Visualizing and Analyzing Landform Change of Surface Coal
Mines
Cowen, WV
Introduction
Surface mining for mineral resources requires that the soil and rock layers be removed in order to
gain access to the mineral deposit. Depending upon the depth of the mineral resources this can
mean moving hundreds of feet of soil and rock. According to current law, this soil and rock
known as overburden or spoil has to be placed back to the approximate original contour. The
definition of approximate original contour, as found in the Surface Mining and Coal Reclamation
Act of 1977 (SMCRA) requires that the final surface configuration, after backfilling and grading,
closely resemble the general surface configuration of the land prior to mining while maintaining
the necessary flexibility to accommodate site specific conditions.
Surface mining for coal in West Virginia has caused dramatic changes to the landforms of the
Appalachian Mountains in addition to changes in the ecosystem and land cover. Some parts of
the mine are lowered in elevation and some parts are raised in elevation. Some areas of
headwaters streams are filled with overburden and these are known as valley fills. Remote
sensing technology enables the detection of these changes over time using photogrammetry and
lidar. This exercise is designed to visualize and analyze changes to the landforms caused by
surface mining. By completing this exercise students will have a better understanding of the
changes to the terrain caused by surface mining.
Objectives
This exercise is designed to support the objective of the iGETT-RS project. The objective of the
iGETT-RS project is to integrate Remote Sensing (RS) with Geographic Information Systems
(GIS). The specific student learning objectives of this exercise are the following:
1. Understand remote sensing elevation data that is available for use in a GIS.
2. Learn about the use of digital elevation model(dem) and lidar data for analysis
3. Utilize the 3D Analyst tools available in ArcGIS
4. Analyze dem raster data to create slope and contour maps
5. Analyze dem raster data to detect changes in elevation and landforms
6. Understand how surface mining changes mountainous landforms
Developed by the Integrated Geospatial Education and Technology Training (iGETT) project, with
funding from the National Science Foundation (DUE-1205069) to the National Council for Geographic
Education. Opinions expressed are those of the author and are not endorsed by NSF. Available for
educational use only. See http://igett.delmar.edu for additional remote sensing exercises and other
teaching materials. Author: Brian Perkins Last modified June 12, 2014.
Part 1 Visualizing Landform Change Workflow
Download Data
Edit Mine
Boundary
Select &
Download Lidar
Data
Mosaic & Clip
Pre-Mining DEM
Create PreMining Slope &
Contour
Create Lidar
Dataset
Convert Lidar
Dataset to DEM
Raster
Clip Post-Mining
DEM Raster
Create PostMining Slope &
Contour
Create Elevation
Change DEM
Raster
Reclassify Raster
& Calculate
Acreage Changed
Create Pre & Post
Mining Profile
Graphs
Part 2 Analyzing Landform Change Workflow
Download
Software
Install Software
Read
Instruction
Manual
Create Pre &
Post Mining TPI
Raster
Classify Pre &
Post Mining
Landforms
Quantify
Change in
Landforms
Students will download data. Students will analyze 2003 (pre-mining) digital elevation model
(dem) data to create slope rasters and contour shapefiles. Students will create a LAS dataset with
lidar files (post mining) and convert the dataset to a raster (dem). Students will then create slope
rasters and contour shapefiles from the dem derived from lidar data. Students will view and
calculate rasters to examine changes in landforms caused by surface mining. Students will create
profile graphs using the 3D Analyst toolbar. Students will calculate the topographic position
index (TPI) and classify and quantify landforms.
Download Data
There are a number of files that have to be downloaded in order to complete this exercise. A
high speed internet connection is recommended because some of the files are large.
Pre-Mining Data
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The pre-mining elevation data is available from the WV GIS Technical Center.
The name of the dataset is Digital Elevation Models (USGS 3-meter) – 2003.
The website address is: http://wvgis.wvu.edu/data/dataset.php?ID=261.
There are 3 options for downloading the dem data.
Choose the 2nd option below which is “Compressed DEMs UTM NAD83 – Vertical Units in
Feet”
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Find and download the following zip files: cowen_wv_USGSAndSAMB_2003_utm83.zip
and erbacon_wv_USGSAndSAMB_2003_utm83.zip.
Extract the zip files into a new folder with its default name.
After extracting there should be 3 files in each folder and one of them will be a .dem file.
Add the 2 dem files to ArcMap.
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Post Mining Data
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Please note that this is an active mine and therefore the post mining data is actually a
misnomer. The lidar data was collected from November 2010 – January 2011. Therefore,
we will be able to see changes during a seven year period.
