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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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NASA NTRS2001

Joint Characterization of Vegetation by Satellite Observations from Visible to Microwave Wavelengths - A Sensitivity Analysis

This study presents an evaluation and comparison of visible, near-infrared, passive, and active microwave observations for vegetation characterization on a global basis for a year, with spatial resolution compatible with climatological studies. Visible and near-infrared observations along with the Normalized Difference Vegetation Index come from the Advanced Very High Resolution Radiometer. An atlas of monthly mean microwave land surface emissivities from 19 to 85 GHz has been calculated from the Special Sensor Microwave/Imager for a year, suppressing the atmospheric problems encountered with the use of simple channel combinations. The active microwave measurements are provided by the ERS-1 scatterometer at 5.25 GHz. The capacity to discriminate between vegetation types and to detect the vegetation phenology is assessed in the context of a vegetation classification obtained from in situ observations. A clustering technique derived from the Kohonen topological maps is used to merge the three data sets and interpret their relative variations. NDVI varies with vegetation density but is not very sensitive in semiarid environments and in forested areas. Spurious seasonal cycles and large spatial variability in several areas suggest that atmospheric contamination and/or solar zenith angle drift still affect the NDVI.

NORMALIZED DIFFERENCE VEGETATIVE INDEX↗
NASA NTRS2004

Maps Characterizing the Lunar Regolith Maturity

There are several parameters characterizing maturity of the lunar regolith. Most reliable of them are the ratio Is/FeO, characterizing relative concentration of nano-phase reduced iron, and the agglutinate content. The ratio Is/FeO is often called the degree of maturity of the lunar regolith. Studies of lunar samples show that the agglutinate content correlates with the maturity degree. Besides, the abundance of crystalline component, independently of its composition, anti-correlates with the maturity degree. In present paper we examine these correlations, mapping the parameter Is/FeO, the abundance of agglutinates in the lunar regolith, and the abundance of the crystalline component presented with pyroxene, plagioclase, olivine, and ilmenite. We use measurements of lunar samples made by Lunar Soil Characterization Consortium (LSCC) and multispectral lunar data of high spatial resolution available after the Clementine mission to the Moon.

V. Kaydash↗
NASA NTRS2008

Statistical Estimation of Orbital Debris Populations with a Spectrum of Object Size

Orbital debris is a real concern for the safe operations of satellites. In general, the hazard of debris impact is a function of the size and spatial distributions of the debris populations. To describe and characterize the debris environment as reliably as possible, the current NASA Orbital Debris Engineering Model (ORDEM2000) is being upgraded to a new version based on new and better quality data. The data-driven ORDEM model covers a wide range of object sizes from 10 microns to greater than 1 meter. This paper reviews the statistical process for the estimation of the debris populations in the new ORDEM upgrade, and discusses the representation of large-size (greater than or equal to 1 m and greater than or equal to 10 cm) populations by SSN catalog objects and the validation of the statistical approach. Also, it presents results for the populations with sizes of greater than or equal to 3.3 cm, greater than or equal to 1 cm, greater than or equal to 100 micrometers, and greater than or equal to 10 micrometers. The orbital debris populations used in the new version of ORDEM are inferred from data based upon appropriate reference (or benchmark) populations instead of the binning of the multi-dimensional orbital-element space. This paper describes all of the major steps used in the population-inference procedure for each size-range. Detailed discussions on data analysis, parameter definition, the correlation between parameters and data, and uncertainty assessment are included.

Xu, Y. -l↗
NASA NTRS2009

Magnetopause Reconnection Impact Parameters from Multiple Spacecraft Magnetic Field Measurements

We present a novel technique that exploits multiple spacecraft data to determine the impact parameters of the most general form of magnetic reconnection at the magnetopause. The method consists of a superposed epoch of multiple spacecraft magnetometer measurements that yields the instantaneous magnetic spatial gradients near a magnetopause reconnection site. The gradients establish the instantaneous positions of the spacecraft relative to the reconnection site. The analysis is well suited to evaluating the spatial scales of singular field line reconnection, which is characterized by a two-dimensional x-type topology adjacent and perpendicular to a reconnecting singular field line. Application of the method to Cluster data known to lie in the vicinity of a northward IMF reconnection site establishes a field topology consistent with singular field line reconnection and a normal magnetic field component of 20 nT. The corresponding current structure consists of a 130 km sheet possibly embedding a thinner. bifurcated sheet.

