Journal articles on the topic 'Scattering Remote sensing systems'
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1
Zhu, Zhiqin, Yaqin Luo, Hongyan Wei, Yong Li, Guanqiu Qi, Neal Mazur, Yuanyuan Li, and Penglong Li. "Atmospheric Light Estimation Based Remote Sensing Image Dehazing." Remote Sensing 13, no. 13 (June 22, 2021): 2432. http://dx.doi.org/10.3390/rs13132432.
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Remote sensing images are widely used in object detection and tracking, military security, and other computer vision tasks. However, remote sensing images are often degraded by suspended aerosol in the air, especially under poor weather conditions, such as fog, haze, and mist. The quality of remote sensing images directly affect the normal operations of computer vision systems. As such, haze removal is a crucial and indispensable pre-processing step in remote sensing image processing. Additionally, most of the existing image dehazing methods are not applicable to all scenes, so the corresponding dehazed images may have varying degrees of color distortion. This paper proposes a novel atmospheric light estimation based dehazing algorithm to obtain high visual-quality remote sensing images. First, a differentiable function is used to train the parameters of a linear scene depth model for the scene depth map generation of remote sensing images. Second, the atmospheric light of each hazy remote sensing image is estimated by the corresponding scene depth map. Then, the corresponding transmission map is estimated on the basis of the estimated atmospheric light by a haze-lines model. Finally, according to the estimated atmospheric light and transmission map, an atmospheric scattering model is applied to remove haze from remote sensing images. The colors of the images dehazed by the proposed method are in line with the perception of human eyes in different scenes. A dataset with 100 remote sensing images from hazy scenes was built for testing. The performance of the proposed image dehazing method is confirmed by theoretical analysis and comparative experiments.
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Kuznecov, A. Yu, A. A. Sadikova, V. I. Gornyj, and I. Sh Latypov. "DEVELOPMENT OF A METHOD FOR SYNTHESIZING AN APERTURE DIAPHRAGM IN HYPERSPECTRAL REMOTE SENSING SYSTEMS FOR EARTH." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 191 (May 2020): 23–30. http://dx.doi.org/10.14489/vkit.2020.05.pp.023-030.
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The aim of the work is to research and develop methods for synthesizing aperture in hyperspectral systems for remote sensing of the Earth to reduce weight and size characteristics by applying methods of program-algorithmic processing of the input signal and implementing the synthesized aperture. A method of neural networks for deconvolution on the construction of a radial basis network is developed. A method has been developed to increase the synthesis of apertures in hyperspectral systems for remote sensing of the Earth. A method for increasing the spatial resolution of images obtained by optical systems for remote sensing of the Earth is described. A method for radiometric calibration of output data has been developed, which allows universalizing the analysis of spectral characteristics. In the process, to achieve the goals were used: methods of spectral optics, mathematical analysis and statistics, methods of processing images and signals. The project results contribute to the reduction of overall weight and cost characteristics and the possibility of synthesizing the aperture at the exit of the polychromator, which will avoid the use of expensive camera lenses in hyperspectral systems of remote sensing of the Earth. The developed methods for synthesizing aperture in hyperspectral systems of remote sensing of the Earth differ from the existing ones in that the receiving device for the video signal does not contain structural changes, and they contain the function of the algorithmic apparatus, which includes the analysis of the functions of the scattering point, the deconvolution of the recorded signal is performed by the method of neural networks after the stage learning.
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Kuznecov, A. Yu, A. A. Sadikova, V. I. Gornyj, and I. Sh Latypov. "DEVELOPMENT OF A METHOD FOR SYNTHESIZING AN APERTURE DIAPHRAGM IN HYPERSPECTRAL REMOTE SENSING SYSTEMS FOR EARTH." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 191 (May 2020): 23–30. http://dx.doi.org/10.14489/vkit.2020.05.pp.023-030.
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The aim of the work is to research and develop methods for synthesizing aperture in hyperspectral systems for remote sensing of the Earth to reduce weight and size characteristics by applying methods of program-algorithmic processing of the input signal and implementing the synthesized aperture. A method of neural networks for deconvolution on the construction of a radial basis network is developed. A method has been developed to increase the synthesis of apertures in hyperspectral systems for remote sensing of the Earth. A method for increasing the spatial resolution of images obtained by optical systems for remote sensing of the Earth is described. A method for radiometric calibration of output data has been developed, which allows universalizing the analysis of spectral characteristics. In the process, to achieve the goals were used: methods of spectral optics, mathematical analysis and statistics, methods of processing images and signals. The project results contribute to the reduction of overall weight and cost characteristics and the possibility of synthesizing the aperture at the exit of the polychromator, which will avoid the use of expensive camera lenses in hyperspectral systems of remote sensing of the Earth. The developed methods for synthesizing aperture in hyperspectral systems of remote sensing of the Earth differ from the existing ones in that the receiving device for the video signal does not contain structural changes, and they contain the function of the algorithmic apparatus, which includes the analysis of the functions of the scattering point, the deconvolution of the recorded signal is performed by the method of neural networks after the stage learning.
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Bala, Jeevan, and Kamlesh Lakhwani. "Performance evaluation of various desmogging techniques for single smoggy images." Modern Physics Letters B 33, no. 05 (February 20, 2019): 1950056. http://dx.doi.org/10.1142/s0217984919500568.
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The worsening air pollution is producing serious smog problems in the world. The high concentration of aerosol, that attenuates the scene radiance and adds undesired scattering illumination into the actual illumination values, has a serious effect on the visibility of the images. Therefore, images captured under smoggy environments suffer from poor visibility. Because, the smog particles attenuate the illumination reflected by the targets and add undesired scattering light. Therefore, imaging under smoggy environments affect the performance of many machine vision systems such as intelligent transportation system, remote sensing imaging, aerial imaging, etc. From the literature, it has been observed that majority of existing researchers have either focused on foggy or hazy images only.
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Böttger, U., and R. Preusker. "Radiative transfer model STORM for full Stokes vector calculations in the visible and near infrared spectral range." Advances in Radio Science 4 (September 6, 2006): 329–35. http://dx.doi.org/10.5194/ars-4-329-2006.
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Abstract. Based on the Matrix-Operator Method the radiative transfer code STORM (STOkes vector Radiative transfer Model) is introduced, which was developed in a joint project of DLR and Institut f{ü}r Weltraumwissenschaften-Freie Universität Berlin. STORM calculates the Stokes parameters (I, Q, U, V) in a plane parallel, multi layered atmosphere in the visible and near infrared spectral range. The scattering characteristics of aerosols are determined by Mie theory. The surface represents a Lambertian reflector or a wind ruffled water surface described by Cox-Munk model. The results of one calculation are the upward and downward directed Stokes parameters for one wavelength at a desired number of sun incident and viewing angles at varying altitudes in the principal plane and other azimuth angles. STORM is applied for an analysis in view of designing downward looking Earth observing optical remote sensing systems and values of the degree of polarization are presented as generic basis for remote sensing system design and data processing.
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Nurtyawan, Rian, Asep Saepuloh, Agung Budi Harto, Ketut Wikantika, and Akihiko Kondoh. "Satellite Imagery for Classification of Rice Growth Phase Using Freeman Decomposition in Indramayu, West Java, Indonesia." HAYATI Journal of Biosciences 25, no. 3 (October 24, 2018): 126. http://dx.doi.org/10.4308/hjb.25.3.126.
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Monitoring at every growth of rice plants is an important information for determining the grain pro-duction estimation of rice. Monitoring must to be have timely work on the rice plant development. However, timely monitoring and the high accuracy of information is a challenge in remote sensing based on rice agriculture monitoring and observation. With increased quality of synthetic aperture radar (SAR) systems utilizing polarimetric information recently, the development and applications of polarimetric SAR (PolSAR) are one of the current major topics in radar remote sensing. The ad-vantages provided by PolSAR data for agricultural monitoring have been extensively studied for applications such as crop type classification and mapping, crop phenology monitoring, productivity assessment based on the sensitivity of polarimetric parameters to indicators of crop conditions. Freeman and Durden successfully decomposed fully PolSAR data into three components: Single bounce, double bounce, and volume scattering. The three-component scattering provide features for distinguishing between different surface cover types. These sensitivities assist in the identification of growing phase. The observed growing phase development in time series, reflected in the consistent temporal trends in scattering, was generally in agreement with crop phenological development stages. Supervised classification was performed on repeat-pass Radarsat-2 images, with an overall classification accuracy of 77.27% achieved using time series Fine beam data. The study demonstrated that Radarsat-2 Fine mode data provide useful information for crop monitoring and classification of rice plants.
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Williams, John K., and J. Vivekanandan. "Sources of Error in Dual-Wavelength Radar Remote Sensing of Cloud Liquid Water Content." Journal of Atmospheric and Oceanic Technology 24, no. 8 (August 1, 2007): 1317–36. http://dx.doi.org/10.1175/jtech2042.1.
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Abstract Dual-wavelength ratio (DWR) techniques offer the prospect of producing high-resolution mapping of cloud microphysical properties, including retrievals of cloud liquid water content (LWC) from reflectivity measured by millimeter-wavelength radars. Unfortunately, noise and artifacts in the DWR require smoothing to obtain physically realistic values of LWC with a concomitant loss of resolution. Factors that cause inaccuracy in the retrieved LWC include uncertainty in gas and liquid water attenuation coefficients, Mie scattering due to large water droplets or ice particles, corruption of the radar reflectivities by noise and nonatmospheric returns, and artifacts due to mismatched radar illumination volumes. The error analysis presented here consists of both analytic and heuristic arguments; it is illustrated using data from the Mount Washington Icing Sensors Project (MWISP) and from an idealized simulation. In addition to offering insight into design considerations for a DWR system, some results suggest methods that may mitigate some of these sources of error for existing systems and datasets.
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Li, Ying. "Monitoring and Mathematical Model Analysis of Dynamic Changes in Land Resources Based on SAR Sensor Image." Journal of Sensors 2021 (September 9, 2021): 1–12. http://dx.doi.org/10.1155/2021/1661825.
