gov (United States)

McGill, Matthew J.; Li, Li-Hua; Hart, William D.; Heymsfield, Gerald M.; Hlavka, Dennis L.; Vaughan, Mark A.; Winker, David M.

2003-01-01

In the near future NASA plans to fly satellites carrying a multi-wavelength backscatter lidar and a 94-GHz cloud profiling radar in formation to provide complete global profiling of cloud and aerosol properties. The CRYSTAL-FACE field campaign, conducted during July 2002, provided the first high-altitude colocated measurements from lidar and cloud profiling radar to simulate these spaceborne sensors. The lidar and radar provide complementary measurements with varying degrees of measurement overlap. This paper presents initial results of the combined airborne lidar-radar measurements during CRYSTAL-FACE. The overlap of instrument sensitivity is presented, within the context of particular CRYSTAL-FACE conditions. Results are presented to quantify the portion of atmospheric profiles sensed independently by each instrument and the portion sensed simultaneously by the two instruments.

Temporal Data Fusion Approaches to Remote Sensing-Based Wetland Classification

Science.gov (United States)

Montgomery, Joshua S. M.

This thesis investigates the ecology of wetlands and associated classification in prairie and boreal environments of Alberta, Canada, using remote sensing technology to enhance classification of wetlands in the province. Objectives of the thesis are divided into two case studies, 1) examining how satellite borne Synthetic Aperture Radar (SAR), optical (RapidEye & SPOT) can be used to evaluate surface water trends in a prairie pothole environment (Shepard Slough); and 2) investigating a data fusion methodology combining SAR, optical and Lidar data to characterize wetland vegetation and surface water attributes in a boreal environment (Utikuma Regional Study Area (URSA)). Surface water extent and hydroperiod products were derived from SAR data, and validated using optical imagery with high accuracies (76-97% overall) for both case studies. High resolution Lidar Digital Elevation Models (DEM), Digital Surface Models (DSM), and Canopy Height Model (CHM) products provided the means for data fusion to extract riparian vegetation communities and surface water; producing model accuracies of (R2 0.90) for URSA, and RMSE of 0.2m to 0.7m at Shepard Slough when compared to field and optical validation data. Integration of Alberta and Canadian wetland classifications systems used to classify and determine economic value of wetlands into the methodology produced thematic maps relevant for policy and decision makers for potential wetland monitoring and policy development.

Aircraft Wake Vortex Measurement with Coherent Doppler Lidar

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Wu Songhua

2016-01-01

Full Text Available Aircraft vortices are generated by the lift-producing surfaces of the aircraft. The variability of near-surface conditions can change the drop rate and cause the cell of the wake vortex to twist and contort unpredictably. The pulsed Coherent Doppler Lidar Detection and Ranging is an indispensable access to real aircraft vortices behavior which transmitting a laser beam and detecting the radiation backscattered by atmospheric aerosol particles. Experiments for Coherent Doppler Lidar measurement of aircraft wake vortices has been successfully carried out at the Beijing Capital International Airport (BCIA. In this paper, the authors discuss the Lidar system, the observation modes carried out in the measurements at BCIA and the characteristics of vortices.

Effects of bathymetric lidar errors on flow properties predicted with a multi-dimensional hydraulic model

Science.gov (United States)

J. McKean; D. Tonina; C. Bohn; C. W. Wright

2014-01-01

New remote sensing technologies and improved computer performance now allow numerical flow modeling over large stream domains. However, there has been limited testing of whether channel topography can be remotely mapped with accuracy necessary for such modeling. We assessed the ability of the Experimental Advanced Airborne Research Lidar, to support a multi-dimensional...

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

Mapping multi-scale vascular plant richness in a forest landscape with integrated LiDAR and hyperspectral remote-sensing.

Science.gov (United States)

Hakkenberg, C R; Zhu, K; Peet, R K; Song, C

2018-02-01

The central role of floristic diversity in maintaining habitat integrity and ecosystem function has propelled efforts to map and monitor its distribution across forest landscapes. While biodiversity studies have traditionally relied largely on ground-based observations, the immensity of the task of generating accurate, repeatable, and spatially-continuous data on biodiversity patterns at large scales has stimulated the development of remote-sensing methods for scaling up from field plot measurements. One such approach is through integrated LiDAR and hyperspectral remote-sensing. However, despite their efficiencies in cost and effort, LiDAR-hyperspectral sensors are still highly constrained in structurally- and taxonomically-heterogeneous forests - especially when species' cover is smaller than the image resolution, intertwined with neighboring taxa, or otherwise obscured by overlapping canopy strata. In light of these challenges, this study goes beyond the remote characterization of upper canopy diversity to instead model total vascular plant species richness in a continuous-cover North Carolina Piedmont forest landscape. We focus on two related, but parallel, tasks. First, we demonstrate an application of predictive biodiversity mapping, using nonparametric models trained with spatially-nested field plots and aerial LiDAR-hyperspectral data, to predict spatially-explicit landscape patterns in floristic diversity across seven spatial scales between 0.01-900 m 2 . Second, we employ bivariate parametric models to test the significance of individual, remotely-sensed predictors of plant richness to determine how parameter estimates vary with scale. Cross-validated results indicate that predictive models were able to account for 15-70% of variance in plant richness, with LiDAR-derived estimates of topography and forest structural complexity, as well as spectral variance in hyperspectral imagery explaining the largest portion of variance in diversity levels. Importantly

Investigating the Potential of Using the Spatial and Spectral Information of Multispectral LiDAR for Object Classification

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Wei Gong

2015-09-01

Full Text Available The abilities of multispectral LiDAR (MSL as a new high-potential active instrument for remote sensing have not been fully revealed. This study demonstrates the potential of using the spectral and spatial features derived from a novel MSL to discriminate surface objects. Data acquired with the MSL include distance information and the intensities of four wavelengths at 556, 670, 700, and 780 nm channels. A support vector machine was used to classify diverse objects in the experimental scene into seven types: wall, ceramic pots, Cactaceae, carton, plastic foam block, and healthy and dead leaves of E. aureum. Different features were used during classification to compare the performance of different detection systems. The spectral backscattered reflectance of one wavelength and distance represented the features from an equivalent single-wavelength LiDAR system; reflectance of the four wavelengths represented the features from an equivalent multispectral image with four bands. Results showed that the overall accuracy of using MSL data was as high as 88.7%, this value was 9.8%–39.2% higher than those obtained using a single-wavelength LiDAR, and 4.2% higher than for multispectral image.

Detecting Precontact Anthropogenic Microtopographic Features in a Forested Landscape with Lidar: A Case Study from the Upper Great Lakes Region, AD 1000-1600.

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Howey, Meghan C L; Sullivan, Franklin B; Tallant, Jason; Kopple, Robert Vande; Palace, Michael W

2016-01-01

Forested settings present challenges for understanding the full extent of past human landscape modifications. Field-based archaeological reconnaissance in forests is low-efficiency and most remote sensing techniques are of limited utility, and together, this means many past sites and features in forests are unknown. Archaeologists have increasingly used light detection and ranging (lidar), a remote sensing tool that uses pulses of light to measure reflecting surfaces at high spatial resolution, to address these limitations. Archaeology studies using lidar have made significant progress identifying permanent structures built by large-scale complex agriculturalist societies. Largely unaccounted for, however, are numerous small and more practical modifications of landscapes by smaller-scale societies. Here we show these may also be detectable with lidar by identifying remnants of food storage pits (cache pits) created by mobile hunter-gatherers in the upper Great Lakes during Late Precontact (ca. AD 1000-1600) that now only exist as subtle microtopographic features. Years of intensive field survey identified 69 cache pit groups between two inland lakes in northern Michigan, almost all of which were located within ~500 m of a lakeshore. Applying a novel series of image processing techniques and statistical analyses to a high spatial resolution DTM we created from commercial-grade lidar, our detection routine identified 139 high potential cache pit clusters. These included most of the previously known clusters as well as several unknown clusters located >1500 m from either lakeshore, much further from lakeshores than all previously identified cultural sites. Food storage is understood to have emerged regionally as a risk-buffering strategy after AD 1000 but our results indicate the current record of hunter-gatherer cache pit food storage is markedly incomplete and this practice and its associated impact on the landscape may be greater than anticipated. Our study also

MERLIN: A French-German Space Lidar Mission Dedicated to Atmospheric Methane

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Gerhard Ehret

2017-10-01

Full Text Available The MEthane Remote sensing Lidar missioN (MERLIN aims at demonstrating the spaceborne active measurement of atmospheric methane, a potent greenhouse gas, based on an Integrated Path Differential Absorption (IPDA nadir-viewing LIght Detecting and Ranging (Lidar instrument. MERLIN is a joint French and German space mission, with a launch currently scheduled for the timeframe 2021/22. The German Space Agency (DLR is responsible for the payload, while the platform (MYRIADE Evolutions product line is developed by the French Space Agency (CNES. The main scientific objective of MERLIN is the delivery of weighted atmospheric columns of methane dry-air mole fractions for all latitudes throughout the year with systematic errors small enough (<3.7 ppb to significantly improve our knowledge of methane sources from global to regional scales, with emphasis on poorly accessible regions in the tropics and at high latitudes. This paper presents the MERLIN objectives, describes the methodology and the main characteristics of the payload and of the platform, and proposes a first assessment of the error budget and its translation into expected uncertainty reduction of methane surface emissions.

Methods from Information Extraction from LIDAR Intensity Data and Multispectral LIDAR Technology

Science.gov (United States)

Scaioni, M.; Höfle, B.; Baungarten Kersting, A. P.; Barazzetti, L.; Previtali, M.; Wujanz, D.

2018-04-01

LiDAR is a consolidated technology for topographic mapping and 3D reconstruction, which is implemented in several platforms On the other hand, the exploitation of the geometric information has been coupled by the use of laser intensity, which may provide additional data for multiple purposes. This option has been emphasized by the availability of sensors working on different wavelength, thus able to provide additional information for classification of surfaces and objects. Several applications ofmonochromatic and multi-spectral LiDAR data have been already developed in different fields: geosciences, agriculture, forestry, building and cultural heritage. The use of intensity data to extract measures of point cloud quality has been also developed. The paper would like to give an overview on the state-of-the-art of these techniques, and to present the modern technologies for the acquisition of multispectral LiDAR data. In addition, the ISPRS WG III/5 on `Information Extraction from LiDAR Intensity Data' has collected and made available a few open data sets to support scholars to do research on this field. This service is presented and data sets delivered so far as are described.

METHODS FROM INFORMATION EXTRACTION FROM LIDAR INTENSITY DATA AND MULTISPECTRAL LIDAR TECHNOLOGY

Directory of Open Access Journals (Sweden)

M. Scaioni

2018-04-01

Full Text Available LiDAR is a consolidated technology for topographic mapping and 3D reconstruction, which is implemented in several platforms On the other hand, the exploitation of the geometric information has been coupled by the use of laser intensity, which may provide additional data for multiple purposes. This option has been emphasized by the availability of sensors working on different wavelength, thus able to provide additional information for classification of surfaces and objects. Several applications ofmonochromatic and multi-spectral LiDAR data have been already developed in different fields: geosciences, agriculture, forestry, building and cultural heritage. The use of intensity data to extract measures of point cloud quality has been also developed. The paper would like to give an overview on the state-of-the-art of these techniques, and to present the modern technologies for the acquisition of multispectral LiDAR data. In addition, the ISPRS WG III/5 on ‘Information Extraction from LiDAR Intensity Data’ has collected and made available a few open data sets to support scholars to do research on this field. This service is presented and data sets delivered so far as are described.

LAnd surface remote sensing Products VAlidation System (LAPVAS) and its preliminary application

Science.gov (United States)

Lin, Xingwen; Wen, Jianguang; Tang, Yong; Ma, Mingguo; Dou, Baocheng; Wu, Xiaodan; Meng, Lumin

2014-11-01

The long term record of remote sensing product shows the land surface parameters with spatial and temporal change to support regional and global scientific research widely. Remote sensing product with different sensors and different algorithms is necessary to be validated to ensure the high quality remote sensing product. Investigation about the remote sensing product validation shows that it is a complex processing both the quality of in-situ data requirement and method of precision assessment. A comprehensive validation should be needed with long time series and multiple land surface types. So a system named as land surface remote sensing product is designed in this paper to assess the uncertainty information of the remote sensing products based on a amount of in situ data and the validation techniques. The designed validation system platform consists of three parts: Validation databases Precision analysis subsystem, Inter-external interface of system. These three parts are built by some essential service modules, such as Data-Read service modules, Data-Insert service modules, Data-Associated service modules, Precision-Analysis service modules, Scale-Change service modules and so on. To run the validation system platform, users could order these service modules and choreograph them by the user interactive and then compete the validation tasks of remote sensing products (such as LAI ,ALBEDO ,VI etc.) . Taking SOA-based architecture as the framework of this system. The benefit of this architecture is the good service modules which could be independent of any development environment by standards such as the Web-Service Description Language(WSDL). The standard language: C++ and java will used as the primary programming language to create service modules. One of the key land surface parameter, albedo, is selected as an example of the system application. It is illustrated that the LAPVAS has a good performance to implement the land surface remote sensing product

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

On Feature Extraction from Large Scale Linear LiDAR Data

Science.gov (United States)

Acharjee, Partha Pratim

Airborne light detection and ranging (LiDAR) can generate co-registered elevation and intensity map over large terrain. The co-registered 3D map and intensity information can be used efficiently for different feature extraction application. In this dissertation, we developed two algorithms for feature extraction, and usages of features for practical applications. One of the developed algorithms can map still and flowing waterbody features, and another one can extract building feature and estimate solar potential on rooftops and facades. Remote sensing capabilities, distinguishing characteristics of laser returns from water surface and specific data collection procedures provide LiDAR data an edge in this application domain. Furthermore, water surface mapping solutions must work on extremely large datasets, from a thousand square miles, to hundreds of thousands of square miles. National and state-wide map generation/upgradation and hydro-flattening of LiDAR data for many other applications are two leading needs of water surface mapping. These call for as much automation as possible. Researchers have developed many semi-automated algorithms using multiple semi-automated tools and human interventions. This reported work describes a consolidated algorithm and toolbox developed for large scale, automated water surface mapping. Geometric features such as flatness of water surface, higher elevation change in water-land interface and, optical properties such as dropouts caused by specular reflection, bimodal intensity distributions were some of the linear LiDAR features exploited for water surface mapping. Large-scale data handling capabilities are incorporated by automated and intelligent windowing, by resolving boundary issues and integrating all results to a single output. This whole algorithm is developed as an ArcGIS toolbox using Python libraries. Testing and validation are performed on a large datasets to determine the effectiveness of the toolbox and results are

The marbll experiment: towards a martian wind lidar

Directory of Open Access Journals (Sweden)

Määttänen Anni

2018-01-01

Full Text Available Operating a lidar on Mars would fulfill the need of accessing wind and aerosol profiles in the atmospheric boundary layer. This is the purpose of the MARs Boundary Layer Lidar (MARBLL instrument. We report recent developments of this compact direct-detection wind lidar designed to operate from the surface of Mars. A new laser source has been developed and an azimuthal scanning capability has been added. Preliminary results of a field campaign are presented.

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

Science.gov (United States)

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

2011-12-01

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

Comparison Study to the Use of Geophysical Methods at Archaeological Sites Observed by Various Remote Sensing Techniques in the Czech Republic

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Roman Křivánek

2017-09-01

Full Text Available A combination of geophysical methods could be very a useful and a practical way of verifying the origin and precise localisation of archaeological situations identified by different remote sensing techniques. The results of different methods (and scales of monitoring these fully non-destructive methods provide distinct data and often complement each other. The presented examples of combinations of these methods/techniques in this study (aerial survey, LIDAR-ALS and surface magnetometer or resistivity survey could provide information on some specifics and may also be limitations in surveying different archaeological terrains, types of archaeological situations and activities. The archaeological site in this contribution is considered to be a material of this study. In case of Neolithic ditch enclosure near Kolín were compared aerial prospection data, magnetometer survey and aerial photo-documentation of excavated site. In the case of hillforts near Levousy we compared LIDAR data with aerial photography and large-scale magnetometer survey. In the case of the medieval castle Liběhrad we compared LIDAR data with geoelectric resistivity measurement. In case of a burial mound cemetery we combined LIDAR data with magnetometer survey. In the case of the production area near Rynartice we combined LIDAR data with magnetometer and resistivity measurements and result of archaeological excavation. Fortunately for successful combination of geophysical and remote sensing results, their conditions and factors for efficient use in archaeology are not the same. On the other hand, the quality and state of many prehistoric, early medieval, medieval and also modern archaeological sites is rapidly changing over time and both groups of techniques represent important support for their comprehensive and precise documentation and protection.

CH4 IPDA Lidar mission data simulator and processor for MERLIN: prototype development at LMD/CNRS/Ecole Polytechnique

Science.gov (United States)

Olivier, Chomette; Armante, Raymond; Crevoisier, Cyril; Delahaye, Thibault; Edouart, Dimitri; Gibert, Fabien; Nahan, Frédéric; Tellier, Yoann

2018-04-01

The MEthane Remote sensing Lidar missioN (MERLIN), currently in phase C, is a joint cooperation between France and Germany on the development of a spatial Integrated Path Differential Absorption (IPDA) LIDAR (LIght Detecting And Ranging) to conduct global observations of atmospheric methane. This presentation will focus on the status of a LIDAR mission data simulator and processor developed at LMD (Laboratoire de Météorologie Dynamique), Ecole Polytechnique, France, for MERLIN to assess the performances in realistic observational situations.

Remote Sensing of Volcanic ASH at the Met Office

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Marenco F.

2016-01-01

Full Text Available The eruption of Eyjafjallajökull in 2010 has triggered the rapid development of volcanic ash remote sensing activities at the Met Office. Volcanic ash qualitative and quantitative mapping have been achieved using lidar on board the Facility for Airborne Atmospheric Measurements (FAAM research aircraft, and using improved satellite retrieval algorithms. After the eruption, a new aircraft facility, the Met Office Civil Contingencies Aircraft (MOCCA, has been set up to enable a rapid response, and a network of ground-based remote sensing sites with lidars and sunphotometers is currently being developed. Thanks to these efforts, the United Kingdom (UK will be much better equipped to deal with such a crisis, should it happen in the future.

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.

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.

The application of LiDAR to investigate foredune morphology and vegetation

Science.gov (United States)

Doyle, Thomas B.; Woodroffe, Colin D.

