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Exam 2 Short Answer Essay Questions (33 points)
Please answer the following questions in a new document. Proof for spelling and grammar errors and submit through the DropBox set up on eCompanion. The essays are due on Tuesday, November 3, 2009 before the start of our class (7:00 pm).
1. How does organization of hierarchical data files differ from the organization of relational data files? (3 points)
Hierarchical data files are grouped in a strict structural way as parent-children (or subordinated elements). One field is designated as the key field, and it is used to organize the hierarchy. The top of hierarchy is the root, comprised of one entity. There is very strong organizational structure based on relationship and leader position of data files. Relational files are flexible and data can be shared by any files.
2. What is the difference between precision and accuracy in GIS? (2 points)
Accuracy = how well data connects with true value. Accuracy is a degree to which a measurement approximates the true value of the object being measured (Glossary).
Precision refers to the level of measurement.
3. What is a УspuriousФ or УsliverФ polygon in GIS? How is it created in a spatial database and how can it be corrected (or eliminated)? (2 points)
A УspuriousФ or УsliverФ polygon is a very small polygon or gap between two lines created erroneously. Spurious polygons can be created by the overlay two parent lines when two lines are overlaid which are actually slightly different versions of the same line, or during polygon overlay when many new smaller polygons can be created, some of which may not represent true spatial variations. Spurious or sliver polygons are a major problem in polygon overlay and the problem cannot be removed by more careful digitizing. Wrong polygons can be corrected or eliminated only by special program tools. Some GISs allow the user to set a tolerance value for deleting spurious polygons during overlay operations. But there are several problems also. If the tolerance is set too high, some legitimate polygons may be deleted. If the tolerance is set too low, some erroneous polygons will be not deleted. Some deletion rules can be based on shape because spurious polygons mostly are long and thin.
4. What is УmetadataФ and why is it important to GIS? (3 points)
Metadata is "data about data" that provides documentation of spatial data, describing content, quality, condition, and other characteristics of a data set. Any item in ArcCatalog have metadata, and we can use the metadata conversion tools to validate the metadata content.
Metadata is important to GIS because it makes spatial information more useful to all types of users. The growing availability of data of all kinds from different sources has helped GIS become widely adopted. Metadata is important when sharing tools, data, and maps. With metadata, data producers publish information about data, and data consumers search for the data they need. Once we''ve found a resource with a search, its metadata will help us decide whether it''s suitable for our purposes. To make this decision, we need to know how accurate or current the resource is and how it can be used. Metadata also answers these questions.
5. How does СdataТ differ from СinformationТ? (2 points)
Data is items of facts (raw facts), collected for examination that can be stored and collected by a computer. Information is a processed data, a set of values as a set of data that has been processed into meaningful form. Data can be thought of as measurements, but information is what those measurements mean. УData" is defined as a body of facts or figures, which have been gathered systematically for one or more specific purposes. Data that make useful information for one person may not be useful to another person. Information is only useful to when it is relevant (to its intended purposes and with appropriate level of required detail), reliable, accurate and verifiable (by independent means), up-to-date and timely (depending on purposes), complete (in terms of attribute, spatial and temporal coverage), intelligible (i.e. comprehensible by its recipients), consistent (with other sources of information), and convenient/easy to handle and adequately protected.
6. Why are information systems more data-oriented today than ђtechnology-oriented? (3 points)
Information systems have 4 elements: data, technology, application, and operators. Information systems are most data-oriented today than technology-oriented because of the 4 elements date are the most stable, and technology is constantly evolving. Data are also the most expensive element, and collecting of data may count 50% of project price and data can be a corporate resource. A data-oriented approach to information system is characterized by managing data as a valuable corporate resource in the same way financial, technical and human resources are managed and it is the concept of information resource management (IRM).
7. What does Сnormalize the dataТ mean in GIS? What is GIS (ArcView) doing to the data? (3 points)
To do an effective map, it is a good idea to normalize the data. Normalized data is also very useful when not creating height values and the colors of areas are driven by statistics that represent counts. Normalized data is good for census data maps. Normalization usually divides a database into two or more tables and defines relationships between the tables.
Also normalization of data means an attribute is expressed as a percentage of the total of the attribute. The values are divided in the classification field by the value in the normalize field or the sum of the values in the normalize field .
8. List the steps necessary to add a field to an existing attribute table in ArcView (2 points)
We need to open the Attribute Table for the layer we want to work. In Attribute table we will select the Option tab and in the new context menu pops up select Add Field. Completing the dialog box and clicking OK, we will add the new field to the layer.
9. How would the incorporation of slope and aspect (from a DEM) and hydrologic information (such as drainage divides and stream networks) into a GIS assist a resource manager? (3 points)
It can give a field view as a concept that the geographic features are represented as surface, regions, or segments in the raster methods of GIS. Raster data model.
10. What is the function of a ''neatline'' on a map? How do you place a ''neatline'' on a map in ArcGIS? (2 pts)
The neatline of a map refers to its frame or border. In geographic data processing, the neatline serves to define the extent of the digital data.
How to do a place of ''neatline'' on a map in ArcGIS: use Insert Ц Neatline and click Place Inside Margins to add a neatline to the map. If you want to add neatlines to individual map elements, use the Frames tab on the Properties form for the element. You can add a neatline around all the graphics using the Neatline tool in the Frame tab the Legend Properties dialog box.
11. How do you add a "legend" to a map in ArcGIS? What are the editing options available in the ArcGIS "Legend" Properties? (3 pts)
Click Legend in the Insert menu. To make modifications and edit it, double click on the legend itself and bring up the Legend Properties dialog box.
12. List and describe how data can be symbolized in ArcView. Include in your discussion, the advantages and disadvantages of each type of symbology, as well as the kind of data (i.e., nominal, ordinal, interval, etc) that works best for each symbology and legend type. Indicate also if the symbology type is specific to СpolygonТ, СarcТ, or СpointТ data. (5 points)
We can symbolize point data, line data, and polygon data. Using Layer property Ц symbology tab setting, we can create different thematic maps or cartograms. These modifications will change color, size, or shape depending on the type of data with which youТre working. We can use dot density, graduated symbols, create own symbology, represent quantity using colors or create chart maps.
There are several ways to symbolize data on a map; the effectiveness of different ways depends on both the purpose of the map and the type of data we are dealing with. Discrete data is a variable in separate categories (property ownership, etc.) Continuous data with a distinct range ( population, temperature, etc) Ц through graduated colors, graduated or proportion symbols, dot density. By clicking on the background button we can change the color of the area behind the chart. Using the color scheme window we can change the color palette. The СsizeТ button allows us control how big the chart is.
