with hard numbers and thresholds.
1.Tobler, W. 1970. “A Computer Movie Simulating Urban Growth in the Detroit Region.” Economic Geography 46 (2): 234–40.
| Lesson 2 | Preview the data |
YOU NEED THE RIGHT DATA to solve the problem of where to locate a park. You explored the study area in lesson 1. Now you can proceed more systematically. What data do you have? How useful is it? Is there data that you need but don’t have? Has the problem been stated clearly enough for you to know what data you need?
Acquiring, evaluating, and organizing data is a big part of an analysis project. This book doesn’t fully re-create the complexity of the real world, because all the basic data required is provided. But much of the data isn’t project-ready, and that need for further preparation reflects the real world of GIS.
The first thing you’ll do in this lesson is draw up a planning document to help keep your tasks in focus. You’ll use this document to list the guidelines for the new park and translate them into specific needs for spatial and attribute data.
After you itemize your data requirements in general terms (park data, river data, and so on), you’ll take stock of your source data and investigate its spatial and attribute properties. You’ll also familiarize yourself with metadata, which is the data you have about your data. Before you decide to use a particular dataset, you may want to know things such as who made the data, when, and to what standard of accuracy.
Once you have a better working knowledge of your data, you’ll reframe the problem statement. GIS is a quantitative technology: you can’t analyze a problem until it’s been stated in measurable terms. Wherever you find the city council’s guidelines to be vague, you’ll replace them with hard numbers.
Exercise 2a: List the data requirements
You must relate the guidelines for the new park to data requirements for the project.
Open the data requirements table
A table has been made in advance to help you keep track of your requirements. It’s an informal document, but it will still be helpful. You can refer to it as the data requirements table.
1)Open Windows Explorer and navigate to C:\EsriPress\UGIS4\ParkSite\MapsAndMore.
2)Double-click the file DataRequirementsTable.doc to open it in Microsoft® Word.
List the requirements
In this section, you’ll review the city council’s guidelines (refer to “Park guidelines” in lesson 1, under “Frame the problem”) and describe in a general way the data needed to satisfy them. The specifics of choosing datasets are presented in lesson 3.
The first guideline was to find a vacant piece of land at least one-quarter acre in size. You can break this down into three requirements:
•Land parcel
•Vacancy
•Size
The requirement for a land parcel is already listed in the table. You need spatial data representing parcels so that you can see candidate sites on the map.
The second requirement is vacancy, which is a characteristic, or attribute, of a parcel. In a GIS dataset, vacancy is often listed with other descriptions of land use (commercial, residential, industrial, and so on). In general terms then, you’re looking for a land-use attribute.
1)In row 2 of the table, under Attribute Data, type (or write) land use.
The third requirement is that the park be one-quarter acre or larger. Like vacancy, acreage is an attribute, although it is one that can be calculated by the software. Because ArcGIS Pro can convert one unit of area to another, you don’t even have to start with acres—any measurement of parcel size will suffice.
2)In row 3, under Requirement, type a quarter acre or more. Under Attribute Data, enter area.
The second guideline under “Park guidelines” is that the park be within the Los Angeles city limits. This sounds like spatial data, and you’ll treat it that way for now. (It could be an attribute, too, because a field in a table might store the name of the city in which each parcel is recorded.)
3)Fill in row 4 as you think it should look, and then check the figure.
The third guideline is that the park be as close as possible to the Los Angeles River.
4)In row 5, for the requirement, put near LA River. Under Spatial Data, put rivers.
Using spatial datasets of parcels and rivers, you can measure the distance from any given parcel to the river.
The fourth guideline is to locate the park not in the vicinity of another park, or away from existing parks.
5)Fill out row 6 as you think it should look.
The fifth guideline also needs to be broken down. You need a neighborhood (spatial data) that has the following:
•high population density (attribute data) and
•lots of children (attribute data).
Neighborhoods tend not to have formal boundaries, so you’re probably not going to find them as such in a spatial dataset. As a proxy, or substitute, you’ll use a set of small, standardized areas defined by the US Census Bureau: either the tracts or block groups you looked at in lesson 1.
6)In row 7, enter in a neighborhood as the requirement. Enter census unit for the spatial data.
7)In row 8, enter densely populated for the requirement and population density for the attribute data.
8)In row 9, enter lots of kids for the requirement. For the attribute data, enter age.
The sixth guideline is that the park be in a lower-income neighborhood. You don’t need to repeat the spatial requirement for a neighborhood from step 6.
9)In row 10, enter lower income for the requirement and income for the attribute data.
The last park
