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All sourcesNASA NTRSDOE OSTI
NASA NTRS2004

Cross-Stream PIV Measurements of Jets With Internal Lobed Mixers

With emphasis being placed on enhanced mixing of jet plumes for noise reduction and on predictions of jet noise based upon turbulent kinetic energy, unsteady measurements of jet plumes are a very important part of jet noise studies. Given that hot flows are of most practical interest, optical techniques such as Particle Image Velocimetry (PIV) are applicable. When the flow has strong azimuthal features, such as those generated by chevrons or lobed mixers, traditional PIV, which aligns the measurement plane parallel to the dominant flow direction is very inefficient, requiring many planes of data to be acquired and stacked up to produce the desired flow cross-sections. This paper presents PIV data acquired in a plane normal to the jet axis, directly measuring the cross-stream gradients and features of an internally mixed nozzle operating at aircraft engine flow conditions. These nozzle systems included variations in lobed mixer penetration, lobe count, lobe scalloping, and nozzle length. Several cases validating the accuracy of the PIV data are examined along with examples of its use in answering questions about the jet noise generation processes in these nozzles. Of most interest is the relationship of low frequency aft-directed noise with turbulence kinetic energy and mean velocity.

Bridges, James↗
NASA NTRS1995

Wing-section optimization for supersonic viscous flow

To improve the shape of a supersonic wing, an automated method that also includes higher fidelity to the flow physics is desirable. With this impetus, an aerodynamic optimization methodology incorporating thin-layer Navier-Stokes equations and sensitivity analysis had been previously developed. Prior to embarking upon the wind design task, the present investigation concentrated on testing the feasibility of the methodology, and the identification of adequate problem formulations, by defining two-dimensional, cost-effective test cases. Starting with two distinctly different initial airfoils, two independent shape optimizations resulted in shapes with similar features: slightly cambered, parabolic profiles with sharp leading- and trailing-edges. Secondly, the normal section to the subsonic portion of the leading edge, which had a high normal angle-of-attack, was considered. The optimization resulted in a shape with twist and camber which eliminated the adverse pressure gradient, hence, exploiting the leading-edge thrust. The wing section shapes obtained in all the test cases had the features predicted by previous studies. Therefore, it was concluded that the flowfield analyses and sensitivity coefficients were computed and fed to the present gradient-based optimizer correctly. Also, as a result of the present two-dimensional study, suggestions were made for the problem formulations which should contribute to an effective wing shape optimization.

Item, Cem C.↗
NASA NTRS2012

Global Patterns of Tectonism on Titan from Mountain Chains and Virgae

This research is based on the exploration of tectonic patterns on Titan from a global perspective. Several moons in the outer solar system display patterns of surface tectonic features that imply global stress fields driven or modified by global forces. Patterns such as these are seen in Europa's tidally induced fracture patterns, Enceladus's tiger stripes, and Ganymede's global expansion induced normal fault bands. Given its proximity to Saturn, as well as its eccentric orbit, tectonic features and global stresses may be present on Titan as well. Titan displays possible tectonic structures, such as mountain chains along its equator (Radebaugh et al. 2007), as well as the unexplored dark linear streaks termed virgae by the IAU. Imaged by Cassini with the RADAR instrument, mountain chains near the equator are observed with a predominante east-west orientation (Liu et al. 2012, Mitri et al. 2010). Orientations such as these can be explained by modifications in the global tidal stress field induced by global contraction followed by rotational spin-up. Also, due to Titan's eccentric orbit, its current rotation rate may be in an equilibrium between tidal spin-up near periapsis and spin-down near apoapsis (Barnes and Fortney 2003). Additional stress from rotational spin-up provides an asymmetry to the stress field. This, combined with an isotropic stress from radial contraction, favors the formation of equatorial mountain chains in an east-west direction. The virgae, which have been imaged by Cassini with both the Visual and Infrared Mapping Spectrometer (VIMS) and Imaging Science Subsystem (ISS) instruments, are located predominately near 30 degrees latitude in either hemisphere. Oriented with a pronounced elongation in the east-west direction, all observed virgae display similar characteristics: similar relative albedos as the surrounding terrain however darkened with an apparent neutral absorber, broken-linear or rounded sharp edges, and connected, angular elements with distinct, linear edges. Virgae imaged during northern latitude passes are oriented with their long dimensions toward Titan's antiSaturn point. If the virgae are of tectonic origin, for instance if the turn out to be i.e. grabens, they could serve as markers to Titan's global stress field. Using them in this way allows for a mapping of global tectonic patterns. These patterns will be tested for consistency against the various sources of global stress and orientations of mountain chains. By determining what drives Titan's tectonics globally, we will be able to place Titan within the context of the other outer planet icy satellites.

