Exercise
Introduction
We have learned the basic operation of ArcGIS through the Learning ArcGIS provided by ESRI. Additionally small exercise is provided here. This exercise is for students who have already known the basic operation of ArcGIS. We will exercise some advanced analysis method using the GIS data sets of Ingham, Eaton and Clinton counties.
1. Display files
Start ArcMap by clicking your Start menu, then clicking All Programs -> Course Software -> ArcGIS -> ArcMap. If you see a dialog, choose the option to start using ArcMap with an existing map and double-click "Browse for maps."
If you don't see the dialog, click the Open button.
Navigate to u:/msu/course/rd/415/EIA_GIS folder.
Double-click EIA_GIS.mxd to open the map document.
You see the map of three counties (Ingham, Eaton and Clinton). Watersheds and boundary of three counties are displayed in the Data View.
2. Save your own file
First of all, click File menu and choose “Save as”. You have to save the EIA_GIS.mxd as your own file to avoid the confliction with other users. Enter your favorite name (XXXX.mxd) in the file name. This file should be saved in the u:/msu/course/rd/415/EIA_GIS folder.
3. Exploring geographic data sets
ArcMap offers advantages for exploring geographic data: you can view many data layers at once. Turn on the check boxes of some layers in which you are interested and confirm what is displayed.
Also it would be interesting for you to click the Zoom In tool and zoom in to the area of MSU as shown below.
The map of the area of MSU. Some layers are displayed as shown in the Table of Contents.
4. Extract two site
Click the Full Extent button and look at the map. Turn on the check box of the School_D layer. From the Selection menu, choose Select By Attributes. The Select By Attributes dialog opens. Next to the Layer field, click the down arrow and choose School_D if it is not already selected. In the Method field, the default method, "Create a new selection," is selected. This is what you want. In the Fields list, double-click [NAME].
The field is added to the expression box below the Fields list. Click the equals sign button. Click Get Unique Values. In the Unique Values list, double-click 'Charlotte Public Schools'. Click Apply and then Close.
Charlotte Public School is selected. Right-click School_D in the Table of Contents, choose Data, then click Export Data.
In the Export Data dialog, click the Browse button next to the Output shapefile or feature class field and navigate to the u:/msu/course/rd/415/EIA_GIS folder.
Double-click u:/msu/course/rd/415/EIA_GIS/Tri county
For Name, enter Charlotte_XXX. Enter your favorite word in XXX such as your name or your favorite number. Click Save, then OK. Click Yes to add the data as a layer to the map.
5. Area Calculation
Right click Charlotte_XXX, choose Open Attribute Table. Attributes of Charlotte_XXX dialog opens. Click Options and choose Add Field. Add Field dialog opens. Enter AREA in the Name field and click the down arrow in the Type field and choose Double. Click OK. AREA field is added.
In the Editor Toolbar, Click Editor and choose Start Editing. Make sure u:/msu/course/rd/415/EIA_GIS/Tri county folder is selected and Charlotte_XXX is displayed in the ‘These layers and tables will be available for editing’ box. Click OK in the Start Editing dialog.
Right click AREA in the Attributes of Charlotte_XXX, and choose Calculate Values. Field Calculator dialog is launched. In the middle of the dialog, check the box next to ‘Advanced’.
Enter the VBA (Visual Basic of Application) script in the Pre-Logic VBA Script Code as follows.
You do not need to understand the VBA because the commonly used VBA scripts are shown on the some web sites. The above is the scripts to calculate the area.
Click OK. In the AREA field, the area of Charlotte Public Schools is calculated. Make sure the area is 330,231,532.077109(m2). Click Close. Click Editor in the Editor Toolbar, and then choose Stop Editing.
Ans. 280,650,295.61029(m2).
6. Histogram
In the Table of Contents, right click Landuse and Soil data flame. Select Activate. Land use map displays in the Data View.
For the Layer field in the Spatial Analyst Toolbar, click the down arrow and choose lu78_Ingham. Then click the histogram button. Histogram of lu78_Ingham dialog opens.
The number of Value field corresponds to the land use type as shown below. Close Histogram of lu78_Ingham dialog.
