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The article discusses the possibility of determining surface elevation using a conventional spaceborne synthetic aperture radar (SAR) survey by one satellite without interferometric phase measurements of the slant range. The capabilities of such determination are examined. A schematic diagram is given. Advantages and disadvantages are analyzed. [ABSTRACT FROM AUTHOR]

Remote sensing observations, especially those from ground-based radars, have been used extensively to discriminate between severe and nonsevere storms. Recent upgrades to operational remote sensing networks in the United States have provided unprecedented spatial and temporal sampling to study such storms. These networks help forecasters subjectively identify storms capable of producing severe weather at the ground; however, uncertainties remain in how to objectively identify severe thunderstorms using the same data. Here, three large-area datasets (geostationary satellite, ground-based radar, and ground-based lightning detection) are used over 28 recent events in an attempt to objectively discriminate between severe and nonsevere storms, with an additional focus on severe storms that produce tornadoes. Among these datasets, radar observations, specifically those at mid- and upper levels (altitudes at and above 4 km), are shown to provide the greatest objective discrimination. Physical and kinematic storm characteristics from all analyzed datasets imply that significantly severe [≥2-in. (5.08 cm) hail and/or ≥65-kt (33.4 m s-1) straight-line winds] and tornadic storms have stronger upward motion and rotation than nonsevere and less severe storms. In addition, these metrics are greatest in tornadic storms during the time in which tornadoes occur. [ABSTRACT FROM AUTHOR]

Englacial layers in Antarctica and Greenland are indicators of the dynamic, rheological and subglacial configuration of the ice sheets. Airborne radar sounder data is the primary remote sensing solution for directly observing englacial layers and structures at the glacier-catchment to ice-sheet scale. However, when traditional along-track synthetic aperture radar (SAR) processing is applied, steep layers can disappear, limiting the detectability and interpretability of englacial layer geometry. This study provides a reconstruction algorithm to address the problem of destructive phase interference during the radargram formation. We develop and apply a novel SAR processor optimized for layer detection that enhances the Signal-to-Noise ratio (SNR) of specular reflectors. The algorithm also enables the automatic estimation of layer slope. We demonstrate the algorithm using data acquired at the Institute Ice Stream, West Antarctica. [ABSTRACT FROM AUTHOR]

Shore-based coherent microwave radar and high-frequency (HF) surface wave radar are two components of a rapidly emerging set of technologies suitable for ocean wave remote sensing. To investigate their differences, this paper describes and analyzes the relationship between the water particle velocity and the wave height spectrum based on linear wave theory which underpins the algorithms developed for the analysis of data collected by coherent microwave radar. The backscatter mechanism which addresses the interaction of the HF radio waves with the ocean surface waves, as well as the empirical method adopted in our HF radar is also presented. The wave characteristics observed by the shore-based coherent S-band radar [Microwave Ocean Remote SEnsor (MORSE)] are analyzed. A multifrequency HF (MHF) radar based on a circular receiving array, which is capable of sensing waves up to 100-km offshore, is also introduced. An intercomparison of the wave height measurements obtained from the MORSE, MHF radar, and wave buoy is made. The comparison indicates that the wave heights measured by the MORSE and the MHF radar are consistent with the buoy-derived wave heights, with the root-mean-square differences (RMSDs) of 0.27 and 0.37 m, respectively. [ABSTRACT FROM AUTHOR]

Ground-based observatories use multi-sensor observations to characterize cloud and precipitation properties. A challenge is how to design strategies to best use these observations to understand the atmosphere and evaluate atmospheric numerical prediction models. This paper introduces the Cloud resolving model Radar SIMulator (CR-SIM), which uses output from high-resolution atmospheric models to emulate multi-wavelength, zenith-pointing, and scanning radar observables and multi-sensor (multi-radar and radar-lidar) integrated products. CR-SIM allows comparisons of the same variables between an atmospheric model simulation and remote sensing products using a forward modeling framework consistent with the microphysical assumptions used in the numerical model simulations. In this paper, we present several applications of CR-SIM for evaluation of a numerical model, quantification of retrieval uncertainty, and optimization of radar sampling strategy using observing system simulation experiments. These applications demonstrate that the application of CR-SIM as a virtual observatory operator on high-resolution model output helps interpret the differences between model results and observations and also improve under-standing of the representativeness errors due to the sampling limitations of the ground-based observatories. CR-SIM is licensed under the GNU GPL package and both the software and the user guide are freely available to scientific community. [ABSTRACT FROM AUTHOR]

The emergence of CubeSats has opened up the possibilities of advanced space missions with lower costs and faster development times. A major factor that limits the functionality of CubeSats is the absence of high-gain antennas (HGAs) that can sustain a high data-rate link for communications or provide the required spatial resolution for remote sensing. In this work, we discuss the development of one of the largest apertures at Ka-band for CubeSats—a 1 m mesh deployable offset reflector antenna, with a stowed volume of 3U ($10\times 10\times 30 \,\,\text {cm}^{3}$)—to enable precipitation radars that can achieve the required spatial resolution while meeting the stringent mechanical constraints posed by the small CubeSat volume. We detail the critical aspects of this antenna design, including RF characterization, antenna fabrication, and measurement. We also describe a novel deployment mechanism that facilitates the packaging of such a large aperture in a small volume. The antenna demonstrated a measured efficiency of 60%, with a half-power beamwidth of 0.60° at 35.75 GHz. The cost reduction afforded by CubeSats makes launching a constellation of such radar based CubeSats practical, allowing higher temporal sampling rates, which is essential for the observation of weather processes with a short-time evolution. [ABSTRACT FROM AUTHOR]

An important objective in scatterometry is the estimation of near-surface wind speed and direction in the presence of rain. We investigate an attenuation correction method using data from the High-Altitude Imaging Wind and Rain Airborne Profiler (HIWRAP) dual-frequency scatterometer, which operates at Ku and Ka band with dual conical scans at incidence angles of 30° and 40°. The method relies on the fact that the differential normalized surface cross section, δσ0 = σ0(Ka) − σ0(Ku), is relatively insensitive to wind speed and direction and that this quantity is closely related to the magnitude of the differential path attenuation, δA = A(Ka) − A(Ku), arising from precipitation, cloud, and atmospheric gases. As the method relies only on the difference between quantities measured in the presence and absence of rain, the estimates are independent of radar calibration error. As a test of the method's accuracy, we make use of the fact that the radar rain reflectivities just above the surface, as seen along different incidence angles, are approximately the same. This yields constraint equations in the form of differences between pairs of path attenuations along different lines of sight to the surface. A second validation method uses the dual-frequency radar returns from the rain just above the surface where it can be shown that the difference between the Ku- and Ka-band-measured radar reflectivity factors provide an estimate of differential path attenuation. Comparisons between the path attenuations derived from the normalized surface cross section and those from these surface-independent methods generally show good agreement. [ABSTRACT FROM AUTHOR]