The post-mining elevation data is available from the WV View.
The website is http://www.wvview.org/wvview-data%20services.htm
The name of the dataset is Webster County Lidar:
http://www.wvview.org/lidar_webster.html.
Each lidar dataset is tiled and numbered so that only the data of interest can be downloaded.
Therefore the lidar tiles have to be accessed prior to downloading the actual lidar files.
Download the tiles: http://www.wvview.org/data/lidar/Webster/LAS/Webster_tiling_scheme.zip
Extract the zip file into a new folder with the default name
First we have to identify the area of interest which we will determine in the Analysis section
below.
Once we know which lidar files to download they can be accessed from this website:
http://www.wvview.org/data/lidar/Webster/LAS/Bare_earth/
Mining Permit Boundary & Valley Fills
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The boundary of the surface mine is available from the WV Department of Environmental
Protection at this website: http://tagis.dep.wv.gov/home/Downloads
The name of the dataset is Mining Permit Boundaries.
Download and extract the zip file http://tagis.dep.wv.gov/data/vector/perbd.zip
The other dataset of interest is the Excess Spoil (Valley) Fills.
Download and extract the zip file: http://tagis.dep.wv.gov/data/vector/vallf.zip
Part 1. Visualizing Landform Change
Mine Boundary
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Open ArcMap
Add perbd.shp file
Right click on file name in table of contents
Select data and export data
We will create a new copy of the shapefile since we want to modify it.
Accept the defaults and save the output feature class file as perbd_brooksrun.shp
Add the exported data to ArcMap as a layer
Now we will select the surface mine of interest. In this case the mine is operated by Brooks Run
Mining, LLC and is known as Seven Pines Mine.
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Open the editor toolbar and start editing
Open the attribute table of the perbd_brooksrun.shp file
Select all records which will highlight the records as shown below:
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Find the 4915 record in the FID field.
Unselect the 4915 record. This is the Seven Pines Mine and the boundary associated with
this permit. This boundary will form our area of interest.
See screenshot below:
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Delete all of the select records by choosing the right icon from the menu options at the top.
Your attribute table should just have one record (4915) as shown below:
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Close the attribute table and zoom to layer. Your ArcMap should look like the following:
This is the permit boundary of the Seven Pines Mine. We will use this to select our lidar files.
Select Lidar Data
We now have to determine which lidar files cover the surface mine. We do this by using the
lidar tiles that we downloaded earlier.
 Add the Webster_tiling_scheme.shp file to ArcMap
 This file shows the footprint of all of the lidar files on this particular project. As shown in
the screenshot below, 9 lidar files cover the surface mine with the exception of a short length
of haul road.
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Identify and record the name of each lidar tile
For example, the upper left corner tile is named: WS_ortho615
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The 615 signifies the lidar file number.
Record the file numbers for all 9 tiles:
_________________
_________________
_________________
_________________
_________________
_________________
_________________
_________________
_________________
Now we can download the 9 lidar las files from the WV View website:
http://www.wvview.org/data/lidar/Webster/LAS/Bare_earth/
Find and save all 9 lidar las files. Save them in a new folder called “lidar data”
Mosaic the Pre-Mining Data
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Add the pre-mining dem files: cowen_wv_USGSAndSAMB_2003_utm83.dem and
erbacon_wv_USGSAndSAMB_2003_utm83.dem
ArcMap should look like the following screenshot
Dark areas are lower elevation while lighter areas are higher elevation. The drainage pattern in
this region of West Virginia is known as dendritic, an essentially random type of drainage
pattern.
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The two dem files will have to be combined prior to doing any analysis
The Mosaic to New Raster function will combine the two rasters
Open ArcToolobx and open the Data Management toolbox
Open the Raster folder and then open the Raster Dataset folder
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Select the Mosaic to New Raster tool
Select the Cowen and Erbacon dem for the input rasters
Specify the output location as a new folder called cowen&erbacon_dem
The raster dataset name should be cowen&erbacon
The number of bands is 1
Accept all other defaults
The output should look like the following. Two rasters have been combined into one
seamless raster:
The next step is to clip the raster to the boundary of the surface mine. Prior to using the
boundary for the raster extraction, you will need to remove the internal parts of the polygon.
 Start editing perbd_brooksrunsurfacemine layer
 Double click on the polygon and edit sketch properties.
 Remove all parts except part 0.
 After removing the internal parts the boundary should look like the following:
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To analyze the elevation data within the mine boundary we will extract the elevation data
within the mine boundary.
