Geog 355 Blog Updated for Spring 2019

January 15, 2019


Fall 2018 offering of Geog 355: Delaware Data, Midterm, and Project

September 30, 2018

Regardless of your position on police bunnies, we are nearing the halfway point of Geog 355 and I have a few updates for you:

  1. You are diligently compiling your progress on the readings and ArcGIS tutorial, on a blog created for the course. Please continue to update me as you add blog postings. Roughly follow the course schedule.
  2. Get going on the Delaware Data Inventory, and complete (with a blog posting indicating such) by Sunday, October 14.
  3. Review the postings from last spring on the Delaware Neighborhood project:
  4. Janelle is working on getting some background information on the Neighborhood Mapping project and she and I will be in touch about the project in the near future.
  5. Once you finish the Delaware Data Inventory and ArcGIS tutorial, you can get going on the Midterm Evaluation. This will be a butt-load of fun and will put your brain deep into the world of doing stuff with GIS. Due Friday, October 26.

Week 7 Updates: Delaware Data & Midterm!

February 26, 2018

Delaware Data Inventory (due Friday, March 9)
Midterm Evaluation (due Wednesday, March 21)


Week 4: Updates

February 9, 2018 Delaware, Ohio Neighborhoods

After a bit of kanoodling about, I managed to get added to one of the Delaware neighborhood groups (Southside Delaware, which includes OWU’s campus).

I then did a series of screen captures to get the entire map (above) of Delaware’s neighborhoods, according to Right mouse click on the map to get a bigger version.

I think this is a good starting point for our project. Keep searching for other relevant information (Delaware wards, subdividions, HOAs, etc.).

And keep up with the readings and such on the schedule.

Week 3: Updates

January 30, 2018

After our rousing meeting on Monday a few things can be reiterated:

  1. Please create your class blog and get me the URL by Thursday
  2. Please consult the course schedule and make a single weekly blog posting that includes
    1. reading notes (so I know you read the stuff)
    2. progress on the tutorial (when we get to it)
    3. project ideas, work on proposal, and updates
    4. other pertinent stuff (such as progress on your writing option, if you are doing one for this course)
    5. email me when you post your weekly post (no later than the Sunday at the end of the week)
  3. Lets plan to meet on Mondays at 1-2pm until further notice.
  4. I’m going to look into ArcOnline accounts for us
  5. We seem to be settling into the Neighborhood Mapping project
    1. scale is an issue:
      1. Delaware has wards (four of them, look it up)
      2. Below that scale, there are neighborhoods (“Downtown”)
      3. Below that scale, there are smaller neighborhoods (“Downtown SoWill” – downtown south of William St.)
    2. sometimes neighborhoods correlate with subdivisions (“Wesleyan Woods”): GIS data on subdivisions
    3. subdivisions have HOA boundaries (Home Owner’s Association): GIS data on HOA in Delaware?
    4. demographic data: from US Census: blocks, block groups, Census tracts (see below: two graphics)
      1. demographic data can be used to create neighborhoods, but this is a bit dangerous (why?).
      2. demographic data can be associated with neighborhoods (say, poverty rate), but this might also be a bit dangerous (why?)
      3. if the City wants to be able to match demographic data to neighborhoods, the neighborhood boundaries have to follow census boundaries (block, block group, etc.). This is important to build into the neighborhood boundary making from the start.

  1. Preliminary proposal, due Friday, February 9. This may be one big proposal, or several related smaller proposals. We’ll figure that out.
    1. Details on Project Proposal
  2. Go back and, individually, complete the Defining and Mapping Neighborhoods stuff from the previous update. Put on ye blog!
  3. Teh major issues: preliminary: these may be sub working groups and writing options if need be:
    1. Literature on Neighborhoods
      1. Academic – Planning, Urban Studies, Geography, etc.
      2. Other literature
    2. Literature and info on methods for determining neighborhoods
      1. surveys
      2. historical research (on Delaware)
    3. Using GIS to map and communicate neighborhoods
      1. including ArcOnline to make the data easily available

Please email or talk to me if you have questions along the way. Bothering me is better than you not doing what you are supposed to do!

