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Peter Fox

GIS for Science

ERTH 4750 (98271)

Week 6, Friday, March 2, 2012

Lab: continued – query/select, thematic maps, geostatistics

Querying your data – world.tab• Selecting

– E.g. select countries in Africa with populations over 2 million and return literacy and inflation rate

– Requires an understanding of what you are querying – TABLEs

• Table->Table list … then Right click on the WORLD table -> Table Structure

• Try the pointer/select tools to select Africa, Window-> New Browser Window (choose the query<x> table from your selection.

• Query SQL Select – now try and build the query

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Earthquakes…• Make a thematic map of recent world earthquakes (see

http://neic.usgs.gov/neis/qed/ for quake data, find the comma-delimited list at bottom; get these data into MapInfo).

• Make a thematic map in which symbol colors represent earthquake depth ranges and symbol sizes represent magnitudes.

• Make a map of recent California earthquakes (from same data but only show quakes within California).

• Include on your map the outline of the San Andreas fault (download from the web or scan a map with the San Andreas fault, register the image, digitize the fault using MapInfo, and make a sa_fault table; show only the fault outline on your final map, not the original raster image). 3

Try these• Read in the file quakes.xls (earthquakes in

the eastern US), create points (latitude column header is epi_lat, longitude column header is epi_long), and plot them on a map of the US (usa).

• Make a file (Excel or text) of the zip codes for 10 of your friends in the US. Read them in, geocode them using zip codes and us_zips, and plot them on a map of the US (usa).

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Another thematic map• Make a thematic map showing population for

the US states.

• Make a thematic map of US state population density.

• Select and map only the states with more than 5 million inhabitants.

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Literacy (world.tab)• Make a thematic map of the literacy rate

among the world's countries.

• Make another map for the ratio of rural to urban inhabitants, using similar coloring schemes.

• Put these two maps on the same layout page and think about whether or not you see a correlation between literacy rates and rural inhabitants.

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More analysis• Using the radon2.xls data, determine whether or not the

'Living' and 'Basement' measurements are correlated. • Use the 'Living' data as the dependent variable (y-data) and

the 'Basement' as independent variable (x-data).– Use the uncertainties in your correlation.– Compare this result to what you would get when uncertainties are not

used. Why is there a difference?– Make a thematic map of the misfits to the data; that is, the predicted

v. observed 'Living' radon. Do you see any spatial patterns in the differences?

– Fit the Living data to a second-order polynomial; R(x,y) = a1 + a2x + a3y + a4xy + a5x2 + a6y2

– Which method does a better job of predicting the Living values at an unknown point?

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Bilinear versus least squares

• Open radon.xls and estimate a bilinear estimate of radon at “some location”

• Calculate mean and standard deviation

• (put it on a map, e.g. renss_cty)

• Compare radon value with an estimate from least squares calculation

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Georegions (lots of blanks to fill in)

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Open PRESSURE.XLSIdentify possible regions based on values and geography

Calculate mean and standard deviation

future• Percent of Homes With Radon Levels Greater Than 4 pCi/L

• Town N Living Sigma Basement Sigma

• Berlin 8 14 6 48 11• Brunswick 94 17 4 46 4• East Greenbush 96 15 2 37 3• Grafton 12 12 5 40 8• Hoosick 19 7 3 34 9• Nassau 18 12 5 35 7• North Greenbush 101 20 3 49 4• Petersburg 11 12 5 46 10• Pittstown 14 13 5 43 8• Poestenkill 22 19 6 57 8• Rensselaer 18 9 4 34 8• Sand Lake 63 15 4 40 4• Schaghticoke 28 16 5 52 8• Schodack 154 21 3 53 3• Stephentown 14 16 5 49 8• Troy city 150 14 3 35 3

• N = number of observations• Living = living quarters measurements• Basement = for basement measurements• Sigma = one standard deviation for corresponding percentages

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