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At least 775 records · Page 43

High resolution Viking Orbiter images: A useful data source for testing the viability of geomorphic processes attributed to Martian landforms

The diversity of landforms visible in the Viking images of Mars have led to a proliforation of geomorphic agents proposed to be active in shaping the Martian surface. While it is likely that numerous different processes have contributed to the geomorphology of Mars throughout Martian history, it is important that proposed Martian geomorphic agents be subjected to critical scrutiny by the scientific community. High resolution Viking Orbiter images represent a data set for investigating geomorphic processes on Mars. Geologic mapping of Mars can take place at a variety of scales, utilizing a variety of image resolutions, but an interpretation of the history of individual landforms is dependent upon the best available spatial resolution. These high resolution images provide the opportunity to examine proposed Martian geomorphic processes. It is clear that researchers may not interpret features in the same way but it is important that high resolution images of candidate features be made available to the scientific community so that a consensus can be reached. This procedure can provide a way to refine the understanding of geomorphic processes on Mars.

Zimbelman, James R.↗

The Geostationary Fourier Transform Spectrometer

The Geostationary Fourier Transform Spectrometer (GeoFTS) is an imaging spectrometer designed for a geostationary orbit (GEO) earth science mission to measure key atmospheric trace gases and process tracers related to climate change and human activity. GEO allows GeoFTS to continuously stare at a region of the earth for frequent sampling to capture the variability of biogenic fluxes and anthropogenic emissions from city to continental spatial scales and temporal scales from diurnal, synoptic, seasonal to interannual. The measurement strategy provides a process based understanding of the carbon cycle from contiguous maps of carbon dioxide (CO2), methane (CH4), carbon monoxide (CO), and chlorophyll fluorescence (CF) collected many times per day at high spatial resolution (~2.7kmx2.7km at nadir). The CO2/CH4/CO/CF measurement suite in the near infrared spectral region provides the information needed to disentangle natural and anthropogenic contributions to atmospheric carbon concentrations and to minimize uncertainties in the flow of carbon between the atmosphere and surface. The half meter cube size GeoFTS instrument is based on a Michelson interferometer design that uses all high TRL components in a modular configuration to reduce complexity and cost. It is self-contained and as independent of the spacecraft as possible with simple spacecraft interfaces, making it ideal to be a "hosted" payload on a commercial communications satellite mission. The hosted payload approach for measuring the major carbon-containing gases in the atmosphere from the geostationary vantage point will affordably advance the scientific understating of carbon cycle processes and climate change.

atmospheric trace gases↗

Spatial Predictive Modeling and Remote Sensing of Land Use Change in the Chesapeake Bay Watershed

This project was focused on modeling the processes by which increasing demand for developed land uses, brought about by changes in the regional economy and the socio-demographics of the region, are translated into a changing spatial pattern of land use. Our study focused on a portion of the Chesapeake Bay Watershed where the spatial patterns of sprawl represent a set of conditions generally prevalent in much of the U.S. Working in the region permitted us access to (i) a time-series of multi-scale and multi-temporal (including historical) satellite imagery and (ii) an established network of collaborating partners and agencies willing to share resources and to utilize developed techniques and model results. In addition, a unique parcel-level tax assessment database and linked parcel boundary maps exists for two counties in the Maryland portion of this region that made it possible to establish a historical cross-section time-series database of parcel level development decisions. Scenario analyses of future land use dynamics provided critical quantitative insight into the impact of alternative land management and policy decisions. These also have been specifically aimed at addressing growth control policies aimed at curbing exurban (sprawl) development. Our initial technical approach included three components: (i) spatial econometric modeling of the development decision, (ii) remote sensing of suburban change and residential land use density, including comparisons of past change from Landsat analyses and more traditional sources, and (iii) linkages between the two through variable initialization and supplementation of parcel level data. To these we added a fourth component, (iv) cellular automata modeling of urbanization, which proved to be a valuable addition to the project. This project has generated both remote sensing and spatially explicit socio-economic data to estimate and calibrate the parameters for two different types of land use change models and has undertaken analyses of these models. One (the CA model) is driven largely by observations on past patterns of land use change, while the other (the EC model) is driven by mechanisms of the land use change decision at the parcel level. Our project may be the first serious attempt at developing both types of models for the same area, using as much common data as possible. We have identified the strengths and weaknesses of the two approaches and plan to continue to revise each model in the light of new data and new lessons learned through continued collaboration. Questions, approaches, findings, publication and presentation lists concerning the research are also presented.

