Lake Icepack and Dry Snowpack Thickness Measurement Using Coherent Multipath Interference of Wideband Planck Radiation

The seasonal terrestrial snowpack is an important source of water for many parts of the globe. The global quantification of the amount of water in the snowpack reservoir has been a long term objective of most remote sensing applications. Thus far, the primary means of quantifying the amount of snow on the ground has been via the differential scatter-darkening mechanism, such as 19 and 37 GHz brightness difference. This technique is region specific and depends on the statistics of snow grain sizes. While a time series of more than 35 years of passive microwave data has been made, progress in understanding the scatter-darkening brightness signature of snow continues, especially for forested areas where vegetation scattering confounds the signature. In addition, monitoring the ice thickness is important in analyzing the pressure exerted to off-shore structures such as wind farms. It is also an essential parameter for the safety of ice fishing and ice skating activities. The current and traditional method of ice thickness measurement is by drilling holes through the ice, which is not only cumbersome but also dangerous. Hence, an accurate remote sensing technique is needed to safely and non-destructively measure the ice and snow thickness. In this work, a novel microwave radiometric technique, wideband autocorrelation radiometry (WiBAR), is introduced. The radiometer offers a direct method to remotely measure the microwave propagation time difference of multipath microwave emission from low-loss layered surfaces, such as a dry snowpack and a freshwater lake icepack. The microwave propagation time difference through the pack yields a measure of its vertical extent; thus, this technique provides a direct measurement of depth. It is also a low-power sensing method since there is no transmitter. A simple geophysical forward model for the multipath interference phenomenon is presented, and the system requirements needed to design a WiBAR instrument are derived. Three different versions of WiBAR instruments operating at L-, S-, and X-band are fabricated from commercial-off-the-shelf (COTS) components. To validate the WiBAR method, simulated laboratory measurements are first performed using a microwave scene simulator circuit. Finally, to prove the potential of this technique as an inversion algorithm, many field measurements were conducted in different winter seasons in the Upper Midwest region, Michigan and Minnesota. It is demonstrated that a WiBAR instrument operating in the frequency range of 7-10 GHz (X-band) can directly measure the icepack thicknesses from nadir to 59 degree of incidence angles. The WiBAR was able to measure the lake icepack thicknesses in the range of 22-59 cm with an accuracy of about 2 cm over this range of incidence angles.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/155227/1/mousavis_1.pd

Microwave Radiometry at Frequencies From 500 to 1400 MHz: An Emerging Technology for Earth Observations

icrowave radiometry has provided valuable spaceborne observations of Earth’s geophysical properties for decades. The recent SMOS, Aquarius, and SMAP satellites have demonstrated the value of measurements at 1400 MHz for observ- ing surface soil moisture, sea surface salinity, sea ice thickness, soil freeze/thaw state, and other geophysical variables. However, the information obtained is limited by penetration through the subsur- face at 1400 MHz and by a reduced sensitivity to surface salinity in cold or wind-roughened waters. Recent airborne experiments have shown the potential of brightness temperature measurements from 500–1400 MHz to address these limitations by enabling sensing of soil moisture and sea ice thickness to greater depths, sensing of temperature deep within ice sheets, improved sensing of sea salinity in cold waters, and enhanced sensitivity to soil moisture under veg- etation canopies. However, the absence of significant spectrum re- served for passive microwave measurements in the 500–1400 MHz band requires both an opportunistic sensing strategy and systems for reducing the impact of radio-frequency interference. Here, we summarize the potential advantages and applications of 500–1400 MHz microwave radiometry for Earth observation and review recent experiments and demonstrations of these concepts. We also describe the remaining questions and challenges to be addressed in advancing to future spaceborne operation of this technology along with recommendations for future research activities

Passive Microwave Remote Sensing of Snow Layers Using Novel Wideband Radiometer Systems and RFI Mitigation

