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NASA NTRSDate not supplied

Unlocking the Mysteries of the Moon’s Shadowed Regions

The Moon poles host large quantities of water-ice deposits in the permanently shadowed regions (PSRs), which are vital for enabling sustainable human space exploration, making these regions high-priority targets for upcoming Artemis missions [1]. Unfortunately, today, the best available orbital lunar imagery [2, 3] lacks the meter-scale resolution and signal needed to understand the geomorphology and trafficability of PSRs, complicating the planning and execution of future missions seeking to explore PSRs. We have developed an image enhancement tool called HORUS (Hyper-effective nOise Removal Unet Software) [4, 5], designed to enhance LRO Narrow-Angle Camera (NAC) optical low-light imagery of permanently shadowed regions by effectively removing the CCD-related, photon, and other residual noises that corrupt the images. The tool is composed of two deep learning neural networks trained on environmental metadata and real and synthetic imagery, the latter generated by a physical noise model (LROC). We demonstrated that HORUS effectively produces low-noise, high-resolution images (~1.5m/px), achieving a 5 to 10x improvement over existing long-exposure images of PSRs. HORUS allows scientists and engineers to identify geomorphic features (e.g., craters and boulders) in shadowed regions as small as 3 meters across as well as to peek inside of small shadowed regions, for the first time. The tool was deployed and thoroughly validated for NASA's VIPER mission [6], where it was applied to 20 candidate target regions across the lunar South Pole. Additionally, we conducted different approaches to validate the resulting HORUS-processed images. With HORUS denoised images, VIPER scientists can increase their confidence on what surface features (previously unseen) exist in the shadowed regions, helping them plan rover traverses more safely and efficiently (e.g., Fig. 1) In this manuscript, we will describe how VIPER scientists are utilizing HORUS denoised images to extract new information from the terrain and increase their confidence in what surface features exist in the shadowed regions. In combination with other high-resolution images and digital elevation maps, HORUS images are helping the team analyze potential lading and science sites, as well as planning traverses more safely and efficiently (e.g., Fig. 1). Additionally, we will describe how HORUS tool unlocks a broad range of scientific and exploration applications to other Artemis and CPLS missions to the lunar poles, including (but not limited to) geomorphic analysis, change detection, surface hazard detection, and terrain relative navigation.

artificial intelligence↗

NASA NTRS2022

File Specification for MERRA-2 Climate Statistics Products

The Modern Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) contains a wealth of information that can be used for weather and climate studies. By combining the assimilation of observations with a frozen version of the Goddard Earth Observing System (GEOS), a global analysis is produced at an hourly temporal resolution spanning from January 1980 through present (Gelaro et al., 2017). It can be difficult to parse through a multidecadal dataset such as MERRA-2 to evaluate the interannual variability of weather that occurs on a daily timescale, let alone determine the occurrence of an extreme weather event. Furthermore, it was recognized that standard metrics were needed to evaluate climate change among climate models and international research efforts. As a result of these concerns, the Expert Team on Climate Change Detection and Indices (ETCCDI) developed a set of indices that represent the frequency and intensity of extreme weather events using a daily time series of 2-m air temperature (T2m) and precipitation (Alexander et al., 2016). These indices were used as a basis to comprise a list of fields that represent daily extreme temperature and precipitation events, heatwaves, multi-day precipitation, as well monthly percentile statistics from the MERRA-2 dataset. Also included in this data product is a climatological long term mean and standard deviation representing the interannual variability on a monthly timescale.

MERRA-2↗

NASA NTRSDate not supplied

Development of Head-Trunk Coordination Measures for Monitoring Postflight Sensorimotor Readaptation Strategies

During exploration missions, individual health assessments will be required to account for variability in neurosensory adaptation and task readiness for the initial extravehicular activities (EVAs). Previous research has identified postflight vestibular alterations and disruptions in head-trunk coordination after both short and long duration spaceflight missions. Astronauts were found to minimize head angular displacement and utilize a consistent forward head tilt theorized as a compensatory approach to stabilize the cephalic system and reduce motion sickness during readaptation to Earth’s gravity. Further, anecdotal self-reports from Shuttle crewmembers stated that pitch and side-to-side head movements immediately post-landing typically resulted in perceived angular self-motion. Notable disruptions also occur upon arrival in orbit, with astronauts choosing waist rotation rather than head movements during dynamic tasks. It is thought that the underlying sensorimotor disruptions may contribute to motion sickness in space and upon landing, postflight gait dysfunction, and inaccurate spatial orientation when performing daily tasks. To better characterize microgravity-induced sensorimotor adaptations, it is important to develop measures and monitoring tools that have high sensitivity in detecting changes in head-trunk coordination.

