High-resolution Radar Data Research Articles

Promising Oldest Ice sites in East Antarctica based on thermodynamical modelling

Abstract. To resolve the mechanisms behind the major climate reorganisation, which occurred between 0.9 and 1.2 Ma, the recovery of a suitable 1.5 million-year-old ice core is fundamental. The quest for an Oldest Ice core requires a number of key boundary conditions, of which the poorly known basal geothermal heat flux (GHF) is lacking. We use a transient thermodynamical 1-D vertical model that solves for the rate of change of temperature in the vertical, with surface temperature and modelled GHF as boundary conditions. For each point on the ice sheet, the model is forced with variations in atmospheric conditions over the last 2 Ma and modelled ice-thickness variations. The process is repeated for a range of GHF values to determine the value of GHF that marks the limit between frozen and melting conditions over the whole ice sheet, taking into account 2 Ma of climate history. These threshold values of GHF are statistically compared to existing GHF data sets. The new probabilistic GHF fields obtained for the ice sheet thus provide the missing boundary conditions in the search for Oldest Ice. High spatial resolution radar data are examined locally in the Dome Fuji and Dome C regions, as these represent the ice core community's primary drilling sites. GHF, bedrock variability, ice thickness and other essential criteria combined highlight a dozen major potential Oldest Ice sites in the vicinity of Dome Fuji and Dome C, where GHF could allow for Oldest Ice.

Nowcasting of Precipitation in the High-Resolution Dallas–Fort Worth (DFW) Urban Radar Remote Sensing Network

Short-term forecasting (nowcasting) of rainfall is widely used in providing early warning, and therefore, has very practical application. The CASA demonstration network deployed in the Dallas–Fort Worth (DFW) area consists of high-resolution X-band radars deployed around the National Weather Service Radar WSR-88D, and nowcasting of precipitation is an important product of this network. The current nowcasting technique DARTS was developed in frequency domain using fast Fourier transforms in order to provide nowcasts in a computationally efficient manner. Building on the earlier work on the CASA Project and the STEPS methodology, a stochastic nowcasting method is developed and tested for the first time in a small-scale urban environment using high-resolution radar data. The key idea is to decompose the reflectivity field into multiple spatial scales and generate stochastic perturbations in each scale to account for uncertainties in the nowcasts. It is shown that the proposed method can produce reliable nowcasts and uncertainty estimates up to 45 min and performs as well or better than DARTS in terms of the standard critical success index and mean error verification scores. Using the scale decomposition of STEPS, a power–law relationship is derived between the spatial scale and Lagrangian lifetime of precipitation on scales between 500 m and 50 km.

Evaluation of Atmospheric Effects on Interferograms Using DEM Errors of Fixed Ground Points.

High-resolution synthetic aperture radar (SAR) data are widely used for disaster monitoring. To extract damaged areas automatically, it is essential to understand the relationships among the sensor specifications, acquisition conditions, and land cover. Our previous studies developed a method for estimating the phase noise of interferograms using several pairs of TerraSAR-X series (TerraSAR-X and TanDEM-X) datasets. Atmospheric disturbance data are also necessary to interpret the interferograms; therefore, the purpose of this study is to estimate the atmospheric effects by focusing on the difference in digital elevation model (DEM) errors between repeat-pass (two interferometric SAR images acquired at different times) and single-pass (two interferometric SAR images acquired simultaneously) interferometry. Single-pass DEM errors are reduced due to the lack of temporal decorrelation and atmospheric disturbances. At a study site in the city of Tsukuba, a quantitative analysis of DEM errors at fixed ground objects shows that the atmospheric effects are estimated to contribute 75% to 80% of the total phase noise in interferograms.

