Google Earth KML

This week was pretty straight forward and simple compared to previous lessons. ( A well needed breather before out final project, perhaps?)

We had to take a mxd from a previous lesson (Module 10 Dot Density map) and convert it into a KML file that allows the information to be displayed in Google Earth (or another similar program).

The only issue I had was going back to an old problem with the dot map, having the dots display onling in urbanized areas. ArcGIS kept crashing everytime I attempted to display it. This time, I got it to work. Either because I reduced the amount of information on the map (no background color, etc.) or because I played with the size of the dots and the number of people each dot represented. Though it did take a good 5 minutes to draw. Once I had the needed elements on my layout displayed, I saved then converted the file via the Map to KML tool in Arc.Once a KML file is created, it's matter of double clicking and displays nicely in Google Earth.

After that, we had to create a tour of the major cities in South Florida. This was also very easy. Clicking the camera button on the tool bar and then clicking the record button. Whatever we do while it's recording, is recorded. Though I had to do it a few times until I had the tour I liked. There was also the trick of displaying and not displaying features, like the pins for the cities or the dots. The trick was find the right moment to uncheck them as the map transitioned to a new area. It's cool how Google Earth does the flying bit. Almost makes any tour look like a professional piece of work. Once in the respective cities, I tried to do a little flying around using the w-a-s-d layout (PC games do matter...).

The other aspect of this lesson was discussing VGI. Google Earth is a tool that seems to be made for anyone to create a basic map. You can add photos, points of interest,etc and share them with a community. If you know how to create KML files, you can go a step further and really create something that can be easily shared with others. I like the open source aspect of it. This is where ESRI fails and companies like Google, Open Street maps or programs like Q-Gis do well. Giving people the ability to map what they want. It's obvious ESRI is attempting to compete with their ArcGIS online and their ArcGlobe, obviously though ESRI is more geared towards organizations that need this tools. However, I'll venture to say that as mapping technologies become more streamlined and easier to access, more and more organizations might opt for open source over paid subscriptions.

Google Map Image with Dot Density layer and related information (legend, etc.)

Geo-Referencing

This week's lab focused on geo- referencing, where by we take un-referenced data (i.e. no geographical projection). We had to take raster data create a reference for it. The data consisted of aerial photos of the UWF campus near Pensacola, Florida. For our purposes we referenced in a basic but effective way. And as beginners in GIS, basic is where we start.

The process works by adding data that is already referenced. In this case, polygons and polylines of roads and buildings on the campus. We then added the raster data. Of course the raster doesn't line up. So we enabled the georeference tool bar. (Everything in ArcGIS comes down to the toolbar). In the tool bar we can first get the raster data to appear in the same space as the buildings/roads layer by selecting Fit to Layer. Then we enable the points. Using the buildings/roads layer, we can connect various points to points on the raster data. I can see the corner of a building, and connect it to it's corresponding polygon. You need to start with the unreferenced data and link it to the referenced data. You need to have at least 5 points.We can then check something called the RIMS error, this will tell us how close those two points are. The error should be under 15. I was able to get the error around 4 on the first raster while still making sure it looked accurate. Having it look accurate is as important as getting a good error value. So one needs to find the right balance. This balance is helped along by using polynomial transformation. There are three levels and the transformation helps to warp the raster data to the points. It can help create a more accurate look but if you use higher levels (as I discovered) it can stretch the raster out and distort it in various ways. The northern half of UWF used a level 1 transformation where as the southern hald used a level 2. Level three really distorted the image. After creating and deleting links I finally got something I felt good with.

We then had to create a buffer zone around an Eagle's nest using the multibuffer tool. This was the easiest part. Input, ouput boom...buffer zone! multi because we created two in one, 330 ft and 600 ft. There was no base map for where the eagles nest is. So I had to add a basemap..for some reason, every time I exported it as a jpeg, it distorted and created a pixalted green mess. I couldn't figure that out. We also used the editing tool to digitize shapes on the map. In our case, the gym and a road. The road was a polyline and the gym, a polygon. I had done this in the past using one of the free ESRI courses which has you digitize a lake. The tool is a little tricky. With the gym, I first tried making a square for each part of the building, but it was hard to line them up and merge them. I went on YouTube, find a viedo and realized there was a way to do it in one sweep...make a lot of little points that match the outline. Though, it didn't come out perfectly, I felt like it worked great.

The next part was the part that you can impress people with the most...no one cares that can you do an awesome job analyzing the best place to set this up or geo code, no the thing that gets the lay people interested are 3D maps! We put our now referenced raste data along with a DEM feature class in Arc Scene. Using the DEM plus the base heights of the buildings we were able to create a 3D map of UWF. This is actually a fun process that I really enjoyed in my Carto class. And your friends often say...ooooh...aaahh....even though in reality the process do it is quite simple despite the number of steps.

Overall this lap helped us to better understand some of the basic mechanics of ArcGIS and how georeferences can be created when none are found. As I near the end of the course, I feel more confident in using ArcGIS...I'm also happy I saved all of those pdfs on my pc so I can look them up when in doubt!

