Journal articles: 'Iterative Airborne Lidar Inversion'

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Stachlewska, I. S., R. Neuber, A. Lampert, C. Ritter, and G. Wehrle. "AMALi – the Airborne Mobile Aerosol Lidar for Arctic research." Atmospheric Chemistry and Physics 10, no. 6 (March 29, 2010): 2947–63. http://dx.doi.org/10.5194/acp-10-2947-2010.

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Abstract. The Airborne Mobile Aerosol Lidar (AMALi) is an instrument developed at the Alfred Wegener Institute for Polar and Marine Research for reliable operation under the challenging weather conditions at the Earth's polar regions. Since 2003 the AMALi has been successfully deployed for measurements in ground-based installation and zenith- or nadir-pointing airborne configurations during several scientific campaigns in the Arctic. The lidar provides backscatter profiles at two wavelengths (355/532 nm or 1064/532 nm) together with the linear depolarization at 532 nm, from which aerosol and cloud properties can be derived. This paper presents the characteristics and capabilities of the AMALi system and gives examples of its usage for airborne and ground-based operations in the Arctic. As this backscatter lidar normally does not operate in aerosol-free layers special evaluation schemes are discussed, the nadir-pointing iterative inversion for the case of an unknown boundary condition and the two-stream approach for the extinction profile calculation if a second lidar system probes the same air mass. Also an intercomparison of the AMALi system with an established ground-based Koldewey Aerosol Raman Lidar (KARL) is given.

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Liu Houtong, 刘厚通, 葛占旗 Ge Zhanqi, 王珍珠 Wang Zhenzhu, 黄威 Huang Wei, and 周军 Zhou Jun. "Extinction Coefficient Inversion of Airborne Lidar Detecting in Low-Altitude by Fernald Iterative Backwark Integration Method (FIBIM)." Acta Optica Sinica 28, no. 10 (2008): 1837–43. http://dx.doi.org/10.3788/aos20082810.1837.

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Chen, Xiang, and Moriya. "Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms." Remote Sensing 12, no. 3 (February 8, 2020): 571. http://dx.doi.org/10.3390/rs12030571.

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Information for individual trees (e.g., position, treetop, height, crown width, and crown edge) is beneficial for forest monitoring and management. Light Detection and Ranging (LiDAR) data have been widely used to retrieve these individual tree parameters from different algorithms, with varying successes. In this study, we used an iterative Triangulated Irregular Network (TIN) algorithm to separate ground and canopy points in airborne LiDAR data, and generated Digital Elevation Models (DEM) by Inverse Distance Weighted (IDW) interpolation, thin spline interpolation, and trend surface interpolation, as well as by using the Kriging algorithm. The height of the point cloud was assigned to a Digital Surface Model (DSM), and a Canopy Height Model (CHM) was acquired. Then, four algorithms (point-cloud-based local maximum algorithm, CHM-based local maximum algorithm, watershed algorithm, and template-matching algorithm) were comparatively used to extract the structural parameters of individual trees. The results indicated that the two local maximum algorithms can effectively detect the treetop; the watershed algorithm can accurately extract individual tree height and determine the tree crown edge; and the template-matching algorithm works well to extract accurate crown width. This study provides a reference for the selection of algorithms in individual tree parameter inversion based on airborne LiDAR data and is of great significance for LiDAR-based forest monitoring and management.

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Zhou, Daniel K., William L. Smith, Xu Liu, Allen M. Larar, Stephen A. Mango, and Hung-Lung Huang. "Physically Retrieving Cloud and Thermodynamic Parameters from Ultraspectral IR Measurements." Journal of the Atmospheric Sciences 64, no. 3 (March 1, 2007): 969–82. http://dx.doi.org/10.1175/jas3877.1.

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Abstract A physical inversion scheme has been developed dealing with cloudy as well as cloud-free radiance observed with ultraspectral infrared sounders to simultaneously retrieve surface, atmospheric thermodynamic, and cloud microphysical parameters. A fast radiative transfer model, which applies to the clouded atmosphere, is used for atmospheric profile and cloud parameter retrieval. A one-dimensional (1D) variational multivariable inversion solution is used to improve an iterative background state defined by an eigenvector-regression retrieval. The solution is iterated in order to account for nonlinearity in the 1D variational solution. It is shown that relatively accurate temperature and moisture retrievals can be achieved below optically thin clouds. For optically thick clouds, accurate temperature and moisture profiles down to cloud-top level are obtained. For both optically thin and thick cloud situations, the cloud-top height can be retrieved with relatively high accuracy (i.e., error <1 km). National Polar-orbiting Operational Environmental Satellite System (NPOESS) Airborne Sounder Testbed Interferometer (NAST-I) retrievals from the The Observing-System Research and Predictability Experiment (THORPEX) Atlantic Regional Campaign are compared with coincident observations obtained from dropsondes and the nadir-pointing cloud physics lidar (CPL). This work was motivated by the need to obtain solutions for atmospheric soundings from infrared radiances observed for every individual field of view, regardless of cloud cover, from future ultraspectral geostationary satellite sounding instruments, such as the Geosynchronous Imaging Fourier Transform Spectrometer (GIFTS). However, this retrieval approach can also be applied to the ultraspectral sounding instruments to fly on polar satellites, such as the Infrared Atmospheric Sounding Interferometer (IASI) on the European MetOp satellite, the Cross-track Infrared Sounder (CrIS) on the NPOESS Preparatory Project, and the follow-on NPOESS series of satellites.

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Gao, Meng, Bryan A. Franz, Kirk Knobelspiesse, Peng-Wang Zhai, Vanderlei Martins, Sharon Burton, Brian Cairns, et al. "Efficient multi-angle polarimetric inversion of aerosols and ocean color powered by a deep neural network forward model." Atmospheric Measurement Techniques 14, no. 6 (June 4, 2021): 4083–110. http://dx.doi.org/10.5194/amt-14-4083-2021.

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Abstract. NASA's Plankton, Aerosol, Cloud, ocean Ecosystem (PACE) mission, scheduled for launch in the timeframe of 2023, will carry a hyperspectral scanning radiometer named the Ocean Color Instrument (OCI) and two multi-angle polarimeters (MAPs): the UMBC Hyper-Angular Rainbow Polarimeter (HARP2) and the SRON Spectro-Polarimeter for Planetary EXploration one (SPEXone). The MAP measurements contain rich information on the microphysical properties of aerosols and hydrosols and therefore can be used to retrieve accurate aerosol properties for complex atmosphere and ocean systems. Most polarimetric aerosol retrieval algorithms utilize vector radiative transfer models iteratively in an optimization approach, which leads to high computational costs that limit their usage in the operational processing of large data volumes acquired by the MAP imagers. In this work, we propose a deep neural network (NN) forward model to represent the radiative transfer simulation of coupled atmosphere and ocean systems for applications to the HARP2 instrument and its predecessors. Through the evaluation of synthetic datasets for AirHARP (airborne version of HARP2), the NN model achieves a numerical accuracy smaller than the instrument uncertainties, with a running time of 0.01 s in a single CPU core or 1 ms in a GPU. Using the NN as a forward model, we built an efficient joint aerosol and ocean color retrieval algorithm called FastMAPOL, evolved from the well-validated Multi-Angular Polarimetric Ocean coLor (MAPOL) algorithm. Retrievals of aerosol properties and water-leaving signals were conducted on both the synthetic data and the AirHARP field measurements from the Aerosol Characterization from Polarimeter and Lidar (ACEPOL) campaign in 2017. From the validation with the synthetic data and the collocated High Spectral Resolution Lidar (HSRL) aerosol products, we demonstrated that the aerosol microphysical properties and water-leaving signals can be retrieved efficiently and within acceptable error. Comparing to the retrieval speed using a conventional radiative transfer forward model, the computational acceleration is 103 times faster with CPU or 104 times with GPU processors. The FastMAPOL algorithm can be used to operationally process the large volume of polarimetric data acquired by PACE and other future Earth-observing satellite missions with similar capabilities.

