Author: ebmontana

Summary of Delaware county GIS data

Parcel

This data layer displays all individual properties as a polygon that can be selected. Displays polygon data  and the corresponding information.

Address point

This data set aims to show the accurate point tied to each street address. The main use of this layer is to provide quick and accurate information to first responders.

Recorded document

An array of points that indicated recorded documents in the Delaware county record coming from each address. This was used to find miscellaneous documents.

Zip code

Separates Delaware county by zip code. In Delaware county there are 21 zip codes represented. Zip coders are used by counties to group addresses by geographic location.

School district

Roughly models similar polygons to zip code. Less School districts are present. School districts can be an important variable for parents moving to a new neighborhood in their decision to buy a home.

Map sheet

All map sheets in Delaware County. Not quite sure what a map sheet is but it seems to represent some form of geographic area.

PLSS(Public land Survey System)

Used by the US military and the Virginia Military service district of Delaware county. The internet said it is a public land use system for compensating Revolutionary war soldiers?

MSAG(Master street address guide)

Shows the 28 political jurisdictions found in Delaware county(ex: townships, cities, villages). Created to show boundaries and is most likely used in finding addresses and general geographic regions. I assume many of these boundaries cross into other counties.

Municipality

This seems to be something like a subset of the MSAG regions but this time I believe it is only showing those with defined corporation limits. Centered around areas of high development.

Farm lot

Shows data from the US military and Virginia military survey. All data is organized into farm plots even though not all the area is a farm plot. I believe they are ranked by percentage farmland based off of their FL_ID.

Township

Separates Delaware into its 19 different townships.

Street Centerline

Shows all major streets in Delaware. Useful for pathfinding and display of density of road systems. Smaller private roads do not seem to be present.

Annexation

Displays polygons that were individually annexed into Delaware counties and several municipalities. Includes date annexed.

Condo

Shows all condominiums located within Delaware county. Can be useful for mailing addresses as well as advertising campaigns that benefit from closely clumped groups of people.

Subdivision

Similar to above lists all subdivisions. Subdivisions are more common than condos here in Delaware county.

Dedicated ROW

Database of all roadlines indicated as right of way. Important in management of road infrastructure and calculating driving distances etc..

Precincts

Separates Delaware county into precincts.USed for voting and can be used by political analysts to identify causes of political background(ex: farmland, urban areas, often linked to political profiles)

Survey

Many individual data points. They indicate places where land surveys have been carried out.

Tax district

Separates Delaware into task districts. Similar to other boundaries that have been drawn around the city/township.

Building outline

Outlines all buildings as of 2024. Very defined polygon drawings that can indicate house shape and size. High number of individual polygons. Shape area and length can be important here in studies done on this value.

Railroads

Indicates railroads. Can be an important factor in determining living areas because of noise issues. Construction companies might choose to build elsewhere based on close proximity to railroads.

Delaware county E911 Data

Used by emergency response units to find individual house centroids and make decisions on things like emergency response placement, and locating emergency addresses.

Building outline data 2021

Same as above (2023, 2024)

Hydrology 

All major waterbodies. Includes the 4 large lakes and some smaller reservoirs and some rivers of a certain size or larger. Includes area and is an important layer for those concerned with available drinking water, recreation, etc.

GPS

Pairs of centroids located nearby to each other vary in distance. Each represents a GPS monument. All were established in 1991 or 1997.

Delaware county contours

Shows the contours of Delaware County. Contours are represented by 2 foot increase and decrease.

Original township

Shows original township location. Includes name and acreage. Does not include for what period these townships existed.

This is a map containing the layers parcel, Street Centerline, and Hydrology.

Week 6

Chapter 7

This chapter puts to practice how we draw polygons and define areas using the GIS. Most of our work for this chapter was spent defining areas using polygons and manipulating those polygons to fit the buildings present on the CMU campus. I think it is interesting that they used Carnegie Mellon because I feel like I remember reading something about them having some sort of tie to GIS work.

One of the most fun parts of this chapter and consequently probably the easiest was smoothing polygons to fit real vectors. We did this for several golf course greens and a small lake.

This second picture is the image of a CAD drawing I input into the GIS. It took me forever to find it and I was worried I had messed something up but then I zoomed to the layer and found it in Cincinnati.

 

 

Chapter 8

Chapter 8 put focus on geocoding which is the geographic signature attributed to different points. We first worked to correct some database values that needed some correcting in a registry of attendee addresses. We also did some fairly basic display changes. In the second part we worked on matching address fields with the address we are given to the correct address table. We also checked for the accuracy of each of the matches and the overall successful match count.

