GY301 Geomorphology Lab 5 Topographic Map: Final GIS Map Construction

Transcription

1 GY301 Geomorphology Lab 5 Topographic Map: Final GIS Map Construction Introduction This document describes how to take the data collected with the total station for the campus topographic map project and use QGIS 2.x to construct the map for each group. Each group may turn in a single map all members of the group will the same raw grade before peer assessment. QGIS is the GIS application software that will be utilized to compose the map, and then as a final step conduct a hydrologic analysis to determine the critical points around LSCB and the Library where stream erosion is most likely to be a problem. QGIS is open source (Free!) and cross-platform so you should be able to complete the map and hydrologic modelling on a Windows, MacOS, or Linux system without major problems. ArcGIS may also be used if preferred. The GIS workstations in LSCB 333 and 146 have both ArcGIS and QGIS installed for those who do not have their own computer system. QGIS may be downloaded at: Use/include the following on the GIS final map: 1. Scale of 1:2, Contour Interval of 0.2m, labeled index contours every 1.0m. 3. Post map of data points (red crosses). 4. Title = Total Station Project: Group {XX}, Fall Semester 20{XX}. 5. Group member names and date due in lower right corner. 6. The corners of the Library, LSCB, LSCB Biology Lecture, and new Administration Building (Meisler) should be identified as points on the survey. In QGIS draw polygons that connect these points. 7. Survey the trees 1-9 that are the white course used in the pace & compass project. 8. Add UTM grid to map frame with 100m spacing.

2 Step 1: Create project file and add aerial base map and other features. First, download the starting files from the resources section of the online GY301 web site. Currently this is the CampusTopoProject.zip file, but check with your instructor to verify. This file should be unzipped in the folder where you intend to work on this project. There will be many files created but basically the following features will be represented by these files: 1. A georeferenced raster image file of the USA campus that used the UTM NAD27 coordinate system. 2. A shape file of the boundary of the mapping area. 3. A shape file of the mapping area polygon that corresponds exactly to the boundary line. 4. A shape file of several key buildings on campus that are to be surveyed during the project. 5. A shape file of the benchmark coordinates (ST01-ST20) that were used to resection the total station during data collection. 6. A partial data set surveyed of a portion of the mapping area that will serve as an example file (GroupX.xls) In addition to these files you will need to have access to your spreadsheet of downloaded survey data collected during the project formatted so that you can refer to an X,Y,Z,ID column in the spreadsheet where X,Y are the UTM easting and northing coordinates, Z is the elevation of the survey point in meters, and ID is the point label. I will be using the GroupX.xls file as an example in class but you should be using your downloaded Total Station data. To start QGIS find the QGIS icon on the desktop or in the Start menu (Windows). Choose the QGIS Desktop application (with or without GRASS ). The main window will open find the add raster button on the left button bar, or from the menu select Layer > Add raster layer to add the aerial base map. You should choose the USA_campus.tif file. The aerial of the campus should now display in the main window. The remainder of the files will be vector shape files so use the Add vector layer icon or menu item to add these files: 1. Boundary.shp (after adding zoom to this layer) 2. ProjectArea.shp (make 50% transparent so you can see through it) 3. Buildings.shp 4. Benchmarks.shp You should now have a map that appears similar to Figure 1. It is important to check a few of the project file properties at this point to make sure everything is properly set before trying to add the survey data. First, let s make sure that the coordinate system (CRS) is defined for the project select from the menu Project > Project Properties. Figure 2 displays the window dialog that shows UTM NAD27 zone 16 selected as the project coordinate system. Also make

