GIS4930 Module 2 - Mountain Top Removal, Appalachia Coal Region (Report)

The  Mountain Top Removal (MTR) method of coal mining in the Appalachian Mountains has been shown to impact the surrounding hydrology (Petrequin). As part of the study of applying GIS to MTR impacts, this project included creating stream and basin features. This was done by mosaicking four DEMs into one layer and then applying several Spatial Analyst Hydrology tools.

Analyzing the impact of the MTR method of coal mining on an area involved comparing imagery from two different time periods. ArcMap and ERDAS Imagine were both used with 2005 imagery to develop a signature file which was then applied to 2010 imagery to develop a map of MTR areas.

Only a portion of the 2010 data was analyzed by Group 3 for SkyTruth. The 7 bands of the 2010 Landsat imagery were consolidated using the Composite Bands tool, and the imagery was clipped to the group's study area in ArcMap. A layer with 50 classes was created in ERDAS Imagine using the Unsupervised Classification tool. Areas which appeared to be part of MTR were classed and symbolized by color accordingly with the remaining areas being classed as NonMTR. Many objects such as stream or river banks, buildings, and roads have identical spectral signatures as MTR and were included initially. They were removed from the MTR features later. In ArcMap, the classified image was reclassified with MTR being assigned a value of 1 and all other Class Names assigned blank values.

From this information, the MTR raster was converted to polygons. MTR features within 400 meters of major rivers or highways were removed from the MTR polygon layer, as were those within 50 meters of streets and other rivers. Features smaller than 40 acres were removed as well. An accuracy assessment was done with a result of 96.7%, and a comparison against the 2005 dataset was made. There was an overall decrease in acreage attributed to MTR from 2005 to 2010, but the data needs to be critiqued further. The 2005 dataset included features of less than 40 acres, while the 2010 data was restricted to features containing more than 40 acres. The 2005 dataset had more than 8,000 features, while the 2010 dataset had fewer than 500 due to the acreage restriction.

A layer package was created with this data and submitted to the group leader for compilation into one dataset for the group's study area, and a map service to present the group findings online was created. This map service was used to create an online map. A soils runoff classification layer was also added to the map. This additional data was selected because runoff from MTR sites impacts the surrounding areas. The online map can be viewed here, although the soils layer is not available to all viewers.

Resource:

Petrequin, M. (2012). Hydrological Impacts of Mountaintop Removal in Appalachia: History and Solutions (Colorado School of Mines, Department of Environmental Science and Engineering).  Retrieved from uwf.edu.

GIS4930 Module 2 - Mountain Top Removal, Appalachia Coal Region (Analyze)

Assessing the impact of Mountain Top Removal (MTR) mining on an area requires comparing imagery of that area taken after a period of time has passed. The Analyze portion of this module helped develop the skills to do just that. Utilizing data from SkyTruth, 2005 Landsat imagery was used in ArcMap to select training samples in known MTR polygons as well as in nonMTR areas. After changing class names, values, and colors for the samples they were compared for overlaps, and a signature file was created to be used in Supervised Classification. The same data was used in Erdas with the "Grow" tool to select several samples to add to the Signature Editor table.

The class was split into several different work groups of 3-4 students to analyze the 2010 data for SkyTruth. Each group was responsible for 2 to 4 images. After the preliminary exercise, the 2010 imagery was prepared by first using the Composite Bands tool to consolidate the 7 bands of the Landsat file and then clipping the imagery to the group's study area in ArcMap. In Erdas the Unsupervised Classification tool was used to create a layer with 50 classes. Areas which seemed to be part of MTR were classed and symbolized by color accordingly. Distinguishing the MTR areas was difficult for me. The remaining areas were classed as NonMTR and symbolized by a different color. Because identical spectral signatures can be assigned to very different types of features, many objects which are not MTR areas are included in the MTR class. This will be accounted for at a later time.

Back in ArcMap, the classified image was reclassified with MTR being assigned a value of 1 and all other Class Names assigned blank values. The resulting image is shown here:

2010 Landsat Imagery Classified for MTR
(NOTE: This image includes some nonMTR features with the same spectral signature as MTR.)

From this information, the MTR raster will need to be converted to polygons and smaller MTR areas removed. Buffers will be created around roads and rivers, and MTR areas within the buffers will be removed. An accuracy assessment will be done as well as a comparison with the 2005 dataset. Each group member will submit packaged data to the group leader for compilation into one dataset for the study area. Finally a map service to present the group findings online will be created. Look for this next week!

GIS4930 Module 2 - Mountain Top Removal, Appalachia Coal Region (Prepare)

This was a two-part lab preparing for a project concerning the coal-mining process of mountain top removal in the Appalachian Mountains of West Virginia. The first part of the lab involved learning about LiDAR as well as creating and viewing LAS datasets in ArcMap. Different point symbology and different filters impact how useful the information can be.

