Not all spatial analyses can be done through computation and formulas. Visualization remains one of the strongest methods for analyzing data on a map. In tandem, visualization and computation is what gives GIS its powerful communication elements.

Types of Analysis

Overlay is one of the most common types of analysis. It is particularly useful for revealing areas that share similarities in two or more attributes.

• Buffers are a method of overlaying used to include areas around an object to be included in the analysis.

Set theory, a mathematical construct, is the basis for analysis in a variety of information systems including GIS.

• Set theory can be expanded on raster data using map algebra, which adds, subtracts, multiplies and divides values associated with spatial areas.

Reclassification, a very useful technique for generating new values, can be achieved using map algebra. A huge plus is that reclassification does not change the definition of spatial units.

“All models are wrong, but some are useful” (107).

There is a general assumption that models reflect the agenda of those that made it. Every map has a purpose – some are more obvious than others, like in the realm of political humor. However, Shuurman warns that models are quickly confused with reality, especially if they have been accepted to society for a significant period of time.

An understanding of the concepts of GIScience is necessary to use GISystems to their full potential. It is not a simple application of making map pictures but generating visual images to conduct spatial analyses can then be used to predict spatial phenomena (148).

“The map is not a neutral representation of territory, but a representation of social relations” (24).

Epistemology and Ontology

Epistemology consists of the methods that we use to understand the world, the perspective in which we see it in order to interpret it.

Four aspects of epistemology-

Ontology is what something really is – its true self. The relation between them is that we use epistemology to interpret the ontology of things. A person’s epistemology of something is dependent on the ontology of it.
Generalization is the elimination of map detail as the scale of the map decreases.

Global Positioning System—

GPS is based on a system of 24 NAVSTAR satellites that continuously circle the globe. Triangulation is the basis for this technology. Three satellite signals is the minimum for obtaining an accurate point location measurement.

Organizing Data
GIS data is stored in tables, like all information systems.

Four essential components to spatial data sets:

Metadata – information about the data. Metadata makes it easy to combine data sets, and without it is nearly impossible.

Standardization - homogenization of similar attributes or entities as a means of using multiple data sources.

An interesting fact: cartographic research has shown that map readers cannot understand more than 7 different categories on a map.

Discrete Features:
Lines, points, or any other locations that can be pinpointed. Essentially, the feature is either there or it is not. Ex: the location of a mountain.

Continuous features:
Cover an entire map leaving no spaces in the data. The phenomenon that is being mapped most likely exists all around the globe, so there are no boundaries for this type of data, only divisions within the data. Ex: temperature across Ohio

Features summarized by areas:
Represent counts or densities of individual features within certain boundaries. Ex: density of schools in Delaware County.

Representing geographic features—

Vector model:
Data is characterized by being on an x,y coordinate plane. Each vector feature consists of points that are plotted on an x,y plane and are then connected by a line, or vector. Vector data can include anything from line to polygons. Anything that can be plotted using x and y is vector data. Most vector data is discrete.

Raster Model:
Data is made up of many small cells representing continuous space. Raster data can include many different layers, with which new raster data can be produced. The raster model is used to map continuous numeric data, such as precipitation or vegetation.

Types of Attributes—
Categories: groups of similar things. Ex: roads that are highways, or roads that are one way.

Ranks: features put in order form high to low. Ex: homes with the highest sell value to homes with the lowest sell value.

Counts and Amounts: actual numbers of a feature. Ex: number of employees at a business.

Ratios: show the relationship between two quantities to more evenly show distribution of data. Ex: density of population within a certain number of units per area.

• All map projections distort the shapes of the features that are being displayed (15).

Mapping represents geographical data in a visual form. It doesn’t create more information than what was originally used, but it allows us to discover patterns within that information.

Earliest computer cartography system in 1964 – Roger Tomlinson and Lee Pratt developed the Canada Geographical Information System.

Visualization is used to manufacture meaning from data when we render it as an image. This allows us to “see” spatial patterns.

GISystems versus GIScience:

• GISystems refers to the technology (hardware and software, like ArcGIS) which is used to compute and translate data onto a map. It refers to any sort of data collection, sorting, classifying, analyzing, and mapping associated with spatial data.

• GIScience refers to the theories and concepts involving spatial relations that underlie those systems. GIScientists ask questions about the data that is stored in a GIS that may go overlooked, such as how the software knows where the boundaries of a place are in relation to another feature.

Application: “GIS-generated maps are the basis for spatial decision making…” (16).

There are two main components that need to be considered when finding what’s inside the place that you are mapping:

Are you mapping a single area or multiple areas?

Single areas are things like buffers, natural boundaries, or something you draw manually. Multiple areas can be contiguous (ZIP codes), disjunct (state parks) or nested (floodplains).

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Once you figure that out, you must determine if the features of the map are discrete or continuous.

Discrete features: location (cities), linear features (roads), discrete areas (parcels)

Continuous features: spatially continuous categories or classes (precipitation, vegetation), continuous values (elevation)

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Finding information about the features that are inside can be done in a  variety of ways. You can:

get a list of the features inside, count the number of features, count the number of features that fall under a certain category, sum the value of the features, or sum the values of features that fall into a certain category.

There are three ways to see features that are partially in a certain area.

You can show only the features that lie completely in the area, you can show the feature completely if it lies in the, or you can show the part of the  feature that only lies within the boundaries of the area.

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There are three good ways of seeing the areas and the features of your map.

Drawing them: good for seeing whether something is inside or outside a certain area.

Selecting them: good for getting lists.

Overlaying them: for finding what lies in multiple areas

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When working with GIS…

Using the vector method can create “slivers” when overlaying areas.

Should you use vector or raster?

Vector is best for seeing areal extent but requires a lot of processing.