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Yang, X., X. Xi, C. Wang, J. Shi, and Y. Huang. "A PHYSICAL INVERSION METHOD OF CANOPY FPAR FROM AIRBORNE LIDAR DATA AND GROUND MEASUREMENTS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B3-2020 (August 21, 2020): 553–57. http://dx.doi.org/10.5194/isprs-archives-xliii-b3-2020-553-2020.

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Abstract. Fraction of absorbed Photosynthetically Active Radiation (FPAR) is one of the pivotal parameters in terrestrial ecosystem modelling and crop growth monitoring. Airborne LiDAR is an advanced active remote sensing technology which can acquire fine three-dimensional canopy structural information quickly and accurately. Although some previous studies have shown that LiDAR-derived metrics had strong relationships with canopy FPARs, these estimation models without physical meaning are hard to be extended to various vegetation canopies and different growth periods. This study proposed a physical FPAR inversion method based on airborne LiDAR data and field measurements. The method considered direct and diffuse radiations separately based on the SAIL model and energy budget balance principle. The canopy FPAR was inversed from the structural information provided by LiDAR point cloud data and the spectral information provided by ground measurements. The estimated FPAR was validated with the field-measured FPAR over 39 maize plots. Results showed that the proposed method had a good performance in estimating the total FPAR of maize canopy (R2 = 0.76, RMSE = 0.062, n = 39). This study provides the potential to estimate the total, direct, and diffuse FPARs of vegetation canopy from airborne LiDAR data.

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Liu, Hang, Peng Chen, Zhihua Mao, and Delu Pan. "Iterative retrieval method for ocean attenuation profiles measured by airborne lidar." Applied Optics 59, no. 10 (February 13, 2020): C42. http://dx.doi.org/10.1364/ao.379406.

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Ji Chengli, 季承荔, and 周军 Zhou Jun. "New Calibration Method for Fernald Forward Inversion of Airborne Lidar Signals." Acta Optica Sinica 29, no. 8 (2009): 2051–58. http://dx.doi.org/10.3788/aos20092908.2051.

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Ma, Xin, Haowei Zhang, Ge Han, Hao Xu, Tianqi Shi, Wei Gong, Yue Ma, and Song Li. "High-Precision CO2 Column Length Analysis on the Basis of a 1.57-μm Dual-Wavelength IPDA Lidar." Sensors 20, no. 20 (October 17, 2020): 5887. http://dx.doi.org/10.3390/s20205887.

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For high-precision measurements of the CO2 column concentration in the atmosphere with airborne integrated path differential absorption (IPDA) Lidar, the exact distance of the Lidar beam to the scattering surface, that is, the length of the column, must be measured accurately. For the high-precision inversion of the column length, we propose a set of methods on the basis of the actual conditions, including autocorrelation detection, adaptive filtering, Gaussian decomposition, and optimized Levenberg–Marquardt fitting based on the generalized Gaussian distribution. Then, based on the information of a pair of laser pulses, we use the direct adjustment method of unequal precision to eliminate the error in the distance measurement. Further, the effect of atmospheric delay on distance measurements is considered, leading to further correction of the inversion results. At last, an airborne experiment was carried out in a sea area near Qinhuangdao, China on 14 March 2019. The results showed that the ranging accuracy can reach 0.9066 m, which achieved an excellent ranging accuracy on 1.57-μm IPDA Lidar and met the requirement for high-precision CO2 column length inversion.

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Marenco, F. "Nadir airborne lidar observations of deep aerosol layers." Atmospheric Measurement Techniques 6, no. 8 (August 15, 2013): 2055–64. http://dx.doi.org/10.5194/amt-6-2055-2013.

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Abstract. The observation of deep and optically thick aerosol layers by a nadir-pointing lidar poses a challenge in terms of the signal inversion into a geophysically meaningful quantity such as extinction coefficient. A far-end reference molecular layer will usually be unavailable if the observed layer is near the surface, and using a near-end reference results in an unstable mathematical solution. In this paper, it is demonstrated that a far-end reference, taken within the aerosol layer, yields a better solution, and that the influence of the reference reduces strongly when coming inward, so that 1–2 km above reference the solution can be trusted. A method is developed to set the reference using the assumption of a well-mixed layer near the surface, and its effect is tested on data collected during recent aircraft-based campaigns. The method is also tested on simulated profiles in order to verify its limits and accuracy. The assumption of a well-mixed layer can be relaxed if one is able to set the reference well within a layer rather than at its boundaries.

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Sattel, Daniel. "Inverting airborne electromagnetic (AEM) data with Zohdy's method." GEOPHYSICS 70, no. 4 (July 2005): G77—G85. http://dx.doi.org/10.1190/1.1990217.

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Zohdy's method for the inversion of dc-resistivity data has been adapted to the inversion of airborne electromagnetic (AEM) data. AEM responses are first transformed into apparent-conductivity depth profiles, followed by an iterative adjustment of layer thicknesses and interval conductivities. The start model, including the number of layers, is determined from the data. This approach optimizes model flexibility without the need for parameter regularization. Results from Zohdy's inversion applied to TEMPEST, GEOTEM, and [Formula: see text] data acquired in a range of conductivity scenarios including the Bull Creek prospect in Queensland, Australia; the Boteti area, Botswana; and the Reid-Mahaffy test site in Ontario, Canada, show well-delineated target zones. A comparison with Occam's inversion shows good agreement between the conductivity-depth models recovered by the two methods, with Zohdy's inversion being 25 to 80 times faster.

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Liu, Chong, and Zhen Feng Shao. "Estimation of Forest Carbon Storage Based on Airborne LiDAR Data." Applied Mechanics and Materials 195-196 (August 2012): 1314–20. http://dx.doi.org/10.4028/www.scientific.net/amm.195-196.1314.

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The objective of this study was to estimate the carbon storage of forest areas by using airborne light detection and ranging (LiDAR) data. Digital canopy height model (CHM) which generated from point cloud data was combined with accurate geo-referenced true color orthophoto image to produce parameter information of trees (height, canopy diameter, DBH data) in test area by marker controlled watershed segmentation algorithm. The total carbon storage of experimental site could be calculated by adopting binary tree volume table and semi-empirical inversion means. This study suggested that the carbon storage of forest areas can be effectively estimated by using LiDAR data, which will play an important role in forest data updating and process of forget sustainable development.

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Martínez Sánchez, Jorge, Álvaro Váquez Álvarez, David López Vilariño, Francisco Fernández Rivera, José Carlos Cabaleiro Domínguez, and Tomás Fernández Pena. "Fast Ground Filtering of Airborne LiDAR Data Based on Iterative Scan-Line Spline Interpolation." Remote Sensing 11, no. 19 (September 27, 2019): 2256. http://dx.doi.org/10.3390/rs11192256.

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Over the last two decades, a wide range of applications have been developed from Light Detection and Ranging (LiDAR) point clouds. Most LiDAR-derived products require the distinction between ground and non-ground points. Because of this, ground filtering its being one of the most studied topics in the literature and robust methods are nowadays available. However, these methods have been designed to work with offline data and they are generally not well suited for real-time scenarios. Aiming to address this issue, this paper proposes an efficient method for ground filtering of airborne LiDAR data based on scan-line processing. In our proposal, an iterative 1-D spline interpolation is performed in each scan line sequentially. The final spline knots of a scan line are taken into account for the next scan line, so that valuable 2-D information is also considered without compromising computational efficiency. Points are labelled into ground and non-ground by analysing their residuals to the final spline. When tested against synthetic ground truth, the method yields a mean kappa value of 88.59% and a mean total error of 0.50%. Experiments with real data also show satisfactory results under visual inspection. Performance tests on a workstation show that the method can process up to 1 million points per second. The original implementation was ported into a low-cost development board to demonstrate its feasibility to run in embedded systems, where throughput was improved by using programmable logic hardware acceleration. Analysis shows that real-time filtering is possible in a high-end board prototype, as it can process the amount of points per second that current lightweight scanners acquire with low-energy consumption.

