GIS 4102 - Module 3 - Geoprocessing

 Geoprocessing is a framework and set of tools for processing geographic and related data. 

In this weeks module 3 for GIS programming we utilized python in conjunction with arcGIS pro in order to perform geoprocessing operations. We began by designing a model in arcGIS pro using the model viewer window. This model was designed in order to clip all soils to a basin layer, select all soils that are designated "not prime farmland", and erase the selected polygons from the clipped soil layer. The following is a screenshot of the model viewer displaying the workflow of the model process.

The result of this model was a shapefile named soil_clip_erase1.shp that displayed all soils within the basin area that are suitable for prime farming. The following is a screenshot of the output shapefile.

The next portion of the module involved designing a script that would add XY coordinates and a 1000m buffer to hospitals.shp while printing success messages, start time, date, and elapsed time. I was able to accomplish this once the workspace and the overwriting of geoprocessing options was established. Adding XY coordinates was a matter of running the acrpy functions copy_managment and addXYmanagment. Print statements were added to display correct success messages, start time, date, and elapsed time. Here is a screenshot of the console after successfully running the script.

And here is a screenshot of the hospitals_buffer.shp displaying the 1000m buffer around hospital locations. 

 

Some tricks I learned over the course of this module involved proper file referencing in both python and ArcGIS pro. Model building involved an understanding of geoprocessing tools such as clip, select and erase. The key to building a correct model was referencing the correct input and output shapefiles.When designing the script for python, proper file referencing and function placement was key in ensuring a proper functioning script. I opted to add elements such as a “/n” spacing command at the end of the getmessages command along with print statements referencing the shapefile being used as the workspace. These elements allowed for a better visualization of the processes occurring in python.

GIS 4006 - Module 3 - Typography

For this weeks Module 3 lab we were tasked with creating a map using adobe illustrator arcgis pro that highlights 17 features in an area of the Florida Keys known as Marathon. After researching Marathon on the wiki page, (https://en.wikipedia.org/wiki/Marathon,_Florida), I learned that Marathon’s name originates from the Florida East Coast Railroad and that the Florida Keys historian Dan Gallager in his book "Florida's Great Ocean Railway" credits New York playwright Wiiter Bynner for naming Marathon.

The theme for this map is as follows; Font: Berlin Sans FB Demi Bold, Size: 18, Color:Town-Yellow, Airport-Red, Statepark-Green, Countryclub-Blue,  Stroke: White.  All features for this module were labeled using this technique with varying font size/color and leader lines. Leader lines, for this map, were drawn with the pen tool in adobe illustrator and the type on a path tool was used to type Font: Berlin Sans FB Demi Bold, Size: 12, Color: Aerial-Black and Hydrographic-Italicized Blue, into the corresponding features GPS coordinate locations.

Features that make my map unique would be a drop shadow applied to the marathon islands feature layers, a color coded font that aids in the location of Town, Airport, Statepark, and Country Club features accompanied by a color coded legend, and, finally, an aesthetic use of symbols, colors, and border frames to highlight a beautiful area such as Marathon, Florida.

GIS 4930 - Project 3: Prepare - Statistical Analysis of Methamphetamine Laboratory Busts

"Most illicit drugs present two serious problems for society. First are the many consequences of drug use for the user, the community, and society as a whole. Second is the violence that accompanies the business of drugs that are transported across national borders through elaborate networks. Methamphetamine contributes to both problems, but in many parts of the country it presents another serious problem, namely the social and environmental damage that comes from domestic methamphetamine production." Methamphetamine Laboratories: The Geography of Drug Production - Ralph A. Weisheit and L. Edward Wells

For this week’s portion of Project 3: Prepare, we were tasked with preparing for a Statistical Analysis of Methamphetamine Laboratory Busts in West Virginia, USA. The final report for this module will consist of a fully constructed multi paged scientific analysis of the West Virginia study area comparing specific census tract demographics to the location of reported meth lab clusters. This analysis will serve to solidify any doubt in regards to medical, property and economical damage, that this drug and the drugs creation processes has wrought on West Virginia over the last few decades. I look forward to performing this analysis and to next week’s ordinary least square regression model creation.

Below is a constructed basemap of the study area with all essential map elements for the module 3 project.

GIS 4035 - Module 3 - LULC classification

For this weeks project, module 3, in GIS 4035 we were tasked with created a land use / land cover classification map for a provided aerial image file. A LULC level II code format was followed and the following codes were applied to the study area and the reasoning for why:

11- Residential - areas that contained buildings that were smaller than commercial size
12 - Commercial and Services - areas that contained larger than home sized buildings and large parking lots
14 - Transportation - main highway
43 - Mixed forest land - all woodland area was categorized under this classification of mixed
51 -  Streams and Canals - smaller streams leading from the bay were categorized as this
53 - Reservoirs - a few small retention ponds in the residential area
54 - Bays and Estuaries - the bay
62 - non-forested wetland - wetland area surrounding the bay that had no trees