Academic literature on the topic 'Air-borne LiDAR'

Indigenous forests cover 24% of New Zealand and provide valuable ecosystem services. However, a national map of forest types, that is, physiognomic types, which would benefit conservation management, does not currently exist at an appropriate level of detail. While traditional forest classification approaches from remote sensing data are based on spectral information alone, the joint use of space-based optical imagery and structural information from synthetic aperture radar (SAR) and canopy metrics from air-borne Light Detection and Ranging (LiDAR) facilitates more detailed and accurate classifications of forest structure. We present a support vector machine (SVM) classification using data from the European Space Agency (ESA) Sentinel-1 and 2 missions, Advanced Land Orbiting Satellite (ALOS) PALSAR, and airborne LiDAR to produce a regional map of physiognomic types of indigenous forest. A five-fold cross-validation (repeated 100 times) of ground data showed that the highest classification accuracy of 80.5% is achieved for bands 2, 3, 4, 8, 11, and 12 from Sentinel-2, the ratio of bands VH (vertical transmit and horizontal receive) and VV (vertical transmit and vertical receive) from Sentinel-1, and mean canopy height and 97th percentile canopy height from LiDAR. The classification based on optical bands alone was 72.7% accurate and the addition of structural metrics from SAR and LiDAR increased accuracy by 7.4%. The classification accuracy is sufficient for many management applications for indigenous forest, including biodiversity management, carbon inventory, pest control, ungulate management, and disease management.

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

We develop the synergetic ground-based active-sensor-system for the evaluation of observations by space-borne lidars. The system consists of second version of multi-field-view multiple-scattering polarization lidar (MFMSPL-2), multiple-field-of-view high spectral resolution polarization lidar, direct-detection Doppler wind lidar, coherent Doppler wind lidar and 94GHz cloud profiling radar. The system can simulate observed signals from sensors onboard the joint Japanese/European mission Earth Clouds, Aerosols and Radiation Explorer (EarthCARE). The observation system can provide unique opportunity to study interaction of cloud microphysics, aerosol microphysics, vertical air motion and vertical distribution of horizontal wind and it will lead to evaluate cloud-convective parameterization and to reduce uncertainties in climate change predictions.

Abstract. Polar stratospheric clouds (PSCs) have been observed from 2014 to 2018 from the lidar observatory at the Antarctic Concordia station (Dome C), included as a primary station in the NDACC (Network for Detection of Atmospheric Climate Change). Many of these measurements have been performed in coincidence with overpasses of the satellite-borne CALIOP (Cloud Aerosol Lidar with Orthogonal Polarization) lidar, in order to perform a comparison in terms of PSC detection and composition classification. Good agreement has been obtained, despite intrinsic differences in observation geometry and data sampling. This study reports, to our knowledge, the most extensive comparison of PSC observations by ground-based and satellite-borne lidars. The PSCs observed by the ground-based lidar and CALIOP form a complementary and congruent dataset and allow us to study the seasonal and interannual variations in PSC occurrences at Dome C. Moreover, a strong correlation with the formation temperature of NAT (nitric acid trihydrate), TNAT, calculated from local temperature, pressure, and H2O and HNO3 concentrations is shown. PSCs appear at Dome C at the beginning of June up to 26 km and start to disappear in the second half of August, when the local temperatures start to rise above TNAT. Rare PSC observations in September coincide with colder air masses below 18 km.

Abstract. We present initial aerosol validation results of the space-borne lidar CALIOP retrievals -onboard the CALIPSO satellite-, using coincident observations performed with a ground-based lidar in Athens, Greece (37.9° N, 23.6° E). A multi-wavelength ground-based backscatter/Raman lidar system is operating since 2000 at the National Technical University of Athens (NTUA) in the framework of the European Aerosol Research LIdar NETwork (EARLINET), the first lidar network for tropospheric aerosol studies on a continental scale. Since July 2006, a total of 40 coincidental aerosol ground-based lidar measurements were performed over Athens during CALIPSO overpasses. The duration of the ground-based lidar measurements was approximately two hours, centred on the satellite overpass time. From the statistical analysis of the ground-based/satellite correlative lidar measurements, a mean bias of the order of 22% for daytime measurements and of 8% for nighttime measurements with respect to the CALIPSO profiles was found for altitudes between 3 and 10 km. The mean bias becomes much larger for altitudes lower that 3 km (of the order of 60%) which is attributed to the decrease of the CALIOP signal-to-noise ratio, as well as to the incomplete overlap height region of the ground based lidar and finally to the distance between the two instruments, resulting to the observation of possibly different air masses. In cases of aerosols layers underlying cirrus clouds, comparison results for aerosol tropospheric profiles become worst, illustrating the limitations of space-borne downward-looking lidar measurements due to strong signal attenuations.