H M Weiss↗

NASA NTRS2023

Capitol Reef Ecological Conservation: Mapping Vegetation Functional Groups to Inform Invasive Vegetation Management, Ecological Conservation and Restoration in Capitol Reef National Park

Invasive exotic plant (IEP) species have been found within the park boundaries of Capitol Reef National Park (CARE) in Utah. Currently, remotely sensed datasets such as the Rangeland Analysis Platform (RAP) from the United States Department of Agriculture (USDA) have been used to investigate IEP species within the park, but validation of the national RAP program is necessary for informing decisions at a local scale. CARE seeks a remote monitoring solution that can precisely target managerial efforts within the park’s challenging terrain and hard-to-reach locations. To fulfill this objective, we harnessed Landsat 8 Operational Land Imager (OLI) imagery and leveraged Random Forest (RF) modeling to generate classification maps characterizing vegetation functional groups for 2013 and 2022 within the park. Subsequently, the Land Change Modeler (LCM) in Idrisi TerrSet facilitated the production of a predicted classification map for 2033. The team also devised an annual grass probability map to accentuate areas impacted by exotic grasses. A comparative assessment between the RF classification map and the RAP map for 2022 revealed an overall agreement of 47.41%, with disparities primarily arising from differences in bare soil and shrub areas. Significantly, the 2022 RF-generated classification map showcased an impressive overall accuracy of 92.17%. In short, the probability map, the land cover change detection spanning 2013 to 2022, and the forecasting of observed trends into the future aids in the evaluation of invasive plant impacts and facilitation of CARE’s preparedness for potential ecological disturbances. Notably, in comparison to the RAP, the RF classification method generates functional group maps that are more representative of the study area.

Vanchy Li↗

NASA NTRS2024

The Active Volcanoes of Kamchatka as Suitable Terrestrial Analogs Within the AVENGERS Initiative: An Opportunity for In-Situ Operational Tests for Future Landing Venus Missions

The next decade will see the return to Venus thanks to a number of missions which have been recently selected and proposed for launch. The Roscosmos Venera-D mission, along with the NASA DAVINCI, NASA VERITAS, ESA EnVision, the ISRO Shukrayaan-1, and the CNSA VOICE missions will open a new era for the exploration of the Earth’s hellish twin planet. The next missions to Venus should be able to shed new light on the science questions such as: a) whether the volcanic activity on this planet is locally constrained, or volcanism acts on a global scale, b) the rate of the present-day volcanic activity, and c) the style of volcanism on Venus, whether it is predominantly effusive, or the occurrence of local episodes of pyroclastic volcanism is also possible. In preparation for the future missions to Venus, the Analogs for VENus’ Geologically Recent Surfaces (AVENGERS) initiative will select and analyze a number of active terrestrial volcanoes as suitable analogs for the identification and analysis of active volcanism on Venus. Among the future missions to Venus, the Roscosmos Venera-D is the only one to be equipped with a lander which will analyze the elemental and mineralogical composition of the surface. As the young topographic rises (areas characterized by recent volcano-tectonic activity) on Venus are being proposed as one of the possible terrain types for the Venera-D landing, it is crucial to look for volcanic areas on Earth where to perform operational tests such as surface drilling and in-situ elemental composition analysis. To this regard, we propose here the analysis of the active volcanoes of the Kamchatka Peninsula in Russia as a very suitable analog for the Venera-D mission, as well as for the analysis of surface change detection due to ongoing eruptions. The Kamchatka Peninsula is located on the eastern margin of the Eurasia plate, in proximity of the Kuril-Kamchatka subduction zone. The volcanoes of the Kamchatka Peninsula are among the most active volcanoes of the world, making them a suitable terrestrial analog in the search for active volcanism on Venus. Moreover, the volcanoes of Kamchatka are characterized by pyroclastic activity. Since the previous Soviet Venera and Vega missions landed over areas which elemental composition was most likely consistent with that of tholeiitic basalts, performing operational tests over areas characterized by pyroclastic activity also offers the unique opportunity to provide us the tools to potentially interpret the diverse output given by landing over portions of the surface of Venus possibly characterized by explosive volcanic products. Finally, the frequent eruptions characterizing the volcanoes of the Kamchatka Peninsula make them also a suitable terrestrial analog for the possible detection of ongoing eruptions on Venus by future missions, which can be achieved by comparing two (or more) radar images of the same volcano (and its surroundings) in two (or more) different moments of time.