Goetz, Scott J.↗

Additional studies of forest classification accuracy as influenced by multispectral scanner spatial resolution

First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.

Sadowski, F. E.↗

A componential model of human interaction with graphs: 1. Linear regression modeling

Task analyses served as the basis for developing the Mixed Arithmetic-Perceptual (MA-P) model, which proposes (1) that people interacting with common graphs to answer common questions apply a set of component processes-searching for indicators, encoding the value of indicators, performing arithmetic operations on the values, making spatial comparisons among indicators, and repsonding; and (2) that the type of graph and user's task determine the combination and order of the components applied (i.e., the processing steps). Two experiments investigated the prediction that response time will be linearly related to the number of processing steps according to the MA-P model. Subjects used line graphs, scatter plots, and stacked bar graphs to answer comparison questions and questions requiring arithmetic calculations. A one-parameter version of the model (with equal weights for all components) and a two-parameter version (with different weights for arithmetic and nonarithmetic processes) accounted for 76%-85% of individual subjects' variance in response time and 61%-68% of the variance taken across all subjects. The discussion addresses possible modifications in the MA-P model, alternative models, and design implications from the MA-P model.

Gillan, Douglas J.↗

The NASA Cold Land Processes Pathfinder Mission (CLPP)

The Cold Land Processes Pathfinder (CLPP) mission concept has been developed to measure hydrologic properties of the Cryosphere. The science driver for the mission is to understand the variability of global water cycling and its consequences for local water resources and climate. The CLPP mission is designed to reduce uncertainty of cold-region precipitation, storage, controls, and feedbacks to the land, atmosphere, and ocean, which in turn will improve prediction of future changes in water cycle dynamics. It will provide the first high-resolution global measurements of Earth's changing snow conditions to: 1) quantify the variability of processes in cold regions, 2) improve understanding of past changes, and 3) enable breakthroughs in prediction of future water resources, weather, and climate. The CLPP concept consists of active (C- and Ku-band) and passive (K- and Ka-band) microwave sensors (with high and moderate spatial resolution respectively) to observe snow water equivalent and snow wetness at local process scales. The CLPP global sampling framework provides necessary capability to relate observed local scale snow characteristics to atmospheric forcings, improve predictive models operating at multiple scales, and to tie the short-term CLPP record to the long-term low-resolution remote sensing climate record of global snow properties.

Cline, D.↗

Alternative Vegetation States in Tropical Forests and Savannas: The Search for Consistent Signals in Diverse Remote Sensing Data

Globally, the spatial distribution of vegetation is governed primarily by climatological factors (rainfall and temperature, seasonality, and inter-annual variability). The local distribution of vegetation, however, depends on local edaphic conditions (soils and topography) and disturbances (fire, herbivory, and anthropogenic activities). Abrupt spatial or temporal changes in vegetation distribution can occur if there are positive (i.e., amplifying) feedbacks favoring certain vegetation states under otherwise similar climatic and edaphic conditions. Previous studies in the tropical savannas of Africa and other continents using the MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF) satellite data product have focused on discontinuities in the distribution of tree cover at different rainfall levels, with bimodal distributions (e.g., concentrations of high and low tree cover) interpreted as alternative vegetation states. Such observed bimodalities over large spatial extents may not be evidence for alternate states, as they may include regions that have different edaphic conditions and disturbance histories. In this study, we conduct a systematic multi-scale analysis of diverse MODIS data streams to quantify the presence and spatial consistency of alternative vegetation states in Sub-Saharan Africa. The analysis is based on the premise that major discontinuities in vegetation structure should also manifest as consistent spatial patterns in a range of remote sensing data streams, including, for example, albedo and land surface temperature (LST). Our results confirm previous observations of bimodal and multimodal distributions of estimated tree cover in the MODIS VCF. However, strong disagreements in the location of multimodality between VCF and other data streams were observed at 1 km scale. Results suggest that the observed distribution of VCF over vast spatial extents are multimodal, not because of local-scale feedbacks and emergent bifurcations (the definition of alternative states), but likely because of other factors including regional scale differences in woody dynamics associated with edaphic, disturbance, and/or anthropogenic processes. These results suggest the need for more in-depth consideration of bifurcation mechanisms and thus the likely spatial and temporal scales at which alternative states driven by different positive feedback processes should manifest.