The second part of the lab involved creating stream and basin features from USGS Digital Elevation Models (DEMs). A mosaic of four DEMs which Group 3 will be using this module was created and clipped to the extent of the class's study area. Several tools of the Hydrology toolset of Spatial Analyst were used then:

1. Fill tool to fill in low spots/pooling areas

2. Flow Direction tool to assign values to each pixel indicating direction of flow across the individual pixels 

3. Flow Accumulation tool to indicate the number of other cells flowing into each cell (to show possible streams)

4. Con tool to eliminate features which likely are not streams

6. Stream to Feature tool to create streams layer

7. Basin tool to create watershed layer

The created streams and basin layers are depicted in this map:

Group 3 - Streams and Basins

Appalachian Mountains

GIS4048 Module 2: Natural Hazards - Lahars

Lahars started off the course’s study of natural hazards. Unfamiliarity with the term lead to some research prior to starting the module requirements. The Javanese word “lahar” used for a volcanic mudflow originated in the 1920s. Its use increased dramatically in the 1980s and 1990s, probably in reaction to the frequent volcanic activity during that time period. In some areas this fast-running mixture of mud caused by rapidly melted snow and ice poses the greatest risk of any volcanic activity. Speeds of 45-50 miles per hour and flow depths of 100 feet where the lahars were confined in valleys have been reported at Mount Rainier. Because of their concrete-like properties, lahars are capable of demolishing most structures. They can also occur during periods when no eruptions are occurring in which case there may be no advance warning of the impending event. For these reasons, the importance of risk assessment and hazard planning is critical. This exercise was created to demonstrate that process.

Acting as a private consultant hired to identify potential inundation zones in the vicinity of Mount Hood, Oregon, the process involved mosaicking digital elevation models and then using the Hydrology Tools to determine drainage flow. Coupling that output with 2010 Census data and Oregon school data, a population analysis and schools-at-risk identification was performed. State and local officials could use this information for hazard planning and response time to help keep area residents and visitors safe from lahars.

After establishing a geodatabase to keep the project organized and efficient, XY tool was used to show the location of Mount Hood. Drainage areas were created from the mosaicked DEMs using some of the Hydrology Tools (Fill to eliminate sinks, Flow Direction to assign direction of flow to individual cells, and Flow Accumulation to calculate how many other cells flow into each cell) to create a stream network. The need for an attribute table for further work called for changing the fill output from a floating point raster to an integer raster. Using the Con tool (conditional statement) reduced the stream network to only those areas with sufficient flow accumulation to qualify as streams. That output was then converted to polyline vector features – areas most likely to become inundated during a lahar. This whole process - creating a stream network from DEMs - was rather fascinating to complete.

Applying buffers to the streams provided areas of potential inundation by lahars which were then used in the selection process with Census population block groups and schools data. This resulted in the areas on which teams should focus for large lahar event hazard planning. From this information the following map was created:

Mount Hood Lahar Hazard Assessment

Populations at risk for being impacted were calculated for the possible inundation zones around drainage basins within the study area only rather than for the entire dataset. The potentially impacted population number outside the study area is much greater than the number calculated and displayed on the map. The values for this map are calculated for the study area only which has a lower population density than the areas to the west, so the block group population ranges may differ from those presented by others. Overall, lahars from Mount Hood have the potential to impact 42,689 people within the study area based on 2010 Bureau of Census figures. Including the area outside the study area 212,791 people could be impacted.

Although it does result in a more cluttered-looking map, especially in areas with small census block groups, the census block group outlines were retained. This was decided primarily to minimize misinterpretation of the map resulting in an underestimate of the actual population with the potential to be impacted by a large lahar.

This particular lab demonstrated the variability in information that could be produced for a client. For example, the lab requirements were focused on lahars, but in reality a hazard-planning team would also want to know what populations would be at risk for other volcanic hazards. In this particular case, one requirement was to provide the number of schools at risk from lahar inundation. However, just outside one of the mile-wide lahar inundation zones was an additional school located closer to Mount Hood. Naturally, one would expect the hazard-planning team to be made aware of this school, but including that information was outside the scope of the lab requirements. This also illustrates the importance of communicating similar situations to a client for further clarification or revision of the data to be provided.

The ability to go back and review previous geoprocessing steps came in quite handy during this lab!

Introduction to Adobe Illustrator

This lab provided an introduction to Adobe Illustrator which can be used to enhance maps exported from ArcMap.  The tools were easy to use with seemingly endless creative possibilities.   Especially helpful while experimenting with AI was toggling visibility to find objects on the artboard and to confirm groupings in the Layers Panel.  Stressed during this lab was learning where and how to place the scale bar objects in the Layers Panel so that the scale bar would be linked to the geographical data.  This ensures proper adjustment with any size changes in the map, so that the scale bar will always correspond accurately to map distances. The map of Florida Cities shown here is the end result of working through this lab.

Florida Cities map created with ArcMap and Adobe Illustrator.