100m wide on 1100000 Estimates show that 10 of a 124000 soil map may represent

100m wide on 1100000 estimates show that 10 of a

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100m wide on 1:100000 Estimates show that 10% of a 1:24000 soil map may represent the boundary lines alone Digital Representation Curves are approximated by many vertices Boundaries are not absolute, but should have a confidence interval
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Data quality DATA OUTPUT GIS data can be presented as maps or charts, which can either be in hard copy or soft copy. Charts can be used to represent graphical data. Examples of graphs include line, bar, area, column, pie. Maps are representation, normally to scale and on a flat medium, of a selection of material or abstract features on, or in relation to, the surface of the earth. Some examples of types of maps include: i. Planimetric -A map designed to portray the horizontal positions of features; vertical information is specifically ignored.
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Data quality DATA OUTPUT ii. Topographic - A map designed to portray features on the surface of the Earth, including relief (elevation).
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Data quality DATA OUTPUT iii. Cadastral - A map representing boundaries of land parcels, ownership, land use, valuation, and other related information.
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Data quality DATA OUTPUT iv. Thematic -A map used to visualize spatial relationships and patterns among information pertaining to some theme or concept. Examples of thematic maps soil map, hotspots for crime map, water pipes map etc.
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Data quality Key for a successful GIS 1. Data input : garbage in garbage out 2. Database maintenance : This appertains to data quality and routinely updating the system. Hardware, software and the data will require periodic updates. 3. Consensus of supporters: The top managers as well as other members of the organization should support the GIS project. 4. Data sharing: This minimizes the cost of GIS project 5. Education and training: This promote understanding of the GIS concept, goals and techniques.
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Data quality Reasons for an unsuccessful GIS 1. Lack of vision: Top management should have a vision for GIS to be set. This involves setting targets, goals and objectives. 2. Lack of long term plans : , there is need for long term planning. Provisions must be made for maintenance of large and complex data which will increase with time. Hardware and software updates must also be planned for. 3. Lack of system and information analysis: There is need to perform system and information analysis prior to implementing GIS. These clarifies the appropriate hardware and software requirements, identifies possible areas of duplication of information flow, storage specifications and computer capabilities that is the speed and memory. 4. Lack of expertise: During the planning and system analysis stage, there is always need to employ the services of a consultant or GIS expert. 5. Lack of support by decision makers: Conflicting interests among the decision makers as to who controls what data, who is supposed to access what data etc. may hamper the smooth running of the project.
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