This guide was created by the staff of the GIS/Data Center at Rice University and is to be used for individual educational purposes only. The steps outlined in this guide require access to ArcGIS Pro software and data that is available both online and at Fondren Library. |
The following text styles are used throughout the guide: Explanatory text appears in a regular font.
Folder and file names are in italics. Names of Programs, Windows, Panes, Views, or Buttons are Capitalized. 'Names of windows or entry fields are in single quotation marks.' "Text to be typed appears in double quotation marks." |
The following step-by-step instructions and screenshots are based on the Windows 7 operating system with the Windows Classic desktop theme and ArcGIS Pro 2.1.3 software. If your personal system configuration varies, you may experience minor differences from the instructions and screenshots. |
Before beginning the tutorial, you will copy all of the required tutorial data onto your Desktop. Option 1 is best if you are completing this tutorial in one of our short courses or from the GIS/Data Center and Option 2 is best if you are completing the tutorial from your own computer.
If you are completing this tutorial from a public computer in Fondren Library and are logged on using the gistrain profile, follow the instructions below:
If you are completing this tutorial from a personal computer, you will need to download the tutorial data online by following the instructions below:
Geoprocessing tools are used to update and analyze data based on particular criteria. The majority of geoprocessing tools generate a new feature class that differs from the input feature class(s) either in feature geometry or tabular attributes or both. In this tutorial you will use geoprocessing tools to generate information that could be used for a collaboration between the Houston Police Department (HPD) and the Houston Independent School District (HISD).
The first set of data you will be working with contains the HPD beat boundaries. Though it has been modified for the purposes of this tutorial, the original data was obtained from the City of Houston GIS Database webpage, which is no longer available, but the original data can still be obtained from the GIS/Data Center data collection.
Notice that the police beats in the City of Houston have been divided into two separate feature classes covering the northern and southern portions of the city respectively. You will now examine their attribute tables.
Notice that you are provided with both the beat number and the district number for each police beat, and there are 55 beats in the north layer.
Notice that the south layer contains 62 beats with the same data fields.
At this point, you wish to combine the north and south police beats into a single layer. You will do so using a geoprocessing tool.
Notice that the Geoprocessing pane has opened on the right as a new tab on top of the Catalog pane. Typically, you would use the 'Find Tools' search box at the top of the Geoprocessing pane to search for the name of the tool you'd like to use, but, at times, especially when learning the software, it can be helpful to view the full hierarchy of all the tools available, because you will often discover related and helpful tools that you didn't know existed and wouldn't know to search for. You might also completely forget the name of a tool, but be able to locate it based on the hierarchy. For these reasons, we will be manually navigating the toolboxes throughout this tutorial. The more typical workflow of searching directly for a specific tool will be covered briefly at the end of the tutorial.
Read the pop-up Merge tool help and review the sample illustration. Notice that this tool merges two like datasets covering different geographic extents together into a single dataset. Clicking on, rather than hovering over, the help button will open the full tool documentation in your default web browser.
After selecting the HPDBeats_South layer, another drop-down menu appears.
Notice that the when you hover over the 'Output Dataset' field, the file path location defaults to your project geodatabase (C:\Users\gistrain\Desktop\Geoprocessing\Geoprocessing.gdb).
When the tool is finished running, you will see a message at the bottom of the Geoprocessing pane with the name of the tool. A green checkmark indicates that the tool ran successfully.
Scroll down the attribute table and notice that the attributes for both the north and south beats feature classes were preserved and combined into a single table with 117 beats. Since you now have all the beats contained in a single layer, you no longer need the separate layers for the north and south beats.
Imagine that HPD would like to manage this collaboration based on police district boundaries instead of police beat boundaries. At this point, your HPD layer only displays the police beat boundaries, but its attribute table does tell you the district number corresponding to each beat.
Notice that each district contains many beats. You will now dissolve the police beats based on this District field so that all individual beat boundaries within a single district will be dissolved into a single unified district boundary.
Read the pop-up Dissolve tool help and review the sample illustration. Notice that this tool dissolves boundaries based on common field values. In this case, you will dissolve the police beat boundaries based on common district values, resulting in a file showing only the larger district boundaries.
Notice that only the dissolve field, in this case the District field, was preserved. Because multiple beats were dissolved into each district, it is not possible to retain all of the attributes of each separate beat.
Since you only need to use the police districts, you may now remove the police beats layer.
Now you will examine the school district boundaries. Though it has been modified for the purposes of this tutorial, the original data was also obtained online from the City of Houston GIS Database webpage, but can now be obtained from the GIS/Data Center data collection.
Notice that this feature class displays the boundary of the Houston Independent School District, which can be considered the study area boundary for this project. All of the other data layers you bring into your map document can be clipped to the study area boundary to reduce the size of the files you are working with, which will eliminate visual clutter and allow various processes to run more quickly. First, you will clip the police districts to the study area boundary.
Read the pop-up Clip tool help and review the sample illustration. Notice that this tool clips one dataset to the extent, or shape, of another dataset.
