Ariel Photography: Visual Interpretation

The objective for exercise 1 was to identify the tone and texture of an aerial photograph. Tone can be described as the brightness or darkness of an area so, the task was to create polygons around areas in the photograph that could be described as very light, light, medium, dark, and very dark. The next task was to identify areas of varying texture which involved a similar process to that of identifying tone. Texture in this case is defined as how smooth or rough the surface appears to be. For this task, polygons were drawn around areas perceived as either very fine, fine, mottled, coarse, and very coarse.

In these tasks, I did accomplish identifying areas of varying tones and textures. I had some challenges because I had to relearn how to create polygons but once I figured it out, the process went smoothly. My next challenge was labeling the polygons. In my first few attempts, the labels did not appear. I believe the problem was simply that the text was too large for the polygons so after adjusting a few settings, I was able to see the labels. 

 The objective of exercise 2 was to identify areas in an aerial photograph by the shape and size (an easily recognizable object like a tree or building), shadow ( an object that can be recognized by the shadow it casts like a water tower), pattern (an area that is recognizable not by a single object but by multiples of an object such as a farm), and association (areas in which conclusions can be drawn based on surrounding features).

With these tasks, new features had to be created, similar to exercise one, but these features were not drawn polygons and were instead points being made on the photo. This exercise went much smoother for me as I had worked out any difficulties in the process for the first exercise.

Google Earth

Screenshot of South Florida Map in Google Earth
 

Well, here it is, the final project for Computer Cartography. This was a great project to end on, I certainly enjoyed working on it.

In this lab, we were instructed to convert data in ArcGIS to KML, use that file to help create a Google Earth Map, and then create a tour with the finished map. 

Using ArcGIS, population, surface water, and county data were uploaded and then converted to a KMZ file using the 'Layer to KML' geoprocessing tool. The KMZ file was transferred and displayed in Google Earth. The resulting map was of the population of South Florida using dot symbology. The dots were layered over a map of Florida which included county boundaries and bodies of water.

The next step in this assignment was to make a tour of the map. This is where it got fun. Within google earth you can elect to add placemarks to areas of interest. That placemark will be shown at the extent in which it was placed. For the purposes of our map tour, we began with an overview of 23 counties in Southern Florida, then zoomed a little closer to show the Miami metropolitan area. From there, we zoomed to the placemark in downtown Miami. Likewise, we showed the cities of Fort Lauderdale, St. Petersburg, and Tampa during this tour as well.

Creating this map and the tour within Google Maps was much easier than I had anticipated it being. That being said, it was still very engaging, and I learned a lot from it. 

Isarithmic Map

 This weeks module covered isarithmic maps. In this lab, we were tasked with creating a precipitation map of Washington state depicted with hypsometric tints, hillshade effect, and contours. Data was acquired from the USDA Geospatial Data Gateway and the PRISM Group at Oregon State University.

In order to show continuous data throughout the map, the data needed to be interpolated. The precipitation data was interpolated using the Parameter-elevation Relationships on Independent Slopes Model (PRISM), which is an analytic tool that uses point-based climate measurements to predict monthly or annual climate behavior. Another useful feature of PRISM is that is accounts for variables in the map such as terrain and elevation by utilizing a digital elevation model (DEM) which enhances the accuracy of climate data.

To complete this map, hypsometric tinting, also known as elevation coloring, was implemented. Hypsometric tinting is used to show elevation differences on a map by using different colors on different elevation ranges. For this map, the hypsometric tinting was implemented by using the geoprocessing tool called Int (Spatial Analyst Tool) and inputting the annual precipitation raster data. Next, contours were overlayed on the hypsometric tints. This was performed using another geoprocessing tool called Contour Listand run using the same annual precipitation raster data.

The result is a map that illustrates how precipitation is impacted by elevation and terrain, which is important for understanding patterns in the climate of any given area.

Choropleth

 

Data Classification

 

Cartographic Design

In this module, there was much emphasis on Gestalts Design Principles. These principles include a visual hierarchy of map elements, the contrast between map features, figure-ground meaning the ability to accentuate chosen objects over others, and the overall balance of the map.

 One example here to show how I used Gestalts principles of visual hierarchy, I put emphasis on the thematic symbols of the schools located in Ward 7 in Washington D.C. The schoolhouse symbols representing high schools were larger than that of the junior high and elementary schools with elementary being the smallest. Too, the coloring for the high schools was darker while the junior high and elementary school colors were lighter.

In this map, the purpose is to show contrast between the study area and the surrounding areas by drawing the readers eye toward the Ward 7 location on the map. To do this, I made this are lighter in color than that of the surrounding states and Washington D.C. area. For the Ward 7 location, a tan color was used while the D.C. area is a medium brown. 

 To achieve balance on this map I used the empty spaces wisely. In the bottom right corner, is the inset map and to the left of Ward 7 on the main map is the legend. I used the empty space in the top right corner for the north arrow and the space in the bottom left corner is the scale bar.

Typography

 In this lab we learned the importance typography and how important it is to the readability of a map and how it contributes to the overall map design. When focusing on the typography of a map, the map maker has to consider a few different elements; font, font size, line spacing, color, and label orientation. In the lecture and readings for this assignment, we were given pointers on how best to use typography to personalize our maps.

In this lab, we were tasked with creating a map of Florida and labeling a few of its major cities and waterways. To do this, I first had to learn the process of labeling point features on a map. In general, this process is simple enough in that all you have to do is select the data you want labeled (ie cities or rivers), go to the labeling tab and click the label button. You can also label the data by specific features as well. Something that, for me, will come in very handy in the future.

I made a few customizations to my map. The first being that I used a star for the capitol, Tallahassee, and made the font size a little bigger to emphasize the visual hierarchy between that city and the other cities. Another customization I used was a swamp graphic for The Everglades and Okefenokee Swamp because I thought the graphic was appropriate to highlight the two swamps on the map. A third customization I made was inserting a light grey base map so as to bring the map of Florida forward.