Analysis of the 16 May 2015 Tipton, Oklahoma, EF-3 Tornado at High Spatiotemporal Resolution Using the Atmospheric Imaging Radar

Abstract In this study, data collected by the Atmospheric Imaging Radar (AIR) are analyzed in conjunction with WSR-88D data (KFDR) for a tornado near Tipton, Oklahoma, on 16 May 2015. The analysis presented herein utilizes PPIs from both radars, polarimetric data from KFDR, time–height plots from the AIR, and a ground-based velocity track display (GBVTD) analysis. This study is novel in that it uses high-resolution mobile radar data (update time of 6–7 s) in tandem with polarimetric data from KFDR in order to identify possible areas of debris, including a debris ring contained within the outer vortex circulation. Leveraging the high spatiotemporal resolution of the AIR with the polarimetric capability of KFDR leads to analysis of reflectivity distributions, debris lofting, kinematic changes, and oscillations in tornado intensity during a portion of the mature stage of the tornado, with a particular focus on the relationship between changes in the reflectivity field and dynamical changes around the tornado. Debris is lofted in a high-reflectivity concentric ring of increasing radius and height around the tornado over several minutes, within the outer weak-echo hole (WEH). Simultaneously, debris lofting and asymmetric reflectivity distribution around the WEH coincide with changes in vortex tilt on multiple occasions. In one instance, hydrometeor fallout appears to precede a possible descending reflectivity core. Using the GBVTD results, near-surface convergence intensifies at the same time and location as when the debris ring is lofted. Additionally, strengthening of the tornado via multiple modes of vertical evolution (i.e., bottom-up intensification over time vs simultaneous intensification throughout the lowest few hundred meters) is observed.

Uncertainty analysis of urban sewer system using spatial simulation of radar rainfall fields: New York City case study

The goal of this study is to investigate the uncertainty of an urban sewer system’s response under various rainfall and infrastructure scenarios by applying a recently developed nonparametric copula-based simulation approach to extreme rainfall fields. The approach allows for Monte Carlo simulation of multiple variables with differing marginal distributions and arbitrary dependence structure. The independent and identically distributed daily extreme rainfall events of the corresponding urban area, extracted from nationwide high resolution radar data stage IV, are the inputs of the spatial simulator. The simulated extreme rainfall fields were used to calculate excess runoff using the Natural Resources Conservation Service’s approach. New York City is selected as a case study and the results highlight the importance of preserving the spatial dependence of rainfall fields between the grids, even for simplified hydrologic models. This study estimates the probability of combined sewer overflows under extreme rainfall events and identifies the most effective locations in New York City to install green infrastructure for detaining excess stormwater runoff. The results of this study are beneficial for planners working on stormwater management and the approach is broadly applicable because it does not rely on extensive sewer system information.

The Hamburg Tornado (7 June 2016) from the perspective of low-cost high-resolution radar data and weather forecast model

A tornado hit the northeastern suburbs of Hamburg, Germany, on 7 June 2016. It had an estimated strength of upper end F1 on the Fujita scale and was short-lived with an approximate duration of only 13 min and a path length of just about 1.3 km. We demonstrate that such a small-scale, extreme event can be observed and forecasted accurately by a low-cost radar and by an atmospheric model with low computational costs, respectively.Observations from a low-cost single polarized X-band radar covering the urban area of Hamburg with 60 m spatial and 30 s temporal resolution are analyzed with respect to their ability to capture the development as well as the track of the tornado. In contrast to the national C-band radar network, the X-band radar is capable of capturing the hook echo of the tornado as well as the circular pattern in rain rates, because of its higher resolution in space and time.High-resolution forecasts of the tornado event are conducted with the computational efficient Conformal Cubic Atmosphere Model (CCAM) in order to test the capability of predicting the tornado with a lead time of a few hours. A three step downscaling method is used to obtain a spatial resolution of 1 km with initial conditions taken from the NCEP analysis. Calculated severe weather indices clearly indicate a potential for a tornado. CCAM cannot explicitly resolve small scale tornadic features but the model simulates a strong convective cell only a few kilometers apart from the tornadic thunderstorm observed by the radar.

