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This paper describes the development and evaluation of a simulation procedure which produces patterns of Landsat data loss attributable to cloud patterns that are characteristic of a crop region. This simulation procedure is part of a simulation system under development which evaluates the performance of crop inventory system components over a number of years and under a variety of conditions.
A technology development plan designed to reduce the data load and data-management problems associated with global study and monitoring missions is described with a heavy emphasis placed on developing mission capabilities to eliminate the collection of unnecessary data. Improved data selectivity can be achieved through sensor automation correlated with the real-time needs of data users. The first phase of the plan includes the Feature Identification and Location Experiment (FILE) which is scheduled for the 1980 Shuttle flight. The FILE experiment is described with attention given to technology needs, development plan, feature recognition and classification, and cloud-snow detection/discrimination. Pointing, tracking and navigation received particular consideration, and it is concluded that this technology plan is viewed as an alternative to approaches to real-time acquisition that are based on extensive onboard format and inventory processing and reliance upon global-satellite-system navigation data.
Abstract. Ammonia (NH3) plays a central role in the chemistry of inorganic secondary aerosols in the atmosphere. The largest emission sector for NH3 is agriculture, where NH3 is volatilized from livestock wastes and fertilized soils. Although the NH3 volatilization from soils is driven by the soil temperature and moisture, many atmospheric chemistry models prescribe the emission using yearly emission inventories and climatological seasonal variations. Here we evaluate an alternative approach where the NH3 emissions from agriculture are simulated interactively using the process model FANv2 (Flow of Agricultural Nitrogen, version 2) coupled to the Community Atmospheric Model with Chemistry (CAM-chem). We run a set of 6-year global simulations using the NH3 emission from FANv2 and three global emission inventories (EDGAR, CEDS and HTAP) and evaluate the model performance using a global set of multi-component (atmospheric NH3 and NH4+, and NH4+ wet deposition) in situ observations. Over East Asia, Europe and North America, the simulations with different emissions perform similarly when compared with the observed geographical patterns. The seasonal distributions of NH3 emissions differ between the inventories, and the comparison to observations suggests that both FANv2 and the inventories would benefit from more realistic timing of fertilizer applications. The largest differences between the simulations occur over data-scarce regions. In Africa, the emissions simulated by FANv2 are 200 %–300 % higher than in the inventories, and the available in situ observations from western and central Africa, as well as NH3 retrievals from the Infrared Atmospheric Sounding Interferometer (IASI) instrument, are consistent with the higher NH3 emissions as simulated by FANv2. Overall, in simulating ammonia and ammonium concentrations over regions with detailed regional emission inventories, the inventories based on these details (HTAP, CEDS) capture the atmospheric concentrations and their seasonal variability the best. However these inventories cannot capture the impact of meteorological variability on the emissions, nor can these inventories couple the emissions to the biogeochemical cycles and their changes with climate drivers. Finally, we show with sensitivity experiments that the simulated time-averaged nitrate concentration in air is sensitive to the temporal resolution of the NH3 emissions. Over the CASTNET monitoring network covering the US, resolving the NH3 emissions hourly instead monthly reduced the positive model bias from approximately 80 % to 60 % of the observed yearly mean nitrate concentration. This suggests that some of the commonly reported overestimation of aerosol nitrate over the US may be related to unresolved temporal variability in the NH3 emissions.
