• Lab: Geocoding/Scanning/Digitizing Information

  Today we'll have a look at how to turn your map resources into electronic maps. For this, we'll need to additional equipment and resources wich we hope you will find useful. While we'd planned on visitting the SNRE site and using their digitizing tablets, due to problems with high-falutin' technology we're stuck here in our lab using old fashioned mouse digitization. No reason to cry over it, though: we can have fun anyway.

  Lab Objectives:

  • tried out a simple web-based geocoding site.
  • gain knowledge of scanning/OCR (as needed)
  • be able to digitize point and polygon themes using the mouse and ArcView
  When you're done, you'll have a point theme and a polygon theme, either of which you could use to investigate spatial autocorrelation.

  Lab 4

  • Just for fun, you might try some geocoding via the internet. This is one way (a very painful way!) of collecting information on the spatial location of an address (Census information and Latitude/Longitude of the Tract/BNA). Try it with some addresses you know, to see if it gets them right!

    When you get down to the tract level, you could consult the Census TIGER files to find the lat/longs of the centroids of the tracts (these too are available from the CIESIN site) - but this would be a lot of work. I'm sure that soon (if not already) some good soul will put a really good full address -> lat/long geocoder on the web. Right now this one is the best we've got!

  • Some of you are still not caught up with the group, so for those who need to, continue working on your earlier labs: lab 1, lab 2, or lab 3.

  • For those who are ready to move on: the maps we are using today were scanned in from books. This is a skill worth acquiring, as you may wish to digitize something of your own someday (perhaps even today!). If you have never scanned before, you should try it, but it's up to you. Sometime during today's lab you should go up (we'll do this one by one) to the multimedia center and scan in any map(s) or image(s) that you want to digitize. If you didn't bring any of your own, one will be provided for you from our stock of fabulously amusing and illustrative examples.

    Leah Estberg will help those needing or wanting help with scanning and/or OCR (Optical Character Recognition - useful for scanning in type-written data from dusty old books, say). We have reserved one of the scanners in the multimedia lab up in PHISA. Just because you scan an image or a map doesn't mean that you're obliged to use it in today's lab. I might suggest that you just use the images we've provided you for the lab, but if you have an equivalent theme (i.e. point or polygon) of your own and would rather work with that, fine.

  • For the rest of this exercise, I will talk about two images: snow.jpg contains polygon and line information, while smallpox.jpg contains point and polygon information. If you have some other image that you want to use instead of these, that's fine! Go ahead, and just replace the names of these file with your own.

    If you're going to use the default images, download them to your space (from the browser) by right-clicking on the links to the images above - you'll be offered the option of saving the links as....

    • Now that you have your image, here's what to do: launch ArcView, first of all, and start a New Project (you will decline their charitable offer to add data for you - we're going to do that the hard way!). You should end up with a fresh View1 open.

    • You need to load an "extension" to allow ArcView to import jpeg files (by default, it only handles tiffs). Make the project window active, then click on the File menu -> Extensions -> JPEG Image Support. Now we'll be able to import your file.

    • Add image smallpox.jpg to the (empty) view. You can do this from the View menu item: click on the Add Theme item, and you will be offered the choice of themes you want to add. In the dialog window that appears you will see Data Source Types. Rather than Feature Data Source, choose Image Data Source. Now move to the directory containing smallpox.jpg, and it should appear as a choice. Select it, and you will see it added to your view (although it doesn't appear until you've clicked its check box).

    • We want to add a new theme to our (empty) view: the theme of the new digitized data. You can do this from the View menu item. When you click on the New Theme item, you will be offered the choice of themes you want to create. This depends on the type of feature (point, line, or polygon) that you want to add. If sites, point; if linear features (e.g. rivers), line; if you want to add counties, choose polygon. We'll start with a point theme (villages which show smallpox scars versus those which don't), so select Point.

    • At this point, you'll want to make your ArcView window as large as possible, to help you see better. You'll also want to Zoom in on areas so that you can get right in the center of the points on the plot. Do that now: zoom in on an area of points that you'll want to digitize. Notice that there are both black filled and unfilled dots: we'll start with the filled dots.

