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May 18, 2020 - This tutorial is still being actively edited. Please wait for this message to disappear before completing or printing, if you'd like to view it in its final form.



TABLE OF CONTENTS

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.

  1. Instruction text is numbered.
  2. Required actions are underlined.
  3. Objects of the actions are in bold.

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 10 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.

 

PART I: Install the R-ArcGIS bridge

  1. Download R and RStudio
    R link:
    R Studio link:

  2. Prepare data on Houston crime statistics
    Thogh you can Google search Houston crime GIS data and find the shapefile (with the link: https://cohgis-mycity.opendata.arcgis.com/datasets/hpd-nibrs-crime), it only contains around 4,000 cases, which is far from complete. As a remedy, we need to download the data from Houston Crime Statistics (with the link: https://www.houstontx.gov/police/cs/Monthly_Crime_Data_by_Street_and_Police_Beat.htm). For example, we can focus on the data of year 2020 till end of May (see the following screenshot).



    Note that the data is in .xlsx format. We need to save it as .csv file and then geocode the addresses to make it a shapefile. You need to use credits for geocoding in ArcGIS Pro. For convenience, I have already downloaded the data (and cleaned a little in terms of addresses) and geocoded it into a shapefile. You can downloaded the .rar file attaced here houston-crime.gdb.rar and proceed. Notice that, for simplicity, I only use the crime cases of the first 10 days of year 2020, that is, dating from January 1, 2020 to January 2, 2020 (I choose 10 days because the step in Part II using Create Space Time Cube by Aggregating Points requires at least 10 time step intervals (in this case, it requires at least 10 days if the time step interval is set as 1 day).

  3. Create a new project in ArcGIS Pro

  4. Install the R-ArcGIS bridge: automatical method/manual method
    Manual method: https://github.com/R-ArcGIS/r-bridge-install

 

 

PART II: Basic statistical analysis

  1. Project the shapefile

  2. Aggregate point data by counts within a defined location

  3. Analyze crime hot spots: One step forward

 

PART III: Enhance the dataset with additional attributes

  1. Add additional attributes to the original dataset

  2. Further prepare the dataset

 

PART IV (KEY SECTION): Conduct statistical analysis using R and ArcGIS Pro

  1. Bridge your data into R

  2. Calculate smoothed crime rates

  3. Continue analysis in ArcGIS Pro

  4. Identify areas with unusually high crime rates


PART V (KEY SECTION): Identify attributes that influence crime

  1. Create a correlation matrix in R to evaluate attribute relationships

 

 

 

 

 

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