Lab 3: Data Formats and Models

1. A data model is a model constructed after abstraction decisions have been made. It is a model that describes and illustrates features of the actual world in a digital form. The two most commonly used data models are vector and raster data models. Vector data models are called discrete data models, they have distinct boundaries and are not continuous. Vector data models are made up of points, lines, and polygons. There are two types of vector data models: spaghetti and topological models. Raster data models are called pixelized data models that define features as a set of cells in a grid. Raster data models are good for processing multiple layers and probabilistic modeling.

2. Topology is the process of establishing proper relationships between the lines, points, and polygons that have been drawn. Topology is important because it ensures proper relationships between features such that all features on the map have the correct connectivity, area definitions, and contiguity. Once these relationships are properly established, the model can be bent and still have the same connectivity and adjacency. Additionally, topology is important because it results in more accurate analyses due to a better resolution of linear and point features.

3. The best type of data model for representing hillside slope would be a raster data model using continuous data. The data model would be able to show a gradual change in elevation between the grid cells. A vector data model would make it seem that the hill is made up of discrete steps of different elevations because there are discrete boundaries in vector data models. Additionally, it is more efficient to use a raster data model for elevation.

4. If the grid cell is very large then it has less resolution. For instance, a 30 m grid cell will not very accurately represent a 15-m wide river because it will double the size of the river. To avoid this you could either use a vector data model, or use small grid cells in order to increase the resolution of the raster data model.

5. Four types of attribute data include: nominal, ordinal, interval, and ratio. Norminal attribute data is categorical data, such as the name of a city. Ordinal attribute data is ranked data, for instance the rank of cities in terms of cleanliness. Interval data is data that is related to an arbitrarily chosen zero value, such as temperature in Celsius. Finally, ratio data is all other types of quantitative data with reference to an absolute zero, such as elevation data.

6. Two types of vector data file formats are shapefile (.shp, .shx) and interchange files (.eOO).

7. Two types of raster data file formats are Imagine (.img) and GeoTIFF (.TIF) files.

8. C. select features

9. The World.mdb geodatabase contains four feature classes

10. The names of the feature classes are cities, countries, disapp_area, and world30

11. The layer file called flight_diver ge depends on a spatial dataset called the flight_diverge shapefile.

12. One way to add data to an ArcMap document is to drag the file from the ArcCatalog view to the ArcMap display window and release the mouse button. Another way is to go to the file menu and select add data from the drop down menu (or select the add data button on the toolbar).

13.