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NASA NTRS2011

Influence of Sensory Dependence on Postural Control

The current project is part of an NSBRI funded project, "Development of Countermeasures to Aid Functional Egress from the Crew Exploration Vehicle Following Long-Duration Spaceflight." The development of this countermeasure is based on the use of imperceptible levels of electrical stimulation to the balance organs of the inner ear to assist and enhance the response of a person s sensorimotor function. These countermeasures could be used to increase an astronaut s re-adaptation rate to Earth s gravity following long-duration space flight. The focus of my project is to evaluate and examine the correlation of sensory preferences for vision and vestibular systems. Disruption of the sensorimotor functions following space flight affects posture, locomotion and spatial orientation tasks in astronauts. The Group Embedded Figures Test (GEFT), the Rod and Frame Test (RFT) and the Computerized Dynamic Posturography Test (CDP) are measurements used to examine subjects visual and vestibular sensory preferences. The analysis of data from these tasks will assist in relating the visual dependence measures recognized in the GEFT and RFT with vestibular dependence measures recognized in the stability measures obtained during CDP. Studying the impact of sensory dependence on the performance in varied tasks will help in the development of targeted countermeasures to help astronauts readapt to gravitational changes after long duration space flight.

Santana, Patricia A.↗

NASA NTRS2012

Online Assessment of Satellite-Derived Global Precipitation Products

Precipitation is difficult to measure and predict. Each year droughts and floods cause severe property damages and human casualties around the world. Accurate measurement and forecast are important for mitigation and preparedness efforts. Significant progress has been made over the past decade in satellite precipitation product development. In particular, products' spatial and temporal resolutions as well as timely availability have been improved by blended techniques. Their resulting products are widely used in various research and applications. However biases and uncertainties are common among precipitation products and an obstacle exists in quickly gaining knowledge of product quality, biases and behavior at a local or regional scale, namely user defined areas or points of interest. Current online inter-comparison and validation services have not addressed this issue adequately. To address this issue, we have developed a prototype to inter-compare satellite derived daily products in the TRMM Online Visualization and Analysis System (TOVAS). Despite its limited functionality and datasets, users can use this tool to generate customized plots within the United States for 2005. In addition, users can download customized data for further analysis, e.g. comparing their gauge data. To meet increasing demands, we plan to increase the temporal coverage and expanded the spatial coverage from the United States to the globe. More products have been added as well. In this poster, we present two new tools: Inter-comparison of 3B42RT and 3B42 Inter-comparison of V6 and V7 TRMM L-3 monthly products The future plans include integrating IPWG (International Precipitation Working Group) Validation Algorithms/statistics, allowing users to generate customized plots and data. In addition, we will expand the current daily products to monthly and their climatology products. Whenever the TRMM science team changes their product version number, users would like to know the differences by inter-comparing both versions of TRMM products in their areas of interest. Making this service available to users will help them to better understand associated changes. We plan to implement this inter-comparison in TRMM standard monthly products with the IPWG algorithms. The plans outlined above will complement and accelerate the existing and ongoing validation activities in the community as well as enhance data services for TRMM and the future Global Precipitation Mission (GPM).