Wendel, Deirdre E.↗
NASA NTRS2011

Global Precipitation Measurement, Validation, and Applications Integrated Hydrologic Validation to Improve Physical Precipitation Retrievals for GPM

Land surface modeling and data assimilation can provide dynamic land surface state variables necessary to support physical precipitation retrieval algorithms over land. It is well-known that surface emission, particularly over the range of frequencies to be included in the Global Precipitation Measurement Mission (GPM), is sensitive to land surface states, including soil properties, vegetation type and greenness, soil moisture, surface temperature, and snow cover, density, and grain size. In order to investigate the robustness of both the land surface model states and the microwave emissivity and forward radiative transfer models, we have undertaken a multi-site investigation as part of the NASA Precipitation Measurement Missions (PMM) Land Surface Characterization Working Group. Specifically, we will demonstrate the performance of the Land Information System (LIS; http://lis.gsfc.nasa.gov; Peters-Lidard et aI., 2007; Kumar et al., 2006) coupled to the Joint Center for Satellite Data Assimilation (JCSDA's) Community Radiative Transfer Model (CRTM; Weng, 2007; van Deist, 2009). The land surface is characterized by complex physical/chemical constituents and creates temporally and spatially heterogeneous surface properties in response to microwave radiation scattering. The uncertainties in surface microwave emission (both surface radiative temperature and emissivity) and very low polarization ratio are linked to difficulties in rainfall detection using low-frequency passive microwave sensors (e.g.,Kummerow et al. 2001). Therefore, addressing these issues is of utmost importance for the GPM mission. There are many approaches to parameterizing land surface emission and radiative transfer, some of which have been customized for snow (e.g., the Helsinki University of Technology or HUT radiative transfer model;) and soil moisture (e.g., the Land Surface Microwave Emission Model or LSMEM).

Peters-Lidar, Christa D.↗
NASA NTRS2013

Fast, High-Precision Readout Circuit for Detector Arrays

The GEO-CAPE mission described in NASA's Earth Science and Applications Decadal Survey requires high spatial, temporal, and spectral resolution measurements to monitor and characterize the rapidly changing chemistry of the troposphere over North and South Americas. High-frame-rate focal plane arrays (FPAs) with many pixels are needed to enable such measurements. A high-throughput digital detector readout integrated circuit (ROIC) that meets the GEO-CAPE FPA needs has been developed, fabricated, and tested. The ROIC is based on an innovative charge integrating, fast, high-precision analog-to-digital circuit that is built into each pixel. The 128×128-pixel ROIC digitizes all 16,384 pixels simultaneously at frame rates up to 16 kHz to provide a completely digital output on a single integrated circuit at an unprecedented rate of 262 million pixels per second. The approach eliminates the need for off focal plane electronics, greatly reducing volume, mass, and power compared to conventional FPA implementations. A focal plane based on this ROIC will require less than 2 W of power on a 1×1-cm integrated circuit. The ROIC is fabricated of silicon using CMOS technology. It is designed to be indium bump bonded to a variety of detector materials including silicon PIN diodes, indium antimonide (InSb), indium gallium arsenide (In- GaAs), and mercury cadmium telluride (HgCdTe) detector arrays to provide coverage over a broad spectral range in the infrared, visible, and ultraviolet spectral ranges.

Rider, David M.↗
NASA NTRS2008

Mapping Electrical Crosstalk in Pixelated Sensor Arrays

Electronic coupling effects such as Inter-Pixel Capacitance (IPC) affect the quantitative interpretation of image data from CMOS, hybrid visible and infrared imagers alike. Existing methods of characterizing IPC do not provide a map of the spatial variation of IPC over all pixels. We demonstrate a deterministic method that provides a direct quantitative map of the crosstalk across an imager. The approach requires only the ability to reset single pixels to an arbitrary voltage, different from the rest of the imager. No illumination source is required. Mapping IPC independently for each pixel is also made practical by the greater S/N ratio achievable for an electrical stimulus than for an optical stimulus, which is subject to both Poisson statistics and diffusion effects of photo-generated charge. The data we present illustrates a more complex picture of IPC in Teledyne HgCdTe and HyViSi focal plane arrays than is presently understood, including the presence of a newly discovered, long range IPC in the HyViSi FPA that extends tens of pixels in distance, likely stemming from extended field effects in the fully depleted substrate. The sensitivity of the measurement approach has been shown to be good enough to distinguish spatial structure in IPC of the order of 0.1%.