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The monitoring and analysis of dynamic changes in land resources can detect the changes of land aimed at a single-band or multiband remote sensing image of multiple phases in a given region or target with image processing methods and can also extract the change information and realize remote sensing monitoring through the comprehensive analysis of multiphase remote sensing images. Synthetic aperture radar (SAR) image change monitoring technology, with the advantages of high resolution, high precision, real-time service, and rapid imaging, can achieve qualitative or quantitative analysis of targets and is gradually widely used in quarterly monitoring, emergency monitoring, postbatch verification, law-enforcement inspection and land inspection, and other remote sensing data acquisitions and analyses. Therefore, on the basis of summarizing the research results of previous research works, this paper expounded the current situation and significance of the researches on the monitoring and analysis of dynamic changes in land resources; elaborated the development background, current situation, and future challenges of SAR sensor data; introduced the methods and principles of band setting, polarization mode, geometric correction, and image filtering; proposed the status target identification of land resources; explored the dynamic information discovery of land resources; conducted the dynamic change monitoring of land resources based on SAR sensor data; analyzed the basis and characteristics of SAR sensor data; performed the generalization and optimization of land resource information; demonstrated the dynamic change analysis of land resources based on SAR sensor data; compared the acceptance ability and accuracy of SAR sensor data; and discussed the discovery and extraction of dynamic information of land resources. The results show that the SAR sensor data can monitor the characteristics of scattering points in land resource observation scenes and can obtain the change information of ground object by distance component and band component, so that the SAR system can make two-dimensional imaging of land resources directly in front of the receiving platform. Thus, the SAR data obtained by multisystem parameters shows great application potential in land resource monitoring, which provides the possibility of decoupling to remove land resources and surface roughness and thus provides possible solutions for land resource analysis in complex environment. The results of this paper provide a reference for the follow-up studies on the monitoring and analysis of dynamic changes in land resources based on SAR sensor data.
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Thompson, Jonathan V., Brett H. Hokr, Wihan Kim, Charles W. Ballmann, Brian E. Applegate, Javier Jo, Alexey Yamilov, Hui Cao, Marlan O. Scully, and Vladislav V. Yakovlev. "Enhanced coupling of light into a turbid medium through microscopic interface engineering." Proceedings of the National Academy of Sciences 114, no. 30 (July 12, 2017): 7941–46. http://dx.doi.org/10.1073/pnas.1705612114.
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There are many optical detection and sensing methods used today that provide powerful ways to diagnose, characterize, and study materials. For example, the measurement of spontaneous Raman scattering allows for remote detection and identification of chemicals. Many other optical techniques provide unique solutions to learn about biological, chemical, and even structural systems. However, when these systems exist in a highly scattering or turbid medium, the optical scattering effects reduce the effectiveness of these methods. In this article, we demonstrate a method to engineer the geometry of the optical interface of a turbid medium, thereby drastically enhancing the coupling efficiency of light into the material. This enhanced optical coupling means that light incident on the material will penetrate deeper into (and through) the medium. It also means that light thus injected into the material will have an enhanced interaction time with particles contained within the material. These results show that, by using the multiple scattering of light in a turbid medium, enhanced light–matter interaction can be achieved; this has a direct impact on spectroscopic methods such as Raman scattering and fluorescence detection in highly scattering regimes. Furthermore, the enhanced penetration depth achieved by this method will directly impact optical techniques that have previously been limited by the inability to deposit sufficient amounts of optical energy below or through highly scattering layers.
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Bebbington, D. H. O., L. Carrea, and G. Wanielik. "Application of Geometric Polarization to Invariance Properties in Bistatic Scattering." Advances in Radio Science 3 (May 13, 2005): 421–25. http://dx.doi.org/10.5194/ars-3-421-2005.
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Abstract. Bistatic polarimetric radars provide target properties which just one monostatic system can not reveal. Moreover, augmentation of monostatic systems through the provision of bistatic receive-only stations can be a cheap way to increase the amount of remote sensing data. However, bistatic scattering needs to be investigated in order to properly define target properties such as symmetries and invariance, especially regarding choices of polarization basis. In this paper we discuss how the geometric theory of polarization, in which the geometry of the Poincaré sphere is directly related to 3-D geometry of space rather than the 2-D geometry of the wavefront plane, can be used to reduce the ambiguities in the interpretation of data. We also show how in the coherent case a complex scalar invariant can be determined irrespective of the basis combinations.
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Sawamura, P., D. Müller, R. M. Hoff, C. A. Hostetler, R. A. Ferrare, J. W. Hair, R. R. Rogers, et al. "Aerosol optical and microphysical retrievals from a hybrid multiwavelength lidar data set – DISCOVER-AQ 2011." Atmospheric Measurement Techniques 7, no. 9 (September 24, 2014): 3095–112. http://dx.doi.org/10.5194/amt-7-3095-2014.
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Abstract. Retrievals of aerosol microphysical properties (effective radius, volume and surface-area concentrations) and aerosol optical properties (complex index of refraction and single-scattering albedo) were obtained from a hybrid multiwavelength lidar data set for the first time. In July 2011, in the Baltimore–Washington DC region, synergistic profiling of optical and microphysical properties of aerosols with both airborne (in situ and remote sensing) and ground-based remote sensing systems was performed during the first deployment of DISCOVER-AQ. The hybrid multiwavelength lidar data set combines ground-based elastic backscatter lidar measurements at 355 nm with airborne High-Spectral-Resolution Lidar (HSRL) measurements at 532 nm and elastic backscatter lidar measurements at 1064 nm that were obtained less than 5 km apart from each other. This was the first study in which optical and microphysical retrievals from lidar were obtained during the day and directly compared to AERONET and in situ measurements for 11 cases. Good agreement was observed between lidar and AERONET retrievals. Larger discrepancies were observed between lidar retrievals and in situ measurements obtained by the aircraft and aerosol hygroscopic effects are believed to be the main factor in such discrepancies.
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Gharechelou, Saeid, Ryutaro Tateishi, and Brian A. Johnson. "A Simple Method for the Parameterization of Surface Roughness from Microwave Remote Sensing." Remote Sensing 10, no. 11 (October 30, 2018): 1711. http://dx.doi.org/10.3390/rs10111711.
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Generally, the characterization of land surface roughness is obtained from the analysis of height variations observed along transects (e.g., root mean square (RMS) height, correlation length, and autocorrelation function). These surface roughness measurements are then used as inputs for surface dynamics modeling, e.g., for soil erosion modeling, runoff estimation, and microwave remote sensing scattering modeling and calibration. In the past, researchers have suggested various methods for estimating roughness parameters based on ground measurements, e.g., using a pin profilometer, but these methods require physical contact with the land and can be time-consuming to conduct. The target of this research is to develop a technique for deriving surface roughness characteristics from digital camera images by applying photogrammetric and geographical information systems (GIS) analysis techniques. First, ground photos acquired by a digital camera in the field were used to create a point cloud and 3D digital terrain model (DTM). Then, the DTM was imported to a GIS environment to calculate the surface roughness parameter for each field site. The results of the roughness derivation can be integrated with soil moisture for backscattering simulation, e.g., for inversion modeling to retrieve the backscattering coefficient. The results show that the proposed method has a high potential for retrieving surface roughness parameters in a time- and cost-efficient manner. The selection of homogeneous fields and the increased spatial distribution of sites in the study area will show a better result for microwave backscattering modeling.
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Roy, Richard J., Matthew Lebsock, Luis Millán, and Ken B. Cooper. "Validation of a G-Band Differential Absorption Cloud Radar for Humidity Remote Sensing." Journal of Atmospheric and Oceanic Technology 37, no. 6 (June 1, 2020): 1085–102. http://dx.doi.org/10.1175/jtech-d-19-0122.1.
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AbstractDifferential absorption radar (DAR) offers an active remote sensing solution to the problem of measuring humidity profiles with high vertical and horizontal resolution in hydrometeor layers. The Vapor In-Cloud Profiling Radar (VIPR) is a frequency-modulated continuous-wave (FMCW) G-band DAR tunable from 167 to 174.8 GHz being developed at the Jet Propulsion Laboratory (JPL). Here we describe ground-based measurements from VIPR performed at the Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) site for humidity product validation. Two distinct measurement capabilities are investigated: 1) humidity profiles inside of cloudy volumes with 180 m vertical resolution, and 2) integrated water vapor (IWV) between the surface and cloud base. High radar sensitivity permits detection of upper-tropospheric clouds and retrieval of humidity profiles above 10 km in height. We develop an improved humidity retrieval algorithm based on a regularized least squares method that includes detailed accounting of measurement covariances and systematic error sources. This regularization mitigates high-spatial-frequency humidity biases that arise from frequency-dependent hydrometeor scattering, which is an important limitation for DAR systems. Through comparisons with over 20 coincident radiosondes, we find close agreement between in situ and remotely sensed humidity profiles, with a correlation coefficient of r = 0.96, root-mean-square error (RMSE) of 0.8 g m−3, and median retrieval precision of 0.5 g m−3. Using a merged radiosonde and Raman lidar product for surface-to-cloud-base IWV, we demonstrate precise column sounding capabilities with r = 1.00, RMSE of 1.2 mm, and median retrieval precision of 0.25 mm.
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Deems, Jeffrey S., Thomas H. Painter, and David C. Finnegan. "Lidar measurement of snow depth: a review." Journal of Glaciology 59, no. 215 (2013): 467–79. http://dx.doi.org/10.3189/2013jog12j154.
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AbstractLaser altimetry (lidar) is a remote-sensing technology that holds tremendous promise for mapping snow depth in snow hydrology and avalanche applications. Recently lidar has seen a dramatic widening of applications in the natural sciences, resulting in technological improvements and an increase in the availability of both airborne and ground-based sensors. Modern sensors allow mapping of vegetation heights and snow or ground surface elevations below forest canopies. Typical vertical accuracies for airborne datasets are decimeter-scale with order 1 m point spacings. Ground-based systems typically provide millimeter-scale range accuracy and sub-meter point spacing over 1 m to several kilometers. Many system parameters, such as scan angle, pulse rate and shot geometry relative to terrain gradients, require specification to achieve specific point coverage densities in forested and/or complex terrain. Additionally, snow has a significant volumetric scattering component, requiring different considerations for error estimation than for other Earth surface materials. We use published estimates of light penetration depth by wavelength to estimate radiative transfer error contributions. This paper presents a review of lidar mapping procedures and error sources, potential errors unique to snow surface remote sensing in the near-infrared and visible wavelengths, and recommendations for projects using lidar for snow-depth mapping.