Planetary Geology↗

NASA NTRSDate not supplied

Assessment of Cloud Fraction Derived from a New Geostationary Satellite Cloud Retrieval Algorithm for CERES and Progress Towards Cross-platform Continuity

For over two decades The Clouds and the Earth’s Radiant Energy System (CERES) project has produced long-term records of top-of-atmosphere (TOA) and surface irradiances for detecting changes in the Earth’s radiation budget and advancing understanding of how clouds contribute to those changes. Accurate characterization of the spatial and temporal distributions of clouds are a critical component for producing CERES datasets. The CERES Cloud Working Group (CWG) derives cloud properties from both geostationary (GEO) and low-Earth orbit (LEO) satellite sensors in order to provide complete global coverage at hourly temporal resolution. However, the use of multiple sensors to provide this spatiotemporal coverage throughout a long-term record presents some challenges, because the various sensors generally have different spectral band characteristics (e.g., spectral band width and response) and spatial resolution. These differences can result in spatial artifacts at the coverage boundary between two sensors or temporal artifacts when one sensor replaces another in the record. For the upcoming Edition 5 release of CERES products, the CWG is developing cloud retrieval algorithms which utilize only spectral bands common to most modern passive satellite radiometers and account for differences in spectral width and response. The goal with this approach is to provide global cloud properties for CERES with greater cross-platform consistency than the previous Edition 4 products and thus mitigate artifacts which are evident at the interface of two sensors. This study focuses on retrieval of total cloud fraction from various GEO sensors, and we use Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) observations to assess the accuracy of total cloud fraction derived from the various sensors. The Edition 5 cloud mask algorithm depends on estimates of cloud-free TOA spectral radiances to differentiate clear and cloudy conditions, and CALIOP is used to assess the accuracy of those estimates when cloud-free conditions are indeed observed.

CALIOP↗

NASA NTRS1990

Millimeter-wave ozone measurements for the network for the detection of stratospheric change

The primary research objective is to initiate long-term monitoring of stratospheric ozone with a ground-based millimeter-wave spectrometer, the first of several such instruments projected to be part of the Network for the Detection of Stratospheric Change. The ultimate goal of this monitoring is twofold. First, to detect any secular trend in stratospheric ozone abundance, whether of natural or anthropogenic origin and, second, to provide ground-truth validation for existing and future satellite measurements of ozone. With this goal in mind, a more immediate objective is to validate the millimeter-wave measurements by tests of the instrument, internal consistency tests on the data, and most importantly, by intercomparison with all other available ozone measurements. The validation process is expected to lead to refinements in the instrument and its operating procedures and in the data analysis. The final objective is to perform short-term scientific studies with the data, including studies of the ozone diurnal and seasonal variations, and comparison of ozone variations with changes in other geophysical parameters, notably temperature and water vapor. Routine observations are now ongoing; these will allow continuing intercomparisons with the Stratospheric Aerosol and Gas Experiment (SAGE II) and one of the lidars, which is permanently on site. The experience gained during the Stratospheric Ozone Intercomparison (STOIC) caused us to refine our calibration procedures and identify the need for internal shielding of the millimeter receiver from radio frequency interference. Installation of this shielding is planned for the near future and should allow improvements in the instrument calibration and a higher signal-to-noise ratio, both of which will result in improved measurement precision.

