Author: gtjefferson

Chap 7 focuses on editing, creating, and deleting polygon features. I learned how to make and digitize point features, use cartography tools to smooth features, and work with CAD drawings. I learned how to move and edit the polygons, and I found this to be an interesting but very useful feature. 

I couldn’t figure out how to make the red that symbolized the parking lot appear. And I also didn’t know how to make the transportation icons pop up. 

7.4 Under HBH1 polygon, I can’t get the colors to show up on the map. 

Chap 8 focuses on learning about the geocoding process, using geocode for ZIP codes and using geocode for addresses using streets. 

8.1 I don’t see an option for Locators. I could not find a “Pick from Map” button, so I wasn’t able to add a point in the geocoding process. When I tried to symbolize using the Collect Events tool, it kept saying, “Collect Events failed.”

Chap 9 focuses on using buffers for proximity analysis, using multiple ring buffers, creating service areas of facilities to estimate a gravity model of demand versus distance from the nearest facility and learning how to perform cluster analysis to explore multidimensional data. 

9. I was unable to summarize when right-clicking “AGE_5_17”. 

 In tutorial 9.3, you learned how to create a multiple ring service area for calibrating a gravity model. During 9.3, when I right-clicked on “Service Area,” there was no option for “Input Data,” so I was not able to import Facilities and apply the settings asked for in the textbook. I also could not find an option for travel settings, so I skipped that step. Then my “UseRate” tool was not calculating, so I wasn’t able to make the scatterplot. 

9.4 Was confusing for me, mainly because of the “your turn”. I was not able to make it look like the pictures it had as examples. 

Chap 5 

Chapter 4 is about learning how to work with spatial databases and databases. For 4.1, I could not put YouthPopulation.gdb as an Output Feature Class. It told me that the folder was empty, so I could not include it or change the name. But when I ran the geoprocessing, I still ended up with the same result that the GIS tutorial textbook showed. 4.1 also wanted me to change the outline for MaricopaCounty and Tracts. But when I found the option for outline width, a big grey shape covered up my screen. 

I wasn’t able to complete all of 4.2; it was hard to modify the tables. And my validate join was invalid, so I could not get Pop youth to join the Tracts feature class. 

I am unable to save the expression “qryDateRange”. I could not find an option for expression under the Select by Attributes tool. So this means I was not able to then reuse a saved query to create a definition query. 

Building the commands for the queries was slightly tedious, but rewarding. 

5.1 explored how to use geographic coordinates. Some things I had to troubleshoot, like under “Projected Coordinate System,” when I double-clicked the folder, nothing happened, so I was not able to click “Hammer-Aitoff (world)”. But then when I saved the project, exited and then opened it again I was able to double-click. 

5.2 was about US map projections. Changing the coordinate system was fun and very easy to follow!

5.3 explained how to set projected coordinate systems 

Chap 6

For 6.2, I don’t have the option for “UpperWestSideStreetsForGeocoding” when using the Pairwise Clip tool for this section. 

I found that sometimes it was very difficult to find and navigate through certain tools. 

Chapter 6 mainly helped me become more familiar with the Pairwise tools, streets, study areas, and data within different boundaries. 

Delaware Data Inventory 

Zipcode: This includes all ZIP codes in Delaware County, Ohio. This dataset is updated on an as-needed basis and is published monthly. 

Street Centerline: This depicts the center of the pavement of public and private roads within Delaware County. The address data was developed from data collected by field observations of current existing addresses. 

Recorded Document: This dataset contains points that represent the recorded documents in Delaware County Recorder’s Plat Books, Cabinets/Slides, and Instruments records. This dataset was made to facilitate the process of locating miscellaneous documents in Delaware County, OH. 

Survey: These are points that are a shapefile of point coverage which represents surveys of land in Delaware County, OH. The surveys are then scanned and saved as PDF files. 

GPS: This dataset has all known GPS monuments that were established in 1991 and 1997. This dataset is also updated on an as-needed basis. 

Subdivision: This dataset has all the subdivisions and condos recorded in the Delaware County Recorder’s Office. This dataset is updated on an as-needed basis.

Parcel: This dataset has polygons that represent all cadastral parcel lines in Delaware County, OH. On a monthly basis, this dataset is maintained and published. 

School District: This dataset has all School Districts in Delaware County, OH. It was first created from the Delaware County Auditor’s parcel records for the school districts. 

Tax District: This dataset has all of the tax districts within Delaware, OH. The data is derived from the Tax District code. 