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Lyons, Anthony P., Derek R. Olson, and Roy E. Hansen. "Modeling the effect of random roughness on synthetic aperture sonar image statistics." Journal of the Acoustical Society of America 152, no. 3 (September 2022): 1363–74. http://dx.doi.org/10.1121/10.0013837.
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A model has been developed to predict the effect of random seafloor roughness on synthetic aperture sonar (SAS) image statistics, based on the composite roughness approximation–a physical scattering model. The continuous variation in scattering strength produced by a random slope field is treated as an intensity scaling on the image speckle produced by the coherent SAS imaging process. Changes in image statistics caused by roughness are quantified in terms of the scintillation index (SI). Factors influencing the SI include the seafloor slope variance, geo-acoustic properties of the seafloor, the probability density function describing the speckle, and the signal-to-noise ratio. Example model-data comparisons are shown for SAS images taken at three different sites using three different high-frequency SAS systems. Agreement between the modeled and measured SI show that it is possible to link range-dependent image statistics to measurable geo-acoustic properties, providing the foundation necessary for solving problems related to the detection of targets using high-frequency imaging sonars, including performance prediction or adaptation of automated detection algorithms. Additionally, this work illustrates the possible use of SAS systems for remote sensing of roughness parameters such as root mean square slope or height.
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Sabery, Shahrzad Minooee, Aleksandr Bystrov, Miguel Navarro-Cía, Peter Gardner, and Marina Gashinova. "Study of Low Terahertz Radar Signal Backscattering for Surface Identification." Sensors 21, no. 9 (April 23, 2021): 2954. http://dx.doi.org/10.3390/s21092954.
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This study explores the scattering of signals within the mm and low Terahertz frequency range, represented by frequencies 79 GHz, 150 GHz, 300 GHz, and 670 GHz, from surfaces with different roughness, to demonstrate advantages of low THz radar for surface discrimination for automotive sensing. The responses of four test surfaces of different roughness were measured and their normalized radar cross sections were estimated as a function of grazing angle and polarization. The Fraunhofer criterion was used as a guideline for determining the type of backscattering (specular and diffuse). The proposed experimental technique provides high accuracy of backscattering coefficient measurement depending on the frequency of the signal, polarization, and grazing angle. An empirical scattering model was used to provide a reference. To compare theoretical and experimental results of the signal scattering on test surfaces, the permittivity of sandpaper has been measured using time-domain spectroscopy. It was shown that the empirical methods for diffuse radar signal scattering developed for lower radar frequencies can be extended for the low THz range with sufficient accuracy. The results obtained will provide reference information for creating remote surface identification systems for automotive use, which will be of particular advantage in surface classification, object classification, and path determination in autonomous automotive vehicle operation.
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Kulie, Mark S., Michael J. Hiley, Ralf Bennartz, Stefan Kneifel, and Simone Tanelli. "Triple-Frequency Radar Reflectivity Signatures of Snow: Observations and Comparisons with Theoretical Ice Particle Scattering Models." Journal of Applied Meteorology and Climatology 53, no. 4 (April 2014): 1080–98. http://dx.doi.org/10.1175/jamc-d-13-066.1.
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AbstractAn observation-based study is presented that utilizes aircraft data from the 2003 Wakasa Bay Advanced Microwave Scanning Radiometer Precipitation Validation Campaign to assess recent advances in the modeling of microwave scattering properties of nonspherical ice particles in the atmosphere. Previous work has suggested that a triple-frequency (Ku–Ka–W band) reflectivity framework appears capable of identifying key microphysical properties of snow, potentially providing much-needed constraints on significant sources of uncertainty in current snowfall retrieval algorithms used for microwave remote sensing instruments. However, these results were based solely on a modeling framework. In contrast, this study considers the triple-frequency approach from an observational perspective using airborne radar observations from the Wakasa Bay field campaign. After accounting for several challenges with the observational dataset, such as beam mismatching and attenuation, observed dual-wavelength ratio results are presented that confirm both the utility of a multifrequency approach to snowfall retrieval and the validity of the unique signatures predicted by complex aggregate ice particle scattering models. This analysis provides valuable insight into the microphysics of frozen precipitation that can in turn be applied to more readily available single- and dual-frequency systems, providing guidance for future precipitation retrieval algorithms.
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Park, Sang-Eun, and Yoon Taek Jung. "Detection of Earthquake-Induced Building Damages Using Polarimetric SAR Data." Remote Sensing 12, no. 1 (January 1, 2020): 137. http://dx.doi.org/10.3390/rs12010137.
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Remote sensing, particularly using synthetic aperture radar (SAR) systems, can be an effective tool in detecting and assessing the area and amount of building damages caused by earthquake or tsunami. Several studies have provided experimental evidence for the importance of polarimetric SAR observations in building damage detection and assessment, particularly caused by a tsunami. This study aims to evaluate the practical applicability of the polarimetric SAR observations to building damage caused by the direct ground-shaking of an earthquake. The urban areas heavily damaged by the 2016 Kumamoto earthquake in Japan have been investigated by using the polarimetric PALSAR-2 data acquired in pre- and post-earthquake conditions. Several polarimetric change detection approaches, such as the changes of polarimetric scattering powers, the matrix dissimilarity measures, and changes of the radar scattering mechanisms, were examined. Optimal damage indicators in the presence of significant natural changes, and a novel change detection method by the fuzzy-based fusion of polarimetric damage indicators are proposed. The accuracy analysis results show that the proposed automatic classification method can successfully detect the selected damaged areas with a detection rate of 90.9% and false-alarm rate of 1.3%.
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Wu, Xuerui, Wenxiao Ma, Junming Xia, Weihua Bai, Shuanggen Jin, and Andrés Calabia. "Spaceborne GNSS-R Soil Moisture Retrieval: Status, Development Opportunities, and Challenges." Remote Sensing 13, no. 1 (December 24, 2020): 45. http://dx.doi.org/10.3390/rs13010045.
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Soil moisture is the most active part of the terrestrial water cycle, and it is a key variable that affects hydrological, bio-ecological, and bio-geochemical processes. Microwave remote sensing is an effective means of monitoring soil moisture, but the existing conventional radiometers and single-station radars cannot meet the scientific needs in terms of temporal and spatial resolution. The emergence of GNSS-R (Global Navigation Satellite Systems Reflectometry) technology provides an alternative method with high temporal and spatial resolution. An important application field of GNSS-R is soil moisture monitoring, but it is still in the initial stage of research, and there are many uncertainties and open issues. Based on a review of the current state-of-the-art of soil moisture retrieval using GNSS-R, this paper points out the limitations of existing research in observation geometry, polarization, and coherent and non-coherent scattering. The smooth surface reflectivity model, the random rough surface scattering model, and the first-order radiation transfer equation model of the vegetation, which are in the form of bistatic and full polarization, are employed. Simulations and analyses of polarization, observation geometry (scattering zenith angle and scattering azimuth angle), Brewster angle, coherent and non-coherent component, surface roughness, and vegetation effects are carried out. The influence of the EIRP (Effective Isotropic Radiated Power) and the RFI (Radio Frequency Interference) on soil moisture retrieval is briefly discussed. Several important development directions for space-borne GNSS-R soil moisture retrieval are pointed out in detail based on the microwave scattering model.
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Kern, C., F. Kick, P. Lübcke, L. Vogel, M. Wöhrbach, and U. Platt. "Theoretical description of functionality, applications, and limitations of SO<sub>2</sub> cameras for the remote sensing of volcanic plumes." Atmospheric Measurement Techniques Discussions 3, no. 1 (February 12, 2010): 531–78. http://dx.doi.org/10.5194/amtd-3-531-2010.
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Abstract. The SO2 camera is a novel technique for the remote sensing of volcanic emissions using solar radiation scattered in the atmosphere as a light source for the measurements. The method is based on measuring the ultra-violet absorption of SO2 in a narrow wavelength window around 310 nm by employing a band-pass interference filter and a 2-D UV-sensitive CCD detector. The effect of aerosol scattering can be eliminated by additionally measuring the incident radiation around 325 nm where the absorption of SO2 is no longer significant, thus rendering the method applicable to optically opaque plumes. The ability to deliver spatially resolved images of volcanic SO2 distributions at a frame rate on the order of 1 Hz makes the SO2 camera a very promising technique for volcanic monitoring and for studying the dynamics of volcanic plumes in the atmosphere. This study gives a theoretical basis for the pertinent aspects of working with SO2 camera systems, including the measurement principle, instrument design, data evaluation and technical applicability. Several issues are identified that influence camera calibration and performance. For one, changes in the solar zenith angle lead to a variable light path length in the stratospheric ozone layer and therefore change the spectral distribution of scattered solar radiation incident at the Earth's surface. The thus varying spectral illumination causes a shift in the calibration of the SO2 camera's results. Secondly, the lack of spectral resolution inherent in the measurement technique leads to a non-linear relationship between measured weighted average optical density and the SO2 column density. In addition, as is the case with all remote sensing techniques that use scattered solar radiation as a light source, the radiative transfer between the sun and the instrument is variable, with both radiative dilution as well as multiple scattering occurring. These effects can lead to both, over or underestimation of the SO2 column density by more than an order of magnitude. As the accurate assessment of volcanic emissions depends on our ability to correct for these issues, recommendations for correcting the individual effects during data analysis are given. Aside from the above mentioned intrinsic effects, the particular technical design of the SO2 camera can also greatly influence its performance, depending on the chosen setup. A general description of the instrument setup is given, and the advantages and disadvantages of certain specific instrument designs are discussed. Finally, several measurement examples are shown and possibilities to combine SO2 camera measurements with other remote sensing techniques are explored.
