GROUND PENETRATING RADAR DATA INTERPRETATION USING ELECTROMAGNETIC FIELD ANALYSIS FOR SEA ICE THICKNESS MEASUREMENT

Observation of sea ice thickness by remote sensing is one of key issues to understand an effect of global warming. However, ground truth must be necessary to discuss this kind of approach. Although there are several methods to acquire ice thickness, Ground Penetrating Radar (GPR) can be good solution because it can discriminate snow-ice and ice-sea water interface thanks to comparative higher spatial resolution than the other methods. In this paper, we carried out GPR measurement in brackish lake and an electromagnetic field analysis in order to interpret the GPR data. The simulation model was assumed considering the actual snow and ice thickness acquired in field measurement. From the simulation results, although it seems difficult to identify the reflection at snow and ice interface due to a thin layer thickness and a low dielectric constant, snow and ice thickness may be estimated by using multiple reflection components

Measurement of snow water equivalent using drone-mounted ultra-wide-band radar

The use of unmanned aerial vehicle (UAV)-mounted radar for obtaining snowpack parameters has seen considerable advances over recent years. However, a robust method of snow density estimation still needs further development. The objective of this work is to develop a method to reliably and remotely estimate snow water equivalent (SWE) using UAV-mounted radar and to perform initial field experiments. In this paper, we present an improved scheme for measuring SWE using ultra-wide-band (UWB) (0.7 to 4.5 GHz) pseudo-noise radar on a moving UAV, which is based on airborne snow depth and density measurements from the same platform. The scheme involves autofocusing procedures with the frequency–wavenumber (F–K) migration algorithm combined with the Dix equation for layered media in addition to altitude correction of the flying platform. Initial results from field experiments show high repeatability (R > 0.92) for depth measurements up to 5.5 m, and good agreement with Monte Carlo simulations for the statistical spread of snow density estimates with standard deviation of 0.108 g/cm3. This paper also outlines needed system improvements to increase the accuracy of a snow density estimator based on an F–K migration technique

Development of analysis approach utilizing extended common mid-point method to estimate asphalt pavement thickness with 3-D GPR

Layer thickness is a critical part of the flexible pavement system. It can affect the structural capacity of existing flexible pavement, and can be used to predict its remaining service life. For newly constructed flexible pavement, obtaining its layer thickness is essential for the purposes of quality control and quality assurance (QC/QA). Currently, most departments of transportation, highway agencies, and consultants in the United States use destructive methods, e.g. coring, to obtain asphalt pavement layer thicknesses. As a non-destructive technique, ground penetration radar (GPR) has also been applied to estimate asphalt pavement thickness. However, the use of GPR is limited due to the difficulty involved in determining the dielectric constant of asphalt pavement in the traditional two-way travel time and surface reflection method. Asphalt mixture is a composite material and, as such, the reflection amplitude of electromagnetic waves could be affected by many factors, such as the presence of moisture. The extended common mid-point (XCMP) method is an alternative method that can be used on the traditional air-coupled pulsed horn antenna to increase the accuracy of asphalt pavement thickness estimation without calibrating the dielectric constant by taking cores. By developing signal processing and numerical analysis techniques, this research attempts to integrate 3-D GPR with the XCMP method, which holds certain advantages over the traditional air-coupled pulsed horn antenna. 3-D GPR is a multi-array stepped-frequency radar that can measure both in-line and cross-line directions at a very close sampling interval. Therefore, 3-D radar provides faster data collection speeds than the pulsed horn antenna and is preferred in large survey areas such as an airport runway/taxiway. To solve the XCMP equations, the time domain sampling rate of the 3-D radar is increased by applying a Whittaker-Shannon interpolation. The XCMP equations are then solved numerically in the least-square sense. By validating the developed algorithm in a full scale test site, the study concludes that by using signal processing techniques and numerical analysis approaches, 3-D radar can be used to accurately predict asphalt layer thickness using the XCMP method when the layer thickness is greater than 50mm

In-Situ Radar Observation of Shallow Lunar Regolith at the Chang’E-5 Landing Site : Research Progress and Perspectives

Funding Information: This work is supported by the National Natural Science Foundation of China (Grant No. 42241139 and 42004099), the Opening Fund of the Key Laboratory of Lunar and Deep Space Exploration, Chinese Academy of Sciences (No. LDSE202005), the National Innovation and Entrepreneurship Training Program for College Students (No. 202310590016), the Fund of Shanghai Institute of Aerospace System Engineering (No. PZ_YY_SYF_JY200275), and the Shenzhen Municipal Government Investment Project (No. 2106_440300_04_03_901272).Peer reviewedPublisher PD