Liu, Zhong↗

NASA NTRSDate not supplied

Effects of Mild Hypobaric Hypoxia on Visual Field Impairment

INTRODUCTION: The primary objective of the Exploration Atmosphere (EA) study is to validate a new prebreathe protocol necessary before exposure to a suited hypobaric environment during extravehicular activity (EVA) from a habitat ‘exploration atmosphere’ of 56.5kPa (8.2 psia), 34% O2, 66% N2. Prebreathe protocols must be time and resource efficient while also controlling Decompression Sickness (DCS) risk to within acceptable limits. The habitat hypobaric exploration atmosphere also results in a mildly hypoxic environment (piO2 = 128mmHg). As a secondary objective of the EA study, we characterized the effects of 11-day exposure to a mild hypobaric hypoxic environment on visual performance. METHODS: Two, 11-day hypobaric chamber tests were performed (EA-1and EA-2, n=8 each) in NASA’s 20-foot chamber at Johnson Space Center where subjects lived in the exploration atmosphere. Subjects also underwent simulated 6-hour EVAs at 85% O2 and 29.6 kPa during EVA on days 3, 5, 7, 9, and 11. Visual acuity (VA), a measure of spatial resolution, and contrast sensitivity (CS), a measure of ability to distinguish ever finer increments of brightness, were assessed on non-EVA days by using gapped Landolt C testing. The luminance was controlled by using a booth, a light monitor, and a lighting rheostat. EA-1 data had revealed problems in lighting control impacting consistency of the data. Procedures were subsequently updated for the EA-2 test. RESULTS: EA-1 data revealed large variance and data recording errors and was removed from the analysis. One participant left the study at Test Day 3 during EA-2. EA-2 ANOVA results showed CS (mean change=0.010 logCSWeber) and VA (mean change, -0.016 logMAR) between pre-test and 11-day test phases; however, neither VA nor CS changes were statistically significant. There were non-statistically significant declines in VA across test phases. DISCUSSION: Overall, visual field performance did not exhibit clinically significant changes (3 lines or greater change in LogMar chart) during exposure to the mild hypoxic exploration atmosphere environment compared to pre-test baseline. The consistency and stability of VA data during EA-2 suggests that the mild hypobaric hypoxic environment did not cause clinically significant negative impacts to participants’ visual field performance.

Visual Acuity↗

NASA NTRSDate not supplied

Effects of Mild Hypobaric Hypoxia on Visual Field Impairment

Visual Acuity↗

NASA NTRS2019

Using Science Operations Tools and Methods from NASA for Remote Presence Ocean Exploration on Earth: E/V Nautilus Cruise NA108

NASA Ames' Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade.In the last two years, we have participated in SUBSEA, a multi-institution collaborative project. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC). In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule.The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team's ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA's Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island's Graduate School of Oceanography (GSO). ISC is GSO's telepresence operations facility.

Lees, David S.↗

NASA NTRS2020

Conducting Efficient Remote Science and Planning Operations for Ocean Exploration Using Exploration Ground Data Systems (xGDS)

NASA Ames’ Exploration Ground Data Systems (xGDS) supports rapid scientific decision making by synchronizing information in time and space, including video and still images, scientific instrument data, and science and operations notes in geographic and temporal context. We have deployed xGDS at multiple NASA field analog missions over the past decade. In the last two years, we have participated in SUBSEA, a multi-institution collaborative project*. SUBSEA used the research ship E/V Nautilus along with its two remotely operated vehicles (ROVs), Hercules and Argus, to explore deep ocean volcanic vents as an analog for ocean worlds (e.g. Enceladus). This work allowed us to compare the existing oceanographic operations methods and technologies used for ocean exploration with corresponding tools and approaches developed and used at NASA. In the first year of SUBSEA we observed existing remote science operations from the Inner Space Center (ISC)**. In the second year, we deployed xGDS at ISC to complement existing capabilities with xGDS tools designed to support remote Nautilus science operations from the ISC. During operations, video, ROV position and instrument telemetry were streamed from the ship to the ISC. As the science team watched dive operations, they could annotate the data with observations that were relevant to their work domain. Later, the team members could review the data at their own pace to collaboratively develop a dive plan for the next day, which had to be delivered on a fixed daily schedule. The opportunity to compare operations under different conditions enabled us to make several key observations about conducting remote science and planning operations efficiently: (i) Reviewing data collaboratively and interactively with temporal and spatial context was critical for the remote science team’s ability to plan dive operations on the Nautilus. (ii) Science team members were actively engaged with the remote dive operations because they could interact with the collected data and visualize it as they desired. (iii) Being able to replay past events at accelerated speeds, and jump to points in time and spaced based on search results, provided efficient access to critical points of interest in a massive volume of data, so the remote science team could deliver plans on time. * SUBSEA (Systematic Underwater Biogeochemical Science and Exploration Analog) is a multi-institution collaboration supported by NASA, NOAA’s Office of Exploration Research (OER), the Ocean Exploration Trust (OET) and the University of Rhode Island’s Graduate School of Oceanography (GSO).

