In this project, I made a GIS model based on my research data that calculates the number of people could be affected by those smelters in Salt Lake Valley and how many water resources like rivers and lakes will be affected.

I build a  research model that analysis the combination of the slope raster data and population raster data to give each smelter a rank based on the affection.

I use fuzzy theory and fuzzy logic in ArcMap and modified details in python code for this fuzzy logic model (see the graph below). First I use x y data of smelters in Salt Lake Valley to create a shapefile with smelters points. Then I use a buffer function with a distance that comes from related research materials to see how wide each smelter will affect. Next, I will use “select by location” function to select the affected blocks and water resources shapefile. The process of "select" can be complete in simple SQL language for the smelters by their unique id number generates in their attribute table.

The result summary will be based on the calculation of census block population and affected water resources will be calculated by their length and area and also provide a name list. For further research, I add an elevation DEM raster file into this model, since the elevation will also affect the air pollution, so the final result will present with a combination of fuzzy logic function and raster analysis.

This is an individual project, besides the analysis, I am also responsible for managing the GIS workflow and control the timeline to make sure each task and their sub-task will be complete on time.

1. This image shows the location of each smelter.

2. This image shows the affected area by buffer distance for each smelter.

3. This image shows the affected census block by the smelters, the darker the color, the more population in that blcok.

4. This image shows the affected water resource by the smelters.

5. This is the final result of raster analysis of the smelter affection, the darker the color, the higher the score of that smelter which means it affect more.

6. This image shows the rank of each smelter by its affection.

## Spatial Modeling

Skills involved in this project:

GIS Analysis, Model Building, Spatial Data and Algorithms, Project Design, GIS workflow, Structural Query Language (SQL).

This is an advanced GIS course that taught me the advanced map and cartographic method and theories to build a better spatial model and work more efficiently for my final project.

This course also have lab sections each week that help me use the theories I learned from the lecture to complete my lab assignments.

After the completion of this course, I am able to:
• Know and understand the definition and composition spatial modeling.
• Know and distinguish different type of spatial model.
• Resolve spatial modeling related problem in ArcGIS.
• Have better viewpoint for other spatial modeling applications in GIS industrial.