    • When you elected to create a new theme, a new icon appeared next to the T icon - a little point, or dot icon. This is the Draw Point icon; click on it, and you can now start digitizing. As you click on a black dot, a small dot will be drawn in; choose a good color for the new theme, so that it is clearly visible against the black dot. This way you will be able to easily see that you have digitized all the dots (haven't missed any).

      If you've zoomed so far that you can't see the whole image, then as you digitize, you may want to switch back and forth between the Draw Point button and the Pan button (the little hand icon), which allows you to move the image to new areas to digitize.

    • When you think that you're done digitizing all the dots, Zoom to Theme (from the View menu). Again, if you chose a good color, you should be able to clearly see that all the black filled dots are covered. Go back and digitize any that you missed. We are now ready to edit the attribute table, to indicate that these points are villages having pock marks.

    • Have a look at the attribute file by choosing Table from the Theme menu. It doesn't look very interesting, does it?! We want to add a field to the table, which we do from the Edit menu. You might call your new field "pox", and leave it a Number, with perhaps width 1 (since it will be binary, 0 or 1). Now we want to edit the pox column, which we do by choosing the I-arrow button on the lower right of the button bar. We want to put a 1 in every box, and it doesn't appear that there's any nice way of doing this so we'll do it the hard way. Click on the first pox box. Type a 1. Hit the enter key, and do it again. And again, and again, and ....

      When you're done, run the statistics on the field, to make sure that you have a max, a mean, and a min of 1.

    • Now we'll go back and add in the unfilled dots, corresponding to villages without pox marks. Back to view, zoom to an area, choose the Draw Point button, and away you go! By default the table values will be zeros, so we don't need to worry about our table any more. When you have digitized all the points, then you should choose Stop Editing from the theme menu.

    • At this point, you can change the symbol used to display the villages by double clicking on the legend. Use Graduated Color instead of Single Symbol, and choose pox as the Classification Field. Choose nice colors for the symbol (by double clicking on each symbol), apply the result, and you should be looking at a nice digitized data set, created from the smallpox.jpg file.

      You can have a look at the data set in a different GIS (GRASS) via WebGIS, selecting the smallpox raster map, smallpox vector map, smallpox site map (choose a bright color for this map), and smallpox region. The vector map shows the Theissen polygons associated with the data as well, and that vector map was used to create the raster map.

      I created this file because I was frustrated when I did exactly what you just did and couldn't figure out how to look at the coordinates of the points I created. They're stored in ESRI's proprietary shapefile, and I couldn't figure out how to get ArcView to show them to me. So I converted the shapefile to an Arc export file, then imported that into my favorite GIS, GRASS (which is free: public domain). I created the Theissen polygons, which again represent "Basins of control", if you will (also called voronoi diagrams), which are regions of space closest to the point contained in the middle of each region.

      There are a couple of cluster statistics available from the WebGIS menu (look at the bottom of the page - click on Cluster Operations). At the bottom of the page which presents itself you will find a list of tests (we haven't talked about any of them yet). Choose one, select the smallpox site file, and then click on any point in the image. You will get a statistic calculated at that point. (We are in the process of adding all the tests which we will discuss in this course, so that people can try out the tests over the web. But enough of this! It doesn't have anything to do with digitizing.)

    • Now we'll move onto polygon themes. We'll create a polygon theme for the snow.jpg file. You may want to start a new project, saving the old one (as well as all the shapefiles) to your directory.

    • Follow the instructions for adding an image theme, only this time it's snow.jpg. Once you have it loaded you will again create a new theme (let's call it snow.shp), only this time it will be a polygon theme.

    • Notice that instead of a point icon, you now have a rectangle icon. Click on it. You have your choice of what sort of polygons you want to add, and we'll only be adding two types. The first one to choose follows the circle, and looks like this:

         -----
       /    /
      |    .
      |     \
      --------
      

      (man, I wish I could find that icon image in some directory somewhere!).

    • We'll use that to make our first region. Start in the upper right corner with the large area labelled ND (again, you'll want to zoom in so that you can see what you're doing). Click on the corner and click again on the northwest tip. Now drag the mouse down a little, and you'll see a region getting traced out. Click as the mouse winds along the edge of the area, and when you get to the southeastern tip, click twice rapidly. A region should be displayed.