Cohen, Tamar E.↗

NASA NTRSDate not supplied

SatCORPS Global Cloud Composite (GCC): the Design and Delivery of A High Quality, High Resolution, Global Cloud Product Available in Near-Real Time

The NASA Satellite ClOud and Radiation Property retrieval System (SatCORPS) supports the development of an analysis ready and cloud-optimized data transformation pipeline and geospatial service enablement of a global cloud composite (GCC) product derived from global geostationary satellite imagery. This geospatial service will be available at high temporal and spatial resolution via the SatCORPS web mapping application for visualization and analysis as well as direct ingestion to common geospatial software and custom programming. The resulting global cloud composite products from the processing pipeline can then be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. Near real time global observations are created through the composition of five geostationary satellites that provides modelling and forecasting communities with the capability to provide high quality and timely information to start the projection process. The Global Cloud Composite product combines information from geostationary satellites, GOES-16, GOES-17, Himawari-8, Meteosat-11 and Meteosat-9 to create a single global composite netcdf file and images using the different products within the netcdf file. The SatCORPS team, though our Global Cloud Composite (GCC) product and web-based visualization tools including Geographical Information System (GIS) services provide near real time global cloud product information to both automated processes and traditional web users that is timely and high quality derived from geostationary satellites. The Global Cloud Composite product takes advantage of the scalable processing resources provided by the AWS batch service to provide new composites every thirty minutes. Because information from each of the low earth orbiting satellites is available on schedules tuned to the specific satellite, the processing algorithm temporally composites the final dataset as each satellite’s information becomes available. The SatCORPS team has leveraged our experience using Amazon Web Services (AWS) to build a low latency high availability tool that allows end users both human and automated to acquire high quality and high-resolution Geostationary Earth Orbiting (GEO) information at zero cost to the end user. This presentation will describe how we architected and implemented the service as well as lessons learned based on our experiences both developing and operating the system. The lessons learned include how we integrated multiple services including Amazon Batch, Amazon S3 and Amazon Lambda service to create a low cost but high-performance processing system that is capable of identifying and processing the most appropriate satellite overpass information into global cloud composites. We will also describe our web-based tools including our Geographic Information System that can be used for visualization and analysis. The products from the processing can be geospatially-service enabled as ArcGIS Image Services and Open Geospatial Consortium (OGC) Web Mapping/Coverage Services for visualization and analysis via a web mapping application and common geospatial software. The SatCORPS Global Composite Cloud product provides sophisticated global composited cloud research products with very low latency that we see that as filling a rapidly growing need in the research and modelling community with no up-front nor ongoing costs associated with downloading or using the information.

AWS AMCE SMCE GCC SATCORPS GLOBAL CLOUD COMPOSITE ↗

NASA NTRS1998

Multi-Scale Fractal Analysis of Image Texture and Pattern

Fractals embody important ideas of self-similarity, in which the spatial behavior or appearance of a system is largely independent of scale. Self-similarity is defined as a property of curves or surfaces where each part is indistinguishable from the whole, or where the form of the curve or surface is invariant with respect to scale. An ideal fractal (or monofractal) curve or surface has a constant dimension over all scales, although it may not be an integer value. This is in contrast to Euclidean or topological dimensions, where discrete one, two, and three dimensions describe curves, planes, and volumes. Theoretically, if the digital numbers of a remotely sensed image resemble an ideal fractal surface, then due to the self-similarity property, the fractal dimension of the image will not vary with scale and resolution. However, most geographical phenomena are not strictly self-similar at all scales, but they can often be modeled by a stochastic fractal in which the scaling and self-similarity properties of the fractal have inexact patterns that can be described by statistics. Stochastic fractal sets relax the monofractal self-similarity assumption and measure many scales and resolutions in order to represent the varying form of a phenomenon as a function of local variables across space. In image interpretation, pattern is defined as the overall spatial form of related features, and the repetition of certain forms is a characteristic pattern found in many cultural objects and some natural features. Texture is the visual impression of coarseness or smoothness caused by the variability or uniformity of image tone or color. A potential use of fractals concerns the analysis of image texture. In these situations it is commonly observed that the degree of roughness or inexactness in an image or surface is a function of scale and not of experimental technique. The fractal dimension of remote sensing data could yield quantitative insight on the spatial complexity and information content contained within these data. A software package known as the Image Characterization and Modeling System (ICAMS) was used to explore how fractal dimension is related to surface texture and pattern. The ICAMS software was verified using simulated images of ideal fractal surfaces with specified dimensions. The fractal dimension for areas of homogeneous land cover in the vicinity of Huntsville, Alabama was measured to investigate the relationship between texture and resolution for different land covers.