Connor, Brian J.↗

NASA NTRS2022

Detecting the Greatest Changes in Global Satellite-Based Precipitation Observations

In recent years, the analysis of abrupt and non-abrupt changes in precipitation has received much attention due to the importance of climate change-related issues (e.g., extreme climate events). In this study, we used a novel segmentation algorithm, DBEST (Detecting Breakpoints and Estimating Segments in Trend), to analyze the greatest changes in precipitation using a monthly pixel-based satellite precipitation dataset (TRMM 3B43) at three different scales: (i) global, (ii) continental, and (iii) climate zone, during the 1998–2019 period. We found significant breakpoints, 14.1%, both in the form of abrupt and non-abrupt changes, in the global scale precipitation at the 0.05 significance level. Most of the abrupt changes were observed near the Equator in the Pacific Ocean and Asian continent, relative to the rest of the globe. Most detected breakpoints occurred during the 1998–1999 and 2009–2011 periods on the global scale. The average precipitation change for the detected breakpoint was ±100 mm, with some regions reaching ±3000 mm. For instance, most portions of northern Africa and Asia experienced major changes of approximately +100 mm. In contrast, most of the South Pacific and South Atlantic Ocean experienced changes of −100 mm during the studied period. Our findings indicated that the larger areas of Africa (23.9%), Asia (22.9%), and Australia (15.4%) experienced significant precipitation breakpoints compared to North America (11.6%), South America (9.3%), Europe (8.3%), and Oceania (9.6%). Furthermore, we found that the majority of detected significant breakpoints occurred in the arid (31.6%) and polar (24.1%) climate zones, while the least significant breakpoints were found for snow-covered (11.5%), equatorial (7.5%), and warm temperate (7.7%) climate zones. Positive breakpoints’ temporal coverage in the arid (54.0%) and equatorial (51.9%) climates were more than those in other climates zones. Here, the findings indicated that large areas of Africa and Asia experienced significant changes in precipitation (−250 to +250 mm). Compared to the average state (trend during a specific period), the greatest changes in precipitation were more abrupt and unpredictable, which might impose a severe threat to the ecology, environment, and natural resources.

Breakpoint↗

NASA NTRS1998

OPAL: Network for the Detection of Stratospheric Change Ozone Profiler Assessment at Lauder, New Zealand. II. Intercomparison of Revised Results

Following a blind intercomparison of ozone profiling instruments in the Network for the Detection of Stratospheric Change at Lauder, New Zealand, revisions to the analyses were made resulting in a new dataset.

OPAL↗

NASA NTRS2006

Long-term Evolution of Upper Stratospheric Ozone at Selected Stations of the Network for the Detection of Stratospheric Change (NDSC)

The long-term evolution of upper stratospheric ozone has been recorded by lidars and microwave radiometers within the ground-based Network for the Detection of Stratospheric Change (NDSC), and by the space-borne Solar Backscatter Ultra-Violet instruments (SBUV), Stratospheric Aerosol and Gas Experiment (SAGE), and Halogen Occultation Experiment (HALOE). Climatological mean differences between these instruments are typically smaller than 5% between 25 and 50 km. Ozone anomaly time series from all instruments, averaged from 35 to 45 km altitude, track each other very well and typically agree within 3 to 5%. SBUV seems to have a slight positive drift against the other instruments. The corresponding 1979 to 1999 period from a transient simulation by the fully coupled MAECHAM4-CHEM chemistry climate model reproduces many features of the observed anomalies. However, in the upper stratosphere the model shows too low ozone values and too negative ozone trends, probably due to an underestimation of methane and a consequent overestimation of ClO. The combination of all observational data sets provides a very consistent picture, with a long-term stability of 2% or better. Upper stratospheric ozone shows three main features: (1) a decline by 10 to 15% since 1980, due to chemical destruction by chlorine; (2) two to three year fluctuations by 5 to 10%, due to the Quasi-Biennial Oscillation (QBO); (3) an 11-year oscillation by about 5%, due to the 11-year solar cycle. The 1979 to 1997 ozone trends are larger at the southern mid-latitude station Lauder (45 S), reaching 8%/decade, compared to only about 6%/decade at Table Mountain (35 N), Haute Provence/Bordeaux (approximately equal to 45 N), and Hohenpeissenberg/Bern(approximately equal to 47 N). At Lauder, Hawaii (20 N), Table Mountain, and Haute Provence, ozone residuals after subtraction of QBO- and solar cycle effects have levelled off in recent years, or are even increasing. Assuming a turning point in January 1997, the change of trend is largest at southern mid-latitude Lauder, +11%/decade, compared to +7%/decade at northern mid-latitudes. This points to a beginning recovery of upper stratospheric ozone. However, chlorine levels are still very high and ozone will remain vulnerable. At this point the most northerly mid-latitude station, Hohenpeissenberg/Bern differs from the other stations, and shows much less clear evidence for a beginning recovery, with a change of trend in 1997 by only +3%/decade. In fact, record low upper stratospheric ozone values were observed at Hohenpeissenberg/Bern, and to a lesser degree at Table Mountain and Haute Provence, in the winters 2003/2004 and 2004/2005.

