gis portfolio - tristandamron

1 | G I S P o r t f o l i o

GIS PORTFOLIO

Created by Tristan Damron


To whom it may concern:

The examples in this portfolio were created using Esri’s ArcMap software unless explicitly stated otherwise.

Furthermore, these examples were compiled during my time in Western Oregon University’s GIS program.

All works in this portfolio licensed under a Creative-Commons Attribution License | November 2017


MAPPING CONCEPTS

Mapping is a key part of GIS. It allows us to view data spatially in a way that is easy for most people to

understand. It is important, therefore, to use proper mapping technique to best present the data you have

been working with.

There is a hierarchy of importance in mapping. In order from most important, to least:

1. Thematic symbols

2. Title, Legend, Labels

3. Base map – Key Features

4. Base map – Other Features

5. Scale, North Arrow, Source, Neat-line, Graticule

Keeping this hierarchy in mind when creating a map ensures that your map has proper composition.

Another key component of map design is the ability to represent your data in a way that makes sense to the

audience. Doing this keeps your maps easy to understand, yet to the point. Using proper symbols for the data

that you are presenting is an effective way to make your maps understandable.

On the following pages, you will find a series of maps all with proper technique.


Figure 1

Figure 1 shows a map of Manhattan, Queens, Brooklyn and the Bronx and displays the police precincts in the

area. This map also displays the major streets in the surrounding area, as well as the surrounding state, New

Jersey. This map uses the GCS_WGS_1984 coordinate system for its projection. The map contains vector data:

point data, (precinct locations,) and polygonal data, (shape file of city limits.) This map follows standard

mapping concepts and includes a north arrow, a neat line, labels, and a ratio for scale.


Figure 2

Figure 2 represents the population of the contiguous 48 states in 2010 as a dot density map. Each red dot on

the map is valued at 10,000 people, as shown under the title. One feature that this map has that is different

from the previous map shown above is the addition of a graticule. This map also features vector data:

polygonal data, (state boundaries,) and point data, (population.) Like in the previous map, this map features a

north arrow, neat line, and scale bar. I am very proud of this map; I think that the contrasting colors work

very well.


Figure 3

Figure 3 shows a map of Polk County, Oregon and the location of cell phone towers in the county. The

symbols on this map were intentionally chosen: the symbol for cell phone towers are yellow and look like

bursts of energy to represent electricity. This map also features many standard map design concepts

including a neat line, north arrow, and legend.


Figure 4

Figure 4 is a reference map of the city of Florence, OR. It features vector data of the area that have been

clipped from a much larger vector of the entire state. The map has labels for the roads, water features, and

parks. This map was chosen because it represents good map symbology: there are clear labels and the

features are correctly classified based on their physical characteristics. This map has standard map design,

featuring a north arrow, neat line, and a legend.


Figure 5

Figure 5 is a thematic map showing the current territorial claims on the continent of Antarctica. This project

was created using QGIS. The vector polygonal data was sourced from earthworks.stanford.edu and NASA. This

map follows standard cartographic technique with a graticule, good symbology, and a detailed legend.

Furthermore, this map features an offset background on the continent to give it more depth.


DATA

We are living in a world controlled by data. It is in everything we do, say, and think. With the birth of the

internet, it has never been easier to find and create new data.

With all of the information in the world, ethical decisions are frequently being made. Questions such as “Is it

okay to collect this data,” or “What are the implications of publishing my findings,” must always be asked by

GIS Analysts. Data is power, and we must use it responsibly.

While there is a seemingly infinite amount of data in the world, GIS primarily deals with spatial data.

There are two basic types of spatial data in GIS:

1. Raster

a. Pixel based, with defined cell size.

2. Vector

a. Not defined to a specific size, and can be manipulated easily.

A simple example of each is raster data is like an image, while vector data is like a line or a point.

The following map samples demonstrate different types of data I have used.


Figure 1

Figure 1 shows a map of the coastal Pacific Northwest and major earthquakes since 2150 BC. These data are

from NOAA’s National Geophysical Data Center, and the map was created in QGIS. The points on this map are

well labeled with the name of the area where the earthquake occurred. The earthquake data being shown is

vector point data. This map features standard mapping design with a scale bar, neat line, title, and labels.


Figure 2

Figure 2 shows a choropleth map of the relationship between population data in New York City and the

number of fire houses. The red dots represent fire houses, and the colored areas indicate population density.

The data for population was broken into 5 categories, from white to black where the darker areas mean a

larger population, and lighter areas mean a smaller population. 5 categories were chosen using a natural

breaks algorithm so as not to clutter the map with a large number of classes which could make the map

difficult to read.


Figure 3

Figure 3 demonstrates the use of another type of data: raster data. Specifically, this map shows an aerial view

of the Columbia River Gorge. This effect was achieved by taking the original raster data, (which lacked much

of the detail shown above,) and applying ArcMap’s “hillshade” to the data. Raster data is continuous data and

is great for creating maps with extreme detail and accuracy.


Figure 4 is a map of voter turnout in the 2016 presidential election by state made in QGIS. This map uses a

vector shape file to outline the states, while the turnout data was entered by hand into an attribute table.

The turnout data was retrieved from www.electproject.org/2016g. The data classification was defined by a

natural breaks algorithm. This map features some standard map design with a title, legend, and well defined

classes.