The tool to use here is called Extract by Mask
Open ArcToolbox, Spatial Analyst toolbox, and Extraction toolbox
cowen&erbacon is the input raster
perbd_brooksrunsurfacemine is the feature mask
Specify a new raster with the file name of mine_dem
Now we have the pre-mining elevation data within the mining boundary
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Dem files are difficult to visualize so we will make a slope map and a contour map.
Open ArcToolbox and open the 3D Analyst toolbox
Make sure the 3D Analyst extension is turned on under the customize menu.
Open the Raster Surface toolbox and create a slope map using the mine_dem file
Accept the defaults and name the file premine_slope
After zooming to the mine boundary your ArcMap should looking like the following:
The default classification and color ramp shows steep slopes in dark red and gentle slopes in
green. As we can see there isn’t much flat land in this area. Only the valleys have gentle slopes
as shown in green in this pre-mining image.
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Examine the data of the slope layer by looking at the symbology
Click on the Symbology tab under layer properties window
Click on classify button
The default is natural breaks (Jenks) with 9 classes
What is the minimum slope?
What is the maximum slope?
What is the average slope?
Next we will create a contour shapefile which will help us visualize the landforms found in the
pre-mining mountainous terrain
 Open ArcToolbox and open the 3D Analyst toolbox
 Open the Raster Surface toolbox and create a contour map using the mine_dem file
 The input raster is the mine_dem
 Name the output file as premine_contour.shp
 The contour interval should be 20 foot
 Accept all other defaults
After zooming in a little bit we can see the pre-mining landforms consisting on numerous ridges
and valleys creating a dendritic drainage pattern. Streams and valleys are indicated by Vs that
point up the valley. Broad flat ridges are indicated by wide spacing between contour lines.
Ridges are also indicated by Us that point downhill. Close spacing of contour lines indicates
steep slopes whereas wide spacing of contour lines indicates gentle slopes. Notice how the
ridges connect and create the coves and valleys typically found in this region.
Examine Post Mining Data
Now we will work with the lidar data and create a new LAS Dataset which enables for quick
viewing of large amount of lidar data
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Open ArcToolbox and open the Data
Management toolbox
Open the LAS Dataset toolbox
Select create LAS Dataset
Browse for the files where you place the 9
lidar files
Add all 9 lidar files to the dataset
Name the dataset post-mining_lasdataset.lasd
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Once you create the LAS Dataset your ArcMap should look like the following:
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You have to zoom to full resolution (by right clicking on dataset) to see the lidar data:
You can clearly see roads and valley fills that have been built. We will now use the LAS Dataset
to create a raster so that we can compare the pre and post mining slopes and contours.
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Open Arc Toolbox and open Conversions Toolbox
Open To Raster Toolbox
Select LAS Dataset to Raster
Specify the output raster name as post-mine_dem
Accept all of the defaults except for sampling value and z factor
The sampling value should be 3 since the pre-mining dem is a 3 meter dem
The pre-mining dem is in feet so we need the post mining dem in feet as well. The LAS
Dataset is in meters. So we must convert meters into feet. 1 meter = 3.28084 feet
So our z factor should be 3.28084
Click Ok
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Your ArcMap should look something like the following:
Now we will clip the post-mine_dem to the boundary of the surface mine.
 Open ArcToolbox, Spatial Analyst toolbox, and Extraction toolbox
 Post-mine_dem is the input raster
 perbd_brooksrunsurfacemine is the feature mask
 Specify a new raster with the file name of postclipdem
 Now we have the post-mining elevation data within the mining boundary
Examine the differences between the pre-mining dem and the post-mining dem. Look for
differences at the dark areas near the heads of valleys.
Pre-Mining DEM
Post-Mining DEM
What differences do you see?
Has the average elevation of the mine site changed? (Hint: look at the statistics in the
properties)
Now we will create a slope map using the postclipdem
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Open ArcToolbox
Open 3D Analyst Toolbox and open Raster Surface Toolbox
Select Slope
postclipdem is the input raster
Specify the file name as postmineslope
Z factor should be 1
Accept all other defaults
Your ArcMap should look like the following
Again we can compare the pre-mining slope to the post-mining slope. Toggle between the premining slope layer and the post-mining slope layer. How has the slope of the land changed
within the mining area?
Pre-Mining Slope
Post-Mining Slope
What is the pre-mining and post-mining average slopes? (Hint: go to Properties, Source and
view Statistics)
Now we can create a post-mining contour shapefile to compare the changes in landforms.
