W F 26: Delaware Data Inventory

Delaware_2008 and 2010 Ponds and Lakes (Ponds and lakes in Delco, was cool to see more in 2010)

Delaware_Address_Pts ( All the points where addresses are in Delaware)

Delaware_Annexations (Best guess is that this is land that was annexed by Delaware county from other cities, like Columbus, Delaware, Scioto or maybe areas that were annexed by those places)

Delaware_Archeological (Points in Delaware county of Archeological importance)

Delaware_Bench_Marks (GPS Benchmark coordinates throughout Delaware county)

Delaware_Building Outlines (Outlines of buildings in Delaware county)

Delaware_ Census_Biock (Population living within a census block)

Delaware_ Census_BiockGroup (Larger group of blocks for measuring population)

Delaware_ Census_ Tract (Looks the same as above but different color)

Delaware_Economic Development Layers (Shows different type of residential development, Two layers do not seem to make sense, not sure what they are)

Delaware_Farmlots (shows farm areas in Delaware county)

Delaware_Floodplain_1OOyr (100yr flood data)

Delaware_Floodplain_500yr (500 yr flood Data, shows area that would be effected)

Delaware_Floodplain_2009 (Have no idea why the whole map is pink? but think it is showing a flooding area of 2009)

Delaware_Floodways (Shows the major flood pathways)

Delaware_Historical_Local (Historical spots for Delaware or Ohio)

Delaware_Historicai_National (National Historic Sites)

Delaware_Hydro (Major bodies of water in Delaware, Great for our project)

Delaware_Hydro_Detail (Major bodies of water, including some ponds, and a freehand sketch of Delaware Run)

Delaware_Landmarks (Landmarks in Delaware)

Delaware_Master Point Coverage (I think this shows where all man made structures are in Delaware county, because there are many different types of structures)

Delaware_Municipalities (shows the different municipalities in Delco)

Delaware_Natural_Heritage_ ODNR ( Nature Sites? Points on the map)

Delaware_ Orthophoto _Detailed_2010 (Ariel photo of north and south Delaware county)

Delaware_Parcels (Parcels for Delco. Great for all projects to find additional data)

Delaware_Parks (Parks in Delaware, might be useful for bird projects)

Delaware_Places of Interest (as it implies, places of interest from police, to cemeteries, used this for hospitals)

Delaware_Precincts (Voting Precincts)

Delaware_Public Land Survey System ( I have no clue what this is, looks like polygon shapes in blue, no info in attributes other than coordinates)

Delaware_Railroad (railroads in Delco, good for projects that need some distinct visual clues to where the location is)

Delaware_Road_Center_Line (Center line of road, good for visual clues on maps)

Delaware_Road_RightOfWay (Shows roads that have Right of Way)

Delaware_School_Districts ( Shows regional school districts)

Delaware_Soils (Soil map for Delaware county, will be useful in Delaware Run project)

Delaware_Subdivision (all the subdivisions in Delco)

Delaware_ TaxDist (Tax ID for local taxes)

Delaware_ Topography (All the township’s topography for Delaware county)

Delaware_ Townships (The different townships in Delaware County)

Delaware_ Townships_Historical (Guessing historic names of the townships)

Delaware_ Watersheds_ ODNR (All the watersheds in Delaware county, how the water drains)

Delaware_ Wetlands (Shows Delaware county wetlands, which we hope to add to with our project)

Delaware_ Woodland_ ODNR (wooded areas)

Delaware_Zip_Codes ( Shows all the different zip codes in Delco)

Delaware_Zoning (Think this might be broken just a big square)

Ohio Wesleyan Parcels (OWU Land)

Watershed-Scioto (Watershed for the Scioto River)

W F 26: Tutorial ch. 16, 17, 18, 19, 20

Chap. 16:

Joining and relating data by attributes or location.

Chap. 17:

Creating features by location query.

Use in parcel mapping.

Chap. 18:

dissolving layers, clipping and exporting maps for analysis.

Explanation of tools toolbar.

Chap. 19:

buffering and overlaying data from attributes. Then creating graphics.

Chap. 20:

creating and combing raster surfaces.

 

M F 24: Tutorial ch. 10, 11, 12, 13, 14, 15

Chap. 10:

Works mainly with layout screen and creating final maps for presentations.

Chap. 11

Creating Geo data bases

Chap. 12

How to create new features.