Abstract. Height-resolved air mass source attribution is crucial for the evaluation of profiling ground-based remote sensing observations, especially when using lidar (light detection and ranging) to investigate different aerosol types throughout the atmosphere. Lidar networks, such as EARLINET (European Aerosol Research Lidar Network) in the frame of ACTRIS (Aerosol, Clouds and Trace Gases), observe profiles of optical aerosol properties almost continuously, but usually, additional information is needed to support the characterization of the observed particles. This work presents an approach explaining how backward trajectories or particle positions from a dispersion model can be combined with geographical information (a land cover classification and manually defined areas) to obtain a continuous and vertically resolved estimate of an air mass source above a certain location. Ideally, such an estimate depends on as few as possible a priori information and auxiliary data. An automated framework for the computation of such an air mass source is presented, and two applications are described. First, the air mass source information is used for the interpretation of air mass sources for three case studies with lidar observations from Limassol (Cyprus), Punta Arenas (Chile) and ship-borne off Cabo Verde. Second, air mass source statistics are calculated for two multi-week campaigns to assess potential observation biases of lidar-based aerosol statistics. Such an automated approach is a valuable tool for the analysis of short-term campaigns but also for long-term data sets, for example, acquired by EARLINET.

Abstract. We present initial aerosol validation results of the space-borne lidar CALIOP -onboard the CALIPSO satellite- Level 1 attenuated backscatter coefficient profiles, using coincident observations performed with a ground-based lidar in Athens, Greece (37.9° N, 23.6° E). A multi-wavelength ground-based backscatter/Raman lidar system is operating since 2000 at the National Technical University of Athens (NTUA) in the framework of the European Aerosol Research LIdar NETwork (EARLINET), the first lidar network for tropospheric aerosol studies on a continental scale. Since July 2006, a total of 40 coincidental aerosol ground-based lidar measurements were performed over Athens during CALIPSO overpasses. The ground-based measurements were performed each time CALIPSO overpasses the station location within a maximum distance of 100 km. The duration of the ground–based lidar measurements was approximately two hours, centred on the satellite overpass time. From the analysis of the ground-based/satellite correlative lidar measurements, a mean bias of the order of 22% for daytime measurements and of 8% for nighttime measurements with respect to the CALIPSO profiles was found for altitudes between 3 and 10 km. The mean bias becomes much larger for altitudes lower that 3 km (of the order of 60%) which is attributed to the increase of aerosol horizontal inhomogeneity within the Planetary Boundary Layer, resulting to the observation of possibly different air masses by the two instruments. In cases of aerosol layers underlying Cirrus clouds, comparison results for aerosol tropospheric profiles become worse. This is attributed to the significant multiple scattering effects in Cirrus clouds experienced by CALIPSO which result in an attenuation which is less than that measured by the ground-based lidar.