Emerson, Charles W.↗

NASA NTRS1994

Technical parameters for specifying imagery requirements

Providing visual information acquired from remote events to various operators, researchers, and practitioners has become progressively more important as the application of special skills in alien or hazardous situations increases. To provide an understanding of the technical parameters required to specify imagery, we have identified, defined, and discussed seven salient characteristics of images: spatial resolution, linearity, luminance resolution, spectral discrimination, temporal discrimination, edge definition, and signal-to-noise ratio. We then describe a generalizing imaging system and identified how various parts of the system affect the image data. To emphasize the different applications of imagery, we have constrasted the common television system with the significant parameters of a televisual imaging system for technical applications. Finally, we have established a method by which the required visual information can be specified by describing certain technical parameters which are directly related to the information content of the imagery. This method requires the user to complete a form listing all pertinent data requirements for the imagery.

Coan, Paul P.↗

NASA NTRS1995

Mississippi State University Center for Air Sea Technology FY95 Research Program

The Mississippi State University (MSU) Center for Air Sea Technology (CAST) evolved from the Institute for Naval Oceanography's (INO) Experimental Center for Mesoscale Ocean Prediction (ECMOP) which was started in 1989. MSU CAST subsequently began operation on 1 October 1992 under an Office of Naval Research (ONR) two-year grant which ended on 30 September 1994. In FY95 MSU CAST was successful in obtaining five additional research grants from ONR, as well as several other research contracts from the Naval Oceanographic Office via NASA, the Naval Research Laboratory, the Army Corps of Engineers, and private industry. In the past, MSU CAST technical research and development has produced tools, systems, techniques, and procedures that improve efficiency and overcome deficiency for both the operational and research communities residing with the Department of Defense, private industry, and university ocean modeling community. We continued this effort with the following thrust areas: to develop advanced methodologies and tools for model evaluation, validation and visualization, both oceanographic and atmospheric; to develop a system-level capability for conducting temporally and ; spatially scaled ocean simulations driven by or are responsive to ocean models, and take into consideration coupling to atmospheric models; to continue the existing oceanographic/atmospheric data management task with emphasis on distributed databases in a network environment, with database optimization and standardization, including use of Mosaic and World Wide Web (WWW) access; and to implement a high performance parallel computing technology for CAST ocean models

Yeske, Lanny↗

NASA NTRS1985

Image processing of aerodynamic data

The use of digital image processing techniques in analyzing and evaluating aerodynamic data is discussed. An image processing system that converts images derived from digital data or from transparent film into black and white, full color, or false color pictures is described. Applications to black and white images of a model wing with a NACA 64-210 section in simulated rain and to computed low properties for transonic flow past a NACA 0012 airfoil are presented. Image processing techniques are used to visualize the variations of water film thicknesses on the wing model and to illustrate the contours of computed Mach numbers for the flow past the NACA 0012 airfoil. Since the computed data for the NACA 0012 airfoil are available only at discrete spatial locations, an interpolation method is used to provide values of the Mach number over the entire field.

