1 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 table from your selection. Query SQL Select – now try and build the query 2

Earthquakes… Make a thematic map of recent world earthquakes (see 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). 4

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. 5

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. 6

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) = a 1 + a 2 x + a 3 y + a 4 xy + a 5 x 2 + a 6 y 2 –Which method does a better job of predicting the Living values at an unknown point? 7

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 8

Georegions (lots of blanks to fill in) 9 Open PRESSURE.XLS Identify 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 Brunswick East Greenbush Grafton Hoosick Nassau North Greenbush Petersburg Pittstown Poestenkill Rensselaer Sand Lake Schaghticoke Schodack Stephentown Troy city N = number of observations Living = living quarters measurements Basement = for basement measurements Sigma = one standard deviation for corresponding percentages 10