Drawing features.

How to use the feature tool.

Chap. 13

How to edit modify and add information to features in the attributes table.

Chap. 14

All about geocoding

Chap. 15

Using the query tool.

Most important, that I had to come back to was creating features by attributes.  This is one of my favorite lessons and saved a lot of time creating new layers.

 

 

W F 19: Tutorial ch. 3, 4, 5, 6, 7, 8, 9

Chap. 3:

Displaying map data:

Worked in ArcMap: Basic concept was to learn layers and general settings.

Basic Navigation

Basic Searches and finding distances.

In this chapter we began working with attribute tables.

Learned basics of sorting and selecting features.

Chap. 4:

Used ArcMap to create a thumbnail graphic.

at step 25 had a crash.

Learned how to add data to a map.

Extended abilities with map layers.

created a finished map with legend.

Chap. 5:

Skipped this section on Online resources. (due to time restraints with work and midterms.

Chap. 6:

Teaches how to work with coordinate systems.

Importance of spatial data.

Chap. 7:

Teaches how to change symbols, colors, and additional layer options.

Found out how to add layers from attributes and create new layers.

Chap. 8:

works on classifying features and mapping densities.

Chap. 9:

Labeling features and using graphic labels.

M F 10: Mitchell ch. 6 &7

Chap. 6:

Mapping what’s nearby:

Basic concept, Using GIS you can find out what features are within a certain distance or within a boundary.

Useful to show affects may be had by event or activity.
Defining Analysis. (liquor stores sending out mails to everyone in 500 ft distance, or fire departments determining coverage.) Distance, Time, Money, basic statistical information.

3 Ways of finding whats nearby: Straight Line Distance or cost over a network. Cost over a surface.

3 Ways of finding whats nearby: Straight Line Distance or cost over a network. Cost over a surface.

K: Two layers to select one on the other layers. Idea of a network would be road directions on Google set up on a huge network.

Use feature to feature: finding specific areas between two points on a map.

Distance surfaces, EX: take a river and do a buffer zone at 10/20

Measuring Distance or cost over a network.
Calculating Cost over a Geographical Network.

**read over chapter 7**

Time series? Tracking time like a bird flying around town.

Tacking features like wildfires, magnitudes?, wind speeds. Showing patterns and features. ?

Calculates over two dates, or times? Showing how much has changed.

K: Data that changes over time, like county parcel data, subtract from today, compare that to a map two years ago, see how things have developed or gotten smaller. Look at when the parcel was divided.

 

W J 29: Mitchell ch. 2 & 3

Chap. 2

 

Mapping helps you decide where things are and how you define objects. This is important to help define patterns or other features that might stand out.

Importance of knowing what you are mapping, asking the right questions and retaining what information is valid and important to the project.

Understanding that everything represents a coordinate that exists at a specific location.

After mapping you can add categories. This will help define the data and group like values.

Chap. 3

Mapping the most and the least:

When mapping the most and the least it adds additional features to be able to gather data.

Importance could be used to find locations of business or number of employees in a certain area, this data in turn could be used to find weak spots in coverage etc..

First you would need to know what you are mapping.

Count and amounts are important and understanding ratios or relations between different features.

Then you can choose the type of map you would like to do,

Ranks are a way to put features in order.

Mapping individual values using classes:

Natural Breaks: This helps find groups or patterns

Quantile: All classes have the same number of features

Equal Interval: All cases have the same range of values

Standard deviations: basically all classes are defined by their distance from the mean value of all the features

Outliers:

This is the data that is the high and low values and can skew the data substantially.

One way of dealing with this issue is to put outliers in their own categories.

You could also group them with their closest counterpart.

Once you get all your values then you can map your data:

Pay close attention to colors, symbols, charts. This will make the data easier to read and understand.

 

 

2.19.14 Class Notes:

** Look at C: GIS data Delaware county data. (C:\GIS Lab Data\Data – Delaware Co)

Go in to Arc GIS (Jot down a little information on what layers are)

Might be useful in midterm or exercise.

Properties.

Do not edit data, you can get a duplicate. **Do not play around with anything that says editing**

2 CDs One is a data CD, that is the one you want. Installing tutorial data, install in specific folder.

Mitchell: 6&7

Chapter 6 (finding whats nearby)

Useful to show affects may be had by event or activity.
Defining Analysis. (liquor stores sending out mails to everyone in 500 ft distance, or fire departments determining coverage.) Distance, Time, Money, basic statistical information.

