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The investigation of permafrost formation global distribution and their appearance in h less than or equal 1 m thick subsurface layer would be investigated successfully by employment of active-passive microwave remote sensing techniques.
The expansion of shrubs in the Arctic tundra fundamentally modifies land-atmosphere interactions. However, it remains unclear how shrub distribution and expansion differ across key species due to challenges with discriminating tundra plant species at regional scales. Here, we combined multi-scale, multi-platform remote sensing and in situ trait measurements to elucidate the distribution patterns and primary controls of two representative deciduous-tall-shrub (DTS) genera, Alnus and Salix, in low-Arctic tundra. We show that topographic features were a key control on DTSs, creating heterogeneous, but predictable distributions of Alnus and Salix fractional cover (fCover). Alnus was more tolerant of elevation and slope and was found on hilly uplands (slope >10°) within a specific elevational band (200–400 m above sea level [MSL]). In contrast, Salix occurred at lower elevations (50–300 m MSL) on gentler slopes (3-10°) and required adequate soil moisture associated with its profligate water use. We also show that niche differentiation between Alnus and Salix changed with patch size, where larger patches were more specialized in resource requirements than individual plants of Alnus and Salix. To understand what constrains the growth of DTSs at locations with low fCover, we developed environmental limiting factor models, which showed that topography limits the upper bound of Alnus and Salix fCover in 69.2% and 48.7% of the landscape, respectively. These findings highlight a critical need to better understand and represent topography-controlled processes and functional traits in regulating shrub distribution, as well as a need for more detailed species classification to predict shrubification in the Arctic.
A single phase, 440 VRMS, 20 kHz power distribution system with a regulated sinusoidal wave form is discussed. A single phase power system minimizes the wiring, sensing, and control complexities required in a multi-sourced redundantly distributed power system. The single phase addresses only the distribution link; mulitphase lower frequency inputs and outputs accommodation techniques are described. While the 440 V operating potential was initially selected for aircraft operating below 50,000 ft, this potential also appears suitable for space power systems. This voltage choice recognizes a reasonable upper limit for semiconductor ratings, yet will direct synthesis of 220 V, 3 power. A 20 kHz operating frequency was selected to be above the range of audibility, minimize the weight of reactive components, yet allow the construction of single power stages of 25 to 30 kW. The regulated sinusoidal distribution system has several advantages. With a regulated voltage, most ac/dc conversions involve rather simple transformer rectifier applications. A sinusoidal distribution system, when used in conjunction with zero crossing switching, represents a minimal source of EMI. The present state of 20 kHz power technology includes computer controls of voltage and/or frequency, low inductance cable, current limiting circuit protection, bi-directional power flow, and motor/generator operating using standard induction machines. A status update and description of each of these items and their significance is presented.
A single phase, 440 VRMS, 20 kHz power distribution system with a regulated sinusoidal wave form is discussed. A single phase power system minimizes the wiring, sensing, and control complexities required in a multi-sourced redundantly distributed power system. The single phase addresses only the distribution links multiphase lower frequency inputs and outputs accommodation techniques are described. While the 440 V operating potential was initially selected for aircraft operating below 50,000 ft, this potential also appears suitable for space power systems. This voltage choice recognizes a reasonable upper limit for semiconductor ratings, yet will direct synthesis of 220 V, 3 power. A 20 kHz operating frequency was selected to be above the range of audibility, minimize the weight of reactive components, yet allow the construction of single power stages of 25 to 30 kW. The regulated sinusoidal distribution system has several advantages. With a regulated voltage, most ac/dc conversions involve rather simple transformer rectifier applications. A sinusoidal distribution system, when used in conjunction with zero crossing switching, represents a minimal source of EMI. The present state of 20 kHz power technology includes computer controls of voltage and/or frequency, low inductance cable, current limiting circuit protection, bi-directional power flow, and motor/generator operating using standard induction machines. A status update and description of each of these items and their significance is presented.