2018-02-01

LiDAR (Light Detection and Ranging) has been used to investigate coastal landform morphology, evolution, and change for almost a decade. Repeated airborne LiDAR surveys can provide the scientific community with significant observations of how shorelines have evolved, which may then enable forecasts of future patterns of change. However, there have been few studies that have considered the application of this new technology to the specific study of foredune morphology and vegetation. The accuracy and appropriateness of airborne LiDAR needs to be assessed, particularly where the density of vegetation may obscure the underlying topography, prior to interpreting derived geomorphic features. This study: i) tests the vertical accuracy of airborne LiDAR in 37 foredune systems along the coast of south-eastern Australia, and ii) demonstrates that it can be used to describe foredune morphology and vegetation in considerable detail. There was a strong correlation between the remotely-sensed LiDAR-derived elevation and field topographic and vegetation surveys (R2 = 0.96). A protocol for obtaining foredune geomorphic and botanical parameters is described. It enables widespread biogeomorphic characterisation along coasts for which LiDAR data is available, which can benefit both coastal managers and researchers alike.

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.

Advances in Small Remotely Piloted Aircraft Communications and Remote Sensing in Maritime Environments including the Arctic

Science.gov (United States)

McGillivary, P. A.; Borges de Sousa, J.; Wackowski, S.; Walker, G.

2011-12-01

Small remotely piloted aircraft have recently been used for maritime remote sensing, including launch and retrieval operations from land, ships and sea ice. Such aircraft can also function to collect and communicate data from other ocean observing system platforms including moorings, tagged animals, drifters, autonomous surface vessels (ASVs), and autonomous underwater vessels (AUVs). The use of small remotely piloted aircraft (or UASs, unmanned aerial systems) with a combination of these capabilities will be required to monitor the vast areas of the open ocean, as well as in harsh high-latitude ecosystems. Indeed, these aircraft are a key component of planned high latitude maritime domain awareness environmental data collection capabilities, including use of visible, IR and hyperspectral sensors, as well as lidar, meteorological sensors, and interferometric synthetic aperture radars (ISARs). We here first describe at-sea demonstrations of improved reliability and bandwidth of communications from ocean sensors on autonomous underwater vehicles to autonomous surface vessels, and then via remotely piloted aircraft to shore, ships and manned aircraft using Delay and Disruption Tolerant (DTN) communication protocols. DTN enables data exchange in communications-challenged environments, such as remote regions of the ocean including high latitudes where low satellite angles and auroral disturbances can be problematic. DTN provides a network architecture and application interface structured around optionally-reliable asynchronous message forwarding, with limited expectations of end-to-end connectivity and node resources. This communications method enables aircraft and surface vessels to function as data mules to move data between physically disparate nodes. We provide examples of the uses of this communication protocol for environmental data collection and data distribution with a variety of different remotely piloted aircraft in a coastal ocean environment. Next, we

Quantifying Wave Breaking Shape and Type in the Surf-Zone Using LiDAR

Science.gov (United States)

Albright, A.; Brodie, K. L.; Hartzell, P. J.; Glennie, C. L.

2017-12-01

Waves change shape as they shoal and break across the surf-zone, ultimately dissipating and transferring their energy into turbulence by either spilling or plunging. This injection of turbulence and changes in wave shape can affect the direction of sediment transport at the seafloor, and ultimately lead to morphological evolution. Typical methods for collecting wave data in the surf-zone include in-situ pressure gauges, velocimeters, ultrasonic sensors, and video imagery. Drawbacks to these data collection methods are low spatial resolution of point measurements, reliance on linear theory to calculate sea-surface elevations, and intensive computations required to extract wave properties from stereo 2D imagery. As a result, few field measurements of the shapes of plunging and/or spilling breakers exist, and existing knowledge is confined to results of laboratory studies. We therefore examine the use of a multi-beam scanning Light Detection and Ranging (LiDAR) remote sensing instrument with the goal of classifying the breaking type of propagating waves in the surf-zone and quantitatively determining wave morphometric properties. Data were collected with a Velodyne HDL-32E LiDAR scanner (360° vertical field of view) mounted on an arm of the Coastal Research Amphibious Buggy (CRAB) at the U.S. Army Corps of Engineers Field Research Facility in Duck, North Carolina. Processed laser scan data are used to visualize the lifecycle of a wave (shoaling, breaking, broken) and identify wave types (spilling, plunging, non-breaking) as they pass beneath the scanner. For each rotation of the LiDAR scanner, the point cloud data are filtered, smoothed, and detrended in order to identify individual waves and measure their properties, such as speed, height, period, upward/downward slope, asymmetry, and skewness. The 3D nature of point cloud data is advantageous for research, because it enables viewing from any angle. In our analysis, plan views are used to separate individual waves

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

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.

Remote Sensing of Crystal Shapes in Ice Clouds

Science.gov (United States)

van Diedenhoven, Bastiaan

2017-01-01

Ice crystals in clouds exist in a virtually limitless variation of geometries. The most basic shapes of ice crystals are columnar or plate-like hexagonal prisms with aspect ratios determined by relative humidity and temperature. However, crystals in ice clouds generally display more complex structures owing to aggregation, riming and growth histories through varying temperature and humidity regimes. Crystal shape is relevant for cloud evolution as it affects microphysical properties such as fall speeds and aggregation efficiency. Furthermore, the scattering properties of ice crystals are affected by their general shape, as well as by microscopic features such as surface roughness, impurities and internal structure. To improve the representation of ice clouds in climate models, increased understanding of the global variation of crystal shape and how it relates to, e.g., location, cloud temperature and atmospheric state is crucial. Here, the remote sensing of ice crystal macroscale and microscale structure from airborne and space-based lidar depolarization observations and multi-directional measurements of total and polarized reflectances is reviewed. In addition, a brief overview is given of in situ and laboratory observations of ice crystal shape as well as the optical properties of ice crystals that serve as foundations for the remote sensing approaches. Lidar depolarization is generally found to increase with increasing cloud height and to vary with latitude. Although this variation is generally linked to the variation of ice crystal shape, the interpretation of the depolarization remains largely qualitative and more research is needed before quantitative conclusions about ice shape can be deduced. The angular variation of total and polarized reflectances of ice clouds has been analyzed by numerous studies in order to infer information about ice crystal shapes from them. From these studies it is apparent that pristine crystals with smooth surfaces are generally

The lidar dark band: An oddity of the radar bright band analogy

Energy Technology Data Exchange (ETDEWEB)

Sassen, K. [Univ. of Utah, Salt Lake City, UT (United States)

1996-04-01

Although much has sbeen learned from independent radar and lidar studies of atmospheric precipitations, occasionally supported by aircraft profiling, what has been lacking is combined optical, microwave, and insitu observations of the melting layer. Fortunately, the rainshowers on April 21, 1994, during the Remote Cloud Sensing intensive obervations Period (RCSIOP) at the Southern Great Plains Cloud and radiation Testbed (CART) site provided an opportunity for coordinated dual-wavelength University of Utah Polarization Diversity Lidar, University of Massachusetts Cloud Profiling Radar System Doppler Radar, and the University of North Dakota Citation aircraft measurements.

Remote sensing of land surface temperature: The directional viewing effect

International Nuclear Information System (INIS)

Smith, J.A.; Schmugge, T.J.; Ballard, J.R. Jr.

1997-01-01

Land Surface Temperature (LST) is an important parameter in understanding global environmental change because it controls many of the underlying processes in the energy budget at the surface and heat and water transport between the surface and the atmosphere. The measurement of LST at a variety of spatial and temporal scales and extension to global coverage requires remote sensing means to achieve these goals. Land surface temperature and emissivity products are currently being derived from satellite and aircraft remote sensing data using a variety of techniques to correct for atmospheric effects. Implicit in the commonly employed approaches is the assumption of isotropy in directional thermal infrared exitance. The theoretical analyses indicate angular variations in apparent infrared temperature will typically yield land surface temperature errors ranging from 1 to 4 C unless corrective measures are applied

Windscanner: 3-D wind and turbulence measurements from three steerable doppler lidars

International Nuclear Information System (INIS)

Mikkelsen, T; Mann, J; Courtney, M; Sjoeholm, M

2008-01-01

At RISOe DTU we has started to build a new-designed laser-based lidar scanning facility for detailed remote measurements of the wind fields engulfing the huge wind turbines of today. Our aim is to measure in real-time 3D wind vector data at several hundred points every second: 1) upstream of the turbine, 2) near the turbine, and 3) in the wakes of the turbine rotors. Our first proto-type Windscanner is now being built from three commercially available Continuous Wave (CW) wind lidars modified with fast adjustable focus length and equipped with 2-D prism-based scan heads, in conjunction with a commercially available pulsed wind lidar for extended vertical profiling range. Design, construction and initial testing of the new 3-D wind lidar scanning facility are described and the functionality of the Windscanner and its potential as a new research facility within the wind energy community is discussed

CH4 IPDA Lidar mission data simulator and processor for MERLIN: prototype development at LMD/CNRS/Ecole Polytechnique

Directory of Open Access Journals (Sweden)

Olivier Chomette

2018-01-01

Full Text Available The MEthane Remote sensing Lidar missioN (MERLIN, currently in phase C, is a joint cooperation between France and Germany on the development of a spatial Integrated Path Differential Absorption (IPDA LIDAR (LIght Detecting And Ranging to conduct global observations of atmospheric methane. This presentation will focus on the status of a LIDAR mission data simulator and processor developed at LMD (Laboratoire de Météorologie Dynamique, Ecole Polytechnique, France, for MERLIN to assess the performances in realistic observational situations.

Studies on surface modification of poly(tetrafluoroethylene) film by remote and direct Ar plasma

International Nuclear Information System (INIS)

Wang Chen; Chen Jierong; Li Ru

2008-01-01

Poly(tetrafluoroethylene) (PTFE) surfaces are modified with remote and direct Ar plasma, and the effects of the modification on the hydrophilicity of PTFE are investigated. The surface microstructures and compositions of the PTFE film were characterized with the goniometer, scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Results show that the remote and direct plasma treatments modify the PTFE surface in morphology and composition, and both modifications cause surface oxidation of PTFE films, in the forming of some polar functional groups enhancing polymer wettability. When the remote and direct Ar plasma treats PTFE film, the contact angles decrease from the untreated 108-58 o and 65.2 o , respectively. The effect of the remote Ar plasma is more noticeable. The role of all kinds of active species, e.g. electrons, ions and free radicals involved in plasma surface modification is further evaluated. This shows that remote Ar plasma can restrain the ion and electron etching reaction and enhance radical reaction

Mapping forest canopy fuels in Yellowstone National Park using lidar and hyperspectral data

Science.gov (United States)

Halligan, Kerry Quinn

The severity and size of wildland fires in the forested western U.S have increased in recent years despite improvements in fire suppression efficiency. This, along with increased density of homes in the wildland-urban interface, has resulted in high costs for fire management and increased risks to human health, safety and property. Crown fires, in comparison to surface fires, pose an especially high risk due to their intensity and high rate of spread. Crown fire models require a range of quantitative fuel parameters which can be difficult and costly to obtain, but advances in lidar and hyperspectral sensor technologies hold promise for delivering these inputs. Further research is needed, however, to assess the strengths and limitations of these technologies and the most appropriate analysis methodologies for estimating crown fuel parameters from these data. This dissertation focuses on retrieving critical crown fuel parameters, including canopy height, canopy bulk density and proportion of dead canopy fuel, from airborne lidar and hyperspectral data. Remote sensing data were used in conjunction with detailed field data on forest parameters and surface reflectance measurements. A new method was developed for retrieving Digital Surface Model (DSM) and Digital Canopy Models (DCM) from first return lidar data. Validation data on individual tree heights demonstrated the high accuracy (r2 0.95) of the DCMs developed via this new algorithm. Lidar-derived DCMs were used to estimate critical crown fire parameters including available canopy fuel, canopy height and canopy bulk density with linear regression model r2 values ranging from 0.75 to 0.85. Hyperspectral data were used in conjunction with Spectral Mixture Analysis (SMA) to assess fuel quality in the form of live versus dead canopy proportions. Severity and stage of insect-caused forest mortality were estimated using the fractional abundance of green vegetation, non-photosynthetic vegetation and shade obtained from

Remote sensing-based detection and quantification of roadway debris following natural disasters

Science.gov (United States)

Axel, Colin; van Aardt, Jan A. N.; Aros-Vera, Felipe; Holguín-Veras, José

2016-05-01

Rapid knowledge of road network conditions is vital to formulate an efficient emergency response plan following any major disaster. Fallen buildings, immobile vehicles, and other forms of debris often render roads impassable to responders. The status of roadways is generally determined through time and resource heavy methods, such as field surveys and manual interpretation of remotely sensed imagery. Airborne lidar systems provide an alternative, cost-effective option for performing network assessments. The 3D data can be collected quickly over a wide area and provide valuable insight about the geometry and structure of the scene. This paper presents a method for automatically detecting and characterizing debris in roadways using airborne lidar data. Points falling within the road extent are extracted from the point cloud and clustered into individual objects using region growing. Objects are classified as debris or non-debris using surface properties and contextual cues. Debris piles are reconstructed as surfaces using alpha shapes, from which an estimate of debris volume can be computed. Results using real lidar data collected after a natural disaster are presented. Initial results indicate that accurate debris maps can be automatically generated using the proposed method. These debris maps would be an invaluable asset to disaster management and emergency response teams attempting to reach survivors despite a crippled transportation network.

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

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

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.

Monitoring cirrus cloud and tropopause height over Hanoi using a compact lidar system

International Nuclear Information System (INIS)

Bui Van Hai; Dinh Van Trung; Nguyen Xuan Tuan; Dao Duy Thang; Nguyen Thanh Binh

2012-01-01

Cirrus clouds in the upper troposphere and the lower stratosphere have attracted great attention due to their important role and impact on the atmospheric radioactive balance. Because cirrus clouds are located high in the atmosphere, their study requires a high resolution remote sensing technique not only for detection but also for the characterization of their properties. The lidar technique with its inherent high sensitivity and resolution has become an indispensable tool for studying and improving our understanding of cirrus cloud. Using lidar technique we can simultaneously measure the cloud height, thickness and follow its temporal evolution. In this paper we describe the development of a compact and highly sensitive lidar system with the aim to remotely monitor for the first time the cirrus clouds over Hanoi (2101:42 N, 10551:12 W). From the lidar data collected during the year 2011. We derive the mean cloud height, location of cloud top, the cloud mean thickness and their temporal evolution. We then compare the location of the cloud top with the position of the tropopause determined the radiosonde data and found good that the distance between cloud top and tropopause remains fairly stable, indicating that generally the top of cirrus clouds is the good tracer of the tropopause. We found that the cirrus clouds are generally located at height between 11.2 to 15 km with average height of 13.4 km. Their thickness is between 0.3 and 3.8 km with average value of 1.7 km. We also compare the properties of cirrus cloud with that observed at other locations around the world based on lidar technique. (author)

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.

Rating of roofs’ surfaces regarding their solar potential and suitability for PV systems, based on LiDAR data

International Nuclear Information System (INIS)

Lukač, Niko; Žlaus, Danijel; Seme, Sebastijan; Žalik, Borut; Štumberger, Gorazd

2013-01-01

Highlights: ► A new method for estimating and rating buildings roofs’ solar potential is presented. ► Considering LiDAR geospatial data together with pyranometer measurements. ► Use of multi-resolution shadowing model with new heuristic vegetation shadowing. ► High correlation between estimated solar potential and onsite measurements. -- Abstract: The roof surfaces within urban areas are constantly attracting interest regarding the installation of photovoltaic systems. These systems can improve self-sufficiency of electricity supply, and can help to decrease the emissions of greenhouse gases throughout urban areas. Unfortunately, some roof surfaces are unsuitable for installing photovoltaic systems. This presented work deals with the rating of roof surfaces within urban areas regarding their solar potential and suitability for the installation of photovoltaic systems. The solar potential of a roof’s surface is determined by a new method that combines extracted urban topography from LiDAR data with the pyranometer measurements of global and diffuse solar irradiances. Heuristic annual vegetation shadowing and a multi-resolution shadowing model, complete the proposed method. The significance of different influential factors (e.g. shadowing) was analysed extensively. A comparison between the results obtained by the proposed method and measurements performed on an actual PV power plant showed a correlation agreement of 97.4%.

CSIR-NLC mobile LIDAR: first scientific results

CSIR Research Space (South Africa)

Sivakumar, V

2009-07-01

Full Text Available sun-photometer employed under AErosol RObotic NETwork (AERONET). Index Terms— Atmospheric measurements, Remote sensing, Aerosols, Air pollution, Meteorology 1. INTRODUCTION Light Detection and Ranging (LIDAR) has become an excellent tool... at University of KwaZulu-Natal as part of cooperation between the Reunion University and the Service d'Aéronomie (CNRS, IPSL, Paris) for climate research studies. It allows for studying the stratosphere- mesosphere (30-80 km) thermal structure...

Remote Control of Tissue Interactions via Engineered Photo-switchable Cell Surfaces

Science.gov (United States)

Luo, Wei; Pulsipher, Abigail; Dutta, Debjit; Lamb, Brian M.; Yousaf, Muhammad N.

2014-09-01

We report a general cell surface molecular engineering strategy via liposome fusion delivery to create a dual photo-active and bio-orthogonal cell surface for remote controlled spatial and temporal manipulation of microtissue assembly and disassembly. Cell surface tailoring of chemoselective functional groups was achieved by a liposome fusion delivery method and quantified by flow cytometry and characterized by a new cell surface lipid pull down mass spectrometry strategy. Dynamic co-culture spheroid tissue assembly in solution and co-culture tissue multilayer assembly on materials was demonstrated by an intercellular photo-oxime ligation that could be remotely cleaved and disassembled on demand. Spatial and temporal control of microtissue structures containing multiple cell types was demonstrated by the generation of patterned multilayers for controlling stem cell differentiation. Remote control of cell interactions via cell surface engineering that allows for real-time manipulation of tissue dynamics may provide tools with the scope to answer fundamental questions of cell communication and initiate new biotechnologies ranging from imaging probes to drug delivery vehicles to regenerative medicine, inexpensive bioreactor technology and tissue engineering therapies.