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Kern, C., F. Kick, P. Lübcke, L. Vogel, M. Wöhrbach, and U. Platt. "Theoretical description of functionality, applications, and limitations of SO<sub>2</sub> cameras for the remote sensing of volcanic plumes." Atmospheric Measurement Techniques 3, no. 3 (June 29, 2010): 733–49. http://dx.doi.org/10.5194/amt-3-733-2010.
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Abstract. The SO2 camera is a novel device for the remote sensing of volcanic emissions using solar radiation scattered in the atmosphere as a light source for the measurements. The method is based on measuring the ultra-violet absorption of SO2 in a narrow wavelength window around 310 nm by employing a band-pass interference filter and a 2 dimensional UV-sensitive CCD detector. The effect of aerosol scattering can in part be compensated by additionally measuring the incident radiation around 325 nm, where the absorption of SO2 is about 30 times weaker, thus rendering the method applicable to optically thin plumes. For plumes with high aerosol optical densities, collocation of an additional moderate resolution spectrometer is desirable to enable a correction of radiative transfer effects. The ability to deliver spatially resolved images of volcanic SO2 distributions at a frame rate on the order of 1 Hz makes the SO2 camera a very promising technique for volcanic monitoring and for studying the dynamics of volcanic plumes in the atmosphere. This study gives a theoretical basis for the pertinent aspects of working with SO2 camera systems, including the measurement principle, instrument design, data evaluation and technical applicability. Several issues are identified that influence camera calibration and performance. For one, changes in the solar zenith angle lead to a variable light path length in the stratospheric ozone layer and therefore change the spectral distribution of scattered solar radiation incident at the Earth's surface. The varying spectral illumination causes a shift in the calibration of the SO2 camera's results. Secondly, the lack of spectral resolution inherent in the measurement technique leads to a non-linear relationship between measured weighted average optical density and the SO2 column density. Thirdly, as is the case with all remote sensing techniques that use scattered solar radiation as a light source, the radiative transfer between the sun and the instrument is variable, with both "radiative dilution" as well as multiple scattering occurring. These effects can lead to both, over or underestimation of the SO2 column density by more than an order of magnitude. As the accurate assessment of volcanic emissions depends on our ability to correct for these issues, recommendations for correcting the individual effects during data analysis are given. Aside from the above mentioned intrinsic effects, the particular technical design of the SO2 camera can also greatly influence its performance, depending on the setup chosen. A general description of an instrument setup is given, and the advantages and disadvantages of certain specific instrument designs are discussed. Finally, several measurement examples are shown and possibilities to combine SO2 camera measurements with other remote sensing techniques are explored.
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Träumner, Katja, Jan Handwerker, Andreas Wieser, and Jens Grenzhäuser. "A Synergy Approach to Estimate Properties of Raindrop Size Distributions Using a Doppler Lidar and Cloud Radar." Journal of Atmospheric and Oceanic Technology 27, no. 6 (June 1, 2010): 1095–100. http://dx.doi.org/10.1175/2010jtecha1377.1.
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Abstract Remote sensing systems like radars and lidars are frequently used in atmospheric measurement campaigns. Because of their different wavelengths, they operate in different scattering regimes. Combined use may result in new measurement options. Here, an approach to estimate raindrop size distribution using vertical velocities measured by a lidar–radar combination is introduced and tested using a 2-μm Doppler lidar and a 35.5-GHz cloud radar. The lidar spectra are evaluated to deduce air motion from the aerosol peak and the fall velocity of the raindrops from the rain peak. The latter is weighted by the area (D2) of the scatters. The fall velocity derived from radar measurements is weighted by D6 (Rayleigh approximation). Assuming a size-dependent fall velocity and an analytical description of the drop size distribution, its parameters are calculated from these data. Comparison of the raindrop size distribution from the lidar–radar combination with in situ measurements on the ground yields satisfying results.
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Dateu, M., and K. Seidel. "Image information mining : exploration of Earth observation archives." Geographica Helvetica 58, no. 2 (June 30, 2003): 154–68. http://dx.doi.org/10.5194/gh-58-154-2003.
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Abstract. The new generation of high resolution imaging satellites acquires huge amounts of data which are stored in large archives. The state-of-the-art Systems for data access allow only queries by geographical location, time of acquisition or type of sensor. This information is often less important than the content of the scene, i.e. structures, objects or scattering properties. Meanwhile, many new applications of remote sensing data are closer to Computer vision and require the knowledge of complicated spatial and structural relationships among image objects. We are creating an intelligent satellite information mining system, a next generation architecture to help users to rapidly collect information, a tool to enhance and to manage the huge amount of historical and newly acquired satellite data-sets by giving experts access to relevant information in an understandable and directly usable form and to provide friendly interfaces for information query and browsing. Research topics are within the frame of Bayesian learning, content-based querying, data modelling and adaptation to user conjecture.
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Mukherjee, Lipi, Peng-Wang Zhai, Meng Gao, Yongxiang Hu, Bryan A. Franz, and P. Jeremy Werdell. "Neural Network Reflectance Prediction Model for Both Open Ocean and Coastal Waters." Remote Sensing 12, no. 9 (April 30, 2020): 1421. http://dx.doi.org/10.3390/rs12091421.
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Remote sensing of global ocean color is a valuable tool for understanding the ecology and biogeochemistry of the worlds oceans, and provides critical input to our knowledge of the global carbon cycle and the impacts of climate change. Ocean polarized reflectance contains information about the constituents of the upper ocean euphotic zone, such as colored dissolved organic matter (CDOM), sediments, phytoplankton, and pollutants. In order to retrieve the information on these constituents, remote sensing algorithms typically rely on radiative transfer models to interpret water color or remote-sensing reflectance; however, this can be resource-prohibitive for operational use due to the extensive CPU time involved in radiative transfer solutions. In this work, we report a fast model based on machine learning techniques, called Neural Network Reflectance Prediction Model (NNRPM), which can be used to predict ocean bidirectional polarized reflectance given inherent optical properties of ocean waters. This supervised model is trained using a large volume of data derived from radiative transfer simulations for coupled atmosphere and ocean systems using the successive order of scattering technique (SOS-CAOS). The performance of the model is validated against another large independent test dataset generated from SOS-CAOS. The model is able to predict both polarized and unpolarized reflectances with an absolute error (AE) less than 0.004 for 99% of test cases. We have also shown that the degree of linear polarization (DoLP) for unpolarized incident light can be predicted with an AE less than 0.002 for 99% of test cases. In general, the simulation time of SOS-CAOS depends on optical depth, and required accuracy. When comparing the average speeds of the NNRPM against the SOS-CAOS model for the same parameters, we see that the NNRPM is able to predict the Ocean BRDF 6000 times faster than SOS-CAOS. Both ultraviolet and visible wavelengths are included in the model to help differentiate between dissolved organic material and chlorophyll in the study of the open ocean and the coastal zone. The incorporation of this model into the retrieval algorithm will make the retrieval process more efficient, and thus applicable for operational use with global satellite observations.
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Onderka, Milan, Marek Rodný, and Yvetta Velísková. "Suspended Particulate Matter Concentrations Retrieved from Self-Calibrated Multispectral Satellite Imagery." Journal of Hydrology and Hydromechanics 59, no. 4 (September 1, 2011): 251–61. http://dx.doi.org/10.2478/v10098-011-0021-9.
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Suspended Particulate Matter Concentrations Retrieved from Self-Calibrated Multispectral Satellite ImageryInland waters are known to be laden with high levels of suspended particulate matter (SPM). Remotely sensed data have been shown to provide a true synoptic view of SPM over vast areas. However, as to date, there is no universal technique that would be capable of retrieving SPM concentrations without a complete reliance on time-consuming and costly ground measurements ora prioriknowledge of inherent optical properties of water-borne constituents. The goal of this paper is to present a novel approach making use of the synergy found between the reflectance in the visual domain (~ 400-700 nm) with the near-infrared portion of the spectrum (~ 700-900 nm). The paper begins with a brief discourse of how the shape and spectral dependence of reflectance is determined by high concentrations of SPM. A modeled example is presented to mimic real-world conditions in fluvial systems, with specific absorption and scattering coefficients of the virtual optically active constituents taken from the literature. Using an optical model, we show that in the visual spectral domain (~ 400-700 nm) the water-leaving radiance responds to increasing SPM (0-100 g m-3) in a non-linear manner. Contrarily to the visual spectra, reflectance in the near infrared domain (~ 700-900 nm) appears to be almost linearly related to a broad range of SPM concentrations. To reduce the number of parameters, the reflectance function (optical model) was approximated with a previously experimentally verified exponential equation (Schiebeet al., 1992: Remote sensing of suspended sediments: the Lake Chicot, Arkansas project, Int. J. Remote Sensing,13, 8, 1487-1509). The SPM term in Schiebe's equation was expressed as a linear function of top-of-atmosphere reflectance. This made it possible to calibrate the reflectance in the visual domain by reflectance values from the near-IR portion of the spectrum. The possibility to retrieve SPM concentrations from only remote sensing data without any auxiliary ground mea-surements is tested on a Landsat ETM + scene acquired over a reservoir with moderately turbid water with SPM concentrations between 15-70 g m-3. The retrieved concentrations (on average) differ from in-situ measurement by ~ 10.5 g m-3.
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Immler, F., D. Engelbart, and O. Schrems. "Fluorescence from atmospheric aerosol detected by a lidar indicates biogenic particles in the lowermost stratosphere." Atmospheric Chemistry and Physics 5, no. 2 (February 8, 2005): 345–55. http://dx.doi.org/10.5194/acp-5-345-2005.
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Abstract. With a lidar system that was installed in Lindenberg/Germany, we observed in June 2003 an extended aerosol layer at 13km altitude in the lowermost stratosphere. This layer created an inelastic backscatter signal that we detected with a water vapour Raman channel, but that was not produced by Raman scattering. Also, we find evidence for inelastic scattering from a smoke plume from a forest fire that we observed in the troposphere. We interpret the unexpected properties of these aerosols as fluorescence induced by the laser beam at organic components of the aerosol particles. Fluorescence from ambient aerosol had not yet been considered detectable by lidar systems. However, organic compounds such as polycyclic aromatic hydrocarbons sticking to the aerosol particles, or bioaerosol such as bacteria, spores or pollen fluoresce when excited with UV-radiation in a way that is detectable by our lidar system. Therefore, we conclude that fluorescence from organic material released by biomass burning creates, inelastic backscatter signals that we measured with our instrument and thus demonstrate a new and powerful way to characterize aerosols by a remote sensing technique. The stratospheric aerosol layer that we have observed in Lindenberg for three consecutive days is likely to be a remnant from Siberian forest fire plumes lifted across the tropopause and transported around the globe.