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Chen, H., M. Cheng, J. Li, and Y. Liu. "AN ITERATIVE TERRAIN RECOVERY APPROACH TO AUTOMATED DTM GENERATION FROM AIRBORNE LIDAR POINT CLOUDS." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XXXIX-B4 (July 31, 2012): 363–68. http://dx.doi.org/10.5194/isprsarchives-xxxix-b4-363-2012.

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dos Santos, Renato César, Mauricio Galo, and Ayman F. Habib. "Regularization of Building Roof Boundaries from Airborne LiDAR Data Using an Iterative CD-Spline." Remote Sensing 12, no. 12 (June 12, 2020): 1904. http://dx.doi.org/10.3390/rs12121904.

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Building boundaries play an essential role in many applications such as urban planning and production of 3D realistic views. In this context, airborne LiDAR data have been explored for the generation of digital building models. Despite the many developed strategies, there is no method capable of encompassing all the complexities in an urban environment. In general, the vast majority of existing regularization methods are based on building boundaries that are made up of straight lines. Therefore, the development of a strategy able to model building boundaries, regardless of their degree of complexity is of high importance. To overcome the limitations of existing strategies, an iterative CD-spline (changeable degree spline) regularization method is proposed. The main contribution is the automated selection of the polynomial function that best models each segment of the building roof boundaries. Conducted experiments with real data verified the ability of the proposed approach in modeling boundaries with different levels of complexities, including buildings composed of complex curved segments and point cloud with different densities, presenting Fscore and PoLiS around 95% and 0.30 m, respectively.

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Zhang, Xiao, Craig Glennie, and Arpan Kusari. "Change Detection From Differential Airborne LiDAR Using a Weighted Anisotropic Iterative Closest Point Algorithm." IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing 8, no. 7 (July 2015): 3338–46. http://dx.doi.org/10.1109/jstars.2015.2398317.

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Kim, Yongmin, and Yang Dam Eo. "Ground point extraction by iterative labeling of airborne LiDAR data in a forested area." KSCE Journal of Civil Engineering 19, no. 7 (February 6, 2015): 2233–39. http://dx.doi.org/10.1007/s12205-015-0319-y.

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Tinel, Claire, Jacques Testud, Jacques Pelon, Robin J. Hogan, Alain Protat, Julien Delanoë, and Dominique Bouniol. "The Retrieval of Ice-Cloud Properties from Cloud Radar and Lidar Synergy." Journal of Applied Meteorology 44, no. 6 (June 1, 2005): 860–75. http://dx.doi.org/10.1175/jam2229.1.

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Abstract Clouds are an important component of the earth’s climate system. A better description of their microphysical properties is needed to improve radiative transfer calculations. In the framework of the Earth, Clouds, Aerosols, and Radiation Explorer (EarthCARE) mission preparation, the radar–lidar (RALI) airborne system, developed at L’Institut Pierre Simon Laplace (France), can be used as an airborne demonstrator. This paper presents an original method that combines cloud radar (94–95 GHz) and lidar data to derive the radiative and microphysical properties of clouds. It combines the apparent backscatter reflectivity from the radar and the apparent backscatter coefficient from the lidar. The principle of this algorithm relies on the use of a relationship between the extinction coefficient and the radar specific attenuation, derived from airborne microphysical data and Mie scattering calculations. To solve radar and lidar equations in the cloud region where signals can be obtained from both instruments, the extinction coefficients at some reference range z0 must be known. Because the algorithms are stable for inversion performed from range z0 toward the emitter, z0 is chosen at the farther cloud boundary as observed by the lidar. Then, making an assumption of a relationship between extinction coefficient and backscattering coefficient, the whole extinction coefficient, the apparent reflectivity, cloud physical parameters, the effective radius, and ice water content profiles are derived. This algorithm is applied to a blind test for downward-looking instruments where the original profiles are derived from in situ measurements. It is also applied to real lidar and radar data, obtained during the 1998 Cloud Lidar and Radar Experiment (CLARE’98) field project when a prototype airborne RALI system was flown pointing at nadir. The results from the synergetic algorithm agree reasonably well with the in situ measurements.

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Zhang, Zhang, Ma, Tian, and Jiang. "Retrieval of Nearshore Bathymetry around Ganquan Island from LiDAR Waveform and QuickBird Image." Applied Sciences 9, no. 20 (October 16, 2019): 4375. http://dx.doi.org/10.3390/app9204375.

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Optical remote sensing is an effective means of water depth measurement, but the current approach of mainstream bathymetric retrieval requires a large amount of onsite measurement data. Such data are hard to obtain from places where underwater terrains are complicated and unsteady, and from sea areas affected by issues with rights and conflicts of interest. In recent years, the emergence of airborne light detection and ranging (LiDAR) provided a new technical means for field bathymetric survey. In this study, water depth inversion was carried out around an island far from the mainland by using remote sensing images and real LiDAR waveform data. Multi-Gaussian function fitting was proposed to extract water depth data from waveform data, and bathymetric values were used as control and validation data of the active and passive combination of water depth inversion. Results show that the relative error was 5.6% for the bathymetric retrieval from LiDAR waveform data, and the accuracy meets the requirements of ocean bathymetry. The average relative error of water depth inversion based on active and passive remote sensing was less than 9%. The method used in this study can also reduce the use of LiDAR data and the cost, thus providing a new idea for future coastal engineering application and construction.

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Rajeev, K., and K. Parameswaran. "Iterative method for the inversion of multiwavelength lidar signals to determine aerosol size distribution." Applied Optics 37, no. 21 (July 20, 1998): 4690. http://dx.doi.org/10.1364/ao.37.004690.

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Gaudfrin, Florian, Olivier Pujol, Romain Ceolato, Guillaume Huss, and Nicolas Riviere. "A new lidar inversion method using a surface reference target applied to the backscattering coefficient and lidar ratio retrievals of a fog-oil plume at short range." Atmospheric Measurement Techniques 13, no. 4 (April 16, 2020): 1921–35. http://dx.doi.org/10.5194/amt-13-1921-2020.

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Abstract. In this paper, a new elastic lidar inversion equation is presented. It is based on the backscattering signal from a surface reference target (SRT) rather than that from a volumetric layer of reference (Rayleigh molecular scatterer) as is usually done. The method presented can be used when the optical properties of such a layer are not available, e.g., in the case of airborne elastic lidar measurements or when the lidar–target line is horizontal Also, a new algorithm is described to retrieve the lidar ratio and the backscattering coefficient of an aerosol plume without any a priori assumptions about the plume. In addition, our algorithm allows a determination of the instrumental constant. This algorithm is theoretically tested, viz. by means of simulated lidar profiles and then using real measurements. Good agreement with available data in the literature has been found.

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Chang, Li-Der. "Bare-earth extraction from airborne LiDAR data based on segmentation modeling and iterative surface corrections." Journal of Applied Remote Sensing 4, no. 1 (August 1, 2010): 041884. http://dx.doi.org/10.1117/1.3491194.

