Geography 291: Geospatial Analysis with Desktop GIS

Chapter 7:

• You can manually digitize a map by creating new map features, as well as editing existing ones.
• You can make edits to specific features or groups of features, including rotating them, moving them, and or changing their specific shape.
• You can import CAD drawings into the software to create more detailed features, or to make ones that match architectural drawings exactly.
• This chapter mostly focuses on the various tools available for creating specific features, and how to modify and import existing ones
• .

Chapter 8:

• This chapter was all about Geocoding data
• Geocoding matches input data to specific locations or features on a map, which can be useful for a variety of purposes
• Geocoding uses a fuzzy search method, and tries to match the most data, rather than making the most accurate matches possible, in order to account for error in the users input
• You can tune the parameters of the search to make it more or less strict, with higher strictness giving better accuracy, and lower strictness giving a  higher match count.
• You can geocode to match various features for varying levels of accuracy depending on your data, such as county vs streets

Chapter 9:

• This chapter focuses on different spatial analysis tools that can be used to gain insights about data

• Buffers are a region that surround a feature out to a certain distance, sort of like circling the feature or feature class
• Buffers allow you to select only the data that falls within their radius, and the radius can be based on distance or travel time depend on application, and can also be graduated to show regions within different distances of the feature
• Network analysis allows you to select specific features within a feature class based on sets of conditions, or can allow you to optimize an already existing network
• Cluster analysis allows you to find clusters of data points that are similar or close to each other, and groups them, and then assigns them a vector in 3D space(?) representing the data point(?)

Chapter 7

1. Editing polygon features
2. Creating and deleting polygon features
3. Using cartography tools
4. Transforming features

I really enjoyed moving the features around and “fixing” the map. It felt like doing a puzzle. Creating polygons and outlining areas was also pretty cool. Everything in this chapter went smoothly, and I can see how this chapter would have some real-world applications in things like architecture. 

Chapter 8

1. Geocoding data using zip codes
2. Geocoding street addresses

This chapter was super easy and short, I wish all of the chapters were like this one. The only issue I encountered was with the “create locator” tool at the beginning of the chapter, I think I accidentally made a copy of the output locator, which I fixed by just renaming it “PARegionZIP_CreateLocator1.”

Chapter 9

1. Using buffers for proximity analysis
2. Using multiple-ring buffers
3. Creating multiple-ring service areas for calibrating a gravity model
4. Using Network Analyst to locate facilities
5. Performing data cluster analysis

I felt like this chapter repeated a lot of things from earlier chapters, just using different methods to get the same results. This was all fairly easy, but it took me a while. I also liked the visuals that the maps created, I can see how this could be useful for someone who works in data analysis or something similar.

Chapter 7

• this chapter introduces tools to do manual digitization by tracing
• creating vector map features

Tutorial 7-1

• used the move button to update a polygon’s position
• rotated a polygon to fit a feature
  • 
  • added vertices to a polygon to change its shape
  • cut a polygon into two separate ones

Tutorial 7-2

• created a feature class to add to the geodatabase
  • added a polygon for a parking lot to the feature
  • 
• deleted polygons
• added polygon via trace

Tutorial 7-3

• can modify GIS using cartography tools
• learned how to smooth out polygons

Tutorial 7-4

• learned how to cover a building with features
• added features over an area and rescaled them

Chapter 8

• Geocoding- GIS process that matches location fields in tabular data to corresponding fields in existing feature classes to map the tabular data
• problem with geocoding is inconsistencies with data entries from data suppliers
• ArcGIS has a rule-based expert system
  • source table
  • reference data
  • geocoding tool
  • locator
• Soundex Key used to identify spelling mistakes

Tutorial 8-1

• created a locator
• created datapoints based on the locator I created
• fixed messed up data
• 

Tutorial 8-2

• geocode by street address to place unique points on map for attendees in the county
• 

Chapter 9

• covering four spatial analytical methods: buffers, service areas, facility location models, and clustering
• network dataset- used for estimating travel distance or time on a street network

Tutorial 9-1

• buffer- polygon surrounding map features of a feature class
• 

Tutorial 9-2

• multiple-ring buffer looks like bull’s eye target

Tutorial 9-3

• service areas are like buffer areas, but extent based on travel over a network
• 

Tutorial 9-4

• location-allocation model in Network Analyst collection of models handles facility location issues
• 

Tutorial 9-5

• goal of data mining is to find hidden structure in large and complex datasets
  • limitation: no way of knowing true clusters in real data to compare with an algorithm
• k-means clustering- partitions dataset with n observations and p variables into k<n clusters

I definitely struggled with this section more than previous chapters. I felt some sections were really good at explaining the content and others brushed through it or had us doing something that was previously gone over but I couldn’t quite remember how to do it without having to flip through a bunch of pages to find the explanation.