Savanna↗

Forward and Backscattering Measurements of Rainfall using the NASA Microwave Link

This paper will present results from a study on the feasibility of making backscatter measurements from rainfall with the NASA/Microwave Link system at Wallops Island, VA. The study entails the implementation of an FMCW radar at the Link frequencies to enable simultaneous forward and backscatter measurements from rain. The Microwave Link system has been successfully employed in the development and testing of rainfall retrieval techniques. As presently configured, the Microwave Link measures attenuation and phase-shift due to rain over a 2.3 km path between the transmitting and receiving antennas. By their very nature, these measured quantities are averaged over the propagation path. As a result, the rainfall estimates obtained from the Link data are also averaged over the propagation path. However, rainfall is a highly variable process in space (as well as time). In order to gain a more detailed knowledge of its microphysics finer spatial resolutions are required. The backscatter measurements would enable range profiling over the Link path permitting a detailed study of the rainfall process. The backscatter measurements will be used in conjunction with the forward measurements and the measurements from a ground-based network of disdrometers and rain gauges located under the propagation path to develop new microwave retrieval techniques, and to test established single-frequency and dual-frequency radar retrieval algorithms relevant to the ongoing TRMM and up coming GPM missions.

Rincon, Rafael F.↗

(abstract) The EOS SAR Mission: A New Approach

The goal of the Earth Orbiting System Synthetic Aperture Radar (EOS SAR) program is to help develop the modeling and observational capabilities to predict and monitor terrestrial and oceanic processes that are either causing global change or resulting from global change. Specifically, the EOS SAR will provide important geophysical products to the EOS data set to improve our understanding of the state and functioning of the Earth system. The strategy for the EOS SAR program is to define the instrument requirements based on required input to geophysical algorithms, provide the processing capability and algorithms to generate such products on the required spatial (global) and temporal (3-5 days) scales, and to provide the spaceborne instrumentation with international partnerships. Initially this partnership has been with Germany; currently we are exploring broader international partnerships. A MultiSAR approach to the EOS SAR which includes a number of SARs provided by Japan, ESA, Germany, Canada, and the US in synergistic orbits could be used to attain a truly global monitoring capability using multifrequency polarimetric signatures. These concepts and several options for mission scenarios will be presented.

Earth Observing System radar imaging international↗

Spatial variability of soil hydraulics and remotely sensed soil parameters

The development of methods to correctly interpret remotely sensed information about soil moisture and soil temperature requires an understanding of water and energy flow in soil, because the signals originate from the surface, or from a shallow surface layer, but reflect processes in the entire profile. One formidable difficulty in this application of soil physics is the spatial heterogeneity of natural soils. Earlier work has suggested that the heterogeneity of soil hydraulic properties may be described by the frequency distribution of a single scale factor. The sensitivity of hydraulic and energetic processes to the variation of this scale factor is explored with a suitable numerical model. It is believed that such an analysis can help in deciding how accurately and extensively basic physical properties of field soils need to be known in order to interpret thermal or radar waveband signals. It appears that the saturated hydraulic conductivity needs to be known only to its order of magnitude, and that the required accuracy of the soil water retention function is about 0.02 volume fraction. Furthermore, the results may be helpful in deciding how the total scene or view field, as perceived through a sensor, is composed from the actual mosaic of transient soil properties, such as surface temperature or surface soil moisture. However, the latter proposition presupposes a random distribution of permanent properties, a condition that may not be met in many instances, and no solution of the problem is apparent.

Lascano, R. J.↗

Training site statistics from Landsat and Seasat satellite imagery registered to a common map base

Landsat and Seasat satellite imagery and training site boundary coordinates were registered to a common Universal Transverse Mercator map base in the Newport Beach area of Orange County, California. The purpose was to establish a spatially-registered, multi-sensor data base which would test the use of Seasat synthetic aperture radar imagery to improve spectral separability of channels used for land use classification of an urban area. Digital image processing techniques originally developed for the digital mosaics of the California Desert and the State of Arizona were adapted to spatially register multispectral and radar data. Techniques included control point selection from imagery and USGS topographic quadrangle maps, control point cataloguing with the Image Based Information System, and spatial and spectral rectifications of the imagery. The radar imagery was pre-processed to reduce its tendency toward uniform data distributions, so that training site statistics for selected Landsat and pre-processed Seasat imagery indicated good spectral separation between channels.

