Week 5- Plunkett

Chapter 6:

 

> Domains provide a way for you to constrain input information by limiting the choice of values for a particular field

> Using domains maintains data integrity- does not allow other values to be added during data collection 

 

Chapter 7:

> The process of creating map features from addresses, place names, etc. is geocoding. 

> To geocode addresses, you need an address table, reference data, and an address locator

 

Chapter 8:

> In the first exercise, I created a kernel density to see where areas of high density may occur.

> Kernel density: the density calculated of point features around each output raster cell 

> Temporal data represents a state in time

 

Chapter 9: 

 

> Rasters are composed of a grid of cells instead of x, y coordinates

> Used to define and record geographic phenomena 

> The reclassify tool is used to replace raster cell values with new cell values so that the rasters can be combined

Chapter 10:

 

> Dynamic labels are created when ArcGIS places labels for features in a layer with one click based on predetermined labeling rules.

> Useful for most mapping projects, but label positions can change depending on map scale 

 

Week 4- Plunkett

Chapter 1:

 

> Point, line, and polygon data is also known as vector data 

> Collecting measured values for any location on the Earth’s surface to form a digital surface is known as a raster. 

 

Chapter 2:

 

> .aptx is the typical project template

>.aprx is a project file 

>.ppkx is a project package

> The contents pane allows you to modify a map’s layers 

 

> Learned how to select individual features 

> Learned how to change feature symbols, display feature symbols, use the measure tool, and package my project to share online. 

> Learned how to convert a 2D map to a 3D one

Chapter 3:

 

> An attribute query is a request for features in a table that meet user-defined criteria. 

 

> Using an attribute join operation, we can join the spreadsheet table to the existing attribute table, as long as there is a common attribute field in each table 

> Columns are often called fields.

> Fields include Object ID, which is a unique identifier assigned to every row in a table

 

> A layer file is a saved symbology scheme that points to a specific source datasheet

> A layer package bundles the layer file along with the source data 

> Joining data based on location is a spatial join- this allows you to define a spatial relationship between two layers and combine their attributes in a new output layer

Chapter 4: 

> A shapefile stores geometry and attribute data for one feature

> A geodatabase is a storage container where sets of features are stored into feature classes

> Nonspatial tables do not have well-defined geometry as feature classes do 

 

Chapter 5:

 

> Python is a coding language that is compatible with ArcGIS

> You can define a workflow in the ‘tasks’ pane

Week 3- Plunkett

Chapter 5: Finding What’s Inside 

 

> Finding what’s inside allows you to see whether an activity occurs inside an area or to summarize info. for several areas to compare 

> You can draw an area boundary on top of features, use an area boundary to select the features inside and summarize them, or combine area boundaries and features to create summary data.

 

Selecting features inside the area:

> Good for getting a list or summary of features inside a single area

> Good for finding what’s within a certain distance of a feature

> You need the dataset containing the areas and a dataset with the features 

 

Overlaying areas and features:

> Good for finding which features are in several areas or how much of something is in one or more areas

 

Using the results:

> Most common summaries include the count and frequency 

 

Summary of a numeric attribute:

> Most common ones include the sum, average, median, and standard deviation 

 

Overlaying areas with discrete features:

> The GIS tags each feature with a code for the area it falls within and assigns the area’s attributes to each feature

Vector method: GIS splits category or class boundaries where they cross areas and creates a new dataset with the areas that result. Each new area has the attributes of both input layers

Raster method: When you combine raster layers, the GIS compares each cell on the area layer to the corresponding cell on the layer containing the categories. It then counts the number of cells of each category in each area, calculates the areal extent by multiplying the number of cells by the area of a cell, and presents the results in a table. 

 

Chapter 6: Finding What’s Nearby 

 

> Finding what’s within a set distance identifies the area, and the features inside the area, affected by an activity. 

Things to consider:

> Is what’s nearby defined by a set distance, or by travel to or from a feature?

> Are you measuring what’s nearby using distance or cost?

> Are you measuring distance over a flat plane or using the curvature of the earth?

 

Info. you need from the analysis:

> List: example is a parcel ID and address of each lot within 300 feet of a road repair project

> Count: can be a total or a count by category 

> Summary statistic: can be a total amount, an amount by category, or a statistical summary (standard deviation, average, etc.)