3D Models

This week we had to learn and understand how to create 3D models in arcgis. This was actually quite fun and I felt like I was learning the details and methods behind programs like Google Earth.

In the lab we mostly followed the ESRI training directions and then followed along on the pdf. We learned how to create 3d models using tools such as extrusion. The ESRI training sections are really good at taking you step by step of the various tools in Arc that you can use. At the end of the day, I learned how to take any scene (in which I can create a Z value based on elevation or height) and create a 3d representation.

If I had a choice, I'd stick to 2d maps. Though 3d maps can display information in interesting ways, I feel that they don't have much practical value. Ultimately ArcGIS is about Data anaylsis, and though there are times in which a proper visualization can  improve this process, those times are limited. Personally, I feel 3d models best work for 2 situations: 1) Seeing something that you can't normally see and 2) keeping people interested.

As for number 1, that can apply to maps that have subterrian information, such as the first map we looked at. There I could see that types of rock and the well depths. Also it can apply to visualizing non spatial information in a spatial way such as the property prices for the parcels map.

3d maps definitely are interesting to look at and will keep people's attention. That being said, it's hard to think of situations in which 3d maps provide better information than a 2d map. And unless you're concerned with the actual physical shape of geographic information, it almost seems unnecessary. But ultimately, making 3d maps are fun and look really cool.

Geocoding

This week we spent time learning what network analysis is and how to perform this in ArcGIS.  So essentially I was able to learn what the mechanism behind google maps directions are (though I'm sure it's more complicated than what we dealt with...because of computer languages etc.)

First we had to gather the data starting with TIGER lines (I love the American..er sorry...USG's love of creating acronyms for everything) from the US Census Bureau's website. Well, this was was actually a pain in the ass for me. I live in China and there's this thing they do, where they censor the whole internet including a lot of USG websites. This is not a cool thing (partly why I'm moving out of this repressive country after only a few months of living here). My VPN, for some reason, couldn't connect to the website. After much frustration, I switched to my other VPN which worked (never doubt the simplest solutions to any problem in life).

Once I had the data needed, I followed the lovely pdf instructions and created a Lake_Roads file for Lake County. I then proceeded to add a smattering of data files (new and old alike) to the Lake County database. Many of the files I added, such as the water, county boundaries, etc were from past modules. I then clipped, exported, re-projected, etc my way through them until I had a set of data that I could work with to make the best possible map. I ended up creating a new water features layer by cutting out water features under 1.5 sq km (I never realized how much water Florida has...it can really clutter a map). I wanted to include the water inside lake county, because the many lakes in Lake County had a real impact on the network of roads and I felt it best to ensure my audience is aware of the "lakeyness" of Lake County.

After my data was arranged into feature classes I created the address locator using the EMS file. The matching of unmatched addresses was a little interesting. I matched using the map for all of them, as each time I added said address to google maps they were no where near the ones on the candidate list (those that had candidates anyway). After I matched the unmatched with the assistance of google maps, I then created the Geocoded results.

I picked the three stations you see displayed in the insert and performed the route network analysis creating the nice blue line. I kept the line in both data frames. For the EMS stations, I selected the cross and had them labeled according to their station number. Using the station numbers I could list all of the addresses in the box on the lower right hand corner of the map. I decided to have the stops look the same as the rest, only I kept the color blue. You'll notice I didn't add the stops to the legend. Here I'm assuming the audience can figure out that those are stops from the numbered order of each stop (1...2...3) and from the title of the insert map "Best Route from Station 141 to 241 to 231".  I was trying to decrease clutter, aiming for minimalism. I attempted to make the EMS stations as preeminent as possible by sort of washing the county out with the color scheme while still trying to make sure the street network was visible.

Hope you like it! 

A map displaying EMS stations in Lake County, Fl.
The insert shows the best possible route for 3 of those stations.
The addresses of the stations are displayed based on the station number,
which are labeled on the map it's self.

Dot Pop!

This weeks class focused on creating a "dot density" map. Essentially, it's a map that has a lot of little dots that represents certain data (in our case, one dot representing many, one-to-many). We had to create a map showing population density in South Florida. Each dot represents 5,000 people. The interesting part about dot mapping with one-to-many dots that they are randomly distributed and do not correspond to geographic points. Though I tried so hard to get the dots to only appear within urban areas, ArcGIS being the ever expensive glitchy  program it is, crashed repeatedly. So I had to make do with excluding the dots from the water layer.

