Terrestrial applications: An intelligent Earth-sensing information system

For Abstract see A82-2214

User data dissemination concepts for earth resources

Domestic data dissemination networks for earth-resources data in the 1985-1995 time frame were evaluated. The following topics were addressed: (1) earth-resources data sources and expected data volumes, (2) future user demand in terms of data volume and timeliness, (3) space-to-space and earth point-to-point transmission link requirements and implementation, (4) preprocessing requirements and implementation, (5) network costs, and (6) technological development to support this implementation. This study was parametric in that the data input (supply) was varied by a factor of about fifteen while the user request (demand) was varied by a factor of about nineteen. Correspondingly, the time from observation to delivery to the user was varied. This parametric evaluation was performed by a computer simulation that was based on network alternatives and resulted in preliminary transmission and preprocessing requirements. The earth-resource data sources considered were: shuttle sorties, synchronous satellites (e.g., SEOS), aircraft, and satellites in polar orbits

NASA Sea Ice Validation Program for the Defense Meteorological Satellite Program Special Sensor Microwave Imager

The history of the program is described along with the SSM/I sensor, including its calibration and geolocation correction procedures used by NASA, SSM/I data flow, and the NASA program to distribute polar gridded SSM/I radiances and sea ice concentrations (SIC) on CD-ROMs. Following a discussion of the NASA algorithm used to convert SSM/I radiances to SICs, results of 95 SSM/I-MSS Landsat IC comparisons for regions in both the Arctic and the Antarctic are presented. The Landsat comparisons show that the overall algorithm accuracy under winter conditions is 7 pct. on average with 4 pct. negative bias. Next, high resolution active and passive microwave image mosaics from coordinated NASA and Navy aircraft underflights over regions of the Beaufort and Chukchi seas in March 1988 were used to show that the algorithm multiyear IC accuracy is 11 pct. on average with a positive bias of 12 pct. Ice edge crossings of the Bering Sea by the NASA DC-8 aircraft were used to show that the SSM/I 15 pct. ice concentration contour corresponds best to the location of the initial bands at the ice edge. Finally, a summary of results and recommendations for improving the SIC retrievals from spaceborne radiometers are provided

Building a CHS Bathymetric Data Warehouse

The CHS is designing and implementing a Source Database for bathymetric data. To store and manage terabytes of bathymetric information for producing CHS products and providing services to clients requires a fresh approach. The implementation of HHCode (Helical Hyperspatial Code) for storing, analyzing and accessing dense spatial data sets in an Oracle Relational Database Management System (RDBMS) is a key technology used to build the data warehouse. The paper addresses the concepts and applications necessary to manage this data within the data repository. Specific areas addressed are aggregation, attribution, and partitioning of the spatial data. The implementation of an on-line, near-line and off-line model to minimize storage costs is described. The approach used to perform horizontal and vertical datum transformations is discussed

On requirements for a satellite mission to measure tropical rainfall

Tropical rainfall data are crucial in determining the role of tropical latent heating in driving the circulation of the global atmosphere. Also, the data are particularly important for testing the realism of climate models, and their ability to simulate and predict climate accurately on the seasonal time scale. Other scientific issues such as the effects of El Nino on climate could be addressed with a reliable, extended time series of tropical rainfall observations. A passive microwave sensor is planned to provide information on the integrated column precipitation content, its areal distribution, and its intensity. An active microwave sensor (radar) will define the layer depth of the precipitation and provide information about the intensity of rain reaching the surface, the key to determining the latent heat input to the atmosphere. A visible/infrared sensor will provide very high resolution information on cloud coverage, type, and top temperatures and also serve as the link between these data and the long and virtually continuous coverage by the geosynchronous meteorological satellites. The unique combination of sensor wavelengths, coverages, and resolving capabilities together with the low-altitude, non-Sun synchronous orbit provide a sampling capability that should yield monthly precipitation amounts to a reasonable accuracy over a 500- by 500-km grid

Synthetic Aperture Radar (SAR) data processing

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed

MODIS information, data and control system (MIDACS) level 2 functional requirements

The MODIS Information, Data and Control System (MIDACS) Level 2 Functional Requirements Document establishes the functional requirements for MIDACS and provides a basis for the mutual understanding between the users and the designers of the EosDIS, including the requirements, operating environment, external interfaces, and development plan. In defining the requirements and scope of the system, this document describes how MIDACS will operate as an element of the EOS within the EosDIS environment. This version of the Level 2 Requirements Document follows an earlier release of a preliminary draft version. The sections on functional and performance requirements do not yet fully represent the requirements of the data system needed to achieve the scientific objectives of the MODIS instruments and science teams. Indeed, the team members have not yet been selected and the team has not yet been formed; however, it has been possible to identify many relevant requirements based on the present concept of EosDIS and through interviews and meetings with key members of the scientific community. These requirements have been grouped by functional component of the data system, and by function within each component. These requirements have been merged with the complete set of Level 1 and Level 2 context diagrams, data flow diagrams, and data dictionary

Geobase Information System Impacts on Space Image Formats

As Geobase Information Systems increase in number, size and complexity, the format compatability of satellite remote sensing data becomes increasingly more important. Because of the vast and continually increasing quantity of data available from remote sensing systems the utility of these data is increasingly dependent on the degree to which their formats facilitate, or hinder, their incorporation into Geobase Information Systems. To merge satellite data into a geobase system requires that they both have a compatible geographic referencing system. Greater acceptance of satellite data by the user community will be facilitated if the data are in a form which most readily corresponds to existing geobase data structures. The conference addressed a number of specific topics and made recommendations