A mini backscatter lidar for airborne measurements in the framework of DACCIWA

Science.gov (United States)

Chazette, Patrick; Totems, Julien; Flamant, Cyrille; Shang, Xiaoxia; Denjean, Cyrielle; Meynadier, Rémi; Perrin, Thierry; Laurens, Marc

2017-04-01

During the international campaign of the European program Dynamics-Aerosol-Chemistry-Cloud Interactions in West Africa (DACCIWA), investigating the relationship between weather, climate and air pollution in southern West Africa, a mini backscatter lidar was embedded on the French research aircraft (ATR42) of the Service des Avions Français Instrumentés pour la Recherche en Environnement (SAFIRE). This implementation was made possible thanks to the support of the Centre National d'Etude Spatial (CNES), with the aim of assessing the relative relevance of airborne or spaceborne (e.g. Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations, CALIPSO) remote sensing instruments. The lidar complemented the various in-situ observations carried out on the plane, by identifying the aerosol layers in the atmospheric column below the aircraft, and bringing strong constraints for the validation of other measurements. The field campaign took place from 27 to 16 July 2016 from Lomé, Togo. The aircraft conducted flights between 1 km and 5 km above the mean sea level (amsl), allowing the coupling of in situ and remote sensing data to assess the properties of the aerosol layers. Aerosol plumes of different origins were identified using the coupling between the lidar cross-polarized channels, satellite observations and a set of back trajectories analyses. During several flights, depolarizing aerosol layers from the northeast were observed between 2.5 and 4 km amsl, which highlight the significant contribution of dust-like particles to the aerosol load in the coastal region. Conversely, air masses originating from the east-southeast were loaded with a mixing of biomass burning and pollution aerosols. The former originated from Central Africa and the latter from human activities in and around large cities (Lomé). The flight sampling strategy and related lidar investigations will be presented and discussed.

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

Remote Sensing of Ecology, Biodiversity and Conservation: A Review from the Perspective of Remote Sensing Specialists

Directory of Open Access Journals (Sweden)

Marc Cattet

2010-11-01

Full Text Available Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC. Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI, inversion algorithm, data fusion, and the integration of remote sensing (RS and geographic information system (GIS.

Remote sensing of ecology, biodiversity and conservation: a review from the perspective of remote sensing specialists.

Science.gov (United States)

Wang, Kai; Franklin, Steven E; Guo, Xulin; Cattet, Marc

2010-01-01

Remote sensing, the science of obtaining information via noncontact recording, has swept the fields of ecology, biodiversity and conservation (EBC). Several quality review papers have contributed to this field. However, these papers often discuss the issues from the standpoint of an ecologist or a biodiversity specialist. This review focuses on the spaceborne remote sensing of EBC from the perspective of remote sensing specialists, i.e., it is organized in the context of state-of-the-art remote sensing technology, including instruments and techniques. Herein, the instruments to be discussed consist of high spatial resolution, hyperspectral, thermal infrared, small-satellite constellation, and LIDAR sensors; and the techniques refer to image classification, vegetation index (VI), inversion algorithm, data fusion, and the integration of remote sensing (RS) and geographic information system (GIS).

A 3D approach to reconstruct continuous optical images using lidar and MODIS

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HuaGuo Huang

2015-06-01

Full Text Available Background Monitoring forest health and biomass for changes over time in the global environment requires the provision of continuous satellite images. However, optical images of land surfaces are generally contaminated when clouds are present or rain occurs. Methods To estimate the actual reflectance of land surfaces masked by clouds and potential rain, 3D simulations by the RAPID radiative transfer model were proposed and conducted on a forest farm dominated by birch and larch in Genhe City, DaXing’AnLing Mountain in Inner Mongolia, China. The canopy height model (CHM from lidar data were used to extract individual tree structures (location, height, crown width. Field measurements related tree height to diameter of breast height (DBH, lowest branch height and leaf area index (LAI. Series of Landsat images were used to classify tree species and land cover. MODIS LAI products were used to estimate the LAI of individual trees. Combining all these input variables to drive RAPID, high-resolution optical remote sensing images were simulated and validated with available satellite images. Results Evaluations on spatial texture, spectral values and directional reflectance were conducted to show comparable results. Conclusions The study provides a proof-of-concept approach to link lidar and MODIS data in the parameterization of RAPID models for high temporal and spatial resolutions of image reconstruction in forest dominated areas.

Extreme dust storm over the eastern Mediterranean in September 2015: satellite, lidar, and surface observations in the Cyprus region

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R.-E. Mamouri

2016-11-01

Full Text Available A record-breaking dust storm originating from desert regions in northern Syria and Iraq occurred over the eastern Mediterranean in September 2015. In this contribution of a series of two articles (part 1, observations; part 2, atmospheric modeling, we provide a comprehensive overview of the aerosol conditions during this extreme dust outbreak in the Cyprus region. These observations are based on satellite observations (MODIS, moderate resolution imaging spectroradiometer of aerosol optical thickness (AOT and Ångström exponent, surface particle mass (PM10 concentrations measured at four sites in Cyprus, visibility observations at three airports in southern Cyprus and corresponding conversion products (particle extinction coefficient, dust mass concentrations, EARLINET (European Aerosol Research Lidar Network lidar observations of dust vertical layering over Limassol, particle optical properties (backscatter, extinction, lidar ratio, linear depolarization ratio, and derived profiles of dust mass concentrations. Maximum 550 nm AOT exceeded values of 5.0, according to MODIS, and the mass loads were correspondingly >  10 g m−2 over Larnaca and Limassol during the passage of an extremely dense dust front on 8 September 2015. Hourly mean PM10 values were close to 8000 µg m−3 and the observed meteorological optical range (visibility was reduced to 300–750 m at Larnaca and Limassol. The visibility observations suggest peak values of the near-surface total suspended particle (TSP extinction coefficients of 6000 Mm−1 and thus TSP mass concentrations of 10 000 µg m−3. The Raman polarization lidar observations mainly indicated a double layer structure of the dust plumes (reaching to about 4 km height, pointing to at least two different dust source regions. Dust particle extinction coefficients (532 nm already exceeded 1000 Mm−1 and the mass concentrations reached 2000 µg m−3 in the elevated dust layers on

Near-field Oblique Remote Sensing of Stream Water-surface Elevation, Slope, and Surface Velocity

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Minear, J. T.; Kinzel, P. J.; Nelson, J. M.; McDonald, R.; Wright, S. A.

2014-12-01

A major challenge for estimating discharges during flood events or in steep channels is the difficulty and hazard inherent in obtaining in-stream measurements. One possible solution is to use near-field remote sensing to obtain simultaneous water-surface elevations, slope, and surface velocities. In this test case, we utilized Terrestrial Laser Scanning (TLS) to remotely measure water-surface elevations and slope in combination with surface velocities estimated from particle image velocimetry (PIV) obtained by video-camera and/or infrared camera. We tested this method at several sites in New Mexico and Colorado using independent validation data consisting of in-channel measurements from survey-grade GPS and Acoustic Doppler Current Profiler (ADCP) instruments. Preliminary results indicate that for relatively turbid or steep streams, TLS collects tens of thousands of water-surface elevations and slopes in minutes, much faster than conventional means and at relatively high precision, at least as good as continuous survey-grade GPS measurements. Estimated surface velocities from this technique are within 15% of measured velocity magnitudes and within 10 degrees from the measured velocity direction (using extrapolation from the shallowest bin of the ADCP measurements). Accurately aligning the PIV results into Cartesian coordinates appears to be one of the main sources of error, primarily due to the sensitivity at these shallow oblique look angles and the low numbers of stationary objects for rectification. Combining remotely-sensed water-surface elevations, slope, and surface velocities produces simultaneous velocity measurements from a large number of locations in the channel and is more spatially extensive than traditional velocity measurements. These factors make this technique useful for improving estimates of flow measurements during flood flows and in steep channels while also decreasing the difficulty and hazard associated with making measurements in these

Object Classification Using Airborne Multispectral LiDAR Data

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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.

Importance of Surface Texture to Infrared Remote Sensing Interpretations

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Kirkland, L. E.; Adams, P. M.; Herr, K. C.; Salisbury, J. W.

2001-11-01

Thermal infrared remote sensing may be used to identify minerals present on the surface using diagnostic spectral bands. As band depth (spectral contrast) exhibited by the mineral increases, the mineral is easier to detect. In order to determine the expected spectral contrast, thermal infrared spectra of typical mineral endmembers are commonly measured in the laboratory. For example, for calcite, well-crystalline limestone is commonly studied. However, carbonates occur in several forms, including thin coatings, indurated carbonate (calcrete), and hot springs deposits. Different formation pathways may cause different microstructures and surface textures. This in turn can also affect the surface texture of the weathered material. Different surface textures can affect the measured band contrast, through roughness that causes a cavity (hohlraum) effect, and particle size and roughness on a scale that causes volume scattering. Thus since detection limits vary with the spectral contrast, surface texture can be an important variable in how detectable a mineral is. To study these issues, we have examined limestone and calcrete deposits at Mormon Mesa, Nevada that have two distinctly different microstructures and surface texture [Kirkland et al., 2001]. The limestone studied has larger grains and the grains frequently have flat, smooth surfaces on the order of 10-50 microns in cross-section length. The calcrete has smaller, more angular calcite grains, which exhibit almost no flat surfaces longer than 5 microns in cross-section length. We will show scanning electron microscope images to compare the different microstructures and surface textures of both the fresh and weathered surfaces, and we will show corresponding thermal infrared spectra to illustrate the different spectral signatures. The results demonstrate the importance of understanding the microstructure of mineral deposits to accurately interpret infrared remote sensing data, especially for studies that lack ground

LIDAR wind speed measurements from a rotating spinner (SpinnerEx 2009)

Energy Technology Data Exchange (ETDEWEB)

Angelou, N.; Mikkelsen, Torben; Hansen, Kasper H.; Sjoeholm, M.; Harris, M.

2010-08-15

In the context of the increasing application of remote sensing techniques in wind energy, the feasibility of upwind observations via a spinner-mounted wind lidar was tested during the SpinnerEx 2009 experiment. The objective was to install a QinetiQ (Natural Power) ZephIR lidar in the rotating spinner of a MW-sized wind turbine, and investigate the approaching wind fields from this vantage point. Time series of wind speed measurements from the lidar with 50 Hz sampling rate were successfully obtained for approximately 60 days, during the measurement campaign lasting from April to August 2009. In this report, information is given regarding the experimental setup and the lidar's operation parameters. The geometrical model used for the reconstruction of the scanning pattern of the lidar is described. This model takes into account the lidar's pointing direction, the spinner axis's vertical tilt and the wind turbine's yaw relative to the mean wind speed direction. The data analysis processes are documented. A methodology for the calculation of the yaw misalignment of the wind turbine relative to the wind direction, as a function of various averaging times, is proposed, using the lidar's instantaneous line-of-sight radial wind speed measurements. Two different setups have been investigated in which the approaching wind field was measured at distances of 0.58 OE and 1.24 OE rotor diameters upwind, respectively. For both setups, the instantaneous yaw misalignment of the turbine has been estimated from the lidar measurements. Data from an adjacent meteorological mast as well as data logged within the wind turbine's control system were used to evaluate the results. (author)

A comparison of accuracy and cost of LiDAR versus stand exam data for landscape management on the Malheur National Forest

Science.gov (United States)

Susan Hummel; A. T. Hudak; E. H. Uebler; M. J. Falkowski; K. A. Megown

2011-01-01

Foresters are increasingly interested in remote sensing data because they provide an overview of landscape conditions, which is impractical with field sample data alone. Light Detection and Ranging (LiDAR) provides exceptional spatial detail of forest structure, but difficulties in processing LiDAR data have limited their application beyond the research community....

Polarimetric LIDAR with FRI sampling for target characterization

Science.gov (United States)

Wijerathna, Erandi; Creusere, Charles D.; Voelz, David; Castorena, Juan

2017-09-01

Polarimetric LIDAR is a significant tool for current remote sensing applications. In addition, measurement of the full waveform of the LIDAR echo provides improved ranging and target discrimination, although, data storage volume in this approach can be problematic. In the work presented here, we investigated the practical issues related to the implementation of a full waveform LIDAR system to identify polarization characteristics of multiple targets within the footprint of the illumination beam. This work was carried out on a laboratory LIDAR testbed that features a flexible arrangement of targets and the ability to change the target polarization characteristics. Targets with different retardance characteristics were illuminated with a linearly polarized laser beam and the return pulse intensities were analyzed by rotating a linear analyzer polarizer in front of a high-speed detector. Additionally, we explored the applicability and the limitations of applying a sparse sampling approach based on Finite Rate of Innovations (FRI) to compress and recover the characteristic parameters of the pulses reflected from the targets. The pulse parameter values extracted by the FRI analysis were accurate and we successfully distinguished the polarimetric characteristics and the range of multiple targets at different depths within the same beam footprint. We also demonstrated the recovery of an unknown target retardance value from the echoes by applying a Mueller matrix system model.

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

Directory of Open Access Journals (Sweden)

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

Atmospheric boundary layer CO2 remote sensing with a direct detection LIDAR instrument based on a widely tunable optical parametric source.

Science.gov (United States)

Cadiou, Erwan; Mammez, Dominique; Dherbecourt, Jean-Baptiste; Gorju, Guillaume; Pelon, Jacques; Melkonian, Jean-Michel; Godard, Antoine; Raybaut, Myriam

2017-10-15

We report on the capability of a direct detection differential absorption lidar (DIAL) for range resolved and integrated path (IPDIAL) remote sensing of CO 2 in the atmospheric boundary layer (ABL). The laser source is an amplified nested cavity optical parametric oscillator (NesCOPO) emitting approximately 8 mJ at the two measurement wavelengths selected near 2050 nm. Direct detection atmospheric measurements are taken from the ground using a 30 Hz frequency switching between emitted wavelengths. Results show that comparable precision measurements are achieved in DIAL and IPDIAL modes (not better than a few ppm) on high SNR targets such as near range ABL aerosol and clouds, respectively. Instrumental limitations are analyzed and degradation due to cloud scattering variability is discussed to explain observed DIAL and IPDIAL limitations.

Scaling of surface energy fluxes using remotely sensed data

Science.gov (United States)

French, Andrew Nichols

Accurate estimates of evapotranspiration (ET) across multiple terrains would greatly ease challenges faced by hydrologists, climate modelers, and agronomists as they attempt to apply theoretical models to real-world situations. One ET estimation approach uses an energy balance model to interpret a combination of meteorological observations taken at the surface and data captured by remote sensors. However, results of this approach have not been accurate because of poor understanding of the relationship between surface energy flux and land cover heterogeneity, combined with limits in available resolution of remote sensors. The purpose of this study was to determine how land cover and image resolution affect ET estimates. Using remotely sensed data collected over El Reno, Oklahoma, during four days in June and July 1997, scale effects on the estimation of spatially distributed ET were investigated. Instantaneous estimates of latent and sensible heat flux were calculated using a two-source surface energy balance model driven by thermal infrared, visible-near infrared, and meteorological data. The heat flux estimates were verified by comparison to independent eddy-covariance observations. Outcomes of observations taken at coarser resolutions were simulated by aggregating remote sensor data and estimated surface energy balance components from the finest sensor resolution (12 meter) to hypothetical resolutions as coarse as one kilometer. Estimated surface energy flux components were found to be significantly dependent on observation scale. For example, average evaporative fraction varied from 0.79, using 12-m resolution data, to 0.93, using 1-km resolution data. Resolution effects upon flux estimates were related to a measure of landscape heterogeneity known as operational scale, reflecting the size of dominant landscape features. Energy flux estimates based on data at resolutions less than 100 m and much greater than 400 m showed a scale-dependent bias. But estimates

LiDAR Vegetation Investigation and Signature Analysis System (LVISA)

Science.gov (United States)

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

2015-04-01

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

Characterization and classification of vegetation canopy structure and distribution within the Great Smoky Mountains National Park using LiDAR

Energy Technology Data Exchange (ETDEWEB)

Kumar, Jitendra [ORNL; HargroveJr., William Walter [United States Department of Agriculture (USDA), United States Forest Service (USFS); Norman, Steven P [United States Department of Agriculture (USDA), United States Forest Service (USFS); Hoffman, Forrest M [ORNL; Newcomb, Doug [U.S. Fish and Wildlife Service

2015-01-01

Vegetation canopy structure is a critically important habit characteristic for many threatened and endangered birds and other animal species, and it is key information needed by forest and wildlife managers for monitoring and managing forest resources, conservation planning and fostering biodiversity. Advances in Light Detection and Ranging (LiDAR) technologies have enabled remote sensing-based studies of vegetation canopies by capturing three-dimensional structures, yielding information not available in two-dimensional images of the landscape pro- vided by traditional multi-spectral remote sensing platforms. However, the large volume data sets produced by airborne LiDAR instruments pose a significant computational challenge, requiring algorithms to identify and analyze patterns of interest buried within LiDAR point clouds in a computationally efficient manner, utilizing state-of-art computing infrastructure. We developed and applied a computationally efficient approach to analyze a large volume of LiDAR data and to characterize and map the vegetation canopy structures for 139,859 hectares (540 sq. miles) in the Great Smoky Mountains National Park. This study helps improve our understanding of the distribution of vegetation and animal habitats in this extremely diverse ecosystem.

The study on the lidar's detection limit for Iodine Gas

Energy Technology Data Exchange (ETDEWEB)

Kim, Dong-lyul; Baik, Seung-Hoon; Park, Seung-Kyu; Park, Nak-Gyu; Ahn, Yong-Jin [Korea Atomic Energy Research Institute, Daejeon (Korea, Republic of)

2015-05-15

A powerful and reliable tool for range-resolved remote sensing of gas concentrations that has proven its capabilities in a variety of studies is the differential absorption lidar (DIAL). Differential absorption lidar (DIAL) is frequently used for atmospheric gas monitoring to detect impurities such as nitrogen dioxide, sulfur dioxide, iodine, and ozone. DIAL can measure air pollutant concentrations with a high spatial resolution by adopting two laser systems with different degrees of absorption between the two different wavelengths. The absorption of the reference wavelength is very weak, while the absorption of the other wavelength is very strong. In this paper, we measured the limit of detection capability of our designed DIAL system. The DIAL measurements were performed using a target iodine cell in the laboratory. We confirmed that the concentration of iodine gas ratio increased after the laser passed through the iodine cell. The system of DIAL(Differential Absorption Lidar) was effective to detect the iodine gas. We obtained the signals from the iodine target cell and the lidar signal from the iodine target cell was proportional to frequency locking ratios.