While land-based high-frequency (HF) radars are the only instruments capable of resolving both the temporal and spatial variability of surface currents in the coastal ocean, recent high-resolution views suggest that the coastal ocean is more complex than presently deployed radar systems are able to reveal. This work uses a hybrid system, having elements of both phased arrays and direction finding radars, to improve the azimuthal resolution of HF radars. Data from two radars deployed along the U.S. East Coast and configured as 8-antenna grid arrays were used to evaluate potential direction finding and signal, or emitter, detection methods. Direction finding methods such as maximum likelihood estimation generally performed better than the well-known multiple signal classification (MUSIC) method given identical emitter detection methods. However, accurately estimating the number of emitters present in HF radar observations is a challenge. As MUSIC's direction-of-arrival (DOA) function permits simple empirical tests that dramatically aid the detection process, MUSIC was found to be the superior method in this study. The 8-antenna arrays were able to provide more accurate estimates of MUSIC's noise subspace than typical 3-antenna systems, eliminating the need for a series of empirical parameters to control MUSIC's performance. Code developed for this research has been made available in an online repository. [ABSTRACT FROM AUTHOR]

Seabirds are well known to be attracted by fishing boats to forage on offal and baits. We used recently developed loggers that record accurate GPS position and detect the presence of boats through their radar emissions to examine how albatrosses use Area Restricted Search (ARS) and if so, have specific ARS behaviours, when attending boats. As much as 78.5% of locations with a radar detection (contact with boat) during a trip occurred within ARS: 36.8% of all large-scale ARS (n = 212) and 14.7% of all small-scale ARS (n = 1476) were associated with the presence of a boat. During small-scale ARS, birds spent more time and had greater sinuosity during boat-associated ARS compared with other ARS that we considered natural. For, small-scale ARS associated with boats, those performed over shelves were longer in duration, had greater sinuosity, and birds spent more time sitting on water compared with oceanic ARS associated with boats. We also found that the proportion of small-scale ARS tend to be more frequently nested in larger-scale ARS was higher for birds associated with boats and that ARS behaviour differed between oceanic (tuna fisheries) and shelf-edge (mainly Patagonian toothfish fisheries) habitats. We suggest that, in seabird species attracted by boats, a significant amount of ARS behaviours are associated with boats, and that it is important to be able to separate ARS behaviours associated to boats from natural searching behaviours. Our study suggest that studying ARS characteristics should help attribute specific behaviours associated to the presence of boats and understand associated risks between fisheries. [ABSTRACT FROM AUTHOR]

Airborne radar sounding can measure conditions within and beneath polar ice sheets. In Antarctica, most digital radar-sounding data have been collected in the last 2 decades, limiting our ability to understand processes that govern longer-term ice-sheet behavior. Here, we demonstrate how analog radar data collected over 40 y ago in Antarctica can be combined with modern records to quantify multidecadal changes. Specifically, we digitize over 400,000 line kilometers of exploratory Antarctic radar data originally recorded on 35-mm optical film between 1971 and 1979. We leverage the increased geometric and radiometric resolution of our digitization process to show how these data can be used to identify and investigate hydrologic, geologic, and topographic features beneath and within the ice sheet. To highlight their scientific potential, we compare the digitized data with contemporary radar measurements to reveal that the remnant eastern ice shelf of Thwaites Glacier in West Antarctica had thinned between 10 and 33% between 1978 and 2009. We also release the collection of scanned radargrams in their entirety in a persistent public archive along with updated geolocation data for a subset of the data that reduces themean positioning error from 5 to 2.5 km. Together, these data represent a unique and renewed extensive, multidecadal historical baseline, critical for observing and modeling ice-sheet change on societally relevant timescales. [ABSTRACT FROM AUTHOR]

A novel procedure based on filtering and interpolation approaches is proposed to estimate the sea state parameters, including significant wave height, peak wave direction, peak period, peak wavenumber, and peak wavelength in shallow waters using the X-band marine radars. The method compensates the distortions introduced by the radar acquisition process and the power decay of the radar signal along the distance applying image-enhancement techniques instead of empirical and semiempirical calibration methods that use signal-to-noise ratio and in situ measurements as external references. To determine the threshold value for the interpolation approach, the influence of the antenna height on shadowing modulation effects is examined through performing an analysis of variance (ANOVA) that uses data from two X-band radars deployed at 10 and 20 m above MSL. ANOVA results reveal that it is possible to explain the increment of intensities affected by shadowing throughout the distance using an adaptive threshold retrieved from a third-order polynomial function of the mean radar cross section (RCS). Finally, an X-band radar is installed at 13 m above MSL to test the proposed technique. During measurements, the wind and wave conditions varied, and the antenna-look direction remained constant. Errors for $H_{s}$ , $\theta _{p}$ , and $T_{p}$ calculated as the difference between estimated and true data show a mean bias and a relative value of 0.05 m (2.72%), 1.52° (5.94%), and 0.15 s (1.67%), respectively. The directional and wave energy spectra derived from radar estimates, acoustic wave and current, ADVs record, as well as JONSWAP formulation are presented to illustrate the improvement resulting from the proposed method over the frequency domain. [ABSTRACT FROM AUTHOR]

In this work, we have presented experimental study for detecting cavity regions inside a tree trunk using circular back projection focusing algorithm (CBPA). First, the validity of CBPA was questioned and then checked by the help of a simulation scenario that were generated using perfect point-scatterers in Matlab programming environment. After achieving perfect reconstruction of the simulated cavity structure together with the tree-body in the simulated scenario, the implementation of CBPA was applied to a real tree-interior imaging radar (TIIR) experiments that were conducted in the laboratory. The resultant focused TIIR radar images of measured data have demonstrated that CBPA can be a strong candidate and successfully utilized for migrating the raw backscattered data for TIIR applications. [ABSTRACT FROM AUTHOR]

The Program of the Antarctic Syowa Mesosphere–Stratosphere–Troposphere/Incoherent Scatter (PANSY) radar is a large atmospheric radar located at the Antarctic Syowa Station (69.01°S, 39.59°E). The PANSY radar performed the first incoherent scatter (IS) measurements in the Antarctic region in 2015. Several specific observations were undertaken in 2017 including a 24-h observation of the ionosphere using a peripheral antenna array to suppress interference from the field-aligned irregularities (FAIs). This paper presents the preliminary results derived from the IS measurements using the PANSY radar and the adaptive signal processing techniques to suppress FAIs. The norm-constrained and directionally constrained minimization of power (NC-DCMP) algorithm was applied to the 24-h ionosphere observations by the PANSY radar with a weighting applied to the directional constraint based on the gain differences of the subarrays. When compared with the conventional nonadaptive approach, the number of usable power profiles was increased by about 24% by the gain-weighted NC-DCMP algorithm, suggesting its effectiveness for FAI clutter suppression in ionosphere observations. Furthermore, detection of FAIs using the dedicated antenna array was found valuable in assessing the reliability of estimations of electron density based on VHF-band IS radar data. [ABSTRACT FROM AUTHOR]

