Slope Modeling & Terrain Analysis (EPAN09)
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The document summarizes a project to create an accurate slope model for Jefferson County, West Virginia using Light Detection and Ranging (LiDAR) data. Field measurements of slope were taken at 34 locations and compared to slope models derived from 10-meter, 3-meter, and 1-meter digital elevation models. The 1-meter LiDAR data was found to most accurately represent the terrain with a higher R2 value and finer detail. The created slope model using this data could potentially be used for planning purposes when combined with other data layers.
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Slope Modeling & Terrain Analysis (EPAN09)
- 1. What’s Your Angle? Slope Modeling & Terrain Analysis Jessica Gormont & Rachel Shirley 3 rd Eastern Panhandle, West Virginia GIS Users Group Meeting September 18, 2009
- 9. DEFINITIONS - LIDAR Photo Source: Dewberry LiDAR ( Li ght D etection A nd R anging) is an optical remote sensing technology that utilizes light to gather topographic data . DEM Hillshade
- 17. 10-m NED DEM (USGS)
- 18. 3-m NED DEM (USGS)
- 19. 1-m LiDAR DEM (USDA-NRCS)
- 20. RESOLUTION PROGRESSION 10-m Slope 3-m Slope 1-m Slope
- 24. ZOOMING IN…
- 25. BLUE RIDGE ELEMENTARY SCHOOL Field Slope = 22% Slope Model = 16 – 24%
- 27. TRUE 3D LINE OF SIGHT ANALYSIS
- 28. HIGH RESOLUTION LAND COVER
Editor's Notes
- Blue Ridge has always been a planning concern due to its unique topography, geology, and land development patterns. Recently the County Commission tasked our office with creating new data layers that will aid planning staff and the public more easily analyze areas on the Blue Ridge and in the county as a whole when planning development. These layers include slope, 2ft topographic contours, and land cover.
- This project was the first step in the data creation process. It’s purpose was… Once we have slope completed, we will go on to generate 2 ft contours, and we have already contracted out to produce land cover data. We hope to have everything ready by the end of the year.
- The focus of this study was the Blue Ridge Mountain Area. This area contains all land in the county east of the Shenandoah River. Affectionately known as “The Mountain” to locals, it is the only part of the county located within the Appalachian Chain; the rest of the county is part of the Shenandoah Valley. Elevation -> lowest point located at junction of two rivers, Shenandoah and Potomac Addresses -> largely located in two main areas which we call Shannondale and Keyes Ferry Acres; much of the southern portion of the mountain is wildlife management areas
- Currently slope is done on an individual parcel basis. Generally, the owner or developer of the property must provide 2-ft contours and an engineer has to hand calculate the slope of the parcel. This can be quite time consuming and expensive for the owner. Using GIS, we can generate slope over large areas very quickly. The entire county can be done in about a day. Since the computer is calculating the data, there is little chance for human error. Also, the GIS software allows for overlays of the slope data with other land conditions, such as geology, tree cover, nearby water bodies. This can give a greater understanding of how development will impact the area.
- Upper Section Rail 25° = 47% Every 100’ run = 47’ rise Lower Section Rail 5° = 9% Every 100’ run = 9’ rise
- Checked 3 slope models against ground truth to determine the accuracy of each. Hawths Analysis Tools – mimicked the way slope is currently calculated
- represented
- Vertical accuracy of GPS not important, using GPS strictly for cartographic purposes
- We created three slope models in total, the 1 st one using a 10-meter DEM… As you can see, the accuracy is significantly better with the 1-m LIDAR data
- The process used to determine the slopes for each model was… R 2 is the “coefficient of determination”, and is the percent of variation of one variable that is explained by the other
- The graphs turned out as… We were trying to graphically depict the correlation between the model slope and the field slope; the field slope is on the x axis and the model slope is on the y axis. We added a trendline to show the correlation between the two slope methods. The closer the R2 value is to 1, the better
- This slide shows how the resolution increased between the different DEMs. There are many more elevation points in the 1-m DEM which gives a more accurate representation of the Earth.
- All of the DEMs created had high R2 values, which indicates that each alone can be used for slope analysis, but since the 1-m is available, it would be the best dataset to use.
- R 2 is often in the 50-60% range in scientific analysis, so 97% is generally good. Is shows the 1-m data is more accurate because it directly ties to the field data. We were somewhat surprised that the 3-m and 10-m values were so similar, but it just be where the points fell.
- Green lower slope, red highest
- The slope is mostly made up of green which is in the 16 to 24 range, and the field slope calculated was 22%, which shows there is a good correlation between the 1-meter data and the field.
- At viewshed – Historic Landmarks Commission interested in using terrain data for line of sight analysis
- Base layer: digital surface model )DSM) 1 st Click: areas visible from a 40ft high tower on top of the Blue Ridge Elementary School. (Note: does not indicate signal propagation).
- 1 st click: 2007 color infrared (CIR) aerial imagery from the National Agricultural Imagery Program (NAIP). NAIP provides important spectral (color) cues to distinguish between vegetated and non-vegetated areas. 2 nd click: 2005 normalized digital surface model (nDSM) derived from LiDAR. The nDSM represents the height of features relative to the ground (blue is ground, yellow to red indicates increasing height). 3 rd click: 2005 intensity image derived from LiDAR. While it appears similar to a black and white orthophoto the intensity image shows the strength of the LiDAR signal. This information is useful for separating out impervious surfaces from bare soil. 4 th click: land cover data. Automated techniques were used to extract land cover information for Jefferson County. The resulting land cover dataset contains over 1 billion pixels (1,157,175,600 to be precise). This picture shows the early stage Land Cover data for the Blue Ridge Elementary School area.
- We would like to thank our project members. The 1 st 3 guided us through the project, and the last 3 peer-reviewed our methodologies.