Figure 4

http://www.electproject.org/2016g




Figure 5

Figure 5 is a map of Pittsburgh, Pennsylvania. Specifically, it is a map showing the frequency of out of hospital

cardiac arrests, (OHCA) in the Pittsburgh area every year. This map uses a combination of vector point data,

(the yellow spheres,) and raster data, (the topography layer and the city layer.) This map features standard

map design with a title, legend, neat-line, and well defined classes.


OVERLAY ANALYSIS

Data in a GIS is often represented in layers. Overlay analysis allows us to take multiple layers or spatial data

and run them through an operation to produce a desired result.

Some common operations of spatial analysis are:

1. Selection

2. Reclassification

3. Dissolve

4. Buffer

5. Overlay

6. Clip/Erase

7. Intersect/Union

The following map examples demonstrate different types of overlay analysis.


Figure 1

Figure 1 shows a map of western Oregon and the habitat of a rare butterfly, (they thrive in forested areas

near water.) Using a concept called overlay analysis, I was able to take a layer of schools, and a layer of the

forest to see where they intersected. I then took the river layer to put a 200 foot buffer around the rivers to

see what schools were within 200 feet of a river. The outcome was the schools where these butterflies could

be found. This map also follows basic map design with a legend, title, labels, and well defined features.


Figure 2

Figure 2 is a map with many overlay operations going on. The gray areas were clipped from a larger data set,

as were the black lines. The red lines were generated by finding where lines intersected through the gray

areas. The green area is a buffer around the black lines that intersect with the gray areas.


Figure 3

Figure 3 shows a map of smoke sensitive areas in Oregon during the Summer of 2017. This map, more

specifically, shows counties that are affected by the smoke and the population of each. This map was created

using QGIS, and features vector data, (county outlines, smoke sensitive areas,) and satellite imagery as a base

map. This map features standard mapping concepts and features a north arrow, legend, and a scale bar.


Figure 4

Figure 4 shows a map of TriMet's, (a local transportation company in Portland, OR,) service coverage across

the city. The map was created using QGIS. This map features line data, (TriMet's routes,) polygonal data,

(neighborhood boundaries, buffer, census tracts,) and point data, (homes within the buffer.) Buffer

geoprocessing was used to achieve the desired result for this project. This map follows standard mapping

concepts and includes a north arrow, a scale bar, and a legend.


ONLINE GIS

The internet is a fantastic tool for bringing people together. It is also a great tool for publishing your content

and getting it out to a large audience for free or cheap.

This is where online GIS thrives.

Online GIS allows us to manipulate, store, and display spatial data using a web browser. This information,

once published online, is available to the entire world. Because of this, Online GIS is proving itself to be an

exciting future for the industry.

The following sample was created using Esri’s Online GIS tools and can be viewed at the following url:

http://arcg.is/bLvi9

http://arcg.is/bLvi9


EDITING

Editing is a powerful tool that allows us to turn polygons, lines, and other symbols into special data that can

be projected on to a map. These data can be added to existing data sets, or created as an entirely new data

set.

These symbols can be used to represent roads, buildings, water features, or anything that occupies space.

They are a

Editing is especially useful when you need to fix an existing data set. Sometimes, data sets are hastily put

together and broken. In industry terms, we say that the features have poor topology, (how the features

occupy space when related to one another.) Editing allows us to correct slivers (where two polygons do not

line up correctly along an edge,) dangles (where a line overshoots or undershoots another line it was

supposed to intersect with,) and issues with snapping (where points on a polygon do not line up.)

The following map examples feature edits that I have made.


Figure 1

Figure 1 shows a map of a fictional bus line in Pittsburgh, PA. The polygons, lines, and points were all edited

by hand and added to a new data set. The labels on this map represent the names of the bus lines.


Figure 2

Figure 2 shows a map of the residence halls at Western Oregon University, and a path that connects them to

the rest of campus. The polygons and lines were edited by hand and added to a new data set. This map

follows standard map design with a title, legend, north arrow, neatline, scale text, and good cartographic

technique.


NETWORKS / GEOCODING

Networks are an important part of modern applications of GIS. They are, simply speaking, a series of

connecting nodes by which logical paths between the nodes can be made. The paths between the nodes are

known as edges, and a junction is the point at which two or more edges intersect.

An application that most people can relate to are GPS directions. Using an application such as Google Maps, a

GIS uses a network to make a path for you from your current location (the source,) to your intended

destination (the sink.)

Applications such as Google Maps using geocoding to take an address and translate it to a physical point on

Earth’s surface.

The following map example demonstrates what networks and geocoding can do in ArcMap.


Figure 1

Figure 1 shows a delivery route for a baking delivery company in San Francisco. The networking was done

using ArcMap’s networking tools. The path that is shown is the most efficient route to all of the destinations

that are expecting deliveries. You may notice the red “x” on the upper-left portion of the map. This signifies a

block, an area that the path cannot cross. This map follows good map design practices and features a title,

neatline, north arrow, and scale bar.


Figure 2

Figure 2 shows a map of the number of participants in a hazardous waste recycling event held in Allegheny

County, PA. This map was made by geocaching the addresses of individuals who attended the event. The

result was a map showing the concentration of attendees from different areas of Allegheny County and the

surrounding areas. This map follows standard map design with a legend, title, north arrow, and neatline.

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