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Muzalevskiy, Konstantin, and Anatoly Zeyliger. "Application of Sentinel-1B Polarimetric Observations to Soil Moisture Retrieval Using Neural Networks: Case Study for Bare Siberian Chernozem Soil." Remote Sensing 13, no. 17 (September 2, 2021): 3480. http://dx.doi.org/10.3390/rs13173480.
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Sentinel-1 is currently the only synthetic-aperture radar, which radar measurements of the earth’s surface to be carried out, regardless of weather conditions, with high resolution up to 5–40 m and high periodicity from several to 12 days. Sentinel-1 creates a technological platform for the development of new globally remote sensing algorithms of soil moisture, not only for hydrological and climatic model applications, but also on a single field scale for individual farms in precision farming systems used. In this paper, the potential of soil moisture remote sensing using polarimetric Sentinel-1B backscattering observations was studied. As a test site, the fallow agricultural field with bare soil near the Minino village (56.0865°N, 92.6772°E), Krasnoyarsk region, the Russian Federation, was chosen. The relationship between the cross-polarized ratio, reflectivity, and the soil surface roughness established Oh used as a basis for developing the algorithm of soil moisture retrieval with neural networks (NNs) computational model. Two NNs is used as a universal regression technique to establish the relationship between scattering anisotropy, entropy and backscattering coefficients measured by the Sentinel-1B on the one hand and reflectivity on the other. Finally, the soil moisture was found from the soil reflectivity in solving the inverse problem using the Mironov dielectric model. During the field campaign from 21 May to 25 August 2020, it was shown that the proposed approach allows us to predict soil moisture values in the layer thickness of 0.00–0.05 m with the root-mean-square error and determination coefficient not worse than 3% and 0.726, respectively. The validity of the proposed approach needs additional verification on a wider dataset using soils of different textures, a wide range of variations in soil surface roughness, and moisture.
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Crabbe, Richard Azu, David William Lamb, Clare Edwards, Karl Andersson, and Derek Schneider. "A Preliminary Investigation of the Potential of Sentinel-1 Radar to Estimate Pasture Biomass in a Grazed, Native Pasture Landscape." Remote Sensing 11, no. 7 (April 10, 2019): 872. http://dx.doi.org/10.3390/rs11070872.
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Knowledge of the aboveground biomass (AGB) of large pasture fields is invaluable as it assists graziers to set stocking rate. In this preliminary evaluation, we investigated the response of Sentinel-1 (S1) Synthetic Aperture Radar (SAR) data to biophysical variables (leaf area index, height and AGB) for native pasture grasses on a hilly, pastoral farm. The S1 polarimetric parameters such as backscattering coefficients, scattering entropy, scattering anisotropy, and mean scattering angle were regressed against the widely used morphological parameters of leaf area index (LAI) and height, as well as AGB of pasture grasses. We found S1 data to be more responsive to the pasture parameters when using a 1 m digital elevation model (DEM) to orthorectify the SAR image than when we employed the often-used Shuttle Radar Topography 30 m and 90 m Missions. With the 1m DEM analysis, a significant quadratic relationship was observed between AGB and VH cross-polarisation (R2 = 0.71), and significant exponential relationships between polarimetric entropy and LAI and AGB (R2 = 0.53 and 0.45, respectively). Similarly, the mean scattering angle showed a significant exponential relationship with LAI and AGB (R2 = 0.58 and R2 = 0.83, respectively). The study also found a significant quadratic relationship between the mean scattering angle and pasture height (R2 = 0.72). Despite a relatively small dataset and single season, the mean scattering angle in conjunction with a generalised additive model (GAM) explained 73% of variance in the AGB estimates. The GAM model estimated AGB with a root mean square error of 392 kg/ha over a range in pasture AGB of 443 kg/ha to 2642 kg/ha with pasture LAI ranging from 0.27 to 1.87 and height 3.25 cm to 13.75 cm. These performance metrics, while indicative at best owing to the limited datasets used, are nonetheless encouraging in terms of the application of S1 data to evaluating pasture parameters under conditions which may preclude use of traditional optical remote sensing systems.
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Sawamura, P., D. Müller, R. M. Hoff, C. A. Hostetler, R. A. Ferrare, J. W. Hair, R. R. Rogers, et al. "Aerosol optical and microphysical retrievals from a hybrid multiwavelength lidar dataset – DISCOVER-AQ 2011." Atmospheric Measurement Techniques Discussions 7, no. 3 (March 28, 2014): 3113–57. http://dx.doi.org/10.5194/amtd-7-3113-2014.
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Abstract. Retrievals of aerosol microphysical properties (e.g. effective radius, volume and surface-area concentrations) and aerosol optical properties (e.g. complex index of refraction and single scattering albedo) were obtained from a hybrid multiwavelength lidar dataset for the first time. In July of 2011, in the Baltimore-Washington DC region, synergistic profiling of optical and microphysical properties of aerosols with both airborne in-situ and ground-based remote sensing systems was performed during the first deployment of DISCOVER-AQ. The hybrid multiwavelength lidar dataset combines elastic ground-based measurements at 355 nm with airborne High Spectral Resolution Lidar (HSRL) measurements at 532 nm and elastic measurements at 1064 nm that were obtained less than 5 km apart of each other. This was the first study in which optical and microphysical retrievals from lidar were obtained during the day and directly compared to AERONET and in-situ measurements for 11 cases. Good agreement was observed between lidar and AERONET retrievals. Larger discrepancies were observed between lidar retrievals and in-situ measurements obtained by the aircraft and aerosol hygroscopic effects are believed to be the main factor of such discrepancies.
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Park and Lee. "On the Use of Single-, Dual-, and Quad-Polarimetric SAR Observation for Landslide Detection." ISPRS International Journal of Geo-Information 8, no. 9 (September 2, 2019): 384. http://dx.doi.org/10.3390/ijgi8090384.
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Remote sensing technologies, particularly with Synthetic Aperture Radar (SAR) system, can provide timely and critical information to assess landslide distributions over large areas. Most space-borne SAR systems have been operating in different polarimetric modes to meet various operational requirements. This study aims to discuss how much detectability can be expected in the landslide map produced from the single-, dual-, and quad-polarization modes of observation. The experimental analysis of the characteristic changes of PALSAR-2 signals showed that quad-polarization parameters indicating signal depolarization properties revealed noticeable landslide-induced temporal changes for all local incidence angle ranges. To produce a landslide map, a simple change detection method based on characteristic scattering properties of landslide areas was proposed. The accuracy assessment results showed that the depolarization parameters, such as the co-pol coherence and polarizing contribution, can identify areas affected by landslides with a detection rate of 60%, and a false-alarm rate of 5%. On the other hand, the single- or dual-pol parameters can only be expected to provide half the accuracy with significant false-alarms in areas with temporal variations independent of landslides.
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Ku, Chiung-Shen, Kun-Shan Chen, Pao-Chi Chang, and Yang-Lang Chang. "Imaging Simulation for Synthetic Aperture Radar: A Full-Wave Approach." Remote Sensing 10, no. 9 (September 3, 2018): 1404. http://dx.doi.org/10.3390/rs10091404.
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Imaging simulation of synthetic aperture radar (SAR) is one of the potential tools in the field of remote sensing. The echo signal in imaging simulation based on the point target model cannot be linked to practical scenes due to the model being a simple mathematical form, stating only the synthetic process and lacking the physical process based on electromagnetic theory. In this paper, the full-wave method is applied to include the electromagnetic effects in raw data generation, and then a refined omega-K algorithm is used to perform image focusing. According to the proposed method, the focused images not only demonstrate the difference under dielectric constant variation but also present the diversified interaction among the targets with the spacing change. In addition, the images are simulated in different observation modes and bandwidths to provide a satisfactory reference for the design of system parameters. The simulation results from the full-wave method also compare well with chamber experiments. The simulation of SAR imaging based on a full-wave method offers more complete recovery of scattering information and is useful in designing future novel SAR systems and in speckle reduction analysis.
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Brunamonti, Simone, Giovanni Martucci, Gonzague Romanens, Yann Poltera, Frank G. Wienhold, Maxime Hervo, Alexander Haefele, and Francisco Navas-Guzmán. "Validation of aerosol backscatter profiles from Raman lidar and ceilometer using balloon-borne measurements." Atmospheric Chemistry and Physics 21, no. 3 (February 16, 2021): 2267–85. http://dx.doi.org/10.5194/acp-21-2267-2021.
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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.
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Choi, Jinho, Seokho Kim, Jung Park, Seung Lee, Young Seo, and Dong Park. "Luminescent Organic Barcode Nanowires for Effective Chemical Sensors." Polymers 11, no. 4 (April 11, 2019): 662. http://dx.doi.org/10.3390/polym11040662.
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Chemical materials are sometimes harmful to the environment as well as humans, plants, and animals. Thus, high-performance sensor systems have become more important in the past few decades. To achieve pH scale sensing in nanosystems, we applied luminescence polymer nanowires with alumina oxide template method with electrochemical polymerization. We made polymer nanowire barcode by alternately stacking poly(3-methylthiophene) (P3MT) and poly(3,4-ethylenedioxythiophene) (PEDOT) in a nanoporous template. After polymerization, a hydrofluoric acid solvent was used to remove the template, and, for changing the pH scale, we used sodium hydroxide. We measured optical properties of each part of barcode using Raman scattering and photoluminescence and confirmed that only P3MT was changed by alkali treatment.
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Camps, Adriano, and Joan Francesc Munoz-Martin. "Analytical Computation of the Spatial Resolution in GNSS-R and Experimental Validation at L1 and L5." Remote Sensing 12, no. 23 (November 28, 2020): 3910. http://dx.doi.org/10.3390/rs12233910.