Lidar signal-to-noise ratio improvements: Considerations and techniques

Science.gov (United States)

Hassebo, Yasser Y.

minimize detected sky background noise while maintaining maximum lidar signal throughput. Measurements, carried at 532 nm, show as much as a factor of 10 improvement in SNR and the attainable lidar range up to 34% over conventional un-polarized schemes. For vertically pointing lidars, the largest improvements are limited to the early morning and late afternoon hours, while for lidars scanning azimuthally and in elevation at angles other than vertical, significant improvements are achievable over more extended time periods. Observed changes in SNR improvements were also related to relative humidity and modification of underlying aerosol microphysics. A second, distinct objective of this research was to utilize multiwavelength lidar techniques to separate plume and cloud particles. Choice of the study location and time for this work was driven mainly by the availability of satellite data collected by NASA INTEX-NA and NOAA NEAQS experiment over New York City on July 21, 2004 in support of MODIS imagery. The lidar results identify smoke plumes over New York City and validate the plume source origin location using NOAA-HYSPLIT back trajectory analysis. Surface measurements, at the time, from in-situ particle counters are presented and show no enhanced PM2.5 loading. This result is supported by lidar measurements, which confirm that nearly all of the aerosol plumes are located above the normal aerosol boundary layer showing that satellite measurements are often incomplete and are not sufficient for assessing surface air quality.

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.

Theory of lidar method for measurement of the modulation transfer function of water layers.

Science.gov (United States)

Dolin, Lev S

2013-01-10

We develop a method to evaluate the modulation transfer function (MTF) of a water layer from the characteristics of lidar signal backscattered by water volume. We propose several designs of a lidar system for remote measurement of the MTF and the procedure to determine optical properties of water using the measured MTF. We discuss a laser system for sea-bottom imaging that accounts for the influence of water slab on the image structure and allows for correction of image distortions caused by light scattering in water. © 2013 Optical Society of America

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.

Hydrologic Remote Sensing and Land Surface Data Assimilation.

Science.gov (United States)

Moradkhani, Hamid

2008-05-06

Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface-atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF) and Particle filter (PF), for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law) and could be a strong alternative to EnKF which is subject to some limitations including the linear

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

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

Science.gov (United States)

Cherukuru, Nihanth Wagmi

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

The Slope Imaging Multi-Polarization Photon-Counting Lidar: Development and Performance Results

Science.gov (United States)

Dabney, Phillip

2010-01-01

The Slope Imaging Multi-polarization Photon-counting Lidar is an airborne instrument developed to demonstrate laser altimetry measurement methods that will enable more efficient observations of topography and surface properties from space. The instrument was developed through the NASA Earth Science Technology Office Instrument Incubator Program with a focus on cryosphere remote sensing. The SIMPL transmitter is an 11 KHz, 1064 nm, plane-polarized micropulse laser transmitter that is frequency doubled to 532 nm and split into four push-broom beams. The receiver employs single-photon, polarimetric ranging at 532 and 1064 nm using Single Photon Counting Modules in order to achieve simultaneous sampling of surface elevation, slope, roughness and depolarizing scattering properties, the latter used to differentiate surface types. Data acquired over ice-covered Lake Erie in February, 2009 are documenting SIMPL s measurement performance and capabilities, demonstrating differentiation of open water and several ice cover types. ICESat-2 will employ several of the technologies advanced by SIMPL, including micropulse, single photon ranging in a multi-beam, push-broom configuration operating at 532 nm.

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.

Quality assessment of water cycle parameters in REMO by radar-lidar synergy

Directory of Open Access Journals (Sweden)

B. Hennemuth

2008-01-01

Full Text Available A comparison study of water cycle parameters derived from ground-based remote-sensing instruments and from the regional model REMO is presented. Observational data sets were collected during three measuring campaigns in summer/autumn 2003 and 2004 at Richard Aßmann Observatory, Lindenberg, Germany. The remote sensing instruments which were used are differential absorption lidar, Doppler lidar, ceilometer, cloud radar, and micro rain radar for the derivation of humidity profiles, ABL height, water vapour flux profiles, cloud parameters, and rain rate. Additionally, surface latent and sensible heat flux and soil moisture were measured. Error ranges and representativity of the data are discussed. For comparisons the regional model REMO was run for all measuring periods with a horizontal resolution of 18 km and 33 vertical levels. Parameter output was every hour. The measured data were transformed to the vertical model grid and averaged in time in order to better match with gridbox model values. The comparisons show that the atmospheric boundary layer is not adequately simulated, on most days it is too shallow and too moist. This is found to be caused by a wrong partitioning of energy at the surface, particularly a too large latent heat flux. The reason is obviously an overestimation of soil moisture during drying periods by the one-layer scheme in the model. The profiles of water vapour transport within the ABL appear to be realistically simulated. The comparison of cloud cover reveals an underestimation of low-level and mid-level clouds by the model, whereas the comparison of high-level clouds is hampered by the inability of the cloud radar to see cirrus clouds above 10 km. Simulated ABL clouds apparently have a too low cloud base, and the vertical extent is underestimated. The ice water content of clouds agree in model and observation whereas the liquid water content is unsufficiently derived from cloud radar reflectivity in the present study

Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar

Science.gov (United States)

Chen, Qi

2015-08-01

Estimating tree aboveground biomass (AGB) and carbon (C) stocks using remote sensing is a critical component for understanding the global C cycle and mitigating climate change. However, the importance of allometry for remote sensing of AGB has not been recognized until recently. The overarching goals of this study are to understand the differences and relationships among three national-scale allometric methods (CRM, Jenkins, and the regional models) of the Forest Inventory and Analysis (FIA) program in the U.S. and to examine the impacts of using alternative allometry on the fitting statistics of remote sensing-based woody AGB models. Airborne lidar data from three study sites in the Pacific Northwest, USA were used to predict woody AGB estimated from the different allometric methods. It was found that the CRM and Jenkins estimates of woody AGB are related via the CRM adjustment factor. In terms of lidar-biomass modeling, CRM had the smallest model errors, while the Jenkins method had the largest ones and the regional method was between. The best model fitting from CRM is attributed to its inclusion of tree height in calculating merchantable stem volume and the strong dependence of non-merchantable stem biomass on merchantable stem biomass. This study also argues that it is important to characterize the allometric model errors for gaining a complete understanding of the remotely-sensed AGB prediction errors.

A time-space synchronization of coherent Doppler scanning lidars for 3D measurements of wind fields

DEFF Research Database (Denmark)

Vasiljevic, Nikola

initiates the laser pulse emission and acquisition of the backscattered light, while the two servo motors conduct the scanner head rotation that provides means to direct the laser pulses into the atmosphere. By controlling the rotation of the three motors from the motion controller the strict......-dimensional flow field by emitting the laser beams from the three spatially separated lidars, directing them to intersect, and moving the beam intersection over an area of interest. Each individual lidar was engineered to be powered by two real servo motors, and one virtual stepper motor. The stepper motor...... synchronization and time control of the emission, steering and acquisition were achieved, resulting that the complete lidar measurement process is controlled from the single hardware component. The system was formed using a novel approach, in which the master computer simultaneously coordinates the remote lidars...

Remote sensing of ecosystem health: opportunities, challenges, and future perspectives.

Science.gov (United States)

Li, Zhaoqin; Xu, Dandan; Guo, Xulin

2014-11-07

Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

Remote Sensing of Ecosystem Health: Opportunities, Challenges, and Future Perspectives

Directory of Open Access Journals (Sweden)

Zhaoqin Li

2014-11-01

Full Text Available Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1 scale issue; (2 transportability issue; (3 data availability; and (4 uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges.

Remote Sensing of Ecosystem Health: Opportunities, Challenges, and Future Perspectives

Science.gov (United States)

Li, Zhaoqin; Xu, Dandan; Guo, Xulin

2014-01-01

Maintaining a healthy ecosystem is essential for maximizing sustainable ecological services of the best quality to human beings. Ecological and conservation research has provided a strong scientific background on identifying ecological health indicators and correspondingly making effective conservation plans. At the same time, ecologists have asserted a strong need for spatially explicit and temporally effective ecosystem health assessments based on remote sensing data. Currently, remote sensing of ecosystem health is only based on one ecosystem attribute: vigor, organization, or resilience. However, an effective ecosystem health assessment should be a comprehensive and dynamic measurement of the three attributes. This paper reviews opportunities of remote sensing, including optical, radar, and LiDAR, for directly estimating indicators of the three ecosystem attributes, discusses the main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system, and provides some future perspectives. The main challenges to develop a remote sensing-based spatially-explicit comprehensive ecosystem health system are: (1) scale issue; (2) transportability issue; (3) data availability; and (4) uncertainties in health indicators estimated from remote sensing data. However, the Radarsat-2 constellation, upcoming new optical sensors on Worldview-3 and Sentinel-2 satellites, and improved technologies for the acquisition and processing of hyperspectral, multi-angle optical, radar, and LiDAR data and multi-sensoral data fusion may partly address the current challenges. PMID:25386759

a Super Voxel-Based Riemannian Graph for Multi Scale Segmentation of LIDAR Point Clouds

Science.gov (United States)

Li, Minglei

2018-04-01

Automatically segmenting LiDAR points into respective independent partitions has become a topic of great importance in photogrammetry, remote sensing and computer vision. In this paper, we cast the problem of point cloud segmentation as a graph optimization problem by constructing a Riemannian graph. The scale space of the observed scene is explored by an octree-based over-segmentation with different depths. The over-segmentation produces many super voxels which restrict the structure of the scene and will be used as nodes of the graph. The Kruskal coordinates are used to compute edge weights that are proportional to the geodesic distance between nodes. Then we compute the edge-weight matrix in which the elements reflect the sectional curvatures associated with the geodesic paths between super voxel nodes on the scene surface. The final segmentation results are generated by clustering similar super voxels and cutting off the weak edges in the graph. The performance of this method was evaluated on LiDAR point clouds for both indoor and outdoor scenes. Additionally, extensive comparisons to state of the art techniques show that our algorithm outperforms on many metrics.

High-resolution LIDAR and ground observations of snow cover in a complex forested terrain in the Sierra Nevada - implications for optical remote sensing of seasonal snow.

Science.gov (United States)

Kostadinov, T. S.; Harpold, A.; Hill, R.; McGwire, K.

2017-12-01

Seasonal snow cover is a key component of the hydrologic regime in many regions of the world, especially those in temperate latitudes with mountainous terrain and dry summers. Such regions support large human populations which depend on the mountain snowpack for their water supplies. It is thus important to quantify snow cover accurately and continuously in these regions. Optical remote-sensing methods are able to detect snow and leverage space-borne spectroradiometers with global coverage such as MODIS to produce global snow cover maps. However, snow is harder to detect accurately in mountainous forested terrain, where topography influences retrieval algorithms, and importantly - forest canopies complicate radiative transfer and obfuscate the snow. Current satellite snow cover algorithms assume that fractional snow-covered area (fSCA) under the canopy is the same as the fSCA in the visible portion of the pixel. In-situ observations and first principles considerations indicate otherwise, therefore there is a need for improvement of the under-canopy correction of snow cover. Here, we leverage multiple LIDAR overflights and in-situ observations with a distributed fiber-optic temperature sensor (DTS) to quantify snow cover under canopy as opposed to gap areas at the Sagehen Experimental Forest in the Northern Sierra Nevada, California, USA. Snow-off LIDAR overflights from 2014 are used to create a baseline high-resolution digital elevation model and classify pixels at 1 m resolution as canopy-covered or gap. Low canopy pixels are excluded from the analysis. Snow-on LIDAR overflights conducted by the Airborne Snow Observatory in 2016 are then used to classify all pixels as snow-covered or not and quantify fSCA under canopies vs. in gap areas over the Sagehen watershed. DTS observations are classified as snow-covered or not based on diel temperature fluctuations and used as validation for the LIDAR observations. LIDAR- and DTS-derived fSCA is also compared with

Estimating forest structural characteristics using the airborne LiDAR scanning system and a near-real time profiling laser system

Science.gov (United States)

Zhao, Kaiguang

LiDAR (Light Detection and Ranging) directly measures canopy vertical structures, and provides an effective remote sensing solution to accurate and spatially-explicit mapping of forest characteristics, such as canopy height and Leaf Area Index. However, many factors, such as large data volume and high costs for data acquisition, precludes the operational and practical use of most currently available LiDARs for frequent and large-scale mapping. At the same time, a growing need is arising for real-time remote sensing platforms, e.g., to provide timely information for urgent applications. This study aims to develop an airborne profiling LiDAR system, featured with on-the-fly data processing, for near real- or real-time forest inventory. The development of such a system involves implementing the on-board data processing and analysis as well as building useful regression-based models to relate LiDAR measurements with forest biophysical parameters. This work established a paradigm for an on-the-fly airborne profiling LiDAR system to inventory regional forest resources in real- or near real-time. The system was developed based on an existing portable airborne laser system (PALS) that has been previously assembled at NASA by Dr. Ross Nelson. Key issues in automating PALS as an on-the-fly system were addressed, including the design of an archetype for the system workflow, the development of efficient and robust algorithms for automatic data processing and analysis, the development of effective regression models to predict forest biophysical parameters from LiDAR measurements, and the implementation of an integrated software package to incorporate all the above development. This work exploited the untouched potential of airborne laser profilers for real-time forest inventory, and therefore, documented an initial step toward developing airborne-laser-based, on-the-fly, real-time, forest inventory systems. Results from this work demonstrated the utility and effectiveness of

Near-surface and columnar measurements with a micro pulse lidar of atmospheric pollen in Barcelona, Spain

Directory of Open Access Journals (Sweden)

M. Sicard

2016-06-01

Full Text Available We present for the first time continuous hourly measurements of pollen near-surface concentration and lidar-derived profiles of particle backscatter coefficients and of volume and particle depolarization ratios during a 5-day pollination event observed in Barcelona, Spain, between 27 and 31 March 2015. Daily average concentrations ranged from 1082 to 2830 pollen m−3. Platanus and Pinus pollen types represented together more than 80 % of the total pollen. Maximum hourly pollen concentrations of 4700 and 1200 m−3 were found for Platanus and Pinus, respectively. Every day a clear diurnal cycle caused by the vertical transport of the airborne pollen was visible on the lidar-derived profiles with maxima usually reached between 12:00 and 15:00 UT. A method based on the lidar polarization capabilities was used to retrieve the contribution of the pollen to the total aerosol optical depth (AOD. On average the diurnal (09:00–17:00 UT pollen AOD was 0.05, which represented 29 % of the total AOD. Maximum values of the pollen AOD and its contribution to the total AOD reached 0.12 and 78 %, respectively. The diurnal means of the volume and particle depolarization ratios in the pollen plume were 0.08 and 0.14, with hourly maxima of 0.18 and 0.33, respectively. The diurnal mean of the height of the pollen plume was found at 1.24 km with maxima varying in the range of 1.47–1.78 km. A correlation study is performed (1 between the depolarization ratios and the pollen near-surface concentration to evaluate the ability of the former parameter to monitor pollen release and (2 between the depolarization ratios as well as pollen AOD and surface downward solar fluxes, which cause the atmospheric turbulences responsible for the particle vertical motion, to examine the dependency of the depolarization ratios and the pollen AOD upon solar fluxes. For the volume depolarization ratio the first correlation study yields to correlation

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

Science.gov (United States)

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

2016-12-01

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

Remote sensing: best practice

Energy Technology Data Exchange (ETDEWEB)

Brown, Gareth [Sgurr Energy (Canada)

2011-07-01

This paper presents remote sensing best practice in the wind industry. Remote sensing is a technique whereby measurements are obtained from the interaction of laser or acoustic pulses with the atmosphere. There is a vast diversity of tools and techniques available and they offer wide scope for reducing project uncertainty and risk but best practice must take into account versatility and flexibility. It should focus on the outcome in terms of results and data. However, traceability of accuracy requires comparison with conventional instruments. The framework for the Boulder protocol is given. Overviews of the guidelines for IEA SODAR and IEA LIDAR are also mentioned. The important elements of IEC 61400-12-1, an international standard for wind turbines, are given. Bankability is defined based on the Boulder protocol and a pie chart is presented that illustrates the uncertainty area covered by remote sensing. In conclusion it can be said that remote sensing is changing perceptions about how wind energy assessments can be made.

Lidar Penetration Depth Observations for Constraining Cloud Longwave Feedbacks

Science.gov (United States)

Vaillant de Guelis, T.; Chepfer, H.; Noel, V.; Guzman, R.; Winker, D. M.; Kay, J. E.; Bonazzola, M.

2017-12-01

Satellite-borne active remote sensing Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observations [CALIPSO; Winker et al., 2010] and CloudSat [Stephens et al., 2002] provide direct measurements of the cloud vertical distribution, with a very high vertical resolution. The penetration depth of the laser of the lidar Z_Opaque is directly linked to the LongWave (LW) Cloud Radiative Effect (CRE) at Top Of Atmosphere (TOA) [Vaillant de Guélis et al., in review]. In addition, this measurement is extremely stable in time making it an excellent observational candidate to verify and constrain the cloud LW feedback mechanism [Chepfer et al., 2014]. In this work, we present a method to decompose the variations of the LW CRE at TOA using cloud properties observed by lidar [GOCCP v3.0; Guzman et al., 2017]. We decompose these variations into contributions due to changes in five cloud properties: opaque cloud cover, opaque cloud altitude, thin cloud cover, thin cloud altitude, and thin cloud emissivity [Vaillant de Guélis et al., in review]. We apply this method, in the real world, to the CRE variations of CALIPSO 2008-2015 record, and, in climate model, to LMDZ6 and CESM simulations of the CRE variations of 2008-2015 period and of the CRE difference between a warm climate and the current climate. In climate model simulations, the same cloud properties as those observed by CALIOP are extracted from the CFMIP Observation Simulator Package (COSP) [Bodas-Salcedo et al., 2011] lidar simulator [Chepfer et al., 2008], which mimics the observations that would be performed by the lidar on board CALIPSO satellite. This method, when applied on multi-model simulations of current and future climate, could reveal the altitude of cloud opacity level observed by lidar as a strong constrain for cloud LW feedback, since the altitude feedback mechanism is physically explainable and the altitude of cloud opacity accurately observed by lidar.

Mapping Plant Diversity and Composition Across North Carolina Piedmont Forest Landscapes Using Lidar-Hyperspectral Remote Sensing

Science.gov (United States)

Hakkenberg, Christopher R.