Despite the promise of the gut microbiome to predict human health, few studies expose the molecular-scale processes underpinning such forecasts. We mined over 200,000 gut-derived genomes from cultivated and uncultivated microbial lineages to inventory the gut microorganisms and their gene content that control trimethylamine-induced cardiovascular disease. We assigned an atherosclerotic profile to the 6,341 microbial genomes that encoded metabolisms associated with heart disease, creating the Methylated Amine Gene Inventory of Catabolism database (MAGICdb). From microbiome gene expression data sets, we demonstrate that MAGICdb enhanced the recovery of disease-relevant genes and identified the most active microorganisms, unveiling future therapeutic targets. From the feces of healthy and diseased subjects, we show that MAGICdb predicted cardiovascular disease status as effectively as traditional lipid blood tests. This functional microbiome catalog is a public, exploitable resource, designed to enable a new era of microbiota-based therapeutics and diagnostics
The author has identified the following significant results. At the Atlanta site (226B) it was found that bulk color composites for October 15, 1972, and April 13, 1973, can be interpreted together to disclose the location of the perennial Kudzu vine (Pyeraria lobata). Land managers concerned with Kudzu eradication could use ERTS-1 to inventory locations over 200 meters (660 feet) square. Microdensitometer data collected on ERTS-1 Bulk photographic products for the Manitou test site (226C) have shown that the 15-step gray-scale tablets are not of systematic equal values corresponding to 1/14 the maximum radiant energy incident on the MSS sensor. The gray-scale values present a third-order polynomial function rather than a direct linear relationship. Although data collected on step tablets for precision photographic products appear more discrete, the density variation within blocks in almost as great as variations between blocks. These system errors will cause problems when attempting to analyze radiometric variances among vegetation and land use classes.
The NASA-U.S. Department of Agriculture Large Area Crop Inventory Experiment (LACIE), aimed at using multispectral remote sensing data from Landsat 1 and 2 to generate accurate annual global crop production forecasts, is discussed. The forecasts take into account meteorological conditions as well as yield and acreage, and may be used to increase the discrimination of U.S. harvest estimates down to regional levels and to provide more accurate early-season predictions. Sample problems involving the determination of wheat harvests and the monitoring of drought conditions are described. Difficulties related to misidentification of abnormally-developing plantations, the automatic classification of homogeneous spectral groups, the computerized generation of colored maps, and the estimation of yields during years when exceptional meteorological conditions prevail are also considered. Samples of Landsat-generated classification maps for Western U.S. and for the Saratov, U.S.S.R. crop regions are given.
Skylab/EREP S190A and S190B film products were optically enhanced and visually interpreted to extract data suitable for; (1) mapping coastal land use; (2) inventorying wetlands vegetation; (3) monitoring tidal conditions; (4) observing suspended sediment patterns; (5) charting surface currents; (6) locating coastal fronts and water mass boundaries; (7) monitoring industrial and municipal waste dumps in the ocean; (8) determining the size and flow direction of river, bay and man-made discharge plumes; and (9) observing ship traffic. Film products were visually analyzed to identify and map ten land-use and vegetation categories at a scale of 1:125,000. Digital tapes from the multispectral scanner were used to prepare thematic maps of land use. Classification accuracies obtained by comparison of derived thematic maps of land-use with USGS-CARETS land-use maps in southern Delaware ranged from 44 percent to 100 percent.
A comprehensive LANDSAT related resource inventory was performed in parts of Ghana, Benin, and Upper Volta to determine resource development potential in areas freed of the disease onchocerciasis. The ultimate success of the project lies in the effective use of the data by host country personnel in resource development projects. This requires project follow-through, adequate training of regional counterparts, and integration of the data into an easily used framework. Present levels of support systems and technical expertise in West Africa indicate that an automated system for natural resource data is not currently appropriate. Suggestions for the greater implementation of such inventories are explored.
A wide spectrum of technology pertaining to the inventory of crops using LANDSAT without in situ training data is addressed. Methods considered include Bayesian based through-the-season methods, estimation technology based on analytical profile fitting methods, and expert-based computer aided methods. Although the research was conducted using U.S. data, the adaptation of the technology to the Southern Hemisphere, especially Argentina was considered.
A photogeologic and remote sensing model of porphyry type mineral sytems is considered along with a Landsat application to development of a tectonic model for hydrocarbon exploration of Devonian shales in west-central Virginia, remote sensing and the funnel philosophy, Landsat-based tectonic and metallogenic synthesis of the southwest United States, and an evolving paradigm for computer vision. Attention is given to the neotectonics of the Tibetan plateau deduced from Landsat MSS image interpretation, remote sensing in northern Arizona, the use of an airborne laser system for vegetation inventories and geobotanical prospecting, an evaluation of Thematic Mapper data for hydrocarbon exploration in low-relief basins, and an evaluation of the information content of high spectral resolution imagery. Other topics explored are related to a major source of new radar data for exploration research, the accuracy of geologic maps produced from Landsat data, and an approach for the geometric rectification of radar imagery.