Steinbrecht, W.↗

NASA NTRS2020

Amazonia Disasters: Assessing Methods for Gold Mining-related Deforestation Detection in Amazonia Using NASA Earth Observations

Artisanal and small-scale gold mining (ASGM) is responsible for a large fraction of deforestation and disturbance in Amazonia. These activities cause severe impacts on the rainforest ecosystem and socioeconomic state of the region. NASA DEVELOP partnered with the Asociación para la Conservación de la Cuenca Amazónica (ACCA), NASA SERVIR Science Coordination Office, and the Spatial Informatics Group to enhance ASGM-related deforestation detection methods. ACCA currently uses the Omnibus Q-test Change Point Detection Algorithm to identify changes in Synthetic Aperture Radar (SAR) monthly-aggregated temporal data from the Sentinel-1 satellite. The team determined the algorithm's accuracy by comparing a stratified random sample of change points against data from January 2019 to June 2020 identified using PlanetScope and Landsat 8 Operational Land Imager (OLI) Earth observations through Collect Earth Online. Our results indicated a users' accuracy of 55% for temporal change detection and producer's and user's accuracies of 99% and 97%, respectively, for detecting when change did not occur. Of the labeled change points, only 19% were due to mining activity. This research can help our partners have a more accurate understanding of where illegal gold mining may be taking place and inform decisions to remediate this activity.

DEVELOP Project Summary↗

NASA NTRS2020

Amazonia Disasters: Assessing Methods for Gold Mining-Related Deforestation Detection in Amazonia Using NASA Earth Observations

DEVELOP Tech Paper↗

NASA NTRS1990

Retrieval methods for ground-based millimeter-wave measurements for the network for the detection of stratospheric change

The fundamental objective is to determine the information available in ground-based millimeter-wave measurements of stratospheric constituent profiles, to identify the optimum method of retrieving this profile information, and to characterize the errors in the final result. A secondary objective is to produce retrieval software for operational use with Network for the Detection of Stratospheric Change (NDSC) measurements of O3, H2O, ClO, and perhaps N2O. Tests were performed on existing ozone retrieval programs in support of ongoing NDSC field measurements. The results show that if random spectral errors and retrieval bias errors are considered, accuracy of the retrieved profile is about 5 percent from 20-50 km, and about 10 percent from 50-60 km.

Connor, Brian J.↗

NASA NTRS2018

The Network for the Detection of Atmospheric Composition Change (NDACC): History, Status and Perspectives

The Network for the Detection of Atmospheric Composition Change (NDACC) is an international global network of more than 90 stations making high-quality measurements of atmospheric composition that began official operations in 1991 after 5 years of planning. Apart from sonde measurements, all measurements in the network are performed by ground-based remote-sensing techniques. Originally named the Network for the Detection of Stratospheric Change (NDSC), the name of the network was changed to NDACC in 2005 to better reflect the expanded scope of its measurements. The primary goal of NDACC is to establish long-term databases for detecting changes and trends in the chemical and physical state of the atmosphere (mesosphere, stratosphere, and troposphere) and to assess the coupling of such changes with climate and air quality. NDACC's origins, station locations, organizational structure, and data archiving are described. NDACC is structured around categories of ground-based observational techniques (sonde, lidar, microwave radiometers, Fourier-transform infrared, UV-visible DOAS (differential optical absorption spectroscopy)-type, and Dobson-Brewer spectrometers, as well as spectral UV radiometers), timely cross-cutting themes (ozone, water vapour, measurement strategies, cross-network data integration), satellite measurement systems, and theory and analyses. Participation in NDACC requires compliance with strict measurement and data protocols to ensure that the network data are of high and consistent quality. To widen its scope, NDACC has established formal collaborative agreements with eight other cooperating networks and Global Atmosphere Watch (GAW). A brief history is provided, major accomplishments of NDACC during its first 25 years of operation are reviewed, and a forward-looking perspective is presented.

