Remote sensing of earth terrain

Abstracts from 46 refereed journal and conference papers are presented for research on remote sensing of earth terrain. The topics covered related to remote sensing include the following: mathematical models, vegetation cover, sea ice, finite difference theory, electromagnetic waves, polarimetry, neural networks, random media, synthetic aperture radar, electromagnetic bias, and others

A direct helicopter EM sea ice thickness inversion, assessed with synthetic and field data

Accuracy and precision of helicopter electromagneticHEM sounding are the essential parameters for HEM seaicethickness profiling. For sea-ice thickness research, thequality of HEM ice thickness estimates must be better than10 cm to detect potential climatologic thickness changes.Weintroduce and assess a direct, 1D HEM data inversion algorithmfor estimating sea-ice thickness. For synthetic qualityassessment, an analytically determined HEM sea-ice thicknesssensitivity is used to derive precision and accuracy. Precisionis related directly to random, instrumental noise, althoughaccuracy is defined by systematic bias arising fromthe data processing algorithm. For the in-phase component ofthe HEM response, sensitivity increases with frequency andcoil spacing, but decreases with flying height. For small-scaleHEM instruments used in sea-ice thickness surveys, instrumentalnoise must not exceed 5 ppm to reach ice thicknessprecision of 10 cm at 15-m nominal flying height. Comparableprecision is yielded at 30-m height for conventional explorationHEM systems with bigger coil spacings. Accuracylosses caused by approximations made for the direct inversionare negligible for brackish water and remain better than10 cm for saline water. Synthetic precision and accuracy estimatesare verified with drill-hole validated field data fromEast Antarctica, where HEM-derived level-ice thicknessagrees with drilling results to within 4%, or 2 cm

Remote sensing of earth terrain

In remote sensing, the encountered geophysical media such as agricultural canopy, forest, snow, or ice are inhomogeneous and contain scatters in a random manner. Furthermore, weather conditions such as fog, mist, or snow cover can intervene the electromagnetic observation of the remotely sensed media. In the modelling of such media accounting for the weather effects, a multi-layer random medium model has been developed. The scattering effects of the random media are described by three-dimensional correlation functions with variances and correlation lengths corresponding to the fluctuation strengths and the physical geometry of the inhomogeneities, respectively. With proper consideration of the dyadic Green's function and its singularities, the strong fluctuation theory is used to calculate the effective permittivities which account for the modification of the wave speed and attenuation in the presence of the scatters. The distorted Born approximation is then applied to obtain the correlations of the scattered fields. From the correlation of the scattered field, calculated is the complete set of scattering coefficients for polarimetric radar observation or brightness temperature in passive radiometer applications. In the remote sensing of terrestrial ecosystems, the development of microwave remote sensing technology and the potential of SAR to measure vegetation structure and biomass have increased effort to conduct experimental and theoretical researches on the interactions between microwave and vegetation canopies. The overall objective is to develop inversion algorithms to retrieve biophysical parameters from radar data. In this perspective, theoretical models and experimental data are methodically interconnected in the following manner: Due to the complexity of the interactions involved, all theoretical models have limited domains of validity; the proposed solution is to use theoretical models, which is validated by experiments, to establish the region in which the radar response is most sensitive to the parameters of interest; theoretically simulated data will be used to generate simple invertible models over the region. For applications to the remote sensing of sea ice, the developed theoretical models need to be tested with experimental measurements. With measured ground truth such as ice thickness, temperature, salinity, and structure, input parameters to the theoretical models can be obtained to calculate the polarimetric scattering coefficients for radars or brightness temperature for radiometers and then compare theoretical results with experimental data. Validated models will play an important role in the interpretation and classification of ice in monitoring global ice cover from space borne remote sensors in the future. We present an inversion algorithm based on a recently developed inversion method referred to as the Renormalized Source-Type Integral Equation approach. The objective of this method is to overcome some of the limitations and difficulties of the iterative Born technique. It recasts the inversion, which is nonlinear in nature, in terms of the solution of a set of linear equations; however, the final inversion equation is still nonlinear. The derived inversion equation is an exact equation which sums up the iterative Neuman (or Born) series in a closed form and, thus, is a valid representation even in the case when the Born series diverges; hence, the name Renormalized Source-Type Integral Equation Approach

Investigating the Capability of a New Surface-Based EM Instrument, the Sea Ice Sensor (SIS), to Measure Sea Ice Thickness