Number / Land use type1 / Urban and Built Up
2 / Agricultural Land
3 / Rangeland
4 / Forest Land
5 / Water
6 / Wetlands
7 / Barren
7. Two-way cross tabulation
In this section, you will produce the cross tabulation of land use and soils in the Ingham and Eaton county. There are many layers in the Table of Contents which may be distinguished by the data type as shown below. Also these data in detail is shown in the Datalist.xls.
Vector / RasterSoils_Ingham / soil_Ingham
Soils_Eaton / soil_Eaton
Soils_Clinton / soil_Clinton
landuse1992_Ingham / lu1992_Ingham
landuse1992_Eaton / lu1992_Eaton
landuse1992_Clinton / lu1992_Clinton
landuse1978_Ingham / lu1978_Ingham
landuse1978_Eaton / lu1978_Eaton
landuse1978_Clinton / lu1978_Clinton
The raster data model is very useful for representing continuous geographic data; that is, phenomena such as land use and soils, which don't have well-defined boundaries and which usually change gradually across a given area. When used to represent continuous data, each raster cell value is a measure of the phenomenon being modeled. For example, in an elevation raster, each cell value represents the elevation of a particular area. The raster data model is commonly used for spatial analysis and modeling. The cross tabulation is one of spatial analysis, so we will deal with raster data sets in this section.
Click the ArcToolbox button. Expand Spatial Analyst Tools, and then expand Zonal. Double-click Tabulate Area. The tabulate area tool dialog displays. On the right, read the description of what the Tabulate area tool does (you may need to click Show Help to see the description).
For Input raster or features zone data field, you need to select the two layers you want to calculate. Next to the Input raster or features field, click the down arrow and choose lu78_Ingham. Make sure ‘Value’ is displayed in the Zone field. Next to the Input raster or features field, click the down arrow and choose ‘soil_Ingham’. Make sure ‘Value’ is also displayed in the Zone field.
For Output table in the Tabulate Area dialog, the default output location (u:/msu/course/rd/415/EIA_GIS/Tricounty) and the output table name (Tabulat_lu78_in1.dbf) are fine. You don't need to change anything. Also the default Processing cell size 100, which means 100 meters, is fine. Click OK.
Open Microsoft Excel and then open the file u:/msu/course/rd/415/EIA_GIS/Tri county Tabulat_lu78_in1.dbf. You see the cross tabulation. The row number (VALUE_1 to 52) correspond to the soil type as shown below and the column number (1 to 7) correspond to the land use type as shown above
Ans. 7527.
Number / Map Unit Symbol / Map Unit NameVALUE_1 / Co / Colwood-Brookston loams
VALUE_2 / OwB / Owosso-Marlette sandy loams, 2 to 6 percent slopes
VALUE_3 / MaB / Marlette fine sandy loam, 2 to 6 percent slopes
VALUE_4 / CaA / Capac loam, 0 to 3 percent slopes
VALUE_5 / Hn / Houghton muck
VALUE_6 / AnA / Aubbeenaubbee-Capac sandy loams, 0 to 3 percent slopes
VALUE_7 / Pa / Palms muck
VALUE_8 / SpB / Spink loamy sand, 0 to 6 percent slopes
VALUE_9 / RdB / Riddles-Hillsdale sandy loams, 2 to 6 percent slopes
VALUE_10 / Ud / Udorthents and Udipsamments
VALUE_11 / KbA / Kibbie loam, 0 to 3 percent slopes
VALUE_12 / W / Water
VALUE_13 / Gr / Granby loamy fine sand
VALUE_14 / OwC / Owosso-Marlette sandy loams, 6 to 12 percent slopes
VALUE_15 / ByA / Brandy sandy loam, 0 to 3 percent slopes
VALUE_16 / UtB / Urban land-Marlette complex, 2 to 12 percent slopes
VALUE_17 / Pt / Pits
VALUE_18 / Ka / Keowns very fine sandy loam
VALUE_19 / UpA / Urban land-Capac-Colwood complex, 0 to 4 percent slopes
VALUE_20 / Ha / Histosols and Aquents, ponded
VALUE_21 / Ed / Edwards muck
VALUE_22 / Ch / Cohoctah silt loam
VALUE_23 / MtB / Metea loamy sand, 2 to 6 percent slopes
VALUE_24 / MaC / Marlette fine sandy loam, 6 to 12 percent slopes
