Geography 291: Geospatial Analysis with Desktop GIS

My name is Lily Ogrodowski, and I am a first-year student from Toledo, Ohio. I’m planning on an environmental major (not sure which one yet!), but I’m also pursuing studies in Chemistry. I may also pick up Sociology/Anthropology, or even Public Health. I have a particular interest in the study of freshwater and lakes/limnology, as well as human geography issues like populations, land use, and urban planning.

Schurmann Ch. 1

In my first week of this class, I completed the introductory quiz which reinforced directives on the syllabus. Then, I read Schurmann Chapter 1, Introducing the Identities of GIS. This introductory chapter has given me a solid introduction to GIS and its uses, history, and impacts. I’ve learned that GIS is more than just digital maps—it emphasizes spatial analysis techniques. While mapping “shows” land features, it seems like applying spatial analysis takes that data and “tells” about patterns the data may reveal. With GIS, spatial analysis can be done while combining many different data sets and maps, proving that GIS is ultimately an interdisciplinary tool with uses that extend far beyond geography alone.

A main focus of the chapter is the comparing and contrasting of the two definitions of GIS: Geographic Information Systems and Geographic Information Science. The author defines GISystems as the mapping and analysis methods coded into GIS programs, while GIScience is the research and theory going on behind the scenes. GISystems are generally accepted and used, while GIScience is the ongoing research and theory development that asks questions about these systems and how they apply in different areas. GISystems are the tools, while GIScience involves taking the tools and tinkering with them.

Additionally, GIScience is most impactful when specific local knowledge is taken into consideration. In the chapter’s example of public wells being linked to cholera cases, a specific understanding of the location of focus inspires a most efficient use of GISystems, thanks to GIScience. However, because GISystems are formulated by people, that means they will inevitably have bias or limited perspectives. The chapter concludes by describing a main goal of future GIS development as involving the integration of multiple ontologies, or conceptual systems of thinking and organization within GIS.

Before reading this chapter, I don’t think I realized how prevalent GIS is in the development of our world. It makes sense that GIS models would be used in agriculture, transportation, energy, and housing, but I did not realize the extent to which GIS plans with efficiency and optimization in mind.

GIS Applications

The first GIS application I found was the Food Environment Atlas from the United States Department of Agriculture (USDA) Economic Research Services. I clicked on the Grocery data set, which shows the number of grocery stores in each county. (The darker the shade of pink means more grocery stores.) I found lots of large zones with few grocery stores or no data in the Appalachia region of Kentucky and West Virginia. (I outlined them with my computer’s Draw tool.) 

I know from research in other classes that these regions face very low income rates, and they are home to food deserts, or places with inadequate access to healthy food.

Grocery | Food Environment Atlas

Next, I found an application from the National Centers for Coastal Ocean Science (NCOOS) that forecasts harmful algal blooms in Lake Erie. I went into the archived videos to find a date with high levels of algal blooms and settled on July 25, 2023. This application is a good example of how overlaying different data sets, like cyanobacterial density and wind patterns, is what makes GIS helpful when explaining the reasons for the trends we see. 

Bloom Position Forecast – NCCOS – National Centers for Coastal Ocean Science

1. Introduction: My name is McKenna Downing, and I am a senior who is majoring in Zoology and minoring in Environmental Science. I am from Pleasant Hill, Ohio, which is 30 minutes north of Dayton. I am on the cross country and track and field teams as a distance runner. After graduation, I plan to find a job in wildlife rehabilitation and environmental education at a nature center (preferably somewhere warmer than Ohio). I am new to GIS but very interested in how it can affect many areas of science, especially in terms of deforestation and land loss.
   