Sea ice thickness measurement is an important parameter in climate system models, safety and efficiency of offshore operations and maritime navigation. Electromagnetic (EM) induction instruments are commonly used to measure this parameter. Sea Ice Sensor (SIS) is a new surface-based EM instrument that utilizes single frequency and multiple transmitter-receiver coil configurations to measure sea ice thickness. This thesis investigates SIS capability to measure sea ice thickness over a variety of sea ice types. Signal sensitivity, the accuracy of the inversion algorithm used and the pitch and roll effect on the inversion results were investigated. Overall SIS proved to provide accurate sea ice thickness estimates over a variety of sea ice types. Utilization of 2 m coil spacing and a single EM data component appeared to be effective and sufficient for most sea ice types. Utilization of Pitch and roll measurements improved results accuracy

The use of Frequency domain Electro-magnetometer for the characterization of permafrost and ice layers.

openSince the industrial revolution human activities caused a record-breaking increase in the Earth’s average temperature due to the extensive use of greenhouse gases. [1] As global temperatures increase; glaciers have undergone a significant retreat in the past few decades.[2] The Ice Memory project aims to preserve ice cores from glaciers worldwide, as a record of Earth's past climate. It involves drilling deep into glaciers, extracting ice cores, and storing them in a dedicated facility in Antarctica. This is to prevent the potential loss of valuable climate archives due to glacier retreat which provides future scientists with valuable information for studying historical climate patterns and understanding the role of human activity in climate change. geophysical investigations are typically required to determine the most suitable drilling positions for ice coring. the most common technique for this purpose is the so-called GPR. (Snow cover of several meters limits the use of ERT and active seismic methods.) While each geophysical technique has certain advantages and limitations, combining them can provide a more detailed picture of changes within rock glaciers. In the present study, electromagnetic prospecting in the frequency domain (FDEM) was performed together with the ground penetration radar (GPR). The former is not a commonly used method for studying glacier environments as FDEM has a lower resolution in the study of glaciers with respect to the GPR. However, as we will see in this study, it is a quick and convenient method to study this type of environment, as it provides a large coverage area in a cost-efficient manner, although with a lower resolution with respect to the GPR. Combining these two techniques provide a more detailed map of the glaciers. comparing the GPR and borehole data with the inverted FDEM datasets (CMD-DUO, GF-Instruments) confirms the effectiveness and applicability of FDEM methodology for investigating glacial bodies in mountainous regions.Since the industrial revolution human activities caused a record-breaking increase in the Earth’s average temperature due to the extensive use of greenhouse gases. [1] As global temperatures increase; glaciers have undergone a significant retreat in the past few decades.[2] The Ice Memory project aims to preserve ice cores from glaciers worldwide, as a record of Earth's past climate. It involves drilling deep into glaciers, extracting ice cores, and storing them in a dedicated facility in Antarctica. This is to prevent the potential loss of valuable climate archives due to glacier retreat which provides future scientists with valuable information for studying historical climate patterns and understanding the role of human activity in climate change. geophysical investigations are typically required to determine the most suitable drilling positions for ice coring. the most common technique for this purpose is the so-called GPR. (Snow cover of several meters limits the use of ERT and active seismic methods.) While each geophysical technique has certain advantages and limitations, combining them can provide a more detailed picture of changes within rock glaciers. In the present study, electromagnetic prospecting in the frequency domain (FDEM) was performed together with the ground penetration radar (GPR). The former is not a commonly used method for studying glacier environments as FDEM has a lower resolution in the study of glaciers with respect to the GPR. However, as we will see in this study, it is a quick and convenient method to study this type of environment, as it provides a large coverage area in a cost-efficient manner, although with a lower resolution with respect to the GPR. Combining these two techniques provide a more detailed map of the glaciers. comparing the GPR and borehole data with the inverted FDEM datasets (CMD-DUO, GF-Instruments) confirms the effectiveness and applicability of FDEM methodology for investigating glacial bodies in mountainous regions

Airborne Electromagnetics as a Method for Arctic Wide Sea Ice Thickness Retrieval

The purpose of this thesis was to mount Airborne Electromagnetic (AEM) sensors for sea-ice thickness retrieval under the wings of long range airplanes and to quantify existing noise sources. Another aim was to determine and to characterise thickness distribution functions of several regions in the central Arctic. The accuracy of a prototype aeroplane EM system was found to be /- 0.5 m. The accuracy was reduced due to wing flexure, which produces noise of equal amplitude as the wanted ocean signal. Other noise sources are inductive ocean-aeroplane coupling and pitch which may disturb the measurements by another 10 percent of the signal. It is suggested to take the 90° out of phase response signal, since wing flexure noise mainly is 180° out of phase. On transects in the central Arctic mean thickness standard errors as low as 0.2 m could be obtained for 10 km long profiles in less deformed ice independently of the age of the ice regime. In a deformed multi year ice (MYI) regime standard errors of 0.2 m were obtained on transects as long as 100 km. These results show that a reduction of central Arctic mean sea-ice thickness by 1.8 between 1991 and 2007 was higher than typical spatial variability

