Author: mltooill

Chapter 7:

• In this chapter, I learned how to trace, select, and move, and rotate polygons. 
• I learned how to add vertices under the edit tab.
• The lasso tool is used to drag vertices and change the polygon shape, and the split tool is to split a polygon. 
• Creating a polygon: On the Edit tab, in the Features group, click Create. In the Create Features pane, click the desired feature, and confirm that Polygon is selected. On the Configure toolbar, with the Line button active, click to add points and draw a feature outlining the polygon. Double-click the last vertex point to finish the polygon.
• Delete polygons also using the delete button in the edit tab after selecting the polygon you want to delete. 
• Use the trace tool to create a polygon feature: On the Edit tab, click Create, and turn Snapping on. In the Create Features pane, click the layer you want and then the Trace button.
• Use the smooth polygon tool when creating the vertices of a new path. A shorter length will result in a more detailed (or smoother) path but will take longer to process.
• Transforming polygons: Turn off the base map layer. Then with the features you want selected, on the edit tab in the features group, click modify. In the Modify Features pane, click the Transform button. Under transformation Method, click Similarity 2D, and click Add New Links. Then, draw lines from vertices to where you want to move your polygon to. 

Chapter 8:

• Create locator -> put in appropriate fields -> run (geocodes survey data). In the Catalog pane, expand Locators, right-click the layer you want, and click Properties. Click Geocoding Options, and expand Match Options.
• Rematch addresses: In the Contents pane, right-click Attendees, click Data, and click Rematch Addresses.
• Symbolize using the Collect Events tool: Search for the collect events tool, apply settings, and run the tool. 
• Geocode addresses -> fill in fields -> run (converts addresses to geographical locations).
• There was very little in the tutorials for this chapter, mainly just geocoding, looking at attribute tables, and sorting data. 

Chapter 9:

• The pairwise buffer tool dissolves interior lines of overlapping buffers, merging them into a single buffer.
• Buffer rings create concentric zones around input features. (Multiple ring buffer tool).
• This chapter had more spatial join tool practice.
• Making a scatterplot example for this tutorial: In the Contents pane, select Polygons_Tags_Pop. On the feature layer’s Data tab, in the Visualize group, click Create Chart > Scatterplot. In the upper left, above Contents, click Chart Properties. In the Chart Properties pane, for X-Axis Number, click AverageTime; for Y-Axis Number, click UseRate.
• On the Analysis tab, in the Workflows group, click Network Analysis > Location-Allocation. Click the Location-Allocation layer tab. In the Input Data group, click Import Facilities, and apply necessary settings. Click Import Demand Points, and apply necessary settings. In the Travel Settings group, for Direction, click Towards Facilities, and type x amount for Facilities. In the Problem Type group, for f(cost, β), click Exponential. For β, type 0.25, and press Tab. Run the model. For this tutorial, this is how specific pools were located (by cost efficiency).
• Data Cluster Analysis: Multivariate Clustering tool -> apply settings -> run the tool.

Chapter 4-

• Right click on fields in an attribute table to edit and remove them.
• On field view of an attribute table, you can add fields. Be sure to click save!
• Joining a data table to a feature class attribute – Joins and relates -> Join -> Input join field -> Join table field -> Validate -> OK
• Exporting a feature class – Contents pane -> Right click -> Data -> Export features -> Enter relevant info -> Run tool
• Calculating sum of fields -> Fields view of attribute table -> Right click field -> Calculate field (calculating % is same except expressions)
• Creating a query – Map tab -> Selection group -> Select by attributes -> Add clauses
• Aggregating data with spatial joins – Search spatial join tool -> Fill in fields -> Run

Chapter 5-

• State plane coordinate system – livingatlas.arcgis.com
• Could not get shapefile to work. File would not be extracted and uploaded.
• Adding X,Y data -Contents pane -> right-click ie. Libraries > Display XY Data -> Output Feature Class: ie. Libraries -> X field: XCOORD -> Y field: YCOORD -> Coordinate System: Current Map -> Run
• Use the KML to Layer tool to convert a KML file to a feature class
• Not going to lie, couldn’t get half of these chapter 5 tutorials to work so there isn’t much to note

 

Chapter 6-

• Pairwise Dissolve tool – Dissolves block groups to create neighborhoods.
• Select attributes to create a study area, then remove original layer to leave only what you want to see.
• Use Select by Location to create study area block groups
• While holding shift, select different block groups. Then, use export features tool to separate them from the rest of the blocks and remove the original layer.
• Pairwise clip tool is for clipping streets
• Merging water features – Merge tool -> choose inputs/outputs -> run tool -> turn off original water layers
• use the Append tool to add features to an existing feature class, considering that both have the same attributes
• The Union tool overlays the geometry and attributes of two input polygon layers to generate a new output polygon layer aka helps determine area.

Chapter 1- 

• I logged into ArcGIS, downloaded the tutorials, and created a new project. I also learned how to save my projects.
• I learned how to add and remove basemaps, like a street basemap, for example, and I learned what layers are and how to add and remove them (located in the contents pane).
• I learned how to share and export files/maps and I familiarized myself with creating and removing pop ups, as well as zooming in and out.
• I practiced making bookmarks.
• Every vector feature class has an attribute table, and each feature (point, line, or polygon) of a feature class has a record or row of data. You right click on a feature class and select “attribute table.” In the map tab, choose “select by attribute.” On the attribute table, click “show selected records.”
• Right clicking on feature classes, attributes, etc. gives you lots of options to choose. You can sort data in different ways (like ascending and descending), deleting data, etc.. 
• Analysis tab -> tools button -> geoprocessing plane -> toolboxes -> expand analysis tools -> statistics -> summary statistics
• Symbolize features classes by right clicking on one and selecting symbology. Then choose the desired symbol. 
• You can label feature classes on a map by choosing a feature class and clicking on the labeling tab at the top of the screen. 
• In the Catalog pane, expand Maps, double-click the desired 3-D feature. Use the right and left buttons to navigate, or the scroll wheel. You can also press V and the down arrow key to tilt the map and see the 3-D view.