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Wang, Qiang, and Wenge Ni-Meister. "Forest Canopy Height and Gaps from Multiangular BRDF, Assessed with Airborne LiDAR Data." Remote Sensing 11, no. 21 (November 1, 2019): 2566. http://dx.doi.org/10.3390/rs11212566.

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Both vegetation multi-angular and LiDAR (light detection and ranging) remote sensing data are indirectly and directly linked with 3D vegetation structure parameters, such as the tree height and vegetation gap fraction, which are critical elements in above-ground biomass and light profiles for photosynthesis estimation. LiDAR, particularly LiDAR using waveform data, provides accurate estimates of these structural parameters but suffers from not enough spatial samplings. Structural parameters retrieved from multiangular imaging data through the inversion of physical models have larger uncertainties. This study searches for an analytical approach to fuse LiDAR and multiangular data. We explore the relationships between vegetation structure parameters derived from airborne vegetation LiDAR data and multiangular data and present a new potential angle vegetation index to retrieve the tree height and gap fraction using multi-angular data in Howland Forest, Maine. The BRDF (bidirectional reflectance distribution factor) index named NDMM (normalized difference between the maximum and minimum reflectance) linearly increases with the tree height and decreases with the gap fraction. In addition, these relationships are also dependent on the wavelength, tree species, and stand density. The NDMM index performs better in conifer (R = 0.451 for tree height and R = 0.472 for the gap fraction using the near infrared band) than in deciduous and mixed forests. It is superior in sparse (R = 0.569 for tree height and R = 0.604 for the gap fraction using the near infrared band) compared to dense forest. Moreover, the NDMM index is more strongly related to tree height and the gap fraction at the near infrared band than at the three visible bands. This study sheds light on the possibility of using multiangular data to map vegetation’s structural parameters in larger regions for carbon cycle studies through the fusion of LiDAR and multiangular remote sensing data.

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Liu, Houtong, and Zhenzhu Wang. "An iterative calibrating method for airborne atmospheric detection lidar based on the klett forward integral equation." Optics Communications 452 (December 2019): 476–80. http://dx.doi.org/10.1016/j.optcom.2019.07.068.

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Yang, Yetao, Rongkui Tang, Jinglei Wang, and Mengjiao Xia. "A hierarchical deep neural network with iterative features for semantic labeling of airborne LiDAR point clouds." Computers & Geosciences 157 (December 2021): 104932. http://dx.doi.org/10.1016/j.cageo.2021.104932.

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Pérez-Ramírez, Daniel, David N. Whiteman, Igor Veselovskii, Richard Ferrare, Gloria Titos, María José Granados-Muñoz, Guadalupe Sánchez-Hernández, and Francisco Navas-Guzmán. "Spatiotemporal changes in aerosol properties by hygroscopic growth and impacts on radiative forcing and heating rates during DISCOVER-AQ 2011." Atmospheric Chemistry and Physics 21, no. 15 (August 11, 2021): 12021–48. http://dx.doi.org/10.5194/acp-21-12021-2021.

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Abstract. This work focuses on the characterization of vertically resolved aerosol hygroscopicity properties and their direct radiative effects through a unique combination of ground-based and airborne remote sensing measurements during the Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) 2011 field campaign in the Baltimore–Washington DC metropolitan area. To that end, we combined aerosol measurements from a multiwavelength Raman lidar located at NASA Goddard Space Flight Center and the airborne NASA Langley High Spectral Resolution Lidar-1 (HSRL-1) lidar system. In situ measurements aboard the P-3B airplane and ground-based Aerosol Robotic Network – Distributed Regional Aerosol Gridded Observational Network (AERONET-DRAGON) served to validate and complement quantifications of aerosol hygroscopicity from lidar measurements and also to extend the study both temporally and spatially. The focus here is on 22 and 29 July 2011, which were very humid days and characterized by a stable atmosphere and increasing relative humidity with height in the planetary boundary layer (PBL). Combined lidar and radiosonde (temperature and water vapor mixing ratio) measurements allowed the retrieval of the Hänel hygroscopic growth factor which agreed with that obtained from airborne in situ measurements and also explained the significant increase of extinction and backscattering with height. Airborne measurements also confirmed aerosol hygroscopicity throughout the entire day in the PBL and identified sulfates and water-soluble organic carbon as the main species of aerosol particles. The combined Raman and HSRL-1 measurements permitted the inversion for aerosol microphysical properties revealing an increase of particle radius with altitude consistent with hygroscopic growth. Aerosol hygroscopicity pattern served as a possible explanation of aerosol optical depth increases during the day, particularly for fine-mode particles. Lidar measurements were used as input to the libRadtran radiative transfer code to obtain vertically resolved aerosol radiative effects and heating rates under dry and humid conditions, and the results reveal that aerosol hygroscopicity is responsible for larger cooling effects in the shortwave range (7–10 W m−2 depending on aerosol load) near the ground, while heating rates produced a warming of 0.12 K d−1 near the top of PBL where aerosol hygroscopic growth was highest.

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Wang, Kunlin, Yi Ma, and Fangrong Zhou. "Tree height inversion combining light detection and ranging and optical remote sensing data." E3S Web of Conferences 165 (2020): 03020. http://dx.doi.org/10.1051/e3sconf/202016503020.

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Tree barriers in transmission line corridors are an important safety hazard.Scientific prediction of tree height and monitoring tree height changes are essential to solve this hidden danger. In this paper, the advantages of airborne lidar and optical remote sensing data are combined to research the method of tree height inversion. Based on glas data of lidar,waveform parameters such as waveform length, waveform leading edge length and waveform trailing edge length were extracted from waveform data by gaussian decomposition method.Terrain feature parameters were extracted from aster gdem data.The tree crown information was extracted from the optical remote sensing image by means of the mean shift algorithm. Then extract the vegetation index with high correlation with tree height.Finally, the extracted waveform feature parameters, topographic feature parameters, and crown index and vegetation index with high correlation are used as model input variables. The tree height inversion model was established using four regression methods, including multiple linear regression (mlr), support vector machine (svm), random forest (rf), and bp neural network (bpnn). The accuracy evaluation was conducted, and it was concluded that the tree height inversion model based on random forest obtained the best accuracy effect.

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Gisinger, Sonja, Johannes Wagner, and Benjamin Witschas. "Airborne measurements and large-eddy simulations of small-scale gravity waves at the tropopause inversion layer over Scandinavia." Atmospheric Chemistry and Physics 20, no. 16 (August 28, 2020): 10091–109. http://dx.doi.org/10.5194/acp-20-10091-2020.

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Abstract. Coordinated airborne measurements were performed by two research aircraft – Deutsches Zentrum für Luft- und Raumfahrt (DLR) Falcon and High Altitude and Long Range Aircraft (HALO) – in Scandinavia during the GW-LCYCLE II (Investigation of the life cycle of gravity waves) campaign in 2016 to investigate gravity wave processes in the upper troposphere and lower stratosphere (UTLS) region. A mountain wave event was probed over southern Scandinavia on 28 January 2016. The collected dataset constitutes a valuable combination of in situ measurements and horizontal- and altitude-resolved Doppler wind lidar and water vapour measurements with the differential absorption lidar (DIAL). In situ data at different flight altitudes and downward-pointing wind lidar measurements show pronounced changes of the horizontal scales in the vertical velocity field and of the leg-averaged momentum fluxes (MFs) in the UTLS region. The vertical velocity field was dominated by small horizontal scales with a decrease from around 20 to < 10 km in the vicinity of the tropopause inversion layer (TIL). These small scales were also found in the water vapour data and backscatter data of the DIAL. The leg-averaged MF profile determined from the wind lidar data is characterized by a pronounced kink of positive fluxes in the TIL and negative fluxes below. The largest contributions to the MF are from waves with scales > 30 km. The combination of the observations and idealized large-eddy simulations revealed the occurrence of interfacial waves having scales < 10 km on the tropopause inversion during the mountain wave event. The contribution of the interfacial waves to the leg-averaged MF is basically zero due to the phase relationship of their horizontal and vertical velocity perturbations. Interfacial waves have already been observed on boundary-layer inversions but their concept has not been applied to tropopause inversions so far. Our idealized simulations reveal that the TIL affects the vertical trend of leg-averaged MF of mountain waves and that interfacial waves can occur also on tropopause inversions. Our analyses of the horizontal- and altitude-resolved airborne observations confirm that interfacial waves actually do occur in the TIL. As predicted by linear theory, the horizontal scale of those waves is determined by the wind and stability conditions above the inversion. They are found downstream of the main mountain peaks and their MF profile varies around zero and can clearly be distinguished from the MF profile of Kelvin–Helmholtz instability. Further, the idealized large-eddy simulations reveal that the presence of the TIL is crucial in producing this kind of trapped wave at tropopause altitude.