Urban landscape monitoring based on high-resolution spaceborne TerraSAR-X data: a case study of Nanjing City, China

ABSTRACTRecently, the performance of high-resolution spaceborne synthetic aperture radar (SAR) data for urban landscape monitoring has attracted increased interest, in particular for regions where rainy weather prevails throughout of year. In this study, the phase component of SAR data was exploited for landscape monitoring in the western area of Nanjing city, China. Twenty-six scenes of TerraSAR-X single-look complex (SLC) interferometric images were acquired for the period of May 2013 to February 2015 and applied for urban change detection as well as surface subsidence monitoring by means of interferometric SAR (InSAR) technologies. Firstly, a small baseline strategy in conjunction with a fast statistically homogeneous pixel selection (FaSHPS) approach were applied for the coherence imagery generation and for the coherent change detection, resulting in a correct probability of better than 90%. Second, the surface deformation was derived with millimetre accuracy using an enhanced multi-temporal InSAR (MT-InSAR) tool by synergistically analyzing the amplitudes and phases of the SAR acquisitions. This study indicates that high-resolution SAR data have the potential for urban landscape monitoring by taking advantage of the interferometric performance and the all-day and all-weather imaging capability.

Enhanced object-based tracking algorithm for convective rain storms and cells

This paper proposes a new object-based storm tracking algorithm, based upon TITAN (Thunderstorm Identification, Tracking, Analysis and Nowcasting). TITAN is a widely-used convective storm tracking algorithm but has limitations in handling small-scale yet high-intensity storm entities due to its single-threshold identification approach. It also has difficulties to effectively track fast-moving storms because of the employed matching approach that largely relies on the overlapping areas between successive storm entities. To address these deficiencies, a number of modifications are proposed and tested in this paper. These include a two-stage multi-threshold storm identification, a new formulation for characterizing storm's physical features, and an enhanced matching technique in synergy with an optical-flow storm field tracker, as well as, according to these modifications, a more complex merging and splitting scheme. High-resolution (5-min and 529-m) radar reflectivity data for 18 storm events over Belgium are used to calibrate and evaluate the algorithm. The performance of the proposed algorithm is compared with that of the original TITAN. The results suggest that the proposed algorithm can better isolate and match convective rainfall entities, as well as to provide more reliable and detailed motion estimates. Furthermore, the improvement is found to be more significant for higher rainfall intensities. The new algorithm has the potential to serve as a basis for further applications, such as storm nowcasting and long-term stochastic spatial and temporal rainfall generation.

SARchaeology—Detecting Palaeochannels Based on High Resolution Radar Data and Their Impact of Changes in the Settlement Pattern in Cilicia (Turkey)

The fertile alluvial plain of Cilicia is bordered by the Taurus and Amanus mountain ranges to the west, north and east and the Mediterranean Sea to the south. Since the Neolithic Period, Plain Cilicia was an important interface between Anatolia and the Levant. The alluvial plain is dominated by three rivers: Tarsus, Seyhan and Ceyhan. The avulsion history of the lower course of the rivers Seyhan and Ceyhan during the Holocene remains an unresolved issue. The knowledge about how former river courses have changed is essential for the identification of ancient toponyms with archaeological sites. The analysis of silted up riverbeds based on high-resolution digital elevation models (TanDEM-X) and historic satellite imagery (CORONA) in this paper provide the first indications for the reconstruction of former river channels. Further evidence is given by the evaluation of the settlement patterns from 3rd to 1st millennium BC.

Position and variability of complex structures in the central East Antarctic Ice Sheet

Abstract Although the flow of the East Antarctic Ice Sheet is well constrained from surface measurements and altimetry, our knowledge of the dynamic processes within the ice sheet remains limited. Recent high-resolution radar data from the Gamburtsev Subglacial Mountains in central East Antarctica reveal a series of anomalous englacial reflectors in the lower half of the ice column that cannot be explained by conventional ice flow. Expanding on previous analyses, we describe the geometrical and morphological features of 12 of these anomalous reflectors. Our description reveals a previously unacknowledged diversity in size, geometry and internal structure of these reflectors. We are able to identify four distinct morphological features: (1) fingers; (2) inclusions; (3) sheets; and (4) folds. The ‘fingers’ and ‘inclusions’ probably form by shear instabilities at the boundary between the reflectors and the surrounding meteoric ice. The ‘sheets’ highlight that basal ice can be uplifted off of the bed and above surrounding meteoric ice, and the ‘folds’ may have formed in local regions of converging flow associated with subglacial topography. The study provides key insights into the rheology, stress and deformational regimes deep within the central East Antarctic Ice Sheet.

