Download Visualization and Management - Water Management - Lecture Slide and more Slides Water and Wastewater Engineering in PDF only on Docsity! Conservation Applications of LiDAR Basics of Using LiDAR Data Exercise #3: Visualization and Management This exercise was developed as part of the “Conservation Applications of LiDAR” project – a series of hands‐on workshops and online resources designed to help Minnesota GIS specialists effectively use LiDAR‐derived data to address natural resource issues. The project was funded by a grant from the Environment and Natural Resources Trust Fund, and was presented by the University of Minnesota Water Resources Center with expertise provided from the University of Minnesota, MN Department of Natural Resources, MN Board of Water and Soil Resources, and USDA Natural Resources Conservation Service. More information is at Docsity.com 2 Data Visualization and Management (Exercise 3 of “Basics of Using LiDAR Data”) Basics of Using LiDAR Data Exercise #3: Visualization and Management Exercise 3: Visualization and Management .......................................................................................... 3 A. Using LiDAR Data .................................................................................................................................. 3 Load Data .............................................................................................................................................. 3 Bare Earth Points .................................................................................................................................. 4 B. Display Techniques ............................................................................................................................... 7 Default Layer Properties ....................................................................................................................... 7 Stretch Types ........................................................................................................................................ 7 Statistics Calculations............................................................................................................................ 8 Adding Color ......................................................................................................................................... 8 Adding Depth and 3D Effect ................................................................................................................. 9 C. Visualization / Comparative Techniques ............................................................................................... 9 Orthophoto/DEM Comparison ............................................................................................................. 9 Add MNGEO Web Map Service (WMS) ................................................................................................ 9 Swipe ................................................................................................................................................... 10 D. Managing Large Datasets ................................................................................................................... 11 Basic Tips ............................................................................................................................................. 11 Strategy ‐ Divide, Then Conquer ......................................................................................................... 12 Batch Processing ................................................................................................................................. 12 Docsity.com 5 Data Visualization and Management (Exercise 3 of “Basics of Using LiDAR Data”) The following function can also be applied to larger selections or clipped areas, but keep the area small to avoid long processing times. 4. Go into ArcToolbox , double‐click Data Management Tools Features Multipart to Singlepart. 5. Input features should be Bare_Earth_Points. 6. Output feature class should be (your folder)\raw_data\single. 7. Click o.k. After processing, you will have a new layer named “single” with 3500 records – all the points associated with the original record selected from the Bare_Earth_Points layer. Next, we’ll get the elevation data for the single points. 8. Go into ArcToolbox , double‐click Data Management Fields Add Field tool add a field called “Elevation”. Set the field type to “FLOAT” as shown below. Leave all other fields to default settings. Click OK. Docsity.com 6 Data Visualization and Management (Exercise 3 of “Basics of Using LiDAR Data”) 9. Now, right click the field you just created in the table, and select Calculate Geometry. 10. You will be warned that all changes will be made permanent, select “yes”. 