Exercise

IntroductionWe have learned the basic operation of ArcGIS through the Learning ArcGIS provided by

ESRI. An additional small exercise is provided here. This exercise is for students who already know 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 will see the map of three counties (Ingham, Eaton and Clinton). Watersheds and county boundaries are displayed in the Data View.

2. Save your own fileFirst 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 setsArcMap 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. It is also interesting 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 siteClick 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 CalculationRight 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(m 2 ).

Exercise In the same way, make new layer named Mason_XXX clipped by ‘Mason

Public Schools (Inghum)’ and calculate the area of Mason_XXX.

6. HistogramIn 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_inghum. Then

click the histogram button . Histogram of lu78_inghum dialog opens.

The number of Value field corresponds to the land use type as shown below.Close Histogram of lu78_inghum dialog.

Number Land use type1 Urban and Built Up2 Agricultural Land3 Rangeland4 Forest Land5 Water6 Wetlands7 Barren

7. Two-way cross tabulationIn this section, you will produce the cross tabulation of land use and soils in the Inghum 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_Inghum soil_InghumSoils_Eaton soil_EatonSoils_Clinton soil_Clintonlanduse1992_Inghum lu1992_Inghumlanduse1992_Eaton lu1992_Eatonlanduse1992_Clinton lu1992_Clintonlanduse1978_Inghum lu1978_Inghumlanduse1978_Eaton lu1978_Eatonlanduse1978_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.

ExecerciseHow many cells of Agricultural land are on the soil type of AnA (VALUE_6: Aubbeenaubbee-Capac sandy loams, 0 to 3 percent slopes).

Number Map Unit Symbol Map Unit NameVALUE_1 Co Colwood-Brookston loamsVALUE_2 OwB Owosso-Marlette sandy loams, 2 to 6 percent slopesVALUE_3 MaB Marlette fine sandy loam, 2 to 6 percent slopesVALUE_4 CaA Capac loam, 0 to 3 percent slopesVALUE_5 Hn Houghton muckVALUE_6 AnA Aubbeenaubbee-Capac sandy loams, 0 to 3 percent slopesVALUE_7 Pa Palms muckVALUE_8 SpB Spink loamy sand, 0 to 6 percent slopesVALUE_9 RdB Riddles-Hillsdale sandy loams, 2 to 6 percent slopesVALUE_1 Ud Udorthents and UdipsammentsVALUE_1 KbA Kibbie loam, 0 to 3 percent slopesVALUE_1 W WaterVALUE_1 Gr Granby loamy fine sandVALUE_1 OwC Owosso-Marlette sandy loams, 6 to 12 percent slopesVALUE_1 ByA Brandy sandy loam, 0 to 3 percent slopesVALUE_1 UtB Urban land-Marlette complex, 2 to 12 percent slopesVALUE_1 Pt PitsVALUE_1 Ka Keowns very fine sandy loamVALUE_1 UpA Urban land-Capac-Colwood complex, 0 to 4 percent slopesVALUE_2 Ha Histosols and Aquents, pondedVALUE_2 Ed Edwards muckVALUE_2 Ch Cohoctah silt loamVALUE_2 MtB Metea loamy sand, 2 to 6 percent slopesVALUE_2 MaC Marlette fine sandy loam, 6 to 12 percent slopesVALUE_2 ThA Thetford loamy sand, 0 to 3 percent slopesVALUE_2 Uu Urban land-Fluvaquents complexVALUE_2 SnB Sisson fine sandy loam, 2 to 6 percent slopesVALUE_2 BrB Boyer sandy loam, 0 to 6 percent slopesVALUE_2 Ln Lenawee silty clay loamVALUE_3 Gf Gilford sandy loamVALUE_3 UeB Urban land-Boyer-Spinks complex, 0 to 10 percent slopesVALUE_3 OtC Oshtemo-Spinks loamy sands, 6 to 12 percent slopesVALUE_3 MtC Metea loamy sand, 6 to 12 percent slopesVALUE_3 Ad Adrian muckVALUE_3 RdC Riddles-Hillsdale sandy loams, 6 to 12 percent slopesVALUE_3 Sb Sebewa loamVALUE_3 MeD2 Maelette loam, 12 to 18 percent slope, erodedVALUE_3 Bo Boots muckVALUE_3 BsE Boyer-Spinks loamy sands, 18 to 30 percent slopesVALUE_4 OsC Oshtemo sandy loam, 6 to 12 percent slopesVALUE_4 BsD Boyer-Spinks loamy sands, 12 to 18 percent slopesVALUE_4 RdD Riddles-Hillsdale sandy loams, 12 to 18 percent slopesVALUE_4 OsB Oshtemo sandy loam, 0 to 6 percent slopesVALUE_4 MrA Matherton sandy loam, 0 to 3 percent slopesVALUE_4 SpC Spink loamy sand, 6 to 12 percent slopesVALUE_4 SnC Sisson fine sandy loam, 6 to 12 percent slopesVALUE_4 OtB Oshtemo-Spinks loamy sands, 0 to 6 percent slopesVALUE_4 Ce Ceresco fine sandy loamVALUE_4 Au Aurelius muckVALUE_5 MoE Marlette-Boyer complex, 18 to 25 percent slopesVALUE_5 Na Napoleon muckVALUE_5 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_inghum. For the Reclass field, click the down arrow and choose Value. Set New values to reclassify as shown below.Old value New value1 02 13 04 05 06 07 0No 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 analysisIn 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_Inghum 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, 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

Inghum county as shown below.

9. Save as a graphic file and Print outYou 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 softwares.

ExerciseReport the spatial characteristics of the land use change of agricultural land in Ingham. The

Paper should include this graphic file.