Cook, C.↗
NASA NTRS2015

NASA Manufacturing and Test Requirements for Normally Closed Pyrovalves for Hazardous Flight Systems Applications

Pyrovalves (figure 1, Basic Pyrovalve Design and Features,) are typically lighter, more reliable, and in most cases less expensive than other types of valves. They also consume less electrical power. They are single-use devices that are used in propulsion systems to isolate propellants or pressurant gases. These fluids may be hazardous because of their toxicity, reactivity, temperature, or high pressure. Note that in the simplified block diagram below not all detail features are shown so that those of major interest are more prominent. The diagram is provided to point out the various features that are discussed in this Specification. Features of some NC parent metal valve designs may differ. In 2013, the NESC concluded an extensive study of the reliability and safety of NC parent metal valves used in payloads carried aboard ELVs. The assessment successfully evaluated technical data to determine the risk of NC parent metal valve leakage or inadvertent activation in ELV payloads. The study resulted in numerous recommendations to ensure personnel and hardware/facility safety during ground processing of ELV payloads. One of those recommendations was to establish a NASA specification for NC parent metal valves. This Specification is a result of that recommendation, which is documented in NESC-RP-10-00614.

McDougle, Stephen H.↗
NASA NTRS2001

Characteristics of Non-Premixed Turbulent Flames in Microgravity

This project is concerned with the characteristics of turbulent hydrocarbon (primarily propane) gas-jet diffusion flames in microgravity. A microgravity environment provides the opportunity to study the structure of turbulent diffusion flames under momentum-dominated conditions (large Froude number) at moderate Reynolds number which is a combination not achievable in normal gravity. This paper summarizes progress made since the last workshop. Primarily, the features of flame radiation from microgravity turbulent jet diffusion flames in a reduced gravity environment are described. Tests were conducted for non-premixed, nitrogen diluted propane flames burning in quiescent air in the NASA Glenn 5.18 Second Zero Gravity Facility. Measured flame radiation from wedge-shaped, axial slices of the flame are compared for microgravity and normal gravity flames. Results from numerical computations of the flame using a k-e model for the turbulence are also presented to show the effects of flame radiation on the thermal field. Flame radiation is an important quantity that is impacted by buoyancy as has been shown in previous studies by the authors and also by Urban et al. It was found that jet diffusion flames burning under microgravity conditions have significantly higher radiative loss (about five to seven times higher) compared to their normal gravity counterparts because of larger flame size in microgravity and larger convective heat loss fraction from the flame in normal gravity. These studies, however, were confined to laminar flames. For the case of turbulent flames, the flame radiation is a function of time and both the time-averaged and time-dependent components are of interest. In this paper, attention is focused primarily on the time-averaged level of the radiation but the turbulent structure of the flame is also assessed from considerations of the radiation power spectra.