Arctic sea ice trafficability: new strategies for a changing icescape

Thesis (Ph.D.) University of Alaska Fairbanks, 2017Sea ice is an important part of the Arctic social-environmental system, in part because it provides a platform for human transportation and for marine flora and fauna that use the ice as a habitat. Sea ice loss projected for coming decades is expected to change ice conditions throughout the Arctic, but little is known about the nature and extent of anticipated changes and in particular potential implications for over-ice travel and ice use as a platform. This question has been addressed here through an extensive effort to link sea ice use and key geophysical properties of sea ice, drawing upon extensive field surveys around on-ice operations and local and Indigenous knowledge for the widely different ice uses and ice regimes of Utqiaġvik, Kotzebue, and Nome, Alaska. A set of nine parameters that constrain landfast sea ice use has been derived, including spatial extent, stability, and timing and persistence of landfast ice. This work lays the foundation for a framework to assess and monitor key ice-parameters relevant in the context of ice-use feasibility, safety, and efficiency, drawing on different remote-sensing techniques. The framework outlines the steps necessary to further evaluate relevant parameters in the context of user objectives and key stakeholder needs for a given ice regime and ice use scenario. I have utilized this framework in case studies for three different ice regimes, where I find uses to be constrained by ice thickness, roughness, and fracture potential and develop assessment strategies with accuracy at the relevant spatial scales. In response to the widely reported importance of high-confidence ice thickness measurements, I have developed a new strategy to estimate appropriate thickness compensation factors. Compensation factors have the potential to reduce risk of misrepresenting areas of thin ice when using point-based in-situ assessment methods along a particular route. This approach was tested on an ice road near Kotzebue, Alaska, where substantial thickness variability results in the need to raise thickness thresholds by 50%. If sea ice is thick enough for safe travel, then the efficiency of travel is relevant and is influenced by the roughness of the ice surface. Here, I develop a technique to derive trafficability measures from ice roughness using polarimetric and interferometric synthetic aperture radar (SAR). Validated using Structure-from-Motion analysis of imagery obtained from an unmanned aerial system near Utqiaġvik, Alaska, I demonstrate the ability of these SAR techniques to map both topography and roughness with potential to guide trail construction efforts towards more trafficable ice. Even when the ice is sufficiently thick to ensure safe travel, potential for fracturing can be a serious hazard through the ability of cracks to compromise load-bearing capacity. Therefore, I have created a state-of-the-art technique using interferometric SAR to assess ice stability with capability of assessing internal ice stress and potential for failure. In an analysis of ice deformation and potential hazards for the Northstar Island ice road near Prudhoe Bay on Alaska's North Slope I have identified a zone of high relative fracture intensity potential that conformed with road inspections and hazard assessments by the operator. Through this work I have investigated the intersection between ice use and geophysics, demonstrating that quantitative evaluation of a given region in the ice use assessment framework developed here can aid in tactical routing of ice trails and roads as well as help inform long-term strategic decision-making regarding the future of Arctic operations on or near sea ice

Late Quaternary terrestrial processes, sediments and history: from glacial to postglacial environments : Excursion guide and abstracts of the INQUA Peribaltic Working Group Meeting and field excursion in Eastern and Central Latvia, August 17 - 22, 2014

University of Latvi

先進的な線形代数のアレイ信号処理への応用に関する研究

Tohoku University佐藤源之課

Spatial variability of aircraft-measured surface energy fluxes in permafrost landscapes

Arctic ecosystems are undergoing a very rapid change due to global warming and their response to climate change has important implications for the global energy budget. Therefore, it is crucial to understand how energy fluxes in the Arctic will respond to any changes in climate related parameters. However, attribution of these responses is challenging because measured fluxes are the sum of multiple processes that respond differently to environmental factors. Here, we present the potential of environmental response functions for quantitatively linking energy flux observations over high latitude permafrost wetlands to environmental drivers in the flux footprints. We used the research aircraft POLAR 5 equipped with a turbulence probe and fast temperature and humidity sensors to measure turbulent energy fluxes along flight tracks across the Alaskan North Slope with the aim to extrapolate the airborne eddy covariance flux measurements from their specific footprint to the entire North Slope. After thorough data pre-processing, wavelet transforms are used to improve spatial discretization of flux observations in order to relate them to biophysically relevant surface properties in the flux footprint. Boosted regression trees are then employed to extract and quantify the functional relationships between the energy fluxes and environmental drivers. Finally, the resulting environmental response functions are used to extrapolate the sensible heat and water vapor exchange over spatio-temporally explicit grids of the Alaskan North Slope. Additionally, simulations from the Weather Research and Forecasting (WRF) model were used to explore the dynamics of the atmospheric boundary layer and to examine results of our extrapolation