Raster is the best for comparing and it is much more efficient. It often categorizes everything automatically, though it can be less accurate.

Goals for our project—-

Removing stereotypes:

• We want to develop a map that helps to alleviate our audience from their personal perspectives about and area. We want to show and engage them in something they rarely or never have thought about, particularly about wildlife.

Promote contact:

• By creating an engaging and inspiring map we hope to encourage our audience to take it a step further on their own. If we go with wildlife, for example, encourage people to bird watch, or something of the sort.

Inform and educate:

• What any good map should do. We have yet to narrow down our audience (though we have an idea), but we need to think about what they already know, what they should know about our topic and what they want to know.

Ideas for actual project—

• Wildlife—Map bird watching locations and patterns. Inform the public of all kinds of birding location around campus or Delaware. Data is accessable.

• Geology—Noting spectacular points of interest in topography and geologic features around Delaware (sulfur spring, Delaware watershed, rock formations). Getting people to imagine the “scale” of geology

• Geothermal hotspots, dynamic processes…? Data may not be accessible

Both these things can be something like “Wildlife Tourism” Nature niches.

Audience—

• We do not yet have a specific audience that would be best to target for our project. One idea is that we target younger kids and their teachers to get them into the wild (birding and topography, etc.) In some way we want to target people who would not normally think about or participate in the subject we choose to base our project on. However, what guarantee’s uninterested people would still look at our map?

Format—

• We haven’t developed this very much, but we definitely want to add supporting document, whether digital or printed to accompany our final map, like a brochure or a website with links to further information.

The first one is a sustainability map of a town called Craik Village in Saskatchewan, Canada. They worked with an organization known as Green Maps to promote their project of a sustainable, environmentally productive community. This map shows all of the eco-friendly buildings and plans for even more eco-friendly places around the town.

The following is a link to the project’s website. There you can find the bigger map as well as the legend. Both are in PDF format available for download:
http://www.craikecovillage.ca/greenmap.html

The second is a map layer viewer, similar to ArcGIS, of Alachua County in Florida. This map details every “green” building, location and industry in the county. It also includes the locations of significant places that act as cultural and preservation utilities, like bike routes or historic buildings. It also identifies conservation and recreation points like nature preserves, and it includes “green pathways” including bus routes and scenic roads. All for these layers can be turned on and off for your viewing and it seems to be a nifty application of animated GIS technology.
Here is the link to that map viewer:
http://maps.alachuacounty.us/geogreen/viewer.htm

The third green map I found is of New York City. The site I got it off of actually has a set of environmental green maps of NYC and is a very cool project. I liked the idea of the compost map of Manhattan. It includes a variety of locations that use composting, in all sorts of ways, like gardening, or green markets.

This link takes you to the Green Maps NYC website. To get to the bigger version of this map, click on “Our NYC Maps,” scroll down to “themed maps” and click on Compost Green Map:
http://www.envirolink.org/external.html?www=http%3A//www.greenmaps.org/nyc/&itemid=20000429112421601417

We begin with the overview of geospatial analysis and the technology that has come about related to this topic in our first reading of the week. Geospatial analysis involves the tools and techniques related to spatial analysis in addition to modeling by Geographic Information Systems and other software. The authors of this guide are determined to cover very specific details and wide-ranging applications, because geospatial analysis can involve many, many different types of topics. What makes geospatial analysis so significant, and successful, is the ability to apply it to and solve real world problems. In order to understand how that works, we must become “spatially literate” in both data and mapping.

According to the guide, we must also recognize the rapid increase in tools and computing technology made available for use by geospatial analysts. These programs should be divided in a way that does not confuse direct spatial analysis and bare bones analysis, even though the most basic input of data converted to a 2-dimentional plane is considered geospatial analysis.

Geovisualization is another important aspect. It is the use, creation and manipulation of maps, images, 3D views, satellite imagery, charts and digital globes. Animated maps and globes fall under this category.

Here are some definitions found in the guide that I think are significant:

Attribute – a data item associated with an individual record in a spatial database. They may be explicit (stored and linked to a data set) or implicit (stored but hidden, sometimes calculated)

Spatial Autocorrelation – a relationship existing between sets of data so that if one changes, the others change as a result. These changes can be positive (in similar directions) or opposite (in opposing directions)

Conflation – to merge two sets of data into a single source, fixing inequalities where they may happen

Geoid – an imaginary shape for the Earth defined by mean sea level with the continents and gravity the same as before, so that some of the land would be seen underwater.

Geospatial – a location relative to the Earth’s surface

Invariance – properties or features that remain unchanged after transformation to a different spatial form

Spatial econometrics – an econometric method dealing with spatial aspects present in cross-sectional and space-time observations

Tesseral/Tessellation – a gridded representation of a plane surface into disjointed polygons

Affine Transformation – when a map is digitized

There is a lot of mathematics associated with geospatial analysis and its software. The rest of the introductory portion of the guide provides examples of some of the equations and notations used in the software, such as measures of spread, measures of centrality, matrix values and common distributions.

The TED uses an applied program that recognizes keywords in tweets across the globe such as “tremor” or “earthquake” and places those posts into a database. The USGS then takes that information to determine the location, magnitude, etc.  The quake information is then placed on a map program similar to  GoogleMaps with the tweets marked where they originated from.

This application of GIS systems and social networks is proving to be an extremely fast way to map out even the slightest tremors.

This is an interview with USGS’s Paul Earle and Michelle Guy on TED:
http://www.usgs.gov/corecast/details.asp?ep=113

Here is an article on TED from ecopolitology.org:
http://ecopolitology.org/2010/01/07/usgs-develops-twitter-based-earthquake-detection-system/

And here is the actual TED twitter page:
http://twitter.com/USGSted