Hegde, U.↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning (ML) Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRSDate not supplied

Transcriptomics-based Machine Learning Analysis Predicts Space-Exposed Murine Livers

Limited sample sizes, high data dimensionality, and sensitivity to technical and biological variability of next generation sequencing (NGS), typically limits machine learning (ML) approaches in spaceflight studies that include radiation effects. However, pooling smaller studies while addressing intra- and inter-study variabilities allows for ML predictive modeling. Here, integration methods were applied to whole transcriptome shotgun sequencing (RNA-seq) data from six mouse liver GeneLab datasets (GLDS) (n ranging from 6 to 39 samples) from with a total of 81 spaceflight and ground-control samples to determine top features (i.e. genes) relevant to spaceflight including the effect of radiation exposure. RNASeq counts were normalized for each study, then merged and scaled across all datasets. Data dimensionality was reduced using a minimum redundancy maximum relevance (MRMR) methodology. Redundancy and relevance were computed using the Pearson correlation and F-statistic, respectively. The top 100 MRMR features were used to predict spaceflight vs. ground-control samples using Random Forest (RF), Support Vector Machine (SVM), and Linear Discriminant Analysis (LDA) classifiers with 5-fold cross validation (CV). Principal component analysis (PCA) on the complete feature set versus the MRMR features shows separation between spaceflight samples and ground controls (Figure 1A). The ML-based gene sets were compared against differential gene expression results obtained with DESeq2 from individual GLDS. Using all features or randomly sampled subsets at matching set sizes with MRMR, a maximum classifier accuracy of 69% was shown on the test set over 5 folds. For all classifiers, CV training using at least the top 30 MRMR genes show minimum 89% accuracy and 0.95 AUC value on the test set over 5 folds (Figure 1B). Baseline set analysis on differentially expressed genes (DEGs) identified using padj ≤ 0.05 show 295 DEGs that overlap at least two studies and 13 DEGs that overlap three studies (Figure 1C). Set analysis between the top 100 MRMR features and the DEGs showed 47 genes that overlap at least one study and 24 genes that overlap two studies. Over-representation analysis showed overlapping biological processes related to fatty acid and lipid metabolism which may indicate these processes in the response to spaceflight stressors. MRMR feature selection for the selected ML methods improve performance relative to a classifier built on all features or randomly sampled subsets. Permutation feature importance within the decorrelated MRMR features showed concordance in feature ranking between ML methods. A challenge of applying ML methods across heterogeneous NGS data is accounting for signal:noise. Here, signal validation across studies was shown by intersecting sets between top MRMR genes and DEGs from DESeq2 analysis. Non-intersecting sets introduce opportunity to explore genes relevant to differentiating space flight exposed groups and implementing ML methods across existing NGS datasets may overcome sample size limitations.

Machine Learning↗
NASA NTRS1978

Bump Cepheids - The mass anomaly as an opacity effect

Nonlinear calculations of models for bump Cepheids indicate that most of the basic features of these stars can be reproduced well by models having normal to nearly normal evolutionary masses and normal helium abundances, if Carson's opacities are adopted. The trends of the properties of the models with various physical parameters are otherwise very similar to those obtained by other authors with the Los Alamos opacities (which have led to Cepheid masses of half the evolutionary masses). Difficulties with the resonance hypothesis of Simon and Schmidt as an explanation of the bump are discussed.

Sastri, V. K.↗
NASA NTRS1979

The energy distribution of Sirius B

The origin of the X-ray emission observed from the DA white dwarf Sirius B is investigated on the basis of low-resolution short wavelength IUE spectrum. Following a correction for the influence of scattered light from Sirius A, the intensity distribution of Sirius B is obtained as a function of wavelength. Comparison of the continuous energy distribution with model atmosphere energy distributions indicates an effective temperature of 25,500 K, which is not high enough to explain the observed X rays as normal photospheric radiation. In addition, with the exception of an unusual feature in the neighborhood of the C I 1657 line, no clear evidence is found of emission lines indicative of a corona, chromosphere or disk, and the origin of the X rays remains unknown.

Boehm-Vitense, E.↗
NASA NTRS1982

Characteristics of future aircraft impacting aircraft and airport compatibility

Results are reported of an opinion survey of selected individuals at the decision-making level within the five major manufacturers of transport aircraft in the United States and Europe. Opinions were obtained concerning both possible and probable existence of over 50 compatibility-related characteristics of transport aircraft in use in the years 1990, 2000, and 2010. The maximum size of aircraft is expected to increase, at a roughly uniform rate, to the year 2010 by 85 percent in passengers, 55 percent in airfreighter payload, and 35 percent in gross weight weight. Companion to the expected growth in payloads and gross weight was the identification of probable increases in aircraft geometrical dimensions and component capability, and use of fully double-decked passenger compartments. Wing span will increase considerably more than normally expected to provide wings of higher aspect ratio. New aircraft features coming into probable use include large turboprops, synthetic jet-A fuel, winglets, wake-vortex-reducing devices and laminar flow control. New operational concepts considered probable include steep approaches, high-speed turnoffs, and taxiway towing for the aircraft, plus passenger bypass of the terminal building, expedited handling of belly cargo and an intermodal cargo container for the payloads.