Natural hazard damage detection based on object-level support vector data description of optical and SAR Earth observations

ABSTRACTThe Earth’s land covers are exposed to several types of environmental changes, issued by either human activities or natural disasters. On 11 March 2011, an earthquake occurred at about 130 km of the east coast of Sendai City in Japan. This earthquake has been followed by a huge tsunami, which caused devastating damages over the wide areas in the eastern coastlines of Japan. In order to manage such crises quickly and efficiently, change maps of affected areas are really crucial for damage estimation and proposing the essential services. Therefore, an automatic extraction of inundated and damaged areas from satellite images, with less user interaction, is essential and helpful. So far, the existing change detection (CD) approaches have a low degree of automation and are not optimal and applicable to high resolution optical and radar remote-sensing data. In order to resolve these problems, an integrated object-level CD method based on an object-based classifier and support vector data description method is proposed. In addition, parameter determination of the proposed method is addressed automatically by using an inter-cluster distance based approach. In order to evaluate the efficiency of the proposed method and extract the damaged areas, various optical and radar remote-sensing images from before and after of Sendai 2011’s tsunami, acquired by IKONOS, Radarsat-2, and TerraSAR-X, were used. The accuracy analysis of results showed a great flexibility for CD of by finding nonlinear object-level solutions to the problem. Furthermore, the comparative analysis of experimental results from IKONOS, Radarsat-2, and TerraSAR-X (kappa coefficient (κ): 0.85, 0.82, 0.76) and Support Vector Machine-based CD techniques (κ = 0.83, 0.73, 0.84), showed that the accuracy of the change maps is relatively improved. Finally, we came to the conclusion that the proposed method is considerably automated and less influenced by the errors in the classification process.

Imaging for High-Resolution Wide-Swath Spaceborne SAR Using Cubic Filtering and NUFFT Based on Circular Orbit Approximation

In the processing of high-resolution wide-swath spaceborne synthetic aperture radar data, the slant range history is difficult to formulate with a high accuracy over a long data-acquisition interval, and the variation of the imaging parameters over the illuminated scene makes it necessary to implement 2-D space-variant processing. To deal with these issues, first, a slant range expression is derived based on a geometry model using a circular arc to approximate the curved trajectory in this paper, which is composed of a hyperbolic term, a cubic term, and a quartic term. Then, the imaging flow based on the slant range model is proposed: a cubic filtering in range is employed to normalize the range-variant secondary range compression; the nonuniform fast Fourier transform (NUFFT) is used to correct the additional range displacement introduced by the cubic filtering and the nonlinear range cell migration (RCM) caused by the range dependence of the velocity; necessary modifications are made on the matched filter for azimuth compression to accommodate the cubic filtering in range and to deal with the high-order terms of the slant range model. The simulation results show that the proposed slant range model has a relatively high accuracy; the range processing procedure that involves an NUFFT following a cubic filtering can apply to the case where the nonlinear chirp scaling algorithm is adopted, and it has the advantage of being capable of dealing with the nonlinear RCM; the azimuth processing procedure can provide satisfactory focusing qualities over a rather large azimuth extent.

A practical algorithm for the retrieval of floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar imagery

In this study, we present an algorithm for summer sea ice conditions that semi-automatically produces the floe size distribution of Arctic sea ice from high-resolution satellite Synthetic Aperture Radar data. Currently, floe size distribution data from satellite images are very rare in the literature, mainly due to the lack of a reliable algorithm to produce such data. Here, we developed the algorithm by combining various image analysis methods, including Kernel Graph Cuts, distance transformation and watershed transformation, and a rule-based boundary revalidation. The developed algorithm has been validated against the ground truth that was extracted manually with the aid of 1-m resolution visible satellite data. Comprehensive validation analysis has shown both perspectives and limitations. The algorithm tends to fail to detect small floes (mostly less than 100 m in mean caliper diameter) compared to ground truth, which is mainly due to limitations in water-ice segmentation. Some variability in the power law exponent of floe size distribution is observed due to the effects of control parameters in the process of de-noising, Kernel Graph Cuts segmentation, thresholds for boundary revalidation and image resolution. Nonetheless, the algorithm, for floes larger than 100 m, has shown a reasonable agreement with ground truth under various selections of these control parameters. Considering that the coverage and spatial resolution of satellite Synthetic Aperture Radar data have increased significantly in recent years, the developed algorithm opens a new possibility to produce large volumes of floe size distribution data, which is essential for improving our understanding and prediction of the Arctic sea ice cover.