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Global navigation satellite systems reflectometry (GNSS-R) is a relatively novel remote sensing technique, but it can be understood as a multi-static radar using satellite navigation signals as signals of opportunity. The scattered signals over sea ice, flooded areas, and even under dense vegetation show a detectable coherent component that can be separated from the incoherent component and processed accordingly. This work derives an analytical formulation of the response of a GNSS-R instrument to a step function in the reflectivity using well-known principles of electromagnetic theory. The evaluation of the spatial resolution then requires a numerical evaluation of the proposed equations, as the width of the transition depends on the reflectivity values of two regions. However, it is found that results are fairly constant over a wide range of reflectivities, and they only vary faster for very high or very low reflectivity gradients. The predicted step response is then satisfactorily compared to airborne experimental results at L1 (1575.42 MHz) and L5 (1176.45 MHz) bands, acquired over a water reservoir south of Melbourne, in terms of width and ringing, and several examples are provided when the transition occurs from land to a rough ocean surface, where the coherent scattering component is no longer dominant.
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Gleason, Scott. "A Real-Time On-Orbit Signal Tracking Algorithm for GNSS Surface Observations." Remote Sensing 11, no. 16 (August 9, 2019): 1858. http://dx.doi.org/10.3390/rs11161858.
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This manuscript describes real-time on-orbit instrument compatible open loop signal tracking techniques for Global Navigation Satellite Systems (GNSS) reflection observations. All GNSS-reflection (GNSS-R) satellite instruments require algorithms which run in real-time on-board the satellite, that are capable of predicting the code phase time delay and Doppler frequency of surface reflected signals. The algorithms presented here are for open loop tracking techniques in reflected GNSS signals for the purposed of making surface remote sensing observations. Initially, the algorithms are demonstrated using high resolution sampled data from the NASA Cyclone GNSS (CYGNSS) mission over ocean and land surfaces. Subsequently. the algorithm performance over ocean regions is analyzed in detail using a larger data set. As part of the analysis, the algorithm is assessed for its speed of convergence, to demonstrate general compatibility with spacecraft instrument processing limitations. Results indicate that over ocean regions is it possible to robustly predict in real time the Doppler frequency and code phase time delay of multiple reflected signal to sufficient precision to make science observations of the scattering surface. These algorithms are intended to provide a baseline technique and variations from which the scientific community can design more specialized algorithms for individual applications.
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Godin, Oleg A., and Kay L. Gemba. "Graduate programs in physical, engineering, and underwater acoustics at the Naval Postgraduate School." Journal of the Acoustical Society of America 152, no. 4 (October 2022): A122. http://dx.doi.org/10.1121/10.0015752.
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The Departments of Physics and of Electrical and Computer Engineering at the Naval Postgraduate School offer graduate programs in acoustics leading to MS and PhD degrees in applied physics and engineering acoustics. Engineering acoustics degrees can be completed in either traditional or distance learning modes. The departments also offer stand-alone academic certificate programs in fundamentals of engineering acoustics, underwater acoustics, and sonar system applications, with a set of three certificates leading to a MS degree in engineering acoustics. MS and PhD programs are interdisciplinary, with courses and laboratory work drawn principally from the fields of physics and electrical engineering. Subjects covered include waves and oscillations; fundamentals of physical and structural acoustics; the generation, propagation, and reception of sound in the ocean; civilian and military applications of sonar systems; and acoustic signal processing. Topics of recent theses and dissertations include development and field testing of novel sensors for atmospheric and ocean acoustics, modeling and measurements of ambient noise and sound propagation in the ocean, sound scattering in underwater waveguides, acoustic vector sensors and vector field properties, acoustic communications, noise interferometry, time reversal in acoustics, geo-acoustic inversion, acoustic remote sensing of the ocean, and acoustics of autonomous underwater and aerial vehicles.
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Fahey, Thomas, Maidul Islam, Alessandro Gardi, and Roberto Sabatini. "Laser Beam Atmospheric Propagation Modelling for Aerospace LIDAR Applications." Atmosphere 12, no. 7 (July 17, 2021): 918. http://dx.doi.org/10.3390/atmos12070918.
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Atmospheric effects have a significant impact on the performance of airborne and space laser systems. Traditional models used to predict propagation effects rely heavily on simplified assumptions of the atmospheric properties and their interactions with laser systems. In the engineering domain, these models need to be continually improved in order to develop tools that can predict laser beam propagation with high accuracy and for a wide range of practical applications such as LIDAR (light detection and ranging), free-space optical communications, remote sensing, etc. The underlying causes of laser beam attenuation in the atmosphere are examined in this paper, with a focus on the dominant linear effects: absorption, scattering, turbulence, and non-linear thermal effects such as blooming, kinetic cooling, and bleaching. These phenomena are quantitatively analyzed, highlighting the implications of the various assumptions made in current modeling approaches. Absorption and scattering, as the dominant causes of attenuation, are generally well captured in existing models and tools, but the impacts of non-linear phenomena are typically not well described as they tend to be application specific. Atmospheric radiative transfer codes, such as MODTRAN, ARTS, etc., and the associated spectral databases, such as HITRAN, are the existing tools that implement state-of-the-art models to quantify the total propagative effects on laser systems. These tools are widely used to analyze system performance, both for design and test/evaluation purposes. However, present day atmospheric radiative transfer codes make several assumptions that reduce accuracy in favor of faster processing. In this paper, the atmospheric radiative transfer models are reviewed highlighting the associated methodologies, assumptions, and limitations. Empirical models are found to offer a robust analysis of atmospheric propagation, which is particularly well-suited for design, development, test and evaluation (DDT&E) purposes. As such, empirical, semi-empirical, and ensemble methodologies are recommended to complement and augment the existing atmospheric radiative transfer codes. There is scope to evolve the numerical codes and empirical approaches to better suit aerospace applications, where fast analysis is required over a range of slant paths, incidence angles, altitudes, and atmospheric conditions, which are not exhaustively captured in current performance assessment methods.
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Trovato, Valentina, Silvia Sfameni, Giulia Rando, Giuseppe Rosace, Sebania Libertino, Ada Ferri, and Maria Rosaria Plutino. "A Review of Stimuli-Responsive Smart Materials for Wearable Technology in Healthcare: Retrospective, Perspective, and Prospective." Molecules 27, no. 17 (September 5, 2022): 5709. http://dx.doi.org/10.3390/molecules27175709.
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In recent years thanks to the Internet of Things (IoT), the demand for the development of miniaturized and wearable sensors has skyrocketed. Among them, novel sensors for wearable medical devices are mostly needed. The aim of this review is to summarize the advancements in this field from current points of view, focusing on sensors embedded into textile fabrics. Indeed, they are portable, lightweight, and the best candidates for monitoring biometric parameters. The possibility of integrating chemical sensors into textiles has opened new markets in smart clothing. Many examples of these systems are represented by color-changing materials due to their capability of altering optical properties, including absorption, reflectance, and scattering, in response to different external stimuli (temperature, humidity, pH, or chemicals). With the goal of smart health monitoring, nanosized sol–gel precursors, bringing coupling agents into their chemical structure, were used to modify halochromic dyestuffs, both minimizing leaching from the treated surfaces and increasing photostability for the development of stimuli-responsive sensors. The literature about the sensing properties of functionalized halochromic azo dyestuffs applied to textile fabrics is reviewed to understand their potential for achieving remote monitoring of health parameters. Finally, challenges and future perspectives are discussed to envisage the developed strategies for the next generation of functionalized halochromic dyestuffs with biocompatible and real-time stimuli-responsive capabilities.
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Verlinden, Kathryn L., and Simon P. de Szoeke. "Simulating Radiative Fluxes through Southeastern Pacific Stratocumulus Clouds during VOCALS-REx." Journal of Atmospheric and Oceanic Technology 35, no. 4 (April 2018): 821–36. http://dx.doi.org/10.1175/jtech-d-17-0169.1.
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ABSTRACTTime series of solar and thermal infrared radiative flux profiles are simulated with the Rapid Radiative Transfer Model (RRTM) using a hierarchy of constraints from radar reflectivity and passive microwave cloud remote sensing measurements collected over a ship in the southeastern tropical Pacific Ocean (20°S) during the second leg of the Variability of American Monsoon Systems (VAMOS) Ocean–Cloud–Atmosphere–Land Study Regional Experiment (VOCALS-REx). Incorporating additional constraints results in simulations of physically consistent radiative profiles throughout the atmosphere, especially within the cloud, where they are difficult to observe precisely. Simulated surface radiative fluxes are compared with those observed on the ship and by aircraft.Due to the strong Rayleigh scattering of drizzle drops compared to cloud droplets that absorb, emit, and scatter natural radiation, cloud radar reflectivity overestimates cloud liquid water content (LWC). As a result, clouds are optically too thick and transmission ratios are too low in simulations using radar LWC. Imposing a triangular (increasing linearly with height from zero at cloud base) LWC profile in agreement with microwave liquid water path (LWP) improves the simulation of the transmission ratio. Constraining the corresponding microphysical cloud effective radius to that retrieved from optical depth, LWP, and cloud thickness results in additional improvements to the simulations. Time series, averages, and composite diurnal cycles of radiative fluxes, heating rates, and cloud radiative forcing are presented.
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Kozhevnikov, D. A., and R. V. Feodortsau. "THE METHOD OF GEOMETRIC CALIBRATION OF OPTOELECTRONIC SYSTEMS BASED ON ELECTRONIC TEST OBJECT." Devices and Methods of Measurements 8, no. 4 (December 15, 2017): 374–85. http://dx.doi.org/10.21122/2220-9506-2017-8-4-46-54.