Climate change can reduce the availability of water resources in many regions, and it will affect agriculture, industry, and energy supply. Snowpack monitoring is important in water resource management as well as flood and avalanche protection. The rapid melting process due to global warming changes the snowpacks' annual statistics, including the extent, and the snow water equivalent (SWE) of seasonal snowpacks, which results in non-stationary annual statistics that should be monitored in nearly daily intervals. The development of advanced radiometric sensors capable of accurately measuring the snowpack thickness and SWE is needed for the long-term study of the snowpack parameters' statistical changes. Passive microwave radiometry provides a means for measuring the microwave emission from a scene of snow and ice. A Wideband Autocorrelation Radiometer (ac{WiBAR}) operating from 1-2~GHz measures spontaneous emission from snowpack at long wavelengths where the scattering is minimized, but the snow layer coherent effects are preserved. By using a wide bandwidth to measure the spacing between frequencies of constructive and destructive interference of the emission from the soil under the snow, it can reveal the microwave travel time through the snow, and thus the snow depth. However, narrowband radio frequency interference (RFI) in the WiBAR's frequency of operations reduces the ability of the WiBAR to measure the thickness accurately. In addition, the current WiBAR system is a frequency domain, FD-WiBAR, system that uses a field-portable spectrum analyzer to collect the data and suffers from high data acquisition time which limits its applications for spaceborne and airborne technologies. In this work, a novel frequency tunable microwave comb filter is proposed for RFI mitigation. The frequency response of the proposed filter has a pattern with many frequencies band-pass and band rejection that preserves the frequency span while reducing the RFI. Moreover, we demonstrate time-domain WiBAR, TD-WiBAR, which presented as an alternative method for FD-WiBAR, and is capable of providing faster data acquisition. A new time-domain calibration is also developed for TD-WiBAR and evaluated with the frequency domain calibration. To validate the TD-WiBAR method, simulated laboratory measurements are performed using a microwave scene simulator circuit. Then the WiBAR instrument is enhanced with the proposed comb filter and showed the RFI mitigation in time-domain mode on an instrument bench test. Furthermore, we analyze the effects of an above snow vegetation layer on brightness temperature spectra, particularly the possible decay of wave coherence arising from volume scattering in the vegetation canopy. In our analysis, the snow layer is assumed to be flat, and its upward emission and surface reflectivities are modeled by a fully coherent model, while an incoherent radiative transfer model describes the volume scattering from the vegetation layer. We proposed a unified framework of vegetation scattering using radiative transfer (RT) theory for passive and active remote sensing of vegetated land surfaces, especially those associated with moderate-to-large vegetation water contents (VWCs), e.g., forest field. The framework allows for modeling passive and active microwave signatures of the vegetated field with the same physical parameters describing the vegetation structure. The proposed model is validated with the passive and active L-band sensor (PALS) acquired in SMAPVEX12 measurements in 2012, demonstrating the applicability of this model.PHDElectrical and Computer EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/169653/1/maryamsa_1.pd

Review Article: Global Monitoring of Snow Water Equivalent Using High-Frequency Radar Remote Sensing

Seasonal snow cover is the largest single component of the cryosphere in areal extent, covering an average of 46 × 106 km2 of Earth\u27s surface (31 % of the land area) each year, and is thus an important expression and driver of the Earth\u27s climate. In recent years, Northern Hemisphere spring snow cover has been declining at about the same rate (∼ −13 % per decade) as Arctic summer sea ice. More than one-sixth of the world\u27s population relies on seasonal snowpack and glaciers for a water supply that is likely to decrease this century. Snow is also a critical component of Earth\u27s cold regions\u27 ecosystems, in which wildlife, vegetation, and snow are strongly interconnected. Snow water equivalent (SWE) describes the quantity of water stored as snow on the land surface and is of fundamental importance to water, energy, and geochemical cycles. Quality global SWE estimates are lacking. Given the vast seasonal extent combined with the spatially variable nature of snow distribution at regional and local scales, surface observations are not able to provide sufficient SWE information. Satellite observations presently cannot provide SWE information at the spatial and temporal resolutions required to address science and high-socio-economic-value applications such as water resource management and streamflow forecasting. In this paper, we review the potential contribution of X- and Ku-band synthetic aperture radar (SAR) for global monitoring of SWE. SAR can image the surface during both day and night regardless of cloud cover, allowing high-frequency revisit at high spatial resolution as demonstrated by missions such as Sentinel-1. The physical basis for estimating SWE from X- and Ku-band radar measurements at local scales is volume scattering by millimeter-scale snow grains. Inference of global snow properties from SAR requires an interdisciplinary approach based on field observations of snow microstructure, physical snow modeling, electromagnetic theory, and retrieval strategies over a range of scales. New field measurement capabilities have enabled significant advances in understanding snow microstructure such as grain size, density, and layering. We describe radar interactions with snow-covered landscapes, the small but rapidly growing number of field datasets used to evaluate retrieval algorithms, the characterization of snowpack properties using radar measurements, and the refinement of retrieval algorithms via synergy with other microwave remote sensing approaches. This review serves to inform the broader snow research, monitoring, and application communities on progress made in recent decades and sets the stage for a new era in SWE remote sensing from SAR measurements