Investigation on Mining Subsidence Based on Multi-Temporal InSAR and Time-Series Analysis of the Small Baseline Subset—Case Study of Working Faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield, China

High-intensity coal mining (large mining height, shallow mining depth, and rapid advancing) frequently causes large-scale ground damage within a short period of time. Understanding mining subsidence under high-intensity mining can provide a basis for mining-induced damage assessment, land remediation in a subsidence area, and ecological reconstruction in vulnerable ecological regions in Western China. In this study, the mining subsidence status of Shendong Coalfield was investigated and analyzed using two-pass differential interferometric synthetic aperture radar (DInSAR) technology based on high-resolution synthetic aperture radar data (RADARSAT-2 precise orbit, multilook fine, 5 m) collected from 20 January 2012 to June 2013. Surface damages in Shendong Coalfield over a period of 504 days under open-pit mining and underground mining were observed. Ground deformation of the high-intensity mining working faces 22201-1/2 in Bu’ertai Mine, Shendong Coalfield was monitored using small baseline subset (SBAS) InSAR technology. (1) DInSAR detected and located 85 ground deformation areas (including ground deformations associated with past-mining activity). The extent of subsidence in Shendong Coalfield presented a progressive increase at an average monthly rate of 13.09 km2 from the initial 54.98 km2 to 225.20 km2, approximately, which accounted for 7% of the total area of Shendong Coalfield; (2) SBAS-InSAR reported that the maximum cumulative subsidence area reached 5.58 km2 above the working faces 22201-1/2. The advance speed of ground destruction (7.9 m/day) was nearly equal to that of underground mining (8.1 m/day).

Disaggregation of Low-Resolution L-Band Radiometry Using C-Band Radar Data

For Earth observation data to be useful for a wide range of land surface applications, a kilometer or finer resolution is required. Unfortunately, passive microwave observations at low microwave frequencies (1–10 GHz), already providing important information on soil moisture and vegetation dynamics, are generally only available at a resolution of tens of kilometers. This letter presents a new downscaling method relating L-band radiometer and C-band radar observations for downscaling purposes. The data were obtained from two extensive airborne field experiments across a 80 000-km2 catchment in south-eastern Australia and coinciding Envisat Advanced Synthetic Aperture Radar acquisitions, performed during the Austral summer and spring of 2010. The novel approach of this study is in the downscaling of coarse-scale emissivities as observed by the radiometer with a new interpretation of the change detection methodology for the radar signal to relate the spatiotemporal changes of those two types of observations at 1 km. It is shown that, for most land surface conditions, a good spatial representation at high resolution is achieved, without considering land surface specific parameterizations, which is promising for using very high resolution radar data from the Sentinel-1 platform for downscaling of passive microwave data from current missions, such as National Aeronautics and Space Administration's Soil Moisture Active Passive and European Space Agency's SMOS.

Dynamic gauge adjustment of high-resolution X-band radar data for convective rain storms: Model-based evaluation against measured combined sewer overflow

Summary Numerous studies have shown that radar rainfall estimates need to be adjusted against rain gauge measurements in order to be useful for hydrological modelling. In the current study we investigate if adjustment can improve radar rainfall estimates to the point where they can be used for modelling overflows from urban drainage systems, and we furthermore investigate the importance of the aggregation period of the adjustment scheme. This is done by continuously adjusting X-band radar data based on the previous 5–30 min of rain data recorded by multiple rain gauges and propagating the rainfall estimates through a hydraulic urban drainage model. The model is built entirely from physical data, without any calibration, to avoid bias towards any specific type of rainfall estimate. The performance is assessed by comparing measured and modelled water levels at a weir downstream of a highly impermeable, well defined, 64 ha urban catchment, for nine overflow generating rain events. The dynamically adjusted radar data perform best when the aggregation period is as small as 10–20 min, in which case it performs much better than static adjusted radar data and data from rain gauges situated 2–3 km away.