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Designing remote sensing of the Earth devices is requires a lot of attention to evaluation lens distortion level and providing the required accuracy values of geometric calibration of optoelectronic systems at all. Test- objects known as most common tools for optical systems geometric calibration. The purpose of the research was creating an automatically method of distortion correction coefficients calculating with a 3 μm precision in the measurement process. The method of geometric calibration of the internal orientation elements of the optical system based on the electronic test object is proposed. The calculation of the test string brightness image from its multispectral image and filtered signal extrema position determination are presented. Ratio of magnitude of the distortion and interval center is given. Three variants of electronic test-objects with different step and element size are considered. Оptimal size of calibration element was defined as 3×3 pixels due to shape of the subpixels with the aspect ratio of the radiating areas about 1 : 3. It is advisable to use IPS as an electronic test object template. An experimental test and measurement stand functional diagram based on the collimator and optical bench «OSK-2CL» is showed. It was determined that test objects with a grid spacing of 4 and 8 pixels can’t provide tolerable image because of non-collimated emission of active sites and scattering on optical surfaces – the shape of the elements is substantially disrupted. Test-object with a 12 pixels grid spacing was used to distortion level analyzing as most suitable.Ratio of coordinate increment and element number graphs for two photographic lenses (Canon EF-S 17-85 f/4-5.6 IS USM and EF-S 18-55 f/3.5-5.6 IS II) are presented. A calculation of the distortion values in edge zones was held, which were respectively 43 μm and 51.6 μm. The technique and algorithm of software implementation is described. Possible directions of the method development are mentioned.
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Jiang, Weijie, Erxiao Liu, Xing Kong, Shengsheng Shi, and Jianjun Liu. "Zhongshan HF Radar Elevation Calibration Based on Ground Backscatter Echoes." Electronics 11, no. 24 (December 19, 2022): 4236. http://dx.doi.org/10.3390/electronics11244236.
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The super dual auroral radar network (SuperDARN) is an important tool in the remote sensing of ionospheric potential convection in middle and high latitudes, and also a major source of elevation data detection. A reliable elevation angle helps estimate the propagation paths of high-frequency radio signals between scattering spots and radars, which is crucial for determining high-frequency radar target geolocation. The SuperDARN radar uses interferometry to estimate the elevation of the returned signal. However, elevation data are still underutilized owing to the difficulties of phase difference calibration induced by the propagation time delay between two arrays. This paper statistically analyzes the distribution features of the group range-elevation angle and group range-virtual height before and after calibration using elevation data from the ground backscatter echoes of the Zhongshan SuperDARN radar, calculating the root mean square error (RMSE) of the virtual height; the results show that the RMSE after calibration is mostly reduced to within 54% of that before calibration. Furthermore, we validate the calibration factor based on the primary phase data. The data from 2013 to 2015 indicate that this technique can be efficiently used to estimate the daily calibration factor. Finally, we present the statistical distribution of the calibration factor, which provides technical support for the calibration of elevation data in the future.
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Gasteiger, J., and V. Freudenthaler. "Benefit of depolarization ratio at λ = 1064 nm for the retrieval of the aerosol microphysics from lidar measurements." Atmospheric Measurement Techniques Discussions 7, no. 5 (May 22, 2014): 5095–115. http://dx.doi.org/10.5194/amtd-7-5095-2014.
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Abstract. A better quantification of aerosol microphysical and optical properties is required to improve the modelling of aerosol effects on weather and climate. This task is methodologically demanding due to the huge diversity of aerosol composition and of their shape and size distribution, and due to the complexity of the relation between the microphysical and optical properties. Lidar remote sensing is a valuable tool to gain spatially and temporally resolved information on aerosol properties. Advanced lidar systems provide sufficient information on the aerosol optical properties for the retrieval of important aerosol microphysical properties. Recently, the mass concentration of transported volcanic ash, which is relevant for the flight safety of airplanes, was retrieved from measurements of such lidar systems in Southern Germany. The relative uncertainty of the retrieved mass concentration was on the order of ±50%. The present study investigates improvements of the retrieval accuracy when the capability of measuring the linear depolarization ratio at 1064 nm is added to the lidar setup. The lidar setups under investigation are based on the setup of MULIS and POLIS of the LMU in Munich which measure the linear depolarization ratio at 355 nm and 532 nm with high accuracy. By comparing results of retrievals applied to simulated lidar measurements with and without the depolarization at 1064 nm it is found that the availability of 1064 nm depolarization measurements reduces the uncertainty of the retrieved mass concentration and effective particle size by a factor of about 2–3. This significant improvement in accuracy is the result of the increased sensitivity of the lidar setup to larger particles. However, the retrieval of the single scattering albedo, which is relevant for the radiative transfer in aerosol layers, does hardly benefit from the availability of 1064 nm depolarization measurements.
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Fedoseeva, Elena V., Georgy G. Shchukin, and Ilya N. Rostokin. "Calibration issues for a three-band microwave radiometric system with background noise compensation." Izmeritel`naya Tekhnika, no. 4 (April 2020): 44–50. http://dx.doi.org/10.32446/0368-1025it.2020-4-44-50.
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For microwave radiometric remote sensing systems in natural environments, the important issue is calibration, i.e. determination-one correspondence of values of the output signal value of the brightness temperature of the sensed region, the largest of which evaluated physical parameters. Microwave radiometric systems operate under the influence of external interference, for example, background noise – radiothermal radiation of the space surrounding the system, received through the scattering region of the antenna pattern. This article examines the influence of background noise on the external calibration of a microwave radiometric system (based on an external “deterministic” noise source) and analyzes the conditions for performing such calibration in a system with compensation for the influence of background noise. The analysis of the output signal of the microwave radiometric system showed a significant influence of background noise on the parameter determined during calibration of the system – the beginning of the receiver scale, due to a change in the value of the contribution of background noise to the output signal when forming two reference levels during calibration from two angular directions. The possibility of reducing the interference effect of background noise on the results of measurements in a microwave radiometric system with a special two-channel antenna operating on two modes of a circular waveguide, with the formation of an additional compensation signal at the antenna output, is shown. The proposed version of the analytical evaluation of the degree of compensation of the influence of background noise on the output differential signal of the system and presents results of its application to numerical analysis of error in external calibration a tri-band microwave radiometric system with compensation of background noise when receiving thermal radiation onthe total aperture of the antenna.
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Lagorio, María Gabriela, Gabriela B. Cordon, Analía Iriel, Juan Manuel Romero, Julián Faivovich, and Carlos Taboada. "Biophotonics. Fluorescence and Reflectance in Living Organisms." Science Reviews - from the end of the world 2, no. 1 (December 18, 2020): 18–41. http://dx.doi.org/10.52712/sciencereviews.v2i1.36.
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The light that emerges from a biological entity is relevant from many aspects. In the first place, it allows the construction of the organism’s image and consequently it is responsible for visual perception and communication. Secondly, it can become an important tool in obtaining both physiological and chemical information from the observed entity, in a non-destructive way. When an organism is illuminated, the non-absorbed energy emerges as transmitted or reflected light. Additionally, fluorescence, phosphorescence or bioluminescence may be emitted. In our research group, we have studied and modelled the light released as reflectance and fluorescence for different biological systems like flowers, fruits, plant leaves, canopies, bird’s plumage and amphibians. In this review, we present the advances we have made in this area. They range from the development of theoretical approaches to the implementation of optical methodologies for practical applications. The analysis of light interaction with biological material, which is the domain of biophotonics, has recently acquired great importance in view of the increasing use of optical techniques to the study of living tissues. However, the interpretation of the photophysical and spectroscopic properties of these systems is usually complicated by several factors: elevated chromophore’s concentration, optical inhomogeneity, multi-scattering of photons and presence of multi-layered structures in most cases. Because of these, the accurate modelling of the interaction with light helps to avoid artifacts and to better interpret the processes that take place. Physical models used in the analysis of chlorophyll fluorescence in leaves and canopies with application in remote sensing, optical methodologies for food control and quantification of fluorescence in vivo for evaluation of its biological relevance are examples of the use of the emission of light and will be presented in this review.
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Hammer, E., M. Gysel, G. C. Roberts, T. Elias, J. Hofer, C. R. Hoyle, N. Bukowiecki, et al. "Size-dependent particle activation properties in fog during the ParisFog 2012/13 field campaign." Atmospheric Chemistry and Physics Discussions 14, no. 7 (April 8, 2014): 9475–516. http://dx.doi.org/10.5194/acpd-14-9475-2014.
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Abstract. Fog causes a variety of hazards in road traffic, maritime navigation, as well as in air traffic and railway traffic. There is a great demand, e.g. from airports, for more reliable fog forecasts to prevent fog related accidents. Improved fog forecasts require a better understanding of the numerous complex mechanisms during the fog life cycle. During winter 2012/13 a field campaign called ParisFog aiming at fog research took place at SIRTA (Instrumented Site for Atmospheric Remote Sensing Research). SIRTA is located about 20 km southwest of the Paris city centre, France in a semi-urban environment. In situ activation properties of the prevailing fog were investigated by measuring: (1) total and interstitial (non-activated) dry particle number size distributions behind two different inlet systems; (2) interstitial hydrated aerosol and fog droplet size distributions at ambient conditions; (3) cloud condensation nuclei (CCN) number concentration at different supersaturations (SS) with a CCN counter. The aerosol particles were characterized regarding their hygroscopic properties, fog droplet activation behavior and contribution to light scattering for 17 developed fog events. Low particle hygroscopicity with an overall median of hygroscopicity parameter, κ, of 0.14 was found, likely caused by substantial influence from local traffic and wood burning emissions. Measurements of the aerosol size distribution at ambient RH revealed that the critical wet diameter, above which the hydrated aerosols activate to fog droplets, is rather large with a median value of 2.4 μm and is highly variable (ranging from 1 to 5 μm) between the different fog events. Thus, the number of activated fog droplets was very small and the non-activated hydrated particles were found to contribute siginificantly to the observed light scattering and thus to the reduction in visibility. Combining all experimental data, the effective peak supersaturation, SSpeak, a measure of the peak supersaturation during the fog formation, was determined. The median SSpeak value was estimated to be in the range from 0.031 to 0.046% (upper and lower limit estimations), which is in good agreement with previous experimental and modeling studies of fog.
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Hammer, E., M. Gysel, G. C. Roberts, T. Elias, J. Hofer, C. R. Hoyle, N. Bukowiecki, et al. "Size-dependent particle activation properties in fog during the ParisFog 2012/13 field campaign." Atmospheric Chemistry and Physics 14, no. 19 (October 7, 2014): 10517–33. http://dx.doi.org/10.5194/acp-14-10517-2014.