11. Now, select the geometry that you’d like to calculate for “elevation” by selecting “Z coordinate of point” under Property. Click OK. Docsity.com 7 Data Visualization and Management (Exercise 3 of “Basics of Using LiDAR Data”) B. Display Techniques Default Layer Properties Default or Standard Display o Limits “stretch” display to 2 Standard Deviations Statistics Drive Display – based on histogram from entire DEM Predefined color ramps – grayscale standard Nearest Neighbor Resampling performed in the background when manipulating layer properties Most display variables changed in Layer Properties Symbology Tab The standard display of any LiDAR dataset or derived product can typically be improved by using a few tools in ArcGIS. For all continuous datasets, contrast stretches can be applied by changing “stretch‐type” to increase visual contrast of a portion of the landscape. The various stretch‐types as listed below utilize the values histogram of the dataset to manipulate display by highlighting or subduing certain portions of the color‐ramp. The result, depending on your selection, is a customized display that amplifies the contrast based on the features you’d like to study more closely. Stretch Types 1. Select the DEM Layer, right‐click PropertiesSymbology tab. 2. Under “stretched” view the “Histograms” button. When you adjust the histogram, you see multiple sets of vertical bars: the purple bars represent the current display values, and the gray bars represent your original values. 3. Examine how “stretch” type affects display by selecting each of the following and zooming in, paying careful attention to the notes for each one: o Custom or Histogram Specification – Manually defined – not recommended o Standard Deviations – Standard display o Histogram Equalize – This setting accentuates minor variations – uplands in this case – by applying the value display equally across the entire histogram o Minimum/Maximum – This setting accentuates larger variations in relief ‐ dendritic drainage in this case – by visually ignoring the tails of the histogram 4. Gamma – This can be used with Standard Deviation or Min/Max stretch types. By applying a gamma correction, you can control the overall brightness of a raster dataset, to enhance the overall contrast and interpretation of the image. Docsity.com 10 Data Visualization and Management (Exercise 3 of “Basics of Using LiDAR Data”) 4. To bring up the Imagery server, type http://geoint.lmic.state.mn.us/cgi‐bin/wms? in the URL window. You can click on the 'Layers' button to see a list of the layers available under the wms. Click 'OK'. 5. To bring up the Scanned DRG server, type http://geoint.lmic.state.mn.us/cgi‐bin/wmsz? in the URL window. You can hit the 'Get Layers' button to see a list of the layers available under the wms. Click 'OK'. 6. Now when you look under 'GIS Servers' you have two new entries: 'LMIC WMS server (aerial photography) on geoint.lmic.state.mn.us' and 'LMIC WMS server (quad sheet drgs) on geoint.lmic.state.mn.us' 7. Still in the 'Add Data' window under 'GIS Servers', highlight one of the services listed under #6 to bring it into the 'Name' window, then click on 'Add'. The service, with all of its layers, has now been added to your ArcMap project. 8. Click on the '+' to open the map service Swipe 1. To display the Effects Toolbar, right‐click anywhere in the toolbar and select Effects. 2. Select the Swipe Tool to "wipe" a layer using a horizontal or vertical line across the screen. 3. Make sure the layer you want to "swipe" is shown in the "Layer:" box. 4. Click on the map and drag to swipe (do not release mouse button; the mouse must be depressed to get the swipe effect.) Example of swipe: Docsity.com 11 Data Visualization and Management (Exercise 3 of “Basics of Using LiDAR Data”) D. Managing Large Datasets Basic Tips o Gear up – Ease of use is often hardware dependent o CPU – multiple core, fast processors o RAM – 64 bit systems allow more RAM – upgrade o Disks – High speed, large – cheap! o Work locally – network speed, USB cables, etc. slow down processing o Allow 20% overage for storage space – ensures better disk functionality, along with the option to defrag or disk check for bad sectors o Store source elevation information only if space is available – download is fast and easy o Avoid display of multiple LiDAR scenes – hang‐ups o Image Analysis – Accelerated rendering, test this with larger display datasets o Calculate BOTH Statistics AND Pyramids for faster drawing later o Backup – external hard drives cheap, failing to archive data it took days to process is not o Contour data can clutter screen, set appropriate scale range limiters such as 1:10,000 Docsity.com 12 Data Visualization and Management (Exercise 3 of “Basics of Using LiDAR Data”) Strategy ‐ Divide, Then Conquer A critical concept in working with LiDAR data involves using “pilot areas” to test processing techniques and methodology on before applying to entire dataset. The “try it and see” approach to LiDAR processing is frustrating and time consuming. Once processing steps have been tested on smaller areas, utilize batch processing or scripting to maximize “autopilot” overnight processing. Batch Processing o Great tactic for processing any dataset which requires running the same tool against a large number of areas o With LiDAR data, the limitation is often the processing speed in which a single dataset can be run o Processing in these smaller chunks is more efficient should files be missing, corrupt, or otherwise unstable o Batch processing is VERY user‐friendly and non‐intimidating for those who don’t write code Document version: February 2013 Docsity.com