Earth resources: A continuing bibliography, issue 46

This bibliography lists 467 reports, articles and other documents introdcued into the NASA scientific and technical information system between April 1 and June 30, 1985. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental cultural resources geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economical analysis

Multiple Volume Scattering in Random Media and Periodic Structures with Applications in Microwave Remote Sensing and Wave Functional Materials

The objective of my research is two-fold: to study wave scattering phenomena in dense volumetric random media and in periodic wave functional materials. For the first part, the goal is to use the microwave remote sensing technique to monitor water resources and global climate change. Towards this goal, I study the microwave scattering behavior of snow and ice sheet. For snowpack scattering, I have extended the traditional dense media radiative transfer (DMRT) approach to include cyclical corrections that give rise to backscattering enhancements, enabling the theory to model combined active and passive observations of snowpack using the same set of physical parameters. Besides DMRT, a fully coherent approach is also developed by solving Maxwell’s equations directly over the entire snowpack including a bottom half space. This revolutionary new approach produces consistent scattering and emission results, and demonstrates backscattering enhancements and coherent layer effects. The birefringence in anisotropic snow layers is also analyzed by numerically solving Maxwell’s equation directly. The effects of rapid density fluctuations in polar ice sheet emission in the 0.5~2.0 GHz spectrum are examined using both fully coherent and partially coherent layered media emission theories that agree with each other and distinct from incoherent approaches. For the second part, the goal is to develop integral equation based methods to solve wave scattering in periodic structures such as photonic crystals and metamaterials that can be used for broadband simulations. Set upon the concept of modal expansion of the periodic Green’s function, we have developed the method of broadband Green’s function with low wavenumber extraction (BBGFL), where a low wavenumber component is extracted and results a non-singular and fast-converging remaining part with simple wavenumber dependence. We’ve applied the technique to simulate band diagrams and modal solutions of periodic structures, and to construct broadband Green’s functions including periodic scatterers.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/135885/1/srtan_1.pd

Remote Sensing of Earth Resources (1970 - 1973 supplement): A literature survey with indexes. Section 2: Indexes

Documents related to the identification and evaluation by means of sensors in spacecraft and aircraft of vegetation, minerals, and other natural resources, and the techniques and potentialities of surveying and keeping up-to-date inventories of such riches are cited. These documents were announced in the NASA scientific and technical information system between March 1970 and December 1973

Multiple Volume Scattering in Random Media and Periodic Structures with Applications in Microwave Remote Sensing and Wave Functional Materials

The objective of my research is two-fold: to study wave scattering phenomena in dense volumetric random media and in periodic wave functional materials. For the first part, the goal is to use the microwave remote sensing technique to monitor water resources and global climate change. Towards this goal, I study the microwave scattering behavior of snow and ice sheet. For snowpack scattering, I have extended the traditional dense media radiative transfer (DMRT) approach to include cyclical corrections that give rise to backscattering enhancements, enabling the theory to model combined active and passive observations of snowpack using the same set of physical parameters. Besides DMRT, a fully coherent approach is also developed by solving Maxwell’s equations directly over the entire snowpack including a bottom half space. This revolutionary new approach produces consistent scattering and emission results, and demonstrates backscattering enhancements and coherent layer effects. The birefringence in anisotropic snow layers is also analyzed by numerically solving Maxwell’s equation directly. The effects of rapid density fluctuations in polar ice sheet emission in the 0.5~2.0 GHz spectrum are examined using both fully coherent and partially coherent layered media emission theories that agree with each other and distinct from incoherent approaches. For the second part, the goal is to develop integral equation based methods to solve wave scattering in periodic structures such as photonic crystals and metamaterials that can be used for broadband simulations. Set upon the concept of modal expansion of the periodic Green’s function, we have developed the method of broadband Green’s function with low wavenumber extraction (BBGFL), where a low wavenumber component is extracted and results a non-singular and fast-converging remaining part with simple wavenumber dependence. We’ve applied the technique to simulate band diagrams and modal solutions of periodic structures, and to construct broadband Green’s functions including periodic scatterers.PHDElectrical EngineeringUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttps://deepblue.lib.umich.edu/bitstream/2027.42/137141/1/srtan_1.pd

Earth resources, a continuing bibliography with indexes

This bibliography lists 541 reports, articles and other documents introduced into the NASA scientific and technical information system. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis