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NASA NTRS2000

Scouts: Using Numbers to Explore Mars In Situ

Mars is a planet with a complex geologic history involving fluvial, volcanic, aeolian, atmospheric, and impact processes. Many critical questions about Mars are still heatedly debated within the scientific community and we still have much to discover. The current Mars exploration philosophy involves remote observation of the planet from orbit and intensive in situ study of a few sites on the surface. Orbital data provides a global picture while in situ investigations provide detailed knowledge at a single location. Mars Scouts are proposed to provide access to multiple locations on Mars. They address the emerging program needs of exploring the diversity of the planet globally in ways that cannot be achieved from orbit. The goal of the Scout is to find a way to investigate many locations on the surface of Mars in an affordable and efficient manner. We have only visited three locations on the surface of Mars, which have very similar characteristics. Increased numbers allows more types of locations to be investigated. The hallmarks of Scouts are numbers and access. Thus the capability of a single Scout will be limited. The science return from a single Scout will be significantly less than from a large science lander or an orbiting spacecraft. Scouts rely on their numbers to collectively provide a substantial increase in our knowledge of Mars. Scouts potentially serve two purposes in the Mars exploration architecture. First, Scouts are a science exploration tool. They provide access to places on Mars we currently can't explore because program focus, surface roughness, elevation, or latitude that we know are scientifically interesting. Scouts can react to new discoveries and evolving ideas about Mars. They can be used to test theories which until proven would not warrant the investment of a large lander. Second, Scouts enable better large scale missions by providing ground truth of remote sensing data and allowing us to "know" sites in advance before sending large landers and sample return missions. This increases the probability of success for these expensive missions both from safety and science return stand-points.

Blaney, D. L.↗

DOE OSTI2012

Sassena — X-ray and neutron scattering calculated from molecular dynamics trajectories using massively parallel computers

Massively parallel computers now permit the molecular dynamics (MD) simulation of multi-million atom systems on time scales up to the microsecond. However, the subsequent analysis of the resulting simulation trajectories has now become a high performance computing problem in itself. Here, we present software for calculating X-ray and neutron scattering intensities from MD simulation data that scales well on massively parallel supercomputers. The calculation and data staging schemes used maximize the degree of parallelism and minimize the IO bandwidth requirements. The strong scaling tested on the Jaguar Petaflop Cray XT5 at Oak Ridge National Laboratory exhibits virtually linear scaling up to 7000 cores for most benchmark systems. Since both MPI and thread parallelism is supported, the software is flexible enough to cover scaling demands for different types of scattering calculations. The result is a high performance tool capable of unifying large-scale supercomputing and a wide variety of neutron/synchrotron technology.

Computer Science↗

DOE OSTI2024

Source shape estimation for neutron imaging systems using convolutional neural networks

Neutron imaging systems are important diagnostic tools for characterizing the physics of inertial confinement fusion reactions at the National Ignition Facility (NIF). In particular, neutron images give diagnostic information on the size, symmetry, and shape of the fusion hot spot and surrounding cold fuel. Images are formed via collection of neutron flux from the source using a system of aperture arrays and scintillator-based detectors. Currently, reconstruction of fusion source geometry from the collected neutron images is accomplished by solving a computationally intensive maximum likelihood estimation problem via expectation maximization. In contrast, it is often useful to have simple representations of the overall source geometry that can be computed quickly. In this work, we develop convolutional neural networks (CNNs) to reconstruct the outer contours of simple source geometries. We compare the performance of the CNN for penumbral and pinhole data and provide experimental demonstrations of our methods on both non-noisy and noisy data.

Machine learning, neutron imaging, source reconstr↗

DOE OSTI2024

ACE-ENA: Fast Liquid Water Content

These data were collected during the Aerosol and Cloud Experiments in the Eastern North Atlantic field campaign as part of ARM Aerial Facility deployment (ACE-ENA, https://www.arm.gov/research/campaigns/aaf2017ace-ena). The ARM Aerial Facility Gulfstream-1 was deployed at Lajes Air Base (IATA: TER, ICAO: LPLA), on Terceira Island in the Azores, Portugal, for the two Intensive Observation Periods from June 20 through July 22, 2017 (IOP#1) and from January 11 through February 22, 2018 (IOP#2). The G-1 aircraft performed 20+19 research flights over the ARM Eastern North Atlantic (ENA) site and Atlantic Ocean to measure atmospheric turbulence, cloud water content and drop size distributions, aerosol precursor gases, aerosol chemical composition and size distributions. The current data set presents re-processed Particle Volume Monitor PVM-100A (aka Gerber probe) data: Liquid Water Content (LWC), Particle Surface Area (PSA), and the effective droplet radius (re) averaged to 50 Hz, 10 Hz, and 1 Hz.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

ToF-SIMS Depth Profiling Of Insulating Samples, Interlaced Mode Or Non-interlaced Mode?

Dual beam depth profiling strategy has been widely adopted in ToF-SIMS depth profiling, in which two basic operation modes, interlaced mode and non-interlaced mode, are commonly used. Generally, interlaced mode is recommended for conductive or semi-conductive samples, whereas non-interlaced mode is recommended for insulating samples, where charge compensation can be an issue. Recent publications, however, show that the interlaced mode can be used effectively for glass depth profiling, despite the fact that glass is an insulator. In this study, we provide a simple guide for choosing between interlaced mode and non-interlaced mode for insulator depth profiling. Two representative cases are presented: (1) depth profiling of a leached glass sample, and (2) depth profiling of a single crystal MgO sample. In brief, the interlaced mode should be attempted first, because (1) it may provide reasonable-quality data, and (2) it is time-saving for most cases, and (3) it introduces low H/C/O background. If data quality is the top priority and measurement time is flexible, non-interlaced mode is recommended because interlaced mode may suffer from low signal intensity and poor mass resolution. A big challenge is tracking trace H/C/O in a highly insulating sample (e.g., MgO), because non-interlaced mode may introduce strong H/C/O background but interlaced mode may suffer from low signal intensity. Meanwhile, a C or Au coating is found to be very effective to improve the signal intensity. Surprisingly, the best analyzing location is not on the C or Au coating, but at the edge (outside) of the coating.

Environmental Molecular Sciences Laboratory↗

DOE OSTI2013

EPR and magnetic susceptibility investigation of iron-zinc-phosphate glass ceramics

(Fe{sub 2}O{sub 3}){sub x}⋅(P{sub 2}O{sub 5}){sub 40}⋅(ZnO){sub 60−x} glass ceramics containing different concentrations of Fe{sub 2}O{sub 3} ranging from 1 to 20 mol% were obtained by heat treatment of glass samples at 650 °C for 2 h. The structural and magnetic properties of these glass ceramics were investigated by means of electron paramagnetic resonance (EPR) and magnetic susceptibility measurements. The EPR spectra of the studied samples revealed absorptions centered at g ≈ 2.0 and 4.3. The compositional variations of the intensity and line width of these absorption lines was interpreted in terms of the variation in Fe{sup 3+} and Fe{sup 2+} ions concentration in the glass ceramics as well as the interaction between the iron ions. The magnetic susceptibility data evidenced the presence of both Fe{sup 3+} and Fe{sup 2+} ions, with their relative content depending on the Fe{sub 2}O{sub 3} concentration. Dipolar and superexchange interactions involving iron ions were revealed depending on the iron content of the sample.

36 MATERIALS SCIENCE↗

DOE OSTI2016

SU-D-207B-07: Development of a CT-Radiomics Based Early Response Prediction Model During Delivery of Chemoradiation Therapy for Pancreatic Cancer

Purpose: Pilot study developing a CT-texture based model for early assessment of treatment response during the delivery of chemoradiation therapy (CRT) for pancreatic cancer. Methods: Daily CT data acquired for 24 pancreatic head cancer patients using CT-on-rails, during the routine CT-guided CRT delivery with a radiation dose of 50.4 Gy in 28 fractions, were analyzed. The pancreas head was contoured on each daily CT. Texture analysis was performed within the pancreas head contour using a research tool (IBEX). Over 1300 texture metrics including: grey level co-occurrence, run-length, histogram, neighborhood intensity difference, and geometrical shape features were calculated for each daily CT. Metric-trend information was established by finding the best fit of either a linear, quadratic, or exponential function for each metric value verses accumulated dose. Thus all the daily CT texture information was consolidated into a best-fit trend type for a given patient and texture metric. Linear correlation was performed between the patient histological response vector (good, medium, poor) and all combinations of 23 patient subgroups (statistical jackknife) determining which metrics were most correlated to response and repeatedly reliable across most patients. Control correlations against CT scanner, reconstruction kernel, and gated/nongated CT images were also calculated. Euclidean distance measure was used to group/sort patient vectors based on the data of these trend-response metrics. Results: We found four specific trend-metrics (Gray Level Coocurence Matrix311-1InverseDiffMomentNorm, Gray Level Coocurence Matrix311-1InverseDiffNorm, Gray Level Coocurence Matrix311-1 Homogeneity2, and Intensity Direct Local StdMean) that were highly correlated with patient response and repeatedly reliable. Our four trend-metric model successfully ordered our pilot response dataset (p=0.00070). We found no significant correlation to our control parameters: gating (p=0.7717), scanner (p=0.9741), and kernel (p=0.8586). Conclusion: We have successfully created a CT-texture based early treatment response prediction model using the CTs acquired during the delivery of chemoradiation therapy for pancreatic cancer. Future testing is required to validate the model with more patient data.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2021

Pooling Data Improves Multimodel IDF Estimates over Median-Based IDF Estimates: Analysis over the Susquehanna and Florida

Traditional multimodel methods for estimating future changes in precipitation intensity, duration, and frequency (IDF) curves rely on mean or median of models’ IDF estimates. Such multimodel estimates are impaired by large estimation uncertainty, shadowing their efficacy in planning efforts. Here, assuming that each climate model is one representation of the underlying data generating process, i.e., the Earth system, we propose a novel extension of current methods through pooling model data: (i) evaluate performance of climate models in simulating the spatial and temporal variability of the observed annual maximum precipitation (AMP), (ii) bias-correct and pool historical and future AMP data of reasonably performing models, and (iii) compute IDF estimates in a nonstationary framework from pooled historical and future model data. Pooling enhances fitting of the extreme value distribution to the data and assumes that data from reasonably performing models represent samples from the “true” underlying data generating distribution. Through Monte Carlo simulations with synthetic data, we show that return periods derived from pooled data have smaller biases and lesser uncertainty than those derived from ensembles of individual model data. We apply this method to NA-CORDEX models to estimate changes in 24-h precipitation intensity–frequency (PIF) estimates over the Susquehanna watershed and Florida peninsula. Our approach identifies significant future changes at more stations compared to median-based PIF estimates. The analysis suggests that almost all stations over the Susquehanna and at least two-thirds of the stations over the Florida peninsula will observe significant increases in 24-h precipitation for 2–100-yr return periods.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2014

Karhunen-Loeve expansion analysis of uncertainties in cloud microphysical property retrievals

Here, this study proposes a methodology of quantifying uncertainties for cloud retrievals on model resolution to facilitate the comparison with model outputs. Primary component analysis is applied to reduce the dimension of random variables (up to a factor of 50) and reveal the cross correlations in the input data, making large sampling computationally feasible and uncertainty quantification accurate and reliable. Our approach has the capability of parameterizing input uncertainties and attributing the uncertainties in the retrieval output to each individual source, which allows sensitivity analysis of cloud retrieval algorithms and provides directions for improving observation instruments as well as strategies. We applied the method to characterize uncertainties in cloud ice water content (IWC) retrieved from the DOE Atmospheric Radiation Measurement (ARM) programs baseline cloud microphysical retrieval algorithm (MICROBASE). We test it with a selected ice cloud case observed on 9 March 2000 at the ARM Southern Great Plains site during its 2000 cloud intensive observing period. The test results indicate that (1) uncertainties in the output retrieved by MICROBASE are comparable amongst different retrievals; (2) The mean values obtained by our UQ method are closer to the aircraft data with less errors compared to the direct ensemble average; (3) Ice water path (IWP) generally incurred larger uncertainty in optically thin ice clouds and there was more variability in vertical in the retrieved IWC; and (4) Uncertainties in the output are mainly due to the interactions among different modes of ARM radar pro files.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

College Bound with the Office of Educational Programs

The Educational Programs Office at NASA Glenn Research Center hosts a variety of programs that takes on the hard task of getting students of all ages interested in pursuing careers in science, mathematics, and engineering. To help assist students along the way there are many programs to participate in such as: the explorers, shadowing opportunities, and paid internships. The Educational Programs Office not only creates learning opportunities for students, they also host workshops to help educators enhance their knowledge these fields. This summer I assisted Marie Borowski in the Educational Programs Office with the Tennessee State University College Bound Program. The Tennessee state University College Bound Program is an intensive two-week summer academic workshop designed to introduce minority students to the profession of engineering. NASA Glenn Research Center sent forty dedicated students on a bus to Nashville, Tennessee to experience college life as a whole. At the college the students day consisted of a math class, aeronautics, ACT/SAT preparation, writing and research, African American Culture, computer science, and study sessions. The students also went on educational field trips to the Fisk Museum, the Space and Rocket Center, and the Parthenon Museum. On the last day of the program the students competed in an oratorical contest where the students made a Powerpoint presentation on the class that they enjoyed the most. There were many processes that had to be put into action for the college bound program to run smoothly. The process started in early January with the preparation of applications. Once prepared, the applications were then sent to schools and past participants in hopes of receiving a well-qualified pool of applicants. Once the applications were received, a prescreening is done which ensures all of the information is complete. Then, they are reviewed by a panel, using a rubric to evaluate them, and the semifinalists are then selected. Interviews are held with the students and their parents had to be interviewed by a panel of judges and graded on a rubric. The scores were added up and the forty students were selected. My job this summer was getting the students ready to leave for Tennessee. My job consisted of working very closely with my mentor, Marie Borowski, compile the student data to provide it to the chaperones, TSU records, and NASA records. I learned about the vital communication between the NASA and the TSU program managers. After all the planning was done and the program had begun I had a chance to fly to Tennessee for six days to observe the students daily activities. The students had adjusted very well to the intense schedule, and seemed very enthusiastic about the activities to follow. The whole group was very attentive and enthusiastic program be longer. My goals for the summer were all met. I wanted to learn and retain all the information I possibly could on the job I was given. I was very happy with the end result.

Neal, Brittany D.↗

DOE OSTI2022

Analyzing Relationships Between Economic and Neighborhood-Related Social Determinants of Health and Intensive Care Unit Length of Stay for Critically Ill Children With Medical Complexity Presenting With Severe Sepsis

Objectives: Of the Social Determinants of Health (SDoH), we evaluated socioeconomic and neighborhood-related factors which may affect children with medical complexity (CMC) admitted to a Pediatric Intensive Care Unit (PICU) in Shelby County, Tennessee with severe sepsis and their association with PICU length of stay (LOS). We hypothesized that census tract-level socioeconomic and neighborhood factors were associated with prolonged PICU LOS in CMC admitted with severe sepsis in the underserved community. Methods: This single-center retrospective observational study included CMC living in Shelby County, Tennessee admitted to the ICU with severe sepsis over an 18-month period. Severe sepsis CMC patients were identified using an existing algorithm incorporated into the electronic medical record at a freestanding children's hospital. SDoH information was collected and analyzed using patient records and publicly available census-tract level data, with ICU length of stay as the primary outcome. Results: 83 encounters representing 73 patients were included in the analysis. The median PICU LOS was 9.04 days (IQR 3.99–20.35). The population was 53% male with a median age of 4.1 years (IQR 1.96–12.02). There were 57 Black/African American patients (68.7%) and 85.5% had public insurance. Based on census tract-level data, about half (49.4%) of the CMC severe sepsis population lived in census tracts classified as suffering from high social vulnerability. There were no statistically significant relationships between any socioeconomic and neighborhood level factors and PICU LOS. Conclusion: Pediatric CMC severe sepsis patients admitted to the PICU do not have prolonged lengths of ICU stay related to socioeconomic and neighborhood-level SDoH at our center. A larger sample with the use of individual-level screening would need to be evaluated for associations between social determinants of health and PICU outcomes of these patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2015

Development of fine-resolution analyses and expanded large-scale forcing properties. Part I: Methodology and evaluation

We produce fine-resolution, three-dimensional fields of meteorological and other variables for the U.S. Department of Energy’s Atmospheric Radiation Measurement (ARM) Southern Great Plains site. The Community Gridpoint Statistical Interpolation system is implemented in a multiscale data assimilation (MS-DA) framework that is used within the Weather Research and Forecasting model at a cloud-resolving resolution of 2 km. The MS-DA algorithm uses existing reanalysis products and constrains fine-scale atmospheric properties by assimilating high-resolution observations. A set of experiments show that the data assimilation analysis realistically reproduces the intensity, structure, and time evolution of clouds and precipitation associated with a mesoscale convective system. Evaluations also show that the large-scale forcing derived from the fine-resolution analysis has an overall accuracy comparable to the existing ARM operational product. For enhanced applications, the fine-resolution fields are used to characterize the contribution of subgrid variability to the large-scale forcing and to derive hydrometeor forcing, which are presented in companion papers.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2018

Designing an effective drug combination for ER stress loading in cancer therapy using a real-time monitoring system

Excess stress caused by accumulation of misfolded proteins inside the endoplasmic reticulum (ER) lumen can cause cells to undergo apoptosis. Misfolded proteins exported from ER to cytoplasm are ubiquitinated and mostly degraded by the proteasome, but can also be destroyed by autophagy mediated by the docking proteins p62 and NBR1. When misfolded proteins accumulate beyond the capacity of these clearance systems, they are transported to the microtubule organization center to form aggresomes, which are also degraded by autophagy. Together, these phenomena suggest the existence of a coordinated intracellular network for coping with the accumulation of misfolded proteins. Thus, rational inhibition of this network system might enhance killing of cancer cells subjected to pronounced ER stress loading. Based on this rationale, we sought to establish a quantitative assay for monitoring ER stress loading. MDA-MB231 cells stably transfected with the ERAI-Venus vector exhibited a strong XBP1 splicing signal in response to ER stress. Using the IncuCyte cell imaging system, we monitored the fluorescence intensity of XBP1-Venus, normalized against cell density, as an ER stress indicator. This parameter correlated closely with other reporters of unfolded protein responses. Assessment of the XBP1-Venus signal during exposure to various drug combinations revealed that simultaneous inhibition of the proteasome, autophagy, and aggresome formation led to more effective ER stress loading and higher cytotoxicity than inhibition of only two components. Our data suggest that this monitoring system is a useful tool for designing effective drug combinations for ER stress loading in cancer therapy.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

The Scaling of MCS, Non‐MCS, and Total Extreme Precipitation With Temperature Over the Central United States

Abstract While extreme precipitation is expected to increase in a warming climate, its scaling with temperature at weather timescales often produces puzzling results. Here, we focus on the summer months over the central U.S. to investigate the scaling of extreme precipitation intensity (EPI) with local temperature and determine the contribution of mesoscale convective systems (MCSs) to the EPI scaling. Using an observational data set that differentiates precipitation associated with MCS and non‐MCS storms, we find that MCS storms contribute to 70% of EPI samples at temperatures lower than 298 K where EPI increases with temperature. However, at temperatures of 298–305 K, MCSs' contribution to EPI decreases as the predominant storm type shifts from MCS to non‐MCS storms, causing EPI to decrease with temperature due to the weaker rainfall intensity associated with non‐MCS storms compared with MCS storms. Our findings underscore the important role of different storm types in affecting the EPI scaling relationships.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Bioplastic design using multitask deep neural networks

Abstract Non-degradable plastic waste jeopardizes our environment, yet our modern lifestyle and current technologies are impossible to sustain without plastics. Bio-synthesized and biodegradable alternatives such as polyhydroxyalkanoates (PHAs) have the potential to replace large portions of the world’s plastic supply with cradle-to-cradle materials, but their chemical complexity and diversity limit traditional resource-intensive experimentation. Here, we develop multitask deep neural network property predictors using available experimental data for a diverse set of nearly 23,000 homo- and copolymer chemistries. Using the predictors, we identify 14 PHA-based bioplastics from a search space of almost 1.4 million candidates which could serve as potential replacements for seven petroleum-based commodity plastics that account for 75% of the world’s yearly plastic production. We also discuss possible synthesis routes for the identified promising materials.

36 MATERIALS SCIENCE↗

DOE OSTI2010

Marine Corps Base Camp Lejeune Greenness Loss from 1984 to 2009

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of development pressures in surrounding areas, impairments due to other anthropogenic disturbances, and increasing requirements for compliance with environmental regulations. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and to optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a minimum 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the first six years of the program (DCERP1) are presented here.The overarching objectives of DCERP are to: (1) understand the effects of military training activities, infrastructure development, and other coastal military installations; (2) develop models, tools, and indicators to evaluate ecosystem health; and (3) recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.This data package contains loss of Green Vegetation data between 1984 and 2009 from Landsat TM5 images. Results are based on the difference in the Tassle Cap greenness band recorded in 1984 to the greenness recorded in 2009. This Intensity of green loss was then developed into a five category green loss classification using the mean and standard deviation of the green loss difference data set, standardized to the 1984-2007 time period: 0. No green loss, green gain, or background 1. No significant change; values > 0 to =< 0.0035 (mean - SD) 2. Light green loss, reduced forest, impacted veg, etc; values > 0.0035 to =< 0.04556 (mean) 3. Moderate green loss; values > 0.04556 to =< 0.0876 (mean + SD) 4. Heavy green loss; values > 0.0876 to max. Classes 2,3, and 4 are retained as significant green loss locations. Polygon patches are labeled with the intensity value in the attribute 'GRIDCODE'. Greenness loss in this area is a good indicator of human impact and development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2010

Marine Corps Base Camp Lejeune Greenness Loss from 1984 to 1990

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of development pressures in surrounding areas, impairments due to other anthropogenic disturbances, and increasing requirements for compliance with environmental regulations. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and to optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a minimum 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the first six years of the program (DCERP1) are presented here.The overarching objectives of DCERP are to: (1) understand the effects of military training activities, infrastructure development, and other coastal military installations; (2) develop models, tools, and indicators to evaluate ecosystem health; and (3) recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.This data package contains Loss of Green Vegetation data between 1984 and 1990 from Landsat TM5 images. Results are based on the difference in the Tassle Cap greenness band recorded in 1984 and the greenness recorded in 1990. This Intensity of green loss was then developed into a five category green loss classification using the mean and standard deviation of the green loss difference data set, standardized to the 1984-2007 time period: 0. No green loss, green gain, or background 1. No significant change; values > 0 to =< 0.0035 (mean - SD) 2. Light green loss, reduced forest, impacted veg, etc; values > 0.0035 to =< 0.04556 (mean) 3. Moderate green loss; values > 0.04556 to =< 0.0876 (mean + SD) 4. Heavy green loss; values > 0.0876 to max. Classes 2, 3, and 4 are retained as significant green loss locations. Polygon patches are labeled with the intensity value in the attribute 'GRIDCODE'. Greenness loss in this area is a good indicator of human impact and development.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2010

Marine Corps Base Camp Lejeune Greenness Loss from 1984 to 2005

Critical military training and testing on lands along the nation’s coastal and estuarine shorelines are increasingly placed at risk because of development pressures in surrounding areas, impairments due to other anthropogenic disturbances, and increasing requirements for compliance with environmental regulations. The U.S. Department of Defense (DoD) intends to enhance and sustain its training and testing assets and to optimize its stewardship of natural resources through the development and application of an ecosystem-based management approach on DoD installations. To accomplish this goal, particularly for installations in estuarine/coastal environments, the Strategic Environmental Research and Development Program (SERDP) launched the Defense Coastal/Estuarine Research Program (DCERP) as a minimum 10-year effort at Marine Corps Base Camp Lejeune (MCBCL) in North Carolina. The results of the first six years of the program (DCERP1) are presented here.The overarching objectives of DCERP are to: (1) understand the effects of military training activities, infrastructure development, and other coastal military installations; (2) develop models, tools, and indicators to evaluate ecosystem health; and (3) recommend adaptive management strategies to sustain ecosystem natural resources within the context of an active military installation.This data package measures Loss of Green Vegetation between 1984 and 2005 from Landsat TM5 images. Results are based on the difference in the Tassle Cap greenness band recorded in 1984 and the greenness recorded in 2005. This Intensity of green loss was then developed into a five category green loss classification using the mean and standard deviation of the green loss difference data set, standardized to the 1984-2007 time period: 0. No green loss, green gain, or background 1. No significant change; values > 0 to =< 0.0035 (mean - SD) 2. Light green loss, reduced forest, impacted veg, etc; values > 0.0035 to =< 0.04556 (mean) 3. Moderate green loss; values > 0.04556 to =< 0.0876 (mean + SD) 4. Heavy green loss; values > 0.0876 to max. Classes 2, 3, and 4 are retained as significant green loss locations. Polygon patches are labeled with the intensity value in the attribute 'GRIDCODE'. Greenness loss in this area is a good indicator of human impact and development.

54 ENVIRONMENTAL SCIENCES↗