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Boerner, Richard, Yusheng Xu, Ramona Baran, Frank Steinbacher, Ludwig Hoegner, and Uwe Stilla. "Registration of Multi-Sensor Bathymetric Point Clouds in Rural Areas Using Point-to-Grid Distances." ISPRS International Journal of Geo-Information 8, no. 4 (April 5, 2019): 178. http://dx.doi.org/10.3390/ijgi8040178.

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This article proposes a method for registration of two different point clouds with different point densities and noise recorded by airborne sensors in rural areas. In particular, multi-sensor point clouds with different point densities are considered. The proposed method is marker-less and uses segmented ground areas for registration.Therefore, the proposed approach offers the possibility to fuse point clouds of different sensors in rural areas within an accuracy of fine registration. In general, such registration is solved with extensive use of control points. The source point cloud is used to calculate a DEM of the ground which is further used to calculate point to raster distances of all points of the target point cloud. Furthermore, each cell of the raster DEM gets a height variance, further addressed as reconstruction accuracy, by calculating the grid. An outlier removal based on a dynamic threshold of distances is used to gain more robustness against noise and small geometry variations. The transformation parameters are calculated with an iterative least-squares optimization of the distances weighted with respect to the reconstruction accuracies of the grid. Evaluations consider two flight campaigns of the Mangfall area inBavaria, Germany, taken with different airborne LiDAR sensors with different point density. The accuracy of the proposed approach is evaluated on the whole flight strip of approximately eight square kilometers as well as on selected scenes in a closer look. For all scenes, it obtained an accuracy of rotation parameters below one tenth degrees and accuracy of translation parameters below the point spacing and chosen cell size of the raster. Furthermore, the possibility of registration of airborne LiDAR and photogrammetric point clouds from UAV taken images is shown with a similar result. The evaluation also shows the robustness of the approach in scenes where a classical iterative closest point (ICP) fails.

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Zhu, Yadan, Juxin Yang, Xiaoxi Zhang, Jiqiao Liu, Xiaopeng Zhu, Huaguo Zang, Tengteng Xia, et al. "Performance Improvement of Spaceborne Carbon Dioxide Detection IPDA LIDAR Using Linearty Optimized Amplifier of Photo-Detector." Remote Sensing 13, no. 10 (May 20, 2021): 2007. http://dx.doi.org/10.3390/rs13102007.

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The spaceborne double-pulse integrated-path differential absorption (IPDA) light detection and ranging (LIDAR) system was found to be helpful in observing atmospheric CO2 and understanding the carbon cycle. The airborne experiments of a scale prototype of China’s planned spaceborne IPDA LIDAR was implemented in 2019. A problem with data inversion caused by the detector module nonlinearity was found. Through many experiments, the amplifier circuit board (ACB) of the detector module was proved to be the main factor causing the nonlinearity. Through amplifier circuit optimization, the original bandwidth of the ACB was changed to 1 MHz by using a fifth-order active filter. Compared with the original version, the linearity of optimized ACB is improved from 42.6% to 0.0747%. The optimized ACB was produced and its linearity was verified by experiments. In addition, the output waveform of the optimized ACB changes significantly, which will affect the random error (RE) of the optimized IPDA LIDAR system. Through the performance simulation, the RE of more than 90% of the global area is less than 0.728 ppm. Finally, the transfer model of the detector module was given, which will be helpful for the further optimization of the CO2 column-averaged dry-air mixing ratio (XCO2) inversion algorithm.

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Tuo, Xingyu, Yin Zhang, Yulin Huang, and Jianyu Yang. "Fast Total Variation Method Based on Iterative Reweighted Norm for Airborne Scanning Radar Super-Resolution Imaging." Remote Sensing 12, no. 18 (September 5, 2020): 2877. http://dx.doi.org/10.3390/rs12182877.

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The total variation (TV) method has been applied to realizing airborne scanning radar super-resolution imaging while maintaining the outline of the target. The iterative reweighted norm (IRN) approach is an algorithm for addressing the minimum Lp norm problem by solving a sequence of minimum weighted L2 norm problems, and has been applied to solving the TV norm. However, during the solving process, the IRN method is required to update the weight term and result term in each iteration, involving multiplications and the inversion of large matrices. Consequently, it suffers from a huge calculation load, which seriously restricts the application of the TV imaging method. In this work, by analyzing the structural characteristics of the matrix involved in iteration, an efficient method based on suitable matrix blocking is proposed. It transforms multiplications and the inversion of large matrices into the computation of multiple small matrices, thereby accelerating the algorithm. The proposed method, called IRN-FTV method, is more time economical than the IRN-TV method, especially for high dimensional observation scenarios. Numerical results illustrate that the proposed IRN-FTV method enjoys preferable computational efficiency without performance degradation.

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Holtham, Elliot, and Douglas W. Oldenburg. "Large-scale inversion of ZTEM data." GEOPHYSICS 77, no. 4 (July 1, 2012): WB37—WB45. http://dx.doi.org/10.1190/geo2011-0367.1.

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A Z-Axis Tipper Electromagnetic Technique (ZTEM) survey is an airborne natural source electromagnetic survey that relates the vertical magnetic field to the horizontal magnetic fields measured at a reference station on the ground. For large airborne surveys, the high number of cells required to discretize the entire area at a reasonable resolution can make the computational cost of inverting the data set all at once prohibitively expensive. We present an iterative methodology that can be used to invert large natural source surveys by using a combination of coarse and fine meshes as well as a domain decomposition that allows the full model area to be split into smaller subproblems, which can be run in parallel. For this procedure, the entire data set is first inverted on a coarse mesh. The recovered coarse model and computed fields are used as starting models and source terms in the subsequent tiled inversions. After each round of tiled inversions, the tiles are merged together to form an update model, which is then forward modeled to determine if the model achieves the target misfit. Following this procedure, we first invert the data computed from a large synthetic model of the Noranda mining camp. The inverted models from this example are consistent among our different tiling choices. The recovered models show excellent large-scale agreement with the true model and they also recover several of the mineralized zones that were not apparent from the initial coarse inversion. Finally, we invert a [Formula: see text] block of the 2010 ZTEM survey collected over the porphyry Pebble Deposit in Alaska. The inverted ZTEM results are consistent with the results obtained using other electromagnetic methods.

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Hoge, Frank E. "Beam attenuation coefficient retrieval by inversion of airborne lidar-induced chromophoric dissolved organic matter fluorescence I Theory." Applied Optics 45, no. 10 (April 1, 2006): 2344. http://dx.doi.org/10.1364/ao.45.002344.