Faulcon, N. D.↗

NASA NTRS1991

Digital visual communications using a Perceptual Components Architecture

The next era of space exploration will generate extraordinary volumes of image data, and management of this image data is beyond current technical capabilities. We propose a strategy for coding visual information that exploits the known properties of early human vision. This Perceptual Components Architecture codes images and image sequences in terms of discrete samples from limited bands of color, spatial frequency, orientation, and temporal frequency. This spatiotemporal pyramid offers efficiency (low bit rate), variable resolution, device independence, error-tolerance, and extensibility.

Watson, Andrew B.↗

NASA NTRS1984

Image-plane processing of visual information

Shannon's theory of information is used to optimize the optical design of sensor-array imaging systems which use neighborhood image-plane signal processing for enhancing edges and compressing dynamic range during image formation. The resultant edge-enhancement, or band-pass-filter, response is found to be very similar to that of human vision. Comparisons of traits in human vision with results from information theory suggest that: (1) Image-plane processing, like preprocessing in human vision, can improve visual information acquisition for pattern recognition when resolving power, sensitivity, and dynamic range are constrained. Improvements include reduced sensitivity to changes in lighter levels, reduced signal dynamic range, reduced data transmission and processing, and reduced aliasing and photosensor noise degradation. (2) Information content can be an appropriate figure of merit for optimizing the optical design of imaging systems when visual information is acquired for pattern recognition. The design trade-offs involve spatial response, sensitivity, and sampling interval.

Huck, F. O.↗

NASA NTRS1998

Physics of Boundaries and their Interactions in Space Plasmas

This final report describes a brief summary of our accomplishments during the complete contract period. Traditionally, due to computational limitations, it has been impossible to obtain a global view of the magnetosphere on ion time and spatial scales. As a result, kinetic-simulations have concentrated on the local structure of different magnetospheric discontinuities and boundaries. However, due to the emergence of low cost supercomputers, as well as by taking full advantage of latest advances in data mining and visualization technology, we were able to bypass our planned (proposed) regional simulations and proceed to large-scale 3-D and 2-D global hybrid simulations of the magnetosphere. As a result, although we are only finishing the second year of the proposed activity, much of the original scientific objectives have been surpassed and new avenues of investigation have been opened. Such simulations have led us to possible explanations of some long-standing issues in magnetospheric physics. They have also enables us to make a number of important discoveries predictions, which need to be looked for in satellite data. Examples include the finding that the bow shock can become unstable to the Kelvin-Helmholtz (KH), (2) the discovery of a mechanism for intermittent reconnection due to ion physics which may be relevant to the explanation of the recurrence rate of flux transfer events (FTEs), and (3) this finding that the current sheet in the near-Earth magnetotail region can become unstable to KH with detectable, unique ionospheric signatures. Further, we demonstrated a viable mechanism for the onset of reconnection at the magnetopause, examined the detailed structure of the boundary layer incorporating curvature effects, and provided an explanation for the large core fields observed within FTEs as well as flux ropes in the magnetotail.

Omidi, Nojan↗

NASA NTRS1998

Physics of Boundaries and their Interactions in Space Plasmas

This final report describes a brief summary of our accomplishments during the complete contract period. Traditionally, due to computational limitations, it has been impossible to obtain a global view of the magnetosphere on ion time and spatial scales. As a result, kinetic simulations have concentrated on the local structure of different magnetospheric discontinuities and boundaries. However, due to the emergence of low cost desktop superconductors, as well as by taking full advantage of latest advances in data mining and visualization technology, we were able to bypass our planned (proposed) regional simulations and proceed to large-scale 3-D and 2-D global hybrid simulations of the magnetosphere. As a result, although we are only finishing the second year of the proposed activity, much of the original scientific objectives have been surpassed and new avenues of investigation have been opened. Such simulations have led us to possible explanations of some long-standing issues in magnetospheric physics. They have also enabled us to make a number of important discoveries/predictions, which need to be looked for in satellite data. Examples include: (1) the finding that the bow shock can become unstable to the Kelvin-Helmholtz (KH;) (2) the discovery of a mechanism for intermittent reconnection due to ion physics which may be relevant to the explanation of the recurrence rate of flux transfer events (FTEs;) and (3) the finding that the current sheet in the near-Earth magnetotail region can become unstable to KH with detectable, unique ionospheric signatures. Further, we demonstrated a viable mechanism for the onset of reconnection at the magnetopause, examined the detailed structure of the boundary layer incorporating curvature effects, and provided an explanation for the large core fields observed within FTEs as well as flux ropes in the magnetotail.