Cryosphere Applications

Synthetic aperture radar (SAR) provides large coverage and high resolution, and it has been proven to be sensitive to both surface and near-surface features related to accumulation, ablation, and metamorphism of snow and firn. Exploiting this sensitivity, SAR polarimetry and polarimetric interferometry found application to land ice for instance for the estimation of wave extinction (which relates to sub surface ice volume structure) and for the estimation of snow water equivalent (which relates to snow density and depth). After presenting these applications, the Chapter proceeds by reviewing applications of SAR polarimetry to sea ice for the classification of different ice types, the estimation of thickness, and the characterisation of its surface. Finally, an application to the characterisation of permafrost regions is considered. For each application, the used (model-based) decomposition and polarimetric parameters are critically described, and real data results from relevant airborne campaigns and space borne acquisitions are reported

Characterisation of the subglacial environment using geophysical constrained Bayesian inversion techniques

An accurate characterization of the inaccessible subglacial environment is key to accurately modelling the dynamic behaviour of ice sheets and glaciers, crucial for predicting sea-level rise. The composition and water content of subglacial material can be inferred from measurements of shear wave velocity (Vs) and bulk electrical resistivity (R), themselves derived from Rayleigh wave dispersion curves and transient electromagnetic (TEM) soundings. Conventional Rayleigh wave and TEM inversions can suffer from poor resolution and non-uniqueness. In this thesis, I present a novel constrained inversion methodology which applies a Markov chain Monte Carlo implementation of Bayesian inversion to produce probability distributions of geophysical parameters. MuLTI (Multimodal Layered Transdimensional Inversion) is used to derive Vs from Rayleigh wave dispersion curves, and its TEM variant, MuLTI-TEM, for evaluating bulk electrical resistivity. The methodologies can include independent depth constraints, drawn from external data sources (e.g., boreholes or other geophysical data), which significantly improves the resolution compared to conventional unconstrained inversions. Compared to such inversions, synthetic studies suggested that MuLTI reduces the error between the true and best-fit models by a factor of 10, and reduces the vertically averaged spread of the Vs distribution twofold, based on the 95% credible intervals. MuLTI and MuLTI-TEM were applied to derive Vs and R profiles from seismic and TEM electromagnetic data acquired on the terminus of the Norwegian glacier Midtdalsbreen. Three subglacial material classifications were determined: sediment (Vs 1600 m/s, R > 500 Ωm) and weathered/fractured bedrock containing saline water (Vs > 1900 m/s, R < 50 Ωm). These algorithms offer a step-change in our ability to resolve and quantify the uncertainties in subsurface inversions, and show promise for constraining the properties of subglacial aquifers beneath Antarctic ice masses. MuLTI and MuLTITEM have both been made publicly available via GitHub to motivate users, in the cryosphere and other environmental settings, for continued advancement

GNSS transpolar earth reflectometry exploriNg system (G-TERN): mission concept

The global navigation satellite system (GNSS) Transpolar Earth Reflectometry exploriNg system (G-TERN) was proposed in response to ESA's Earth Explorer 9 revised call by a team of 33 multi-disciplinary scientists. The primary objective of the mission is to quantify at high spatio-temporal resolution crucial characteristics, processes and interactions between sea ice, and other Earth system components in order to advance the understanding and prediction of climate change and its impacts on the environment and society. The objective is articulated through three key questions. 1) In a rapidly changing Arctic regime and under the resilient Antarctic sea ice trend, how will highly dynamic forcings and couplings between the various components of the ocean, atmosphere, and cryosphere modify or influence the processes governing the characteristics of the sea ice cover (ice production, growth, deformation, and melt)? 2) What are the impacts of extreme events and feedback mechanisms on sea ice evolution? 3) What are the effects of the cryosphere behaviors, either rapidly changing or resiliently stable, on the global oceanic and atmospheric circulation and mid-latitude extreme events? To contribute answering these questions, G-TERN will measure key parameters of the sea ice, the oceans, and the atmosphere with frequent and dense coverage over polar areas, becoming a “dynamic mapper”of the ice conditions, the ice production, and the loss in multiple time and space scales, and surrounding environment. Over polar areas, the G-TERN will measure sea ice surface elevation (<;10 cm precision), roughness, and polarimetry aspects at 30-km resolution and 3-days full coverage. G-TERN will implement the interferometric GNSS reflectometry concept, from a single satellite in near-polar orbit with capability for 12 simultaneous observations. Unlike currently orbiting GNSS reflectometry missions, the G-TERN uses the full GNSS available bandwidth to improve its ranging measurements. The lifetime would be 2025-2030 or optimally 2025-2035, covering key stages of the transition toward a nearly ice-free Arctic Ocean in summer. This paper describes the mission objectives, it reviews its measurement techniques, summarizes the suggested implementation, and finally, it estimates the expected performance.Peer ReviewedPostprint (published version