3D Cartography

Good day all,
     This post is dedicated to this weeks Cartography assignment exploring 3D Mapping. A number of applications were used in this, to include ArcMap, ArcScene, ArcGlobe, and Google Earth. The data for the lab was provided from ESRI.com for a training session produced by ESRI, as well as information provided from UWF. Some of the overall objectives for this week were too describe or list data types and applications for performing techniques related to creating 3D maps.
     The lecture this week was largely provided through ESRI related products, from a lecture provided to one of their user conferences and a White Paper discussing 3D mapping. Lets hit on some of the key pieces of information from the training before going into some of the applications used this week. 3D data is created by adding a third element to a normal Cartesian (X,Y) or grid based point location commonly referred to as the Z-value. This is most typically used to reference height above or below a surface. Buildings usually have a positive Z value referencing the height of the building, whereas wells extend below ground with a negative Z-value for their depth. The surface mentioned here also has to originate in some particular form for our applications. These are usually found in raster data or a triangulated irregular network (TIN); think many points across a plain all connected via triangles, where each point and location between points or on the triangle face can have a determined Z value. Now understanding this let us look at some of the basic applications performed in this weeks training.

The above is a converted 2D image based on the Z value for each cell in the raster of Crater Lake in Oregon. Ive taken the data and also given it a 2x exaggeration to enhance the 3D visual scene depth just for this snapshot. You can see the water layer for the lake as well as streams in the area. All of these layers have been provided the appropriate Z value to sit on or in the appropriate location for this data set.

This picture started as a TIN (described above) to provide the surface to drape the aerial photo over top of, which then in turn had the buildings extruded to match their overall height and footprint. These extruded buildings could then have any number of actions performed on or about them. Imagine we could change their colors to reflect what type of building, commercial, industrial, residential area they belong too, or anything else you could think of to denote one building type vs another.

Here is another application for 3D maps where the height portrayed does not reflect actual building height. We are depicting this area by two criteria; the first being the color code which represents different zoning types, and the height which represents the overall value of the representative building. The higher the block, the more the building is worth. You could use the same principle to apply to population by census tract or other enumeration unit.

Overall 3D mapping applications can be used for as many things as you can imagine, though some of the most common now are for areal simulation, urban planning, transportation network, real estate, and census. These are fast evolving into more and more common applications, particularly with off the shelf software such as Google Earth. A few of the only disadvantages to the 3D map are the time to produce and sometimes cost of material, software, and data to create the map. However these maps are inherently the wave of the future. I hope you've enjoyed this scratching of the surface of 3D maps.

Dot Maps and Southern Florida

Greetings all,
      This post is all about Dot Mapping. That is mapping which uses dots representing a particular value to show the distribution of some discrete (raw data total) phenomena across a given area. The map below was created for this weeks Cartography assignment. Some of the key learning objectives for this week were to determine when and how to employ dot mapping, and to understand the fundamentals that go into creating a good dot map. The population data being mapped was furnished by UWF, and the map itself was created entirely within ArcMAP.

Here is my Southern Florida population distribution map. I've tried to make it as simple a map as possible. It is essentially just dots and legend, not much else. But with these dots there has been a lot of thought. The main principles that go into making a dot map are, where should dots be placed, how big and what value should a dot be, and how should the dots be organized in the areas they get placed. Notice that dots don't fall in any of the wetland areas or on the lakes, but around them. That's because urban areas and subsequently population don't occur on or in these areas. The dots themselves have been aligned with urban areas (not pictured for clutter concerns). But you get the idea by having the wetlands and lakes pictured. Also notice that each dot represents 20,000 people, and you can see the major areas around the coast and some of the key cities with highest populations density because of it. I determined this particular number to be most effective because of one dot in particular. You see the one on the south west bulge of lake Okeechobee? At a 1 to 25,000 dot ratio, that dot is no longer there, but at 1 dot equals 20,000 it is as seen. I wanted to leave the sparsely populated central areas with some representation, but still a high enough number to not overload the densely populated coastal areas with lower valued dots. I hope you enjoy and find some interest in my map. Thank you.

Camping with Vector Analyses

Good day everyone,

      This post is about my Intro To GIS assignment focusing in Vector Analyses with ArcGIS. The assignment utilized a few different data layers with particular attributes and had me working with Buffer tools, Overlay tools, and Attribute selection tools. All of this went to the creation of the map of the central portion of De Soto National Forest Mississippi. The map was created exclusively in ArcMAP, with data layers being provided by UWF, and the manipulation all performed by myself. 

Here's a look at some of the objectives for this week before we get to some key definitions and the map itself. 

• Define, Create and use ArcGIS Buffer and Overlay tools
• Create a script in ArcPy (Python Code) to run the buffer tool
• Analyze vector data using spatial queries
• Identify the 6 overlay operations available and recall when to use each
• Use the overlay modeling tool to combine or exclude multiple features
• Distinguish between multipart and singlepart layers and convert between the two

What is the Buffer tool? This tool allows you to create a buffer area around an object. That object can be a point, line, or polygon. You can set a specific distance around that object for analyses purposes. For example, the map below used buffers around the water and roads to locate areas common to both.