focal plane array↗
NASA NTRS2014

Introducing Multisensor Satellite Radiance-Based Evaluation for Regional Earth System Modeling

Earth System modeling has become more complex, and its evaluation using satellite data has also become more difficult due to model and data diversity. Therefore, the fundamental methodology of using satellite direct measurements with instrumental simulators should be addressed especially for modeling community members lacking a solid background of radiative transfer and scattering theory. This manuscript introduces principles of multisatellite, multisensor radiance-based evaluation methods for a fully coupled regional Earth System model: NASA-Unified Weather Research and Forecasting (NU-WRF) model. We use a NU-WRF case study simulation over West Africa as an example of evaluating aerosol-cloud-precipitation-land processes with various satellite observations. NU-WRF-simulated geophysical parameters are converted to the satellite-observable raw radiance and backscatter under nearly consistent physics assumptions via the multisensor satellite simulator, the Goddard Satellite Data Simulator Unit. We present varied examples of simple yet robust methods that characterize forecast errors and model physics biases through the spatial and statistical interpretation of various satellite raw signals: infrared brightness temperature (Tb) for surface skin temperature and cloud top temperature, microwave Tb for precipitation ice and surface flooding, and radar and lidar backscatter for aerosol-cloud profiling simultaneously. Because raw satellite signals integrate many sources of geophysical information, we demonstrate user-defined thresholds and a simple statistical process to facilitate evaluations, including the infrared-microwave-based cloud types and lidar/radar-based profile classifications.

Planetary Boundary Layer↗
NASA NTRS2018

Results from One Year of Ka-Band Beacon Measurements at Svalbard

Since April 1, 2016, a Ka-band (20.198 GHz) propagation terminal has been installed and operating at the Svalsat facility in Longyearbyen, Norway. This campaign is a joint effort between the European Space Agency (ESA), Kongsberg Satellite Services (KSAT), the French Aerospace Laboratory (ONERA), the Centre National d'Etudes Spatiales (CNES), and NASA Glenn Research Center (GRC) to characterize atmospheric attenuation, scintillation, and depolarization in the Ka-band in high latitude regions at low elevation angles. The propagation terminal observes the Thor 7 20.198 GHz RHCP beacon at nominally 2.6 deg elevation angle. Simultaneous 10 Hz and 1 Hz sampling is performed and a total dynamic range of 35 dB is achieved. One year of propagation data has been collected and the preliminary results are presented in this paper. From the first year of measurements, it is observed that at these low elevation angles, strong scintillation/multi-path conditions, as well as significant depolarization events can occur which may impose difficulties in meeting mission link acquisition requirements at 5 deg elevation angle, such as those desired by the Joint Polar Satellite System (JPSS) mission. The design of the dual-polarized terminal with integrated digital radiometer, as well as the data processing techniques are described, along with the first year results and preliminary conclusions.

Nessel, James↗
NASA NTRS2021

Testing Short-term Variability and Sampling of Primary Volatiles in Comet 46P/Wirtanen

The exceptionally favorable close approach of Jupiter-family comet 46P/Wirtanen in 2018 December enabled characterization of its primary volatile composition with exceptionally high spatial resolution and sensitivities using the iSHELL spectrograph at the NASA Infrared Telescope Facility on Maunakea, HI. We sampled emissions from H2O, HCN, C2H2, NH3,C2H6, and CH3OH on UT 2018 December 21 using two instrumental settings that spanned the 2.9–3.6μm spectral region. We also obtained a sensitive 3σupper limit for H2CO and for the rarely studied molecule HC3N. We report rotational temperatures, production rates, and mixing ratios(relative to H2O as well as to C2H6). We place our results in context by comparing them with other comets observed at near-IR wavelengths. We also compare our results with those obtained using the NIRSPEC-2 spectrograph on Keck II on UT December 17 and 18 and with results obtained from iSHELL on other dates during the same apparition. Within1–2σ uncertainty, production rates obtained for all molecules in this work were consistent with those obtained using NIRSPEC-2 except H2O, indicating low-level variability on a timescale of days. Mixing ratios with respect to H2O in 46P/Wirtanen were consistent with corresponding values from NIRSPEC-2 within the uncertainty with the exception of CH3OH, which yielded a higher ratio on December 21. Our measurements afforded a high temporal resolution that spanned∼2/3 of the rotational period of 46P/Wirtanen, enabling us to test short-term variability in the production rates of H2O and HCN due to rotational effects. Both H2O and HCN production rates showed similar temporal variability, resulting in nearly constant HCN/H2O

