Physical and Space Geodesy - Essay Example

Space geodesy is also known as satellite geodesy. Point positioning is a major application that accurately determines the coordinates of points in space, land, and sea. The locations of points are determined by linking measurements of known points with terrestrial positions that are not known. It may include transformation between astronomical C.S and terrestrial C.S. Use of GPS satellites, triangulation, and other satellite geodesy are used for the known points positioning. The satellite geodesy is relevant in inter-satellite tracking. Space geodesy determines the positions of points, both relatively and absolutely. Space geodesy, currently, has been formed to provide abundant and accurate geodetic data than the classical systems.

Satellite geodesy helps in the determination of precise local or regional geodetic control, earth’s gravitational pull determination, and modeling and measurement of geodynamic phenomenon. Geodynamic phenomena include polar motion, crustal deformation, and the earth’s rotation. Space geodesy consists of observation and computational techniques which allow for solutions above geodetic problems by precise measurements to or from artificial satellites.

1. Geometrical geodesy

This is the geodesy aspect that strictly concerns geometrical relationships of the earth’s surface. The earth’s surface is measured in different ways, such as triangulation, electronic surveys, and trilateration for the purpose of determining the shape, size of the earth, and the precise location of points on the surface of the earth. Geometric geodesy is a science that considers the geoid by the use of the astrogeodetic method.

Question2

1. The Characteristics of Spatial Data Errors

Most of the spatial data errors are processing errors: Numerical errors, cascading errors, topological errors, digitizing, and geocoding errors. Processing errors are those errors that are introduced during digitizing and processing. For example, the conversion of data from raster to vector may introduce distortions. These errors occur in several ways in the data that undergo manipulation.

1. Numerical errors exist when different computers produce significantly different results for the same problem. These errors are a result of the different capabilities of computers to perform complex math operations. Computer processing discrepancies occur in rounding off operations and are subject to the inherent limits of number manipulation in the faulty processors. Accurate conversion of existing maps to digital form is a major challenge. Numerical errors in processing can lead to inaccurate results since computers must manipulate data in digital format.
2. Errors in topological analysis occur as a result of poor connectivity, adjacency, and containment. They are characterized by non-uniform data which causes variations. The multiple map overlay may result in problems such as sliver polygons, dangles, overshoots, and undershoots. Accuracy variations in different map layers may be noticed during processing leading to the virtual data creation which may be difficult to detect from real data.
3. Digitizing and geocoding errors occur at geocoding, digitizing, boundary intersection, overlay, and errors from raster to vector conversion.
4. Other errors in the spatial analysis may be a result of physiological variations. The operator may experience involuntary muscle contraction that may result in spikes, polygon knots, loops, and switchbacks.
5. Damaged maps may cause errors while digitizing. They may be also regarded as operator errors while digitizing. Any record of biases can be checked by comparing the digitized version and the original version.
6. Errors as a result of the data collection include; errors of remote sensing data acquisition, errors in source maps data, and field data acquisition errors.
7. Components of Spatial Data Uncertainty in Risk Analysis

Uncertainties exist in geographical data components which include; location attributes, spatial dependence attributes, and typological attributes. Recognition of the mentioned forms of uncertainty is very vital since it is employed in risk assessment and analysis. Policymakers also use the analysis to support their decisions regarding policies. Geographic data are often assumed to be error-free after the consideration of all uncertainties. The components of spatial uncertainties that we should consider are data precision, accuracy, completeness, consistency, accuracy/error, lineage, currency, currency, credibility, subjectivity, and interrelatedness. The above categories of uncertainty can be matched to time, space, and attribute composition of data to show the typology of other uncertainties.

1. Accuracy/error: accuracy and error define the difference between the actual measurements and the observation of measurements based on estimation device and procedure.
2. Completeness: perform risk analysis by checking the degree of information comprehensiveness.
3. Precision: this is the exactness of the information. Precision is derived from the estimation device and parameters of measurements.
4. Consistency: is the extent of agreement of data or information components. The data that is obtained from the process of spatial analysis should be consistent for uniformity.
5. Subjectivity: this is the range in which mans’ interpretation and judgment are taking part in information extraction. It is a component of uncertainty that is difficult to assess and will have some level of subjectivity.
6. Credibility: use of sources that are reliable, based on experience, motivation, percentage of correctness, and other factors.
7. Interrelatedness: involves sources that are not dependent on other information. Used when the story is authentic and does not need other clarifications.
8. Currency: this is the information or the data justification of risk analysis depending on both the time span and context that the information was obtained.