Ryan Miller3/5/2008(12/14)Lab #4Part 11. Do the points and lines represent the data with the same level of abstraction? Discuss in terms of their representation of the two data layers (cities, roads) that we have added so far, and in terms of other types of data that they might represent.Both points and lines can be used to label discrete data vector data. In this lab, points are used to identify cities, while lines are used to define state boundaries and major road ways. Otherdata types that lines may represent are: cartographic or contour data, rivers, and boundaries. Points represent a discrete spatial location like a city on a map.Also the polygon is collection of lines, represents an area; one of the example is national boundaries2. What happens when you use the identify tool? Is the option to change the layer(s) being identified useful? The identify tool allows the user to retrieve information about features in the data frame of ArcGIS. By simply clicking on a given area within the active data frame, the user can identify itsfeatures and display its attributes. Depending on the viewing perspective of the data, when using the identify tool, the user may select more than one feature. If all data layers are active, the identify tool will identify all features within the area being selected. The option to change the layers that are being identified is useful because it allows the user to only work with data within a certain layer.3. Why do you think the Field Definition requires that you differentiate between text and numeric data types? Why do you need to specify the field width?There must be a differentiation between numerical and text data types because text data only includes alphabetical characters (i.e. abcd...) rather than only numeric characters (i.e. 1234). Thewidth must be specified so that a one-to-one match can be made between the new weather data and the existing names within the attribute table on the “states” layer. If there is not an exact match between the two data sets, the data cannot be joined properly. So if the width is set too short, the entirety of a state name may not be included.4. What has changed in the table after joining?After joining the weather.dbf file to the attribute table of the “states” layer, all of the information from the weather.dbf file has now been added to the attribute table of the “states” layer. So, the states with their associated weather conditions created in the weather.dbf file were added to the “states” layer.5. How is the original attribute data from the States layer distinguished from the Weather data that you joined?The new attribute data is distinguished from the original attribute data in that the new data now occupies two separate data fields within the original table. So within that field it states associated weather condition for the 10 state names that had been previously selected and for the states that do not have a designated weather condition, the table simply states <null>.6. What would happen if you tried to join the attributes from the States layer to the Weather data (rather than joining the Weather data to the States data as you just did)? The join would be unsuccessful primarily because you would be trying to join spatial data to numerical data. As well, another reason that it would not succeed is that the weather data table only includes records for ten states. Since the state data table includes information for all fifty states, had the state data table been joined to the weather data table, all information of the remaining forty would have been lost. Print Screen of Selected RecordPrint Screen of New Attribute TablePart 21. What does the reclassification step in Step 1 accomplish?The reclassification step allows the user to make ArcGIS reinterpret the data so that it can better reflect what the user wants. In doing so, the user in this step is able to tell ArcGis to assign new values to the different distances. High scores = close to roads.2. At the end of Step 3, what does the map tell you in terms of the developer’s office building project? What do the highest scores represent? What do the lowest scores represent? Step 3 allows the user to combine all of the data that had been yielded in the previous analyses into one map. The company wishing to construct their new office building can now easily see the areas that are best suitable for construction with respect to the combined road and stream proximity suitability scores. The combined suitability scores reflect the best area for construction. On the map, the highest numbers reflect the best areas for construction while conversely; the lowest numbers represent areas that should be avoided.3. What does Step 4 accomplish towards producing the final suitability data layer?Step 4 allows the user to not take into consideration suitability scores based upon stream and road proximity but also the areas of the city that are zoned for and allow the construction of an office building. In doing so, the suitability map has been further refined and now provides an even more client specific end product. Had this step not been completed, the client would have issues finding an appropriate location for her office building since there would be no distinction between areas suitable and not suitablefor her office.4. Prepare a brief executive summary (~2 paragraphs) to the developer, summarizing your results. Include a short description of the analysis you performed and indicate the locationsyou think would be the best choices for her office project. The goal of this assessment was to determine the suitability of land areas within Chapel Hill, NC for the construction of a large commercial office building. Using data provided by the Geography department at the University of North Carolina Chapel Hill and their ArcGIS capabilities, two suitability analyses were performed to determine the most appropriate location to construct the office building as per the instructions of the owner. This analysis took into account proximity to main roads within the municipality and local area hydrology. Since the owner specified that his office building be constructed close to existing roads and avoid areas near local streams, the results from both analyses were joined to best represent the areas that demonstrate both characteristics. Lastly, to take into account the local zoning practices, a layer containing the current zoning areas of Chapel Hill was combined with