Week 2 Updates

January 23, 2018

First: Create your course WordPress blog and email me the URL (by this Friday, January 26)

Second: Do the stuff as suggested on the course schedule.

Third: Make a single weekly blog posting that includes

  • reading notes (so I know you read the stuff)
  • progress on the tutorial (when we get to it)
  • project ideas, work on proposal, and updates
  • other pertinent stuff (such as progress on your writing option, if you are doing one for this course)
  • email me when you post your weekly post (no later than the Sunday at the end of the week)

Writing Options: if you want to keep the writing option, please do the following

  • let me know you are doing the writing option (email) before Friday February 2
  • include a paragraph or so describing the writing option paper
  • outline of the paper due by Friday March 2
  • draft of the paper (rough is ok) due before spring break


We are headed towards a preliminary project proposal, due Friday, February 9. This may be one big proposal, or several related smaller proposals. We’ll figure that out.

It seems like we are levitating towards a group effort on defining and mapping Delaware Neighborhoods

  • If you are interested in working on something else, talk to me.

We will work with the GIS Coordinator for Delaware (Rachel Hostetler) and her office (including Janelle Valdinger)

Brad B. is doing an internship at their office this semester, and will work on the project there and as part of our course. Janelle works there, so she will be able to help with coordination between the Coordinator and ourselves.

Defining and Mapping Neighborhoods: each of you…

  1. What is a neighborhood? Dig around (internet, library resources, etc.) and write-up a paragraph. Write another paragraph on neighborhoods (Delaware or otherwise) you are familiar with
  2. Find three examples of neighborhood mapping: like Columbus Neighborhood Map
  3. Sign up on (try your Delaware or actual home address): it’s a kind of social media but limited to neighborhoods. How do they determine what a neighborhood is?
  4. Literature search: defining and mapping neighborhoods: find five potentially useful sources that address ways that neighborhoods are defined and mapped.
    • Like this: “Defining Neighborhoods for Research and Policy” by Claudia Coulton (Cityscape, Vol. 14, No. 2, 2012, pp. 231-236)
    • Be creative with your keywords: “neighborhood” GIS or “neighborhood” “define” “mapping” etc. Don’t include sources that are not particularly relevant.
    • When you find a good source on Google Scholar, click on the link that says “Cited by” and this will take you to additional sources that cite the source (and, thus, were published later). This is a good way to find additional sources. Full text links (for some sources) are to the right of the source.
    • If you find a good source, but there is not a full text link, use our Library resources to find the full text (Summon and online databases).
    • Email and talk to Krygier
  5. Five sources from these sites (or others):
    1. Search Google or Bing (in general)
    2. Search Google Scholar
    3. Search Summon (via OWU Library: the All search on this page)
    4. Search our online databases
  6. Create a brief annotated bibliography of your sources and put on your blog: what’s that? Look here.
  7. Begin to sort out major issues in the topic, to help us form sub-groups: for example:
    1. Theoretical literature on how neighborhoods are defined
    2. Methods for determining neighborhood boundaries (including surveys, etc.)
    3. GIS and mapping and neighborhood determination
    4. And so on… these could be the individual writing option papers (which, at the end, we compile together into a handbook on the topic).

A few additional issues:

  • We may have Brad work on a prototype project that shows us how we can go from the data to ArcGIS to ArcOnline. Look up what ArcOnline is about.
  • We may be able to work on a second set of more natural “neighborhoods” – Anthropogenic Biomes (article) and a previous course project “A Proposal for Delaware County Anthromes.” Review the Proposal document and jot down a few notes in your weekly posting.



Geog 355, Spring 2018: Week 2: Getting Started

January 22, 2018

  1. Review syllabus, schedule, readings, blogs
  2. Updated Projects page with examples of proposals, reports, maps, etc. for selected projects
  3. Discuss Project Ideas

Updated for Spring 2018 Version of Geography 355

November 2, 2017

Monday March 24: Projects

March 24, 2014


Time to get going on the projects, none of which, thank God, involve poorly conceived haircuts from the early 1970s.

1. Project Blogs

Make sure that your group are all able to get access to the project blogs I set up earlier in the semester. Make sure you put any relevant information for your project, including the preliminary project proposal, on the project blog.