Above is a map of all of the addresses in the attendee address database. 

After matching the data in the attribute table we ran a select by attribute based off of the accuracy score of the address matching(score 90 or above). Those fields were highlighted and then the map updated to show the addresses we had a match on vs. the ones we don’t have a match for.

 

Chapter 9

 

Chapter 9 focused on spatial analysis and drawing boundaries around distance to points. This chapter’s work was focused in the city of Pittsburgh where the analysis was on pool availability for the youth and in the last module crime. I found this module to be pretty challenging at times but mostly that was because I was not reading the directions thoroughly and looking for the right buttons. The first two modules introduced buffer rings to show locations around a point and how to add multiple of these buffers around one single point.

We then created a map called a gravity model which instead of showing distance to a point as equidistant use more complex real world logic to discover the distance to the nearest pool(pictured below)

We also created a spider plot graph to show distances without a set color interval. Each of the lines connects from a pool to a block centroid. Finally we organized crime data to come to spatial conclusions about different demographic groups and their crime impacts.

 

Tutorial

Chapter 4

 

This chapter was all about working with datasets. The first 2 subchapter modules had you implement data sets into the tutorial and started with some dataset management. Later chapters focused on summing data, selecting by certain data fields, and joining data types to find the answers you desire. There was also the introduction of SQL queries which gave some baseline knowledge on how one might code within the SQL language to get the desired data.

 Above is a Maricopa County figure separated by municipalities that was implemented in the first sub module.

You could switch between the normal easy to read GIS interface and the SQL coding tab to see how the identifiers would be used and written in a SQL query.

 

Chapter 5

First modules focused on teaching about distortion in a chunk of the world displayed. It illustrates how world maps are less accurate than smaller maps where all features are on a similar geographic plane. Ex: maps of the US are more accurate than maps of the world that have inaccurate representations of Greenland, Antarctica, etc. Many of the modules in this chapter also introduced various coordinate systems to label distinct features at exact locations. There was a lot of work that focused on finding the correct downloaded data in file explorer and implementing it into the GIS. I probably struggled with this chapter the most but I thought the last module was pretty cool and I can see the real world applications for these processes.

This first map displays libraries spread across New York City.

This second one is a map of Hennepin County, Minnesota with elevation contours and bike routes downloaded from the USGS website.

Chapter 6

This chapter had us focus on merging and breaking up spatial entities using both the merge tool and dissolving polygons to generalize distinct areas into more regular polygons. It had us use selection tools to find all streets within an area and used the pairwise clip tool to cut off unnecessary street data(pictured below).

There was a large focus on using geoprocessing tools in this chapter as we did various processes. The image below is a shot of New York fire streets. We can manipulate the data in a way that would be useful to firemen in the city. 

The last module showed similar use by showing the total number of people with disabilities in certain tracts and providing the information of where these tracts fall within fire station territories. I assume that this is useful because firemen have to assume that some people who are disabled(ex: in a wheelchair, can’t get out of bed) may be harder to account for at the scene of a fire or they may need medical assistance themselves.

Tutorial

Chapter 1

 

In the first chapter of the tutorial a massive amount of information was presented. Many aspects of how you can interact with various panels in the GIS and various display elements were explored. All of our work centered around Alleghany county PA and the urgent care availability and type of urgent care as it relates to other factors (ex:pop density, total pop per area, etc.) while also including other features like roads and rivers.

This map rendering focuses on the two different types of healthcare facilities in the county. The green dots(subsidized FQHC clinics)  and their subsequent buffers are concentrated in the areas where poverty is most likely to occur. The Urgent Care Clinics(unsubsidized are located primarily in the suburbs where poverty is less common.

At the very end of the 1st tutorial we got to turn the map into a 3d model based on population density. You can see the same concentration in the center of the county but now with more variable range since it can be displayed in height.

 

Chapter 2

 

Chapter 2 had a huge emphasis on the symbology feature when you would right click one of the terms in the contents page. It focused on ways that you could display and scale data.

This image used the display by dot density symbology to show the population of individuals receiving food stamps over the age of 60(red) and individuals under the age of 18(blue)

Another cool thing this chapter looked at was at what scales do we have various names for places to come up. I got confused a couple of times on this one because things were taking a while to show up because they were appearing at similar layers and on a pretty huge scale.

Chapter 3

This chapter had a focus on the cross compatibility between the ArcGIS pro application and the online version where documents made in the pro version are made more accessible and user friendly. The system for editing your maps in the online version is much simpler but as a result lacks the ability to do complex tasks. The first part of chapter 3 also demonstrated how to include legends onto existing maps and how to show two maps at once for comparison.