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Liu Hou-Tong, Chen Liang-Fu, and Su Lin. "Theoretical research of Fernald forward integration method for aerosol backscatter coefficient inversion of airborne atmosphere detecting lidar." Acta Physica Sinica 60, no. 6 (2011): 064204. http://dx.doi.org/10.7498/aps.60.064204.

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Chung, Eui-Seok, and Brian J. Soden. "A Satellite-Based Assessment of Upper-Tropospheric Water Vapor Measurements during AFWEX." Journal of Applied Meteorology and Climatology 48, no. 11 (November 1, 2009): 2284–94. http://dx.doi.org/10.1175/2009jamc2250.1.

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Abstract Consistency of upper-tropospheric water vapor measurements from a variety of state-of-the-art instruments was assessed using collocated Geostationary Operational Environmental Satellite-8 (GOES-8) 6.7-μm brightness temperatures as a common benchmark during the Atmospheric Radiation Measurement Program (ARM) First International Satellite Cloud Climatology Project (ISCCP) Regional Experiment (FIRE) Water Vapor Experiment (AFWEX). To avoid uncertainties associated with the inversion of satellite-measured radiances into water vapor quantity, profiles of temperature and humidity observed from in situ, ground-based, and airborne instruments are inserted into a radiative transfer model to simulate the brightness temperature that the GOES-8 would have observed under those conditions (i.e., profile-to-radiance approach). Comparisons showed that Vaisala RS80-H radiosondes and Meteolabor Snow White chilled-mirror dewpoint hygrometers are systemically drier in the upper troposphere by ∼30%–40% relative to the GOES-8 measured upper-tropospheric humidity (UTH). By contrast, two ground-based Raman lidars (Cloud and Radiation Test Bed Raman lidar and scanning Raman lidar) and one airborne differential absorption lidar agree to within 10% of the GOES-8 measured UTH. These results indicate that upper-tropospheric water vapor can be monitored by these lidars and well-calibrated, stable geostationary satellites with an uncertainty of less than 10%, and that correction procedures are required to rectify the inherent deficiencies of humidity measurements in the upper troposphere from these radiosondes.

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Bruggisser, Moritz, Markus Hollaus, Di Wang, and Norbert Pfeifer. "Adaptive Framework for the Delineation of Homogeneous Forest Areas Based on LiDAR Points." Remote Sensing 11, no. 2 (January 18, 2019): 189. http://dx.doi.org/10.3390/rs11020189.

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We propose a flexible framework for automated forest patch delineations that exploits a set of canopy structure features computed from airborne laser scanning (ALS) point clouds. The approach is based on an iterative subdivision of the point cloud using k-means clustering followed by an iterative merging step to tackle oversegmentation. The framework can be adapted for different applications by selecting relevant input features that best measure the intended homogeneity. In our study, the performance of the segmentation framework was tested for the delineation of forest patches with a homogeneous canopy height structure on the one hand and with similar water cycle conditions on the other. For the latter delineation, canopy components that impact interception and evapotranspiration were used, and the delineation was mainly driven by leaf area, tree functional type, and foliage density. The framework was further tested on two scenes covering a variety of forest conditions and topographies. We demonstrate that the delineated patches capture well the spatial distributions of relevant canopy features that are used for defining the homogeneity. The consistencies range from R 2 = 0 . 84 to R 2 = 0 . 86 and from R 2 = 0 . 80 to R 2 = 0 . 91 for the most relevant features in the delineation of patches with similar height structure and water cycle conditions, respectively.

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Papagiannopoulos, Nikolaos, Giuseppe D'Amico, Anna Gialitaki, Nicolae Ajtai, Lucas Alados-Arboledas, Aldo Amodeo, Vassilis Amiridis, et al. "An EARLINET early warning system for atmospheric aerosol aviation hazards." Atmospheric Chemistry and Physics 20, no. 18 (September 15, 2020): 10775–89. http://dx.doi.org/10.5194/acp-20-10775-2020.

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Abstract. A stand-alone lidar-based method for detecting airborne hazards for aviation in near real time (NRT) is presented. A polarization lidar allows for the identification of irregular-shaped particles such as volcanic dust and desert dust. The Single Calculus Chain (SCC) of the European Aerosol Research Lidar Network (EARLINET) delivers high-resolution preprocessed data: the calibrated total attenuated backscatter and the calibrated volume linear depolarization ratio time series. From these calibrated lidar signals, the particle backscatter coefficient and the particle depolarization ratio can be derived in temporally high resolution and thus provide the basis of the NRT early warning system (EWS). In particular, an iterative method for the retrieval of the particle backscatter is implemented. This improved capability was designed as a pilot that will produce alerts for imminent threats for aviation. The method is applied to data during two diverse aerosol scenarios: first, a record breaking desert dust intrusion in March 2018 over Finokalia, Greece, and, second, an intrusion of volcanic particles originating from Mount Etna, Italy, in June 2019 over Antikythera, Greece. Additionally, a devoted observational period including several EARLINET lidar systems demonstrates the network's preparedness to offer insight into natural hazards that affect the aviation sector.

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Portniaguine, Oleg, and Michael S. Zhdanov. "3‐D magnetic inversion with data compression and image focusing." GEOPHYSICS 67, no. 5 (September 2002): 1532–41. http://dx.doi.org/10.1190/1.1512749.

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We develop a method of 3‐D magnetic anomaly inversion based on traditional Tikhonov regularization theory. We use a minimum support stabilizing functional to generate a sharp, focused inverse image. An iterative inversion process is constructed in the space of weighted model parameters that accelerates the convergence and robustness of the method. The weighting functions are selected based on sensitivity analysis. To speed up the computations and to decrease the size of memory required, we use a compression technique based on cubic interpolation. Our method is designed for inversion of total magnetic anomalies, assuming the anomalous field is caused by induced magnetization only. The method is applied to synthetic data for typical models of magnetic anomalies and is tested on real airborne data provided by ExxonMobil Upstream Research Company.

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Liu, Z. Q., P. C. Li, S. H. Huang, C. L. Ye, Q. Ma, and J. J. Yang. "AUTOMATIC GLOBAL REGISTRATION BETWEEN AIRBORNE LIDAR DATA AND REMOTE SENSING IMAGE BASED ON STRAIGHT LINE FEATURES." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 1191–97. http://dx.doi.org/10.5194/isprs-archives-xlii-3-1191-2018.

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An automatic global registration approach for point clouds and remote sensing image based on straight line features is proposed which is insensitive to rotational and scale transformation. First, the building ridge lines and contour lines in point clouds are automatically detected as registration primitives by integrating region growth and topology identification. Second, the collinear condition equation is selected as registration transformation function which is based on rotation matrix described by unit quaternion. The similarity measure is established according to the distance between the corresponding straight line features from point clouds and the image in the same reference coordinate system. Finally, an iterative Hough transform is adopted to simultaneously estimate the parameters and obtain correspondence between registration primitives. Experimental results prove the proposed method is valid and the spectral information is useful for the following classification processing.

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Zhu, Yadan, Juxin Yang, Xiao Chen, Xiaopeng Zhu, Junxuan Zhang, Shiguang Li, Yanguang Sun, et al. "Airborne Validation Experiment of 1.57-μm Double-Pulse IPDA LIDAR for Atmospheric Carbon Dioxide Measurement." Remote Sensing 12, no. 12 (June 22, 2020): 1999. http://dx.doi.org/10.3390/rs12121999.

