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NASA NTRS2006

Sensing Super-position: Visual Instrument Sensor Replacement

Maluf, David A.↗

NASA NTRS2007

Sensing Super-Position: Human Sensing Beyond the Visual Spectrum

The coming decade of fast, cheap and miniaturized electronics and sensory devices opens new pathways for the development of sophisticated equipment to overcome limitations of the human senses. This paper addresses the technical feasibility of augmenting human vision through Sensing Super-position by mixing natural Human sensing. The current implementation of the device translates visual and other passive or active sensory instruments into sounds, which become relevant when the visual resolution is insufficient for very difficult and particular sensing tasks. A successful Sensing Super-position meets many human and pilot vehicle system requirements. The system can be further developed into cheap, portable, and low power taking into account the limited capabilities of the human user as well as the typical characteristics of his dynamic environment. The system operates in real time, giving the desired information for the particular augmented sensing tasks. The Sensing Super-position device increases the image resolution perception and is obtained via an auditory representation as well as the visual representation. Auditory mapping is performed to distribute an image in time. The three-dimensional spatial brightness and multi-spectral maps of a sensed image are processed using real-time image processing techniques (e.g. histogram normalization) and transformed into a two-dimensional map of an audio signal as a function of frequency and time. This paper details the approach of developing Sensing Super-position systems as a way to augment the human vision system by exploiting the capabilities of Lie human hearing system as an additional neural input. The human hearing system is capable of learning to process and interpret extremely complicated and rapidly changing auditory patterns. The known capabilities of the human hearing system to learn and understand complicated auditory patterns provided the basic motivation for developing an image-to-sound mapping system. The human brain is superior to most existing computer systems in rapidly extracting relevant information from blurred, noisy, and redundant images. From a theoretical viewpoint, this means that the available bandwidth is not exploited in an optimal way. While image-processing techniques can manipulate, condense and focus the information (e.g., Fourier Transforms), keeping the mapping as direct and simple as possible might also reduce the risk of accidentally filtering out important clues. After all, especially a perfect non-redundant sound representation is prone to loss of relevant information in the non-perfect human hearing system. Also, a complicated non-redundant image-to-sound mapping may well be far more difficult to learn and comprehend than a straightforward mapping, while the mapping system would increase in complexity and cost. This work will demonstrate some basic information processing for optimal information capture for headmounted systems.

Maluf, David A.↗

NASA NTRS1995

The composite classification problem in optical information processing

Optical pattern recognition allows objects to be recognized from their images and permits their positional parameters to be estimated accurately in real time. The guiding principle behind optical pattern recognition is that a lens focusing a beam of coherent light modulated with an image produces the two-dimensinal Fourier transform of that image. When the resulting output is further transformed by the matched filter corresponding to the original image, one obtains the autocorrelation function of the original image, which has a peak at the origin. Such a device is called an optical correlator and may be used to recognize the locate the image for which it is designed. (From a practical perspective, an approximation to the matched filter must be used since the spatial light modulator (SLM) on which the filter is implemented usually does not allow one to independently control both the magnitude and phase of the filter.) Generally, one is not just concerned with recognizing a single image but is interested in recognizing a variety of rotated and scaled views of a particular image. In order to recognize these different views using an optical correlator, one may select a subset of these views (whose elements are called training images) and then use a composite filter that is designed to produce a correlation peak for each training image. Presumably, these peaks should be sharp and easily distinguishable from the surrounding correlation plane values. In this report we consider two areas of research regarding composite optical correlators. First, we consider the question of how best to choose the training images that are used to design the composite filter. With regard to quantity, the number of training images should be large enough to adequately represent all possible views of the targeted object yet small enough to ensure that the resolution of the filter is not exhausted. As for the images themselves, they should be distinct enough to avoid numerical difficulties yet similar enough to avoid gaps in which certain views of the target will be unrecognized. One method that we introduce to study this problem is called probing and involves the creation of the artificial imagery. The second problem we consider involves the clasification of the composite filter's correlation plane data. In particular, we would like to determine not only whether or not we are viewing a training image, but, in the former case, we would like to determine which training image is being viewed. This second problem is investigated using traditional M-ary hypothesis testing techniques.