Forest modification, from local stress to global change, has given rise to efforts to model, map, and monitor critical properties of forest communities like structure, composition, and diversity. Predictive models based on data from spatially-nested field plots and LiDAR-hyperspectral remote sensing systems are one particularly effective means towards the otherwise prohibitively resource-intensive task of consistently characterizing forest community dynamics at landscape scales. However, to date, most predictive models fail to account for actual (rather than idealized) species and community distributions, are unsuccessful in predicting understory components in structurally and taxonomically heterogeneous forests, and may suffer from diminished predictive accuracy due to incongruity in scale and precision between field plot samples, remotely-sensed data, and target biota of varying size and density. This three-part study addresses these and other concerns in the modeling and mapping of emergent properties of forest communities by shifting the scope of prediction from the individual or taxon to the whole stand or community. It is, after all, at the stand scale where emergent properties like functional processes, biodiversity, and habitat aggregate and manifest. In the first study, I explore the relationship between forest structure (a proxy for successional demographics and resource competition) and tree species diversity in the North Carolina Piedmont, highlighting the empirical basis and potential for utilizing forest structure from LiDAR in predictive models of tree species diversity. I then extend these conclusions to map landscape pattern in multi-scale vascular plant diversity as well as turnover in community-continua at varying compositional resolutions in a North Carolina Piedmont landscape using remotely-sensed LiDAR-hyperspectral estimates of topography, canopy structure, and foliar biochemistry. Recognizing that the distinction between correlation and

Extensive Sampling of Forest Carbon using High Density Power Line Lidar

Science.gov (United States)

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

2013-12-01

Estimating carbon sequestration and greenhouse gas emissions from forest management, natural processes, and disturbance is of growing interest for mitigating global warming. Ponderosa pine is common at mid-elevations throughout the western United States and is a dominant tree species in southwestern forests. Existing unmanaged "relict" sites and stand reconstructions of southwestern ponderosa pine forests from before European settlement (late 1800s) provide evidence of forests of larger trees of lower density and less vulnerability to severe fires than today's typical conditions of high densities of small trees that have resulted from a century of fire suppression. Forest treatments to improve forest health in the region include tree cutting focused on small-diameter trees (thinning), low-intensity prescribed burning, and monitoring rather than suppressing wildfires. Stimulated by several uncharacteristically-intense fires in the last decade, a collaborative process found strong stakeholder agreement to accelerate forest treatments to reduce fire risk and restore ecological conditions. Land use planning to ramp up management is underway and could benefit from quick and inexpensive techniques to inventory tree-level carbon because existing inventory data are not adequate to capture the range of forest structural conditions. Our approach overcomes these shortcomings by employing recent breakthroughs in estimating aboveground biomass from high resolution light detection and ranging (lidar) remote sensing. Lidar is an active remote sensing technique, analogous to radar, which measures the time required for a transmitted pulse of laser light to return to the sensor after reflection from a target. Lidar data can capture 3-dimensional forest structure with greater detail and broader spatial coverage than is feasible with conventional field measurements. We developed a novel methodology for extensive sampling and field validation of forest carbon, applicable to managed and

Water vapor spectroscopy in the 815-nm wavelength region for Differential Absorption Lidar measurements

Science.gov (United States)

Ponsardin, Patrick; Browell, Edward V.

1995-01-01

The differential absorption lidar (DIAL) technique was first applied to the remote measurement of atmospheric water vapor profiles from airborne platforms in 1981. The successful interpretation of the lidar profiles relies strongly on an accurate knowledge of specific water vapor absorption line parameters: line strength, pressure broadening coefficient, pressure-induced shift coefficient and the respective temperature-dependence factors. NASA Langley Research Center has developed and is currently testing an autonomous airborne water vapor lidar system: LASE (Lidar Atmospheric Sensing Experiment). This DIAL system uses a Nd:YAG-pumped Ti:Sapphire laser seeded by a diode laser as a lidar transmitter. The tunable diode has been selected to operate in the 813-818 nm wavelength region. This 5-nm spectral interval offers a large distribution of strengths for temperature-insensitive water vapor absorption lines. In support of the LASE project, a series of spectroscopic measurements were conducted for the 16 absorption lines that have been identified for use in the LASE measurements. Prior to this work, the experimental data for this water vapor absorption band were limited - to our knowledge - to the line strengths and to the line positions.

TWO METHODS FOR REMOTE ESTIMATION OF COMPLETE URBAN SURFACE TEMPERATURE

Directory of Open Access Journals (Sweden)

L. Jiang

2017-09-01

Full Text Available Complete urban surface temperature (TC is a key parameter for evaluating the energy exchange between the urban surface and atmosphere. At the present stage, the estimation of TC still needs detailed 3D structure information of the urban surface, however, it is often difficult to obtain the geometric structure and composition of the corresponding temperature of urban surface, so that there is still lack of concise and efficient method for estimating the TC by remote sensing. Based on the four typical urban surface scale models, combined with the Envi-met model, thermal radiant directionality forward modeling and kernel model, we analyzed a complete day and night cycle hourly component temperature and radiation temperature in each direction of two seasons of summer and winter, and calculated hemispherical integral temperature and TC. The conclusion is obtained by examining the relationship of directional radiation temperature, hemispherical integral temperature and TC: (1 There is an optimal angle of radiation temperature approaching the TC in a single observation direction when viewing zenith angle is 45–60°, the viewing azimuth near the vertical surface of the sun main plane, the average absolute difference is about 1.1 K in the daytime. (2 There are several (3–5 times directional temperatures of different view angle, under the situation of using the thermal radiation directionality kernel model can more accurately calculate the hemispherical integral temperature close to TC, the mean absolute error is about 1.0 K in the daytime. This study proposed simple and effective strategies for estimating TC by remote sensing, which are expected to improve the quantitative level of remote sensing of urban thermal environment.

Surface morphology of caldera-forming eruption deposits revealed by lidar mapping of Crater Lake National Park, Oregon- Implications for emplacement and surface modification

Science.gov (United States)

Robinson, Joel E.; Bacon, Charles R.; Major, Jon J.; Wright, Heather M.; Vallance, James W.

2017-01-01

Large explosive eruptions of silicic magma can produce widespread pumice fall, extensive ignimbrite sheets, and collapse calderas. The surfaces of voluminous ignimbrites are rarely preserved or documented because most terrestrial examples are heavily vegetated, or severely modified by post-depositional processes. Much research addresses the internal sedimentary characteristics, flow processes, and depositional mechanisms of ignimbrites, however, surface features of ignimbrites are less well documented and understood, except for comparatively small-volume deposits of historical eruptions. The ~7,700 calendar year B.P. climactic eruption of Mount Mazama, USA vented ~50 km3 of magma, deposited first as rhyodacite pumice fall and then as a zoned rhyodacite-to-andesite ignimbrite as Crater Lake caldera collapsed. Lidar collected during summer 2010 reveals the remarkably well-preserved surface of the Mazama ignimbrite and related deposits surrounding Crater Lake caldera in unprecedented detail despite forest cover. The ±1 m lateral and ±4 cm vertical resolution lidar allows surface morphologies to be classified. Surface morphologies are created by internal depositional processes and can point to the processes at work when pyroclastic flows come to rest. We describe nine surface features including furrow-ridge sets and wedge-shaped mounds in pumice fall eroded by high-energy pyroclastic surges, flow- parallel ridges that record the passage of multiple pyroclastic flows, perched benches of marginal deposits stranded by more-mobile pyroclastic-flow cores, hummocks of dense clasts interpreted as lag deposit, transverse ridges that mark the compression and imbrication of flows as they came to rest, scarps indicating ignimbrite remobilization, fields of pit craters caused by phreatic explosions, fractures and cracks caused by extensional processes resulting from ignimbrite volume loss, and stream channels eroded in the newly formed surface. The nine morphologies presented

Estimation of Spatial Trends in LAI in Heterogeneous Semi-arid Ecosystems using Full Waveform Lidar

Science.gov (United States)

Glenn, N. F.; Ilangakoon, N.; Spaete, L.; Dashti, H.

2017-12-01

Leaf area index (LAI) is a key structural trait that is defined by the plant functional type (PFT) and controlled by prevailing climate- and human-driven ecosystem stresses. Estimates of LAI using remote sensing techniques are limited by the uncertainties of vegetation inter and intra-gap fraction estimates; this is especially the case in sparse, low stature vegetated ecosystems. Small footprint full waveform lidar digitizes the total amount of return energy with the direction information as a near continuous waveform at a high vertical resolution (1 ns). Thus waveform lidar provides additional data matrices to capture vegetation gaps as well as PFTs that can be used to constrain the uncertainties of LAI estimates. In this study, we calculated a radiometrically calibrated full waveform parameter called backscatter cross section, along with other data matrices from the waveform to estimate vegetation gaps across plots (10 m x 10 m) in a semi-arid ecosystem in the western US. The LAI was then estimated using empirical relationships with directional gap fraction. Full waveform-derived gap fraction based LAI showed a high correlation with field observed shrub LAI (R2 = 0.66, RMSE = 0.24) compared to discrete return lidar based LAI (R2 = 0.01, RMSE = 0.5). The data matrices derived from full waveform lidar classified a number of deciduous and evergreen tree species, shrub species, and bare ground with an overall accuracy of 89% at 10 m. A similar analysis was performed at 1m with overall accuracy of 80%. The next step is to use these relationships to map the PFTs LAI at 10 m spatial scale across the larger study regions. The results show the exciting potential of full waveform lidar to identify plant functional types and LAI in low-stature vegetation dominated semi-arid ecosystems, an ecosystem in which many other remote sensing techniques fail. These results can be used to assess ecosystem state, habitat suitability as well as to constrain model uncertainties in

Assessing degradation across a land-use gradient in the Kruger National Park area using advanced remote sensing modalities

CSIR Research Space (South Africa)

Van Aardt, JAN

2011-01-01

Full Text Available relatively novel remote sensing approaches, namely imaging spectroscopy (hyperspectral remote sensing) and light detection and ranging (lidar), have the potential to alleviate this constraint. Specifically, the Carnegie Airborne Observatory, a state...

Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA using small-fooprint lidar data

Science.gov (United States)

Yunsuk Kim; Zhiqiang Yang; Warren B. Cohen; Dirk Pflugmacher; Chris L. Lauver; John L. Vankat

2009-01-01

Accurate estimation of live and dead biomass in forested ecosystems is important for studies of carbon dynamics, biodiversity, wildfire behavior, and for forest management. Lidar remote sensing has been used successfully to estimate live biomass, but studies focusing on dead biomass are rare. We used lidar data, in conjunction with field measurements from 58 plots to...

Patterns of Canopy and Surface Layer Consumption in a Boreal Forest Fire from Repeat Airborne Lidar

Science.gov (United States)

Alonzo, Michael; Morton, Douglas C.; Cook, Bruce D.; Andersen, Hans-Erik; Babcock, Chad; Pattison, Robert

2017-01-01

Fire in the boreal region is the dominant agent of forest disturbance with direct impacts on ecosystem structure, carbon cycling, and global climate. Global and biome-scale impacts are mediated by burn severity, measured as loss of forest canopy and consumption of the soil organic layer. To date, knowledge of the spatial variability in burn severity has been limited by sparse field sampling and moderate resolution satellite data. Here, we used pre- and post-fire airborne lidar data to directly estimate changes in canopy vertical structure and surface elevation for a 2005 boreal forest fire on Alaskas Kenai Peninsula. We found that both canopy and surface losses were strongly linked to pre-fire species composition and exhibited important fine-scale spatial variability at sub-30m resolution. The fractional reduction in canopy volume ranged from 0.61 in lowland black spruce stands to 0.27 in mixed white spruce and broad leaf forest. Residual structure largely reflects standing dead trees, highlighting the influence of pre-fire forest structure on delayed carbon losses from above ground biomass, post-fire albedo, and variability in understory light environments. Median loss of surface elevation was highest in lowland black spruce stands (0.18 m) but much lower in mixed stands (0.02 m), consistent with differences in pre-fire organic layer accumulation. Spatially continuous depth-of-burn estimates from repeat lidar measurements provide novel information to constrain carbon emissions from the surface organic layer and may inform related research on post-fire successional trajectories. Spectral measures of burn severity from Landsat were correlated with canopy (r = 0.76) and surface (r = -0.71) removal in black spruce stands but captured less of the spatial variability in fire effects for mixed stands (canopy r = 0.56, surface r = -0.26), underscoring the difficulty in capturing fire effects in heterogeneous boreal forest landscapes using proxy measures of burn severity

Applications of airborne remote sensing in atmospheric sciences research

Science.gov (United States)

Serafin, R. J.; Szejwach, G.; Phillips, B. B.

1984-01-01

This paper explores the potential for airborne remote sensing for atmospheric sciences research. Passive and active techniques from the microwave to visible bands are discussed. It is concluded that technology has progressed sufficiently in several areas that the time is right to develop and operate new remote sensing instruments for use by the community of atmospheric scientists as general purpose tools. Promising candidates include Doppler radar and lidar, infrared short range radiometry, and microwave radiometry.

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...

Evaluating UAV and LiDAR Retrieval of Snow Depth in a Coniferous Forest in Arizona

Science.gov (United States)

Van Leeuwen, W. J. D.; Broxton, P.; Biederman, J. A.

2017-12-01

Remote sensing of snow depth and cover in forested environments is challenging. Trees interfere with the remote sensing of snowpack below the canopy and cause large variations in the spatial distribution of the snowpack itself (e.g. between below canopy environments to shaded gaps to open clearings). The distribution of trees and topographic variation make it challenging to monitor the snowpack with in-situ observations. Airborne LiDAR has improved our ability to monitor snowpack over large areas in montane and forested environments because of its high sampling rate and ability to penetrate the canopy. However, these LiDAR flights can be too expensive and time-consuming to process, making it hard to use them for real-time snow monitoring. In this research, we evaluate Structure from Motion (SfM) as an alternative to Airborne LiDAR to generate high-resolution snow depth data in forested environments. This past winter, we conducted a snow field campaign over Arizona's Mogollon Rim where we acquired aerial LiDAR, multi-angle aerial photography from a UAV, and extensive field observations of snow depth at two sites. LiDAR and SFM derived snow depth maps were generated by comparing "snow-on" and "snow-off" LiDAR and SfM data. The SfM- and LiDAR-generated snow depth maps were similar at a site with fewer trees, though there were more discrepancies at a site with more trees. Both compared reasonably well with the field observations at the sparser forested site, with poorer agreement at the denser forested site. Finally, although the SfM produced point clouds with much higher point densities than the aerial LiDAR, the SfM was not able to produce meaningful snow depth estimates directly underneath trees and had trouble in areas with deep shadows. Based on these findings, we are optimizing our UAV data acquisition strategies for this upcoming field season. We are using these data, along with high-resolution hydrological modeling, to gain a better understanding of how

Hydrologic Remote Sensing and Land Surface Data Assimilation

Directory of Open Access Journals (Sweden)

Hamid Moradkhani

2008-05-01

Full Text Available Accurate, reliable and skillful forecasting of key environmental variables such as soil moisture and snow are of paramount importance due to their strong influence on many water resources applications including flood control, agricultural production and effective water resources management which collectively control the behavior of the climate system. Soil moisture is a key state variable in land surface–atmosphere interactions affecting surface energy fluxes, runoff and the radiation balance. Snow processes also have a large influence on land-atmosphere energy exchanges due to snow high albedo, low thermal conductivity and considerable spatial and temporal variability resulting in the dramatic change on surface and ground temperature. Measurement of these two variables is possible through variety of methods using ground-based and remote sensing procedures. Remote sensing, however, holds great promise for soil moisture and snow measurements which have considerable spatial and temporal variability. Merging these measurements with hydrologic model outputs in a systematic and effective way results in an improvement of land surface model prediction. Data Assimilation provides a mechanism to combine these two sources of estimation. Much success has been attained in recent years in using data from passive microwave sensors and assimilating them into the models. This paper provides an overview of the remote sensing measurement techniques for soil moisture and snow data and describes the advances in data assimilation techniques through the ensemble filtering, mainly Ensemble Kalman filter (EnKF and Particle filter (PF, for improving the model prediction and reducing the uncertainties involved in prediction process. It is believed that PF provides a complete representation of the probability distribution of state variables of interests (according to sequential Bayes law and could be a strong alternative to EnKF which is subject to some

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....

[An operational remote sensing algorithm of land surface evapotranspiration based on NOAA PAL dataset].

Science.gov (United States)

Hou, Ying-Yu; He, Yan-Bo; Wang, Jian-Lin; Tian, Guo-Liang

2009-10-01

Based on the time series 10-day composite NOAA Pathfinder AVHRR Land (PAL) dataset (8 km x 8 km), and by using land surface energy balance equation and "VI-Ts" (vegetation index-land surface temperature) method, a new algorithm of land surface evapotranspiration (ET) was constructed. This new algorithm did not need the support from meteorological observation data, and all of its parameters and variables were directly inversed or derived from remote sensing data. A widely accepted ET model of remote sensing, i. e., SEBS model, was chosen to validate the new algorithm. The validation test showed that both the ET and its seasonal variation trend estimated by SEBS model and our new algorithm accorded well, suggesting that the ET estimated from the new algorithm was reliable, being able to reflect the actual land surface ET. The new ET algorithm of remote sensing was practical and operational, which offered a new approach to study the spatiotemporal variation of ET in continental scale and global scale based on the long-term time series satellite remote sensing images.

Airborne Lidar Measurements of Below-canopy Surface Water Height , Slope and Optical Properties in the Florida Everglades Shark River Slough

Science.gov (United States)

Dabney, P.; Harding, D. J.; Valett, S. R.; Yu, A. W.; Feliciano, E. A.; Neuenschwander, A. L.; Pitts, K.

2015-12-01

Determining the presence, persistence, optical properties and variation in height and slope of surface water beneath the dense canopies of flooded forests and mangrove stands could contribute to studies of the acquisition of water and nutrients by plant roots. NASA's airborne Slope Imaging Multi-polarization Photon-counting Lidar (SIMPL) provides unique capabilities that can identify below-canopy surface water, measure its height with respect to vegetation constituents with sub-decimeter precision and quantify its slope. It also provides information on canopy structure and closure, the water column extinction profile as a proxy for turbidity and water depth, with the penetration depth constrained by turbidity. It achieves this by using four laser beams operating at two wavelengths with measurements of water surface elevation at 1064 nm (near infrared) and water column properties at 532 nm (green), analogous to a bathymetric lidar. Importantly the instrument adds a polarimetry function, like some atmospheric lidars, which measures the amount of depolarization determined by the degree to which the plane-parallel transmitted laser pulse energy is converted to the perpendicular state. The degree of depolarization is sensitive to the number of photon multiple-scattering events. For the water surface, which is specular consisting only of single-scattering events, the near-infrared received signal retains the parallel polarization state. Absence of the perpendicular signal uniquely identifies surface water. Penetration of green light and the depth profile of photons converted to the perpendicular state compared to those in the parallel state is a measure of water-column multiple scattering, providing a relative measure of turbidity. The amount of photons reflected from the canopy versus the water provides a wavelength-dependent measure of canopy closure. By rapidly firing laser pulses (11,400 pulses per second) with a narrow width (1 nsec) and detecting single photons

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

Intracavity upconversion for IR absorption lidar: Comparison of linear and ring cavity designs

DEFF Research Database (Denmark)

Meng, Lichun; Høgstedt, Lasse; Tidemand-Lichtenberg, Peter

2017-01-01

Upconversion detection is a promising technology for measurement of IR signals in the 1.5 μm–2 μm region used for lidar remote sensing [1-2]. In comparison to conventional InGaAs detector, the upconversion detector can achieve IR detection with better signal-to-noise ratio (SNR), not only due...