2. Updates for each group:

Delaware Run:

I gave Ali Smith a copy of the document Peter Schantz sent me with his concerns from the perspective of Buildings & Grounds. We need to take those concerns and expand them and supplement them and develop an ArcGIS MXD file with appropriate data (using existing Delaware data, and data you collect).

Del Run MXD Project File: Ali Smith has been working on a MXD file that has relevant Delaware data layers. Part of this requires figuring out more information about each layer (such as what the soil types are and what they mean), the flood plane information, etc. You then need to plan for additional data collection: trees, (potentially) soil samples, infrastructure, etc. At this point: figure out a list of data you think would be relevant to the project and start to plan how to collect that data and get it into the MXD file

Thermal/Urban Heat Island:

I am having the QGIS software installed on the Geography Research room computer (224). That might take until the end of the week. In the meantime:

1) Carefully review the information on the tutorial I gave you last week, and see if you think you will be able to do the QGIS Tutorial once the QGIS software is available: Review the online info for QGIS.

2) Review info on Landsat Data.

3) I have had EarthExplorer recommended as the site to access and download the thermal IR data. This will be band 6 of the Landsat data (see the review PDF in part 2 above).

Chimney Swift / Bird Habitat:

1) Make sure that we have copies of the plans for the swift towers in a format that the contractor can review (also B&G). I believe Alex had this in Sketch-up but we need to print. I can get files printed in color at Duplicating.

2) Plan for revisions of the bird habitat map. The previous version, b&w copies of which I can give you today, is not so great. I suggest we start with a fresh MXD file of campus and surrounding areas (walkable from campus) and start to map out the different habitats as areas. There is a start to a classification of bird habitats on the old map: we can start with that. Look up additional info on defining urban bird habitat. Start to compile data into a MXD file. Plan for a map that fits on tabloid sized paper and can be used in the field. We will also map out existing bird houses, feeders, etc.

Dick Tuttle will be in class Wed and we need to review the plans with him (have printouts) and also get input from him on the habitats map.

Tech / Drone:

I suggest that Christian & Chris work with learning to operate the Drone and take images. We need to figure out the optimal resolution and other details for taking imagery.

Patrick can work on stitching together the imagery and adding coordinates (so we can display the images in ArcGIS): I will have Windows Photoshop installed soon. For now, the Mac in the back room off the GIS lab has an older version of Photoshop. There are also sites online for stitching together air images. Check out MapKnitter first, then CleVR or AutoStitch.

Reading: Schuurman ch 2 & 3

February 18, 2014


On no snow for Christmas in Finland

Schuurman: GIS: A Short Introduction

Ch. 2: GIS, Human Geography, and the Intellectual Territory Between Them

GISystems & GIScience based on assumptions that privilege certain approaches to understanding the world (natural and human).

Geography: diverse, undisciplined discipline, origins in 1800s

GIS since the late 1960s, parts of cartography & quantitative methods

  • sometimes rocky relationship between these and Geography in general

Mind the Gap: The Distance Between Human Geography and GIS

Little overlap between GIS and Human Geographers until the late 1980s

Geographers critique: GIS is mere technique, no intellectual component

  • GIS processes facts, but can’t generate meaningful understanding
  • GIS based on positivism and/or naïve empiricism: neither well respected approaches/theories in Geography

Positivism/empiricism: experiment/test/trial: sense perceptions are the only admissible basis of human knowledge and precise thought; natural and social processes can be understood (via hypothesis testing and data analysis) and follow strict laws; designed to supersede theology and metaphysics.

