Category: Course Student Work

1. Zip Codes

This dataset maps all zip codes within Delaware County, carefully refined through census data and postal records. 

2. School Districts

A spatial representation of school district boundaries based on auditor parcel records. 

3. Building Outlines (2023)

This dataset contains the most recent building footprint data, offering insights into urban development and property mapping. 

4. Parcels

Cadastral parcel lines defining property boundaries, maintained daily.

5. Street Centerlines

This dataset maps the center of public and private roads, designed for 911 emergency response, accident reporting, and transportation planning. 

6. Condo & Subdivision Boundaries

The condo dataset outlines recorded condominium properties, while the subdivision dataset includes all recorded housing developments. 

7. Address Points

This dataset provides accurate placement of addresses within parcels, supporting geocoding, 911 services, and disaster response. 

8. Recorded Documents

This dataset includes survey plats, annexations, and legal documents related to land use changes. 

9. Dedicated Right-of-Way (ROW)

Tracks public roads and utility corridors, showing which land is set aside for public infrastructure.]

10. E911 Data

This dataset supports emergency response services, ensuring that addresses are accurately placed for quick location tracking. 

11. Hydrology

Maps all major waterways, rivers, and streams within Delaware County, enhanced using LiDAR data. .

12. GPS Monuments

A dataset identifying surveyed GPS reference points from 1991 and 1997. 

13. Farm Lots & Annexations

The farm lot dataset maps historical agricultural land divisions, while the annexation dataset tracks boundary changes since 1853. 

14. Tax Districts

This dataset defines taxation zones, determining property tax rates based on location.

Chapter 9

Chapter 9 focuses on spatial analysis techniques, providing hands-on experience with proximity analysis, service areas, facility location modeling, and cluster detection. The service area analysis with Network Analyst caught my attention too—it made me think about how healthcare access in affected communities could be mapped and improved. The facility location modeling was cool because it helps optimize the placement of cleanup or medical facilities, something I hadn’t considered before.

Chapter 10

This chapter introduced me to raster data processing, which felt like a whole new way of thinking about GIS. I found kernel density mapping especially interesting—it’s a great way to visualize concentration patterns. The risk index modeling was another highlight because it combines multiple factors into a single predictive map. I also liked how raster data allows for continuous data representation, making it ideal for environmental applications like pollution spread or elevation modeling.

 

Chapter 11

This was probably the most visually exciting chapter so far. Seeing geographic data in 3D made patterns much more obvious, especially when extruding data to show differences in contamination or population density. I really enjoyed creating local scenes because it felt more immersive. The line-of-sight analysis was a cool concept.  Overall, this chapter made me realize how 3D GIS can make spatial data more intuitive.

Address Point: represents all certified addresses in Delaware County. These addresses are updated daily and the updates are published once a month. 

Annexation: annexations and boundaries since 1853, annexation just means territory here. 

Building outline: this set is of building outlines and structures for all structures in Delaware county. It was last updated in 2023. 

Condo: All condo polygons within Delaware county. 

Dedicated ROW: lines that are designed Right-of-Way. This data is updated daily and published monthly. Consists of all dedicated road right of way polygons in the county. 

Delaware County contours: 2018 two foot contours, topography of the county?

Delaware County E911 Data: Uses address point data to reverse geocode coordinates to determine the closest emergency services location. Updated daily and published monthly. 

Farm lot: identifies farm lots in both US Military and Virginia Military Survey Districts. 

GPS: all GPS monuments that were established in 1991 and 1997. 

Hydrology: All major waterways in Delaware County. 

MSAG: master stress address guide. Used political jurisdictions in the townships, cities, and villages within the county.  

Map sheet: all map sheets within Delaware county. 

Municipality: all municipalities within Delaware county. 

Original township: has all boundaries of the townships within the county before tax districts change their shapes. 

PLSS: public land survey system polygons are used for the US Military and the Virginia Military Districts for Delaware county. 

Parcel: represents all cadastral parcel lines within Delaware County. These geometries are maintained by the Delaware County Auditor’s office. 

Precinct: consists of the voting precincts for Delaware county under the data of the Board of Elections

Recorded document: recorded documents in Delaware County Recorder’s Plat Books, Cabinet/Slides and Instruments Records that would not be represented by the subdivision plats that are active. This is used to track down miscellaneous documents within the county. 

School district: school district boundaries within Delaware County. 

Street centerline: center of pavement in public and private roads within Delaware County. This was developed by address information. 

Subdivision: subdivision and condo records for Delaware County. 

Survey: shapefiles of point coverage that are representative of surveys of land within the county. 

Tax district: tax districts defined by the Delaware County Auditor’s Real Estate office. 

Township: data of 19 townships that make up Delaware County. 

Zipcode: all zipcodes within Delaware country defined by the 2000 census, the postal service, and the tax mailing addresses.