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The demand for greenhouse gas measurement has increased dramatically due to global warming. A 1.57-μm airborne double-pulse integrated-path differential absorption (IPDA) light detection and ranging (LIDAR) system for CO2 concentration measurement was developed. The airborne field experiments of this IPDA LIDAR system were conducted at a flight altitude of approximately 7 km, and the weak echo signal of the ocean area was successfully received. The matched filter algorithm was applied to the retrieval of the weak signals, and the pulse integration method was used to improve the signal-to-noise ratio. The inversion results of the CO2 column-averaged dry-air mixing ratio (XCO2) by the scheme of averaging after log (AVD) and the scheme of averaging signals before log were compared. The AVD method was found more effective for the experiment. The long-term correlation between the changing trends of XCO2 retrieved by the IPDA LIDAR system and CO2 dry-air volume mixing ratio measured by the in-situ instrument reached 92%. In the steady stage of the open area (30 km away from the coast), which is almost unaffected by the residential areas, the mean value of XCO2 retrieved by the IPDA LIDAR system was 414.69 ppm, with the standard deviation being 1.02 ppm. Compared with the CO2 concentration measured by the in-situ instrument in the same period, bias was 1.30 ppm. The flight path passed across the ocean, residential, and mountainous areas, with the mean value of XCO2 of the three areas being 419.35, 429.29, and 422.52 ppm, respectively. The gradient of the residential and ocean areas was 9.94 ppm, with that of the residential and mountainous areas being 6.77 ppm. Obvious gradients were found in different regions.

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Müller, D., C. A. Hostetler, R. A. Ferrare, S. P. Burton, E. Chemyakin, A. Kolgotin, J. W. Hair, et al. "Airborne multiwavelength High Spectral Resolution Lidar (HSRL-2) observations during TCAP 2012: vertical profiles of optical and microphysical properties of a smoke/urban haze plume over the northeastern coast of the US." Atmospheric Measurement Techniques Discussions 7, no. 2 (February 6, 2014): 1059–73. http://dx.doi.org/10.5194/amtd-7-1059-2014.

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Abstract. We present measurements acquired by the world's first airborne multiwavelength High Spectral Resolution Lidar (HSRL-2), developed by NASA Langley Research Center. The instrument was operated during Phase 1 of the Department of Energy (DOE) Two-Column Aerosol Project (TCAP)in July 2012. We observed pollution outflow from the northeast coast of the US out over the West Atlantic Ocean. Lidar ratios were 50–60 sr at 355 nm and 60–70 sr at 532 nm. Extinction-related Ångström exponents were on average 1.2–1.7 indicating comparably small particles. Our novel automated, unsupervised data inversion algorithm retrieves particle effective radii of approximately 0.2 μm, which is in agreement with the large Ångström exponents. We find good agreement with particle size parameters obtained from coincident in situ measurements carried out with the DOE Gulfstream-1 aircraft.

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Perrone, M. R., P. Burlizzi, F. De Tomasi, and A. Chaikovsky. "Profiling of fine- and coarse-mode particles with LIRIC (LIdar/Radiometer Inversion Code)." Atmospheric Measurement Techniques Discussions 7, no. 8 (August 27, 2014): 8881–926. http://dx.doi.org/10.5194/amtd-7-8881-2014.

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Abstract. The paper investigates numerical procedures that allow determining the dependence on altitude of aerosol properties from multi wavelength elastic lidar signals. In particular, the potential of the LIdar/Radiometer Inversion Code (LIRIC) to retrieve the vertical profiles of fine and coarse-mode particles by combining 3-wavelength lidar measurements and collocated AERONET (AErosol RObotic NETwork) sun/sky photometer measurements is investigated. The used lidar signals are at 355, 532 and 1064 nm. Aerosol extinction coefficient (αL), lidar ratio (LRL), and Ångstrom exponent (ÅL) profiles from LIRIC are compared with the corresponding profiles (α, LR, and Å) retrieved from a Constrained Iterative Inversion (CII) procedure to investigate the LIRIC retrieval ability. Then, an aerosol classification framework which relies on the use of a graphical framework and on the combined analysis of the Ångstrom exponent (at the 355 and 1064 nm wavelength pair, Å(355, 1064)) and its spectral curvature (ΔÅ = Å(355, 532)–Å(532, 1064)) is used to investigate the ability of LIRIC to retrieve vertical profiles of fine and coarse-mode particles. The Å-ΔÅ aerosol classification framework allows estimating the dependence on altitude of the aerosol fine modal radius and of the fine mode contribution to the whole aerosol optical thickness, as discussed in Perrone et al. (2014). The application of LIRIC to three different aerosol scenarios dealing with aerosol properties dependent on altitude has revealed that the differences between αL and α vary with the altitude and on average increase with the decrease of the lidar signal wavelength. It has also been found that the differences between ÅL and corresponding Å values vary with the altitude and the wavelength pair. The sensitivity of Ångstrom exponents to the aerosol size distribution which vary with the wavelength pair was responsible for these last results. The aerosol classification framework has revealed that the deviations between LIRIC and the corresponding CII-procedure retrieval products are due to the fact that LIRIC does not allow to the modal radius of fine mode particles to vary with the altitude. It is shown that this represents the main source of uncertainties in LIRIC results. The plot on the graphical framework of the Å-ΔÅ data points retrieved from the CII-procedure has indicated that the fine-mode-particle modal radius can vary with altitude when particles from different sources and/or from different advection routes contribute to the aerosol load. Analytical back trajectories combined with linear particle depolarization ratio profiles from lidar measurements at 355 nm and dust concentrations from the Barcelona Supercomputing Center-Dust REgional Atmospheric Model (BSC-DREAM) have been used to demonstrate the dependence on altitude of the aerosol properties.

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Thompson, David R., Brian H. Kahn, Philip G. Brodrick, Matthew D. Lebsock, Mark Richardson, and Robert O. Green. "Spectroscopic imaging of sub-kilometer spatial structure in lower-tropospheric water vapor." Atmospheric Measurement Techniques 14, no. 4 (April 12, 2021): 2827–40. http://dx.doi.org/10.5194/amt-14-2827-2021.

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Abstract. The subgrid spatial variability of water vapor is an important geophysical parameter for modeling tropical convention and cloud processes in atmospheric models. This study maps sub-kilometer spatial structures in total atmospheric column water vapor with visible to shortwave infrared (VSWIR) imaging spectroscopy. We describe our inversion approach and validate its accuracy with coincident measurements by airborne imaging spectrometers and the AERONET ground-based observation network. Next, data from NASA's AVIRIS-NG spectrometer enable the highest-resolution measurement to date of water vapor's spatial variability and scaling properties. We find second-order structure function scaling exponents consistent with prior studies of convective atmospheres. Airborne lidar data show that this total column measurement provides information about variability in the lower troposphere. We conclude by discussing the implications of these measurements and paths toward future campaigns to build upon these results.

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Liang, Bingyang, Chen Qiu, Feng Han, Chunhui Zhu, Na Liu, Hai Liu, Fubo Liu, Guangyou Fang, and Qing Huo Liu. "A New Inversion Method Based on Distorted Born Iterative Method for Grounded Electrical Source Airborne Transient Electromagnetics." IEEE Transactions on Geoscience and Remote Sensing 56, no. 2 (February 2018): 877–87. http://dx.doi.org/10.1109/tgrs.2017.2756086.

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PANG, Yong, and Zeng-Yuan LI. "Inversion of biomass components of the temperate forest using airborne Lidar technology in Xiaoxing’an Mountains, Northeastern of China." Chinese Journal of Plant Ecology 36, no. 10 (January 28, 2013): 1095–105. http://dx.doi.org/10.3724/sp.j.1258.2012.01095.

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Rahn, David A., Thomas R. Parish, and David Leon. "Airborne Measurements of Coastal Jet Transition around Point Conception, California." Monthly Weather Review 141, no. 11 (October 25, 2013): 3827–39. http://dx.doi.org/10.1175/mwr-d-13-00030.1.