  • ex) central place theory in Geography
  • ex) much of science and some social science.
  • ex) less comfort with qualitative methods
  • ex) less comfort with theories that use empirical data but don’t see laws governing human behavior and activity (feminism: role of gender in shaping society, but these are not laws – they can be overcome and changed for the better of all)

1980s: lots of debates

  • GIS people with a more positivistic, scientific approach vs human geographers with more qualitative, social theory approaches
  • GIS very limited view of the world, requires very specific, empirical data, can ask very specific questions, and get very specific results.
  • GIS driven by corporate and military needs
  • GIS expensive and exclusive; elitist

Brian Harley (The Nature of Maps), Denis Wood (The Power of Maps)

  • critique of maps: social constructions for creating and maintaining power
  • selectively show certain things, not others; create and enforce social status quo
  • maps create a space of political territories (broader scale) and privately owned property (detailed scale) and make those human conceptions real in the landscape
  • ex) the “nation” / “states” – relatively new concept; problem in Mid East
  • ex) property ownership: relatively new human concept
  • ex) zoning

Maps created by elites to shape and enforce geographic reality to suit their needs

John Pickles: Ground Truth: apply same critique to GIS

  • GIS is for maintaining order, just like paper maps before them
  • Friday Harbor meeting: beginning of a dialog
  • alternatives: Particapatory GIS, counter-mapping, qualitative methods “GIS2”

Epistemology and Ontology in GIS

  • epistemology: the methods we use to study the world; each has assumptions and perspectives that shape the questions, analysis, and interpretation of results
  • ontology: what things really are (how the world must be to make sense of it)
  • ontology (computer science)

ex) we have extensive GIS technology for determining the fastest route for an ambulance to get a sick person to the hospital, but we don’t ask why so many people get sick.

ex) GIS is used extensively to plan new developments and roads but is very much less able to help understand the extensive negative impact of such development on the environment

ex) Forest in India

Use quantitative methods to test IR energy reflectance from various types of vegetation and different kinds of land cover in an area; gather data, test hypothesis, generate specific measurable value that differentiates a forest from other areas.

  • Use remote sensing to define areas that have a certain % reflection of IR energy; any less than that % is not a forest, any more than that % is.
  • then create a map of forests (and not forests; can do this all in GIS from afar)
  • Empirical epistemology, we can “sense” reflected energy and use that do define and distinguish forest from other areas.
  • Empirical ontology: the world consists of measurable objects, some of which reflect energy and specific kinds of energy reflectance lead us to understand and locate real forests.

Use qualitative methods such as interviews and mental mapping to have different people in the same area of India show where forest is on a map, and describe what forest is to them

  • state foresters: will claim much more territory is in forest as it is their job to preserve and create forested areas
  • farmers: will identify tree covered territory as wasteland or unproductive land, not forest
  • forest dwelling, hunters/gatherers: will focus on areas that are diverse and provide them with food and resources; not “forests” planted by the foresters (not diverse, not a good source of food and resources)
  • a qualitative epistemology: assumes that the reality of “forest” is shaped by human social factors; collect data (mental maps) but interpretation leads to ideas of how a forest is a human construct, even “untouched” forest
  • a qualitative ontology that suggests that sensory measurements in the world are incapable of measuring and helping to understand the social construction of forest; “reality” is shaped and made via social processes.  Social theory explains social processes, but these are not “laws” or unchangeable.
  • Counter Mapping: Peluso: Whose Woods Are These?

Data Models and Ontology

Vector data model: point, line, area (necessary to encode data into the GIS)

  • People: US Census blocks
  • define an area as a particular block, count the number of people
  • all of space is filled with blocks
  • what is the real nature of humans and where they live?

Raster data model: grid of cells

  • land use: each cell (can be very fine) assigned a type of land use based on energy reflected from it
  • complex mosaic of land uses often generalized into agricultural, commercial, etc
  • again, all space is some kind of land use
  • what is the real nature of land use?

Object oriented data models

  • see all geographic features as objects; location as one attribute
  • group together similar objects (roads) and have subclasses (federal, state, local)
  • hierarchical: each “parent” object has attributes common to its subclasses
  • discrete, separate entities in a neutral space; can fill space or not
  • what is the real nature of any geographic feature?  “Forest” as an object?

All data models are reductionist: they simplify complex reality

Need to know how that is occurring and how it shapes understanding when using
GIS or any method

Looking for the Social in GIS

Social aspects of science, technology, GIS

  • ex) funding and research on health biased towards white males

Science as autonomous vs social

Kuhn: The Structure of Scientific Revolutions

  • paradigms: accepted practices and belief systems in science; structure how science is done until enough doubt is cast to accept a new system.
  • what is to be observed and scrutinized, the kind of questions that are supposed to be asked and probed for answers in relation to this subject, how these questions are to be put, how the results of scientific investigations should be interpreted.
  • ex) Copernicus proposed a cosmology with the Sun at the center and the Earth as one of the planets revolving around the Sun.