Wave–current interaction is a common and important phenomenon in the ocean. As an ocean remote sensing tool, high-frequency (HF) radar can be used to measure currents and wave parameters. In this paper, the possibility of studying wave–current interaction using HF radar is investigated. The first-order spectral power (FSP) of HF radar is used to explore the effect of current on the Bragg wave. By analyzing the FSP change with current (FSP-current distribution), we find that, in deep water, the wave–current interactions mainly belong to 2-D refraction case, while, over a relatively shallow shelf, the interactions are stronger and more complicated. Based on local topography and current field data at Taiwan Strait, the simulation results obtained using the SWAN model confirm the 2-D refraction of the Bragg wave. When the wave–current interaction is stable, we compensate the FSP with radar-measured currents according to the radar extracted FSP-current distribution and achieve a more accurate wind estimation. Comparisons between the original and refined wind fields show the effectiveness and necessity of the current-based compensation. [ABSTRACT FROM AUTHOR]

Microwave backscattering models play key roles in surface scattering modeling and soil moisture inversion in active microwave remote sensing. However, numerous evaluations indicate that significant discrepancies between the model simulations and radar observations remain, and these discrepancies are regarded to be attributed to inaccuracies in the models. What do such discrepancies originate from is unclear and has not been comprehensively analyzed. To this end, this paper presents an uncertainty analysis to explore the intrinsic reason for the discrepancies between the backscattering model simulations and radar observations. The probability distribution function and the corresponding statistical characteristics are introduced to describe the uncertainty in the model outputs. We find that the scale dependence of the key model inputs leads to significant uncertainties in the model inputs, and the uncertainties are transferred into the model outputs. Thus, the discrepancies between the model simulations and radar observations are intrinsically caused by the spatial scaling and related uncertainties of key model inputs. In short, the scale mismatch between the model inputs and remote sensing pixels is an intrinsic factor that causes the discrepancies between the model simulations and radar observations. This finding suggests that the scaling effect of model inputs should be carefully considered when using the backscattering models at the pixel scale, and equivalent inputs matched at the corresponding scales should be developed for remote sensing applications. Thus, this analysis insights into the scale dependence of inputs for backscattering models and suggests to provide scale-matched inputs where the models are applied at different scales. [ABSTRACT FROM AUTHOR]

Simulation of radar sounder (RS) data is important for understanding the radar response of subsurface features to facilitate the interpretation of the real data. Conventional electromagnetic simulators require the definition of complex geoelectrical models of the investigated targets. They also involve time-complex solutions of Maxwell’s equations for computing the received electric field, which leads to very high computation time. Furthermore, the simulated radargrams are often not realistic as it is very difficult to model all the variables involved in the data acquisition. In this paper, we propose a novel simulation approach that exploits the data available from existing RSs in geologically analogous terrains, to produce realistic simulations of the investigated RS target. This simulation strategy is based on minimizing the difference between the analog and the investigated acquisition scenarios. This is done by applying a series of corrections, which depend on the relation between the radargram characteristics and the physical variables describing the acquisition process. The aim is to produce radargrams that resemble the investigated scenario in terms of the echo magnitude, bandwidth, range resolution, and along-track resolution. Experimental results present three case studies for different possibilities of the analog and the investigated scenarios. The validation of the simulated radargrams with actual data demonstrates the effectiveness of the proposed approach. Finally, we also present a real application of this approach for the simulation of Radar for Icy Moon Exploration (RIME) radargrams for a combination of instrument and target parameters, using the SHAllow RADar (SHARAD) radargram acquired over the geological analog of a selected RIME target. [ABSTRACT FROM AUTHOR]

This study presents a simulated simultaneous retrieval of mass mean cloud ice particle effective diameter, ice water content, water vapor, and temperature profiles using a combination of a 94‐GHz cloud radar and multifrequency (118, 183, 240, 310, 380, 664, and 850 GHz) millimeter‐ and submillimeter‐wave radiometers from a space platform. The retrieval capabilities and uncertainties of the combined radar and microwave radiometers are quantified. We show that this combined active and passive remote sensing approach with SmallSat technologies addresses a gap in the current state‐of‐the‐art remote sensing measurements of ice cloud properties, especially deriving vertical profiles of ice cloud particle sizes in the atmosphere together with the ambient thermodynamic conditions. Therefore, this new approach can serve as a plausible candidate for future missions that target cloud and precipitation processes to improve weather forecasts and climate predictions. Key Points: This study presents a simulated ice cloud retrieval by a radar and multifrequency microwave radiometer space platformThis combined active and passive remote sensing approach outperforms current state‐of‐the‐art remote sensing of ice cloud propertiesIt serves as a plausible candidate for future missions that target cloud and precipitation processes [ABSTRACT FROM AUTHOR]

As one important part of post-earthquake loss assessment, building damage detection has important significance for understanding the disaster in time, implementing the emergency response, and post-disaster reconstructing. In recent years the development of the multi-platform remote sensing and the high-resolution remote sensing technology have provided opportunities to building damage detection with high accuracy. In this paper， firstly，the basic building damage characteristics and the concrete classification criteria are introduced. Then，the common damage detection methods at home and abroad based on the remote sensing technology are concluded，including the single-temporal image detection of the post-earthquake, the change detection between the pre-earthquake and the post-earthquake images，and the damage detection based on the multi-sources data. Limitations and drawbacks of these methods are proposed. Finally, combining with some cutting-edge technologies in remote sensing domain，the latest research progress of building damage detection based on the high-resolution remote sensing technology，synthetic aperture radar technology，light detection and ranging technology 9 and oblique aerial photography technology are summarized in detail. [ABSTRACT FROM AUTHOR]