Chapter 4:

Chapter four focused on file geodatabases. The various sections went over importing data into a new ArcGIS pro project, modifying attribute tables, carrying out attribute queries, aggregating data with spatial joints, using central point features for polygons, and creating a new table for a one-to – many join. In section 4.5, I was having trouble  figuring out how to use calculated geometry attributes. X and y coordinates weren’t showing up. 

Chapter 5:

Chapter five’s focus was on spatial data. In this chapter we learned how to work with world map projections, work with US map projections, setting projected coordinate systems, work with vector data formats, work with US Census map layers and data tables, and download geospatial data. I definitely had the most trouble with downloading the geospatial data and getting the data to present how I wanted. I also had trouble with the csv file and getting the data to upload but I eventually worked it out. 

Chapter 6:

Chapter 6 was all about geoprocessing. The topics discussed were dissolving features to create neighborhoods and fire divisions and battalions, extracting data and clipping features for a study area, merging water features, appending firehouses and police stations to EMS facilities, intersecting features to determine streets in fore company zones, using Union on neighborhoods and land-use features, and using the tabulate intersection tool. This chapter felt less difficult than the previous two. The merging of feature classes ran smoothly and I felt like I understood these sections better.

Chapter 7:

• I learned how to move and rotate polygons to align with the corresponding building on the map.
• I learned how to edit vertex points in order to align with the exact shape of the corresponding building.
• Lastly, I learned how to delete polygons and use cartography tools like smoothing polygons.

Chapter 8:

• I learned how to implement a ZIP code locator.
• The table in which I looked at allowed me to see discrepancies within the data and fix any issues it may have had.
• Additionally I learned how to match the ZIP codes I previously input with the correct addresses.

Chapter 9:

• I learned how to make buffers around certain aspects of the map and how to change the diameter or size of each buffer.
• I put buffers around other buffers as well which created “multiple ring buffers”.
• Finally, I learned how to spatially join areas.

Ch 7:

I learned how to create and edit features on the map. I added vortex points for bus stops and rotated building polygons. The editing tools made it, so I realize how flexible GIS is for changing features.

Ch8:

I learned about geocoding which is what connects data tables to map locations using addresses. I struggled with the locator. I rematched some of the addresses and used graduated symbols to symbolize results. I struggled with aligning the records and this showed me that even with slightly inexact results the system is still very helpful in the big picture. 

Ch 9:

I used spatial analysis tools like buffers and clustering in this chapter. I made a buffer around pools and then with that information found that most kids live within that radius. I used service-area maps, scatterplots, and cluster analysis. 

 

Chapter 7

In chapter seven I started with editing, creating, and deleting polygon features. This was very straightforward and easy to understand. Moving and rotating the polygons to the correct location was actually quite enjoyable. I then used cartography tools to smooth out polygon features and make them look much nicer. I also transformed features  with a CAD drawing. I also found this section to be somewhat fun. I am proud to announce that I somehow did not have any problems in this section which has been a first for me so that’s exciting.

 

Chapter 8

In this chapter I learned a lot about the geocoding process which matches location fields in tabular data. In the first tutorial I geocoded data using zip codes. I built a zip code locator, geocoded data by zip code, rematched data by zip code, and then symbolized using using the collect events tool. This process was pretty quick and simple and I got it done with no issues. In the second tutorial I geocoded street addresses. I messed up the locator tool at first by forgetting a few setting to apply but the second time around I did it correctly. Other than that mistake this also went by pretty quickly.

Chapter 9

In chapter 9 I started off by learning to use buffers which I really enjoyed. I just like the way they look on the map… I then created multiple-ring service areas for calibrating a gravity model and polygons for them. This was really interesting to see travel time to pools and the colors relating to “quality” like poor or excellent. When it came to using the spatial join tool in this chapter I was struggling at first because I couldn’t find the output fields and merge rule but I think I figured it out by just clicking the specific output field and then finding a sum button. I’m not sure if that was correct but I did it anyway. I also optimally located facilities using ArcGIS Network Analyst and performed cluster analysis to explore multidimensional data. This chapter took a bit longer because of some small random problems but I got it all figured out.