3 Ways of finding whats nearby: Straight Line Distance or cost over a network. Cost over a surface.

K: Two layers to select one on the other layers. Idea of a network would be road directions on Google set up on a huge network.

Use feature to feature: finding specific areas between two points on a map.

Distance surfaces, EX: take a river and do a buffer zone at 10/20

Measuring Distance or cost over a network.
Calculating Cost over a Geographical Network.

**read over chapter 7**

Time series? Tracking time like a bird flying around town.

Tacking features like wildfires, magnitudes?, wind speeds. Showing patterns and features. ?

Calculates over two dates, or times? Showing how much has changed.

K: Data that changes over time, like county parcel data, subtract from today, compare that to a map two years ago, see how things have developed or gotten smaller. Look at when the parcel was divided.

Schuurman ch. 2 & 3

Technical way VS human response. Use it in a way that is top down tech heavy, Government agencies using.

Beginning GIS was used for tracking trucks and non-profit for political methods. Epistemology VS Ontology. How we see or the perspectives.

Points lines and area Ontology
Quickest way to get from a – b, not necessarily quality of drive Epistemology

Basic Vector Data: Points

Points, lines, areas.

Raster is more imagery.

Chapt. 3

Data Collection: Human collection. GPS location.

K: information collected by census, counties, states, nations, income and such.

H: Meta data, because so much data is out there, what is associated with it, and as of when.

4 & 5

Talks about how GIS is different that regular cartography. GIS population changes. Contained within and area.

Overlay analysis, correlation of relationships. At risk for fire.

Patterns of distortion.

GISystems – tools

GIScience – thoughts behind

find our what is in a general area, based on things like time, distance, and cost.

Straight Line Distance: Boundaries

Distance or Cost Over a Network.

Cost or surface.

Sustainability Region: Notes:

Experimental Class: Liberal arts come together to expand environmental science.

Forest:
Introduced Species (-)
Variation of under-story
Density Variation
Gaps
Cleaner Water

Urban:
Patchwork
More disturbance
asphalt
Introduced Species (+)
Warmer – Night
Land Use change
less biodiversity
Pollutants (+) of some types

What are the justifications?
Study or impact on local systems. Climate. Biome pretty new.

Adding the human element adds complexity to mapping. (however oversimplifying could create issues as well)

**interesting that campus would be a large continuous Bio Space.**

How do we describe humans as a biologist:
Bipedal
Highly Social
Long Lived
1-6 young
clear vegetation
build out of wood, stone, concrete, glass,
cultivate
redistribute water
air pollutants
organic waste

*Brief review of GIS Projects**

**Interesting idea about the run being a flood plain.**

~Garlic Mustard Project~
What do invasive plants do to the ecosystems they invade?
Take resources
Influence the resources available
Change nutrient cycles
change ecosystem fire regimes
Change the soil microbes.

Garlic Mustard interactions with Native Plants:
Suppress spring ephemeral
may influence nutrient cycling through effects

Allelopathy: Cyanide in its tissues

High Spring photosynthetic Rates?

Urbanization:
high disturbance
high resources
human vectors
urban heat island may promote plant growth

Urban sites should be good environment for invasive.

6 sites: to study.

**Climate change in a microcosm.**

GIS:
More idea of Urban and Rural (very complicated). Data from GIS, with high temperatures (like heat islands)

Putting People On The Map / Global Urban Land Use Trends and Climate Impacts

office-space-sounds-like-someboys-got-a-bad-case-of-the-mondays

 

Anthropogenic Biomes

– Most biomes have been altered by humans. (wow, human dominated Biomes now cover more Earth surfaces compared to wild.)

Existing Biome systems either ignore human interaction or simply into four groups.

-Human interactions on Biomes is often over simplified, but in order to get a global understanding.

-Using Anthropogenic Biomes get a better data set as it divides into 18 groups as opposed to 4, with 3 wild biomes.

80% of human inhabitants live in Dense settlements or villages.  (interesting calculations on mapping, possible question would be to better understand how the information is being process as it seem major areas are considered to be human impacted but in very remote areas. I wonder if this is due to more complex systems like environmental.)

