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ERTS data and aerial photography are shown to represent valuable tools for the inventory and management of inland wetlands. The two discussed examples of the application of remotely-sensed data to specific wetland management needs and requirements are the Great Dismal Swamp of Virginia-North Carolina and the Water Conservation District of southern Florida.
The author has identified the following significant results. ERTS-1 data and aerial photography are proving to be a useful tool for the inventory and management of inland wetlands. Two examples of the application of remotely-sensed data to specific wetland management needs or requirements are discussed. Studies of the Great Dismal Swamp are utilizing ERTS-1 imagery and color IR photography in: (1) study area selection; (2) field inspection; (3) vegetation mapping; (4) identification of drainage characteristics and moisture regime; (5) location of intensive study areas; and (6) detection of change. Thematic extractions of ERTS-1 data made using the United States Geological Survey's Autographic Theme Extraction System are aiding analyses of swamp hydrologic regime and providing information pertinent to quick recognition and inventory of wetlands from ERTS-1. DCP'S in south Florida wetlands provide near-real time data for water resources managers. Data relayed by satellite can be entered into models to provide predictive data and water storage information for long-term and short-term decision making.
Aircraft and satellite remote sensing systems which are capable of contributing to watershed management are described and include: the multispectral scanner subsystem on LANDSAT and the basic multispectral camera array flown on high altitude aircraft such as the U-2. Various aspects of watershed management investigated by remote sensing systems are discussed. Major areas included are: snow mapping, surface water inventories, flood management, hydrologic land use monitoring, and watershed modeling. It is indicated that technological advances in remote sensing of hydrological data must be coupled with an expansion of awareness and training in remote sensing techniques of the watershed management community.
The application of NASA earth resource survey technology to resource management and environmental protection in Michigan was investigated. Remote sensing techniques to aid Michigan government agencies were applied in the following activities: (1) land use inventory and management, (2) great lakes shorelands protection and management, (3) wetlands protection and management, and (4) soil survey. In addition, information was disseminated on remote sensing technology, and advice and assistance was provided to a number of users.
In early 2014, an executive memo was released directing the improvement of the management of and access to scientific collections funded by government resources. In the spirit of this memo, NASA’s Human Research Program (HRP) funded a project to review existing residual samples in long-term storage for viability, identification, and scientific significance. These samples were to be collected in a centralized location and a detailed inventory was to be conducted to create the Human Sample Repository (HSR). HSR would work to review data from over 27,000 samples, from flight research projects dating back to 1998. The samples themselves would be reviewed, re-labeled, and organized into easy to retrieve, long-term storage. In addition to the older residual samples, HSR would expand to include pristine samples from all consenting crew who have flown on International Space Station (ISS) missions. All samples inventoried and managed by HSR are intended for the same purpose; to support future research projects which will utilize advanced technologies or techniques, by providing one-of-a-kind sample collections that can not be replicated. With this mission in mind, HSR will continue to collect residual samples from HRP funded projects and pristine samples from consenting crew, to further build this unique collection and increase the diversity of flight samples available to the scientific community.
It is apparent that the rate of remote sensing technique development is increasing at a much faster pace than is the rate at which these same techniques are being put to practical use by earth resource managers and inventory specialists. It has become increasingly important to bridge this widening gap between remote sensing specialists and potential users. Members of the University of California project on remote sensing of earth resources have been actively participating in efforts to overcome this gap by maintaining library facilities, disseminating research findings, training remote sensing specialists, and interacting with resource managers.
Logistics management has emerged as a key component to activities conducted in space. The RFID Enabled Autonomous Logistics Management (REALM) system has played a key role in providing cargo tracking capabilities in the noisy environment of the ISS. Currently, the inferencing engines used by REALM to predict the location of RFID tagged items operate on an hour of data. Movements aboard space stations occur on the scales of seconds. In this work we propose a new inferencing engine, that produces an embedding space that represents the location of RFID marked cargo on the scale of 30 seconds to 2 minutes of data, allowing for the categorization of movement of cargo, and predictions of a coarse location in less time than existing engines.
Application of remote sensing to inventory and management of ranges resources
There are no author-identified significant results in this report. This investigation is concerned with the development of automated interpretation techniques for the recognition and identification of earth resources. The resources will be identified by using both multispectral and spatial signatures. Ground truth data and aircraft underflight photography will be used to train the recognition algorithms. The data processed will be RBV and MSS images acquired by ERTS-1 satellite, over six test sites located in the vicinities of: Phoenix, Arizona; Weslaco, Texas; Cascade Mountains, Washington; New Orleans, Louisiana; Salt Lake City, Utah; and Salton Sea, California. The processed data will be thematic maps of resources consisting of annotated and outlined images. The seasonal changes of hydrologic and agricultural resources will also be identified. The results are expected to be applicable to a future automatic system of resource inventory and management.