Conner, D. W.↗
NASA NTRS1984

The crater density of a linear feature

The standard method of crater counting presently employed permits determination of the relative ages of areal geologic features on cratered planets and satellites. A new method is presented which calculates the areal density of the craters superposed upon linear features. The method produces an effective synthetic area around the linear feature for each crater bin size, permitting the line counts to be compared directly with standard area counts. The shape of the synthetic area produced by the method is an oval, with the calculation of this area for each in being dependent on the median crater size for that bin, as well as the length and width of the linear feature. Incorporated into the method's equation is a factor to normalize the count to one million square kilometers for each bin. Because of the dependence of the method on the crater sizes, the largest possible number of bins should be counted for the method to be the most effective.

Spong, L.↗
NASA NTRS1989

Calibration of the Berkeley EUV Airglow Rocket Spectrometer

The Berkeley Extreme-ultraviolet Airglow Rocket Spectrometer (BEARS), a multiinstrument sounding rocket payload, made comprehensive measurements of the earth's dayglow. The primary instruments consisted of two near-normal Rowland mount spectrometers: one channel to measure several atomic oxygen features at high spectral resolution (about 1.5 A) in the band passes 980-1040 and 1300-1360 A, and the other to measure EUV dayglow and the solar EUV simultaneously in a much broader bandpass (250-1150 A) at moderate resolution (about 10 A). The payload also included a hydrogen Lyman-alpha photometer to monitor the solar irradiance and goecoronal emissions. The instrument was calibrated at the EUV calibration facility at the University of California at Berkeley, and was subsequently launched successfully on September 30, 1988 aboard a four-stage experimental sounding rocket, Black Brant XII flight 12.041 WT. The calibration procedure and resulting data are presented.

Cotton, Daniel M.↗
NASA NTRS1992

On the asymptotic improvement of supervised learning by utilizing additional unlabeled samples - Normal mixture density case

The effect of additional unlabeled samples in improving the supervised learning process is studied in this paper. Three learning processes. supervised, unsupervised, and combined supervised-unsupervised, are compared by studying the asymptotic behavior of the estimates obtained under each process. Upper and lower bounds on the asymptotic covariance matrices are derived. It is shown that under a normal mixture density assumption for the probability density function of the feature space, the combined supervised-unsupervised learning is always superior to the supervised learning in achieving better estimates. Experimental results are provided to verify the theoretical concepts.

Shahshahani, Behzad M.↗
NASA NTRS1996

Are There Optical Solitary Wave Solutions in Linear Media with Group Velocity Dispersion?

A generalized exact optical bright solitary wave solution in a three dimensional dispersive linear medium is presented. The most interesting property of the solution is that it can exist in the normal group-velocity-dispersion (GVD) region. In addition, another peculiar feature is that it may achieve a condition of 'zero-dispersion' to the media so that a solitary wave of arbitrarily small amplitude may be propagated with no dependence on is pulse width.