 Open ArcToolbox and open the 3D Analyst toolbox
 Open the Raster Surface toolbox and create a contour map using the postclipdem file
 The input raster is the postclipdem
 Name the output file as postmine_contour.shp
 The contour interval should be 20 foot
 Accept all other defaults
A side by side comparison of the pre and post mining contour shows the dramatic change in
landforms.
Pre-Mining Contour
Post-Mining Contour
Describe the change in landforms that you see when comparing the pre and post contour maps.
DEMs from two different time periods can be directly compared by mathematical equations. In
this case we will subtract one raster from another to see the changes in elevation that have taken
place.
 Open Arc Toolbox
 Open 3D Analyst Toolbox
 Open Raster Math Toolbox
 Select Minus
 The post-mine dem (filename: postmineclip) should be the first input raster
 The pre-mine dem (filename: mine_dem) should be the second input raster
 Specify the filename as minus_dem
 After adjusting symbology, Your ArcMap should look like the following:
Areas of green and dark green gained in elevation. These are the valley areas which were filled
with mining spoils. Areas of white show only a small (-30’ to 40’) change in elevation whereas
areas in red and dark red show a loss in elevation. By adding the valley fill shapefile that was
downloaded earlier we can see that the areas of elevation gain correspond to the valley fills
mapped by the WV DEP. Valley fills are shown as a dotted line.
We know that some areas of the surface mine have changed in elevation but to what extent?
Next we will determine the acreage of the areas that have gained or lost elevation. In order to do
so we need to reclassify the raster from floating point data type into integer data type.
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Open Arc Toolbox
Open 3D Analyst Toolbox
Open Raster Reclass Toolbox
Select Reclassify
The input raster should be the minus_dem
The classes should automatically form
The output raster should be named reclass_dem
Accept all other defaults
We can now open the attribute table and calculate the areas of each class.
 Add a field to the attribute table called Acreage
 It should be the double type field
 Right click on the Acreage column title and select Field Calculator
 Create the following formula in the field calculator
 Acreage = [COUNT] *9 *0.0002471
In order to calculate acreage of each class, we are multiplying the number of pixels by the
pixel area (3 meters x 3 meters = 9m2 ) and then converting from square meters to acres by
multiplying by 0.0002471.
 Click Ok
 Fill in your answer below
Elevation Change
Acreage
-274’ to -106’
-105’ to -31’=
-30’ to 41’
42’ to 137’
138’ to 339’
There is another way that landform changes can be visualized using 3D Analyst. This is by
interpolating elevations along a line and then viewing it in profile. This is like taking a slice
through the surface mine. Like the other comparisons we will look at a pre-mine profile and a
post-mine profile.
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Open the 3D Analyst toolbar
Select the pre-mine dem in the drop down box
Select the fifth icon to the right of the drop down box
Next draw a line all the way across the surface mine much like the one shown below:
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Now select the profile graph icon and this will create a graph showing the profile of the dem
prior to mining.
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Your graph should look something like the following:
Pre-Mine DEM Profile Graph
2,500
2,450
2,400
2,350
2,300
2,250
2,200
2,150
2,100
2,050
2,000
1,950
0
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200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
2,200
2,400
2,600
2,800
3,000
Modify the properties of your graph and title it: Pre-Mine DEM Profile Graph. Save the
graph with that filename as well.
Now it is time to repeat the process but this time select the post-mine dem in the drop down
box
Draw another line across the surface mine. Be sure to use the vertices of your previous line
to get an accurate comparison
Create another profile graph. Name it: Post-Mine DEM Profile Graph. Save the graph with
that filename as well.
Post-mine DEM Profile Graph
2,500
2,450
2,400
2,350
2,300
2,250
2,200
2,150
2,100
0
200
400
600
800
1,000
1,200
1,400
1,600
1,800
2,000
2,200
2,400
2,600
2,800
How much did the first valley from the left side of the profile graph change in elevation?
How much did the second peak from the left side of the profile graph change in elevation?
3,000
Part 2. Analyzing Landform Change
Introduction
This part of the exercise analyzes and quantifies the landforms on the mine site prior to mining
and after mining. The topographic position index (TPI) is a method to determine the relative
position of a topographic feature. The TPI compares the elevation of each cell in a DEM to the
mean elevation of a specified neighborhood around that cell. The topographic position index
was created by Andrew Weiss and presented at an ESRI user conference. The methodology was
further refined and incorporated in an extension for ArcView 3.x by Jeff Jenness of Jenness
Enterprises.