VALUE_25 / ThA / Thetford loamy sand, 0 to 3 percent slopes
VALUE_26 / Uu / Urban land-Fluvaquents complex
VALUE_27 / SnB / Sisson fine sandy loam, 2 to 6 percent slopes
VALUE_28 / BrB / Boyer sandy loam, 0 to 6 percent slopes
VALUE_29 / Ln / Lenawee silty clay loam
VALUE_30 / Gf / Gilford sandy loam
VALUE_31 / UeB / Urban land-Boyer-Spinks complex, 0 to 10 percent slopes
VALUE_32 / OtC / Oshtemo-Spinks loamy sands, 6 to 12 percent slopes
VALUE_33 / MtC / Metea loamy sand, 6 to 12 percent slopes
VALUE_34 / Ad / Adrian muck
VALUE_35 / RdC / Riddles-Hillsdale sandy loams, 6 to 12 percent slopes
VALUE_36 / Sb / Sebewa loam
VALUE_37 / MeD2 / Maelette loam, 12 to 18 percent slope, eroded
VALUE_38 / Bo / Boots muck
VALUE_39 / BsE / Boyer-Spinks loamy sands, 18 to 30 percent slopes
VALUE_40 / OsC / Oshtemo sandy loam, 6 to 12 percent slopes
VALUE_41 / BsD / Boyer-Spinks loamy sands, 12 to 18 percent slopes
VALUE_42 / RdD / Riddles-Hillsdale sandy loams, 12 to 18 percent slopes
VALUE_43 / OsB / Oshtemo sandy loam, 0 to 6 percent slopes
VALUE_44 / MrA / Matherton sandy loam, 0 to 3 percent slopes
VALUE_45 / SpC / Spink loamy sand, 6 to 12 percent slopes
VALUE_46 / SnC / Sisson fine sandy loam, 6 to 12 percent slopes
VALUE_47 / OtB / Oshtemo-Spinks loamy sands, 0 to 6 percent slopes
VALUE_48 / Ce / Ceresco fine sandy loam
VALUE_49 / Au / Aurelius muck
VALUE_50 / MoE / Marlette-Boyer complex, 18 to 25 percent slopes
VALUE_51 / Na / Napoleon muck
VALUE_52 / EvB / Eleva variant channery sandy loam, 2 to 6 percent slopes
8. Overlay analysis (weighted or unweighted)
In this section, you will learn overlay method through analyzing the land-use change between 1978 and 1992.
8.1 Reclassify
We will focus on the land-use change of agricultural lands and need to modify the attribute value. In the Spatial Analyst Toolbar, Click Spatial Analyst and choose Reclassify. Reclassify dialog opens. For the Input raster field, click the down arrow and choose lu78_Ingham. For the Reclass field, click the down arrow and choose Value. Set New values to reclassify as shown below.
Old value / New value1 / 0
2 / 1
3 / 0
4 / 0
5 / 0
6 / 0
7 / 0
No data / No data
For output raster field, click the Open button. For Name, input the ‘lu78_XXX’ (XXX is your favorite name or number).
8.2 Overlay analysis
In the Spatial Analyst Toolbar, Click Spatial Analyst and choose Raster Calculator. Raster Calculator dialog opens. For Layers, double click lu78_XXX. The field is added to the expression box below the Fields list. Click the * sign button and input 100. Click + sign button and double click lu92_Ingham in the Layers field. Click Evaluate.
‘Calculation’ layer is added in the Table of Contents.
Right click ‘Calculation’ and choose Properties. Select Symbology tab and select Unique Values for Show field. You can see all unique values. Lu78_XXX is weighted 100 times. So land-use conversion from Agricultural Land to land use in 1992 is represented as the number between 111 and 192.
You can see the spatial distribution of land-use changes if you modify the Legend. Right click Calculation and choose Properties. Select Symbology Tab and click Import button. Choose Calculation.lyr, which is prepared for the exercise, and then click Add. Click OK. Land use change from agricultural land is displayed spatially. On the Tools toolbar, click the Zoom In tool. Zoom in the Ingham county as shown below.
9. Save as a graphic file and Print out
You can save the graphic as a graphics file. Click the Layout View button. From the File menu, choose Export Map. In the Export Map dialog, navigate to your local folder, such as your local computer or USB flash drive and so on.
Name the file your favorite name. In the Type of file click dropdown list, and choose JPEG (*.jpeg). You can use this graphic file in the Microsoft PowerPoint and other software.