Abstract In this paired study, we apply a recently developed high-resolution bathymetry estimation algorithm ("cBathy") to X-band marine radar observations at two nearshore field sites. The algorithm exploits observations of the spatial structure of wave phase to attain wavenumber estimates, inverts the linear water wave dispersion relation for depth, and then applies a Kalman filter to objectively update the bathymetry estimates. Previously, performance has only been tested using optical video observations. In this first of two papers, performance of the algorithm using X-band radar image time series is tested at two disparate barred beach environments: Duck, NC, USA, and Benson Beach, WA, USA. Each of the test beaches is either co-located with (Duck, NC) or geographically close to (Benson Beach, WA) those utilized in the original algorithm verification. Concurrent echosounder surveys are used as ground truth. The bulk performance of the radar-derived bathymetry estimate at Duck, NC, achieves 0.49 m root-mean-square error (RMSE) with 0.26 m bias deep. This compares well with the bulk performance of the concurrent estimate derived using optical video (0.44 m RMSE and 0.23 m bias deep). The radar-derived bathymetry estimate performance at Benson Beach, is similar (0.35 m RMSE and 0.11 m bias shallow), and is comparable to that of an optical video derived estimate at a similar Pacific Northwest beach (0.56 m RMSE and 0.41 m bias shallow). At both beaches, significantly higher performance is achieved at locations deeper than 2 m (offshore of the surfzone) than at locations shallower than 2 m (surfzone), where errors are often a large fraction of the total depth. Lastly, several weeks of observations are utilized to assess the sensitivity of algorithm quality control to environmental conditions. Thresholds based on the shoreward component of wind stress and offshore wave steepness are identified and shown to impact the areal coverage of radar-derived bathymetric estimates. Overall, these results demonstrate the viability of marine radar observations as input to the cBathy algorithm and delineate some environmental constraints on algorithm performance. In the companion paper, the algorithm is extended to areas where tidal currents are important, including an ebb tidal shoal and an estuary mouth. Highlights • Depth estimation algorithm, cBathy, is applied to X-band radar image time series. • Performance is assessed at two beaches (North Carolina and Washington, USA). • Accuracy via radar is comparable to video-based performance (reported previously). • Frequency of updates increases with wave height and when wind blows toward shore. [ABSTRACT FROM AUTHOR]

Abstract As one of the most important ecosystems, wetlands are threatened from both natural and anthropogenic activities. Mapping wetland is one of the curtail needs in order to prevent further loss. Since the beginning of the Remote Sensing revolution, different approaches using satellite images have been used for mapping and monitoring wetlands. In this paper we investigate the potential of the recently launched Sentinel satellites, both separate and in combination, for accurately mapping of different wetland classes using Support Vector Machines (SVMs) learning classifier. For investigating the influence of the Sentinel-2 red-edge bands, and the radar bands from Sentinel-1, three different datasets have been analyzed. The results showed that for more accurate mapping of different wetland classes, different datasets should be used. Thus, the red-edge bands have significant influence over the intensive vegetated wetland classes such as swamps, and the radar bands have significant influence over partially decayed vegetated wetland areas such as bogs. For future studies, in addition to the analyzed datasets, we recommend adding and investigating several vegetation indices for mapping and monitoring wetland areas. Highlights • Combination of optical and radar data for wetland monitoring • Supported Vector Machine algorithm for wetlands classification • Significant influence of the Red-edge bands over intense vegetated wetlands • Significant influence of the Radar data over decayed vegetated wetlands [ABSTRACT FROM AUTHOR]

Ground-based snowfall observations over Antarctica are rare due to the harsh environment and high logistical, equipment maintenance, and operational costs. Satellite measurements are crucial to provide continent-wide precipitation estimates, and this highlights the importance of validating the satellite estimates with measurements collected by ground-based Antarctic stations. The NASA CloudSat satellite, launched in 2006, is equipped with a 94 GHz (W-band) Cloud Profiling Radar (CPR) that provides measurements of reflectivity profiles of clouds and precipitation, whereas the incoming ESA/JAXA EarthCARE mission will add Doppler capability to a 94 GHz radar. This study explores how the synergy between two instruments available at most Antarctic stations, i.e., Micro Rain Radar (24 GHz, K-band) and laser disdrometer, can be used to validate satellite-borne W-band radar measurements, including Doppler estimates. A new validation methodology (K2W) was proposed to combine these instruments for simulating the 94 GHz reflectivity and Doppler measurements from Micro Rain Radar spectra. Assessment of the proposed K2W conversion methodology showed that the CloudSat Z e profiles can be simulated by the method with 0.2 dB mean difference at the lowest satellite radar range bin when time lag within ±12.5 min and the distance within 25 km around the CloudSat overpass were considered. With the K2W method, the 94 GHz Doppler velocity below 1 km altitude that would be observed by EarthCARE was obtained, and the standard deviation of the simulated Doppler velocity was found to be smaller than about 0.2 m s−1. The simulated 94 GHz Doppler radar profile information, which is less affected by attenuation compared to ground-based 94 GHz radar, will significantly improve the quantification of precipitation over Antarctica. This methodology will be applied to further assess the EarthCARE CPR Doppler velocity measurement accuracy as well as the Level 2 standard products for precipitation in Antarctica and at many other ground observation sites. • Synergy between 24 GHz Micro Rain Radar and disdrometer is used by K2W methodology • 94 GHz Doppler Spectra below 1 km were obtained in Antarctica • CloudSat radar reflectivity was evaluated within 0.2 dB by K2W • EarthCARE radar Doppler velocities are expected to be evaluated within 0.2 m s−1 • The wide applicability of K2W hugely raises opportunities for EarthCARE validation [ABSTRACT FROM AUTHOR]

Wildfires are unintentional fires that damage natural environments but do also contribute to ecological sustainability. Monitoring wildfires is therefore a vital component in the management of natural ecosystems. Remote sensing techniques such as burn indices derived from optical data have been used widely to monitor wildfires. The most prevalent focus within the literature of remote sensing of wildfires is on wildfires that occur in large plant forms such as forests and savannas (e.g., Xulu et al., 2021; Shekede et al., 2021). Many studies have applied remote sensing in the mapping of wildfires in South Africa; however, most of these studies focused on the use of a ingle type of remotely sensed data, mainly optical data (e.g., Ngadze et al., 2020; Urban et al., 2020; Belenguer-Plomer et al., 2021). The use of optical data is limited to convenient seasons since technology works optimally in cloud free conditions. In contrast, RADAR has the ability to penetrate clouds, and therefore there is a need to explore the utility of RADAR to map fire burns. [ABSTRACT FROM AUTHOR]

We demonstrate the feasibility of solving atmospheric remote sensing problems with machine learning using conditional generative adversarial networks (CGANs), implemented using convolutional neural networks. We apply the CGAN to generating two‐dimensional cloud vertical structures that would be observed by the CloudSat satellite‐based radar, using only the collocated Moderate‐Resolution Imaging Spectrometer measurements as input. The CGAN is usually able to generate reasonable guesses of the cloud structure and can infer complex structures such as multilayer clouds from the Moderate‐Resolution Imaging Spectrometer data. This network, which is formulated probabilistically, also estimates the uncertainty of its own predictions. We examine the statistics of the generated data and analyze the response of the network to each input parameter. The success of the CGAN in solving this problem suggests that generative adversarial networks are applicable to a wide range of problems in atmospheric science, a field characterized by complex spatial structures and observational uncertainties. Key Points: We trained a generative adversarial network (GAN) to generate cloud vertical structuresThe network generates plausible CloudSat scenes, given MODIS data as an inputThis demonstrates the potential usefulness of GANs in atmospheric science [ABSTRACT FROM AUTHOR]