 

Data Inventory

Address point 

• Representation of all addresses in Delaware County in Ohio that is intended for appraisal mapping, emergency response, accident reporting, geocoding and disaster management 

 

Annexation 

• Contains the annexations and conforming boundaries in Delaware County.

 

Building outlines 2023

• All building outlines for all structures in Delaware County and updated last in 2023.

 

Condo

• All condominium polygons in Delaware County.

 

E911

• Uses the address dataset to match it with the corresponding emergency service that is closest.

 

GPS

• Identifies all GPS monuments from 1991 and 1997 and is updated as needed and is published monthly

 

MSAG

• Includes 28 political jurisdiction with the purpose of locating a counties boundary

 

Municipality 

• Includes all of the municipalities in Delaware County 

 

Parcel

• Consists of polygons that represent cadastral parcel lines in Delaware. 

 

Precinct 

• Data set consists of voting precincts within Delaware and is used and directed by the board of elections.

 

Recorded document

• Consists of points that represent recorded documents such as vacations, subdivisions, centerline surveys, surveys, annexations, and other documents. The purpose of this is to locate miscellaneous documents in Delaware as it relates to the cadastral landbase.

School district  

• Consists of all the school districts in Delaware

 

Street centerline 

• Depicts the center of pavement on all roads, public and private. Intended use is for appraisal mapping, 911 emergency response, accident reporting, geocoding, disaster management, and roadway inventory.

 

Subdivision

• All of the subdivisions and condos that are recorded in the Delaware County Recorder’s office.

 

Survey

• Point coverage that represents surveys of land in Delaware. 

 

Tax district

• Consists of all tax districts within Delaware county
•  

Address point: all the address in the county, freshly published monthly

Annexations: This data is the annexations and boundaries freshly published monthly.

Building Outline 2023: the outline for all structures in the county.updated after new buildings or structures have been erected 

Condo: This data is all condos in the county.

E911: can reverse geocode. It is used for emergencies typically and is updated daily, and published monthly.

GPS: highlights all GPS monuments in the county that were established between 1991-1997.

MSAG: It consists of 28 political jurisdictions and was created to help facilitate the process of locating the county’s boundaries.

Municipality: This is all of the municipalities in the county.

Parcel: Polygons that are all cadastral parcel lines in the county. maintained by the county GIS office/are stored in the recorder’s office.

Precinct: This is the voting precincts of the county.

Recorded Document: Points representing recorded documents in a number of county records

School District: This is all the school districts in the county

Street Centerline: Location Based Response System centerlines are the center of pavement on roads in the county.

Subdivision: This is all subdivisions and condos in the county.

Survey: A shapefile of point coverage representing surveys of land.

Tax District: This is all tax districts and has been defined by the Real Estate Office

Address Point: These are all certified addresses in the county, they are indicated at the building centroid. They are most commonly used for disaster management and emergencies.

Annexations: This data is the annexations and boundaries and is constantly being updated. The data is published monthly.

Building Outline 2023: This is the outline for all structures in the county. It is updated after new buildings or structures have been created.

Condo: This data is all condos in the county. It is recorded by the county recorder office.

E911: This uses the address points dataset. This data makes it possible to reverse geocode a set of coordinates. It is used for emergencies typically and is updated daily, and published monthly.

GPS: This data highlights all GPS monuments in the county that were established between 1991-1997.

MSAG: MSAG or Master Street Address Guide is a data featureset. It consists of 28 political jurisdictions and was created to help facilitate the process of locating the county’s boundaries.

Municipality: This is all of the municipalities in the county.

Parcel: Polygons that are all cadastral parcel lines in the county. The are maintained by the county GIS office and are stored in the recorder’s office.

Precinct: This is the voting precincts of the county. It is under the direction of the Board of Elections and is maintained by the GIS office.

Recorded Document: Points representing recorded documents in a number of county records. They can include annexations, surveys, and subdivisions in the county.

School District: This is all the school districts in the county and was created by the auditor’s office.

Street Centerline: The LBRS or Location Based Response System centerlines are the center of pavement on roads in the county. It was created using field observation and is intended for geocoding, disasters and emergencies.

Subdivision: This is all subdivisions and condos in the county.

Survey: A shapefile of point coverage representing surveys of land. Old survey volumes are not included, all of the points are of surveys as of May 2004.

Tax District: This is all tax districts and has been defined by the Real Estate Office; it is dissolved by the Tax District Code.

GIS Tutorial for ArcGIS Pro

Chapter 9: Spatial Analysis

This chapter introduces spatial analysis techniques used to examine geographic patterns and relationships. It covers essential tools like buffering, which creates zones around features, and overlay analysis, which helps combine multiple datasets to determine intersections. The tutorials walk through various spatial analysis applications, such as proximity analysis for service areas and clustering to identify data patterns. A major takeaway is that spatial analysis provides insights by identifying relationships between spatial elements. These techniques are useful in decision-making for urban planning, environmental assessments, and resource management. One challenge encountered was configuring buffer distances correctly to ensure accurate analysis.

