How consistent are the relationships among the observations, including topology?
Compliance with the accuracy standard was ensured by the collection of photo identifiable GPS ground control before and after the acquisition of aerial imagery. The following checks were performed. 1. The ground control and airborne GPS data stream were validated through a fully analytical bundle aerotriangulation adjustment. 2. The lidar-derived DEM surface from the North Carolina Floodplain Mapping Program was used in ortho rectification. 3. Digital orthophotography was validated through an inspection of edge matching and visual inspection for image quality. 4. Planimetry was validated through an inspection of edge matching and visual inspection for data quality.
Every polygon has a single label point and all polygons are closed. The same lithologic unit may extend across a state line but have different formation names in different states. Discrepancies at state borders. Compilation of the lithogeochemical data layer using state geologic maps also resulted in some discontinuities at state borders. The lithogeochemical unit assigned to a bedrock unit was based primarily on its description on the appropriate state geologic map. Because the information contained on the individual state maps was interpreted and assembled by different groups of geologists, the compiled data set is not always internally consistent. In addition, the state map descriptions have generalized the chemical and mineral-assemblage characteristics of the bedrock units and formations across the different states; thus, regional trends in lithology or metamorphic grade may have resulted in different generalized descriptions of the same geologic unit in adjacent states.
The responsibility for the NURE HSSR program was given to four U.S. Dept. of Energy Laboratories. Each lab was assigned a region of the United States and given the authority to develop their own collection, analytical, and data management methodologies. This decision resulted in the creation of several different sample collection manuals, preprinted sample collection note forms, analytical methods, and data report formats. Thus there is a large amount of inconsistency in reported data between laboratories; especially in the site and sample description fields. Program changes over time also introduced additional inconsistencies, even within data reports from a single laboratory. One of the primary goals of this reformatting effort has been the elimination of as many inconsistencies as possible. These problems with consistency fall into at least 7 categories. The following describes each category of consistency problem and the formatting process used to resolve the issue. Many database f
The sampling design for this study was not statistically based; rather, sites were chosen to provide data on dust influx at soil- study sites and to answer specific questions about the relations of dust to local source lithology and type, distance from source, and climate. Some sites were chosen for their proximity to potential dust sources of different lithologic composition (for example, playas versus granitic, calcic, or mafic alluvial fans). Other sites were placed along transects crossing topographic barriers downwind from a dust source. These transects include sites east of Tonopah (43-46) crossing the rhyolitic Kawich Range, sites downwind of northern (40, 35, 36) and central Death Valley ( 38, 39, 11-14) crossing the mixed-lithology Grapevine and Funeral Mountains, respectively, and sites downwind of Desert Dry Lake crossing the calcareous Sheep Range (47-50) north of Las Vegas. In addition, some sites were chosen for their proximity to weather stations. Specific locations for
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