Hall, Eric B.↗

NASA NTRS2000

Applications of Fractal Analytical Techniques in the Estimation of Operational Scale

The observational scale and the resolution of remotely sensed imagery are essential considerations in the interpretation process. Many atmospheric, hydrologic, and other natural and human-influenced spatial phenomena are inherently scale dependent and are governed by different physical processes at different spatial domains. This spatial and operational heterogeneity constrains the ability to compare interpretations of phenomena and processes observed in higher spatial resolution imagery to similar interpretations obtained from lower resolution imagery. This is a particularly acute problem, since longterm global change investigations will require high spatial resolution Earth Observing System (EOS), Landsat 7, or commercial satellite data to be combined with lower resolution imagery from older sensors such as Landsat TM and MSS. Fractal analysis is a useful technique for identifying the effects of scale changes on remotely sensed imagery. The fractal dimension of an image is a non-integer value between two and three which indicates the degree of complexity in the texture and shapes depicted in the image. A true fractal surface exhibits self-similarity, a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution, and the slope of the fractal dimension-resolution relationship would be zero. Most geographical phenomena, however, are not self-similar at all scales, but they can be modeled by a stochastic fractal in which the scaling properties of the image exhibit patterns that can be described by statistics such as area-perimeter ratios and autocovariances. Stochastic fractal sets relax the self-similarity assumption and measure many scales and resolutions to represent the varying form of a phenomenon as the pixel size is increased in a convolution process. We have observed that for images of homogeneous land covers, the fractal dimension varies linearly with changes in resolution or pixel size over the range of past, current, and planned space-borne sensors. This relationship differs significantly in images of agricultural, urban, and forest land covers, with urban areas retaining the same level of complexity, forested areas growing smoother, and agricultural areas growing more complex as small pixels are aggregated into larger, mixed pixels. Images of scenes having a mixture of land covers have fractal dimensions that exhibit a non-linear, complex relationship to pixel size. Measuring the fractal dimension of a difference image derived from two images of the same area obtained on different dates showed that the fractal dimension increased steadily, then exhibited a sharp decrease at increasing levels of pixel aggregation. This breakpoint of the fractal dimension/resolution plot is related to the spatial domain or operational scale of the phenomenon exhibiting the predominant visible difference between the two images (in this case, mountain snow cover). The degree to which an image departs from a theoretical ideal fractal surface provides clues as to how much information is altered or lost in the processes of rescaling and rectification. The measured fractal dimension of complex, composite land covers such as urban areas also provides a useful textural index that can assist image classification of complex scenes.

Emerson, Charles W.↗

NASA NTRS1992

Airborne lidar and radiometric observations of PBL- and low clouds

Boundary layer- and low altitude clouds over open ocean and continent areas have been studied during several field campaigns since mid-1990 using the French airborne backscatter lidar LEANDRE in conjunction with on-board IR and visible radiometers. LEANDRE is an automatic system, and a modification of the instrumental parameters, when airborne, is computer controlled through an operator keyboard. The vertical range squared lidar signals and instrument status are displayed in real time on two dedicated monitors. The lidar is used either down- or up-looking while the aircraft is flying above or below clouds. A switching of the viewing configuration takes about a minute. The lidar measurements provide a high resolution description of cloud morphology and holes in cloud layers. The flights were conducted during various meteorological conditions on single or multilayer stratocumulus and cumulus decks. Analysis on a single shot basis of cloud top (or bottom) altitude and a plot of the corresponding histogram allows one to determine a probability density function (PDF). The preliminary results show the PDFs for cloud top are not Gaussian and symmetric about the mean value. The skewness varies with atmospheric conditions. An example of results recorded over the Atlantic ocean near Biarritz is displayed, showing: (1) the range squared lidar signals as a function of time (here 100 s corresponds to about 8 km, 60 shots are averaged on horizontal); the Planetary Boundary Layer (PBL) - up to 600 m - is observed at the beginning of the leg as well as on surface returns, giving an indication of the porosity; (2) the cloud top altitude variation between 2.4 to 2.8 km during the 150 to 320 s section; and (3) the corresponding PDF. Similar results are obtained on stratocumulus over land. Single shot measurements can be used also to determine an optical porosity at a small scale as well as a fractional cloudiness at a larger scale. A comparison of cloud top altitude retrieved from lidar and narrowbeam IR radiometer is conducted to study the scale integration problem. A good agreement within less than 100 m relies on spatial uniformity and an optically thick layer. In the presence of holes, a discrepancy is observed. This is illustrated in figure 2, displaying as a function of time (1) the lidar signals; (2) the target temperature (either clouds or sea surface) retreived from a narrowbeam IR radiometer, 17 C is the sea surface temperature on that day; and (3) the visible flux, linked to cloud albedo, measured by a pyranometer. In preparation of ASTEX, down- and up-looking measurements where conducted on stratocumulus clouds over the Atlantic Ocean near Quimper in Brittany. Depending on the flight pattern orientation with respect to the wind, the top and bottom cloud morphologies are different. Preliminary results are given on cloud morphology, cloud top PDFs, optical porosity, fractional cloudiness, and comparison of lidar and radiometric measurements.