This first image is of a map made in the GIS that was then transferred to StoryMaps to be viewed. A brief introduction and summary of the map was included as well as the necessary citations and their usages.

This last image is a dataset and map that was transferred from ArcGIS pro to the online GIS. Using the Dashboard utility we could make a simple table and corresponding charts.

Chapter 4

Chapter 4 talks about density(the number of things within a certain area/ volume) It talks about two ways to show density with the density by area model and the density by defined area or by surface. Density by defined area takes a distinguishable area(ex: county, zip code, etc) and collects the number of features and displays the area as a certain color based on the gradient number that the area has been given. Density by surface does not require defined borders and the range is editable. To find the density for either of these to find its range on the color coded gradient you must find the number of features and divide that by the area of which you are finding the density for. 

 

I face some confusion about the representation of density through defined cells. Is the total map split up into equal cells and the number of the features counted and then the circle is placed in the middle of the cell or is the cell based off of the location of the features being studied(ex: businesses, employees, etc)Or does the GIS find the average distance between all points in the cell and move the circle to that point.

 

I enjoy that they often include what one particular map might be used for and by whom it might be used. It is good to have a clear explanation of how these techniques are used by everyday people and businesses.

 

Chapter 5

This chapter “finding what’s inside” had a focus on defined areas and how you can manipulate both their visual properties and informational properties to gain insight. The example of a flood plain was used a lot in this chapter to show how different areas can be overlaid with each other. You can take a group of defined areas(in the text it was personal properties categorized by their use) and overlay something like a floodplain or a watershed above the initial scape. You can also emphasize different parts of the map, for instance you can only include parts of the property area that are included in the flood plain area or you can have all properties with a part in the floodplain highlighted. The text makes it clear that this sort of mapping would be very important for things like watershed access, flooding, fire protection, school districts and more.

 

The text also made some comparative examples with drawing areas vs. Selecting the features inside the area. Drawing does not require any complex calculations so it is much easier to do but cannot list information so it is visual only. The other option selecting the features is good for knowing what is inside a group of areas but does not allow you to analyze areas individually. There is also the third option of overlay which lists multiple layers and allows you to draw conclusions based on which things overlay each other. The main drawback to this though is that it uses a lot of computational power. 

 

An interesting question one might ask is how can these three methods be used together to make more meaningful conclusions?

 

Chapter 6

I think that it is an interesting idea to map the distance of something by cost. I wish you could do that in google maps to see how much you would need to spend on fuel.

 

This chapter analyzed the display of distance and how we show paths. A lot of the information seems like it would be tied to GPS but there was also some discussion of how it could be used by police stations, fire stations, etc… to understand their travel range. There was also discussion of the variable of cost which was a different way of looking at distance not in terms of location but in resources used to reach a point. I believe that this is a way to incorporate terrain changes into the mapping process.

 

There is also the sectioning of distances using inclusive rings which include all features from the outside to the center of the circle and distinct bands which are different distances from the center point and can indicate the number of features within a distinct distance band.

Another interesting style mentioned in the text was spider graphs which send a point straight to a feature within a certain range.

 

Switching from distance to cost creates a more detailed contour map because of the terrain features mapped.

Chapter 1

The first chapter introduces us to many of the essential techniques used in mapping and display of geographic features. Beginning with the first section you realize that it is paramount that you be specific in defining the geographic features you want to display and their corresponding attributes. Next we examine the choices one must make when deciding the way you want to gather/ display the information in question. In terms of display we are presented with the ideas of vector or rather format that have different levels of scalability with the vector option being adapted to a wide range of scales the rather methods looses sharpness at smaller scales but is perhaps more adept at showing the blend between to regions. We also have ways of defining the data we aim to present/analyze. Very distinctly data can be modeled discretely while regions with similar conditions or qualities are modeled continuously. Lastly they can be summarized by areas where specific points are given greater importance by being defined to a distinct geographic location.

 

I find some confusion about how lines might be drawn with individual points. What sort of software might be used to generate points on a line or are the points created by hand to model larger phenomena?

 

What advantages might the Rather method have at a smaller scale. Would it be easier to demonstrate the pervading category within a cell using the rather model as opposed to showing the distinctive line used by the vector model?

 

Each feature displayed on the map is given different attributes which are not shown on the map but rather in the table of information but ultimately determine how each feature is represented. Geographic borders remain constant between different features.