Township: This dataset has all of the 19 different townships that make up Delaware County, OH. It is published on an as-needed basis. 

Aerial Imagery: “2024 3in Aerial Imagery. Flown Spring 2024”

Building Outline 2023: Building outlines 2023

2021 Imagery (SID File): Delaware County, Ohio. 

Condo: This dataset has all the condominium polygons in Delaware County, OH.

Address Point: The state of Ohio Location based Response System Address_Points data set is a spatially accurate representation of all certified addresses in Delaware County, OH.The layer makes it so you can reverse geocode a set of coordinates to determine the closest valid address and is intended to provide 911 agencies with the information needed to comply with Phase II 911 requirements. 

Address Points – DXF: The State of Ohio Location Based Response System (LBRS) Address Points data provides for a spatially accurate placement of addresses within a given parcel in Delaware County, OH. Through a partnership between the State and Ohio and Delaware county helped create the data. 

Annexation: The data set has Delaware County’s annexations as well as conforming boundaries from 1853 to now. This dataset is updated on an as-needed basis once the annexation has been recorded with the Delaware County Recorders office.

Building Outline 2021: The dataset has building outlines for all structures in Delaware Country, OH. The layer was updated in 2021. 

Building Outline 2023:Building Outlines 2023 

Dedicated row: This dataset consists of all the lines that are designed Right-of-Way within Delaware County, OH. 

Delaware County Contours: 2018 Two Foot Contours 

Farm lot: This dataset has all the farmlots in both the US Military and the Virginia Military Survey Districts of Delaware Country, OH. The dataset was created to facilitate in identifying all of the farmlots and their boundaries in both US Military and Virginia Military Survey districts of Delaware County, OH. 

Hydrology: The dataset has all the major waterways in Delaware County, OH. In 2018 the data was enhanced with LIDAR based data. 

Map Sheet: The dataset contains all of the map sheers within Delaware Country, OH.

Original Township: The dataset contains the original boundaries of the townships in Delaware County, OH before the tax district changes affected their shapes. 

Chapter 1 mainly took me through how to use the program and what everything does. I learned how to configure the maps and work with the data. I also learned how to manipulate that data into tables. The easiest part was making the 3d map, and it was really cool to look at/explore. 

I wasn’t able to complete the query for 1.2, part 4, for searching for a feature. 

There was no option to list by drawing order. 

There was also no option I could find for toolboxes in the geoprocessing pane. 

And I could not find an option for text symbol group. 

Chap 2

I could not find the symbol for Commercial.

There is no Label class group in the labeling tab. 

I’m unclear on how to use pop-ups, specifically how to display the needed data. 

When I did a definition query, I could not find the option to have all my values show up on the map. 

I did not have the Soup Kitchen value. In my food facilities option, below it only says <all other values>, but it does not show the values. 

I learned how to use a query to limit features. Using the symbology pane throughout Chapter 2 kept confusing me. For example, in 2.5, I was supposed to choose Circle 3 within the template symbol, but I didn’t see an option to do that.

I learned about Choropleth maps and struggled a bit to make one. I originally could not find an Advanced Symbology option button when making the Choropleth map. I ended up finding it later, so I went back and did things according to this step. The odd thing was that in the classes section in Symbology, I did not have more than one upper value. 

For 2.8, I could not find the Visibility Range group. 

Chapter 3

3.1 Was very tedious when making both the maps of the US and learning how to use the legends. 

3.3 I did not understand how to add the Metropolitan Employment layer to my story. 

Chapter 3 walked me through making map layouts and charts, how to share maps to ArcGIS Online, how to use the map viewer, how to make a story in ArcGIS StoryMaps, and also how to use/make a dashboard. This was all new information for me as I followed the steps. Some of the steps were hard to follow/understand, but I had the least amount of trouble with Chapter 3.

Chapter 4

Mapping density is crucial for maps, as it shows you where the highest concentration of a feature is. Density maps are also useful when observing patterns and mapping areas of different sizes. Using these maps allows you to measure the number of features with areal units (ex: hectares/square miles); this is a valuable feature so that distribution over area can be seen adequately. Density maps become very helpful when you are trying to map census tracts or countries since they vary in size.
To map density, you can shade areas based on density value, or you can create a density surface. Different density features can include locations of businesses, crimes, and numbers of employees.
Dots can be used to represent the density of the locations (specifically individual locations). The dots will represent a certain number of features (ex: one dot may be 2 birds). The closer together the dots are, the higher the density is.
To calculate the density: divide the total number of features by the area of the polygon
A density surface is created in the GIS and is created as a raster layer. A density surface can be made from individual locations or linear features (roads/streams).