What is the Overlay toolset? This is a set of tools which allow you to combine, erase, modify or update the feature and information from multiple thematic layers to create a new layer for continued analyses. Several tools were used in the map below, such as the Union tool to combine two different layers, an Intersection tool to identify areas common to two layers rather than combining them, and an Erase tool to remove unwanted areas. 

What are attribute selection tools? Easy, these are tools that allow you to select specific attribute features by specifying the information in a layer you are looking for, or by location. These were used in concert with the other tools above for the final product.

Final Map highlighting particularly good areas for camping based on specific criteria. 

My map highlights all of the possible camp sites based on the criteria listed in the lower center portion. These areas are highlighted against a 1 meter imagery Basemap of the area. Also prominently displayed are two of the biggest discriminators for the choice in camping location, the roads and water features. I also took the liberty of adding an inset map of the regional perspective of this area.

The final product above was a culmination of buffering the roads and waterways by the specified distances on the map, then combining the separate layers via Union. Then selecting the attribute areas that were common to both. And finally erasing the Conservation Areas which are not pictured to not be a distraction from the key features. Thus we are left with the best places to camp in De Soto National Forest, at least by these factors. Enjoy your next visit! 

Flow Line Mapping

Greetings All,
       This post is all about flow line maps, and this weeks exercise Cartography assignment involving creating a flow line map. The objectives for this week were simple, create a flow line map using proper design techniques, calculate the appropriate / proportional line widths, and apply style and visual effects utilizing Corel Draw x7. The map below was created entirely in Corel Draw, with two base maps of the Worlds Countries, and a choropleth of United States immigration provided by UWF.
       Flow Maps defined: These are maps which are used to depict the movement of some phenomena between various geographic locations, most often utilizing lines of varying widths or tones to represent how much movement there is. Further, the map below is sub-categorized as a Distributive flow map. That is a map focusing on the movement of commodities, people, or ideas between geographic regions. This is why we are using this style of map to look at Immigration to the United States in 2007 as the main theme.

Here is my flow map, broken down into three parts; the main map, inset map, and the main map legend. 
Overall I wanted to maintain a certain simplicity with a light background to not detract from the focus elements, Ie the flow lines. There are two main stylistic effects employed. The drop shadowing which is applied to the flow lines as well as the countries in the main map. These are to help break up the figure ground. The countries become figure to the ground that is the oceans while the flow lines which are so much more bold are still figure to the ground that is the rest of the main map. 
The inset map features a choropleth of Percent of total immigrants by state, which is shaded in tones similar to the background. I wanted to keep this area de-emphasized compared to the main map. However i wanted to ensure the data you are looking for becomes readily apparent. I utilized beveling in the states with the highest percentage values. I chose to do this because there are only 11 states in the upper 4 of 5 classes for the classification method used. This made it easier to distinguish just these states and not wash out large areas with too much bevel. The bevel height was adjusted to reflect lower to higher while maintaining a sequential color scheme. 
The third pane with the map legend simply highlights the flow lines through proportional width while also specifying the total immigrants per region. In incorporates the same effects as the main map, predominately the drop shadow.
I hope you enjoy my flow map, thank you.

Isarithmic Mapping and To Contour or Not To Contour.

Good day readers,
      The subject of this post is this weeks Cartography assignment dedicated to Isarithmic mapping. That is maps that depict smooth, continuous phenomena such as rainfall or temperature across an area. The most common of these is a contour map. Before we get any further lets look briefly at the assignment and some of the objects I worked toward along the way. This assignment was based of the school provided data of precipitation over a 30 year cycle for Washington. It was mapped entirely in ArcMAP. Some objectives are as follows:

• Define an Isarithmic Map, review different kinds of isarithmic maps
• Identify appropriate data types for Isarithmic mapping
• Recall different interpolation methods (Triangulation, kriging, Inverse Distance Weighted, PRISM)
• Recognize the different symbolization methods
• Describe the basics of and create contour lines
• Work with continuous raster data
• Implement continuous tone symbology
• Implement hypsometric symbology
• Employ hill-shade relief 

The biggest difference between the two final products below is the method of symbolization. The two methods portrayed are that of Hypsometric Tinting (first / preferred map) and a Continuous Tone map. Lets look at the definition followed by the map employing the technique.

Hypsometric Tint: These are shaded or color scaled areas between contour lines that enhance your ability to visualize a 3-D surface because we can associate the lighter colors with lower values and darker colors with higher values. 

As you can see this map is classed, showing specific value ranges for each specific color. It is also contoured to given further definition to the changes in value. Interpolation and the PRISM method are both introduced to help interpret the map. Given that we want to know where the areas of higher and lower rainfall occur, and both are equally important a diverging color scheme is employed. Not the dark orange for lowest values, and dark blue for highest.  Hill shading is also employed, essentially breaking out the natural terrain be adding shadow to the terrain features.

Continuous Tones: This style differs from the above by showing a smooth transition for all values, where each point is shaded with a color tone proportional to the data value at that point. 

This map shows a steady changing in color tone from the lowest to highest values. You can see that this causes some washing our of areas with very steady values such as the eastern portion of the state where values are lowest. you lose a sense of the depressions that is more clear in the hypsometric tint map. Hill shading is also employed. As this was not my preferred map I chose not to employ contour lines on it. given the washed out nature of some of the colored areas, when employing contours they appeared more haphazard given the values they represented.

This has been a look at Isarithmic maps. Thank you for your time.