Jenness Enterprises then created a Land Facet Corridor Designer, which included the functions
of creating a topographic position index and classifying landforms into categories based on
digital elevation models. This software won 2nd Place, Best Desktop Application at the 2010
ESRI International User Conference in San Diego, CA. It was also featured in the Fall 2010
Edition of ArcNews. The use of topographic position index and classification of landforms will
be used to analyze the change in landforms due to surface mining.
Software
The Land Facet Corridor Designer, is free to download from Jenness Enterprises. The designer
works as an ArcMap toolbar. The toolbar can be download here:
http://www.jennessent.com/arcgis/land_facets.htm. After downloading and extracting the folder,
follow the installation directions in the read me file. ArcMap must be closed while you are
installing the software. After successful installation, open ArcMap and turn on the Land Facet
Analysis toolbar. It looks like the following:
The manual can be accessed here: http://www.jennessent.com/downloads/Land_Facet_Tools.pdf.
Read pages 49 – 62 of the manual to understand the topographic position index tool. For further
background on the topographic position index and classifying landforms refer to the Weiss
poster: http://www.jennessent.com/downloads/TPI-poster-TNC_18x22.pdf
Analysis
First we will create a topographic position index for the pre-mining dem and the post mining
dem.
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Mouse over the toolbar and select the topographic position
index tools
Select Create TPI Raster
Select the pre-mining dem (mine_dem) for the raster layer
Use the TPI under the TPI type
The neighborhood shape should be circle
The neighborhood size units should be cells
Enter 5 for the Neighborhood radius
Accept all other defaults
Create a new folder called TPI Data
Name the file premine_tpi
Click Ok
The output should look like the following:
Ridge landforms are shown in red and valleys are shown in green. The units of the TPI raster
are in feet derived from the dem. A ridge cell with a value of 25 means that that cell is 25
feet above the average surrounding neighborhood cells. Likewise a valley cell with a value
of -20 means that that cell is 20 feet below the average surrounding neighborhood cells.
Slopes are shown in a tan color in the image above.
How would you describe the ridges and valleys in the topographic position index?
Now repeat the steps above and create a TPI raster for the post-mining dem using the
postclipdem file. Use the same values and settings. Name your file postmine_tpi. Your
output should look the following:
How have the ridge and valley landforms been changed due to surface mining?
Now we will classify the landforms based upon the TPI and slope of the dem into 4 classes of
landforms for the pre-mining and post-mining dem files. This will allow us to quantify the
area of valleys, gentle slopes, steep slopes and ridges before and after mining.
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Select the topographic position index tools from the toolbar
Select the topographic position, 4 category option
Select the Reset Class Names button
Change class 1 to Valleys
Utilize the pre-mining dem file (mine_dem)
Neighborhood options should be circle, cells and a radius of 5
Set the following parameters: A = -6; B = 6; S = 20
Name your output file premine_4cat
Click Ok
Your output should look like the following:
Valleys are shown in light blue, gentle slopes in light tan, steep slopes in green and ridges in
light red. In this pre-mining landform classification we can see that most of the landforms are in
their natural state.
Now repeat the process above to create a post-mining 4 category landform classification. Use
the postclipdem file. Use the same values and settings. Name your output file as postmine_4cat.
Your output should look like the following:
As we can see, there is a lot more gentle slope landforms, fewer natural valleys and ridges after
surface mining has occurred. The last step is to quantify this change.
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Open the attribute table of the premine_4cat file and calculate the acreage of each landform
Create a new field called Acreage of the double type
Right click on the Acreage column title and select Field Calculator
Create the following formula in the field calculator
Acreage = [COUNT] *9 *0.0002471
In order to calculate acreage of each class, we are multiplying the number of pixels by the
pixel area (3 meters x 3 meters = 9m2 ) and then converting from square meters to acres by
multiplying by 0.0002471.
Repeat this process for the postmine_4cat file
Fill the table below with your answers and calculate the change in acreage
Landform Type
Valleys
Gentle Slopes
Steep Slopes
Ridges
Pre-Mining Acreage
30
54
1271
17
Post-Mining Acreage
63
297
945
64
Change
33
243
-326
47
Our results indicate that there is 326 fewer acres of steep slope landforms after mining. An
increase of 243 acres of gentle slope landforms has occurred due to surface mining. An apparent
increase of ridges and valleys is due to headwalls and drainage structures created during the
mining process. These ridges and valleys are small landform features and are not equivalent to
the original landforms.