Palaeoenvironmental analysis of large-scale, high-resolution GPR and magnetometry data sets: the Viking Age site of Gokstad in Norway

Large-scale, high-resolution geophysical data sets offer new possibilities for the comprehensive study of archaeological landscapes. In addition to the mere archaeological component, these data sets carry palaeoenvironmental information about the study area. Such information was known but rarely used in conventional geophysical surveys, which is mainly due to methodological issues. The Viking Age site of Gokstad in the Norwegian Province of Vestfold was chosen as a pilot study in order to perform a palaeoenvironmental analysis of large-scale, high-resolution ground-penetrating radar (GPR) and magnetometry data sets. The aim was to investigate how much palaeoenvironmental information is contained in such data sets, how this information can be extracted and analysed and whether it is relevant for the archaeological interpretation. Results yielded a variety of different palaeoenvironmental aspects including characteristics of the Viking Age shoreline, traces of former topography as well as insights into the palaeohydrology of the study area.

Object-Based Method for Estimating Tsunami-Induced Damage Using TerraSAR-X Data

The object-based method we developed to estimate building damage uses high-resolution synthetic aperture radar (TerraSAR-X) data from the 2011 Tohoku earthquake and tsunami. The damage function we developed involves the relationship between changes in the sigma nought values of pre- and postevent TerraSAR-X data and the damage ratio of washed-away buildings. We confirmed that the function performed as expected by estimating the number of washed-away buildings in homogeneous areas, agreeing well with ground truth data verified by a Pearson fs correlation coefficient of 0.99. The same damage function applied at another test site yielded a Pearson's correlation coefficient of 0.98. These results are sufficient to ensure transferability. We then simplified and semiautomated these processes in an ArcGIS environment, estimating building damage in the city of Sendai within 26 minutes.

Sentinel-1 bathymetry for North Sea palaeolandscape analysis

ABSTRACTSubmerged palaeolandscapes can contain pristine underwater heritage. Regular monitoring of these areas is essential to assess and mitigate threats from development including construction, mining, and commercial trawling. While bathymetry alone may be insufficient to detect submerged palaeolandscape features, it can nonetheless recognize previously mapped structures that have a topographic expression. The Sentinel-1 constellation will provide unprecedented access to freely available, high-resolution Synthetic Aperture Radar (SAR) data, acquired systematically and with long-term continuity, and may constitute a cost-effective solution for the monitoring of submerged palaeolandscapes. The article shows the application of a recently developed bathymetric algorithm to Sentinel-1 SAR data over a region of the southern North Sea. Results show general agreement with water depth data obtained from the European Marine Observation and Data Network portal for bathymetry (EMODnet). To assess the support that SAR bathymetry can provide to the analysis of submerged palaeolandscapes, the Sentinel-1-derived water depths were compared to a palaeolandscape map of the same area produced by the North Sea Palaeolandscapes Project (NSPP). Results show a clear correspondence between certain topographic structures identified in the Sentinel-1 water depth map and features interpreted by the NSPP as early Holocene lakes, rivers, and landscape topography.

Joint use of multiple Synthetic Aperture Radar imagery for the detection of bivalve beds and morphological changes on intertidal flats

We analyzed a large amount of high-resolution Synthetic Aperture Radar (SAR) data of dry-fallen intertidal flats on the German North Sea coast with respect to the imaging of sediments, macrophytes, and mussels. TerraSAR-X and Radarsat-2 images of four test areas acquired from 2008 to 2013 form the basis for the present investigation and are used to demonstrate that pairs of SAR images, if combined through basic algebraic operations, can already provide indicators for morphological changes and for bivalve (oyster and mussel) beds. Multi-temporal analyses of series of SAR images allow detecting bivalve beds, since the radar backscattering from those beds is generally high, whereas that from sediments may vary with imaging geometry and environmental conditions. Our results further show evidence that also single-acquisition, dual-polarization SAR imagery can be used in this respect. The polarization coefficient (i.e., the ratio of the difference and the sum of both co-polarizations) can be used to infer indicators for oyster and blue-mussel beds.