Airborne imaging spectroscopy has evolved dramatically since the 1980s as a robust remote sensing technique used to generate 2-dimensional maps of surface properties over large spatial areas. Traditional applications for passive airborne imaging spectroscopy include interrogation of surface composition, such as mapping of vegetation diversity and surface geological composition. Two recent applications are particularly relevant to the needs of both the oil and gas as well as government sectors: quantification of surficial hydrocarbon thickness in aquatic environments and mapping atmospheric greenhouse gas components. These techniques provide valuable capabilities for petroleum seepage in addition to detection and quantification of fugitive emissions. New empirical data that provides insight into the source strength of anthropogenic methane will be reviewed, with particular emphasis on the evolving constraints enabled by new methane remote sensing techniques. Contemporary studies attribute high-strength point sources as significantly contributing to the national methane inventory and underscore the need for high performance remote sensing technologies that provide quantitative leak detection. Imaging sensors that map spatial distributions of methane anomalies provide effective techniques to detect, localize, and quantify fugitive leaks. Airborne remote sensing instruments provide the unique combination of high spatial resolution (<1 m) and large coverage required to directly attribute methane emissions to individual emission sources. This capability cannot currently be achieved using spaceborne sensors. In this study, results from recent NASA remote sensing field experiments focused on point-source leak detection, will be highlighted. This includes existing quantitative capabilities for oil and methane using state-of-the-art airborne remote sensing instruments. While these capabilities are of interest to NASA for assessment of environmental impact and global climate change, industry similarly seeks to detect and localize leaks of both oil and methane across operating fields. In some cases, higher sensitivities desired for upstream and downstream applications can only be provided by new airborne remote sensing instruments tailored specifically for a given application. There exists a unique opportunity for alignment of efforts between commercial and government sectors to advance the next generation of instruments to provide more sensitive leak detection capabilities, including those for quantitative source strength determination.
The Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) and the Cloud, Aerosol, and Complex Terrain Interactions Experiment Proposal (CACTI) field campaigns provided an unprecedented thirteen-disdrometer dataset in Central Argentina during the Intensive (IOP, 15 November to 15 December 2018) and Extended (EOP, 15 October 2018 to 30 April 2019) Observational Periods. The drop size distribution (DSD) parameters and their variability were analyzed across the region of interest, which was divided into three subregions characterized by the differing proximity to the Sierras de Córdoba (SDC), in order to assess the impact of complex terrain on the DSD parameters. A rigorous quality control of the data was first performed. The frequency distributions of DSD-derived parameters were analyzed, including the normalized intercept parameter (logN w ), the mean volume diameter (D 0 ), the mean mass diameter (D m ), the shape parameter (μ), the liquid water content (LWC), and the rain rate (R). The region closest to the SDC presented higher values of logN w , lower D 0 , and higher μ, while the opposite occurred in the farthest region, i.e., the concentration of small drops decreased while the concentration of bigger drops increased with the distance to the east of the SDC. Furthermore, the region closest to the SDC showed a bimodal distribution of D 0 : the lower values of D 0 were associated with higher values of logN w and were found more frequently during the afternoon, while the higher D 0 were associated with lower logN w and occurred more frequently during the night. The data were analyzed in comparison to the statistical analysis of Dolan et al. 2018 and sorted according to the classification proposed in the cited study. The logN w -D 0 and LWC-D 0 two-dimensional distributions allowed further discussion around the applicability of other mid-latitude and global precipitation classification schemes (startiform/convection) in the region of interest. Finally, three precipitation case studies were analyzed with supporting polarimetric radar data in order to relate the DSD characteristics to the precipitation type and the microphysical processes involved in each case.
The rapid deployment of distributed energy resources (DERs) is creating stresses on utility assets in the distribution networks. The service transformer, which is the most commonly used utility asset is often not monitored, since the cost of available sensing solutions is as high as the transformer itself. This paper presents a method to use an array of printed circuit board coils to intelligently monitor North American pole top service transformers. The approach, uses a novel, self-calibrating algorithm to infer the fixed geometry of the installation, by recording data over an extended period of time. The proposed method can enable rapid installation of a non-intrusive sensor that can be used to monitor loading levels of the distribution transformer. Furthermore, these sensors can help in planning, prognostics and advanced situational awareness for utilities.
Aircraft design has been progressing toward reduced structural weight to improve fuel efficiency, increase performance, and reduce cost. Lightweight aircraft structures are more flexible than conventional designs and require new design considerations. Intelligent sensing allows for enhanced control and monitoring of aircraft, which enables increased structurally efficiency. The NASA Dryden Flight Research Center (DFRC) has developed an instrumentation system and analysis techniques that combine to make distributed structural measurements practical for lightweight vehicles. Dryden's Fiber Optic Strain Sensing (FOSS) technology enables a multitude of lightweight, distributed surface strain measurements. The analysis techniques, referred to as the Displacement Transfer Functions (DTF) and Load Transfer Functions (LTF), use surface strain values to calculate structural deflections and operational loads. The combined system is useful for real-time monitoring of aeroelastic structures, along with many other applications. This paper describes how the capabilities of the measurement system were demonstrated using subscale test articles that represent simple aircraft structures. Empirical FOSS strain data were used within the DTF to calculate the displacement of the article and within the LTF to calculate bending moments due to loads acting on the article. The results of the tests, accuracy of the measurements, and a sensitivity analysis are presented.