Clark, J.↗

Using Multi-Scale Modeling Systems and Satellite Data to Study the Precipitation Processes

In recent years, exponentially increasing computer power has extended Cloud Resolving Model (CRM) integrations from hours to months, the number of computational grid points from less than a thousand to close to ten million. Three-dimensional models are now more prevalent. Much attention is devoted to precipitating cloud systems where the crucial 1-km scales are resolved in horizontal domains as large as 10,000 km in two-dimensions, and 1,000 x 1,000 km2 in three-dimensions. Cloud resolving models now provide statistical information useful for developing more realistic physically based parameterizations for climate models and numerical weather prediction models. It is also expected that NWP and mesoscale model can be run in grid size similar to cloud resolving model through nesting technique. Recently, a multi-scale modeling system with unified physics was developed at NASA Goddard. It consists of (l) a cloud-resolving model (Goddard Cumulus Ensemble model, GCE model), (2) a regional scale model (a NASA unified weather research and forecast, WRF), (3) a coupled CRM and global model (Goddard Multi-scale Modeling Framework, MMF), and (4) a land modeling system. The same microphysical processes, long and short wave radiative transfer and land processes and the explicit cloud-radiation, and cloud-land surface interactive processes are applied in this multi-scale modeling system. This modeling system has been coupled with a multi-satellite simulator to use NASA high-resolution satellite data to identify the strengths and weaknesses of cloud and precipitation processes simulated by the model. In this talk, the recent developments and applications of the multi-scale modeling system will be presented. In particular, the results from using multi-scale modeling system to study the precipitating systems and hurricanes/typhoons will be presented. The high-resolution spatial and temporal visualization will be utilized to show the evolution of precipitation processes. Also how to use of the multi-satellite simulator tqimproy~ precipitation processes will be discussed.

Tao, Wei-Kuo↗

Spatial Scaling of Snow Observations and Microwave Emission Modeling During CLPX and Appropriate Satellite Sensor Resolution

Accurate estimates of snow water equivalent and other properties play an important role in weather, natural hazard, and hydrological forecasting and climate modeling over a range of scales in space and time. Remote sensing-derived estimates have traditionally been of the "snapshot" type, but techniques involving models with assimilation are also being explored. In both cases, forward emission models are useful to understand the observed passive microwave signatures and developing retrieval algorithms. However, mismatches between passive microwave sensor resolutions and the scales of processes controlling subpixel heterogeneity can affect the accuracy of the estimates. Improving the spatial resolution of new passive microwave satellite sensors is a major desire in order to (literally) resolve such subpixel heterogeneity, but limited spacecraft and mission resources impose severe constraints and tradeoffs. In order to maximize science return while mitigating risk for a satellite concept, it is essential to understand the scaling behavior of snow in terms of what the sensor sees (brightness temperature) as well as in terms of the actual variability of snow. NASA's Cold Land Processes Experiment-1 (CLPX-1: Colorado, 2002 and 2003) was designed to provide data to measure these scaling behaviors for varying snow conditions in areas with forested, alpine, and meadow/pasture land cover. We will use observations from CLPX-1 ground, airborne, and satellite passive microwave sensors to examine and evaluate the scaling behavior of observed and modeled brightness temperatures and observed and retrieved snow parameters across scales from meters to 10's of kilometers. The conclusions will provide direct examples of the appropriate spatial sampling scales of new sensors for snow remote sensing. The analyses will also illustrate the effects and spatial scales of the underlying phenomena (e.g., land cover) that control subpixel heterogeneity.

Kim, Edward J.↗

Impact experimentation and the microgravity environment: An overview

Impact is an ubiquitous physical process in the solar system. It occurs on all solid bodies and operates over a spectrum of scales, influencing geologic processes ranging from accretion, the early evolution of planetary bodies, the petrogenetic and spatial relations of lunar samples, the surface characteristics and interpretation of spectral data of asteroidal bodies, to the nature of some meteorites. Understanding impact phenomena is therefore paramount in constraining and underpinning a large number of research efforts into fundamental planetary geology. Gravity is an important parameter in impact processes. The physical environment offered by the Space Station represents an unique opportunity to extend the experimental aspect of impact studies into the microgravity (less than 1 g) regime. Through the use of free floating targets, it may be possible to explore in detail phenomena associated with the collision of bodies. Such experiments can address questions regarding early and late accretional processes, catastrophic disruption and asteroidal evolution, as well as the effects of large impacts on the momentum and spin of the target bodies. The last question is of considerable topical interest with respect to the hypothesized origin of the moon by a Mars-sized impact on Earth.