Methods:
Make a density map by area if the data you have is already summarized by area.
Make a density surface if you have individual locations (sample points and lines).

Dot density map:
This is a map that uses dots to represent a total count or amount based on how much each dot represents
The dots don’t represent the actual locations
Used for quicker reads of the map
Represents density graphically
Cell size: determines how the patterns show on the maps.
Search radius: This affects how many patterns will show up on the maps.

Chapter 5
Single area: A single area makes it so you can monitor activity.
Buffer: defines a distance around a feature
Discrete features: are identifiable features (locations and linear features)

Overlaying areas and features creates a new layer that has the attributes of both of the layers. Overlaying can also be used to compare the two layers. This can be helpful when trying to find which features are in each of several areas or finding how much of a feature is in one or more areas. To do this, you need data within an area (a dataset with features) that includes all the attributes you want to summarize.

To see which areas are discrete, you can shade the outer area with a lighter color or draw the boundaries of that area’s features on top. By doing this, you can emphasize the features inside the area. Another option is filling out the outer area with a pattern or a translucent color. If you are shading discrete areas

To map a single area, you can shade the area in or use a thick line to show the boundary.
Count: the total number of features inside an area.
Frequency: the number of features that are in a given value.
Sum: the total number/overall total
Average: the total of a number divided by the number of features
Median: the value in the middle of the range
Standard deviation: the average amount of values

Raster method: this method combines raster layers. The GIS will compare each cell with the area layer that corresponds to the layer containing the categories. The number of cells is counted for each category within each area.

Chapter 6

This chapter how to find what happens within a distance on a map. It explains the importance of traveling range, how to define and measure what is near, and how to measure travel.

Traveling range: A measured distance (measured by space, time, and cost)

If you want to find what is nearby on the map, then you can calculate a straight-line distance. Or you can assess the cost over a net distance, or assess the cost across a surface. These are different methods that can be used. Sometimes the features that surround a certain area may already be within the area of influence.
Distance is used to know how close something is to another thing. To find what is nearby, you can use cost. A common cost is time, and time can be used to find what is nearby. An example would be that it takes longer for a customer to get to a store because bad weather impacts traffic. When considering travel, you can map what is nearby by distance or cost. The most accurate way to do this is to map travel costs.

Inclusive rings: Circles that encapsulate a certain distance
Spider diagram: looks like a spider; the GIS draws lines to two or more sources with a similar location
Distance surface: used to make buffers at specific distances

Chapter one

GIS can be used for more purposes than building geodatabases and making maps. Most notably, it can be used to address pressing issues and world problems. GIS is used to look at geographic information/patterns in data and address relationships between features. The features can be quite simple, and they can also be quite complex. To begin, you must start with an analysis; to do this, you need to figure out the information needed. It is important to be as specific as possible with your question. Next, you must understand the data to be able to decide the method you use. Once you have your method, you can process the data to then be able to interpret it.

Discrete features: have locations and lines, and the actual location can be pinpointed at any given spot.
Continuous phenomena: precipitation or temperature that can be found or measured anywhere. This will blanket the whole area that we are mapping.
Continuous data: often begins with sample points that can be regularly or irregularly spaced out. It can also show areas closed in by boundaries if everything inside the boundary is the same.
Features summarized by area: can represent the counts or density of individual features that are in certain boundaries. An example mentioned by the book is the number of businesses in each zip code and the total length of streams in each watershed, and lastly, the number of households in each country.
Categories: groups of similar characteristics/things.
Ranks: ranks features from high to low, mainly used for direct measures when they are difficult or if the quantity represents a combination of factors.
Counts and amounts: a count shows the true number of features on a map. The amount is any quantity associated with a feature that is measurable.
Ratio: shows the relationship between two different quantities.
Continuous and non- continuous values: counts, amounts, and ratios are continuous values.

It seems like you have to be very careful and technical with how you use GIS. One part that I read talked about cell size: if you use a cell size too big, some information can be lost, and if you use a cell size too small, then it takes up too much storage space.