Flamant, P. H.↗

NASA NTRS2021

Gravity Wave Observations by the Mars Science Laboratory REMS Pressure Sensor and Comparison with Mesoscale Atmospheric Modeling with MarsWRF

Surface pressure measurements on Mars have revealed a wide variety of atmospheric phenomena. The Mars Science Laboratory Rover Environmental Monitoring Station pressure sensor dataset is now the longest duration record of surface pressure on Mars. We use the first 2580 martian sols, nearly 4 Mars years,of measurements to identify atmospheric pressure waves with periods of tens of minutes to hours using wavelet analysis on residual pressure after the tidal harmonics are removed. We find these waves have a clear diurnal cycle with strongest activity in the early morning and late evening and a seasonal cycle with the strongest waves in the second half of the martian year (Ls= 180-360°). The strongest such waves of the entire mission occurred during the Mars Year 34 global dust storm. Comparable atmospheric waves are identified using atmospheric modeling with the MarsWRF general circulation model in a “nested” high spatial resolution mode. With the support of the modeling, we find these waves best fit the expected properties of inertia-gravity waves with horizontal wavelengths of O(100s) of km. PLAIN LANGUAGE SUMMARY Measuring air pressure from the surface of Mars has revealed a wide variety of atmospheric phenomena. The Curiosity rover's record or surface air pressure is now the longest yet made on Mars.We use the first ~8 years of Curiosity's pressure observations to look for atmospheric waves with periods of tens of minutes to hours. We find these waves have a clear pattern in their daily behavior with the strongest activity in the early morning and late evening and a seasonal cycle with the strongest waves in the second half of the martian year (Northern hemisphere fall and winter). The strongest such waves occurred in 2018 during a global dust storm. We find comparable waves in atmospheric modeling. With the support of modeling, we find these waves best fit the expected properties of buoyancy waves forced by airflow over topography with horizontal wavelengths of 100-1000 km.

Scott D Guzewich↗

NASA NTRSDate not supplied

Utilizing Earth Observations to Understand Landscape Patterns and Assist in Wildlife Management in Iona National Park, Angola

Following the end of the Angolan Civil War (1975-2002), human habitation in Iona National Park has grown exponentially, as has the livestock population. An ongoing drought beginning in 2017 has brought people, livestock, and wildlife into increasing competition for resources within the park. This study used Earth observation data, primarily Landsat and Sentinel imagery, to examine landscape trends to improve wildlife preservation approaches in Iona National Park, Angola. In collaboration with the NGO African Parks, we developed a robust land use and land cover (LULC) classification model using remote sensing data to augment sparse ground-based data in this arid land region. We used Google Earth Engine and a random forest classifier to map vegetation types, water bodies, and potential wildlife habitats. This analysis resulted in a high spatial resolution LULC time-series between 1984-2023, highlighting critical periods of socioecological change over the past 40 years. These results increased the partner’s ability to make scientifically grounded decisions about resource allocation and conservation priorities. This analysis supports the feasibility of applying remote sensing techniques coupled with machine learning models in dry regions, where standard survey methods are frequently limited by accessibility and resource availability. However, we identified limitations in ground-truth data and the difficulty of recognizing certain vegetation types in arid areas. Despite these limitations, the study demonstrated Earth observations' ability to transform wildlife management techniques in distant and data-scarce locations, providing a reproducible foundation for similar ecosystems around the world.