Table 1. Anthropogenic biome descriptions (p 442) good resource for descriptions of biomes.

By using satellite imagery it is fascinating how you can overlay the geographical locations with the implications of human activity. (land cover vs. land use)

Conventional ecosystem model with added human population density and land use:  Ecosystem processes = f(population density, land use, biota, climate, terrain, geology)

Projections though young in development suggest that increased land use is probable.

Conventional Biome systems are not obsolete, however anthropogenic biomes may be more accurate when accounting for human impact on these systems and projections of global trends.

**Interesting in the conclusion**

Human interaction has now become pervasive on what is consider terrestrial biomes. Most of what is considered “nature” is embedded with  anthropogenic mosaics of land use and cover.

 

 Global Urban Land Use Trends and Climate Impacts

2050 70% of the worlds population will live in urban areas. (mostly in Asia)

How these areas develop determine infrastructure needs and energy consumption.

Once these systems are in place they are hard to reverse, and can be problematic depending on where areas are developed.  (This is in relation to climate impacts, like coastal areas and such)

Economy systems seem to be most effected in concerns of human land use trends and climate impacts as areas move from agriculture to manufacturing.

vital for understanding Urban footprint and the effects it has on climate.

 

 

 

 

Mitchell Chapter 5.5

VORTEXII

Another beautiful day in the neighborhood

Selecting Features Inside An Area:

Using this method you basically specify the features and the area desired.

GIS will then check the location and flag the features that are within the area selected.

You can then use a data table to get further information about the features which allows you to summarize attributes associated with them.

This information can be used in several ways:

Examples:

PARCELS

Parcels within a 100-year floodplain.

911calls

Calls to 911 within a group of neighborhoods. In this method it does not distinguish between features, it only shows that it is one of them.

LIQ

Parcels within 500 feet of a restaurant requesting a liquor license.  This example shows how features can be used to see a geological selection with features in a certain distance.

students

Number of student by census block group.  This example highlights data that is already summarized by an area and fully enclosed within its boundaries.

Using the results:

Using GIS to create a report you can then use the information as needed. For our project this could be used to show all the trees that would be in a possible restoration path.

Example: Properties that would be  within 500 feet of a proposed liquor store:

information

There are several statistical summaries that can be used as well:

Count: total number of features inside the area.

Frequency: number of features with a given value or with a range of values inside a given area. This can be displayed as a bar chart or pie chart for easy reference.

Example:

charts

A summary of a numeric attribute:

Based on:

*Sum: an overall total.

*Average (or mean): total of numeric attributes divided by number of features. (reminder that very high/low numbers can skew the average)

*Median: middle range of values.

*Standard Deviation: average amount values are from mean.

Basic concept is that you would show features inside desired area with different colors to highlight the areas of interest. This can be with single attributes (like 100 year flood) or multiple attributes like property types.

Example:

100yr property

Overlaying Areas and Features:

This method allows one to find discrete features inside the selected area and summarize them.

Overlaying areas with discrete features:

This tool is versatile because the attributes are permanently stored in the features data table. With GIS tags each feature has a code for the area it falls within and then assigns the areas attributes to each feature.

In short this allows to overlay different sets of information to get an idea of how they interact.

Example of how this works: pg. 107

Overlay example

*Something to think about when creating a map this way. To show the area that the information is representing think about using brighter colors to show the mapped area surrounded by neutral colors. (for example a floodplain would be more visible than the whole parcel affected by it)

Overlaying Areas with Continuous Categories or Classes:

Much like the aforementioned this uses GIS to summarize the amount of each class or category falling within one of more areas. A good example would be precipitation mapping.

This method uses either Vector or Raster method:

Due to the way that the vector method works there is a chance that you end up with areas called “Slivers”, this is where borders become slightly offset.

GIS provides a tool to automate the process  of merging subsequent calculations into larger adjacent areas.

Important reminder about Raster and Vector methods:

Vector is more a more precise measure of areal extent but can cause more processing due to removal of slivers.

The Raster method is more efficient but can be less accurate.

Examples of results:  (left: single area with multiple categories, right: Multiple areas with single category, not shown multiple areas with multiple categories)

single area with single results multiple area with single results

Overlaying Areas With Continuous Values:

basically if you have an area like elevation GIS can summarize the statistic in each area based on things like mean, minimum value, value range, standard deviation, and sum.