lidar↗

NASA NTRS2009

Satellite Observations for Detecting and Tracking Changes in Atmospheric Composition

The satellite observations provide constraints on detailed atmospheric modeling, including emissions inventories, indications of transport, harmonized data over vast areas suitable for trends analysis, and a link between spatial scales ranging from local to global, and temporal scales from diurnal to interannual. 1 The National Oceanic and Atmospheric Administration's (NOAA) long-term commitments help provide these observations in cooperation with international meteorological organizations. NASA s long-term commitments will advance scientifically important observations as part of its Earth Science Program, and will assist the transition of the science measurements to applied analyses through the Applied Science Program. Both NASA and NOAA have begun to provide near realtime data and tools to visualize and analyze satellite data,2 while maintaining data quality, validation, and standards. Consequently, decision-makers can expect satellite data services to support air quality decision making now and in the future. The international scientific community's Integrated Global Atmosphere Chemistry Observation System Report3 outlined a plan for ground-based, airborne and satellite measurements and models to integrate the observations into a four-dimensional representation of the atmosphere (space and time) to support assessment and policy information needs. This plan is being carried out under the Global Earth Observation System of Systems (GEOSS). Demonstrations of such an integrated capability4 provide new understanding of the changing atmosphere and link policy decisions to benefits for society. In this article, we highlight the use of satellite data to constrain biomass burning emissions, to assess oxides of nitrogen (NO(x)) emission reductions, and to contribute to state implementation plans, as examples of the use of satellite observations for detecting and tracking changes in atmospheric composition.

Neil, Doreen O.↗

NASA NTRS1975

Psychophysical Models for Signal Detection with Time Varying Uncertainty

Psychophysical models for the behavior of the human operator in detection tasks which include change in detectability, correlation between observations and deferred decisions are developed. Classical Signal Detection Theory (SDT) is discussed and its emphasis on the sensory processes is contrasted to decision strategies. The analysis of decision strategies utilizes detection tasks with time varying signal strength. The classical theory is modified to include such tasks and several optimal decision strategies are explored. Two methods of classifying strategies are suggested. The first method is similar to the analysis of ROC curves, while the second is based on the relation between the criterion level (CL) and the detectability. Experiments to verify the analysis of tasks with changes of signal strength are designed. The results show that subjects are aware of changes in detectability and tend to use strategies that involve changes in the CL's.

Gai, E.↗

NASA NTRS1983

Detecting forest canopy change due to insect activity using Landsat MSS

Multitemporal Landsat multispectral scanner data were analyzed to test various computer-aided analysis techniques for detecting significant forest canopy alteration. Three data transformations - differencing, ratioing, and a vegetative index difference - were tested to determine which best delineated gypsy moth defoliation. Response surface analyses were conducted to determine optimal threshold levels for the individual transformed bands and band combinations. Results indicate that, of the three transformations investigated, a vegetative index difference (VID) transformation most accurately delineates forest canopy change. Band 5 (0.6 to 0.7 micron ratioed data did nearly as well. However, other single bands and band combinations did not improve upon the band 5 ratio and VID results.

Nelson, R. F.↗

NASA NTRS2014

Wetware, Hardware, or Software Incapacitation: Observational Methods to Determine When Autonomy Should Assume Control

Control-theoretic modeling of human operator's dynamic behavior in manual control tasks has a long, rich history. There has been significant work on techniques used to identify the pilot model of a given structure. This research attempts to go beyond pilot identification based on experimental data to develop a predictor of pilot behavior. Two methods for pre-dicting pilot stick input during changing aircraft dynamics and deducing changes in pilot behavior are presented This approach may also have the capability to detect a change in a subject due to workload, engagement, etc., or the effects of changes in vehicle dynamics on the pilot. With this ability to detect changes in piloting behavior, the possibility now exists to mediate human adverse behaviors, hardware failures, and software anomalies with autono-my that may ameliorate these undesirable effects. However, appropriate timing of when au-tonomy should assume control is dependent on criticality of actions to safety, sensitivity of methods to accurately detect these adverse changes, and effects of changes in levels of auto-mation of the system as a whole.

Trujillo, Anna C.↗