Younas Khan↗
DOE OSTI2020

Distribution Development for the RDX Regional Model at Los Alamos National Laboratory - 20385

Representing uncertainty in model inputs often means finding a balance between uncertainty and physical reality. Developing wide distributions may seem conservative in principle, but this approach may lead to unrealistic model results. Characterizing the current state of knowledge of stochastic inputs presents many challenges, especially if the data available are limited or have limited relevance to the site. Relationships among these inputs may also be important to represent but are typically complex or difficult to define. Often special adjustments must be made to account for reduced credibility in particular data. If parameters are strongly related to one another, a correlation structure may be developed for input to the model. Other techniques such as regression models may be used to incorporate relationships between the information available and the desired parameters. The process of developing distributions must consider details of the model in terms of what the distribution is meant to represent. This paper uses the example of a probabilistic fate and transport model for hexahydro-1,3,5-trinitro-1,3,5-triazine (RDX) in the regional aquifer at Los Alamos National Laboratory (LANL). For many parameters, a single draw is applied to all space and time over which the model is run, for a single iteration. This simplification is often made for many reasons, and can often be beneficial, but also adds additional complexity in the distribution development process. Defining the distributional goals as they relate to the modeling process is an important step, which should take place prior to evaluation of the data. Usually, the distributions developed are meant to characterize the average value of the parameter over the spatial and temporal domain of the model. Distribution development requires consideration of many sources of information on the parameter where available, ideally from multiple references. Examples of different sources include data from different references but also from different conditions, measurement methods, or experimental types. Depending on these conditions and the reliability or relevance of particular references, different sources of data may each contribute valuable information but have varying relevance to the site. In these cases, weighting data unequally is a useful way to incorporate this information. As an example, aqueous dispersivity data are available for a variety of rock types. Only a few values are available for the desired rock type, and this is not enough to develop a distribution. Therefore, dispersivity values from other rock types are included in distribution development but are down-weighted such that the best data have the most influence on the distribution developed. In another case, K{sub d} distributions in the model are meant to represent a known composition of multiple soil types. Data from these materials are weighted accordingly to develop a distribution for the weighted average K{sub d} across soil types. Other cases include varying reliability of different sources, and weighting data according to the confidence in these sources. In some cases, input parameters are correlated with one another. An example is advective porosity, which is positively correlated with total porosity and must be less than total porosity. Paired data with both parameters must exist to discern the relationship between the two parameters and if it is necessary to build a correlation structure into the model. In general, correlated parameters may be represented in the model by a multivariate distribution, or perhaps more desirably, capturing the correlation within the developed distributions which may be treated as independent from one another. In the example of porosity, this can be done by transforming advective porosity into a proportion of total porosity which may be drawn independently from the distribution of total porosity. This paper explores how complex data and correlations can be incorporated to meet the distributional goals of the model, using the RDX regional model as a detailed example. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Development of a Research Reactor Protocol for Neutron Multiplication Measurements

Establishing a protocol for measurements on research reactors is the next step in advanced subcritical neutron multiplication inference measurements. Such measurements can help identify deficiencies and quantify uncertainties in nuclear data and validate predictive Monte Carlo radiation transport simulation capabilities related to subcritical neutron multiplication inference techniques. This work expands on previous benchmark-quality efforts performed at the National Criticality Experiments Research Center (NCERC) located in Nevada, including subcritical experiments with a 4.5-kg {alpha}-phase plutonium sphere surrounded by copper, tungsten and nickel. Evaluations of the nickel and tungsten measurements have both been accepted into the International Criticality Safety Benchmark Evaluation Project (ICSBEP) Handbook. The nickel benchmark was the first ICSBEP-accepted evaluation of measurements using the Feynman Variance-to-Mean method based on the Hage-Cifarelli formulism, and was the culmination of many years of subcritical experiment research. To help establish a protocol for research reactor-based subcritical measurements, a series of Critical and Subcritical {Phi}-Power Experiments at Rensselaer (CaSPER) have been designed. This neutron multiplication measurement series will be executed at the Rensselaer Polytechnic Institute Walthousen Reactor Critical Facility (RPI-RCF) in upstate New York. The RPI reactor facility can provide benchmark-quality integral experimental configurations where different reactivity states can be achieved by varying the control rod height/water height in the reactor. The diversity of achievable configurations are also unique in contrast to previous subcritical benchmark measurements in that they are spatially complex, involve different materials (fuel, moderator), and are characterized by system-specific neutron cross section sensitivities (various energy ranges and neutron reaction contributions). It is worth noting that previous proof-of-concept subcritical measurements have been performed on thermal systems at NCERC, at a variety of reactivity states by separation distance, yet it was not possible to know the reactivity of various configurations accurately for benchmarking (there are no control rod worth curves as there are no control rods). (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2018