The Material Safety Data Sheets (MSDSs) listed in this index reflect product inventories and associated MSDSs which have been submitted to the Toxic Substance Registry database maintained by the Base Operations Contractor at the Kennedy Space Center. The purpose of this index is to provide a means to access information on the hazards associated with the toxic and otherwise hazardous chemicals stored and used at the Kennedy Space Center.
Boreal Ecosystem-Atmospheric Study (BOREAS) hardcopy maps are a collection of approximately 1,000 hardcopy maps representing the physical, climatological, and historical attributes of areas covering primarily the Manitoba and Saskatchewan provinces of Canada. These maps were collected by BOREAS Information System (BORIS) and Canada for Remote Sensing (CCRS) staff to provide basic information about site positions, manmade features, topography, geology, hydrology, land cover types, fire history, climate, and soils of the BOREAS study region. These maps are not available for distribution through the BOREAS project but may be used as an on-site resource. Information is provided within this document for individuals who want to order copies of these maps from the original map source. Note that the maps are not contained on the BOREAS CD-ROM set. An inventory listing file is supplied on the CD-ROM to inform users of the maps that are available. This inventory listing is available from the Earth Observing System Data and Information System (EOSDIS) Oak Ridge National Laboratory (ORNL) Distributed Active Archive Center (DAAC). For hardcopies of the individual maps, contact the sources provided.
Central Africa has the second largest unfragmented block of tropical rain forest in the world; it is also one of the largest carbon and biodiversity reservoirs. With nearly one-third of the forest currently allocated for logging, the region is poised to undergo extensive land-use change. Through the mapping of the forests, our Integrated Forest Monitoring System for Central Africa (INFORMS) project aims to monitor habitat alteration, support biodiversity conservation, and promote better land-use planning and forest management. Designed as an interdisciplinary project, its goal is to integrate data acquired from satellites with field observations from forest inventories, wildlife surveys, and socio-economic studies to map and monitor forest resources. This project also emphasizes on collaboration and coordination with international, regional, national, and local partners-including non-profit, governmental, and commercial sectors. This project has been focused on developing remote sensing products for the needs of forest conservation and management, insuring that research findings are incorporated in forest management plans at the national level. The societal impact of INFORMS can be also appreciated through the development of a regional remote sensing network in central Africa. With a regional office in Kinshasa, (www.OSFAC.org), the contribution to the development of forest management plans for 1.5 million hectares of forests in northern Republic of Congo (www.tt-timber.com), and the monitoring of park encroachments in the Albertine region (Uganda and DRC) (www.albertinerift.org).
Ground-based, air-borne and space-based, infrared spectra of a wide variety of objects have revealed prominent absorption and emission features due to large molecules and small dust grains. Analysis of this data reveals a highly diverse interstellar and circumstellar grain inventory, including both amorphous materials and highly crystalline compounds (silicates and carbon). This diversity points towards a wide range of physical and chemical birthsites as well as a complex processing of these grains in the interstellar medium. In this talk, I will review the dust inventory contrasting and comparing both the interstellar and circumstellar reservoirs. The focus will be on the processes that play a role in the lifecycle of dust in the interstellar medium.
The movie describes collaboration between NASA and Vint Cerf on the development of Disruption Tolerant Networks (DTN) for use in space exploration. Current evaluation efforts at Johnson Space Center are focused on the use of DTNs in space communications. Tests include the ability of rovers to store data for later display, tracking local and remote habitat inventory using radio-frequency identification tags, and merging networks.