GIS technology: how have applications developed for the military and environmental science come to shape studies using GIS for non-military and non-environmental science applications?

What is the point ?

GIS is growing rapidly as a method used by diverse people and for diverse applications use growing faster than an understanding of the assumptions and limits of GIS particularly more conceptual, theoretical, even philosophical issues

Important to approach and use GIS with a few things in mind

  • it does tend to privilege one of many approaches to understanding the world: empirical, positivist, scientific; it is not the only way to address particular issues and is not “neutral” or “objective” or necessarily better than other approaches with different assumptions.
  • it is connected to social context: it is a powerful, persuasive tool that has been developed for military and government applications; it is used by experts with training and organizations with big budgets and power; it is in many ways a very elitist method for understanding the world.
  • GIS is always in flux: GIS is not set in stone: development of internet GIS: GoogleMaps and GoogleEarth and slew of similar applications: how will this more “populist” GIS open the door to different kinds of GIS and GIS analysis?  GIS technology will always evolve within a social context.

Schuurman GIS: A Short Introduction

Ch. 3: The Devil is in the Data: Collection, Representation, and Standardization

“Data are not the transparent manifestation of reality in digital terms.  They are the expression of particular points of view and agendas that begin as observations, and are transformed into numbers in data tables that provide the basis for spatial analysis.”

“Data are an artifact that reflects people, policy, and agendas.”

The Politics and Practicalities of Data Collection

Human data collection: often by area (Census block, zip code)

  • U.S. Census: Politics of counting people
  • Census count leads to allocation of money, voting districts
  • undercount of homeless, poor, minorities (3.3 million in 2000)
  • Pima Co. Az: 15,000 undercount, $30 million loss in funds
  • Delaware Co. OH: undercount of about 8000
  • statistical sampling can correct (opposed for Political reasons)

Environmental data collection: often by location

  • GPS: relatively to very accurate locations
  • Military origins; selective availability; competing system (Galileo, EU)
  • primary (collect yourself) vs secondary (use already collected) data

Organizing Data

  • table of data in GIS: like a spreadsheet: ArcGIS Demo
  • spatial data: location (in some coordinate system): where
  • attribute data: describe the spatial data: what
  • consistency: should not be gaps or missing data (although common)
  • scale: large vs small scale maps;
  • scale does not exist in computers; generalize to view: ex) Google Maps
  • scale at which data has been collected (detailed vs general): ex) DALIS data vs. ESRI data
  • aggregation: group of Census blocks > Block group > Census Tract: ex) Geog 222 Exercise 6
  • data interpolation: filling in missing values: terrain shading, temperature

Metadata: Data about Data

Sharing data leads to the need to know about data: when collected, at what scale, who…

  • ex) DALIS data

Sharing Data: Interoperability

  • “a common language for computational environments”
  • cross-platform and cross-software data compatability
  • like a text (.txt) file

Semantic interoperability: the practical problem associated with “philosophical” issues

  • ex) pond: means different things to different people/institutions, thus different in different data sets: how to integrate?
  • ex) wildlife biologists (forest classified in terms of habitat vs foresters (forest classified in terms of resource assessment)
  • ex) different ways of defining what a road isuse metadata to assess these differences
  • they will always exist: ignoring them can lead to problems

Moral of the story: data are not reality!


“Data are compiled with a particular purpose in mind, and they reflect the assumptions and preconceptions of both the data collectors and data users.  They are, in fact, stories about the world that change depending on the teller.”

  • data is the basis of all GIS analysis
  • not a matter of good or bad data
  • not a matter of more or less accurate data
  • but a matter of the appropriateness of the data to a particular task
  • metadata clarifies the story the data can tell: who collected it with what assumptions under what conditions and for what purpose
  • vital to be critical and understand your data, not just take it as a given