3 sure that the checkbox Enable on the fly CRS transformations is checked. Select the OK button to finish. Step 2: Add survey data to project file. The next will add the survey data stored in a spreadsheet to your project file so that it can be used to calculate a digital elevation model (DEM) that may later be contoured. Before starting this step verify that your spreadsheet file is in the working folder, and that it contains all of your data. Remember that the benchmarks that I give you can be used as additional data points. In addition, make sure that your spreadsheet has meaningful header labels (i.e. UTM_X, UTM_Y, Elev_m, etc.) so that you can easily pick the correct column when prompted by QGIS. The Excel file format that QGIS recognizes is.xls so if the Excel file is in the.xlsx format you need to load it into Excel and then use Save As to save a copy in the.xls format. In this example I will use a previous project file named ExampleData.xls. This comes from a data set collected by students when the mapping area was not as large as it is now so it will not cover the entire map area. Figure 3 shows the first 45 rows of the ExampleData.xls file that I will be using for this example project. Note the header labels in the first row. To import the Excel.xls file you will need to have activated the XyTools QGIS plugin. Take a moment to verify that this is true using the Plugins > Manage and Install Plugins menu. Choose the menu option Vector > XY Tools > Open Excel File.. Browse the directory until you find your Excel file (.xls). Select the file name and then set the information as in Figure 4. Note that whatever name you used as the column header labels for the x and y coordinates should be used here in this dialog. You should now see your data plotted properly on the map- check with your instructor if this does not occur. Note that in the layer window QGIS is indicating that the newly imported data is being stored as a temporary file. If you want to permanently save it you must export it to a shape point file. We want to do this anyway so you can use the data with gridding algorithms later on. You can now delete the temporary file created in the previous step. Step 3: Convert text data in shape point file to floating point numbers. In order to use the survey data in latter mathematical gridding algorithms they need to exist in the point shape file as true floating point numbers. Currently the columns are all in text format so we need to create 3 new floating point fields (attributes) x, y, z that will contain the floating point values of the (x,y,z) coordinates of the survey points. Right-click on the shape point file in the left legend window, then select properties > General. Change the layer name to Survey Data and select OK. Right-click on the layer name again and then choose Open attribute table. You will now see the structure of the

4 attribute table it is just like the original Excel file. Click the Pencil button to enter Edit mode. Find the button for adding a new column (attribute) and left-click on it. Fill in the window dialog as in Figure 6: 1. Name= x 2. Comment= UTM x coordinate 3. Type=decimal number 4. Field width = 15 digits 5. Decimal precision = 2 digits Click the OK button after making the above settings and you should be returned to the attribute table, but with an additional column on the right labeled x. All of the values in the column will be null. Now the string values in the UTM_X column must be converted to a floating point number and inserted in the x column row-by-row. There is an automated way to do this select the Open field calculator button on the button bar. Fill the window dialog out as indicated in Figure 7. Here are some notes on filling in the dialog properly: 1. Select the Update existing field option. 2. Select the x field as the field to be updated. Be careful here- you don t want to change the wrong column! 3. The large open window is the expression that will do the conversion. I first chose from the right window Conversion > toreal() that converts a string to a real number, and then from the Fields category I selected UTM_X because that is the field that contains the UTM X coordinate in string format. You will have to add the closing right parentheses. The real number equivalent will be inserted on the matching x cell when OK is selected. Select OK to run the field calculation query. You will now see decimal numbers appear in the x column. Use the same sequence to convert the UTM_Y string values to y, and Elev_m string values to z decimal numbers. Note that in the attribute table string values are left-justified, whereas decimal number values are right-justified. In this example I wound up with a blank column filled with null values so I used the Delete column to remove it. The survey data point shape file is now ready to be used with mathematical gridding algorithms just remember the numeric values are in columns ( x,y, z ). The attribute table should look something like Figure 8. Step 4: Interpolating a elevation surface (DEM) from the survey data. One of the primary goals of the exercise is to produce a digital topographic contour layer, however, all computer contour-generating algorithms need a DEM to produce usable results. A DEM is nothing more than a regularly-spaced (x,y,z) grid where (x,y) are the geographic coordinates of each grid node, and (z) is the value of elevation at that location. The survey data does not qualify as a DEM because the