2. Schuurman Chapter 1: Nadine Schuurman begins Chapter 1 by illustrating GIS as a large system, not a specific tool with a fixed or secure identity. Different companies or organizations use GIS for their specific jobs, and do not consider what others use it for. GIS dates back to the 1960s, when pieces of paper were layered on top of each other in order to find the best route for a highway. I think that’s really interesting because a problem that seemed difficult was made easy using a form of GIS. There were many people who were involved in the technology of GIS, such as Roger Tomlinson and Lee Pratt, who created the first computer cartography system to create a map of an area featuring all geographic features. I think that it is also interesting that GIS came around when it did, when information was being translated into technological terms and being distributed that way. The main way Schuurman tells us GIS was used in the early stages was to map data distributions, particularly within the environment. It makes me curious if these people would know how much of an effect it would have on the future! She then goes on to discuss how some GIS researchers perceive the system as a way to increase accessibility for spatial analysis. I think that’s really cool because there are so many professions in the world that can benefit from using this system. I also love the idea of GIScience and GIScientists. The classification of spatial entities can be difficult, because people can easily disagree on these parts. An example of this that Schuurman mentions is how to define where a mountain stops and the foothills begin. And it’s so cool that John Snow was able to use the concepts of GIS to figure out the cholera outbreak! I really liked how this chapter discussed how we use GIS in our daily lives, mostly without even realizing it. So many people use this system in different ways, and Schuurman wrote and described it very well.
3. GIS Applications (1): Wildlife Migration: Understanding the migration of wildlife is incredibly important, and this research paper focused on how scientists used GIS mapping techniques to track the migration of wildebeest across the Serengeti-Mara habitat. The research included the mean routes of the wildebeest across the landscape and the amount of green space before and after the wildebeest had come through. The results found that the less green space in an area before the wildebeest arrived, the less likely they were to travel through that area because of the lack of water. Source: Musiega, D.E. and Kazadi, S.-N. (2004), Simulating the East African wildebeest migration patterns using GIS and remote sensing. African Journal of Ecology, 42: 355-362. https://doi.org/10.1111/j.1365-2028.2004.00538.x
4. GIS Applications (2): Plant Conservation: This research paper focused on using GIS methods in order to implement plant restoration programs in Portugal. They focused on bryophytes and how they grew within a natural reserve with different species of vegetation, including alien species of plants, and varying levels of altitude. The researchers collected information from the reserve using aerial GIS mapping. it was found that the bryophytes all had differing levels of need within the reserve, with some doing well at altitude and others not. The alien species (invasives), also played a part, because they would grow quickly and outcompete the endangered bryophytes. GIS was helpful in finding these results, and is demonstrated in the map below. Source: https://www.sciencedirect.com/science/article/pii/S0006320703001253
5. I completed the GEOG 291 Quiz!

 

1. Introduction

Hello, my name is Andrea Pichardo, and I am an ENVS student interested in understanding how geography and technology intersect to explain real-world issues. I am especially interested in how spatial data can be used to analyze social and environmental patterns, such as access to resources, environmental impacts, and community-level change. I am new to Geographic Information Systems, but I am excited to learn how GIS tools are used across different fields and how they influence decision-making in everyday life.

2. Comments on Schuurman:

In Chapter 1, Schuurman explains that GIS is much more than a tool for making maps. One idea that stood out to me is that GIS does not have a single, fixed identity. Instead, its meaning changes depending on who is using it and for what purpose. For some people, GIS is mainly software that helps organize spatial data, while for others it represents a scientific way of thinking about space and spatial relationships. This made me realize that GIS is not just technical, but also conceptual and interpretive.

I also found the distinction between GIS as a system and GIS as a science especially interesting. GISystems focus on practical tasks such as urban planning, transportation routing, or managing infrastructure. GIScience, on the other hand, asks deeper questions about how spatial data is created, categorized, and analyzed. Schuurman emphasizes that decisions like where boundaries are drawn or which data is included can significantly affect results. This challenged my assumption that GIS outputs are always neutral or objective, and it made me more aware of the role human choices play in shaping geographic information.

Another important theme in the chapter is visualization. Schuurman explains that maps and spatial images allow people to see patterns that might not be obvious in tables or written descriptions. The example of John Snow’s cholera map shows how visualizing data spatially can lead to meaningful insights and real-world change. At the same time, she points out that visualizations can oversimplify complex situations if users do not critically examine the data behind them.

Overall, this chapter helped me see GIS as a powerful tool that influences how we understand space, make decisions, and interpret the world, rather than just a technical mapping skill.

3. GIS Application Areas

Application 1: Crime Mapping and Public Safety

GIS is widely used in crime analysis to map crime incidents, identify hotspots, and allocate police resources more effectively. Law enforcement agencies use GIS to analyze spatial patterns of crime over time, helping them predict where crimes are more likely to occur and develop targeted prevention strategies. Crime maps also allow communities and policymakers to better understand safety concerns and evaluate the effectiveness of interventions.