Chapter 10: Raster GIS

This chapter explores working with raster data, which is crucial for environmental and topographic analysis. The tutorials focus on processing raster datasets, performing raster calculations, and creating heat maps using kernel density analysis. Additionally, it introduces the concept of suitability modeling by combining multiple raster layers. Understanding how raster data represents continuous surfaces like elevation and temperature is essential for GIS applications. Challenges included managing large raster files and selecting appropriate classification methods for visualization.

Chapter 11: 3D GIS

This chapter focuses on working with three-dimensional data to enhance spatial visualization. It covers tools for creating and manipulating 3D scenes, converting 2D features into 3D representations, and performing line-of-sight analysis. Tutorials include building elevation models and integrating LiDAR data for realistic 3D mapping. Unfortunately, the 3D feature is still not working on my side, which limited my ability to complete most of the exercises in this chapter. Since I couldn’t properly load or visualize the 3D elements, I continued reading through the material to understand the concepts.

Chapter 9

In chapter nine tutorial 3, I couldn’t find the travel settings group, so I couldn’t create the new map. There’s also no name or Average time to be able to align. I think it has to do with not having output fields or merge rules in the expand fields option. I also can’t find UseRate, so I also had to skip this part of section 3.

Chapter 10 

I didn’t have LandUse_Pgh from chapter 10 so I can’t put it inside the geodatabase. I Just used LandUse_Pgh.tif instead and hoped for the best, the rest was fine and making the model tool was fun and easy. 

Chapter 11

In chapter 11 it was fun exploring the maps and learning to navigate through them. In tutorial 4 I couldn’t click the bridges in the create features pane, so I had to skip over it.

This week I finally got all of the kinks out of my program and finally was able to do real work again (thank you for your help again haha). 

 

Chapter 9 focuses on spatial analysis techniques. The first tutorial covers buffer analysis, teaching me how to create simple and multiple-ring buffers to analyze proximity and influence zones around geographic features. Next, the chapter delves into service area analysis using the Network Analyst extension, where I learned to calculate accessible areas from a specific location based on time or distance, like determining the coverage of a service center or retail store. Another tutorial introduces gravity model calibration, where multiple-ring buffers are used to analyze how factors like population density or store location impact spatial interactions between locations. The chapter also includes a cluster analysis tutorial, which taught me about identifying spatial patterns and concentrations in data, such as crime hot spots or the distribution of resources. I overall learned essential spatial analysis skills, enabling them to apply these techniques to real-world problems in urban planning, environmental science, and other fields.

Chapter 10 focuses on analyzing and working with raster data. The first tutorial introduces map algebra, which is used to perform mathematical operations on raster data to analyze spatial patterns, such as calculating slopes, elevations, or vegetation indices. Next, the chapter covers reclassifying raster data, where I learned how to change the values of a raster layer based on specific criteria, such as reclassifying land cover types or soil classifications to simplify analysis. Another tutorial explores focal statistics and neighborhood analysis, teaching how to perform operations that analyze the values of cells in a raster based on the values of their neighboring cells. I found it cool that this application is useful in environmental studies like habitat suitability or pollution analysis. The chapter also includes tutorials on raster overlays, which demonstrate how to combine multiple raster layers to identify areas that meet certain conditions, such as finding regions that are both prone to flooding and have high population densities. Overall I feel more confident with raster data handling and analysis.

Chapter 11 focuses on working with vector data and performing advanced vector analysis. The chapter begins with a tutorial on overlay analysis. I was taught how to combine multiple vector layers to identify areas where features from different datasets intersect, such as determining regions with both high population density and environmentally sensitive areas. The next tutorial covers proximity analysis, where I figured out how to use tools like buffers and proximity analysis to identify features within a certain distance of each other. The chapter also explores intersecting and union operations, demonstrating how to combine different vector layers to create new layers that represent areas where features overlap or merge, essential for tasks like land use planning or conservation efforts. Additionally, I was introduced to spatial joins, a technique that enables the combination of attribute data from different layers based on their spatial relationship, like joining census data with geographic boundaries. Which I found particularly cool. Finally, the chapter covers density analysis. I was able to identify clusters or concentrations of features like the distribution of crime or disease outbreaks in certain urban areas using animation which I really liked!

Chapter 9: 

Chapter 9 focused on using buffers for proximity analysis once again in the city of Pittsburgh. This was interesting to me because I’m from Pittsburgh and it was cool to see proximity placed where I’m from.

Chapter 10:

Chapter 10 used Raster more than I had seen prior. I only ran into an issue when I accidentally deleted my raster set and had to go back and restart chapter 10 combined old techniques with new it was quite interesting. 

Chapter 11:

Chapter 11 involved 3-D GIS this was the most difficult chapter but most rewarding I mean take away from this class has been that GIS can be used for drastically more than what I ever anticipate