Final Project Portfolio

Project Blog

Metadata Project

Readings Summary with Keen & Taylor



Delaware Metadata Set

Delaware_2008 and 2010 Ponds and Lakes: This dataset shows the locations of ponds and lakes within Delaware County and can be useful to determine the presence of wildlife in an area.

Delaware_Address_Pts: The location of all address points in the county.

Delaware_Annexations: This dataset is has a very obscure description, but it should probably mean areas in a township that are in the process of being annexed by a surrounding city.

Delaware_Archeological: Potentially dig or important prehistoric sites?

Delaware_Bench_Marks: Location of geographical benchmarks that are used in USGS maps.

Delaware_Building Outlines: Outlines of the buildings in the county

Delaware_ Census_Block: No data

Delaware_ Census_BiockGroup: Same

Delaware_ Census_ Tract: Statistical data about parts of the county

Delaware_Economic Development Layers: The economic development projects currently going on.

Delaware_Farmlots: The areas in the county that are farms.

Delaware_Floodplain_1OOyr: The area that a river will flood approximately every 100 years. Important for which areas will receive water damage as a result of this flooding.

Delaware_Floodplain_500yr: The extent of the area that will flood every 500 years. The info may not be available for this because one of this magnitude may not have occurred yet.

Delaware_Floodplain_2009: Areas that are at risk for seasonal flooding.

Delaware_Floodways: Stream channels that are at risk to flooding.

Delaware_Historical_Local: Local historical landmarks, such as Edwards Gym.

Delaware_Historical_National: Location of national landmarks, such as the birthplace of Rutherford B. Hayes.

Delaware_Hydro: Major bodies of water in the county

Delaware_Hydro_Detail: Every body of water in the county

Delaware_Landmarks: Points of interest within the county

Delaware_Master Point Coverage: Similar to address points

Delaware_Municipalities: Cities and towns (not townships) in the county, such as Powell and Delaware.

Delaware_Natural_Heritage_ ODNR: Locations of geologic importance classified by the ODNR

Delaware_ Orthophoto _Detailed_2010: Very detailed raster data that comes in 3 separate layers. Images are very clear and are updated more frequently than are Google Maps.

Delaware_Parcels: Every parcel in the county, including classification and ownership

Delaware_Parks: All parks in the county

Delaware_Places of Interest: Similar to landmarks

Delaware_Precincts: Voting precincts within Delaware. This determines where people go to vote when it is time to.

Delaware_Public Land Survey System: A grid placed on the map of every location that has been surveyed.

Delaware_Railroad: Location of railroads in the county

Delaware_Road_Center_Line: Shows the median/center-line for all roads in the county.

Delaware_Road_RightOfWay: Shows the entire right of way owned for roads, including sidewalks, in the county

Delaware_School_Districts: Shows the breaking up of school districts within the county, such as the boundary of where someone goes to Buckeye Valley rather than Delaware Hayes.

Delaware_Soils: The surface soil types across the county

Delaware_Subdivision: The different residential subdivisions within the county

Delaware_ TaxDist: The different tax districts within the county.

Delaware_ Topography: Shows the elevation changes in the county by overlaying a shaded relief map.

Delaware_ Townships: The county’s different townships, like Liberty and Troy

Delaware_ Townships_Historical: The township as they looked in previous years.

Delaware_ Watersheds_ ODNR: The different watersheds within the county.

Delaware_ Wetlands: The county’s wetlands

Delaware_ Woodland_ ODNR: The wooded areas of the county.

Delaware_Zip_Codes: Geographical cutoffs for the zip codes in the county.

Ohio Wesleyan Parcels: Parcels that are owned by OWU

Watershed-Scioto: The entire extent of the Scioto River’s watershed.

Chapter 6: Finding What’s Nearby – Summary

Why map what’s nearby?

It is useful because it can show what areas may be affected by an event or activity, or being able to find things within a set distance so those areas can be monitored. Finding a traveling range of say a fire station shows what areas are served by that station, and also shows if there are any areas that are not served so that new fire stations can be built.

Defining Your Analysis

How do you define how near things are? One way is to use radius distance and another way is to use distance traveled from a specific location. Distance is a method of measurement, but cost, such as time or money, can also be measured. Once you figure out what to measure, the question becomes whether or not you need list, category type, or statistical summary of the data needed. Then what are the ranges that need to be included. How many? Should inclusive rings or distinct bands be used if a distance radius is being used?

3 Ways of Finding What’s Nearby

Straight Line Distance. Distance or Cost over a Network. Cost Over a Surface.

Using Straight Line Distance

This can be used to create a buffer and find what’s inside of it, find features within a given distance, find features from one point to another, and calculating a continuous distance along a certain source. For creating a buffer around a source, one can then find features within that source. Data could also be gathered and plotted for several source points, as well as within several different distance ranges. Selecting features within a distance is similar to a buffer zone, but the difference is that the program does not create a boundary around the source. Feature to feature is useful to find locations in relation to a source. Distance surfaces involves creating distance layers at specific intervals and creates buffers at each of these intervals.

Measuring Distance or Cost over a Network

Calculating Cost over a Geographic Network


Railroads use GIS to not only maps out their route networks, as seen in the map above with the Union Pacific’s Route Map, but they can about be used for visually showing the carloads of certain lines, the high points of elevation on the network, or the plans for a new expansion or relocation of a current line. This can also be shown on maps of a previous era, as the Penn Central Map, while it used an older mapping technique, could be updated to show where the line went during the time of it’s short reign. GIS, along with GPS, can also show where cars and locomotives have been on the railroad, and can help with logistical planning and tracking carloads on the railroad to help with getting the cars for delivery on time.

The Schuurmann Reading

-GIS is enjoying a massive boom right now. The piece at the beginning didn’t even include how omnipresent Google Maps is and how all smart phones include an app for some kind of mapping tool (iMaps or Google Maps). And a lot of people use these tools on a daily basis. Even though these are very base level GIS programs, it shows how expansive GIS is throughout people’s lives today, even to the point where people rely on it completely (and maybe a little too much).

-GIS comes from the concept of overlay, and is not just one strict data set. This allows data to be added and subtract from the map depending on what the user wants. This also allows for massive 3rd party expansion of data related to these maps that are not included with the maps themselves. Also, it allows for data to be updated to insure constant accuracy.

-The whole argument over whether mapping of data is easier to read than tables or numerical data comes back to the whole idea of people learn in different ways. While many people may be able to interpret map data easier than tables, some people still may interpret tables better than maps.

-There’s a GIScientist? So, how do they go about analyzing the data provided in the map?