I created this map entirely in ArcGIS, never using AI once (I know, I know, I can't believe it either. It's such a good looking map). The first step in creating any map is figuring out the base layers and the colors to use. I went with natural colors. A blue background (the sea) and a light green for the south Florida area. You'll notice a grayed out section of Florida to the north. This is the county layers from previous modules. I decided to include this layer to create continuity instead of making south Florida look like it had been hacked off and is floating in a nebulous space.It think it's quite clear that the green area is the area we're concerned with. For the water layer, I used a layer from a previous module as opposed to the one given to us. I did this because, the water layer you see is more refined and shows major water sources. The layer given to us for Module 10 was all water and instead of taking hours to clean up that layer, I took the easy route and just clipped this layer! ( I think it was from my Intro to GIS class). For the colors, a dark blue for the lakes and a lighter blue for the streams. As for the wetlands,I went with the ESRI wetland but removed the background color and changed the foreground color to blue. By removing the background color, it allows the wetland feaure to blend into the green of the county layer map. For the urban areas, I went with the color you see. I think it's easy to see on the map while not conflicting with the colors. Essentially, it's not jarring to the eye. I then included an insert map using a US State boundary shape file I had on my computer. Next was the cities. I went with the following cities because I felt they gave the best reference points on either coast. Originally, I was using the city picture to represent the cities on the map, however, when the dots were added, the cities became covered in red dots and it was hard to see not aesthetically pleasing. Instead, I went with the circle dot and turned it blue. It's easier to see when the dots were added. The dots, I decided to go with red. Red is easy to see against blue and green. Also, the red made the dots the most prominent feature.

For the dots, I tried to have them mask by the urban layer. However, every time I attempted to mask it to be only in the urban area, Arc crashed. I tried changing the ordering of the layers. I tried deleting everything and relayer it and masking it different times in different ways. But every time I selected the urban layer and try to mask the dots to only appear there, it crashed. So I had to settle with excluding the water layer. This then inspired me to write a summary about the map (something we've done on other maps in the class and in the intro to GIS course). I wanted to make it clear that the dots are not geographic points. (Not one to one dots). Originally, I went with dots that represented 15,000 people but I felt it wasn't accurate. Instead, I went with each dot representing 5,000 people.

Dot Density map of overall population in South Florida. As the disclaimer explains above, the dots are not geographic points. The map was created entirely in ArcGIS. 

Bufferin'

This weeks class objective was ti use buffer tools to perform a vector analysis. The task was to determine the best possible location for camp sites based on certain parameters. We were given feature classes of roads, rivers, lakes and conservation areas within Desoto National Forest.

First, before I dove into the pdf guide, I downloaded some shape files from the Mississippi Geospatial Clearing house. (I knew where Desoto was located). The files were parks & reserves, state boundaries and county boundaries. I wanted to see where exactly this data was located as well as provide a base map to make it more aesthetically pleasing and detailed as opposed to having lines and polygons floating in an ambiguous space.  Using these layers, I figured out that the given feature classes were inside Desoto National Forest that was inside of Perry County, Mississippi (So, not the whole forest).

I then added the base layers and created an insert using the state boundary maps. I put our feature classes on top and then followed the pdf verbatim. The buffering was quite straight forward, if you knew what tool works best. We were tasked with joining the buffers of the rivers with the roads. I found the intersect tool worked best because it only took one step as opposed to several with the union. The next part was to find the buffers that intersected at within the buffers of both the water features (150m for lakes, 500 m for rivers) and the roads buffer (300m). Once I found those, I then had to erase buffers that were inside conservation areas. For this, I used the erase tool. Once I used the tools to determine the best places for camp sites, the next task was making it look good.

For that, I map the forest a light green. I left the conservation areas with a dark green. Though the examples given don't have the conservation areas displayed, I felt it best to display it so people could better understand how the best places to camp came to be. (If you knew the area within a certain distance of roads and water is where the best camp spots are  you would be curious why some of those spots were missing from the map even knowing that it excluded conservation areas.)
I then added the insert map, the title, legend, neatline and north area. I tried to keep the map simple in terms of placement and color to keep it aesthetically pleasing. When it comes to design, I'm a minimalist.

Map of possible camp sites in the Perry County portion of Desoto Natinal Forsest. The salmon color areas are the possible sites. An explnation of the map is in the lower portion between the legend and insert. 

Flowy Lines of Migrants

This week's lesson in cartography was in flow lines. Essentially, they're nice long, flowing lines with an arrow on one end. (In simplistic terms.) We were tasked with creating a flow line map that displays immigration by continent to the US. During this process I realized something, AI is not meant for maps. Thank god the file we were given already had the layers organized. Exporting an arc map to AI, creates such chaos on the layer front. I digress.

In making this map, I first considered how the lines would work. I decided to have all the lines run into each other. I did this to reduce clutter. I do regret, however, making each line a different color. Looking at it below, I feel it didn't quite come out the way I wanted. It's hard to see the Oceania line, for example. I then changed the color of each continent, except for the US. For the US, I changed the color to a red so it could stand out. Europe, sadly, looks washed out. (oh the pain of last minute work).  For the insert, I didn't go with an at scale. I blew up Hawaii and Alaska, though I kept their directionality. I made the legend in ArcGIS and then copied it over to AI.

I made a legend using the arrows and matching the arrows to the line width I figured out in the lab exercise (5pt being the maximum). I then put the respective number of immigrants next to each one.

I added drop shadows where I though would best show the lines and other information. Also, I like to keep things simple. I felt the large white border with the space to show my legend without a neatline, worked well. I felt my color choice on the map is also simple. The colors aren't too bright. I find the colors to be demur.

I like the central concept of flow lines, however, I'm I feel most stories can be told in better ways than with flow lines. They're thematic and can look compelling but also can clutter the map quite easily.