Chapter two

Maps are used to see where and what a certain feature is. If you look at the allotment of features on the map, you can notice patterns that better help you understand the area that is being mapped. GIS can be used to map the location of different features to see if certain features occur in the same place. The book gives examples of businesses mapping customers by age, a police station creating maps based on crimes that vary in type, or seeing if assaults and thefts happen in the same area.
When planning a map, make sure that geographical coordinates are assigned and that each feature has a different category. Each feature needs a code that is unique to that feature. The GIS will store the location of all the features with a pair of geographic coordinates that will define their shape(line or area). Symbols will be assigned to the features as you specify them.
For linear features (streets), the GIS will draw lines to connect the points of interest that define the shape of each street. For areas like land, the GIS will draw the outline, or it will fill them in with a certain color or pattern.
When dealing with a subset of features, it is important to map the features in a data layer. Mapping within subsets is more commonly used with individual locations.
It is important when mapping an area that is large area to have fewer than seven categories. This makes it easier to see patterns. And if there are more than seven categories, then grouping some of the categories will help lessen the initial number.
Freeways are often drawn wider than highways.

Chapter three

Maps show location, but to add more factors to elevate the amount of information that a map shows, you can add different features based on quantities. Some features that can be mapped are: discrete features, continuous phenomena, and data summarized by area.
Quantities can be: amounts, ratios, or ranks.
When summarizing by area, if you use counts or amounts, they can skew the patterns if the areas happen to vary in size
The most common ratios are averages, proportions, and densities
Proportions: show you what part of a whole each quantity represents and are often shown as percentages.
Densities show you where the features are concentrated. (value/area=value per unit of area). Density is used to show distribution for the areas that are being summarized
Ranks put features in order from high to low. Ranks are used to show relative values instead of measured values. Sometimes direct measurements may be hard. Ranks also tend to be mapped as individual values. Also, it is worth noting that you should assign one symbol for each rank. And if you have too many ranks (more than seven), put them into classes.
Classes: Classes are counts, amounts, and ratios grouped. Using classes is helpful when the map is used for public discussion since it makes the viewer able to compare areas more quickly. How you decide to define the class will determine what features fall into each class and what the map will look like.
Individual values: Individual values can present a clear picture of data since the features are not grouped. If you map individual values, then you can search for certain patterns in the raw data, this can help if you are unfamiliar with the data or the area that you are mapping when looking for subtle patterns in the data.
Natural breaks: a classification that finds groups and patterns that are inherent in the data. The values in a class are probable to be similar, and the values between different classes are different.
Equal interval: each class has an equal scope of values (the difference between high and low values is the same for each class).
Standard deviation: “each class is defined by its distance from the mean value of all the features”

Finished GEOG 291 Quiz!!

Hello! I am Talia Jefferson. I am a sophomore and am majoring in Environmental Science. I love getting outside, taking walks, and watching different shows.

Before reading  Schuurman ch. 1 I was not aware of what GIS was/is. It was a term that I heard a lot last year and yet I never took the time to understand what it meant. When I have thought of GIS, my first thoughts were mapping, and now I know that is only a tiny part of what GIS does.  GIS began as a way for a landscape architect to make the most optimal route for a new highway. It began as a need for innovation and then eventually evolved.

I realized while reading I had heard the term GIS in National Geographic docs. I remember in the vidoes, GIS was used to reconstruct a visual of what land in an area looked like hundreds to thousand years ago. I always found this very interesting and a good use of tech. The visual reconstruction made it so the scientists could start to understand ancient life and practices to enhance our historical knowledge. It is always important to learn and understand the past, especially the parts of ancient history that is still left widely unknown. But this is not the only good GIS can do. The article mentioned GIS success in health, agriculture, development etc…

Gis is used to map an area to then analyze spatial data within location and other descriptions. Which is then used to for urban planning, tracking natural disasters/climate, used for businesses, resource management…all things that are important to help society function efficiently. Before reading this article I did not understand the importance of GIS. It was merely a word I heard from time to time and one I never put my thought into. Now I can appreciate the full extent of GIS and the science behind it while also learning how to use it in this class.

This image represents three main areas that show the analysis of the spatial context of the services for LQBGTIA people that were disproportionately located in areas with less people of color and underrepresented in Black/African American and Hispanic/Latino groups.

Chicago LGBTQ service sites and race/ethnicity. Racial/ethnic data is based on the 2011–2015 American Community Survey estimates and presented at the block group level. ORD, O’Hare International Airport; MDW, Midway International Airport

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This image is a map of the climate in norther Iran. The purpose of the map is to plan for planting and restoration of the endangered lily in the northern part of Iran. More maps were preparied that then were overlaid in GIS software to separate suitable regions for planting vs non-suitable regions for planting. It was found that 19 suitable regions were compatible with the site condition of the species were queried in the GIS.

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