 

Finding what’s nearby:

> Straight line distance: specify the source feature and the distance, and the GIS finds the area or the surrounding features within the distance

> Distance or cost over a network: specify the source locations and a distance or travel cost along each linear feature

> Cost over a surface: specify the location of the source features and a travel cost. The GIS creates a new layer showing the travel cost from each source feature

 

Creating a buffer: 

> Specify the source feature and the buffer distance

> You can save the line as a permanent boundary or use it temporarily to find out what or how much of something is inside the area

> If you have several source features, GIS can buffer each source at the same distance or have it draw a variable distance buffer based on an attribute of each 

> You can also specify several source features and the GIS will create buffers around all of them at once.

> If you want to find features within the distance of more than one source feature, you’ll need to create separate buffers and select the features surrounding each

 

Spider diagram: if a location is near two or more sources, GIS draws a line to each 

 

Creating cell distance ranges: each cell potentially has a unique value. You display the the values using graduated colors so you can see the patterns

> You can summarize either discrete features or continuous data within the distance

> You can limit the area for which the GIS calculates distance by specifying a maximum distance  

 

Chapter 7: Mapping Change 

 

> Geographic features can change in location or change in character or magnitude

> Mapping change in location helps you see how features behave so you can predict where they might move

> Mapping change in character or magnitude shows how conditions in a given place have changed.

 

The geographic features:

> You can map discrete features that physically move, or events that represent geographic phenomena that change location 

> Discrete features can be tracked as they move through space 

> Might be individual features you can map paths for (hurricanes, vehicles, animals, etc).

> Events such as crime or earthquakes can represent geographic phenomena that occur at different locations 

 

Measuring time:

> You can measure time in trends, ‘before and after,’ and through cycles

> If you’re mapping trends, you need to determine the interval, the number of dates, and the duration. The duration divided by the number of dates gives you the interval. 

 

Mapping change:

> Time series: good for showing changes in boundaries, values for discrete areas, or surfaces.

– Good for showing the patterns of individual movement if you’re tracking many features, such as 911 calls over time.

> Showing fewer maps, farther apart in time, may make a change in values easier to see 

> Showing more maps closer together in time may reveal patterns that are missed when using fewer maps 

> It is difficult to compare more than five or six maps at a time

> Tracking map: good for showing movement in discrete locations, linear features, or area boundaries. 

– Good for showing incremental movement of discrete features 

> Linear features are often mapped before and after an event 

> Measuring change: measure and map change to show the amount, percentage, or rate of change in a place. 

Lee L.- Week 3

Chapter 5

    • Mapping what is occurring inside an area is significant for monitoring, so when something occurs out of the ordinary, they know to take action
    • Taking how many areas you have to look inside into consideration, is it a singular area or is it multiple? 
      • Singular areas such as library districts allow you to monitor activity on a smaller scale. 
    • What’s a buffer? I thought I escaped these, but chemistry always finds a way to invade every discipline I’m in
      • Wrong buffer, these ones define a distance around a specific feature, like a stream buffer which is off limits to logging. (Does this mean they can only get so close to it on a map?)
    • Administrative or natural boundary-> parcel or land, watershed
    • Several areas would be contiguous, a prime example of this would be zip codes. 
    • Disjunct-An example of these would be state parks
    • Discrete features: unique and identifiable. Can list and count them as well as summarize them
      • Locations
      • Linear features: roads, pipelines
      •  Discrete features: Parcels 
    • Continuous features represent more seamless and geographic phenomena. 
      • A summarization of features in each area 
        • Spatially continuous categories or classes like vegetative type or range of elevation (SOIL TYPES, I LOVE SOIL).
    • Three ways to find what’s inside
  • Drawing areas or features
        • Visual approach is good for seeing whether one or more features are inside or outside of an area (In or out of bounds)
        • Need a dataset containing the boundary of an area or areas and a dataset containing the features necessary
        • Types: Locations, lines, areas, surfaces (The whole nine yards) 
        • Quick and easy, but visual based only so there is a slack of information from the inside
  • Selecting the features inside an area
        • Getting a list or summary of features inside a single area, or group of areas you’re treating as one 
        • Also good at finding what’s within a given distance of a feature
        • Types: Locations, lines, and areas (No surfaces. One time a guy said a seal was an impervious surface, is this true?)
        • Good for scaling down on information in a singular area, but doesn’t really let you know information in other areas (Only all areas as a whole.) 
  • Overlaying the areas and features
      • Combines area and features to create a new layer with the attributes of both or compares the two layers to calculate summary statistics for each area on the fly. 
      • Finding which features are inside which area, and summarizing how many or how much by area
      • Types: Locations, lines, areas, surfaces (The whole nine yards again)
      • Good for finding and displaying what’s within each of the several areas, but requires more processing 
      • The color palettes for these maps were created by god himself, they’re aesthetically pleasing and honestly are a little reward for reading through this book