Winds observed in the Northern European seas with wind lidars, meteorological masts and satellite

DEFF Research Database (Denmark)

Hasager, Charlotte Bay; Stein, D.; Peña, Alfredo

2013-01-01

Ocean winds have been observed in the Baltic, Irish and North Seas from a combination of groundbased lidars, tall offshore meteorological masts and satellites remote sensing in recent years. In the FP7 project NORSEWInD (2008-2012) the project partners joined forces to ensure collection of these ...

Estimation of the under-surface temperature pattern by dynamic remote sensing

Energy Technology Data Exchange (ETDEWEB)

Inamura, M [Univ. of Tokyo; Tao, R; Katsuma, T; Toyota, H

1977-10-01

There are three basic classifications of remote sensing: passive RS, which involves measurement of reflected solar radiation; active RS, which involves the use of microwaves or laser radar; and infrared scanning. These methods make possible the determination of an object's surface temperature, its effective emissivity, and its effective reflectivity. The surface temperature, in effect, contains information concerning the structure below the surface. Fundamental experiments were conducted to extract sub-surface information by means of 'dynamic remote sensing.' Aluminum objects were embedded in a container filled with sand, and the container was heated from below. First, the spatial transfer function of the medium (sand) was determined, the surface temperature pattern was filtered, and the subsurface temperature pattern was calculated, allowing the subsurface forms of the aluminum objects to be estimated. The relationship between the thermal input (bottom temperature) and the thermal output (surface temperature) was expressed in terms of electrical circuit analogs, and the heat capacity and thermal conductivity of the sample were calculated, permitting estimation of its composition. This technique will be useful for groundwater and mineral exploration and for nondestructive testing.

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

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

Water Mapping Using Multispectral Airborne LIDAR Data

Science.gov (United States)

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

2018-04-01

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

Autonomous target recognition using remotely sensed surface vibration measurements

Science.gov (United States)

Geurts, James; Ruck, Dennis W.; Rogers, Steven K.; Oxley, Mark E.; Barr, Dallas N.

1993-09-01

The remotely measured surface vibration signatures of tactical military ground vehicles are investigated for use in target classification and identification friend or foe (IFF) systems. The use of remote surface vibration sensing by a laser radar reduces the effects of partial occlusion, concealment, and camouflage experienced by automatic target recognition systems using traditional imagery in a tactical battlefield environment. Linear Predictive Coding (LPC) efficiently represents the vibration signatures and nearest neighbor classifiers exploit the LPC feature set using a variety of distortion metrics. Nearest neighbor classifiers achieve an 88 percent classification rate in an eight class problem, representing a classification performance increase of thirty percent from previous efforts. A novel confidence figure of merit is implemented to attain a 100 percent classification rate with less than 60 percent rejection. The high classification rates are achieved on a target set which would pose significant problems to traditional image-based recognition systems. The targets are presented to the sensor in a variety of aspects and engine speeds at a range of 1 kilometer. The classification rates achieved demonstrate the benefits of using remote vibration measurement in a ground IFF system. The signature modeling and classification system can also be used to identify rotary and fixed-wing targets.

Field test of an all-semiconductor laser-based coherent continuous-wave Doppler lidar for wind energy applications

DEFF Research Database (Denmark)

Sjöholm, Mikael; Dellwik, Ebba; Hu, Qi

-produced all-semiconductor laser. The instrument is a coherent continuous-wave lidar with two fixed-focus telescopes for launching laser beams in two different directions. The alternation between the telescopes is achieved by a novel switching technique without any moving parts. Here, we report results from...... signal strength from external atmospheric parameters such as relative humidity and concentrations of atmospheric particles is discussed. This novel lidar instrument design seems to offer a promising low-cost alternative for prevision remote sensing of wind turbine inflow....

Research on the space-borne coherent wind lidar technique and the prototype experiment

Science.gov (United States)

Gao, Long; Tao, Yuliang; An, Chao; Yang, Jukui; Du, Guojun; Zheng, Yongchao

2016-10-01

Space-borne coherent wind lidar technique is considered as one of the most promising and appropriate remote Sensing methods for successfully measuring the whole global vector wind profile between the lower atmosphere and the middle atmosphere. Compared with other traditional methods, the space-borne coherent wind lidar has some advantages, such as, the all-day operation; many lidar systems can be integrated into the same satellite because of the light-weight and the small size, eye-safe wavelength, and being insensitive to the background light. Therefore, this coherent lidar could be widely applied into the earth climate research, disaster monitoring, numerical weather forecast, environment protection. In this paper, the 2μm space-borne coherent wind lidar system for measuring the vector wind profile is proposed. And the technical parameters about the sub-system of the coherent wind lidar are simulated and the all sub-system schemes are proposed. For sake of validating the technical parameters of the space-borne coherent wind lidar system and the optical off-axis telescope, the weak laser signal detection technique, etc. The proto-type coherent wind lidar is produced and the experiments for checking the performance of this proto-type coherent wind lidar are finished with the hard-target and the soft target, and the horizontal wind and the vertical wind profile are measured and calibrated, respectively. For this proto-type coherent wind lidar, the wavelength is 1.54μm, the pulse energy 80μJ, the pulse width 300ns, the diameter of the off-axis telescope 120mm, the single wedge for cone scanning with the 40°angle, and the two dualbalanced InGaAs detector modules are used. The experiment results are well consisted with the simulation process, and these results show that the wind profile between the vertical altitude 4km can be measured, the accuracy of the wind velocity and the wind direction are better than 1m/s and +/-10°, respectively.

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).

How to apply the optimal estimation method to your lidar measurements for improved retrievals of temperature and composition

Science.gov (United States)

Sica, R. J.; Haefele, A.; Jalali, A.; Gamage, S.; Farhani, G.

2018-04-01

The optimal estimation method (OEM) has a long history of use in passive remote sensing, but has only recently been applied to active instruments like lidar. The OEM's advantage over traditional techniques includes obtaining a full systematic and random uncertainty budget plus the ability to work with the raw measurements without first applying instrument corrections. In our meeting presentation we will show you how to use the OEM for temperature and composition retrievals for Rayleigh-scatter, Ramanscatter and DIAL lidars.

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

Science.gov (United States)

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

2017-01-19

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

Quantifying TOLNet Ozone Lidar Accuracy During the 2014 DISCOVER-AQ and FRAPPE Campaigns

Science.gov (United States)

Wang, Lihua; Newchurch, Michael J.; Alvarez, Raul J., II; Berkoff, Timothy A.; Brown, Steven S.; Carrion, William; De Young, Russell J.; Johnson, Bryan J.; Ganoe, Rene; Gronoff, Guillaume;

Surface-enhanced Raman fiberoptic sensors for remote monitoring

Energy Technology Data Exchange (ETDEWEB)

Stokes, D.L.; Alarie, J.P.; Vo-Dinh, T. [Oak Ridge National Lab., TN (United States). Health Sciences Research Div.

1995-09-01

A new sensor design for remote surface-enhanced Raman scattering (SERS) measurements has been developed for environmental applications. The design features the modification of an optical fiber using layers of alumina microparticles and silver coatings for inducing the SERS effect at the sensing probe. A single fiber carries both the laser excitation and the SERS signal radiation, keeping optical parameters at the remote tip simple and consistent. The small tip size achievable with this configuration also demonstrates potential of this new design as a microsensor for in-situ measurement in microenvironments. Details of sensor tip fabrication and optical system design are described. SERS spectra of aqueous environmental samples acquired in-situ using the SERS sensor are also presented to illustrate the effectiveness of the SERS sensor.

Application of lidar and optical data for oil palm plantation management in Malaysia

Science.gov (United States)

Shafri, Helmi Z. M.; Ismail, Mohd Hasmadi; Razi, Mohd Khairil M.; Anuar, Mohd Izzuddin; Ahmad, Abdul Rahman

2012-11-01

Proper oil palm plantation management is crucial for Malaysia as the country depends heavily on palm oil as a major source of national income. Precision agriculture is considered as one of the approaches that can be adopted to improve plantation practices for plantation managers such as the government-owned FELDA. However, currently the implementation of precision agriculture based on remote sensing and GIS is still lacking. This study explores the potential of the use of LiDAR and optical remote sensing data for plantation road and terrain planning for planting purposes. Traditional approaches use land surveying techniques that are time consuming and costly for vast plantation areas. The first ever airborne LiDAR and multispectral survey for oil palm plantation was carried out in early 2012 to test its feasibility. Preliminary results show the efficiency of such technology in demanding engineering and agricultural requirements of oil palm plantation. The most significant advantage of the approach is that it allows plantation managers to accurately plan the plantation road and determine the planting positions of new oil palm seedlings. Furthermore, this creates for the first time, digital database of oil palm estate and the airborne imagery can also be used for related activities such as oil palm tree inventory and detection of palm diseases. This work serves as the pioneer towards a more frequent application of LiDAR and multispectral data for oil palm plantation in Malaysia.

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%.

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.

Lidar Measurements of Ozone, Aerosols, and Clouds Observed in the Tropics Near Central America During TC4-Costa Rica

Science.gov (United States)

Hair, J. W.; Browell, E.; Butler, C.; Fenn, M.; Notari, A.; Simpson, S.; Ismail, S.; Avery, M.

2007-12-01

Large-scale measurements of ozone and aerosol distributions were made from the NASA DC-8 aircraft during the TC4 (Tropical Composition, Cloud, and Climate Coupling) field experiment conducted from June 28 - August 10, 2007 based in San Jose, Costa Rica. Remote measurements were made with an airborne lidar to provide ozone and multiple-wavelength aerosol and cloud backscatter profiles from near the surface to above the tropopause along the flight track. Aerosol depolarization measurements were also made for the detection of nonspherical aerosols, such as mineral dust, biomass burning, and recent emissions from South American volcanoes. Long-range transport of Saharan dust with depolarizing aerosols was frequently observed in the lower troposphere both over the Caribbean Sea and Pacific Ocean and within the marine boundary layer. In addition, visible and sub-visible cirrus clouds were observed with the multi-wavelength backscatter and depolarization measurements. Initial distributions of ozone, aerosol, and cloud are presented which will be used to interpret large-scale atmospheric processes. In situ measurements of ozone and aerosols made onboard the DC-8 will be compared to the remote lidar measurements. This paper provides a first look at the characteristics of ozone, aerosol, and cloud distributions that were encountered during this field experiment and provide a unique dataset that will be further related through satellite data, backward trajectories, and chemical transport models (CTM) to sources and sinks of ozone, aerosols, and clouds and to dynamical, chemical, and radiative processes.

Remote measurements of water pollution with a lidar polarimeter

Science.gov (United States)

Sheives, T. C.; Rouse, J. W., Jr.; Mayo, W. T., Jr.

1974-01-01

This paper examines a dual polarization laser backscatter system as a method for remote measurements of certain water quality parameters. Analytical models for describing the backscatter from turbid water and oil on turbid water are presented and compared with experimental data. Laser backscatter field measurements from natural waterways are presented and compared with simultaneous ground observations of the water quality parameters: turbidity, suspended solids, and transmittance. The results of this study show that the analytical models appear valid and that the sensor investigated is applicable to remote measurements of these water quality parameters and oil spills on water.-

Calculating the ecosystem service of water storage in isolated wetlands using LIDAR in north central Florida, USA

Science.gov (United States)

This study used remotely-sensed Light Detection and Ranging (LiDAR) data to estimate potential water storage capacity of isolated wetlands in north central Florida. The data were used to calculate the water storage potential of >8500 polygons identified as isolated wetlands. We ...

EAARL Topography-Vicksburg National Military Park 2007: First Surface

Science.gov (United States)

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Segura, Martha; Yates, Xan

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first-surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the National Park Service (NPS), Gulf Coast Network, Lafayette, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of the Vicksburg National Military Park in Mississippi, acquired on September 12, 2007. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the EAARL system, and the resulting data were then

EAARL Coastal Topography-Pearl River Delta 2008: First Surface

Science.gov (United States)

Nayegandhi, Amar; Brock, John C.; Wright, C. Wayne; Miner, Michael D.; Michael, D.; Yates, Xan; Bonisteel, Jamie M.

2009-01-01

These remotely sensed, geographically referenced elevation measurements of Lidar-derived first surface (FS) topography were produced as a collaborative effort between the U.S. Geological Survey (USGS), Florida Integrated Science Center (FISC), St. Petersburg, FL; the University of New Orleans (UNO), Pontchartrain Institute for Environmental Sciences (PIES), New Orleans, LA; and the National Aeronautics and Space Administration (NASA), Wallops Flight Facility, VA. This project provides highly detailed and accurate datasets of a portion of the Pearl River Delta in Louisiana and Mississippi, acquired March 9-11, 2008. The datasets are made available for use as a management tool to research scientists and natural resource managers. An innovative airborne Lidar instrument originally developed at the NASA Wallops Flight Facility, and known as the Experimental Advanced Airborne Research Lidar (EAARL), was used during data acquisition. The EAARL system is a raster-scanning, waveform-resolving, green-wavelength (532-nanometer) Lidar designed to map near-shore bathymetry, topography, and vegetation structure simultaneously. The EAARL sensor suite includes the raster-scanning, water-penetrating full-waveform adaptive Lidar, a down-looking red-green-blue (RGB) digital camera, a high-resolution multi-spectral color infrared (CIR) camera, two precision dual-frequency kinematic carrier-phase GPS receivers, and an integrated miniature digital inertial measurement unit, which provide for submeter georeferencing of each laser sample. The nominal EAARL platform is a twin-engine Cessna 310 aircraft, but the instrument may be deployed on a range of light aircraft. A single pilot, a Lidar operator, and a data analyst constitute the crew for most survey operations. This sensor has the potential to make significant contributions in measuring sub-aerial and submarine coastal topography within cross-environmental surveys. Elevation measurements were collected over the survey area using the

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 Remote Sensing of Surface Radiative Temperature over Barbados.

Science.gov (United States)

remote sensing of surface radiative temperature over Barbados was undertaken using a PRT-5 attached to a light aircraft. Traverses across the centre of the island, over the rugged east coast area, and the urban area of Bridgetown were undertaken at different times of day and night in the last week of June and the first week of December, 1969. These traverses show that surface variations in long-wave radiation emission lie within plus or minus 5% of the observations over grass at a representative site. The quick response of the surface to sunset and sunrise was

Tentative detection of clear-air turbulence using a ground-based Rayleigh lidar.

Science.gov (United States)

Hauchecorne, Alain; Cot, Charles; Dalaudier, Francis; Porteneuve, Jacques; Gaudo, Thierry; Wilson, Richard; Cénac, Claire; Laqui, Christian; Keckhut, Philippe; Perrin, Jean-Marie; Dolfi, Agnès; Cézard, Nicolas; Lombard, Laurent; Besson, Claudine

2016-05-01

Atmospheric gravity waves and turbulence generate small-scale fluctuations of wind, pressure, density, and temperature in the atmosphere. These fluctuations represent a real hazard for commercial aircraft and are known by the generic name of clear-air turbulence (CAT). Numerical weather prediction models do not resolve CAT and therefore provide only a probability of occurrence. A ground-based Rayleigh lidar was designed and implemented to remotely detect and characterize the atmospheric variability induced by turbulence in vertical scales between 40 m and a few hundred meters. Field measurements were performed at Observatoire de Haute-Provence (OHP, France) on 8 December 2008 and 23 June 2009. The estimate of the mean squared amplitude of bidimensional fluctuations of lidar signal showed excess compared to the estimated contribution of the instrumental noise. This excess can be attributed to atmospheric turbulence with a 95% confidence level. During the first night, data from collocated stratosphere-troposphere (ST) radar were available. Altitudes of the turbulent layers detected by the lidar were roughly consistent with those of layers with enhanced radar echo. The derived values of turbulence parameters Cn2 or CT2 were in the range of those published in the literature using ST radar data. However, the detection was at the limit of the instrumental noise and additional measurement campaigns are highly desirable to confirm these initial results. This is to our knowledge the first successful attempt to detect CAT in the free troposphere using an incoherent Rayleigh lidar system. The built lidar device may serve as a test bed for the definition of embarked CAT detection lidar systems aboard airliners.

PERFORMANCE EVALUATION OF A LIGHT-WEIGHT MULTI-ECHO LIDAR FOR UNMANNED ROTORCRAFT APPLICATIONS

Directory of Open Access Journals (Sweden)

G. Conte

2013-08-01

Full Text Available The paper presents a light-weight and low-cost airborne terrain mapping system. The developed Airborne LiDAR Scanner (ALS system consists of a high-precision GNSS receiver, an inertial measurement unit and a magnetic compass which are used to complement a LiDAR sensor in order to compute a digital surface model. Evaluation of the accuracy of the generated surface model is presented. Additionally, a comparison is provided between the surface model generated from the developed ALS system and a model generated using a commercial photogrammetric software. Finally, the multi-echo capability of the used LiDAR sensor is evaluated in areas covered with dense vegetation. The ALS system and camera systems were mounted on-board an industrial unmanned helicopter of around 100 kilograms maximum take-off weight. Presented results are based on real flight-test data.

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.

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.

A Decade Remote Sensing River Bathymetry with the Experimental Advanced Airborne Research LiDAR

Science.gov (United States)

Kinzel, P. J.; Legleiter, C. J.; Nelson, J. M.; Skinner, K.