Emmanuel Aklie↗

NASA NTRS1972

Discrimination of fluoride and phosphate contamination in central Florida for analyses of environmental effects

A study was made of the spatial registration of fluoride and phosphate pollution parameters in central Florida by utilizing remote sensing techniques. Multispectral remote sensing data were collected over the area and processed to produce multispectral recognition maps. These processed data were used to map land areas and waters containing concentrations of fluoride and phosphate. Maps showing distribution of affected and unaffected vegetation were produced. In addition, the multispectral data were processed by single band radiometric slicing to produce radiometric maps used to delineate areas of high ultraviolet radiance, which indicates high fluoride concentrations. The multispectral parameter maps and radiometric maps in combination showed distinctive patterns, which are correlated with areas known to be affected by fluoride and phosphate contamination. These remote sensing techniques have the potential for regional use to assess the environmental impact of fluoride and phosphate wastes in central Florida.

Coker, A. E.↗

NASA NTRS1974

Behavior of atmospheric ozone determined from Nimbus satellite backscatter ultraviolet data

A substantial global data base on the spatial and temporal variations of high level atmospheric ozone distribution and total ozone amount for the time period 1970 through 1973 was obtained by the Backscatter Ultraviolet (BUV) instrument onboard the Nimbus 4 satellite. BUV total ozone data from all available orbits on each day of the period were processed to obtain zonal mean ozone amounts. Northern Hemisphere ozone and Southern Hemisphere ozone values are given, and the interhemispheric relationships identified. Vertical ozone profile information is interpreted to furnish data on seasonal total ozone changes. Selected ozone mixing ratio cross sections were analyzed, and the resulting zonally-symmetric patterns are presented.

Krueger, A. J.↗

NASA NTRS1982

A microprocessor-based one dimensional optical data processor for spatial frequency analysis

A high degree of accuracy was obtained in measuring the spatial frequency spectrum of known samples using an optical data processor based on a microprocessor, which reliably collected intensity versus angle data. Stray light control, system alignment, and angle measurement problems were addressed and solved. The capabilities of the instrument were extended by the addition of appropriate optics to allow the use of different wavelengths of laser radiation and by increasing the travel limits of the rotating arm to + or - 160 degrees. The acquisition, storage, and plotting of data by the computer permits the researcher a free hand in data manipulation such as subtracting background scattering from a diffraction pattern. Tests conducted to verify the operation of the processor using a 25 mm diameter pinhole, a 39.37 line pairs per mm series of multiple slits, and a microscope slide coated with 1.091 mm diameter polystyrene latex spheres are described.

Collier, R. L.↗

NASA NTRS1982

The Delta-K ocean wave spectrometer - Aircraft measurements and theoretical system analysis

Measurements of the relative strength of ocean surface wave spectral components have been made from an aircraft using the two-frequency microwave resonance technique. A coherent Ku-band radar was used to study the Bragg type resonance matching (at the difference frequency Delta-f) to the surface wave components. The spatial spectrum of the surface reflectivity modulation was then computed as the value of Delta-f was varied over a matching range of approximately 15 150 m in surface wavelength. This paper contains experimental results from flights conducted during the 1979 MARSEN project and the 1980 ARSLOE project, and the objective here is to present the radar results in terms of the variety of surface illumination geometries encountered. It will be shown that the MARSEN results, with the narrow footprint, are consistent with a one-dimensional theoretical approach and that the ARSLOE results, with a symmetric beam pattern, agree well with the existing two-dimensional theory.

Weissman, D. E.↗

NASA NTRS1986

Meso-beta scale perturbations of the wind field by thunderstorm cells

Data from the high density storm-scale rawinsonde network of the Severe Environmental Storms and Mesoscale Experiment revealed temporal and spatial changes in the divergence fields of the troposphere in response to severe storm evolution on May 2, 1979; these changes were detectable on the meso-beta scale. This unique set of data was subsequently used to study the evolution of the wind, divergence and vertical motion fields in the presence of intense convection. Mid- and upper-tropospheric divergence was superimposed over low-level convergence. The divergence, which has a maximum value of .0004/s, occurred 75 to 100 km upwind as well as over the tornadic cells. To the south of the storm cells, the kinematic pattern was in reverse, upper level convergence was superimposed over low-level divergence. A vertical motion doublet was found to ascend over the squall line and descend about 70 km south of the squall line. It is suggested that the following effects are accountable for the nature of the kinematic fields: (1) blocking of tropospheric environmental flow by the storm cells, (2) anvil outflows, particularly from the tornadic cells, and (3) divergence from the exit region of the jet stream.