Chapter 6

  • This is a thick mama chapter indeed
  • Using GIS can help us find out what’s occurring within a set distance of a feature, and help us find what is within traveling range. 
  • This makes me think of Apple or Google maps a bit, where you rely on the app to help you find things like restaurants, stores, etc. (Usually it tells you most places within a 20-40 mile radius rather than giving you a location to an ice cream place in Wisconsin, unless it is a business name within Wisconsin and that is the only one present in the GPS system.)
  • Totally not a virus. Trust me…im a dolphin
  • I never knew mapping.  I typed this thought out about 7 hours ago and I had no clue what I was going to say. 
  • Wait, I remembered what I was going to say. I never knew that maps had a cost or budget really. I know that there’s a system budget that is more like a resource value rather than a currency oriented cost but this seems like an actual cost.
  • Okay, so cost is more of an aspect like time and a more precise measure of what’s nearby. 
  • Things are adding up in the little brain, does this explain why there are sometimes alternative routes? (other than obvious factors like road construction, etc.) Because sometimes the cost of time isn’t really as valuable to those who aren’t on a time crunch compared to others? (Ex. It takes 1 hour and 35 minutes for me to get home to Cambridge, OH from Delaware, OH. I hate taking the highway so I’m willing to give up that cost of time and take a 2 hour drive home if it means I don’t have to take the highway.) 
  • Planar method: appropriate when area of interest is relatively small (cities, counties, states.) 
  • Geodesic method: larger scale, revolving around the interest in bigger areas like countries, continents, the big momma Earth. 
  • Lots of reiteration in these chapters, also that equation for distance was yucky. 1.5/10
  • Cost layer?? 
    • Reclassify existing layer based on an attribute value. 
    • Creating multiple layers? Combine all the input layers. 

Chapter 7

  • People typically map what’s changed in order to anticipate future conditions
    • Does this apply to climate change? Like those deforestation maps where we anticipate less treeage in an area? 
  • It does, I think. (Flipped to the next page and was violently humbled. :o) ) 
  • We can also look at features that move! Although I find that hard to calculate at the moment unless you’re a meteorologist or a person who monitors natural disasters frequently. 
    • Discrete features: tracked as they move through space. So we can map paths for things like hurricanes or animals. 
    • Linear can track things like the direction a stream is going or the boundary of a fire. 
    • A fun fact about me is I hate Smokey the Bear, if you read this post, ask me why. 
    • When it showed linear range, it made me think of my animal behavior class in the spring when we looked at turtles going to nest and then going to the opposite pole location because of the magnet things in their brains. (So it was technically the right area, but not. AKA, the turtle went to the other side of the island, but was in line with the location it was supposed to nest at. I don’t know how to explain this.) 
    • Natural disasters and crimes represent geographical phenomena that occur in different locations. They are tracked and mapped in a specific instant. 
    • How do we map things in real time? Does that fall under the realm of specific instant? 

The three time patterns

  • A trend-change between two (or more) dates or times 
  • Before and after-conditions preceding and following an event
  • A cycle-change over a recurring time period, such as day, month, or year. 
  • Moth 

Three more ways, but for mapping change

  • Time series 
    • Good for showing changes in boundaries, values for discrete areas, or surfaces. 
    • Create a map for each time or date showing the location or characteristics of features. 
  • Tracking map 
    • Good for showing movement in a discrete location, linear feature, or area boundary. 
    • Create a single map showing locations of the features at several dates and times. (Weather?) 
  • Measuring change
    • Change to show the amount, percentage, or rate of change in a place. 
    • Calculated by difference of amount in a category or in the value of numeric attributes, and display the features based on said values. 

Good stuff John. 