 

Chapter 2

The text states “ The GIS reads these and assigns geographic coordinates.” This got me thinking. Are all GIS the same or do some have different capabilities and handicaps?

 

This chapter of the textbook seems to be more focused on what the GIS is capable of and is less focused on the specific geographic features and their attached attributes that the user implements into the GIS. It also dived into the aesthetics of mapmaking and gave some helpful tips on styling, shaping and color coding of various features as well as how you can make maps more simplified through multiple levels of map complexity. One essential point that I got from this part of the textbook is that your map should aspire to be readable by everyone but should also be helpful to experts in whatever subject they aim to map.

 

There was also some focus on what to display to convey information best to the reader. I am wondering if there will be a greater emphasis on what to include and not include in your map in one of the coming sections ex: what things not to input into your map to make it seem unprofessional(clip art, 3d graphics etc).

 

I thought it was interesting that the maximum number of colors you should include was 7. I hadn’t thought about mapmaking that way psychologically but it does make sense. Is there some fluctuation in this where people can comprehend more than 7 shades? It is also sometimes necessary to use more than 7 shades. How can you make this more user friendly?

 

Chapter 3

The idea of summarizing data from most to least seems somewhat elementary to me. Would it not be better to explain how these things are programmed into a map?

 

I think the distinction between count and amount is an important distinction to make but I feel like the words are so similar would other more technical terminology make definitions seem more distinct example #categories paired with amount, etc..

 

The 3D modelling looks complex and I had not thought about the use of a light source to create shadows and how the positioning of that light source might create a very different visual.

 

This chapter focused on display of variables and mapping things from most to least. It examined the different ways you can choose to group numbers or ways that you can have the GIS automatically separate numbers into different classes using things like natural breaks. It then talked about some more ways to distinguish between these different classes you have made, For example: using line width when showing quality of stream health etc. and introduced charts to show categorical data internal to the area on the GIS. The chapter also gave a very helpful breakdown of the advantages and disadvantages of different types of display styles which I thought was really nice and simplified the earlier knowledge well and provided basis for comparison.

I completed the GEOG 291 quiz and reviewed the syllabus

Hello my name is Elliott Montana and I am a junior here at Ohio Wesleyan. I enjoy swimming on the swim team and going out fishing with my buddies. I am a Biology and Geography dual major hoping to pursue a career in natural resources/wildlife crime prevention. I think that the addition of GIS skills both as a desktop and online application will boost my career success in the field I plan to enter.

 

I have heard about GIS from several colleagues during my first year here at OWU and felt confused by what exactly it was and how it was used. My first interpretation is that it was solely a device used to make 3D maps. I now see that it is more complex than that and encompasses not just the technology used but also the analysis used to interpret the figures and data collected.

 

I thought that the idea of GIS being the “clearing of the fuzzy” was an interesting sentiment and made some sense to me. To me this translates to a set of decisions that help us define the distinct patterns that we can sense while viewing spatial objects through a geographic lens ex; what separates a mountain and a hill.

 

In addition to this I had not realized quite how much GIS is built into all the systems that function in our human society ex: The garbage routes and bike paths mentioned in the text. I had assumed that these processes were carried out by polling methods or simple measurements of distance covered.

 

I do not believe that my understanding of what GIS is has reached completion(I don’t believe anybody’s understanding of new and evolving things ever reaches 100%) but I think I will gain a better understanding of the concept over the next reading and practical hands-on experience with the technology.

 

Application 1

 

A GIS spatial analysis was used for several different factors in projecting habitat suitability for several species of marine fish in the Port Phillip Bay. The catch data was taken by fishing companies in the bay. Parameters measured include depth, substratum and sediment type.

Morris, L., & Ball, D. (2006, January 1). Habitat suitability modelling of economically important fish species with commercial fisheries data. Ices Journal Of Marine Science. Academic.Oup.Com. https://academic.oup.com/icesjms/article/63/9/1590/696978?utm_source=chatgpt.com&login=true

 

Application 2

The next study aimed to identify swimming pools within an area using  the Normalized Difference Water Index (NDWI) which works within a GIS system to identify standing water that is constituted as a swimming pool. The purpose of this is to identify places where mosquitoes might be breeding in an effort to combat the spread of the deadly West Nile virus.

APA Style

McFeeters, S. K. (2013). Using the Normalized Difference Water Index (NDWI) within a Geographic Information System to Detect Swimming Pools for Mosquito Abatement: A Practical Approach. Remote Sensing, 5(7), 3544-3561. https://doi.org/10.3390/rs5073544