Grieve, R. A. F.↗

Aeroelastic Deformation Measurements of Flap, Gap, and Overhang on a Semispan Model

Single-camera, single-view videogrammetry has been used to determine static aeroelastic deformation of a slotted flap configuration on a semispan model at the National Transonic Facility (NTF). Deformation was determined by comparing wind-off to wind-on spatial data from targets placed on the main element, shroud, and flap of the model. Digitized video images from a camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. The videogrammetric technique has been established at NASA facilities as the technique of choice when high-volume static aeroelastic data with minimum impact on data taking is required. The primary measurement at the NTF with this technique in the past has been the measurement of static aeroelastic wing twist on full span models. The first results using the videogrammetric technique for the measurement of component deformation during semispan testing at the NTF are presented.

Burner, A. W.↗

Aeroelastic Deformation Measurements of Flap, Gap, and Overhang on a Semispan Model

Single-camera, single-view videogrammetry has been used for the first time to determine static aeroelastic deformation of a slotted flap configuration on a semispan model at the National Transonic Facility (NTF). Deformation was determined by comparing wind-off to wind-on spatial data from targets placed on the main element, shroud, and flap of the model. Digitized video images from a camera were recorded and processed to automatically determine target image plane locations that were then corrected for sensor, lens, and frame grabber spatial errors. The videogrammetric technique used for the measurements presented here has been established at NASA facilities as the technique of choice when high-volume static aeroelastic data with minimum impact on data taking is required. However, the primary measurement at the NTF with this technique in the past has been the measurement of the static aeroelastic wing twist of the main wing element on full span models rather than for the measurement of component deformation. Considerations for using the videogrammetric technique for semispan component deformation measurements as well as representative results are presented.

Burner, A. W.↗

The ALEXIS data processing package: An IDL based system

The Array of Low Energy X-ray Imaging Sensors (ALEXIS) experiment consists of a mini-satellite containing six wide angle EUV/ultrasoft x-ray telescopes. Its purpose is to map out the sky in three narrow (approximately 5 percent) bandpasses around 66, 71, and 93 eV. The 66 and 71 eV bandpasses are centered on intense Fe emission lines which are characteristic of million degree plasmas such as the one thought to produce the soft x-ray background. The 93 eV bandpass is not near any strong emission lines and is more sensitive to continuum sources. The mission will be launched on the Pegasus Air Launched Vehicle in the second half of 1992 into a 400-nautical-mile, high inclination orbit and will be controlled entirely from a small ground station located at Los Alamos. The project is a collaborative effort between Los Alamos National Laboratory, Sandia National Laboratory, and the University of California-Berkeley Space Sciences Laboratory. The six telescopes are arranged in three pairs. As the satellite spins twice a minute they scan the entire anti-solar hemisphere. Each f/1 telescope consists of a spherical, multilayer-coated mirror with a curved, microchannel plate detector located at the prime focus. The multilayer coatings determine the bandpasses of the telescopes. The field of view of each telescope is 30 degrees with a spatial resolution of 0.5 degree, limited by spherical aberration. The data processing requirements for ALEXIS are large. Each event is one of the six telescopes is telemetered to the ground with its time of arrival and position on the detector. This information must be folded with the aspect solution for the satellite to reconstruct the direction on the sky from which the photon came. Because of the way the six telescopes scan the sky, the effective exposure calculation is also very computationally intensive. ALEXIS may generate up to 100 megabytes of raw data per day, which are converted into a gigabyte per day of processed data. While the processing job for ALEXIS is sizable, the programming staff is small. To maximize programming efficiency, and to make the best use of tools available in the public domain, we chose IDL as our software development platform. IDL was used from the start of instrument development through flight. We use IDL as a top-level executive for the processing tasks (replacing Unix shell scripts), as a device independent graphics engine, as a database manager, and as a final data manipulator. IDL routines spawn special purpose C programs to perform detailed telemetry deconvolution and other specialized functions. We discuss the use of IDL and C within the processing and archiving strategy for the ALEXIS data anlaysis system as implemented on a SPARCstation platform. We also show results from our End-to-End software simulation capability as processed by our analysis codes.

Bloch, J. J.↗

Optical implementation of neocognitron and its applications to radar signature discrimination

A feature-extraction-based optoelectronic neural network is introduced. The system implementation approach applies the principle of the neocognitron paradigm first introduced by Fukushima et al. (1983). A multichannel correlator is used as a building block of a generic single layer of the neocognitron for shift-invariant feature correlation. Multilayer processing is achieved by iteratively feeding back the output of the feature correlator to the input spatial light modulator. Successful pattern recognition with intraclass fault tolerance and interclass discrimination is achieved using this optoelectronic neocognitron. Detailed system analysis is described. Experimental demonstration of radar signature processing is also provided.

Chao, Tien-Hsin↗