Using a spatially-distributed hydrologic biogeochemistry model with a nitrogen transport module to study the spatial variation of carbon processes in a Critical Zone Observatory

Terrestrial carbon processes are affected by soil moisture, soil temperature, nitrogen availability and solar radiation, among other factors. Most of the current ecosystem biogeochemistry models represent one point in space, and have limited characterization of hydrologic processes. Therefore these models can neither resolve the topographically driven spatial variability of water, energy, and nutrient, nor their effects on carbon processes. A spatially-distributed land surface hydrologic biogeochemistry model, Flux-PIHM-BGC, is developed by coupling the Biome-BGC model with a physically-based land surface hydrologic model, Flux-PIHM. In the coupled system, each Flux-PIHM model grid couples a 1-D Biome-BGC model. In addition, a topographic solar radiation module and an advection-driven nitrogen transport module are added to represent the impact of topography on nutrient transport and solar energy distribution. Because Flux-PIHM is able to simulate lateral groundwater flow and represent the land surface heterogeneities caused by topography, Flux-PIHM-BGC is capable of simulating the complex interaction among water, energy, nutrient, and carbon in time and space. The Flux-PIHM-BGC model is tested at the Susquehanna/Shale Hills Critical Zone Observatory. Model results show that distributions of carbon and nitrogen stocks and fluxes are strongly affected by topography and landscape position, and tree growth is nitrogen limited. The predicted aboveground and soil carbon distributions generally agree with the macro patterns observed. Although the model underestimates the spatial variation, the predicted watershed average values are close to the observations. Lastly, the coupled Flux-PIHM-BGC model provides an important tool to study spatial variations in terrestrial carbon and nitrogen processes and their interactions with environmental factors, and to predict the spatial structure of the responses of ecosystems to climate change.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1994

A scanning defect mapping system for semiconductor characterization

We have developed an optical scanning system that generates maps of the spatial distributions of defects in single and polycrystalline silicon wafers. This instrument, called Scanning Defect Mapping System, utilizes differences in the scattering characteristics of dislocation etch pits and grain boundaries from a defect-etched sample to identify and count them. This system simultaneously operates in the dislocation mode and the grain boundary (GB) mode. In the 'dislocation mode,' the optical scattering from the etch pits is used to statistically count dislocations, while ignoring the GB's. Likewise, in the 'grain boundary mode' the system only recognizes the local scattering from the GB's to generate grain boundary distributions. The information generated by this instrument is valuable for material quality control, identifying mechanisms of defect generation and the nature of thermal stresses during the crystal growth, and the solar cell process design.

Sopori, Bushnan L.↗
NASA NTRS2026

Characterizing the subglacial environment of lower Thwaites Glacier using radar modeling

Understanding the spatial heterogeneity beneath Thwaites Glacier, West Antarctica, is vital to projecting its impact on future sea levels. Radar-echo sounding (RES) is commonly used to infer subglacial conditions, but these data can be challenging to interpret. We assess basal heterogeneity across Thwaites Glacier by comparing RES returns to a radar backscattering simulator for over 400 km of RES data. The modeled variations in bed returned power exhibited a strong correlation with actual RES data in 40% of our simulated flight segments, which we consider evidence for a relatively homogeneous glacier bed. Other sites (40%) demonstrated improved fit quality when hydrology or substrate transitions were introduced in the bed material model. The remaining simulated segments (20%) were diagnosed as having more complex basal heterogeneity. The spatial distribution of complex heterogeneity appears to coincide with asymmetric patterns in the RES specularity content, which has been interpreted in previous studies as a signature for channelized hydrology. Conversely, the homogeneous substrate locations coincide with areas of fast-moving ice in western Thwaites. Our simulation method can isolate power variations induced by material heterogeneity vs topography, which is an important limitation of existing RES analysis methods.