During the past decades, radar sounder (RS) instruments have been effectively used to detect subglacial lakes (SLs). SLs appear as flat, smooth, and bright reflectors in RS radargrams. The visual interpretation has been the main approach to SL detection in radargrams. However, this approach is subjective and inappropriate for processing large amounts of radargrams. While the analysis of RS data for understanding the subglacial hydrology has recently received increased attention, the literature on the development of automatic methods specifically designed for SL detection is still limited. In order to fill this gap, in this paper, we propose a novel automatic technique for SL detection. The technique is made up of two steps: 1) feature extraction and 2) automatic detection. In the first step, we define and extract three families of features for discriminating between the lake and nonlake radar reflections. The features model locally the basal topography, the shape of the basal reflected waveforms, and the statistical properties of the basal signal. In the second step, we provide the features as input to a support vector machine classifier to perform the automatic SL detection. The proposed technique has been applied to radargrams acquired over two large regions in East Antarctica and Siple Coast. The obtained results, which are validated both quantitatively and qualitatively, confirm the robustness of the features and their capabilities to effectively characterize SLs. Moreover, they prove the potentiality of the method to process large amounts of radargrams and update the current SL inventory. [ABSTRACT FROM AUTHOR]

The ability of in situ snowflake microphysical observations to constrain estimates of surface snowfall accumulations derived from coincident, ground-based radar observations is explored. As part of the High-Latitude Measurement of Snowfall (HiLaMS) field campaign, a Micro Rain Radar (MRR), Precipitation Imaging Package (PIP), and Multi-Angle Snow Camera (MASC) were deployed to the Haukeliseter Test Site run by the Norwegian Meteorological Institute during winter 2016/17. This measurement site lies near an elevation of 1000 m in the mountains of southern Norway and houses a double-fence automated reference (DFAR) snow gauge and a comprehensive set of meteorological observations. MASC and PIP observations provided estimates of particle size distribution (PSD), fall speed, and habit. These properties were used as input for a snowfall retrieval algorithm using coincident MRR reflectivity measurements. Retrieved surface snowfall accumulations were evaluated against DFAR observations to quantify retrieval performance as a function of meteorological conditions for the Haukeliseter site. These analyses found differences of less than 10% between DFAR- and MRR-retrieved estimates over the field season when using either PIP or MASC observations for low wind "upslope" events. Larger biases of at least 50% were found for high wind "pulsed" events likely because of sampling limitations in the in situ observations used to constrain the retrieval. However, assumptions of MRR Doppler velocity for mean particle fall speed and a temperature-based PSD parameterization reduced this difference to +16% for the pulsed events. Although promising, these results ultimately depend upon selection of a snowflake particle model that is well matched to scene environmental conditions. [ABSTRACT FROM AUTHOR]

By using long pulses with extended dwell time, radar sensitivity is enhanced such that more clear-air returns are usable. This enhanced capability can increase clear-air data coverage and provide additional information for radar wind analysis and data assimilation. To explore this potential capability and related benefits, a new scan mode with long pulses and low antenna rotation rate is derived from the existing clear-air scan mode and applied to the named KOUN S-band test bed radar at NSSL. Velocities collected using this newly modified scan mode are significantly enhanced in data coverage compared to those collected with the unmodified scan mode from the nearby test bed radar (named KCRI). However, transmitter duty cycle limits the pulse repetition frequency (PRF) to 455 Hz for the long pulses, which reduces the Nyquist velocity to 12.53 m s−1 for the new scan mode. Such a small Nyquist interval leads to significantly worse problems with aliased velocities. A recently developed dealiasing algorithm is modified by using external reference velocities from KCRI to overcome increased difficulties in dealiasing, making the velocities from KOUN useful over increased range and area. This implies that similar increases in velocity data coverage can be achieved without using external reference velocities if the newly modified scan is paired with an unmodified scan into dual-PRF scans. This dual-PRF approach is proposed for future development. [ABSTRACT FROM AUTHOR]

A hybrid, empirical radar wave inversion technique that treats swell and wind waves separately is presented and evaluated using a single 48-MHz radar unit and in situ wave measurements. This hybrid approach greatly reduces errors in radar wave inversion during swell seas. Our analysis suggests that, prior to the inversion, the second-order spectrum should be normalized using Barrick's weighting function because this process removes harmonic and corner reflection peaks from the inversion and improves the results. In addition, the resulting calibration constants for the wind wave component are not wave-frequency dependent and are similar in magnitude to those found in previous studies using different operating-frequency radars. This result suggests radar frequency independence, although additional experimental verification is required. The swell component of the model presented here ignores the effect of swell's propagation direction on the radar signal. Although this approach has several limitations and may only be useful near the coast (where swell propagates close to perpendicular to the coastline), the resulting wave inversion is accurate even when swell is propagating close to perpendicular to the radar beam direction. RMS differences relative to in situ wave height measurements range from 0.16 to 0.25 m as the radar beam angle increases from 22° to 56°. [ABSTRACT FROM AUTHOR]

Quadratically varying phase codes applied from pulse to pulse can be used to impart a range-dependent frequency shift in the decoded signal of a pulsed radar. Radars employing such codes can operate at extremely high pulse repetition frequencies (PRFs) with overlaid signals from multiple echo trips separated in the spectral domain. When operating at high PRFs, the radar duty cycle can approach 50% in a single-antenna system. High duty cycle operation results in a substantial increase in average transmit power with a proportional increase in signal processing gain as compared to a conventional pulsed radar. The shortest quadratic phase code, or base code, has a length equal to the number of echo trips M that can be unambiguously resolved in the spectral domain. The decoded waveform is essentially free from range sidelobes under ideal conditions. However, amplitude and phase errors associated with nonideal phase coding result in range sidelobes that appear at all echo trips in the decoded signal. These sidelobes can be suppressed by using a composite phase code composed of a periodically repeating base phase code added to a much longer quadratic code with a proportionally slower phase variation. Meteorological data gathered with a Ka-band radar operating at 3.0-MHz PRF at 45% duty cycle are presented. A comparison of these data with data gathered in short-pulse mode at a duty cycle of 0.3% exhibited a 21-dB improvement in the Doppler spectrum signal-to-noise ratio, equal to the ratio of the respective duty cycles. [ABSTRACT FROM AUTHOR]