Ulanski, S. L.↗

NASA NTRS1996

Temporal Evolution of SL-9 Impact Sites on Jupiter and Global Maps of Jupiter from Multi-Observatory Visible and Infrared Images

The objective of this research was to investigate the temporal behavior of the impact features on Jupiter created by the fragments of the Shoemaker Levy-9 comet that collided with the planet in July 1994. The primary observations used in the study were ground based images of Jupiter acquired from the Swedish Solar Vacuum Tube on the island of La Palma in the Canary Islands. The measurement of position of the impact features in images acquired immediately after the impact over a period of a few days revealed that the apparent drift rates were too high and that a repetitive pattern could be seen in the longitude position on successive rotations. This could be explained only by the fact that the measured longitudes of the impact sites were being affected by parallax due to a significant elevation of the impact debris above the nominal cloud top altitude value used for image navigation. Once the apparent positions are analyzed as a function of the meridian angle, the parallax equation can be used to infer the height of the impact features above the cloud deck, once the true impact position (longitude) for the feature is known. Due to their inherent high spatial resolution, the HST measurements of the impact site locations have been accepted widely. However, these suffer from the parallax themselves since few of them were obtained at central meridian. Ground based imaging have the potential to improve this knowledge as they do observe most of the impact sites on either side of the central meridian, except for the degraded resolution. Measurements over a large number of images enables us to minimize the position error through regression and thus estimate both the actual impact site location devoid of parallax bias, and also of the altitude level of the impact debris above the cloud deck. With rapid imaging there is the potential to examine the time evolution of the altitude level. Several hundred ground based images were processed, navigated and subjected to the impact site location measurements. HST images were also acquired and used to calibrate the results and to improve the sample. The resources available enabled an in-depth study only of impact site A, however, many more images have since become available through the global network observations through Lowell Observatory.

Limaye, Sanjay S.↗

NASA NTRS1979

The benefits of using short-interval satellite images to derive winds for tropical cyclones

During the 1975, 1976 and 1977 North Atlantic hurricane seasons, NOAA/NESS and NASA/GSFC conducted a cooperative program to determine the best resolution and frequency now available from satellite images for deriving winds to study and forecast tropical cyclones. High spatial and temporal resolution satellite imagery made it feasible to provide a large number of lower and upper tropospheric winds which can be obtained by tracking clouds within 650 km of tropical cyclone centers. Up to 10 (5) times as many low-level winds were derived from images spaced at 3 or 7.5 min intervals as from those at 30 min (15 min) intervals. Rapid-scan full-resolution IR and visible images minimized the 'erroneous' winds derived by tracking cloud elements that propagate by growing on one side and dissipating on the other and by tracking repetitive patterns that provided ambiguous indications of direction of movement.

Rodgers, E.↗

NASA NTRS1987

Mass distribution and evolutionary scheme for central stars of planetary nebulae

IUE data and a distance measuring method that considered central stars in optically thick nebulae were used to examine mass distributions of planetary nebulae. Other data such as spectral type, spatial and kinematic characteristics, etc., were studied to derive relationships between population type and mass distribution. A central star mass range of at least 0.55 solar mass was obtained. Stars with masses of at least 0.64 solar mass, concentrated in the galactic disk, originated from 1.5 solar mass stars. Low mass nuclei originated in old disk or halo populations and evolved from 1.0 solar mass objects. A mass-loss parameter value of 1/3 was calculated for red giants, implying that white dwarfs evolve from stars of under 5 solar masses. Mass distributions around planetary nuclei were concluded to follow patterns associated with the individual mass.