2012-12-01

Since 2002, the first generation of the Experimental Advanced Airborne Research LiDAR (EAARL-A) sensor has been deployed for mapping rivers and streams. We present and summarize the results of comparisons between ground truth surveys and bathymetry collected by the EAARL-A sensor in a suite of rivers across the United States. These comparisons include reaches on the Platte River (NE), Boise and Deadwood Rivers (ID), Blue and Colorado Rivers (CO), Klamath and Trinity Rivers (CA), and the Shenandoah River (VA). In addition to diverse channel morphologies (braided, single thread, and meandering) these rivers possess a variety of substrates (sand, gravel, and bedrock) and a wide range of optical characteristics which influence the attenuation and scattering of laser energy through the water column. Root mean square errors between ground truth elevations and those measured by the EAARL-A ranged from 0.15-m in rivers with relatively low turbidity and highly reflective sandy bottoms to over 0.5-m in turbid rivers with less reflective substrates. Mapping accuracy with the EAARL-A has proved challenging in pools where bottom returns are either absent in waveforms or are of such low intensity that they are treated as noise by waveform processing algorithms. Resolving bathymetry in shallow depths where near surface and bottom returns are typically convolved also presents difficulties for waveform processing routines. The results of these evaluations provide an empirical framework to discuss the capabilities and limitations of the EAARL-A sensor as well as previous generations of post-processing software for extracting bathymetry from complex waveforms. These experiences and field studies not only provide benchmarks for the evaluation of the next generation of bathymetric LiDARs for use in river mapping, but also highlight the importance of developing and standardizing more rigorous methods to characterize substrate reflectance and in-situ optical properties at study sites

Overview of Lidar Contributions to the Atmospheric Carbon and Transport - America (ACT-America) Program

Science.gov (United States)

Davis, K. J.; Meadows, B.; Barrick, J. D. W.; Bell, E.; Browell, E. V.; Campbell, J. F.; DiGangi, J. P.; Chen, G.; Dobler, J. T.; Fan, T. F.; Feng, S.; Fried, A.; Kooi, S. A.; Lauvaux, T.; Lin, B.; McGill, M. J.; Miles, N.; Nehrir, A. R.; Obland, M. D.; O'Dell, C.; Pal, S.; Pauly, R.; Sweeney, C.; Yang, M. Y.

2017-12-01

The Atmospheric Carbon and Transport - America (ACT-America) is an Earth Venture Suborbital -2 (EVS-2) mission sponsored by the Earth Science Division of NASA's Science Mission Directorate. A major objective is to enhance our knowledge of the sources/sinks and transport of atmospheric CO2 through the application of remote and in situ airborne measurements of CO2 and other atmospheric properties on spatial and temporal scales not previously available to the science community. ACT-America consists of five campaigns to measure regional carbon and evaluate transport under various meteorological conditions in three regional areas of the Continental United States. Three of the five campaigns, summer 2016, winter 2017, and fall 2017, have taken place. Data have been collected during these campaigns using 2 airborne platforms (NASA Wallops' C-130 and NASA Langley's B-200) with in-situ instruments on both aircraft and three lidar systems on the C-130, along with instrumented towers and coordinated under flights with the Orbiting Carbon Observatory (OCO-2) satellite. The lidar systems include the Harris Corp. Multi-Frequency Fiber Laser Lidar (MFLL), the NASA Langley ASCENDS CarbonHawk Experiment Simulator (ACES) and the Goddard Cloud Physics Laboratory (CPL). The airborne lidars provide unique data that complement the more traditional in situ sensors. Lidar CO2 measurements provide integrated views of spatial variations of partial columns of atmospheric CO2 which can be adjusted to the column of scientific interest by changing flight altitudes. Lidar backscatter data provide detailed views of atmospheric layers, including the atmospheric boundary layer, residual layers, and cloud layers. The combination of these two lidars provide a far more comprehensive view of atmospheric structure and CO2 content than can be achieved with in situ measurements alone. This presentation provides an overview of the application of these three lidar systems toward achieving ACT

Offshore winds mapped from satellite remote sensing

DEFF Research Database (Denmark)

Hasager, Charlotte Bay

2014-01-01

the uncertainty on the model results on the offshore wind resource, it is necessary to compare model results with observations. Observations from ground-based wind lidar and satellite remote sensing are the two main technologies that can provide new types of offshore wind data at relatively low cost....... The advantages of microwave satellite remote sensing are 1) horizontal spatial coverage, 2) long data archives and 3) high spatial detail both in the coastal zone and of far-field wind farm wake. Passive microwave ocean wind speed data are available since 1987 with up to 6 observations per day with near...

Earth and atmospheric remote sensing; Proceedings of the Meeting, Orlando, FL, Apr. 2-4, 1991

Science.gov (United States)

Curran, Robert J. (Editor); Smith, James A. (Editor); Watson, Ken (Editor)

1991-01-01

The papers presented in this volume address the technical aspects of earth and atmospheric remote sensing. Topics discussed include spaceborne and ground-based applications of laser remote sensing, advanced applications of lasers in remote sensing, laser ranging applications, data analysis and systems for biospheric processes, measurements for biospheric processes, and remote sensing for geology and geophysics. Papers are presented on a space-qualified laser transmitter for lidar applications, solid state lasers for planetary exploration, automated band selection for multispectral meteorological applications, aerospace remote sensing of natural water organics, and remote sensing of volcanic ash hazards to aircraft.

A Survey of LIDAR Technology and Its Use in Spacecraft Relative Navigation

Science.gov (United States)

Christian, John A.; Cryan, Scott P.

2013-01-01

This paper provides a survey of modern LIght Detection And Ranging (LIDAR) sensors from a perspective of how they can be used for spacecraft relative navigation. In addition to LIDAR technology commonly used in space applications today (e.g. scanning, flash), this paper reviews emerging LIDAR technologies gaining traction in other non-aerospace fields. The discussion will include an overview of sensor operating principles and specific pros/cons for each type of LIDAR. This paper provides a comprehensive review of LIDAR technology as applied specifically to spacecraft relative navigation. HE problem of orbital rendezvous and docking has been a consistent challenge for complex space missions since before the Gemini 8 spacecraft performed the first successful on-orbit docking of two spacecraft in 1966. Over the years, a great deal of effort has been devoted to advancing technology associated with all aspects of the rendezvous, proximity operations, and docking (RPOD) flight phase. After years of perfecting the art of crewed rendezvous with the Gemini, Apollo, and Space Shuttle programs, NASA began investigating the problem of autonomous rendezvous and docking (AR&D) to support a host of different mission applications. Some of these applications include autonomous resupply of the International Space Station (ISS), robotic servicing/refueling of existing orbital assets, and on-orbit assembly.1 The push towards a robust AR&D capability has led to an intensified interest in a number of different sensors capable of providing insight into the relative state of two spacecraft. The present work focuses on exploring the state-of-the-art in one of these sensors - LIght Detection And Ranging (LIDAR) sensors. It should be noted that the military community frequently uses the acronym LADAR (LAser Detection And Ranging) to refer to what this paper calls LIDARs. A LIDAR is an active remote sensing device that is typically used in space applications to obtain the range to one or more

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

Mapping snags and understory shrubs for LiDAR based assessment of wildlife habitat suitability

Science.gov (United States)

Sebastian Martinuzzi; Lee A. Vierling; William A. Gould; Michael J. Falkowski; Jeffrey S. Evans; Andrew T. Hudak; Kerri T. Vierling

2009-01-01

The lack of maps depicting forest three-dimensional structure, particularly as pertaining to snags and understory shrub species distribution, is a major limitation for managing wildlife habitat in forests. Developing new techniques to remotely map snags and understory shrubs is therefore an important need. To address this, we first evaluated the use of LiDAR data for...

A remote sensing and GIS-enabled highway asset management system : final report.

Science.gov (United States)

2016-04-01

The objective of this project is to validate the use of commercial remote sensing and spatial information : (CRS&SI) technologies, including emerging 3D line laser imaging technology, mobile LiDAR, image : processing algorithms, and GPS/GIS technolog...

A REMOTE SENSING AND GIS-ENABLED HIGHWAY ASSET MANAGEMENT SYSTEM PHASE 2

Science.gov (United States)

2018-02-02

The objective of this project is to validate the use of commercial remote sensing and spatial information (CRS&SI) technologies, including emerging 3D line laser imaging technology, mobile light detection and ranging (LiDAR), image processing algorit...

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

Science.gov (United States)

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

2016-01-01

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

Data processing technique for multiangle lidar sounding of poorly stratified polluted atmospheres: Theory and experiment

Science.gov (United States)

Cyle E. Wold; Vladimir A. Kovalev; Alexander P. Petkov; Wei Min Hao

2012-01-01

Scanning elastic lidar, which can operate in different slant directions, is the most appropriate remote sensing tool for investigating the optical properties of smoke-polluted atmospheres. However, the commonly used methodologies of multiangle measurements are based on the assumption of horizontal stratification of the searched atmosphere1,2. When working in real...

Range Information Characterization of the Hokuyo UST-20LX LIDAR Sensor

Directory of Open Access Journals (Sweden)

Matthew A. Cooper

2018-05-01

Full Text Available This paper presents a study on the data measurements that the Hokuyo UST-20LX Laser Rangefinder produces, which compiles into an overall characterization of the LiDAR sensor relative to indoor environments. The range measurements, beam divergence, angular resolution, error effect due to some common painted and wooden surfaces, and the error due to target surface orientation are analyzed. It was shown that using a statistical average of sensor measurements provides a more accurate range measurement. It was also shown that the major source of errors for the Hokuyo UST-20LX sensor was caused by something that will be referred to as “mixed pixels”. Additional error sources are target surface material, and the range relative to the sensor. The purpose of this paper was twofold: (1 to describe a series of tests that can be performed to characterize various aspects of a LIDAR system from a user perspective, and (2 present a detailed characterization of the commonly-used Hokuyo UST-20LX LIDAR sensor.

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.

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

Directory of Open Access Journals (Sweden)

Mwafag Ghanma

2004-07-01

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

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

Directory of Open Access Journals (Sweden)

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.

Remote sensing estimates of impervious surfaces for pluvial flood modelling

DEFF Research Database (Denmark)

Kaspersen, Per Skougaard; Drews, Martin

This paper investigates the accuracy of medium resolution (MR) satellite imagery in estimating impervious surfaces for European cities at the detail required for pluvial flood modelling. Using remote sensing techniques enables precise and systematic quantification of the influence of the past 30...

A Hierarchical Object-oriented Urban Land Cover Classification Using WorldView-2 Imagery and Airborne LiDAR data

Science.gov (United States)

Wu, M. F.; Sun, Z. C.; Yang, B.; Yu, S. S.

2016-11-01

In order to reduce the “salt and pepper” in pixel-based urban land cover classification and expand the application of fusion of multi-source data in the field of urban remote sensing, WorldView-2 imagery and airborne Light Detection and Ranging (LiDAR) data were used to improve the classification of urban land cover. An approach of object- oriented hierarchical classification was proposed in our study. The processing of proposed method consisted of two hierarchies. (1) In the first hierarchy, LiDAR Normalized Digital Surface Model (nDSM) image was segmented to objects. The NDVI, Costal Blue and nDSM thresholds were set for extracting building objects. (2) In the second hierarchy, after removing building objects, WorldView-2 fused imagery was obtained by Haze-ratio-based (HR) fusion, and was segmented. A SVM classifier was applied to generate road/parking lot, vegetation and bare soil objects. (3) Trees and grasslands were split based on an nDSM threshold (2.4 meter). The results showed that compared with pixel-based and non-hierarchical object-oriented approach, proposed method provided a better performance of urban land cover classification, the overall accuracy (OA) and overall kappa (OK) improved up to 92.75% and 0.90. Furthermore, proposed method reduced “salt and pepper” in pixel-based classification, improved the extraction accuracy of buildings based on LiDAR nDSM image segmentation, and reduced the confusion between trees and grasslands through setting nDSM threshold.

Remote Sensing of Three-dimensional Winds with Elastic Lidar: Explanation of Maximum Cross-correlation Method

Science.gov (United States)

Buttler, William T.; Soriano, Cecilia; Baldasano, Jose M.; Nickel, George H.

Maximum cross-correlation provides a method toremotely de-ter-mine high-lyre-solved three-dimensional fields of horizontalwinds with e-las-tic li-darthrough-out large volumes of the planetaryboundary layer (PBL). This paperdetails the technique and shows comparisonsbetween elastic lidar winds, remotelysensed laser Doppler velocimeter (LDV) windprofiles, and radiosonde winds.Radiosonde wind data were acquired at Barcelona,Spain, during the BarcelonaAir-Quality Initiative (1992), and the LDVwind data were acquired at SunlandPark, New Mexico during the 1994 Border AreaAir-Quality Study. Comparisonsshow good agreement between the differentinstruments, and demonstrate the methoduseful for air pollution management at thelocal/regional scale. Elastic lidar windscould thus offer insight into aerosol andpollution transport within the PBL. Lidarwind fields might also be used to nudge orimprove initialization and evaluation ofatmospheric meteorological models.

2010 ARRA Lidar: California Coastal Project (Zone 3)

Data.gov (United States)

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

2010 ARRA Lidar: California Coastal Project (Zone 4)

Data.gov (United States)

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

2-Micron Triple-Pulse Integrated Path Differential Absorption Lidar Development for Simultaneous Airborne Column Measurements of Carbon Dioxide and Water Vapor in the Atmosphere

Science.gov (United States)

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

2016-01-01

For more than 15 years, NASA Langley Research Center (LaRC) has contributed in developing several 2-micron carbon dioxide active remote sensors using the DIAL technique. Currently, an airborne 2-micron triple-pulse integrated path differential absorption (IPDA) lidar is under development at NASA LaRC. This paper focuses on the advancement of the 2-micron triple-pulse IPDA lidar development. Updates on the state-of-the-art triple-pulse laser transmitter will be presented including the status of wavelength control, packaging and lidar integration. In addition, receiver development updates will also be presented, including telescope integration, detection systems and data acquisition electronics. Future plan for IPDA lidar system for ground integration, testing and flight validation will be presented.

Integrating remotely sensed surface water extent into continental scale hydrology.

Science.gov (United States)

Revilla-Romero, Beatriz; Wanders, Niko; Burek, Peter; Salamon, Peter; de Roo, Ad

2016-12-01

In hydrological forecasting, data assimilation techniques are employed to improve estimates of initial conditions to update incorrect model states with observational data. However, the limited availability of continuous and up-to-date ground streamflow data is one of the main constraints for large-scale flood forecasting models. This is the first study that assess the impact of assimilating daily remotely sensed surface water extent at a 0.1° × 0.1° spatial resolution derived from the Global Flood Detection System (GFDS) into a global rainfall-runoff including large ungauged areas at the continental spatial scale in Africa and South America. Surface water extent is observed using a range of passive microwave remote sensors. The methodology uses the brightness temperature as water bodies have a lower emissivity. In a time series, the satellite signal is expected to vary with changes in water surface, and anomalies can be correlated with flood events. The Ensemble Kalman Filter (EnKF) is a Monte-Carlo implementation of data assimilation and used here by applying random sampling perturbations to the precipitation inputs to account for uncertainty obtaining ensemble streamflow simulations from the LISFLOOD model. Results of the updated streamflow simulation are compared to baseline simulations, without assimilation of the satellite-derived surface water extent. Validation is done in over 100 in situ river gauges using daily streamflow observations in the African and South American continent over a one year period. Some of the more commonly used metrics in hydrology were calculated: KGE', NSE, PBIAS%, R 2 , RMSE, and VE. Results show that, for example, NSE score improved on 61 out of 101 stations obtaining significant improvements in both the timing and volume of the flow peaks. Whereas the validation at gauges located in lowland jungle obtained poorest performance mainly due to the closed forest influence on the satellite signal retrieval. The conclusion is that

VERTICAL ACCURACY COMPARISON OF DIGITAL ELEVATION MODEL FROM LIDAR AND MULTITEMPORAL SATELLITE IMAGERY

Directory of Open Access Journals (Sweden)

J. Octariady

2017-05-01

Full Text Available Digital elevation model serves to illustrate the appearance of the earth's surface. DEM can be produced from a wide variety of data sources including from radar data, LiDAR data, and stereo satellite imagery. Making the LiDAR DEM conducted using point cloud data from LiDAR sensor. Making a DEM from stereo satellite imagery can be done using same temporal or multitemporal stereo satellite imagery. How much the accuracy of DEM generated from multitemporal stereo stellite imagery and LiDAR data is not known with certainty. The study was conducted using LiDAR DEM data and multitemporal stereo satellite imagery DEM. Multitemporal stereo satellite imagery generated semi-automatically by using 3 scene stereo satellite imagery with acquisition 2013–2014. The high value given each of DEM serve as the basis for calculating high accuracy DEM respectively. The results showed the high value differences in the fraction of the meter between LiDAR DEM and multitemporal stereo satellite imagery DEM.

The Use of Three-Dimensional Convolutional Neural Networks to Interpret LiDAR for Forest Inventory

Directory of Open Access Journals (Sweden)

Elias Ayrey

2018-04-01

Full Text Available As light detection and ranging (LiDAR technology becomes more available, it has become common to use these datasets to generate remotely sensed forest inventories across landscapes. Traditional methods for generating these inventories employ the use of height and proportion metrics to measure LiDAR returns and relate these back to field data using predictive models. Here, we employ a three-dimensional convolutional neural network (CNN, a deep learning technique that scans the LiDAR data and automatically generates useful features for predicting forest attributes. We test the accuracy in estimating forest attributes using the three-dimensional implementations of different CNN models commonly used in the field of image recognition. Using the best performing model architecture, we compared CNN performance to models developed using traditional height metrics. The results of this comparison show that CNNs produced 12% less prediction error when estimating biomass, 6% less in estimating tree count, and 2% less when estimating the percentage of needleleaf trees. We conclude that using CNNs can be a more accurate means of interpreting LiDAR data for forest inventories compared to standard approaches.

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

Estimating forest and woodland aboveground biomass using active and passive remote sensing

Science.gov (United States)

Wu, Zhuoting; Dye, Dennis G.; Vogel, John M.; Middleton, Barry R.

2016-01-01

Aboveground biomass was estimated from active and passive remote sensing sources, including airborne lidar and Landsat-8 satellites, in an eastern Arizona (USA) study area comprised of forest and woodland ecosystems. Compared to field measurements, airborne lidar enabled direct estimation of individual tree height with a slope of 0.98 (R2 = 0.98). At the plot-level, lidar-derived height and intensity metrics provided the most robust estimate for aboveground biomass, producing dominant species-based aboveground models with errors ranging from 4 to 14Mg ha –1 across all woodland and forest species. Landsat-8 imagery produced dominant species-based aboveground biomass models with errors ranging from 10 to 28 Mg ha –1. Thus, airborne lidar allowed for estimates for fine-scale aboveground biomass mapping with low uncertainty, while Landsat-8 seems best suited for broader spatial scale products such as a national biomass essential climate variable (ECV) based on land cover types for the United States.