5 locations are arbitrary, and not part of a rectangular grid pattern. The survey points must be interpolated into the DEM grid. We will use the inverse distance weighted algorithm to do the interpolation because it tends to make a smooth surface much like natural topographic surfaces. At this point open the Processing > Toolbox menu option. Make sure the Advanced Interface is selected at the bottom of the window that opens. You should see a category of processing options labeled SAGA. Expand this tab. Select Raster Creation Tools > Inverse distance weighted interpolation, and then double-click. In this windows dialog there are a lot of options but for our purposes only 3 items need to be edited: 1. The layer to be interpolated should be set to the survey data shape file, in this example GroupXdata. 2. Select is the attribute value to use as elevation: this should be z (or whatever you named the elevation attribute). 3. The grid size should be set to 1.0 meters. This will be the resolution spacing of the DEM along the x and y axes. Figure 9 displays the full window dialog for IDW interpolation with the above changes in effect. Remember that the DEM grid just created is a temporary file that will disappear if we close QGIS. If it looks reasonable then we need to save it: right-click on the Grid layer name and select Save As. In this example I use the name SAGA_DEM_IDW.tif (geotiff format). Make sure that you save it to your working folder. You can now remove the original temporary GRID layer with a right-click, then remove. This completes the DEM creation step. Step 5: Generate the Topographic Contours. We will use the SAGA module Vector <-> Raster > Contours processing tool to generate topographic contours from the DEM. Figure 10 contains the settings for the window dialog. Note that the contour interval is 0.2m so index contours should be every 5 * 0.2m = 1.0m. Remember that on topographic maps index contours should be bolder than other contour lines, and should be labeled. To control the generation of index contours and to label them we will create two additional columns (fields) in the contour line attribute table: Name Type Values 1. Index Integer 1=Index;0=Not index 2. Label String Contour value label string (blank if it is not an index contour) Open the attribute table for contours and add the above columns. The run the calculation query with the field calculator as in Figure 11. You should see all index contours (i.e. 36.0, 37.0, 38.0,.) take on a value of 1, with non-index contour values set to a zero value.

6 In order for the index values to have an effect you need to classify the contours based on the index attribute value. Right-click on the contour lines layer and then choose properties. Used the settings in the Figure 12 window dialog to classify the contours based on the index value. The index line width was set to use the map scale width of 0.7m and the non-index contours 0.3m. The color was set for both to brown as is typical for topographic contours. Next, we will use a calculation query to build labels for the contours: a string equal to the numeric elevation value for index contours, but blank ( ) for non-index contours. Figure 13 contains the window dialog from opening the field calculator tool on the contour lines. Right-click on the contour lines layer name, and then select properties. Configure the window dialog that opens as per Figure 14. Basically you are turning on the labeling for the contour lines layer using the label attribute as the source of the label. Center the label on the line. Note that the repeat spacing was set to 100 map units you may want to experiment with this setting. The Figure 15 map displays the contour lines with labels over the mapping area. Step 6: Hydrologic Modelling As a final step let s use the DEM already generated to model the hydrologic drainage around the project area. The ultimate goal will be to take the drainage map outside and see how well it may correlate with areas in the mapping area that are suffering drainage and erosion problems. There are many hydrology modeling tools built into QGIS, however, we are going to use one of the simpler models: SAGA Terrain Analysis Hydrology > Catchment area (flow tracing). The output of the model will be a raster image that predicts where stream drainage will form in the various catchments in the mapping area. Make sure the Processing Tools window is open and then expand the SAGA collection. Expand the Terrain Analysis Hydrology section and look for Catchment Area (Flow Tracing). The Figure 16 graphic shows the window dialog for this processing tool basically you just input the DEM as the source. Allow it to make a temporary output file. All of the options are set to the default values just make sure the input source is the DEM. You may encounter some minor error messages that can be safely ignored after the model completes. You will have a grayscale image added to the project that represents the drainage patterns in the mapping area. Save this image to the file SAGA_catchment_ft.tif in your working folder (remember that it is just a temporary file presently). We are going to enhance this grayscale image with color : right-click on the image layer name and select properties. In the style area change the render type to single-band pseudocolor. Click the Classify button to add color levels. Figure 17 displays the settings in the window dialog. Note that the transparency is set to 50% so you can see through this layer to base map features (see the transparency tab). The highest values (blue) indicate the stream channels. We will take these maps outside to see how well the correlate with real erosional problem areas.

