More ArcMap steps

The idea is to develop a sense that you know what you're doing with the software, but more for intellectual than for technical reasons: having clearly in mind how vector GIS can be used to visualize the patterns in data, starting from statistics on defined areas (counties, provinces, etc.). The examples we'll use today are from North American agriculture, simply because I have some pretty detailed data available.

Start by exploring the maps available at USDA's NASS (National Agricultural Statistics Service) ...and the first question might be: how useable are the services here? What can and can't you find maps of? What would you like to be able to map that you (seemingly) can't? What questions arise as you look over the available maps?

Look also at 1997 Agricultural Atlas

If we interest ourselves in soybeans for a moment: Look at Soybeans Harvested 2002 and Yield per acre, and then look at Soybeans Harvested 1924-2000 (and try some of the other animations too).

What questions arise here? And how could we get some answers to them? ??What are soybeans used for?? It happens that I have a page from a couple of years ago ...and one of the terms that comes up when one starts to explore the world of the soybean is glyphosate, also known by its trade name: Roundup. There's quite a story there...

So let's make some maps. First, see if the R: drive is mapped and functioning (look under My Computer. If there's a RED X, RIGHT-click My Computer, choose 'Disconnect Network Drive' and then choose R; then RIGHT-click again, choose Map Network Drive, choose R:, and type \\acadproj\vol8 in the box... which SHOULD result in successful mapping)

Next: Start ArcMap, and choose to open an Existing map. Navigate to R:\global and choose usagric.mxd ...which includes data on a very broad range of agricultural variables, much of it/them from the 1987 Census of Agriculture. The layers include Counties (basic data from 2000 Census, but also agricultural summary statistics at the end of the dataset), STOCK, CROP2 and CROP1, HERB, and AGCHEM. Each of those latter 5 has a hefty range of obscurely-labeled variables, decoded via codes at http://home.wlu.edu/~blackmerh/humangeog/aglabels.html

Spend some time exploring what the possible subjects are before you plunge into making maps with the data. What interests you in this realm? Some specific crop or animal? Some characteristic of farms? (like farms as % of households)

You know the basic moves: RIGHT-click on a label like 'STOCK Polygon', LEFT-click on Properties, use the Symbology tab, under Show and Quantities, choose Graduated Color...

Note that there's a CODE -99 for missing data, and we'd like to exclude that. Click Classify... and then Exclusion... and use the Data Exclusion Properties to specify that (for example) "CA1261" = -99 is entered...

Anyhow, what I'd like you to do is EXPLORE the various things you can do with agriculture data, and make some interesting maps.

It's always possible to EXPORT a screen image as a JPG, but that doesn't include the LEGEND information, and robs the map of some of its potential interest as a communication. To fix that, once you've got an interesting-looking map on the screen, from the VIEW menu choose LAYOUT view (you've been using DATA view up to now).

You can set the space you're working in to LANDSCAPE mode via the FILE menu's Page Setup command; you can insert the Legend onto the Layout via the Insert menu; you can insert a Title or other text, and then move the items around and resize them. You can change items within the legend by (1) RIGHT-click (2) convert to graphics (3) ungroup (4) delete or reorganize the elements ...

eventually you'll be happy enough to SAVE the result of your manipulations as a .jpg, and this time the resulting image will have the configuration of the layout view.

The assignment for next time: by noon on 10 February, make one or more interesting maps using the US agriculture datasets, and link jpg file(s) in your logfile. Write an EXPLANATION of the patterns you've depicted, and include what you think are the outstanding QUESTIONS that the image(s) pose.