Map/Image:

Sources:

•National Institute of Justice, GIS and Crime Mapping

•Chainey & Ratcliffe (2005), GIS and Crime Mapping

Application 2: Environmental Monitoring and Conservation

GIS plays a crucial role in environmental science by helping researchers monitor ecosystems, track land-use change, and manage conservation efforts. For example, GIS is used to map wildlife habitats, analyze deforestation, and assess the impacts of climate change. By layering environmental data such as vegetation, elevation, and human activity, GIS allows scientists to make informed decisions about conservation planning and resource management.

Map/Image:

Sources:

•ESRI, GIS for Environmental Management

•Turner et al. (2001), Landscape Ecology in Theory and Practice

4. Was the quiz completed?

Yes.

Delaware data:

• Delaware County E911 Data: All addresses in Delaware County
• Dedicated ROW: All right of way lines in Delaware County
• Building Outline 2021: Building outlines for all structures in Delaware County in 2021
• Map Sheet: All map sheets in Delaware County
• Township: All 19 townships in Delaware County
• Zip Code: Zip codes in Delaware County
• Farm Lot: All farm lots in the US Military and Virginia Military survey districts in Delaware county
• Annexation: All Annexations and conforming boundaries, 1853 – now in Delaware County
• Survey: Survey points that represent land surveys in Delaware County
• Tax District: All tax districts in Delaware County
• Hydrology: All major waterways in Delaware County
• GPS: All GPS monuments from 1991 and 1997
• Original Townships: Original townships in Delaware County
• Precincts: All voting precincts in Delaware County
• School District: All the school districts in Delaware County
• Building Outline 2023: All the building outlines in Delaware County
• Street Centerlines: The Center of Pavement of roads in Delaware County
• Address Points: All the Addresses in Delaware County
• Parcel: All of the cadastral parcel lines in Delaware County
• Condo: All of the condos in Delaware County
• Subdivision: All of the subdivisions and condos in Delaware County
• Record Documents: All points of recorded documents in Delaware County
• PLSS: All of the public land survey system polygons in both the US Military and the Virginia Military Survey Districts of Delaware County

Delaware Data Inventory:

PLSS: All of the public land survey system polygons in both the US Military and the Virginia Military Survey Districts of Delaware County

Township: All 19 townships in Delaware County

Dedicated ROW: All right of way lines in Delaware County

Precincts: All voting precincts in Delaware County

Delaware County E911 Data: All addresses in Delaware County

Building Outline 2021: Building outlines for all structures in Delaware County in 2021

Original Townships: Original townships in Delaware County

Map Sheet: All map sheets in Delaware County

Farm Lot: All farm lots in the US Military and Virginia Military survey districts in Delaware county

Annexation: All Annexations and conforming boundaries, 1853 – now in Delaware County

Survey: Survey points that represent land surveys in Delaware County

Tax District: All tax districts in Delaware County

Hydrology: All major waterways in Delaware County

GPS: All GPS monuments from 1991 and 1997

Zip Code: Zip codes in Delaware County

School District: All the school districts in Delaware County

Building Outline 2023: All the building outlines in Delaware County

Street Centerlines: The Center of Pavement of roads in Delaware County

Address Points: All the Addresses in Delaware County

Parcel: All of the cadastral parcel lines in Delaware County

Condo: All of the condos in Delaware County

Subdivision: All of the subdivisions and condos in Delaware County

Record Documents: All points of recorded documents in Delaware County

 

Most of the data is pretty straight forward based on names. If I dont specify assume its in Delaware County I got lazy at the end

ZIP CODE: Contains Zip Codes in Delaware County
SCHOOL DISTRICT: All school districts
BUILDING OUTLINE: all building outlines
PLSS: all public land survery system data
TOWNSHIP: all 19 townships of delaware county
STREET CENTERLINE: center of all streets
Address Points: All Addresses of the parcels in Delaware county
Parcel: All parcel locations
Condo: All condo
Subdivision: All subdivisions + condos
Recorded Documents: All points recorded in Plats books and other recorded documentation
Dedicated ROW: the dedicated Right Of Way points
Precinct: Voting Precincts
Map Sheet: all map sheets
Farm Lot: Farmlots in US military survey districts
Annexations: Delaware county annexations since 1853
Survey: Surveys on land
Tax District: all tax districts
Hydrology: water
GPS: all GPS monuments