Omidi, Nojan↗

NASA NTRS2011

Accessing Recent Trend of Land Surface Temperature from Satellite Observations

Land surface temperature (Ts) is an important element to measure the state of terrestrial ecosystems and to study surface energy budgets. In support of the land cover/land use change-related international program MAIRS (Monsoon Asia Integrated Regional Study), we have collected global monthly Ts measured by MODIS since the beginning of the missions. The MODIS Ts time series have approximately 11 years of data from Terra since 2000 and approximately 9 years of data from Aqua since 2002, which makes possible to study the recent climate, such as trend. In this study, monthly climatology from two platforms are calculated and compared with that from AIRS. The spatial patterns of Ts trends are accessed, focusing on the Eurasia region. Furthermore, MODIS Ts trends are compared with those from AIRS and NASA's atmospheric assimilation model, MERRA (Modern Era Retrospective-analysis for Research and Applications). The preliminary results indicate that the recent 8-year Ts trend shows an oscillation-type spatial variation over Eurasia. The pattern is consistent for data from MODIS, AIRS, and MERRA, with the positive center over Eastern Europe, and the negative center over Central Siberia. The calculated climatology and anomaly of MODIS Ts will be integrated into the online visualization system, Giovanni, at NASA GES DISC for easy use by scientists and general public.

Shen, Suhung↗

NASA NTRS2011

Metric Learning for Hyperspectral Image Segmentation

We present a metric learning approach to improve the performance of unsupervised hyperspectral image segmentation. Unsupervised spatial segmentation can assist both user visualization and automatic recognition of surface features. Analysts can use spatially-continuous segments to decrease noise levels and/or localize feature boundaries. However, existing segmentation methods use tasks-agnostic measures of similarity. Here we learn task-specific similarity measures from training data, improving segment fidelity to classes of interest. Multiclass Linear Discriminate Analysis produces a linear transform that optimally separates a labeled set of training classes. The defines a distance metric that generalized to a new scenes, enabling graph-based segmentation that emphasizes key spectral features. We describe tests based on data from the Compact Reconnaissance Imaging Spectrometer (CRISM) in which learned metrics improve segment homogeneity with respect to mineralogical classes.

Compact Reconnaissance Imaging Spectrometer (CRISM↗

NASA NTRS2021

Hydrologic Baseline Conditions and Projected Trends for Kennedy Space Center and the Cape Canaveral Barrier Island Complex

The purpose of this document is the creation of a comprehensive collection of data, information and knowledge on the eco-hydrologic setting, and current and predicted (2030 -2080) hydrologic conditions that will directly and indirectly influence the Kennedy Space Center (KSC) industrial and ecological system. Focus is on identification of existing data sources (web based, published, in-house) and identification of future possible needs. The document will aid in assessment of risks to the National Aeronautics and Space Administration (NASA) and stakeholder missions associated with changing local, regional and global conditions. This living document will allow for rapid updates as new data and improved spatial data (LiDAR elevations, land use, land cover, runoff coefficients, etc.) are accumulated by the Environmental Management Branch (EMB), stakeholders, and supporting staff from the NASA Environmental and Medical Contract (NEMCON) currently managed by Herndon Solutions Group LLC. (HSG).The report summarizes and visualizes hydrologic conditions supporting long-term trends monitoring, management and regulatory compliance needs, climate risk mitigation, and achievement of KSC and stakeholder’s sustainability goals. Future utility may extend to implementation actions of the KSC future development plan, KSC updates to future KSC Environmental Resource Documents (ERD), and the regional multi-agency Indian River Lagoon Health Initiative.

Carlton Hall↗