7 Step 7: Printing results I want each group to print a hard copy map of the start data with DEM and contours and survey points plotted (see Figure 18). Do not have the stream catchment raster on for this map. In Figure 18 you will see the map in a cleaned up state: 1. Layer names have been spelled out, as have contour categories. 2. The grayscale DEM has been changed to a single-band pseudo color with colors arranged at equal elevations increments. See if you can do the same in the properties > style section of this layer. Note the following: a. Initially after changing from single-band grayscale to color you need to set the min=35 and max = 60 to take in the full range of the DEM. Your values may be somewhat different depending on the data you collected- try to set a min an max that is a multiple of 5m. b. The color ramp selected was spectral. c. Select mode = equal interval. d. Classes = 6 (or whatever number gives to a 5m interval) e. Note that the inverted checkbox is checked to make the maximum elevations a red color. f. You should have a setup that looks like Figure 19. g. Note that it took some effort to setup the style for the DEM layer. You can save the Style to a file to be re-used later in case you do a similar DEM and want the same settings- see the Style button. You will also note that the topographic contours have been clipped to the mapping boundary. There is an automatic way to do this in the Vector > Geoprocessing Tools menu. Try to accomplish this on your own using the Project Area polygon as the clipping boundary. It is probably best to let the clipping result default to a temporary result, verify that the result is what is desired, and then right-click on the layer name and select Save As to save to a file in your working directory. Don t forget to remove the temporary layer from the project. This is where saving the layer style can pay dividends because it took some time to create the style symbology for the contours layer. Go to the Properties > Style settings for this layer and save the style to a contours.qml file. When you generate the clipped contours layer you can set the style by loading the contours.qml file from the style button. Make sure your final map is cleaned up like Figure 18 before getting setup for printing. In the QGIS system to use the Project > New Print Composer to create a print composition window. You use the composer to add a legend, scale bar, etc., to complete the map so you must become familiar with how this works to make the final map. When you make a new map composition you will

8 first be asked for the name of the map composition use a name like Layout1. You will then see a new window activated where the final map will built. Follow these steps to build the map layout: 1. Use the Layout > Add Map to drag a rectangle area for the map frame. Use a RF of 1:2500 to set the scale of the drawing. Leave enough room for an upper title, lower scale bar, and a legend in the right side of the layout. The page layout should be landscape. You may need to use the Move item content to center the map in the frame. 2. Use the Layout > Add Arrow to insert a North Arrow in the upper left corner of the layout. Use the Layout > Add Label to insert an N below the arrow. 3. Use the Layout > Add Scalebar menu selection to add a scale bar centered below the map frame. 4. Use the Layout > Add Legend menu selection to add a legend frame along the right side of the layout. With the legend frame selected uncheck the auto-update checkbox this will allow you to remove any unwanted legend items. 5. Select the main map frame and then scroll down the Items tab until the Grid item is visible. Use the + button to create a new grid named grid1. Use an (X,Y) spacing of 50 meters for the grid. Turn on the Draw coordinates checkbox, and then select a Custom format. Use the following expression in the expression window: to set the number of decimals to 0. You should have the map layout similar to Figure 20. Add your group number and the members of the group in the lower right with the label tool and use Project > Print to make a hard copy to turn in.

9 Figure 1: QGIS map window after inserting given vector and raster files.

10 Figure 2: Setting the project coordinate system (CRS=UTM NAD27 zone 16).

11 Figure 3: Format of the example Excel data file.

12 Figure 4: Window dialog for adding an Excel survey data to the project as points.

13 Figure 5: Window dialog for saving the temporary Excel import file as an ESRI shape file.

14 Figure 6: Defining a new floating point column in the shape file.

15 Figure 7: Window dialog for converting string values to decimal numbers in the point shape file.

16 Figure 8: Layout of survey data point shape file with numeric "x", "y", and "z" fields added.

17 Figure 9: SAGA IDW interpolation window dialog settings for creating the DEM from survey data.

18 Figure 10: Contour generation dialog window for SAGA: Vector <-> Raster > Contour lines.

19 Figure 11: Calculation query setup for computing the index column values: 1=index contour, 0= non-index contour.

20 Figure 12: Categorizing the contours lines into index and non-index symbology with the "index" attribute.

21 Figure 13: Field calculation for the label field.

22 Figure 14: Label setup for the contour lines layer.

23 Figure 15: Appearance of map with contour lines labeled.

24 Figure 16: Window dialog for the SAGA Catchment area (flow tracing) processing tool.

25 Figure 17: Setting the style properties of the catchment raster.

26 Figure 18: Cleaned up version of the map prior to printing setup.

27 Figure 19: Window dialog setup for the DEM style.

28 Figure 20: Map layout for printing.