Eye-SAH-Ryth-mik Mappin'

This week was isarithmic mapping...or how those contour and weather maps are made. Isarithmic mapping is different from choropeth mapping in that the data is not bound by enumeration units. Isarithmic mapping is good for data that doesn't correspond to to the artificiality of borders, data like weather patterns, other natural phenomena or even human activity that transcends enumeration units (population distribution as opposed to density). Isarithmic mapping works best with continuous smooth data.

First, in order to understand how isarithmic maps work, one needs to know interpolation of the data points. Enumeration units are not used, points are used instead. These points can be "true" (a weather station) or "conceptual" (data from over a larger area placed into one point). This, for me, wasn't that easy to grasp. Our book had tons of little formulas for the variety of interpolation it presented us with. I suppose though, knowing the basics is what's important because as a GIS user, I can better display and explain the information if I know the process that went into creating it. Like a car salesman who knows the basic of automotive assembly.

The objective for the lab was to use isarithmic mapping and display the data through 2 different symbologies. The first was continuous tone which shows colors or shades proportional to the data being displayed. In our case, the 30 years average of precipitation in Washington state.  The colors in a continuous tone map sort of flow into each other and I feel, is easy for any map reader to understand.

The second was hypsometric mapping. It's similar to continuous tone however it's used more to show how the data is impacted by elevation. I feel hypsoemetric mapping is somewhere in between choropeth mapping and the continuous tone symbology in that hypsoemtric almost creates clear breaks in the data. Those breaks are the change in elevation. It's useful when elevation's impact on the data is important. Below is the final map product, a hypsometric map with contours. The contour lines help to illustrate how hypsometric creates breaks based on elevation. Those breaks almost create the appearance of an enumeration units (knowing that there are no enumeration units, but instead points).

I feel the map, with it's symbology, shows use where precipitation is greatest by elevation where as the continuous map shows us a more general trend in precipitation.

This map presents us the 30 year average of rainfall over the state of Washington. It uses hypsometic symbology  and contour lines (see above). The data was created using PRISM. PRISM uses point data underlined with elevation and is related to "climate fingerprint" or the historical weather pattern of an area based on it's physiology (mountains, etc.).  

Data Searchin'

Week 7 and 8 was all about hunting for the data. That meant (literal) hours of downloading from the various websites (FGDL and Labins). Given the fact I'm in the People's (non) Republic of China, the internet is not the fastest especially when I have my VPN running to get to most of the data.

Once I had the data I wanted, it was time to build the map in Arc. The first issue I encountered was the projection. Initially, I added the vector data I wanted and then projected that data into State Plane. I then added the raster data (aerials) and it ended up somewhere in the atlantic despite having the same datum and projection as the frame. This was well, annoying. I did a lot of research and a few GIS blogs mentioned that with projections, UTM and state plane were troublesome in ARC. After some troubleshooting of my own, I decided to see if the order in which I "layered" the map would make a difference...and it did. Hopefully this wasn't something I glossed over in this course. So I put in the raster data first, then the vector and it all lined up. I could project and reproject to my heart's content and all was well.

St. Joseph Bay Invasive Plants:
I decided to go with wetlands in my map, however, Gulf county Florida seems to be nothing but wetlands...I then added a managed (conservation) layer (that I clipped). I clipped the wetlands layer to the managed layer. So now my map only shows wetlands inside the managed areas (surprisingly, not much given the sensitivity). I used this in my St. Jospeh bay map. I then layered the invasive plants layer on top. I finally added an aerial of St. Joseph state park (with the plants on top).  I added a insert to show the location within Gulf county. Everything is projected in State Plane.

 

Invasive Plants in Managed Areas, Gulf County, FL
I overlaid the managed areas with the state park layer and the Fish and Wildlife Commission managed areas layer so in my invasive plant wide Gulf county map, you could see who owns what. The pink is privately managed land. In the southern portion of the FWC area, the invasive plants clump up, so I created an insert to make out it better.    Everything is projected in State Plane.  

DEM Gulf County

This one was pretty straight forward. Also, I didn't reporject. The DEM is in Albers Conical. I realized though, I should've added a blue background Gulf of Mexico and St. Joseph Bay). My original thinking was that the 0 elevation would line up with the Gulf. However, not a great idea.