Abstract. Remote-sensing measurements by light detection and ranging (lidar) instruments are fundamental for the monitoring of altitude-resolved aerosol optical properties. Here we validate vertical profiles of aerosol backscatter coefficient (βaer) measured by two independent lidar systems using co-located balloon-borne measurements performed by Compact Optical Backscatter Aerosol Detector (COBALD) sondes. COBALD provides high-precision in situ measurements of βaer at two wavelengths (455 and 940 nm). The two analyzed lidar systems are the research Raman Lidar for Meteorological Observations (RALMO) and the commercial CHM15K ceilometer (Lufft, Germany). We consider in total 17 RALMO and 31 CHM15K profiles, co-located with simultaneous COBALD soundings performed throughout the years 2014–2019 at the MeteoSwiss observatory of Payerne (Switzerland). The RALMO (355 nm) and CHM15K (1064 nm) measurements are converted to 455 and 940 nm, respectively, using the Ångström exponent profiles retrieved from COBALD data. To account for the different receiver field-of-view (FOV) angles between the two lidars (0.01–0.02∘) and COBALD (6∘), we derive a custom-made correction using Mie-theory scattering simulations. Our analysis shows that both lidar instruments achieve on average a good agreement with COBALD measurements in the boundary layer and free troposphere, up to 6 km altitude. For medium-high-aerosol-content measurements at altitudes below 3 km, the mean ± standard deviation difference in βaer calculated from all considered soundings is −2 % ± 37 % (−0.018 ± 0.237 Mm−1 sr−1 at 455 nm) for RALMO−COBALD and +5 % ± 43 % (+0.009 ± 0.185 Mm−1 sr−1 at 940 mm) for CHM15K−COBALD. Above 3 km altitude, absolute deviations generally decrease, while relative deviations increase due to the prevalence of air masses with low aerosol content. Uncertainties related to the FOV correction and spatial- and temporal-variability effects (associated with the balloon's drift with altitude and different integration times) contribute to the large standard deviations observed at low altitudes. The lack of information on the aerosol size distribution and the high atmospheric variability prevent an accurate quantification of these effects. Nevertheless, the excellent agreement observed in individual profiles, including fine and complex structures in the βaer vertical distribution, shows that under optimal conditions, the discrepancies with the in situ measurements are typically comparable to the estimated statistical uncertainties in the remote-sensing measurements. Therefore, we conclude that βaer profiles measured by the RALMO and CHM15K lidar systems are in good agreement with in situ measurements by COBALD sondes up to 6 km altitude.

Abstract. Cirrus ice particle sedimentation velocity (vr) is one of the critical variables for the parameterization of cirrus properties in a global climate model (GCM). In this study a methodology to estimate cirrus properties, such as crystal mean fall speed, through successive lidar measurements is evaluated. This "Match" technique has been applied on cirrus cloud observations and then tested with measurements from two ground-based lidars located in the Mediterranean Area. These systems have similar instrumental characteristics, and are operated manually respectively at the Observatory of Haute Provence (OHP, 43.9° N, 5.7° E) in France and at Rome Tor Vergata (RTV, 41.8° N, 12.6° E) in Italy at a distance of approximately 600 km providing systematic measurements since several years. The both sites are along a typical direction of an air path and a test case of an upper tropospheric cirrus, observed over both sites during the night between 13 and 14 of March 2008, has been identified and investigated. The analysis through lidar primarily parameters (cloud shape and vertical location) reveals a case of a thin sub-visible cirrus (SVC) located around the tropopause. The feasibility to estimate crystal fall velocity has been tested and values of 1.4–1.9 cm s−1, consistent with simple-shaped small crystals, have been retrieved. Despite several uncertainties that affect the single-wavelength lidar measurements, sedimentation could be a partial reason for the cirrus property changes (e.g. geometrical thickness and back-scattering profile distribution) observed from one site to the other. The backward trajectory analysis suggests a type of cirrus formed by large-scale transport processes (adiabatic cooling of moist air masses coming from the subtropical area around Mexico gulf), which is characterized by a long atmospheric lifetime and horizontal extension of several hundreds of km. This study shows that such approach can be improved in using closer locations, ancillary data (e.g. temperature, water vapour, etc.), particle distribution utilizing multi-wavelengths space-borne lidar measurements or balloon size particle and cirrus microphysical-resolved models.

Abstract. A unique data set of ship-borne lidar measurements of Saharan dust layers above the Atlantic ocean has been collected aboard the research vessel Polarstern with a mobile Aerosol Raman Lidar (MARL) during the LIMPIDO-campaign in June 2000. Extended Saharan dust layers have been observed in the region between 8.5° N and 34° N in an altitude range between 2 and 6 km. The continental, North African origin of the probed air masses is confirmed by 8-day backward trajectories. The Saharan dust is characterized by an optical depth in the range of 0.1 and 0.3, a depolarization around 10\\% and high lidar ratios of 45 sr at 532 nm and 75 sr at 355 nm. The backscattering by the dust particles at the UV-wavelength is relatively weak, resulting in a negative color index. From the measured optical properties the effective radius and the refractive index of the dust particles are derived using a new approach based on Mie Theory and non-spherical scattering calculations. The low backscatter coefficient observed at 355 nm is due to significant absorption which increases with decreasing wavelength. This finding agrees very well with results from satellite and sun photometer measurements. The effective radii decrease from about 3 mm base to 0.6 mm at the top of the dust plumes. The non-spherical shapes of the dust particles are responsible for the high values of the lidar ratios.