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Abstract. Fog-induced visibility reduction is responsible for a variety of hazards in the transport sector. Therefore there is a large demand for an improved understanding of fog formation and thus improved forecasts. Improved fog forecasts require a better understanding of the numerous complex mechanisms during the fog life cycle. During winter 2012/13 a field campaign called ParisFog aiming at fog research took place at SIRTA (Instrumented Site for Atmospheric Remote Sensing Research). SIRTA is located about 20 km southwest of the Paris city center, France, in a semi-urban environment. In situ activation properties of the prevailing fog were investigated by measuring (1) total and interstitial (non-activated) dry particle number size distributions behind two different inlet systems; (2) interstitial hydrated aerosol and fog droplet size distributions at ambient conditions; and (3) cloud condensation nuclei (CCN) number concentration at different supersaturations (SS) with a CCN counter. The aerosol particles were characterized regarding their hygroscopic properties, fog droplet activation behavior and contribution to light scattering for 17 developed fog events. Low particle hygroscopicity with an overall median of the hygroscopicity parameter, κ, of 0.14 was found, likely caused by substantial influence from local traffic and wood burning emissions. Measurements of the aerosol size distribution at ambient RH revealed that the critical wet diameter, above which the hydrated aerosols activate to fog droplets, is rather large (with a median value of 2.6μm) and is highly variable (ranging from 1 to 5μm) between the different fog events. Thus, the number of activated fog droplets was very small and the non-activated hydrated particles were found to contribute significantly to the observed light scattering and thus to the reduction in visibility. Combining all experimental data, the effective peak supersaturation, SSpeak, a measure of the peak supersaturation during the fog formation, was determined. The median SSpeak value was estimated to be in the range from 0.031 to 0.046% (upper and lower limit estimations), which is in good agreement with previous experimental and modeling studies of fog.
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Pfreundschuh, Simon, Stuart Fox, Patrick Eriksson, David Duncan, Stefan A. Buehler, Manfred Brath, Richard Cotton, and Florian Ewald. "Synergistic radar and sub-millimeter radiometer retrievals of ice hydrometeors in mid-latitude frontal cloud systems." Atmospheric Measurement Techniques 15, no. 3 (February 9, 2022): 677–99. http://dx.doi.org/10.5194/amt-15-677-2022.
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Abstract. Accurate measurements of ice hydrometeors are required to improve the representation of clouds and precipitation in weather and climate models. In this study, a newly developed, synergistic retrieval algorithm that combines radar with passive millimeter and sub-millimeter observations is applied to observations of three frontally generated, mid-latitude cloud systems in order to validate the retrieval and assess its capabilities to constrain the properties of ice hydrometeors. To account for uncertainty in the assumed shapes of ice particles, the retrieval is run multiple times while the shape is varied. Good agreement with in situ measurements of ice water content and particle concentrations for particle maximum diameters larger than 200 µm is found for one of the flights for the large plate aggregate and the six-bullet rosette shapes. The variational retrieval fits the observations well, although small systematic deviations are observed for some of the sub-millimeter channels pointing towards issues with the sensor calibration or the modeling of gas absorption. For one of the flights the quality of the fit to the observations exhibits a weak dependency on the assumed ice particle shape, indicating that the employed combination of observations may provide limited information on the shape of ice particles in the observed clouds. Compared to a radar-only retrieval, the results show an improved sensitivity of the synergistic retrieval to the microphysical properties of ice hydrometeors at the base of the cloud. Our findings indicate that the synergy between active and passive microwave observations may improve remote-sensing measurements of ice hydrometeors and thus help to reduce uncertainties that affect currently available data products. Due to the increased sensitivity to their microphysical properties, the retrieval may also be a valuable tool to study ice hydrometeors in field campaigns. The good fits obtained to the observations increase confidence in the modeling of clouds in the Atmospheric Radiative Transfer Simulator and the corresponding single scattering database, which were used to implement the retrieval forward model. Our results demonstrate the suitability of these tools to produce realistic simulations for upcoming sub-millimeter sensors such as the Ice Cloud Image or the Arctic Weather Satellite.
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Mei, Liang, Teng Ma, Zhen Zhang, Ruonan Fei, Kun Liu, Zhenfeng Gong, and Hui Li. "Experimental Calibration of the Overlap Factor for the Pulsed Atmospheric Lidar by Employing a Collocated Scheimpflug Lidar." Remote Sensing 12, no. 7 (April 10, 2020): 1227. http://dx.doi.org/10.3390/rs12071227.
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Lidar techniques have been widely employed for atmospheric remote sensing during past decades. However, an important drawback of the traditional atmospheric pulsed lidar technique is the large blind range, typically hundreds of meters, due to incomplete overlap between the transmitter and the receiver, etc. The large blind range prevents the successful retrieval of the near-ground aerosol profile, which is of great significance for both meteorological studies and environmental monitoring. In this work, we have demonstrated a new experimental approach to calibrate the overlap factor of the Mie-scattering pulsed lidar system by employing a collocated Scheimpflug lidar (SLidar) system. A calibration method of the overlap factor has been proposed and evaluated with lidar data measured in different ranges. The overlap factor, experimentally determined by the collocated SLidar system, has also been validated through horizontal comparison measurements. It has been found out that the median overlap factor evaluated by the proposed method agreed very well with the overlap factor obtained by the linear fitting approach with the assumption of homogeneous atmospheric conditions, and the discrepancy was generally less than 10%. Meanwhile, simultaneous measurements employing the SLidar system and the pulsed lidar system have been carried out to extend the measurement range of lidar techniques by gluing the lidar curves measured by the two systems. The profile of the aerosol extinction coefficient from the near surface at around 90 m up to 28 km can be well resolved in a slant measurement geometry during nighttime. This work has demonstrated a great potential of employing the SLidar technique for the calibration of the overlap factor and the extension of the measurement range for pulsed lidar techniques.
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Hari Priya, S., P. V. Jayasri, E. V. S. Sita Kumari, and A. V. V. Prasad. "ON THE ESTIMATION OF POLARIMETRIC PARAMETERS FOR OIL SLICK FEATURE DETECTION FROM HYBRID POL AND DERIVED PSEUDO QUAD POL SAR DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-5 (November 19, 2018): 629–35. http://dx.doi.org/10.5194/isprs-archives-xlii-5-629-2018.
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<p><strong>Abstract.</strong> Oil spills in oceans have a significant long term effect on the marine ecosystem and are of prime concern for maritime economy. In order to locate and estimate the oil spread area and for quantitative damage assessment, it is required to continually monitor the affected area on the sea and its surroundings and space based remote sensing makes this technically viable. Synthetic Aperture Radar SAR with its high sensitivity to target dielectric constant, look angle and polarization-dependent target backscatter has become a potential tool for oil-spill observation and maritime monitoring. From conventional single-channel SAR (single-pol, HH or VV) to multi-channel SAR – (Dual/Quad-polarization) and more recently compact polarimetric (Hybrid/Slant Linear) SAR systems have been widely used for oil-spill detection in the seas. Various polarimetric features have been proposed to classify oil spills using full, dual and compact polarimetric SAR. RISAT-1 is a C-band SAR with Circular Transmit and Linear Receive (CTLR) hybrid polarimetric imaging capability.This study is aimed at the polarimetric processing of RISAT-1 hybrid pol single look complex (SLC) data for derivation of the decisive polarimetric parameters which can be used to identify oil spills in oceans and their discrimination from look-alike signatures. In order to understand ocean–oil spill signatures from full-quad pol SAR, pseudo-quad pol covariance matrix is constructed from RISAT-1 hybrid pol using polarimetric scattering models .Then polarimetric processing is carried out over pseudo-quad pol data for oil slick detection. In-house developed software is used for carrying out the above oil-spill study.</p>
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Barbosa, C., E. Novo, R. Ferreira, L. Carvalho, C. Cairo, F. Lopes, J. Stech, and E. Alcantara. "Brazilian inland water bio-optical dataset to support carbon budget studies in reservoirs as well as anthropogenic impacts in Amazon floodplain lakes: Preliminary results." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W3 (April 30, 2015): 1439–46. http://dx.doi.org/10.5194/isprsarchives-xl-7-w3-1439-2015.
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This work presents ongoing efforts and preliminary results for building a dataset that represents the first and most comprehensive bio-optical information available on Brazilian inland waters to support the development of remote sensing algorithms for monitoring aquatic systems. From 2012 to 2014 optical and limnological data was gathered along thirteen field campaigns in five Brazilian reservoirs, in an irrigation and domestic water supply reservoir located in semi-arid northeast of the country and in Amazonian floodplain lakes, thus covering the diversity of Brazilian inland waters. At each site 20 stations, on average, were sampled to acquire profiles of the following optical variables: absorption, attenuation, scattering, and backscattering coefficients and radiances/irradiances spectra above and in-water. Alongside these measurements, water samples were collected for determining concentrations of chlorophyll-a (Chl-a), Total Suspended Solid (TSS), Total Dissolved Carbon (TDC) and its organic/inorganic fractions, CDOM absorption, phytoplankton specific absorption [aph*] and Non-Algal Particles absorption [aNAP*]. Preliminary results show that Chl-a concentrations ranged from 0.6 to 243μg/L in reservoirs and 0.90 to 92μg/L in Amazonian lakes, while TSS concentrations ranged from 0.3 to 31mg/L in reservoirs and 0.5 to 162mg/L in Amazonian lakes. In situ beam attenuation coefficients ranged from 1.4 to 16m-1 in reservoirs and 12.5 to 38m-1 in Amazonian lakes, while diffuse attenuation coefficients of downwelling irradiance over the Photosynthetically Active Radiation (Kd(PAR)) extended from 0.35 to 4.5m-1 in reservoirs and 1.69 to 13.30m-1 in Amazonian lakes. Our research group is building this dataset anticipating future demands for algorithm validation regarding OLI/Landsat8 data and ESA Sentinel missions to be launched as of 2015.