Antarctic glaciology↗
NASA NTRS2000

Fractal Characterization of Multitemporal Remote Sensing Data

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the capture, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISs. Scale is fundamental to the characterization of geo-spatial data as represented in GISs, but we have relatively little insight on how to measure the effects of scale in representing data that are acquired in different formats and exist in varying spatial, temporal and radiometric configurations. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective. "Scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which lead to substantial confusion in the input, manipulation, analysis, and output operations. Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale' across all disciplines that use GISs.

Quattrochi, Dale A.↗
NASA NTRS2002

Tracking Avian Reservoirs of Arboviruses using Remote Sensing and Radiotelemetry

Encephalitis is caused by a virus that is transmitted by mosquitoes between mammalian hosts. The virus is closely related to the West Nile virus (WNV), which started in New York in 1999, and has since spread to 25 states. Like encephalitis, WNV is vectored by mosquitoes, and the primary hosts are birds; humans are accidental, or'dead-end' hosts. Very little is understood about the behavior of these bird populations, and how they intersect - both in time and in space - with mosquito populations. Exploring these relationships is the first step in developing models for encephalitis and WNV transmission risk. This project combines remotely sensed data with radiotelemetry to create a spatiotemporal map of encephalitis viral activity in bird and mosquito populations in the Sacramento Valley of California. Specifically, remote sensing (RS) and geographic information system (GIS) technologies were used to characterize habitats utilized by both avian viral reservoirs and the mosquitoes that vector encephalitis. Radiotelemetry and serosurveys (blood) were then used to spatially and temporally track the patterns of infection. The project uses Landsat ETM+ multitemporal satellite data to characterize habitats utilized by both birds and the mosquito vectors. Mist nets were used to sample members of individual flocks of blackbirds and cowbirds over a period of several months; these birds were then bled to assess their viral status, banded, and fitted with transmitters. Radiotelemetry was used to spatially and temporally track the distribution of banded birds and their associated flocks. The movement of these indicator flocks were compared with the location of remotely sensed (adult and larval) mosquito habitats to determine the intersection of bird's and vectors; this is key in understanding where and when transmission occurs from bird to bird, as well as from bird to mammal, via mosquito. The relationships found during the project are being used to generate a model of encephalitis transmission risk in California.

Beck, L.↗
NASA NTRS1998

Fractal Characterization of Multitemporal Scaled Remote Sensing Data

Scale is an "innate" concept in geographic information systems. It is recognized as something that is intrinsic to the ingestion, storage, manipulation, analysis, modeling, and output of space and time data within a GIS purview, yet the relative meaning and ramifications of scaling spatial and temporal data from this perspective remain enigmatic. As GISs become more sophisticated as a product of more robust software and more powerful computer systems, there is an urgent need to examine the issue of scale, and its relationship to the whole body of spatiotemporal data, as imparted in GISS. Scale is fundamental to the characterization of geo-spatial data as represented in GISS, but we have relatively little insight on the effects of, or how to measure the effects of, scale in representing multiscaled data; i.e., data that are acquired in different formats (e.g., map, digital) and exist in varying spatial, temporal, and in the case of remote sensing data, radiometric, configurations. This is particularly true in the emerging era of Integrated GISs (IGIS), wherein spatial data in a variety of formats (e.g., raster, vector) are combined with multiscaled remote sensing data, capable of performing highly sophisticated space-time data analyses and modeling. Moreover, the complexities associated with the integration of multiscaled data sets in a multitude of formats are exacerbated by the confusion of what the term "scale" is from a multidisciplinary perspective; i.e., "scale" takes on significantly different meanings depending upon one's disciplinary background and spatial perspective which can lead to substantive confusion in the input, manipulation, analyses, and output of IGISs (Quattrochi, 1993). Hence, we must begin to look at the universality of scale and begin to develop the theory, methods, and techniques necessary to advance knowledge on the "Science of Scale" across a wide number of spatial disciplines that use GISs.

Quattrochi, Dale A.↗