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Automated information extraction procedures for analysis of multitemporal LANDSAT data in non-U.S. crop inventory and monitoring are reviewed. Experiments to develope and evaluate crop area estimation technologies for spring small grains, summer crops, corn, and soybeans are discussed.
Automated information extraction procedures for analysis of multitemporal Landsat data in non-U.S. crop inventory and monitoring are reviewed. Experiments to develop and evaluate crop area estimation technologies for spring small grains, summer crops, corn, and soybeans are discussed. Previously announced in STAR as N82-32793
An inventory scheme based on the use of computer processed LANDSAT MSS data was developed. Output from the inventory scheme provides an estimate of the standing net saw timber volume of a major timber species on a selected forested area of the Navajo Nation. Such estimates are based on the values of parameters currently used for scaled sawlog conversion to mill output. The multistage variable probability sampling appears capable of producing estimates which compare favorably with those produced using conventional techniques. In addition, the reduction in time, manpower, and overall costs lend it to numerous applications.
Regional planning agencies are currently expressing a need for detailed land cover/use information to effectively meet the requirements of various federal programs. Individual data sources have advantages and limitations in fulfilling this need, both in terms of time/cost and technological capability. A methodology has been developed to merge land cover/use data from LANDSAT, aerial photography and map sources to maximize the effective use of a variety of data sources in the provision of an integrated information system for regional analysis. A test of the proposed inventory method is currently under way in four central Michigan townships. This test will evaluate the compatibility, accuracy and cost of the integrated method with reference to inventories developed from a single data source, and determine both the technological feasibility and analytical potential of such a system.
NASA's Earth Observing System Data and Information System (EOSDIS) has been a central component of NASA Earth observation program for over 10 years. It is one of the largest civilian science information system in the US, performing ingest, archive and distribution of over 3 terabytes of data per day much of which is from NASA s flagship missions Terra, Aqua and Aura. The system supports a variety of science disciplines including polar processes, land cover change, radiation budget, and most especially global climate change. The EOSDIS data centers, collocated with centers of science discipline expertise, archive and distribute standard data products produced by science investigator-led processing systems. Key to the success of EOSDIS is the concept of core versus community requirements. EOSDIS supports a core set of services to meet specific NASA needs and relies on community-developed services to meet specific user needs. EOSDIS offers a metadata registry, ECHO (Earth Observing System Clearinghouse), through which the scientific community can easily discover and exchange NASA s Earth science data and services. Users can search, manage, and access the contents of ECHO s registries (data and services) through user-developed and community-tailored interfaces or clients. The ECHO framework has become the primary access point for cross-Data Center search-and-order of EOSDIS and other Earth Science data holdings archived at the EOSDIS data centers. ECHO s Warehouse Inventory Search Tool (WIST) is the primary web-based client for discovering and ordering cross-discipline data from the EOSDIS data centers. The architecture of the EOSDIS provides a platform for the publication, discovery, understanding and access to NASA s Earth Observation resources and allows for easy integration of new datasets. The EOSDIS also has developed several methods for incorporating socioeconomic data into its data collection. Over the years, we have developed several methods for determining needs of the user community including use of the American Customer Satisfaction Index and a broad metrics program.
The author has identified the following significant results. A current uniform land inventory was derived, in part, from LANDSAT data. The State has the ability to convert processed land information from LANDSAT to Ohio Capability Analysis Program (OCAP). The OCAP is a computer information and mapping system comprised of various programs used to digitally store, analyze, and display land capability information. More accurate processing of LANDSAT data could lead to reasonably accurate, useful land allocations models. It was feasible to use LANDSAT data to investigate minerals, pollution, land use, and resource inventory.
Statistical methods for inventory boundary determination and data compression in automatic processing of multispectral scanner remote sensor earth observations from aircraft and spacecraft
The author has identified the following significant results. Segerstrom delineated many grabens (down-faulted blocks) not shown on published maps of Argentina nor of South America. The faults that border the grabens are better appreciated in ERTS-1 imagery than on air photos or on the ground because of the masking affect of alluvial fill deposits. In frame no. 1188-13545 a change in local prevailing wind direction from east to southeast is noted in sand streams. In frame no. 1188-13551 it was surprising to see that Solar del Hombre Muerto was covered with water. In November 1971 the investigator has driven across the salt pan several times without wetting his wheels. It was also possible to differentiate the following rock and soil classes: Granites, metamorphic, volcanic rocks, Tertiary and Quaternary clastic deposits and salt pans. Portions of railroads and highways as well as small towns were identified. In frame no. 1188-13551 the Incahuasi Gold Mine and the Tincalayu Borax Mine were located.
There are no author-identified significant results in this report.
The author has identified the following significant results. A color composite of image E1010-14035, dated 2 August 1972, covers the west central Bolivian Altiplano near Salar de Coipasa. It clearly shows the distribution of surface water and scant patches of vegetation. The Salar de Coipasa is the largest body of water in the area, about 130 sq km of dark blue fresh water. A lighter blue area south of the lake suggests a thin cover of highly saline water superposed on salt beds. The scattered vegetation patches are presumed to be native grasses, lichens, and possibly Indian potato and maiz areas. A detailed study has been made of the scene which provides 12 different interpretive overlays including geology, volcanology, soils, hydrology, and relative permeability. It was found that color composites provide at least 40% more information that do black and white renditions. An excellent example of change detection was provided by image E1244-14051, dated 24 March 1973. Water in the Salar de Coipasa had more than doubled as a result of the rains of the Bolivian winter, which generally occur in the February-March period. The Salars are excellent and highly sensitive moisture indicators in this highly arid region.