The author has identified the following significant results. Automatic stratification of forested land from ERTS-1 data provides a valuable tool for resource management. The results are useful for wood product yield estimates, recreation and wildlife management, forest inventory, and forest condition monitoring. Automatic procedures based on both multispectral and spatial features are evaluated. With five classes, training and testing on the same samples, classification accuracy of 74 percent was achieved using the MSS multispectral features. When adding texture computed from 8 x 8 arrays, classification accuracy of 90 percent was obtained.
The author has identified the following significant results. This investigation is concerned with the development of automated interpretation techniques for the recognition and identification of earth resources. The resources will be identified by using both multispectral and spatial signatures. Ground truth data and aircraft underflight photography will be used to train the recognition algorithms. The data processed will be RBV and MSS images acquired by the ERTS-1 satellite, over six tests sites located in the vicinities of: Phoenix, Arizona; Weslaco, Texas; Cascade Mountains, Washington; New Orleans, Louisiana; Salt Lake, Utah; and Salton Sea, California. The processed data will be thematic maps of resources consisting of annotated and outlined images. The seasonal changes of hydrologic and agricultural resources will also be identified. The results are expected to be applicable to a future automatic system of resource inventory and management.
Automatic stratification of forested land from ERTS-1 data provides a valuable tool for resource management. The results are useful for wood product yield estimates, recreation and wild life management, forest inventory and forest condition monitoring. Automatic procedures based on both multi-spectral and spatial features are evaluated. With five classes, training and testing on the same samples, classification accuracy of 74% was achieved using the MSS multispectral features. When adding texture computed from 8 x 8 arrays, classification accuracy of 99% was obtained.
System definition studies were conducted of the Earth Observatory Satellite (EOS). The studies show that the concept of an Earth Observatory Satellite in a near-earth, sun-synchronous orbit would make a unique contribution to the goals of a coordinated program for acquisition of data for environmental research with applications to earth resource inventory and management. The technical details for the proposed development of sensors, spacecraft, and a ground data processing system are presented.
Proposed hand-held tool applies indelible bar code to small parts. Possible to identify parts for management of inventory without tags or labels. Microprocessor supplies bar-code data to impact-printer-like device. Device drives replaceable scribe, which cuts bar code on surface of part. Used to mark serially controlled parts for military and aerospace equipment. Also adapts for discrete marking of bulk items used in food and pharmaceutical processing.
A component acquisition plan contains the information needed to evaluate, select, and acquire software and hardware components necessary for successful completion of the AdaNET Dynamic Software Inventory (DSI) Management System Prototype. This plan will evolve and be applicable to all phases of the DSI prototype development. Resources, budgets, schedules, and organizations related to component acquisition activities are provided. A purpose and description of a software or hardware component which is to be acquired are presented. Since this is a plan for acquisition of all components, this section is not applicable. The procurement activities and events conducted by the acquirer are described and who is responsible is identified, where the activity will be performed, and when the activities will occur for each planned procurement. Acquisition requirements describe the specific requirements and standards to be followed during component acquisition. The activities which will take place during component acquisition are described. A list of abbreviations and acronyms, and a glossary are contained.
SafetyChem is a computer program that maintains a relational database for tracking chemicals and associated hazards at Johnson Space Center (JSC) by use of a Web-based graphical user interface. The SafetyChem database is accessible to authorized users via a JSC intranet. All new chemicals pass through a safety office, where information on hazards, required personal protective equipment (PPE), fire-protection warnings, and target organ effects (TOEs) is extracted from material safety data sheets (MSDSs) and recorded in the database. The database facilitates real-time management of inventory with attention to such issues as stability, shelf life, reduction of waste through transfer of unused chemicals to laboratories that need them, quantification of chemical wastes, and identification of chemicals for which disposal is required. Upon searching the database for a chemical, the user receives information on physical properties of the chemical, hazard warnings, required PPE, a link to the MSDS, and references to the applicable International Standards Organization (ISO) 9000 standard work instructions and the applicable job hazard analysis. Also, to reduce the labor hours needed to comply with reporting requirements of the Occupational Safety and Health Administration, the data can be directly exported into the JSC hazardous- materials database.
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