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

Measurements of atmospheric properties become progressively more difficult with altitude above the surface of the earth, and even surface measurements are difficult over the oceans. First balloons, then airplanes and rockets, were used to carry instruments aloft to make in-situ measurements. Now remote sensors, both ground-based and satellite-borne, are used to monitor the atmosphere. In this context, upper air means all of the troposphere above the first hundred meters or so and, in some cases, the stratosphere. There are many uncertainties associated with remote sensing, so there is a demand for in-situ sensors to verify remote measurements. In addition, the balloon- borne instrument package is relatively inexpensive. However, it should be noted that cost is a matter of perspective; a satellite with its instrumentation, ground station, etc. may be cost-effective when the mission is to make measurements all over the world with good space and time resolution, as synoptic meteorology demands. Upper air measurements of pressure, temperature, water vapor, and winds can be made using in-situ instrument packages (carried aloft by balloons, rockets, or airplanes) and by remote sensors. Remote sensors can be classified as active (energy emitters like radar or lidar) or passive (receiving only, like microwave radiometers), and by whether they “look” up from the ground or down from a satellite. Remote sensors are surveyed briefly before discussing in-situ instruments. Profiles of temperature, humidity, density, etc. can be estimated from satellites using multiple narrow-band radiometers. These are passive sensors that measure longwave radiation upwelling from the atmosphere. For example, temperature profiles can be estimated from satellites by measuring infrared radiation emitted by CO2 (bands around 5000 μm) and O2 (bands around 3.4μm and 15μm) in the atmosphere. Winds can be estimated from cloud movements or by using the Doppler frequency shift due to some component of the atmosphere being carried along with the wind. An active sensor (radar) is used to estimate precipitation and, if it is a Doppler radar, determine winds. The great advantage of satellite-borne instruments is that they can cover the whole earth with excellent spatial resolution.

Weather phenomena occur over a very broad range of scales of space and time, from the global circulation systems that extend around the earth’s circumference to the small eddies that cause cigarette smoke to swirl and mix with clear air. Each circulation can be described in terms of its approximate horizontal diameter and lifetime. Large-scale weather systems, such as hemispheric wave patterns called Rossby waves, monsoons, high and low pressure centers, and fronts, are called synopticscale weather systems. Temperature, humidity, pressure, and wind measurements collected simultaneously all over the world are used to analyze and forecast the evolution of these systems, which have diameters greater than 200 km (125 mi) and lifetimes of days to months. Mesoscale weather events include diurnal wind systems such as mountain wind systems, like breezes, sea breezes, thunderstorms, and other phenomena with horizontal scales that range from 2 to 200 km (1 to 125 mi) and lifetimes that range from hours to days. Mesoscale meteorologists use networks of surface- based instruments, balloon-borne sounding systems, remote sensing systems (e.g., radar, lidar, and sodar), and aircraft to make observations on these scales. Microscale meteorology focuses on local or small-scale atmospheric phenomena with diameters below 2 km (1 mi) and lifetimes from seconds to hours, including gusts and turbulence, dust devils, thermals, and certain cloud types. Microscale studies are usually confined to the layer of air from the earth’s surface to an altitude where surface effects become negligible (approximately 1000 feet or 300 m at night and 5000 feet or 1500 m during the day). A fourth and less rigorously defined term, the regional scale, denotes circulations and weather events occurring on horizontal scales from 500 to 5000 km (310 to 3100 mi). The regional scale is thus smaller than synoptic scale, but larger than mesoscale. The term is often used to describe events that occur within more or less homogeneous physiographic provinces (e.g., the Pacific Northwest region). Major mountain ranges impact the weather on the synoptic scale. They anchor large-scale pressure systems in the Northern Hemisphere, cause low and high pressure weather systems to form, and produce large-scale seasonal wind systems in Asia and North America.