Work I was supposed to start last week for Final

Zip Code- Contains all zip codes within Delaware county

Street centerline- The center of pavement of public and private roads within Delaware county. It was developed from data collected by field observation of existing address locations and by adding addresses using building permit information.

Recorded Document- points that represent recorded documents in the Delaware County Recorder’s Plat Books, Cabinet/Slides and Instruments Records which are not represented by subdivision plats that are active. (vacations, subdivisions, centerline surveys, surveys, annexations, and miscellaneous documents within Delaware County, Ohio)

Survey- a shape file of a point coverage that represents surveys of land within Delaware County, Ohio.

GPS- This dataset identifes all GPS monuments that were established in 1991 and 1997. This dataset updated on an as-needed basis, and is published monthly.

Parcel- consists of polygons that represent all cadastral parcel lines within Delaware County, Ohio.

Subdivision- consists of all subdivisions and condos recorded in the Delaware County Recorder’s office. This dataset is updated on a daily basis and is published monthly.

School Districts- all School Districts within Delaware County, Ohio.

Tax Districts- consists of all tax districts within Delaware County, Ohio. The data is defined by the Delaware County Auditor’s Real Estate Office.

Township- consists of 19 different townships that make up Delaware County, Ohio. This dataset is updated on an as-needed basis and is published monthly.

Annexation- contains Delaware County’s annexations and conforming boundaries from 1853 to present.

Address Point- a spatially accurate representation of all certified addresses within Delaware County Ohio.

PLSS-consists of all the Public Land Survey System (PLSS) polygons in both the US Military and the Virginia Military Survey Districts of Delaware County.

Condo- consists of all condominium polygons within Delaware County, Ohio that have been recorded with the Delaware County Recorders Office.

Farm Lot- consists of all the farmlots in both the US Military and the Virginia Military Survey Districts of Delaware County.

Precincts- consists of Voting Precincts within Delaware County, Ohio.

Building Outline 2023- all it says it building outline 2023

Delaware County E911 Data- For some reason this summary had the same summary as Address points and I dont think thats right.

Original Township-consists of the original boundaries of the townships in Delaware County, Ohio before tax district changes affected their shapes.

Building Outline 2021- consists of building outlines for all structures in Delaware County, Ohio. The layer was updated in 2021.

Dedicated ROW- consists of all lines that are designated Right-of-Way within Delaware County, Ohio. This data is line data that is created through the daily updates of Delaware County’s Parcel data.

Map Sheets- consists of all map sheets within Delaware County, Ohio

Hydrology- consists of all major waterways within Delaware County, Ohio. This data was enhanced in 2018 with LIDAR based data.

ROW- consists of all lines that are designated Right-of-Way within Delaware County, Ohio. This data is line data that is created through the daily updates of Delaware County’s Parcel data.

Address Points DXF- a spatially accurate placement of addresses within a given parcel in Delaware County.

2024 Ariel Imagery- 2024 3in Aerial Imagery. Flown Spring 2024.

Delaware County Contours- 2018 Two Foot Contours

2022 Leaf-On Imagery (SID file)- 2022 Imagery 12in Resolution

Here is my ArcGis Pro project with the Parcel, Street Centerline, and Hydrology layers. Okay so never mind I can’t find the screenshot on my hard drive but I did it and it was very purple.

 

Chapter 7).

In this tutorial I practiced the skills of creating and editing GIS features. We learned about the implementation of GPS receivers and applications. We worked with current features as well as to develop new features for the CMU campus of Pittsburgh. 

This first screenshot shows me adding and moving vertex points. The tutorial told me to add 4 to get the right shape, but I added about 6 and still got the same end result, it just took some time. 

I added a feature class and created a point feature for bus stops. I have a screenshot of this:

At the end of tutorial 7, I worked to rotate buildings, and transform polygons. There is a lot that can be done through the edit tab and I think it was super cool to be able to align the polygons of the floor plan with the actual building on the map. The building we worked with was Hamburg Hall in color on the map. I included two sequential screenshots of this process. Overall this chapter went pretty smoothly.

Chapter 8). 