Natural gas pipeline corrosion represents a substantial cost and safety concern during normal operations. The effective and real-time monitoring of corrosion is important to detect and mitigate pipeline risks before corrosion-related catastrophic events happen. Here, we describe the use of iron (Fe) coated optical fiber sensors (OFS) for distributed corrosion monitoring where Fe acts as a corrosion proxy. By using an optical backscattering reflectometer (OBR), corrosion was monitored based on the increase in the backscattered intensity amplitude of the light being passed as Fe underwent corrosion. The Fe-coated OFSs were prepared with a film thickness between 25–225 nanometers (nm) by an electroless plating approach and corroded by a carbon dioxide (CO2)-saturated acidic electrolyte. The corrosion rate (CR) was approximately 2.5 millimeters (mm)/year for Fe with a film thickness of 30 nm and increased with film thickness. Backscattering-based CRs were supported by visible light transmission measurements, which have been previously demonstrated. Additionally, a correlation between the intermittent transmission and residual Fe film thickness during the corrosion of Fe was established. The corrosion was measurable out to > 100 meters (m), which is a significant improvement over our previous work, which showed corrosion sensing at < 10 m. The corrosion sensor was also tested in soil at > 1 foot depth.
The Tharsis province of Mars displays a variety of small volcanic vent (10s krn in diameter) morphologies. These features were identified in Mariner and Viking images [1-4], and Mars Orbiter Laser Altimeter (MOLA) data show them to be more abundant than originally observed [5,6]. Recent studies are classifying their diverse morphologies [7-9]. Building on this work, we are mapping the location of small volcanic vents (small-vents) in the Tharsis province using MOLA, Thermal Emission Imaging System, and High Resolution Stereo Camera data [10]. Here we report on a preliminary study of the spatial and alignment relationships between small-vents south of Pavonis Mons, as determined by nearest neighbor and two-point azimuth statistical analyses. Terrestrial monogenetic volcanic fields display four fundamental characteristics: 1) recurrence rates of eruptions,2 ) vent abundance, 3) vent distribution, and 4) tectonic relationships [11]. While understanding recurrence rates typically requires field measurements, insight into vent abundance, distribution, and tectonic relationships can be established by mapping of remotely sensed data, and subsequent application of spatial statistical studies [11,12], the goal of which is to link the distribution of vents to causal processes.
The Geoscience Laser Altimeter System launched in early 2003 is the first satellite instrument in space to globally observe the distribution of clouds and aerosol through laser remote sensing. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the calibrated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data is expected to significantly enhance knowledge in several areas of atmospheric science, in particular the distribution, transport and influence of atmospheric aerosol. Measurements of the coverage and height of polar and cirrus cloud should be significantly more accurate than previous global measurement. Initial result from the first several months of operation will be presented.
The Geoscience Laser Altimeter System launched in early 2003 is the first satellite instrument IC space to globally observe the distribution of clouds and aerosol through laser remote sensing. The instrument is a basic backscatter lidar that operates at two wavelengths, 532 and 1064 nm. The mission data products for atmospheric observations include the calibrated, observed, attenuated backscatter cross section for cloud and aerosol; height detection for multiple cloud layers; planetary boundary layer height; cirrus and aerosol optical depth and the height distribution of aerosol and cloud scattering cross section profiles. The data will enhance knowledge in several areas of atmospheric science: the distribution, transport and influence of atmospheric aerosol, significantly more accurate measurements of the coverage and height of cirrus and other clouds, polar cloud climatology and radiation influence, the dynamics planetary boundary layer and others. An overview and summary of initial results are presented. Initial results from the first months of operation show the detailed height structure of clouds and aerosol on a global basis as expected. The 532 nm channel was expected to be the more sensitive and primary channel for aerosol measurements, but extensive aerosol loading in many regions are observed by the 1064 nm channel. Sensitivities are down to a few times l0(exp 6) l/(m-sr), much better than originally expected. The 532 channel adds an order of magnitude addition sensitivity. Initial comparisons to aerosol models have been done. Similarly for global cloud cover, good results are obtained just from the 1064 nm channel and from both channels, a measurement of multiple layers and cloud overlap has been made. Antarctica observations show high levels of total cloud cover including unique low-level cirrus and blowing snow. Data products have been generated for cloud, aerosol and PBL presence and heights in addition to the basic scattering cross section profiles.