The aim of this investigation was to establish the validity of a GPS-based tracking system (Polar Team Pro System, PTPS) for estimating sprint performance and to evaluate additional diagnostic indices derived from the temporal course of the movement velocity. Thirty-four male soccer players (20 ± 4 years) performed a 20 m sprint test measured by timing gates (TG), and while wearing the PTPS. To evaluate the relevance of additional velocity-based parameters to discriminate between faster and slower athletes, the median-split method was applied to the 20-m times. Practical relevance was estimated using standardized mean differences (d) between the subgroups. Differences between the criterion reference (TG) and PTPS for the 10 and 20 m splits did not vary from zero (dt10: -0.01 ± 0.07 s, P = 0.7, d < -0.1; dt20: -0.01 ± 0.08 s, P = 0.4, d < -0.2). Although subgroups revealed large differences in their sprint times (d = -2.5), the average accelerations between 5 and 20 km/h as well as 20 and 25 km/h showed merely small effects (d < 0.5). Consequently, analyses of velocity curves derived from PTPS may help to clarify the occurrence of performance in outdoor sports. Thus, training consequences can be drawn which contribute to the differentiation and individualization of sprint training. [ABSTRACT FROM AUTHOR]

In this work, a mechanism is proposed to enhance the remote sensing accuracy of conducting objects located within continuous random media. Through our mechanism, operating frequency would be selected properly for preciously radar detection. In this regard, numerical analysis for the influence of medium characteristics on the radar cross section (RCS) is conducted. Illumination region is assumed as partially convex surface while considering targets having large sizes of about four wavelengths. We handle the effect of various parameters such as the medium randomness intensity and scale size, target configuration having curvature and size and incident waves polarization. Waves are backscattering from objects in both free space and random medium while considering horizontal polarization of incident waves. Such polarization generates creeping waves in which they have an extra impact on the backscattering waves where would be avoided through our mechanism. [ABSTRACT FROM AUTHOR]

Fire has a diverse range of impacts on Earth's physical and social systems. Accurate and up to date information on areas affected by fire is critical to better understand drivers of fire activity, as well as its relevance for biogeochemical cycles, climate, air quality, and to aid fire management. Mapping burned areas was traditionally done from field sketches. With the launch of the first Earth observation satellites, remote sensing quickly became a more practical alternative to detect burned areas, as they provide timely regional and global coverage of fire occurrence. This review paper explores the physical basis to detect burned area from satellite observations, describes the historical trends of using satellite sensors to monitor burned areas, summarizes the most recent approaches to map burned areas and evaluates the existing burned area products (both at global and regional scales). Finally, it identifies potential future opportunities to further improve burned area detection from Earth observation satellites. • A review of burned area trends in past 40 years of RS is performed. • Different sensors used for BA mapping presented, including Radar and Lidar. • Main burned area products are commented [ABSTRACT FROM AUTHOR]

The traditional U-turn design has significantly improved traffic operations for relieving traffic congestion. However, the U-turn diversion and merge segments still cause traffic conflicts and delays. In this paper, an exclusive spur dike U-turn lane (ESUL) is proposed with the aim of addressing the disadvantages of the traditional U-turn design. ESUL provides a separate U-turn lane to diverge, decelerate, U-turn, accelerate and merge without interacting with through traffic. The effectiveness of ESUL is demonstrated through a field data investigation, simulation and analysis with VISSIM software. The proposed design is evaluated in terms of three parameters: travel time, delay and number of stops. Compared to the traditional U-turn design, ESUL can reduce travel time by 29.15%, delay by 66.70% and the number of stops by 100% at most. The results showed that ESUL has better performance than the traditional U-turn design and could be implemented to reduce traffic congestion and the potential hazards caused by U-turn maneuvers. [ABSTRACT FROM AUTHOR]

Interference among frequency modulated continues wave automotive radars can either increase the noise floor, which occurs in the most cases, or generate a ghost target in rare situations. To address the increment of noise floor due to interference, we proposed a low calculation cost method using adaptive noise canceller to increase the signal-to-interference ratio. In a quadrature receiver, the interference in the positive half of frequency spectrum is correlated to that in the negative half of frequency spectrum, whereas the beat frequencies from real targets are always present in the positive frequency. Thus, we estimated the power of the negative frequency as an indication of interference, and fed the positive frequency and negative frequency components into the primary and reference channel of an adaptive noise canceller, respectively. The least mean square algorithm was used to solve for the optimum filter solution. As a result, both the simulation and experiment showed a good interference mitigation performance. [ABSTRACT FROM AUTHOR]

The purpose of Fuzzy Comprehensive CS-SVR Model (FCCS-SVR) is to evaluate and monitor the health status of a radar equipment and then keep its safe operation. Due to reasons such as few samples, slow changes and the nonlinear structure of data of fault monitoring signal, the health status evaluation of a radar system is quite difficult. By establishing the evaluation index system of a radar, the combination of AHP method and Entropy weight method is studied in this paper. In order to evaluate the value of health status, several optimization algorithms including PSO, GA, BA and CS are used for optimizing the parameters of SVR model. Meanwhile, in order to avoid the problem that the system is at the edge of the state, a radar health assessment method based on the combination of Fuzzy Comprehensive Evaluation and Cuckoo Search-Support Vector Regression (CS-SVR), which is named as Fuzzy Comprehensive CS-SVR (FCCS-SVR), is further proposed. The result of case analysis reflects that the state evaluation of the radar system is realized. The system performance analysis shows that the use of FCCS-SVR evaluation method provides a high recognition rate and can accurately assess the health status of the radar system. [ABSTRACT FROM AUTHOR]

Fisheries compete with seabirds for vanishing marine resources, but also produce fishery waste consumed by seabirds. Marine birds may therefore avoid or seek fishing vessels, and have evolved complex, plastic behavioural responses to vessel presence. Understanding these responses is essential to the conservation of a globally declining seabird community. We studied Cape gannets (Morus capensis), which compete with fisheries for reduced sardine (Sardinops sagax) resources in the Benguela upwelling region off South Africa. Using bird-borne GPS trackers coupled with newly-developed ship-radar detectors we show that foraging gannets seldom attended fishing vessels. Rather, they switched from eating scarce sardines or energetically-poor fishery waste to targeting locally abundant saury (Scomberesox saurus). This pelagic fish is brought into the seascape by warm water influx, and is not commercially exploited by fisheries. Cape gannets thereby show dietary plasticity, allowing them to maintain adult body condition and chick growth rates. This diet switch is a strong indicator that Cape gannets forage in an ecologically perturbed marine environment. [ABSTRACT FROM AUTHOR]

A three-dimensional (3D) image reconstruction method for the spinning target based on the radar network is proposed in this letter and the design concept is sourced from the similarity of the two-dimensional (2D) imaging result with the target’s mapping on the imaging plane. The proposed method has the capacity to generate 3D image of the spinning target by reconstructing the scattering distribution in 3D Cartesian space. Firstly, the inverse Radon transform is applied to obtain the imaging result of the spinning target and the mapping formulas for mapping the air points onto the 2D image plane are derived. In addition, the radar network 3D image reconstruction model for the spinning target is constructed and the corresponding algorithm for solving the reconstruction model is proposed. Finally, some experiment results are given to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The problem considered is that of estimating unambiguously migrating targets observed with a wideband radar. We extend a previously described sparse Bayesian algorithm to the presence of diffuse clutter and off-grid targets. A hybrid-Gibbs sampler is formulated to jointly estimate the sparse target amplitude vector, the grid mismatch, and the (assumed) autoregressive noise. Results on synthetic and fully experimental data show that targets can be actually unambiguously estimated even if located in blind speeds. [ABSTRACT FROM AUTHOR]