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Abstract Low-level winds along the Californian coast during spring and early summer are typically strong and contained within the cool, well-mixed marine boundary layer (MBL). A temperature inversion separates the MBL from the warmer free troposphere. This setup is often represented by a two-layer shallow-water system with a lateral boundary. Near a prominent point such as Point Conception, California, the fast-moving MBL flow is supercritical and can exhibit distinct features including a compression bulge and an expansion fan. Measurements from the University of Wyoming King Air research aircraft on 19 May 2012 during the Precision Atmospheric MBL Experiment (PreAMBLE) captured wind in excess of 14 m s−1 off of Point Conception under clear skies and wind ~2 m s−1 east of San Miguel in the California Bight. A compression bulge was identified upwind of Point Conception. When the flow rounds the point, the MBL undergoes a near collapse and there is a spike in MBL height embedded in the general decrease of MBL height with greater turbulence just downwind that is associated with greater mixing through the inversion layer. Lidar and in situ measurements reveal that transport of continental aerosol is present near the pronounced MBL height change and that there is a complex vertical structure within the Santa Barbara Channel. Horizontal pressure gradients are obtained by measuring the slope of an isobaric surface. Observations of wind and pressure perturbations are able to be linked through a simple Bernoulli relationship. Variation of MBL depth explains most, but not all of the variation of the isobaric surface.

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Wen, Z., L. Zhao, W. Zhang, E. Chen, and K. Xu. "THE EFFECTS OF COHERENCE CALCULATION ON FOREST HEIGHT ESTIMATION USING SINC MODEL." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B1-2020 (August 6, 2020): 637–42. http://dx.doi.org/10.5194/isprs-archives-xliii-b1-2020-637-2020.

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Abstract. In this paper, the effects of coherence on forest height estimation by SINC model based on Tandem-X InSAR data were explored. First, different coherence calculation methods and different window sizes were used to obtain interferometric coherence images. Then, the forest heights were obtained based on SINC model. Finally, the estimated forest heights were validated against reference data from airborne LIDAR CHM (Canopy height model, CHM). The results showed that the coherence calculation algorithm affect the forest height inversion results with SINC model. The algorithm using only phase information for coherence calculation show better performance than the other one using both magnitude and phase information. Meanwhile, window size selecting for coherence calculation also affect the forest height estimation results. In this study, window size with 9 × 9 shows best agreement with the forest height extracted from LiDAR CHM. The R2 and RMSE are 0.656 and 3.54 m, respectively.

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Fournier, Dominique, Lindsey J. Heagy, and Douglas W. Oldenburg. "Sparse magnetic vector inversion in spherical coordinates." GEOPHYSICS 85, no. 3 (May 1, 2020): J33—J49. http://dx.doi.org/10.1190/geo2019-0244.1.

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Magnetic vector inversion (MVI) has received considerable attention over recent years for processing magnetic field data that are affected by remanent magnetization. However, the magnetization models obtained with current inversion algorithms are generally too smooth to be easily interpreted geologically. To address this, we have reviewed the MVI formulated in a spherical coordinate system. We tackle convergence issues posed by the nonlinear transformation from Cartesian to spherical coordinates by using an iterative sensitivity weighting approach and a scaling of the spherical parameters. The spherical formulation allows us to impose sparsity assumptions on the magnitude and direction of magnetization independently and, as a result, the inversion recovers simpler and more coherent magnetization orientations. The numerical implementation of our algorithm on large-scale problems is facilitated by discretizing the forward problem using tiled octree meshes. All of our results are generated using the open-source SimPEG software. We determine the enhanced capabilities of our algorithm on a large airborne magnetic survey collected over the Kevitsa Ni-Cu-platinum group elements (PGE) deposit. The recovered magnetization direction inside the ultramafic intrusion and in the host stratigraphy is consistent with laboratory measurements and provides evidence for tectonic deformation.

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Mereu, Luigi, Simona Scollo, Antonella Boselli, Giuseppe Leto, Ricardo Zanmar Sanchez, Costanza Bonadonna, and Frank Silvio Marzano. "Dual-Wavelength Polarimetric Lidar Observations of the Volcanic Ash Cloud Produced during the 2016 Etna Eruption." Remote Sensing 13, no. 9 (April 29, 2021): 1728. http://dx.doi.org/10.3390/rs13091728.

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Lidar observations are very useful to analyse dispersed volcanic clouds in the troposphere mainly because of their high range resolution, providing morphological as well as microphysical (size and mass) properties. In this work, we analyse the volcanic cloud of 18 May 2016 at Mt. Etna, in Italy, retrieved by polarimetric dual-wavelength Lidar measurements. We use the AMPLE (Aerosol Multi-Wavelength Polarization Lidar Experiment) system, located in Catania, about 25 km from the Etna summit craters, pointing at a thin volcanic cloud layer, clearly visible and dispersed from the summit craters at the altitude between 2 and 4 km and 6 and 7 km above the sea level. Both the backscattering and linear depolarization profiles at 355 nm (UV, ultraviolet) and 532 nm (VIS, visible) wavelengths, respectively, were obtained using different angles at 20°, 30°, 40° and 90°. The proposed approach inverts the Lidar measurements with a physically based inversion methodology named Volcanic Ash Lidar Retrieval (VALR), based on Maximum-Likelihood (ML). VALRML can provide estimates of volcanic ash mean size and mass concentration at a resolution of few tens of meters. We also compared those results with two methods: Single-variate Regression (SR) and Multi-variate Regression (MR). SR uses the backscattering coefficient or backscattering and depolarization coefficients of one wavelength (UV or VIS in our cases). The MR method uses the backscattering coefficient of both wavelengths (UV and VIS). In absence of in situ airborne validation data, the discrepancy among the different retrieval techniques is estimated with respect to the VALR ML algorithm. The VALR ML analysis provides ash concentrations between about 0.1 μg/m3 and 1 mg/m3 and particle mean sizes of 0.1 μm and 6 μm, respectively. Results show that, for the SR method differences are less than <10%, using the backscattering coefficient only and backscattering and depolarization coefficients. Moreover, we find differences of 20–30% respect to VALR ML, considering well-known parametric retrieval methods. VALR algorithms show how a physics-based inversion approaches can effectively exploit the spectral-polarimetric Lidar AMPLE capability.

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Müller, D., C. A. Hostetler, R. A. Ferrare, S. P. Burton, E. Chemyakin, A. Kolgotin, J. W. Hair, et al. "Airborne Multiwavelength High Spectral Resolution Lidar (HSRL-2) observations during TCAP 2012: vertical profiles of optical and microphysical properties of a smoke/urban haze plume over the northeastern coast of the US." Atmospheric Measurement Techniques 7, no. 10 (October 10, 2014): 3487–96. http://dx.doi.org/10.5194/amt-7-3487-2014.

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Abstract. We present measurements acquired by the world's first airborne 3 backscatter (β) + 2 extinction (α) High Spectral Resolution Lidar (HSRL-2). HSRL-2 measures particle backscatter coefficients at 355, 532, and 1064 nm, and particle extinction coefficients at 355 and 532 nm. The instrument has been developed by the NASA Langley Research Center. The instrument was operated during Phase 1 of the Department of Energy (DOE) Two-Column Aerosol Project (TCAP) in July 2012. We observed pollution outflow from the northeastern coast of the US out over the western Atlantic Ocean. Lidar ratios were 50–60 sr at 355 nm and 60–70 sr at 532 nm. Extinction-related Ångström exponents were on average 1.2–1.7, indicating comparably small particles. Our novel automated, unsupervised data inversion algorithm retrieved particle effective radii of approximately 0.2 μm, which is in agreement with the large Ångström exponents. We find good agreement with particle size parameters obtained from coincident in situ measurements carried out with the DOE Gulfstream-1 aircraft.

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