Heap, Sara R.↗

NASA NTRS2003

A Comparison of Latent Heat Fluxes over Global Oceans for Four Flux Products

To improve our understanding of global energy and water cycle variability, and to improve model simulations of climate variations, it is vital to have accurate latent heat fluxes (LHF) over global oceans. Monthly LHF, 10-m wind speed (U10m), 10-m specific humidity (Q10h), and sea-air humidity difference (Qs-Q10m) of GSSTF2 (version 2 Goddard Satellite-based Surface Turbulent Fluxes) over global Oceans during 1992-93 are compared with those of HOAPS (Hamburg Ocean Atmosphere Parameters and Fluxes from Satellite Data), NCEP (NCEP/NCAR reanalysis). The mean differences, standard deviations of differences, and temporal correlation of these monthly variables over global Oceans during 1992-93 between GSSTF2 and each of the three datasets are analyzed. The large-scale patterns of the 2yr-mean fields for these variables are similar among these four datasets, but significant quantitative differences are found. The temporal correlation is higher in the northern extratropics than in the south for all variables, with the contrast being especially large for da Silva as a result of more missing ship data in the south. The da Silva has extremely low temporal correlation and large differences with GSSTF2 for all variables in the southern extratropics, indicating that da Silva hardly produces a realistic variability in these variables. The NCEP has extremely low temporal correlation (0.27) and large spatial variations of differences with GSSTF2 for Qs-Q10m in the tropics, which causes the low correlation for LHF. Over the tropics, the HOAPS LHF is significantly smaller than GSSTF2 by approx. 31% (37 W/sq m), whereas the other two datasets are comparable to GSSTF2. This is because the HOAPS has systematically smaller LHF than GSSTF2 in space, while the other two datasets have very large spatial variations of large positive and negative LHF differences with GSSTF2 to cancel and to produce smaller regional-mean differences. Our analyses suggest that the GSSTF2 latent heat flux, surface air humidity, and winds are likely to be more realistic than the other three flux datasets examined, although those of GSSTF2 are still subject to regional biases.

Chou, Shu-Hsien↗

NASA NTRS1995

Cellular localization of the Ca2+ binding TCH3 protein of Arabidopsis

TCH3 is an Arabidopsis touch (TCH) gene isolated as a result of its strong and rapid upregulation in response to mechanical stimuli, such as touch and wind. TCH3 encodes an unusual calcium ion-binding protein that is closely related to calmodulin but has the potential to bind six calcium ions. Here it is shown that TCH3 shows a restricted pattern of accumulation during Arabidopsis vegetative development. These data provide insight into the endogenous signals that may regulate TCH3 expression and the sites of TCH3 action. TCH3 is abundant in the shoot apical meristem, vascular tissue, the root columella and pericycle cells that give rise to lateral roots. In addition, TCH3 accumulation in cells of developing shoots and roots closely correlates with the process of cellular expansion. Following wind stimulation, TCH3 becomes more abundant in specific regions including the branchpoints of leaf primordia and stipules, pith parenchyma, and the vascular tissue. The consequences of TCH3 upregulation by wind are therefore spatially restricted and TCH3 may function at these sites to modify cell or tissue characteristics following mechanical stimulation. Because TCH3 accumulates specifically in cells and tissues that are thought to be under the influence of auxin, auxin levels may regulate TCH3 expression during development. TCH3 is upregulated in response to low levels of exogenous indole-3-acetic acid (IAA), but not by inactive auxin-related compounds. These results suggest that TCH3 protein may play roles in mediating physiological responses to auxin and mechanical environmental stimuli.

NASA Discipline Plant Biology↗

NASA NTRS1996

Paleobiology, community ecology, and scales of ecological pattern

The fossil record provides a wealth of data on the role of regional processes and historical events in shaping biological communities over a variety of time scales. The Quaternary record with its evidence of repeated climatic change shows that both terrestrial and marine species shifted independently rather than as cohesive assemblages over scales of thousands of years. Larger scale patterns also show a strong individualistic component to taxon dynamics; assemblage stability, when it occurs, is difficult to separate from shared responses to low rates of environmental change. Nevertheless, the fossil record does suggest that some biotic interactions influence large-scale ecological and evolutionary patterns, albeit in more diffuse and protracted fashions than those generally studied by community ecologists. These include: (1) the resistance by incumbents to the establishment of new or invading taxa, with episodes of explosive diversification often appearing contingent on the removal of incumbents at extinction events; (2) steady states of within-habitat and global diversity at longer time scales (10(7)-l0(8) yr), despite enormous turnover of taxa; and (3) morphological and biogeographic responses to increased intensities of predation and substratum disturbance over similarly long time scales. The behavior of species and communities over the array of temporal and spatial scales in the fossil record takes on additional significance for framing conservation strategies, and for understanding recovery of species, lineages, and communities from environmental changes.

NASA Discipline Exobiology↗