Multiplatform measurements of the active and passive instruments from A‐Train were employed to observationally characterize particle structures over a spectrum of precipitating clouds from shallow cumulus to deep convection. Radar reflectivity profiles were composited as a function of temperature, with particle type superimposed to depict how storm regimes exert different particle habit structures. The deep convective system was found to have a relatively simple structure, which is dominated by randomly oriented ice, followed by snow and rain at the bottom, whereas the shallow cold system consisting high cloud tops with precipitation far below contains various hydrometeors, such as ice plates and drizzles. The deep convective system was further analyzed to demonstrate how the vertical microphysical structure tends to systematically transition from nonprecipitating to precipitating characteristics with differing cloud top buoyancies indicative of the "life stage" of convective development. The analysis offers a link between dynamical characteristics of convective systems and their inner hydrometeors structures. Plain Language Summary: Clouds are composed of liquid water droplets and condensed ice crystals or a mixture of both. Compared to liquid droplets, ice crystals are generally larger in size and, even with the same mass, allow more sunlight to reach the Earth's surface. Ice crystals also grow faster and end up falling as snow or melted rain, shortening the lifetime of a cloud. The phase states of these liquid and ice particles do not only persist over the lifetime of the cloud, but thermodynamic transitions between them often occur. Although these cloud‐precipitation and thermodynamic phase processes occur in the vertical direction of the atmosphere, the vertical internal phase compositions of cloud‐precipitation systems are still an open question in the atmospheric sciences, resulting in uncertainties in the surface temperature estimations in warmed atmospheres. In our study, we integrated independent measurements from space, analyzed various precipitating clouds from shallow to towering convective systems, and revealed variabilities in the vertical particle constituents among the precipitating cloud regimes. Studying the "static" measurement in a more "dynamical" context, we also show the observational insight of how the vertical structure of deep convective systems changes from "cloud mode" to "precipitation mode" during the course of their development. Key Points: Characterized vertical structures of global precipitating clouds over the spectrum of storm regimes from shallow cumulus to deep convectionIdentified clear differences in hydrometeor constituents, including particle phase and shapes, depending on the precipitating cloud systemsDeep convective system exerted transition of its microphysical structure from nonprecipitating to precipitating mode with changing buoyancy [ABSTRACT FROM AUTHOR]

Abstract LabOSat (acronym for "Laboratory On a Satellite") is a type of electronic platform designed to perform experiments in harsh, remote environments. Up to now, LabOSat platforms have been used mainly for characterizing and validating custom and commercial electronic devices at Low Earth Orbits (LEO). Many of these platforms are running experiments aboard ÑuSat satellites, which are built and operated by Argentine company Satellogic. A brief description of LabOSat platforms is presented here, along with details of their validation both at LEO and at a nuclear reactor. The electrical characterization of custom non-volatile memory cells — as performed by a LabOSat platform at LEO — is also described, and the results of such experiment are compared with results obtained on Earth. The memory cells studied were TiO 2 -based and La 1/3 Ca 2/3 MnO 3 -based ReRAM devices. Highlights • LabOSat, a characterization platform, was tested under radiation environments. • Satellite payload: excellent performance at Low Earth Orbits (LEO) in a 3-year mission. • LabOSat platform was used to study ReRAM cells on board microsatellites. • Measurements on ReRAM cells at LEO are in agreement with on-Earth measurements. [ABSTRACT FROM AUTHOR]

In this paper, an ultra-wideband fully integrated imaging radar at sub-terahertz (sub-THz) frequencies is presented, which demonstrates a fine lateral resolution without using any focal lens/mirror. We have achieved a lateral resolution of 2 mm for an object at 23-cm distance as well as a range resolution of 2.7 mm. To achieve the decent range resolution, in a frequency modulation continuous wave radar configuration, a state-of-the-art chirp bandwidth (BW) of 62.4 GHz at a center frequency of 221.1 GHz is generated and efficiently radiated. We have presented a design technique for the optimal design of the passive embedding around the core transistor to maximize the tuning BW of the voltage controlled oscillator. At the receiver side, to maximize the intermediate frequency level, a subharmonic mixer is utilized, which is designed for the lowest conversion loss. Finally, to obtain the fine lateral resolution, we have implemented near-field beamforming algorithm based on the inverse synthetic aperture radar (ISAR) systems. The synthesized beamwidth is less than 0.5°; hence, high-resolution images are reconstructed. The system is fabricated in a 55-nm BiCMOS process. To the best of our knowledge, this is the first imaging radar at THz/sub-THz frequencies, which utilizes ISAR to achieve a high lateral resolution while the radar system is fully integrated. [ABSTRACT FROM AUTHOR]

Remote sensing is a particularly suitable tool for monitoring land use but also particularly suited for déforestation monito-ring. By launching the Setinel-1 and Sentinel-2 satellites in the Copernicus program, the community now has free data with important time-revisits allowing the greatest number of people to effectively monitor land cover of a study area. This paper présents a land use monitoring method based on the combination of two approaches computed using Open Source tools (QGIS, Orfeo ToolBox, python). First, we focus on land use monitoring at an annual time scale using Sentinel-1 and Sentinel-2 data, and then, by the use f entienl-1 data, we detect changes in the forest cover due to déforestation at bi-monthly time scale. The results obtained show a very good synergy of thèse approaches allowing the complementary of optical and radar data. In order to make accessible the proposed method, ail the used open source tools are available on this link http ://remotesensing4all.net/index.php/2018/09/11/kit-use-des-donnees-radar-sentinel-1-in-de-latelier-radar-du-FOSS4G-en-2018-2/. [ABSTRACT FROM AUTHOR]

Instantaneous liquid-equivalent snowfall rates S retrieved from CloudSat W-band cloud radar reflectivity Ze measurements are compared to estimates of S from operational Weather Surveillance Radar-1988 Doppler (WSR-88D) systems when the CloudSat satellite overflew the ground-based radar sites during spatially extensive nimbostratus snowfall events. For these comparisons, the ground-based radar measurements are interpolated to closely match in space and time spaceborne radar resolution volumes above ground clutter, thus avoiding uncertainties in deriving near-surface snowfall rates from measurements aloft by both radar types. Although typical uncertainties of both ground-based and spaceborne snowfall-rate retrieval approaches are quite high, the results from the standard optimal estimation CloudSat 2C-SNOW-PROFILE algorithm are on average in good agreement with the WSR-88D default snowfall algorithm results with correlation coefficients being around 0.8–0.85. The CloudSat standard optimal estimation snowfall-rate products are also shown to be in satisfactory agreement with retrievals from several simple W-band Ze–S relations suggested earlier. The snowfall rate and snow/ice water content (IWC) parameters from the CloudSat 2C-SNOW-PROFILE algorithm are highly interdependent. A tight relation between S and IWC is apparently introduced through the ice particle fall velocity assumption that is made in the reflectivity-based snowfall retrieval algorithm. This suggests that ice sedimentation rate estimates can also be deduced from applications of numerous empirical IWC–reflectivity relations derived previously for different cloud conditions when appropriate assumptions about fall velocities are made. Intercomparisons between different CloudSat snow/ice water content products indicated significant discrepancies in IWC values from different standard CloudSat retrieval algorithms. [ABSTRACT FROM AUTHOR]