Li, Zhonghao↗
NASA NTRS2011

High-Temperature Thermometer Using Cr-Doped GdAlO3 Broadband Luminescence

A new concept has been developed for a high-temperature luminescence-based optical thermometer that both shows the desired temperature sensitivity in the upper temperature range of present state-of-the-art luminescence thermometers (above 1,300 C), while maintaining substantial stronger luminescence signal intensity that will allow these optical thermometers to operate in the presence of the high thermal background radiation typical of industrial applications. This objective is attained by using a Cr-doped GdAlO3 (Cr:GdAlO3) sensor with an orthorhombic perovskite structure, resulting in broadband luminescence that remains strong at high temperature due to the favorable electron energy level spacing of Cr:GdAlO3. The Cr:GdAlO3 temperature (and pressure) sensor can be incorporated into, or applied onto, a component s surface when a non-contact surface temperature measurement is desired, or alternatively, the temperature sensor can be attached to the end of a fiber-optic probe that can then be positioned at the location where the temperature measurement is desired. In the case of the fiber-optic probe, both the pulsed excitation and the luminescence emission travel through the fiber-optic light guide. In either case, a pulsed light source provides excitation of the luminescence, and the broadband luminescence emission is collected. Real-time temperature measurements are obtain ed using a least-squares fitting algorithm that determines the luminescence decay time, which has a known temperature dependence established by calibration. Due to the broad absorption and emission bands for Cr:GdAlO3, there is considerable flexibility in the choice of excitation wavelength and emission wavelength detection bands. The strategic choice of the GdAlO3 host is based on its high crystal field, phase stability, and distorted symmetry at the Cr3+ occupation sites. The use of the broadband emission for temperature sensing at high temperatures is a key feature of the invention and is novel since broadband luminescence emission normally shows severe thermal quenching. The tightly bound AlO6 octahedra in GdAlO3 results in a larger energy barrier to nonradiative decays than in other materials and therefore makes using broadband emission for temperature sensing possible at high temperatures. This approach results in a substantial increase in temperature capability. For example, the most commonly used Cr-doped crystal used for luminescence-based temperature measurements, ruby, has only been demonstrated up to 600 C, whereas the Cr:GdAlO3 optical thermometer under development has already been shown to exhibit useful luminescence up to 1,300 C. Because GdAlO3 is non-reactive and is stable in harsh, high-temperature environments, sensors composed of Cr:GdAlO3 will be very well suited for remote high-temperature measurements in engine or industrial environments where its intense high-temperature luminescence will stand out above significant thermal radiation background levels.

Eldridge, Jeffrey↗
NASA NTRS2023

2022 Research & Technology Report

The 2022 Research and Technology Annual Report represents what is hopefully the “new normal” for portfolio execution. The portfolio took advantage of the best features of the virtual work environment with collaborations across the nation without any geographical constraints. This allowed key partnerships between NASA Marshall Space Flight Center (MSFC) and other NASA centers, other government agencies, industry, and academia. Also, because there were no longer any constraints on laboratory and test capabilities, we were able to make significant progress with hands-on technology development, fabrication and testing that is critical to validating the efficacy of advanced technology.

J. W. Dankanich↗
NASA NTRS2024

South Africa Ecological Conservation: Identifying and Mapping Riparian Areas in South Africa with Earth Observations

Riparian zones are thin strips of wetland that occur along the edges of rivers, lakes, and other water bodies. They provide many ecosystem and societal benefits such as stream bank stabilization, flood control, and habitat stability, making these zones very important areas to preserve and protect. Recognizing the need to accurately map these ecosystems in a cost-effective way, we partnered with the South African National Biodiversity Institute (SANBI) and the Biodiversity Survey of the Cape(BioSCape) to develop a GI methodology using Esri's ArcGIS Pro and data from Landsat 9 Operational Land Imager-2, Sentinel-2 Multispectral Instrument, and the Shuttle Radar Topography Mission to identify potential riparian zones (PRZ) and observed riparian vegetation(ORV) in the Southern Cape and the North West Province of South Africa to estimate the actual riparian vegetation (ARV) within those areas. Potential riparian ecosystems were calculated by utilizing a Topographic Wetness Index (TWI) and a water feature layer, while observed riparian vegetation were calculated by overlaying a Normalized Difference Vegetation Index (NDVI) and TWI. Actual Riparian Vegetation is determined by the overlap of ORV with PRZ and is done with conditional statements; ORV within PRZ is ARV. This method significantly improved a current riparian land cover classification since it combined high resolution optical imagery and topographic data. We anticipate such maps will be used by conservationists and practitioners interested in riparian monitoring and management.

Remote Sensing↗