Tutorial 8 was all about geocoding which connects location fields and the rows and columns of the data to the relative fields in feature classes. This maps the data from the data table. This process has many real life applications and uses. There are some limitations to geocoding in that not all matches will be accurate and so a rule-based expert system software is used by ArcGIS pro to facilitate as much correlation and precision as possible. I made sure not to use the World Geocoding Service within ArcGIS pro. 

For the 8-1 your turn exercise, I was able to add a new point to the map via the rematch addresses pane but in the table it was showing coordinates under the match address column whereas the other unmatched records showed as zip codes not coordinates. I can’t seem to find the slight error that is causing this but I still was able to do it. I think maybe the issue was that I corrected the zip code for that last record when I was just supposed to choose an approximate point.  

Once the survey data was geocoded to zip code center points, I symbolized the attendees feature class using graduated symbols, with symbol size increasing as the number of attendees increases:

In 8-2 I worked to geocode the street addresses. I ran into some bumps with the locator tool but I think I figured things out. I built a street locator and set its geocoding option, geocoded attendee data by street address, and then selected minimum candidate and matching scores. For the your turn exercises for 8-2, I found that 872 matched. The tutorial says 873 is supposed to be the number but I don’t think this matters too much. I included a screenshot where you can see the selected records through the attribute and on the map. In order to identify the number of matched records with a minimum score of 90, I used the select by attributes tool to build a query that expressed for the score to be greater than or equal to 90. The results showed a good geocoding performance. 

At the end of chapter 8, I symbolized and produced final geocoding results:

Chapter 9).

In this tutorial we learned the second part of the visualization of spatial data is the analysis of the data. Engaging in spatial analysis helps us to answer profound real life questions raised and displayed by the data. For instance, a map may show patterns or reveal an issue, but the analysis part allows for work towards solutions to that issue or recurring negative trend. The four fundamental spatial analytical methods we explored are buffers, service areas, facility location models, and clustering. I started off by using buffers for the purpose of proximity analysis. A buffer is simply a polygon that encompasses map features of a feature class. 

Here is a screenshot of the first your turn exercise in 9-1. We created a buffer of the pools feature class, particularly a one mile buffer. Then I performed some analysis, calculating the number and percentage of youths within that distance. I found that 42,548 youths are within that distance. About 87 percent of all youths in the city are close to a pool. 

This next screenshot is from tutorial 9-3 in which I created multiple-ring service-area polygons, spatially joined service areas and pool tags, calculated pool use statistics for service areas, and finally created a scatter plot.  I had some issues with the spatial join tool but I got through things it just took much longer than expected. 

For the very last part of 9-3, involving fitting a curve to the gravity model data points, I was able to open the excel spreadsheet but the beta values were already entered. Thus, the resulting average absolute error values were already there as well. And I’m not sure if we were supposed to just take a look at this stuff or actually do something. It seemed like we were just exploring the spreadsheet and noting those things so I moved on. 

For the 9-4 tutorial your turn exercise, I was able to do the first model run and create the first map but when I tried to do the second model run I kept getting Solve errors. I was able to work with using Network Analyst to locate facilities and see what this looks like, but when I kept getting errors for the second model I tried to figure out the issue but it kept occurring. I included a screenshot of what I produced and I learned that this sort of map is used for visualization. You can see the lines and essentially the lines show the demand relationship between pools and block centroids.

For the your turn exercise of tutorial 9-5, I was able to run the summary statistics tool and create the table with the mean values, but there were a few rows that were in different places then what arcGIS pro showed. I got all the exact same values, things were just in varying positions. Below is my work from 9-5 with performing a cluster analysis. 

CHAP 7:

•  Shows us how to edit polygons, adding or subtracting features deleting and tracing them
• Shows us how to use cartography tools to smooth features
• How to export a CAD drawing

 

CHAP 8:

• Talks about geocoding
• shows us how to use ZIP locators to find Zip codes and then how to geocode them
• Shows us how to rematch data
• Also shows similar traits for street address stuff

 

CHAP 9:

• Shows us how to turn buffers into pairwise buffers, removing the overlapping lines
• Shows us how to build centroids to buffers
• Shows how to make multiring buffers
• Allows us to make a “clipping group” of sorts with buffers
• Allows us to make “pools”, shows us how to make scatterplots,
• shows us how to table data cluster data

Chapter 7

 

Chapter 8

 

Chapter 9