Accurate and automated dealiasing of radar data is important for data interpretation and downstream applications such as numerical weather prediction (NWP) models. In this paper an improved radial velocity dealiasing scheme is presented and evaluated using observations from several S-band radars under the severe weather conditions of typhoons and hurricanes. This scheme, named Automated Dealiasing for Typhoon and Hurricane (ADTH), is a further development of the China New Generation Doppler Weather Radar (CINRAD) improved dealiasing algorithm (CIDA). The upgraded algorithm ADTH includes three modules designed to select the first radial from which the dealiasing process starts, to conduct a two-way multipass dealiasing, and to perform an error check for a final local dealiasing. The dealiasing algorithm is applied to two typhoon hurricane cases and four typhoon cases observed with radars from CINRAD, NEXRAD of the United States, and the Taiwan radar network for a continuous period of 12 h for each of the selected cases. The results show that ADTH outperforms CIDA for all of the test cases. [ABSTRACT FROM AUTHOR]

This paper constructed a stacked-autoencoder neural network model (SAE model) to estimate sea state bias (SSB) based on radar altimeter data. Six cycles of the geophysical data record (GDR) from Jason-1/2 radar altimeters were used as a training dataset, and the other 2 cycles of the GDR from Jason-1/2 were used for testing. The inputs to this SAE model include the significant wave height (SWH), wind speed (U), sea surface height (SSH), backscatter coefficient (σ0) and automatic gain control (AGC), and the model outputs the SSB. The model includes one input layer, three hidden layers and one output layer. The SSBs in the GDR of Jason-1/2 were obtained from a nonparametric model based on the SWH and U as input variables; thus, the model has high accuracy but low efficiency. The SSBs in the GDR of HY-2A were computed using a four-parameter parametric model that uses the SWH and U as input variables; therefore, this model’s computational speed is high but its accuracy is low. Thus, we used the HY-2A radar altimeter as an unseen validation dataset to evaluate the performance of the SAE model. Then, we analyzed the contrasting results of these methods, including the differences in the SSB, explained variance, residual error and operational efficiency. The results demonstrate not only that the accuracy of the SAE model is superior to that of the conventional parametric model but also that its operational efficiency is better than that of the nonparametric model. [ABSTRACT FROM AUTHOR]

Purpose An interactive processing scheme is proposed to improve the target detection probability as well as the tracking performance of the radar system.Design/methodology/approach Firstly, with the spatial-correlated features extracted from the foreground and background statistical models, the thresholds were adapted to distinguish the dim small targets from clutters in the complex incoherent radar images. Then, the target trajectories were constructed with the target tracking algorithm. According to the temporal correlation with the target life cycle, the thresholding values were modified in the neighbourhood of the predicted positions to improve the detection sensitivity in these areas during the tracking process. Finally, the temporal-correlated features of the remained clutters were used to further reduce the false alarm rate.Findings The proposed algorithm was applied on the simulated data, as well as the image sequences obtained with the incoherent marine radars. The detection results demonstrated that the interactive algorithm could detect and track the dim small targets with relatively low false alarm rate.Practical implications The interactive processing scheme could be applied for low-altitude airspace surveillance with incoherent marine radar.Originality/value The proposed scheme outperforms the classical radar target detection algorithms and the state-of-the-art image processing algorithms for video-based surveillance. [ABSTRACT FROM AUTHOR]

Lakes are a key geographical feature in Canada and have an impact on the regional climate. In the winter, they are important for recreational activities such as snowmobiling and ice fishing and act as part of an important supply route for northern communities. The ability to accurately report lake ice characteristics such as thickness is vital, however, it is underreported in Canada and there is a lack of lake ice thickness records for temperate latitude areas such as Central Ontario. Here, we evaluate the application of previously developed temperature models and RADARSAT-2 for estimating lake ice thickness in Central Ontario and provide insight into the regions long term ice thickness variability. The ALS Environmental Science Shallow Water Ice Profiler (SWIP) was used for validation of both temperature and radar-based models. Results indicate that the traditional approach that uses temperatures to predict ice thickness during ice growth has low RMSE values of 2.3 cm and correlations of greater than 0.9. For ice decay, similar low RMSE values of 2.1 cm and high correlations of 0.97 were found. Using RADARSAT-2 to estimate ice thickness results in R2 values of 0.6 (p < 0.01) but high RMSE values of 11.7 cm. Uncertainty in the RADARSAT-2 approach may be linked to unexplored questions about scattering mechanisms and the interaction of radar signal with mid-latitude lake ice. The application of optimized temperature models to a long-term temperature record revealed a thinning of ice cover by 0.81 cm per decade. [ABSTRACT FROM AUTHOR]

Satellite remote sensing has made great strides in the last few decades, which enables the long-term consistent observations of many variables of the terrestrial water cycle and thus advances the understanding of the terrestrial water cycle. This paper reviews the principles of remote sensing in retrieving key variables of the terrestrial water cycle, illustrates the progress of satellite remote sen-sing in hydrological applications, and discusses the future direction. Although most of hydrological states and fluxes variables are observable by remote sensing, closing terrestrial water budget with the remote sensing products is still an open question, suggesting more efforts are needed to improve the hydrological consistency of the remote sensing products. In the future, efforts should be made to develop new generation sensors and platforms for the consistent remote sensing products with finer spatiotemporal resolution. At the same time, efforts should be devoted to the evaluation of remote sen-sing products of the terrestrial water cycle through carrying out integrated field experiments. [ABSTRACT FROM AUTHOR]

This paper introduces a new concept of slow-time spatial frequency space, also known as “slow-time $k$ -space,” and redefines the associated cross-range bandwidth, which arises naturally from Doppler radar tomography. The slow-time $k$ -space is the most suitable for narrow-band radar imaging, and can be augmented for higher resolution imaging by appropriate signal processing. The respective relationships with the more traditional concepts of fast-time $k$ -space and signal (or range) bandwidth are explained. We also discuss image resolution limits and demonstrate the concepts with simulated data examples. [ABSTRACT FROM AUTHOR]