Soil moisture estimations from a distributed hydrological model and two microwave sensors were compared with ground measurements collected during the MAC-HYDRO'90 experiment. The comparison was done with the purpose of evaluating the performance of the hydrological model and examining the limitations of remote sensing techniques used in soil moisture estimation. An image integration technique was used to integrate and analyze rainfall, soil properties, land cover, topography, and remote sensing imagery. Results indicate that the hydrological model and microwave sensors successfully picked up temporal variations of soil moisture and that the spatial soil moisture pattern may be remotely sensed with reasonable accuracy using existing algorithms.
Microorganisms efficiently coordinate phenotype expressions through a decision-making process known as quorum sensing (QS). We investigated QS amongst distinct, spatially distributed microbial aggregates under various flow conditions using a process-driven numerical model. Model simulations assess the conditions suitable for QS induction and quantify the importance of advective transport of signaling molecules. In addition, advection dilutes signaling molecules so that faster flow conditions require higher microbial densities, faster signal production rates, or higher sensitivities to signaling molecules to induce QS. However, autoinduction of signal production can substantially increase the transport distance of signaling molecules in both upstream and downstream directions. We present empirical approximations to the solutions of the advection–diffusion–reaction equation that describe the concentration profiles of signaling molecules for a wide range of flow and reaction rates. These empirical relationships, which predict the distribution of dissolved solutes along pore channels, allow to quantitatively estimate the effective communication distances amongst multiple microbial aggregates without further numerical simulations.
Quantum sensing promises to revolutionize sensing applications by employing quantum states of light or matter as sensing probes. Photons are the clear choice as quantum probes for remote sensing because they can travel to and interact with a distant target. Existing schemes are mainly based on the quantum illumination framework, which requires quantum memory to store a single photon of an initially entangled pair until its twin reflects off a target and returns for final correlation measurements. Existing demonstrations are limited to tabletop experiments, and expanding the sensing range faces various roadblocks, including long-time quantum storage and photon loss and noise when transmitting quantum signals over long distances. We propose a novel quantum sensing framework that addresses these challenges using quantum frequency combs with path identity for remote sensing of signatures (“qCOMBPASS”). The combination of one key quantum phenomenon and two quantum resources—namely, quantum-induced coherence by path identity, quantum frequency combs, and two-mode squeezed light—allows for quantum remote sensing without requiring quantum memory. The proposed scheme is akin to a quantum radar based on entangled frequency-comb pairs that uses path identity to detect, range, or sense a remote target of interest by measuring pulses of one comb in the pair that never traveled to the target but that contains target information “teleported” by quantum-induced coherence by path identity from the other comb in the pair that traveled to the target but is not detected. We develop the basic qCOMBPASS theory, analyze the properties of the qCOMBPASS transceiver, and introduce the qCOMBPASS equation—a quantum analog of the well-known LIDAR equation in classical remote sensing. We also describe an experimental scheme to demonstrate the concept using two-mode squeezed quantum combs. qCOMBPASS can strongly impact various applications in remote quantum sensing, imaging, metrology, and communications. These applications include detection and ranging of low-reflectivity objects, measurement of small displacements of a remote target with precision beyond the standard quantum limit (SQL), standoff hyperspectral quantum imaging, discreet surveillance from space with low detection probability (detect without being detected), very-long-baseline interferometry, quantum Doppler sensing, quantum clock synchronization, and networks of distributed quantum sensors. Published by the American Physical Society 2024
The effects are considered of an absorbing, emitting, and scattering atmosphere upon the remote sensing of surface areas having non-uniform intensity. These atmospheric effects may be significant in determination, by remote sensing, of non-uniform surface temperature distributions, and the results of the investigation are applicable in such cases. Analytical methods and a digital computational program are presented, expressing the results in terms of contrast and contrast transmittance between two adjacent emitting areas having unequal intensities, in the presence of a additional disturbing emitters. In the computational procedure, emitting areas are replaced by point-source emitters, each assigned and effective intensity based upon the intensity of the area it replaces. Absorbing, emitting, and scattering behavior of the atmosphere may be specified in the computational procedure either by means of analytical atmospheric models or by means of calibrating ground level emitters.
A multichannel scanning device may fail to observe objects because of obstructions blocking the view, or different categories of objects may make up a resolution element giving rise to a single observation. Ground truth will be required on any such categories of objects in order to estimate their expected proportions associated with various classes represented in the remote sensing data. Considering the classes to be distributed as multivariate normal with different mean vectors and common covariance, maximum likelihood estimates are given for the expected proportions of objects associated with different classes, using the Bayes procedure for classification of individuals obtained from these classes. An approximate solution for simultaneous confidence intervals on these proportions is given, and thereby a sample-size needed to achieve a desired amount of accuracy for the estimates is determined.
Remote sensing data were incorporated into a spatially distributed model of snowpack evolution. Preliminary results are presented on the estimation of primary parameters needed in such a model.