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.

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.

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.

Heterodyne lidar for chemical sensing

International Nuclear Information System (INIS)

Oldenborg, Richard C.; Tiee, Joe J.; Shimada, Tsutomu; Wilson, Carl W.; Remelius, Dennis K.; Fox, Jay; Swim, Cynthia

2004-01-01

The overall objective is to assess the detection performance of LWIR (long wavelength infrared) coherent Lidar systems that potentially possess enhanced effluent detection capabilities. Previous work conducted by Los Alamos has demonstrated that infrared DIfferential Absorption Lidar (DIAL) is capable of detecting chemicals in plumes from long standoff ranges. Our DIAL approach relied on the reflectivity of topographical targets to provide a strong return signal. With the inherent advantage of applying heterodyne transceivers to approach single-photon detection in LWIR, it is projected that marked improvements in detection range or in spatial coverage can be attained. In some cases, the added photon detection sensitivity could be utilized for sensing 'soft targets', such as atmospheric and threat aerosols where return signal strength is drastically reduced, as opposed to topographical targets. This would allow range resolved measurements and could lead to the mitigation of the limiting source of noise due to spectral/spatial/temporal variability of the ground scene. The ability to distinguish normal variations in the background from true chemical signatures is crucial to the further development of sensitive remote chemical sensing technologies. One main difficulty in demonstrating coherent DIAL detection is the development of suitable heterodyne transceivers that can achieve rapid multi-wavelength tuning required for obtaining spectral signature information. LANL has recently devised a novel multi-wavelength heterodyne transceiver concept that addresses this issue. A 5-KHz prototype coherent CO 2 transceiver has been constructed and is being now used to help address important issues in remote CBW agent standoff detection. Laboratory measurements of signal-to-noise ratio (SNR) will be reported. Since the heterodyne detection scheme fundamentally has poor shot-to-shot signal statistics, in order to achieve sensitive detection limits, favorable averaging statistics

Empirical Radiometric Normalization of Road Points from Terrestrial Mobile Lidar System

Directory of Open Access Journals (Sweden)

Tee-Ann Teo

2015-05-01

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

LIDAR Measurements of the Vertical Distribution of Aerosol Optical and Physical Properties over Central Asia

Science.gov (United States)

The vertical structure of aerosol optical and physical properties was measured by Lidar in Eastern Kyrgyzstan, Central Asia, from June 2008 to May 2009. Lidar measurements were supplemented with surface-based measurements of PM2.5 and PM10 mass and chemical ...

INTEGRATION OF LIDAR DATA INTO A MUNICIPAL GIS TO STUDY SOLAR RADIATION

Directory of Open Access Journals (Sweden)

P. Africani

2013-04-01

Full Text Available Identifying the right roofs to install solar panels inside a urban area is crucial for both private citizens and the whole local population. The aim is not easy because a lot of consideration must be made: insolation, orientation of the surface, size of the surface, shading due to topography, shading due to taller buildings next the surface, shading due to taller vegetation and other possible problems typical of urban areas like the presence of chimneys. Accuracy of data related to the analyzed surfaces is indeed fundamental, and also the detail of geometric models used to represent buildings and their roofs. The complexity that these roofs can reach is elevated. This work uses LiDAR data to obtain, with a semi-automatic technique, the full geometry of each roof part complementing the pre-existing building data in the municipal cartography. With this data is possible to evaluate the placement of solar panels on roofs of a whole city analyzing the solar potential of each building in detail. Other traditional techniques, like photogrammetry, need strong manual editing effort in order to identify slopes and insert vector on surfaces at the right height. Regarding LiDAR data, in order to perform accurate modelling, it is necessary to obtain an high density point cloud. The method proposed can also be used as a fast and linear workflow process for an area where LiDAR data are available and a municipal cartography already exist: LiDAR data can be furthermore successfully used to cross-check errors in pre-existent digital cartography that can remain otherwise hidden.

Improving three-tier environmental assessment model by using a 3D scanning FLS-AM series hyperspectral lidar

Science.gov (United States)

Samberg, Andre; Babichenko, Sergei; Poryvkina, Larisa

2005-05-01

Delay between the time when natural disaster, for example, oil accident in coastal water, occurred and the time when environmental protection actions, for example, water and shoreline clean-up, started is of significant importance. Mostly remote sensing techniques are considered as (near) real-time and suitable for multiple tasks. These techniques in combination with rapid environmental assessment methodologies would form multi-tier environmental assessment model, which allows creating (near) real-time datasets and optimizing sampling scenarios. This paper presents the idea of three-tier environmental assessment model. Here all three tiers are briefly described to show the linkages between them, with a particular focus on the first tier. Furthermore, it is described how large-scale environmental assessment can be improved by using an airborne 3-D scanning FLS-AM series hyperspectral lidar. This new aircraft-based sensor is typically applied for oil mapping on sea/ground surface and extracting optical features of subjects. In general, a sampling network, which is based on three-tier environmental assessment model, can include ship(s) and aircraft(s). The airborne 3-D scanning FLS-AM series hyperspectral lidar helps to speed up the whole process of assessing of area of natural disaster significantly, because this is a real-time remote sensing mean. For instance, it can deliver such information as georeferenced oil spill position in WGS-84, the estimated size of the whole oil spill, and the estimated amount of oil in seawater or on ground. All information is produced in digital form and, thus, can be directly transferred into a customer"s GIS (Geographical Information System) system.

Lidar-revised geologic map of the Des Moines 7.5' quadrangle, King County, Washington

Science.gov (United States)

Tabor, Rowland W.; Booth, Derek B.

2017-11-06

This map is an interpretation of a modern lidar digital elevation model combined with the geology depicted on the Geologic Map of the Des Moines 7.5' Quadrangle, King County, Washington (Booth and Waldron, 2004). Booth and Waldron described, interpreted, and located the geology on the 1:24,000-scale topographic map of the Des Moines 7.5' quadrangle. The base map that they used was originally compiled in 1943 and revised using 1990 aerial photographs; it has 25-ft contours, nominal horizontal resolution of about 40 ft (12 m), and nominal mean vertical accuracy of about 10 ft (3 m). Similar to many geologic maps, much of the geology in the Booth and Waldron (2004) map was interpreted from landforms portrayed on the topographic map. In 2001, the Puget Sound Lidar Consortium obtained a lidar-derived digital elevation model (DEM) for much of the Puget Sound area, including the entire Des Moines 7.5' quadrangle. This new DEM has a horizontal resolution of about 6 ft (2 m) and a mean vertical accuracy of about 1 ft (0.3 m). The greater resolution and accuracy of the lidar DEM compared to topography constructed from air-photo stereo models have much improved the interpretation of geology, even in this heavily developed area, especially the distribution and relative age of some surficial deposits. For a brief description of the light detection and ranging (lidar) remote sensing method and this data acquisition program, see Haugerud and others (2003). 

Quantifying spatial variability of depth of peat burn in wetlands in relation to antecedent characteristics using field data, multi-temporal and multi-spectral LiDAR

Science.gov (United States)

Chasmer, L.; Flade, L.; Virk, R.; Montgomery, J. S.; Hopkinson, C.; Thompson, D. K.; Petrone, R. M.; Devito, K.

2017-12-01

Landscape changes in the hydrological characteristics of wetlands in some parts of the Boreal region of Canada are occurring as a result of climate-induced feedbacks and anthropogenic disturbance. Wetlands are largely resilient to wildfire, however, natural, climatic and anthropogenic disturbances can change surface water regimes and predispose wetlands to greater depth of peat burn. Over broad areas, peat loss contributes to significant pollution emissions, which can affect community health. In this study, we a) quantify depth of peat burn and relationships to antecedent conditions (species type, topography, surficial geology) within three classified wetlands found in the Boreal Plains ecoregion of western Canada; and b) examine the impacts of wildfire on post-fire ground surface energy balance to determine how peat loss might affect local hydro-climatology and surface water feedbacks. High-resolution optical imagery, pre- and post-burn multi-spectral Light Detection And Ranging (LiDAR), airborne thermal infrared imagery, and field validation data products are integrated to identify multiple complex interactions within the study wetlands. LiDAR-derived depth of peat burn is within 1 cm (average) compared with measured (RMSE = 9 cm over the control surface), demonstrating the utility of LiDAR with high point return density. Depth of burn also correlates strongly with variations in Normalised Burn Ratio (NBR) determined for ground surfaces only. Antecedent conditions including topographic position, soil moisture, soil type and wetland species also have complex interactions with depth of peat loss within wetlands observed in other studies. However, while field measurements are important for validation and understanding eco-hydrological processes, results from remote sensing are spatially continuous. Temporal LiDAR data illustrate the full range of variability in depth of burn and wetland characteristics following fire. Finally, measurements of instantaneous surface

Selection Algorithm for the CALIPSO Lidar Aerosol Extinction-to-Backscatter Ratio

Science.gov (United States)

Omar, Ali H.; Winker, David M.; Vaughan, Mark A.

2006-01-01

The extinction-to-backscatter ratio (S(sub a)) is an important parameter used in the determination of the aerosol extinction and subsequently the optical depth from lidar backscatter measurements. We outline the algorithm used to determine Sa for the Cloud and Aerosol Lidar and Infrared Pathfinder Spaceborne Observations (CALIPSO) lidar. S(sub a) for the CALIPSO lidar will either be selected from a look-up table or calculated using the lidar measurements depending on the characteristics of aerosol layer. Whenever suitable lofted layers are encountered, S(sub a) is computed directly from the integrated backscatter and transmittance. In all other cases, the CALIPSO observables: the depolarization ratio, delta, the layer integrated attenuated backscatter, beta, and the mean layer total attenuated color ratio, gamma, together with the surface type, are used to aid in aerosol typing. Once the type is identified, a look-up-table developed primarily from worldwide observations, is used to determine the S(sub a) value. The CALIPSO aerosol models include desert dust, biomass burning, background, polluted continental, polluted dust, and marine aerosols.

Novel solid state lasers for Lidar applications at 2 μm

Science.gov (United States)

Della Valle, G.; Galzerano, G.; Toncelli, A.; Tonelli, M.; Laporta, P.

2005-09-01

A review on the results achieved by our group in the development of novel solid-state lasers for Lidar applications at 2 μm is presented. These lasers, based on fluoride crystals (YLF4, BaY2F8, and KYF4) doped with Tm and Ho ions, are characterized by high-efficiency and wide wavelength tunability around 2 μm. Single crystals of LiYF4, BaY2F8, and KYF4 codoped with the same Tm3+ and Ho3+ concentrations were successfully grown by the Czochralski method. The full spectroscopic characterization of the different laser crystals and the comparison between the laser performance are presented. Continuous wave operation was efficiently demonstrated by means of a CW diode-pumping. These oscillators find interesting applications in the field of remote sensing (Lidar and Dial systems) as well as in high-resolution molecular spectroscopy, frequency metrology, and biomedical applications.

Impact of communal land use and conservation on woody vegetation structure in the Lowveld savannas of South Africa – Lidar results

CSIR Research Space (South Africa)

Wessels, Konrad J

2011-04-01

Full Text Available use and conservation on woody vegetation structure in the Lowveld savannas of South Africa ? Lidar results. K.J. Wesselsa*, R. Mathieub, B.F.N. Erasmusc, G.P. Asnerd, I.P.J. Smite, J.A.N. Van Aardtf, R. Mainb, J. Fisherb,c a Remote Sensing... with related studies, suggest that communal land use have a higher impact on the woody cover below 5m than both elephants and fire. Keywords: Carnegie Airborne Observatory (CAO), Lidar, fuel wood, South Africa, Savannas, woody vegetation structure 1...

Big data; sensor networks and remotely-sensed data for mapping; feature extraction from lidar

Science.gov (United States)

Tlhabano, Lorato

2018-05-01

Unmanned aerial vehicles (UAVs) can be used for mapping in the close range domain, combining aerial and terrestrial photogrammetry and now the emergence of affordable platforms to carry these technologies has opened up new opportunities for mapping and modeling cadastral boundaries. At the current state mainly low cost UAVs fitted with sensors are used in mapping projects with low budgets, the amount of data produced by the UAVs can be enormous hence the need for big data techniques' and concepts. The past couple of years have witnessed the dramatic rise of low-cost UAVs fitted with high tech Lidar sensors and as such the UAVS have now reached a level of practical reliability and professionalism which allow the use of these systems as mapping platforms. UAV based mapping provides not only the required accuracy with respect to cadastral laws and policies as well as requirements for feature extraction from the data sets and maps produced, UAVs are also competitive to other measurement technologies in terms of economic aspects. In the following an overview on how the various technologies of UAVs, big data concepts and lidar sensor technologies can work together to revolutionize cadastral mapping particularly in Africa and as a test case Botswana in particular will be used to investigate these technologies. These technologies can be combined to efficiently provide cadastral mapping in difficult to reach areas and over large areas of land similar to the Land Administration Procedures, Capacity and Systems (LAPCAS) exercise which was recently undertaken by the Botswana government, we will show how the uses of UAVS fitted with lidar sensor and utilizing big data concepts could have reduced not only costs and time for our government but also how UAVS could have provided more detailed cadastral maps.

Doppler lidar investigation of wind turbine wake characteristics and atmospheric turbulence under different surface roughness.

Science.gov (United States)

Zhai, Xiaochun; Wu, Songhua; Liu, Bingyi

2017-06-12

Four field experiments based on Pulsed Coherent Doppler Lidar with different surface roughness have been carried out in 2013-2015 to study the turbulent wind field in the vicinity of operating wind turbine in the onshore and offshore wind parks. The turbulence characteristics in ambient atmosphere and wake area was analyzed using transverse structure function based on Plane Position Indicator scanning mode. An automatic wake processing procedure was developed to determine the wake velocity deficit by considering the effect of ambient velocity disturbance and wake meandering with the mean wind direction. It is found that the turbine wake obviously enhances the atmospheric turbulence mixing, and the difference in the correlation of turbulence parameters under different surface roughness is significant. The dependence of wake parameters including the wake velocity deficit and wake length on wind velocity and turbulence intensity are analyzed and compared with other studies, which validates the empirical model and simulation of a turbine wake for various atmosphere conditions.

The Myres Hill remote sensing intercomparison study: preliminary results

Energy Technology Data Exchange (ETDEWEB)

Clive, P J M; Chindurza, I [SgurrEnergy Ltd, 79 Coplaw Street, Glasgow G42 7JG, Scotland (United Kingdom); Ravey, I; Bass, J [RES Group Ltd, James Blyth House, 7000 Academy Park, Glasgow, Scotland (United Kingdom); Boyle, R J; Jones, P [TUV NEL Ltd, East Kilbride, Glasgow G75 0QF, Scotland (United Kingdom); Lang, S J [Sustainable Energy Research Group, University College Cork (Ireland); Bradley, S [Mighty River Power, Level 14, 23-29 Albert Street, Auckland (New Zealand); Hay, L [Garrad Hassan and Partners Ltd, 2064 Maryhill Road, Glasgow G20 0AB, Scotland (United Kingdom); Oldroyd, A [Oldbaum Services Ltd, Schoolhouse, Brig o' Turk, Callander, Scotland (United Kingdom); Stickland, M [University of Strathclyde, 16 Richmond Street, Glasgow G1 1XQ, Scotland (United Kingdom)], E-mail: peter.clive@sgurrenergy.com

2008-05-01

Two remote sensing techniques (SODAR and LIDAR) have been developed for measuring wind speed and turbulence from ground level up to altitudes of 300 m or higher. Although originally developed in the defence sector, these techniques are now generating considerable interest in the renewable energy and meteorological sectors. Despite the benefits of these instruments they are not yet generally accepted for due diligence measurements by wind energy developers and financial institutions. There is a requirement for a series of independent assessments of these new metrology techniques, comparing their measurements with the approved cup-type anemometer readings. This is being addressed at TUV NEL's Myres Hill wind turbine test site in a measurement programme supported by the DIUS National Measurement Systems Measurement for Innovators scheme and a consortium of 21 industrial collaborators. Data from SODAR and LIDAR systems are being compared with results from cup-type anemometers mounted at different heights on an 80m meteorological mast. An ultrasonic sensor is also mounted on the mast. The objective of the test programme is to assess the effectiveness of SODAR and LIDAR wind speed measurement techniques under different operating regimes and atmospheric conditions. Results from the measurements will provide definitive data on the performance of the remote wind speed sensing techniques under test on complex terrain typical of many wind farm sites. Preliminary measurements based on data acquired during the initial measurement campaign are presented.

Inter-comparison of lidar and ceilometer retrievals for aerosol and Planetary Boundary Layer profiling over Athens, Greece

Directory of Open Access Journals (Sweden)

G. Tsaknakis

2011-06-01

Full Text Available This study presents an inter-comparison of two active remote sensors (lidar and ceilometer to determine the mixing layer height and structure of the Planetary Boundary Layer (PBL and to retrieve tropospheric aerosol vertical profiles over Athens, Greece. This inter-comparison was performed under various strongly different aerosol loads/types (urban air pollution, biomass burning and Saharan dust event, implementing two different lidar systems (one portable Raymetrics S.A. lidar system running at 355 nm and one multi-wavelength Raman lidar system running at 355 nm, 532 nm and 1064 nm and one CL31 Vaisala S.A. ceilometer (running at 910 nm. Spectral conversions of the ceilometer's data were performed using the Ångström exponent estimated by ultraviolet multi-filter radiometer (UV-MFR measurements. The inter-comparison was based on two parameters: the mixing layer height determined by the presence of the suspended aerosols and the attenuated backscatter coefficient. Additionally, radiosonde data were used to derive the PBL height. In general, a good agreement was found between the ceilometer and the lidar techniques in both inter-compared parameters in the height range from 500 m to 5000 m, while the limitations of each instrument are also examined.

Calculating the ecosystem service of water storage in isolated wetlands using LiDAR in north central Florida, USA (presentation)

Science.gov (United States)

This study used remotely-sensed Light Detection and Ranging (LiDAR) data to estimate potential water storage capacity of isolated wetlands in north central Florida. The data were used to calculate the water storage potential of >8500 polygons identified as isolated wetlands. We f...

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...

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

Science.gov (United States)

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

2014-12-01

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

Assessment of particle emissions inventories in northeastern U.S., using remote sensing, Lidar technology, air pollution sensors, and a Lagrangian particle dispersion model

Science.gov (United States)