The geologic evolution of Mars is reviewed on the basis of data obtained by the Viking and previous missions. Current knowledge of the mean density and moment of inertia factor of Mars are surveyed and the constraints these data place on the structure and composition of the interior are discussed. Inferences drawn about Martian surface composition and mineralogy from lava modeling studies, in situ analyses, remote sensing observations, flow morphometry and investigations of weathering under Martian conditions are presented, and data on the topography, gravity field and structural features are considered in relation to the structure and deformational history of the crust. The temporal and spatial distribution of volcanic units are considered as a constraint on the thermal evolution of the planet, and other constraints on Martian thermal history, such as magnetic field data, are reviewed. Finally, the volatile inventory of Mars is discussed based on elemental and isotopic atmospheric abundance data and geological constraints on H2O and CO2 abundances.
Changes in classification detail of forest species descriptions were made for Landsat data on 2.2 million acres in northwestern California. Because basic forest canopy structures may exhibit very similar E-M energy reflectance patterns in different environmental regions, classification labels based on Landsat spectral signatures alone become very generalized when mapping large heterogeneous ecological regions. By adding a seven ecological zone stratification, a 167% improvement in classification detail was made over the results achieved without it. The seven zone stratification is a less costly alternative to the inclusion of complex collateral information, such as terrain data and soil type, into the Landsat data base when making inventories of areas greater than 500,000 acres.
Image products and numeric data were extracted from both TM and MSS data in an effort to evaluate the quality of these data for interpreting major agricultural resources and conditions in California's Central Valley. The utility of TM data appears excellent for meeting most of the inventory objectives of the agricultural resource specialist. These data should be extremely valuable for crop type and area proportion estimation, for updating agricultural land use survey maps at 1:24,000-scale and smaller, for field boundary definition, and for determining the size and location of individual farmsteads.
A multistage sampling technique, with probability proportional to size, for forest volume inventory using remote sensing data is developed and evaluated. The study area is located in the Southeastern Brazil. The LANDSAT 4 digital data of the study area are used in the first stage for automatic classification of reforested areas. Four classes of pine and eucalypt with different tree volumes are classified utilizing a maximum likelihood classification algorithm. Color infrared aerial photographs are utilized in the second stage of sampling. In the third state (ground level) the time volume of each class is determined. The total time volume of each class is expanded through a statistical procedure taking into account all the three stages of sampling. This procedure results in an accurate time volume estimate with a smaller number of aerial photographs and reduced time in field work.
A multistage sampling technique, with probability proportional to size, is developed for a forest volume inventory using remote sensing data. The LANDSAT data, Panchromatic aerial photographs, and field data are collected. Based on age and homogeneity, pine and eucalyptus classes are identified. Selection of tertiary sampling units is made through aerial photographs to minimize field work. The sampling errors for eucalyptus and pine ranged from 8.34 to 21.89 percent and from 7.18 to 8.60 percent, respectively.
Before county and local governments will utilize satellite data extensively for landcover inventories, digital image processing techniques must be developed to identify transitional land-use conditions and create large-scale, readable land-cover maps. This study examines a satellite-based land-cover inventory done for Schoharie County, New York and reviews the problems encountered in identifying and mapping brushland - a significant transitional land use - within the county and region. Brushland throughout the Northeast represents a barometer for measuring the shift away from agricultural land use to second-home property. Detecting and locating brushland on a regular basis can greatly assist county and local government officials in planning and managing a county's future.
Discussed are a variety of remotely sensed data sources that may have utility in the identification of conservation practices and related linear features. Test sites were evaluated in Alabama, Kansas, Mississippi, and Oklahoma using one or more of a variety of remotely sensed data sources, including color infrared photography (CIR), LANDSAT Thematic Mapper (TM) data, and aircraft-acquired Thermal Infrared Multispectral Scanner (TIMS) data. Both visual examination and computer-implemented enhancement procedures were used to identify conservation practices and other linear features. For the Kansas, Mississippi, and Oklahoma test sites, photo interpretations of CIR identified up to 24 of the 109 conservation practices from a matrix derived from the SCS National Handbook of Conservation Practices. The conservation practice matrix was modified to predict the possibility of identifying the 109 practices at various photographic scales based on the observed results as well as photo interpreter experience. Some practices were successfully identified in TM data through visual identification, but a number of existing practices were of such size and shape that the resolution of the TM could not detect them accurately. A series of computer-automated decorrelation and filtering procedures served to enhance the conservation practices in TM data with only fair success. However, features such as field boundaries, roads, water bodies, and the Urban/Ag interface were easily differentiated. Similar enhancement techniques applied to 5 and 10 meter TIMS data proved much more useful in delineating terraces, grass waterways, and drainage ditches as well as the features mentioned above, due partly to improved resolution and partly to thermally influenced moisture conditions. Spatially oriented data such as those derived from remotely sensed data offer some promise in the inventory and monitoring of conservation practices as well as in supplying parameter data for a variety of computer-implemented agricultural models.
The Material Safety Data Sheets (MSDSs) listed reflect product inventories and associated MSDSs which were submitted to the Toxic Substance Registry data base maintained by the Base Operations Contractors of the Biomedical Operations and Research Office of NASA Kennedy. The purpose of the index is to provide a means of accessing information on the hazards associated with the toxic and otherwise hazardous chemicals stored and used at NASA Kennedy. Indices are provided for manufacturers, trademarks, and stock numbers.