Notice that the resulting HPDDistricts_HISD layer maintains the police district boundaries, but limits the extent of the districts to the extent of the HISD boundary. You no longer need the full extent police districts layer and may remove it.
You will now work with a dataset containing the locations of all violent crimes (including murder, rape, aggravated assault, and robbery) occurring in 2010, as reported by HPD. Though the data has been pre-processed for this tutorial, the original data tables can be obtained online from the Houston Police Department Crime Statistics webpage at https://www.houstontx.gov/police/cs/crime-stats-archives.htm.
The crime layer may take a while to load and appear in the map view. You will now clip the crime layer to the study area boundary to reduce the size of the dataset.
Notice that the Geoprocessing pane always displays the parameters of the last tool that you ran. Since you want to run the clip tool a second time and will be clipping to the same HISD extent as in the previous run, it is quicker to modify the existing parameters than to click the back arrow and launch the clip tool again from scratch.
Even though the clip process itself will only take a few seconds, it may again take a couple minutes for the new layer to display on the map view.
Notice that you are provided with the date and hour of the crime, the type of offense, the premise code, the number of offenses, and the approximate address. Since crimes are actually only reported by the block address range, not the exact street address, this address represents the midpoint of the block on which the crime was reported.
The final dataset you will work with contains the locations of all the elementary schools in HISD. Though it has been modified for the purposes of this tutorial, the original data can be obtained online from the Texas Education Agency School District Locator Data Download webpage at http://schoolsdata2-tea-texas.opendata.arcgis.com/
Notice that you are provided with the elementary school name, address, and grade range.
Now you will create a one-half mile buffer around each school, so that you will later be able to count the number of violent crimes occurring in 2010 within each buffer.
Notice that all three fields contained in the original schools point layer (school name, address, and grade range) have been preserved. In addition, a new field has been added stating the radius of the buffer in feet.
At this point, you can see all of the violent crime locations, along with the half-mile school buffers, but much of the map is so densely covered with overlapping points that it becomes difficult to tell exactly how many points there are and to see the underlying school buffers. In addition, while you can see the spatial distribution of the points, you are not provided with any sort of useful summary of the data. Performing a spatial join will allow you to discover exactly how many violent crimes occurred within a half mile of each school in 2010.
The goal of performing this spatial join is to add a numeric field to the school buffer attribute table that tells you how many crime points are contained within each school buffer.
The Spatial Join tool will open within the Geoprocessing pane. For 'Target Features', the HISDElemSchools_HalfMileBuffer is already selected, since that is the layer from which you launched the tool.
The 'Field Map of Join Features' describes how the features will be summarized as they are joined. The first half of the list of fields displays the attributes of the school buffer layer, ending with the Shape_Area field. The second half of the list of fields, beginning with the Date field, displays the attributes of the crime layer. A count field indicating how many crime points intersect with each half-mile buffer will automatically be provided. Since many crimes will be appended to each school buffer, it does not make sense to generate summary statistics about the crime fields, because variables like offense type, premise code, and address cannot be averaged. By default, the table would output only the attributes of the first crime encountered within each buffer, which could be very misleading. Therefore, you will remove all the crime attributes from the output fields.
Notice the newly added Join_Count field. This field tells you how many crime points are contained within each school buffer. Notice also that only the fields from the schools attribute table have been included in the result, because we removed all the crime fields from the output.
Since the newly joined schools buffer layer contains all of the same information as the original schools buffer layer, plus the new Join_Count field, you no longer need the original buffer layer. Since your crime data has now been summarized, you no longer need the original crime points either.
The Symbology pane has opened on the right as a new tab on top of the Geoprocessing pane.
Leave the fifth upper value as is, since this is the true upper value for the dataset. You can now easily tell which schools have the largest number of violent crimes occurring within a half mile radius.
You now have an attribute table that tells you the number of violent crimes that occurred within one year within a half mile of each school, but you would also like to have a table that tells you in which police district each elementary school lies. To create this table, you will perform another spatial join to add the attributes of the police beat to the back of each school that lies inside it.
At this point, only the elementary school point locations and the police district boundaries should be visible.
Remember that, at this point, the attribute table only contains the school name, address, and grade range.
Since each school is entirely within a single district and no data is being summarized, it is okay to leave all of the output fields. The new layer should appear at the top of your Contents pane.
Notice the newly added District field that tells you which police district each school falls within. Scroll down the table view and notice that five schools do not have a district assigned to them. That is because those schools fall within HISD, but do not fall within the City of Houston police jurisdiction.
In this tutorial, you navigated to various geoprocessing tools directly through the Toolbox; however, it is likely that when you go to work on your own, you may not remember exactly where all those tools are located. As long as you can remember the name of the tool or what it does, you can find it using the search function.
This tab shows five commonly used tools, along with all the tools you have run recently and any tools you have marked as a favorite by right-clicking on the tool name and selecting Add To Favorites.
Within the history tab, you will see a complete list of all of the tools you have run in order. Double-clicking on any tool in the history will reopen the tool with the exact settings used in that run. Using the History tab is a great way to review previous work for documentation purposes or to rerun a set of tools or slightly modify tool parameters with minimal thought.