      Beware spurious rapid double clicks! That signals "all done". I try to consciously pause a bit between clicks as I move.

    • From now on, we want to create areas that adjoin this first region (or other regions), so we need to switch tools: go to the rectangle button again, choosing the last button, which looks sort of like

         ----------
       /****/    /
      |****.    .
      |****|     \
      -------------
      

      This cryptic symbol means that you're going to add an adjoining region. To do so, let's work on the 37/103 region next to the ND region. The strategy is to click inside the ND region, then click on a point where our new region will join the ND region (the northeast corner is good). Then click on the northwest corner, and descend the winding region edge, clicking as you go. If all goes well, you'll click all the way back to the first region. Go a little bit into the first region, double click, and the second region should magically appear.

    • Again, we probably should add the data as we go (i.e. the 37 103 part). Add two fields to your table, Population and Deaths, and edit them to incorporate the data (you'll need to choose some missing value indicator).

    • You can start in one region and end in another. So if you wanted to next digitize the 31/298 polygon, you could start in the 37/103 region near the northwest corner of 31/298, and end in the ND region.

      Keep this up until your hand hurts, until time runs out, or until you run screaming from the lab shouting "I never want to see another mouse again as long as I live!": then quit.

      This is the map and data set that was used for the BW join statistics example that you saw in your reading and lecture. If you finish this map, then you could create the BW map by adding a rate variable (derived from Population and Deaths), and coding by above and below the median. The neighbors can be obtained using the SPlus extension, but you take this on at great risk - two large, unweildy pieces of software trying to work together, yuck!

  • Don't forget to evaluate this lab, lab 4. While you're at it, evaluate lecture 4 at the same time!

  • One more thing: next week's lab will be a "project fest": rather than have a structured affair, you will be working on whipping your project into shape. The instructors and Leah Estberg will all be present to help: to commiserate, to cajole, to assist in any fashion possible (data conversion, visualization, etc.). This means that we expect you to have your data and question decided by next Thursday. We ask you to please formally respond to the first assignment (due 1/26/99!), which you can access from the Assignments button at the official course home page by Tuesday.

• Software: ArcView, Photoshop (image scanning), Omni Page (OCR)

• Featured techniques: scanning, digitizing

• Readings:
  Principal Readings:
  1. Brownson, R. C. 1998. Outbreak and Cluster Investigations. In Applied Epidemiology (Eds R. C. Brownson and D. B. Petitti). Oxford University Press.
  Reference Readings:
  1. Centers for Disease Control. 1990. Guidelines for Investigating Clusters of Health events. MMWR 39 (RR-11):1-23.
  2. Jacquez, G. M., L. A. Waller, R. Grimson, D. Wartenberg. 1996. The Analysis of Disease Clusters, Part I: State of the Art. Infect. Control Hosp Epidemiol. 117:319-327.
  3. Thacker, S. B., D. F. Stroup, R. G. Parrish, H. A. Anderson. 1996. Surveillance in environmental public health: Issues, systems and sources. American Journal of Public Health 86:633-638.

• Data:
  • We're digitizing our own!

• Links:
  • Geoff's Power Point lecture.
  • Here's a nice web reference for disease patterns for some of the more common infectious diseases, including the CHAART Disease Monitoring Data Needs for surveillance of these disease.
    CHAART is beginning to provide some exercises in GIS/Remote Sensing. These look very interesting, and involve using Imagine image processing software.
  • Sentiweb summary. This is a nice surveillance site, which includes animations, and data.
  • Disease Surveillance On-line, for Canada (Cancer, HD, etc.). Cancer Data, for example, is available on a very crude spatial scale (Canadian provinces). They now have a fluwatch.
  • Check out the University of Washington's site on emerging infections of international public health importance. Lots of interesting on-line lectures await you, including this one concerning surveillance.
  • "http://www.cste.org lists nationally reportable infectious diseases and other conditions." (from the notes from Ellen K. Cromley's (UConn) Workshop GIS and epidemiology of infectious disease in San Diego)
  • One company is sponsoring a flu surveillance project for the U.S.

Page by Andy Long. Comments appreciated.