GIS4930 - Module 2: Mountain-Top Removal (Prepare Week)

During the first week of Mountain-Top Removal (MTR), data preparation was the primary goal and the following were the accomplished objectives:

• Watch Lecture video of Amber interviewing John Amos, creator of SkyTruth
• Understand the Study Area & What to deliver this week
• User Mosaic raster toolset to create a mosaic dataset
• Use ArcMap's Hydrology toolset to create stream and basin spatial data
• Fix a python script template to automate the creation of Mosaic and Hydrology features
• Create a basemap using outputs of Mosaic raster and Hydrology toolsets
• Create Blog and iteratively update using Demming Cycle: plan-do-study-act
• Create an MTR Story Map 
• Create an MTR Journal 

The map on left illustrates the study region for Project 2: MTR spans five state borders: Ohio, West Virginia, Virginia, Tennessee, and Kentucky.  This region has an area of approximately 77,904,706,396 Sq m (~19,250,672 Acres).  Members of Group 1 worked with data associated with this eastern area as shown on the map to the left.  I downloaded all the basic US States from an ESRI site that is referenced below to make this simple map to highlight the Study Region.

The map on the right is a copy of a working map document I created to troubleshoot a standalone python script that automated the process of creating a mosaic raster dataset and creating hydrology spatial data (streams and basins) from a Digital Elevation Model (DEM).  I started with passing 4 DEM rasters assigned to Group 1 into the Mosaic raster toolset.  In the python script, these 4 DEMs where expressed in an array that was passed to the MosaicToNewRaster_managment method.  And the output of this method would then be passed to another tool (ExtractByMask) that masks/clips the raster to the boundary of the Group 1 study area.    This new masked raster has a set of elevation data ranging from  1435 - 156 meters as you can see from the legend (darn, looks like I forgot the reference to meters in the legend).  This new range of elevation data in the new DEM Raster was then used by the hydrology toolset to generate streams and basins by running a set of tools where the output of each tool feeds the next method.  Again, this tool/method execution (call stack) was very obvious in the script and nicely commented as step 4 - 10.  Fixing the script was really just a plumbing task of creating the appropriate file paths to keep the inputs and outputs from colliding as each tool passed their outputs to the next tool.  I added an inset map to make reference to the study region shown as a purple boundary. The red colored area is the Group 1 work area I analyzed this week.  The Hydrology toolset did all the work of generating the streams and basin features. The python script made this weeks data preparation very fast and efficient.  The boundary features where provide in this weeks project data.  And the ESRI basemap was added via ArcMap 10.6.1.  The state boundary features in the inset map I downloaded from Census Tiger files.

What was learned this week?
Getting the python script to work was a little tricky at first, but once I got into troubleshooting the script and got all my variables set to my planned file paths, the script quickly started behaving and stopped complaining soo much.  The old meme is true: "If you don't use it, you lose it".  But there is a remedy, start using the old skillset.  There might be a little dust on your bottle of python knowledge, but once you brush off the cobwebs, you might be surprised about what's inside (which reminds me of an oldie but goodie song from David Lee Murphy - http://www.davidlee.com/music/song-lyrics/out-with-a-bang-lyrics/dust-on-the-bottle/)

What was fun this week?
The fun things this week were story maps, getting the python to behave, experimenting with those light grey base-maps, and learning about the Mosaic and Hydrology Toolsets.  I found a short YouTube video that helped me get started understanding the Hydrology Fill method, sinks, and headwaters (see reference link below).

What were some Weekly Positives?
 SKYTRUTH - https://www.skytruth.org/
 SKYTRUTH helps the masses see the change so citizens can participate to help CHANGE IT.


In summary, this week was an eye-opening experience of the coal industry and the MTR process.  I liked exploring and getting started with Story Mapping and this weeks python script was a good python reminder experience.  At first, getting started with the script template was challenging.  It was a long time since I last cracked open a python editor.  I started with understanding what the script was meant to accomplish and first created a working map document with all my planned empty folders for my script to dump the generated features.  I stuck with the basics of wrapping all method calls with verbose print statements and walked the call stack until I resolved all script errors.  I then used my working map document to visualize the expected features: Raster (DEM), streams (line), basins (polygon).  The top-down execution of method calls in the python script made it easy to follow the logic and workflow of data manipulation this week.
Finally, I reused the working map document.  I created a new map document by copying my working map document.  After a few edits and applying all the map essentials, I was able to quickly create the map displayed above.  This weeks course material is starting to get easier to decipher and I'm starting to develop a rhythm to complete weekly assignments and getting reacquainted with searching and downloading GIS data.

References:
• http://desktop.arcgis.com/en/arcmap/latest/manage-data/raster-and-images/defining-or-modifying-a-raster-coordinate-system.htm
• http://desktop.arcgis.com/en/arcmap/latest/tools/spatial-analyst-toolbox/an-overview-of-the-hydrology-tools.htm
• https://www.arcgis.com/home/item.html?id=f7f805eb65eb4ab787a0a3e1116ca7e5
• https://www.youtube.com/watch?v=0D5kG6_3rTI
• http://www.davidlee.com/music/song-lyrics/out-with-a-bang-lyrics/dust-on-the-bottle/