Accurately quantifying methane (CH4) emissions from the oil and gas (O&G) industry is challenging given the existence of many potential emission sources, differences in industry practices and regulations, and often incomplete or out-of-date activity data. It is thus important to regularly assess emission inventories and support improvements by deriving independent estimates using state-of-the-science approaches. Recent research has provided CH4 emission estimates from the O&G supply chains based on different measurement techniques at multiple spatio-temporal scales. Natural gas basin-scale aircraft-based atmospheric measurements indicate greater CH4 emissions than emission inventories based on up-scaling of component-/facility-level emission measurements from a relatively small sample size. Here we present results from a coordinated field study that compares concurrent CH4 emission measurements using different techniques and scales to better understand the strengths and weaknesses of each approach, with a focus on the aircraft-based estimation method. We describe the importance of (i) decades of measurement technology development, (ii) experience in designing measurement sampling strategies and aligning system boundaries, and (Hi) properly interpreting CH4 emission estimates for successfully reconciling aircraft-based measurements with emission inventories and for identifying CH4 emission mitigation potential. We illustrate that aircraft-based top-down estimates represent a brief snapshot of total basin-level CH4 emissions. Thus, a high spatio-temporally resolved bottom-up emission inventory is needed to identify key CH4 sources (including episodic sources) at the process level. While this paper provides a brief overview of the overall study design and findings, its focus is on the implementation of the aircraft measurements and its interpretation and results. A separate paper describes in more detail the overall organizational structure of the study as well as the study implications from an industry perspective.
Radioactive sources offer many benefits in medicine, industry and education but the lack of appropriate long-term management when they eventually become disused has led to accidents, in some cases with serious consequences, and increased their vulnerability for use in a malicious act. This lack is evident in the absence of clearly defined policy and strategy, responsibilities and resources to meet those responsibilities for safe, secure and sustainable management of disused sources. The strengthening of national legislative and regulatory infrastructures globally has led to major improvements in the protection and control of radioactive sources. Nevertheless, in many countries, radioactive sources were in use before such infrastructures had been developed or adequately strengthened and were therefore not under regulatory control. The paper presents some aspects from Egyptian experience related to safe and secure measures for management of Cs-137, Ra-226 and Co-60 sealed sources. Data relating to the disused radioactive sealed sources, DSRS inventory as well as the arrangements made in order to prepare for conditioning of sources is presented. The efforts made by technical staff and radiation protection team for all arrangements and details such as conditioning set-up, working area, leakage test, certified stainless capsules, radiation protection measures and sources characterization in addition to all security measures for stored DSRS are also presented. (authors)
Inherent in interplanetary space travel are unprecedented challenges that could threaten mission success and negatively impact crew health and performance. Return to definitive care is essentially untenable and resources will be constrained with practically no re-supply capability. Access to ground-based medical expertise will be significantly delayed under nominal conditions with exacerbation during conjunction or prolonged dust storms. Taken together, these challenges necessitate the development of a progressively autonomous medical operational support system to assist the crew medical officer (CMO). While support from ground based medical experts will remain indispensable for pre-mission planning, the approach to management of acute/emergent medical contingencies will require a gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. To progressively enable EIMO, a series of meetings were convened with subject matter experts from within NASA, academia and industry to facilitate mapping of the path to support autonomous medical operations. Topics explored in these meetings included the scope of data (storage capacity, usage, transmission rate and bandwidth, computing capacity), CMO training, supply and resource management and task load balance. Recommendations from these meetings will inform the EIMO Concept of Operations and definition of the associated requirements culminating in updates to the NASA 3001 standards. The EIMO project team will work with stakeholders to conceptualize a clinical decision support system (CDSS) to assist the CMO in response to medical contingencies when terrestrial support is delayed or otherwise unavailable. The CDSS will be a system of systems that will utilize data from numerous input vectors. Successful deployment of the CDSS will facilitate medical decision making while decreasing the cognitive load leading to an improvement in task load balancing. Additional benefits of the envisioned CDSS include assistance with inventory management, locating resources, storage/retrieval of medical records, highlighting trends in recorded data, in addition to providing a consult for diagnosis and treatment. More advanced features might include passive monitoring to identify early warning signs of behavioral or medical anomalies to possibly pre-empt onset of conditions that would compromise crew health and performance.