Chapter 4-

This chapter was about mapping density. I learned that you would use this to show highest concentration of features are, and to look at patterns rather than locations of the individual features. It eases viewing of maps with higher concentration as well. You map density two ways, either create a density surface or create a map based on features summarized by defined area. In a map based on features summarized by defined area, it would be mapped graphically, with a dot map, or just by calculating density value for each area. This method is easy buy doesn’t show exact centers of density, especially in large areas. Density is treated as a ratio with this method. Dot maps could be used when you’re mapping individual locations summarized by defined areas, and they show the density graphically. With a dot map you map each area based on total count or amount, and specify each dot value. This method is used when you already summarized by area or for comparing administrative or natural areas with defined borders. When you’re graphing a density surface, you use a raster layer and each cell gets a density value based on the number of features in the cell. The density surface method is precise, but requires more data processing.  This method is used when you want to see the concentration of point or line features. The GIS in this method will define a neighborhood around each cell center, and total the number of features that are in the neighborhood then divide that number by the area of the neighborhood. It then creates a running average of features per area. When calculating density values, you can do it based on cell size, search radius, calculation method, or units.

Chapter 5-

This chapter overviews how to tell what features are within a given area. You would map what’s inside to monitor what’s occurring within the area or to compare multiple areas on what’s inside of them. Monitoring areas allow people to know when to take action on the features within, and comparing areas will tell where there is more or less of something. You would draw an area boundary on top of the features and select the features inside and summarize them. When looking at a single area, you can monitor the info with several ways. These include; a service area around a central facility, a buffer that defines a distance around some feature, an administrative or natural boundary, an area you draw manually, or the result of a model. Multiple areas are for comparing, they could be contiguous, disjunct, or nested. This chapter also explains the three ways to find what’s inside; drawing areas and features, selecting the features inside the area, or overlaying the areas and features. Drawing areas and features are good when you want to see whether one or a few features are inside and out of the area and is created showing the boundary of the area and the features. Selecting the features inside the area is good for getting a summary of features inside areas and finding out what’s within a given distance of  a features and it’s created by specifying the area and the layer containing the features. Lastly overlaying the areas and features is good for finding which features are in each of the several areas or how much of something is in the areas, and it’s created by combining the area and the features ot create a new layer with the attributes of both or by comparing the two layers to calculate summary statistics for each area.

Chapter 6-

This chapter is about spatial proximity and nearness queries in GIS. It explores how to define, measure, and interpret what is near in a geographic context. To find what’s nearby, you can measure straight-line distance, measure distance or cost over a network, or measure cost over a surface. You can measure nearby based on a set distance, or on a travel to or from the feature.  Measuring using cost for example is how much time it takes from one feature to another. There are three ways to find what’s nearby; straight line distance, cost over a surface, and distance or cost over a network. For Straight line distances, you specify the source feature and the distance and the GIS will find the area or surrounding features. For cost over a surface, you specify location of the features and a travel cost and the GIS will create a new layer showing the travel cost from each feature. Lastly for distance or cost over a network, you specify the locations and a distance or travel cost along each linear feature and the GIS finds which segments of the network are within the distance or cost.

Chapter 7:

Chapter 7 introduced several tools for manual digitization through tracing. Using base maps, we learned how to create new feature classes and digitize features based on base maps or existing layers. We also used LiDAR data as a reference for heads-up digitizing. In addition, we practiced editing existing features and creating new ones for a university campus, including adding new structures, building additions, and renovations to existing facilities.

Chapter 8:

In Chapter 8, section 1 of this tutorial, we geocoded survey data collected by a Pittsburg arts organization that hosts an annual event. The geocoded survey data was used to explore potential marketing, philanthropy, and other communication opportunities with the organization’s patrons. In section 2, we built on the arts event data from section 1 by adding street addresses and more detailed location information for the attendees, which would be useful for marketing purposes. We also geocoded the data by street address to create unique point locations for each attendee on the map.

Chapter 9:

In this chapter, we moved beyond simply visualizing spatial data to actively using it to answer questions and solve problems. We explored four spatial analytical problems: Buffers, service areas, facility location models, and clustering. Our work included building buffers and using gravity models to estimate the nearest swimming pol to residents homes. This analysis helped determine which public pools should remain open during a budget crisis. We also performed cluster analysis to examine demographic and spatial patterns among individuals arrested for serious violent crimes. Additionally, the chapter introduced the concept of a network dataset, which is used to estimate travel distance or time along a street