 

Abbey S Delaware Data Inventory

DATA SUMMARY

  • Zip Code
    • Contains all zip codes in Delaware County
  • Recorded Document
    • Points that represent recorded docs in Delaware County Recorder’s Plat Books (how purchased property is divided in an area), Cabinet slides, and Instruments
  • School District
    • Consists of all school districts in Delaware County
  • Map Sheet
    • Consists of all map sheets in Delaware County
  • Farm Lot
    • All farm lots in US Military and VA Military Survey of Delaware County
  • Township
    • Created to identify geographic boundaries of each township in Delaware County
  • Street Centerline
    • LBRS depict center of pavement of public/ private roads in Delaware County
  • Annexation
    • Contains annexation data and conforming boundaries
  • Condo
    • Consists of all condominium polygons in Delaware County
  • Subdivision
    • All subdivisions and condos in Delaware County Recorder’s office
  • Survey
    • Locations of the survey plat
  • Dedicated ROW
    • Shows all dedicated right of way polygons in Delaware County
  • Tax District
    • All tax districts in Delaware County
  • GPS
    • All GPS monuments est. 1991 and 1997
  • Parcels-DXF
    • All parcels in Delaware County
  • Subdivsions-DXF
    • All subdivisions and condos in Delaware County Recorder’s office
    • DXF- kind of vector file (I think)
  • Original Township
    • Original boundaries of townships in Delaware County
  • Imagery 2019
    • Raster layer
  • Hydrology
    • All major waterways in Delaware County
  • Precinct
    • Polygons that determine voting precinct boundaries in Delaware County
  • Parcel
    • All parcels in Delaware County
  • PLSS
    • Contains polygons of boundaries of 2 land survey districts in Delaware County
  • Address Points
    • All addresses in Delaware County
  • 2022 Leaf- on imagery (SID file)
    • Image collection
  • Building outline
    • All building outlines for structures in Delaware County
  • Delaware County Contours
    • File geodatabase
    • 2 foot contours for Delaware County
  • Address Points- DXF
    • CAD Drawing
    • LBRS provides spatially accurate placement of addresses
  • Street Centerlines- DXF
    • CAD drawing
    • Depict center of pavement of public and private roads in Delaware County
  • Building Outlines- DXF
    • CAD drawing
  • 2021 Imagery (SID file)
    • Image collection
  • Delaware County E911 Data
    • Feature Service

Some of these data were self-explanatory, and others required a little more reading.

Definitions:

  • CAD drawing- Detailed illustration using vector/ raster based graphics to create traditional drafts
  • Feature service- Serve feature data  and nonspatial tables over internet
  • File geodatabase- Collection of files that can store spatial and nonspatial data

 

Jocelyn Weaver – Week 5

Chapter 6:

  • Domains provide a way for you to constrain input information by limiting the choice of values for a particular field, helps maintain data integrity
  • Organization – shared online workspace that is tied to your software license
  • Tree inventory map allows urban forest managers ti identify areas in which tree conditions can be poor and prioritize maintenance

Chapter 7:

  • Geocoding- create features from information that describes or names a location, typically an address
    • Address table
    • Reference data
    • Address locator – file contains the reference data and various geocoding rules and settings
  • Buffers are polygons that are created around a feature at specified distances

Chapter 8:

  • Temporal data – data that has a time attribute
  • Hot spot analysis – determines which areas are significant, including areas that are hot and cold and areas that are not significant are white
  • Space-time cube – helps visualize the data, the bins can be viewed in 2 or 3 dimensions and can show patterns of incidents over time

Chapter 9:

  • Cells – raster is composed of a grid of cells, instead of discrete x,y coordinates that define geographic entities
  • Discrete data – shows distinct and discernible regions on a map, such as soil type
  • Continuous data – there are smooth transitions between variations in the data
  • Map algebra – language that combines GIS layers, is fundamental to raster analysis
  • NoData – no values were recorded in cell (not the same as 0)
  • Mask – means of identifying areas to be included in a geoprocessing operation
  • Hillshade – surface layer that depicts shadows to model the effect of an illumination source over terrain of the land
  • Azimuth – the direction of the sun, expressed in positive degrees
  • Altitude – angle of the sun above horizon

Chapter 10:

  • Labels – based on one or more feature attributes and placed near or on a feature
  • Label class – used to specify detailed aspects of how labels are positioned and symbolized
  • Map frames – containers for maps in your page layout
  • Scale bar – dynamic element that provides an indication of the size of a feature and distance on the map

Abby Charlton – Week 5 and Delaware Data Inventory

Here is Chapters 6-10 and the Delaware Data Inventory. The second PDF is a series of maps from the chapters (I do not remember which ones they belong to), and the last maps are from the Delaware Data inventory. Tried to put them into a pdf but the files were all more than 20 mg–click on them or they will be blurry…

Chapter 6-10 and Delaware Data Chapter 6-10 and Delaware Data