Chapter 2-

• In this chapter, I worked on adding and changing more symbols, like in chapter 1, specifically changing things like color, color scheme, and text size. 
• To remove duplicate labels, follow these steps: 1) Right click the layer under concern and click Labeling Properties. 2) Click Position, then Conflict Resolution. 3) Expand “Remove Duplicate Labels”, then click Remove All. This removes duplicate labels. 
• Why did we use the numbers 4901, 4902, and 4903 for creating a definition query instead of any other ascending numbers? 
• A choropleth map is a thematic map that uses varying shades or colors to represent data values across different geographic regions, making it easier to visualize and compare data distributions. 
• View tab -> convert -> to local scene -> contents pane -> drag feature class in question to above 3D layers heading -> feature layer tab -> extrusion group -> type -> base height -> extrusion group -> field -> select the relevant field.
•  Importing symbology: symbology pane -> import symbology
• Dot density map: go to symbology and set dot density as primary symbology
• Go to the feature layer tab to utilize the visibility range tool. This changes what distance you can see labels at (zoom in and labels disappear, zoom out and they reappear, and vice versa). 

Chapter 3-

• You can use guides in order to place features of a map precisely. Right click on the space you want to add a feature, and make sure that ruler and guides are selected. Then, you can click on the ruler once you close out of that screen and choose “add guide.”
• On the insert tab, you select legend to add a legend. When one legend is selected, you can choose legend items and show properties to display more information on the legend. 
• You can add text for a title and many other things under the insert tab.  
• Data tab -> visual group -> create chart. At the top of the chart properties plane, choose general, and then add a chart title and x and y axis labels. You can adjust color, size, and thickness on these charts. 
• Sharing a map online: Share tab -> share A’s -> web map -> add your name in name field -> fill in other summary info -> under share, choose with everyone -> analyze -> share.
• I logged into ArcGIS Online and found the map that I just shared under my content. On ArcGIS Online, I was able to change features and symbology. 
• The story maps on ArcGIS were pretty cool, I really liked the format of them and getting to create my own. All of the steps were pretty self explanatory and something that I could have done without the tutorial. 
• To create a dashboard on ArcGIS Online, go to the app launcher (9 dots) and select dashboards. You have to apply the settings relevant to the work that you’re doing. 
• On the dashboard toolbar (left side of screen) you can add different elements, like tables. This didn’t work well for me because after I created the tables, I couldn’t get them to show up on the map at all, but they showed up as a separate tab. As I was following along with the tutorial, I should have been able to accomplish this but it did not work. 

Chapter 4- 

• Density maps are used for identifying patterns rather than showing the precise location of something. They are more useful for mapping areas.
• For a density map, densities for a specific area can be represented by different shading or a density surface. You can map the densities of points or lines. You can also map data that is summarized by area. 
• Density of features (number of businesses in an area) or feature values (like how many employees are at each business) can be mapped. 
• Density by defined area can be graphed using dots or density value. Calculating density value- divide the number of features by the area of the polygon.
• Density graphed by a density surface- Created as a raster layer. Every cell in that layer is assigned a density value, which can be found using the number of features within a radius of the cell. This type of graphing gives the most detail, but is the most difficult to make. 
• Which method should you use? 
  • Defined area- when you already have data already summarized by area or when you want to compare administrative or natural areas with defined borders.
  • Density surface- Shows the concentration of points or lines.
• Calculating a density value for defined areas-
  • “Add a new field to the feature data table to hold the density value.” (Mitchell, 2020)
  • “Then, assign the density values by dividing the value you’re mapping by the area of the polygon.” (Mitchell, 2020)
  • “If the density units are different from the area units, you’ll need to use a conversion factor in the calculation to change the area units to the density units.” (Mitchell, 2020)
• Creating a dot density map- 
  • “The GIS divides the value of the polygon by the amount represented by a dot to find out how many dots to draw in each area.” (Mitchell, 2020)
  • GIS places dots randomly within the area. The dots do not actually represent locations. 
• Cell size- determines how coarse patterns on your map will be. 
  • 1. Convert density units to cell units (1 sq. km = 1,000 m * 1,000 m = 1,000,000 sq. m)
  • 2. Divide by the number of cells(1,000,000 sq. meters / 100 cells = 10,000 sq. meters per cell)
  • 3. Take the square root to get the cell size (one side)
• Search Radius- the larger the search radius, the more generalized the patterns in the density surface will be. The smaller it is, the more local variation shown. 
• Contour lines- Contour lines connect points of equal density value on the surface.

Chapter 5-

• Finding what’s inside-
  • Single area- ex. Customers within a proposed sales territory or a service area around a central facility.
  • Several areas- ex. the number of businesses within a group of zip codes.
• Multiple areas- 
  • Contiguous- such as zip codes or water sheds.
  • Disjunct- such as state parks.
  • Nested- such as 50- and 100-year floodplains, or the area within 1, 2, and 3 miles of a store
• In your map, linear features and discrete areas may not all fall inside the set boundary of a map. You can choose to include features only fully in a designated area, only the parts that lie within the boundary, or what partially lies in a designated area. 
• 3 ways of finding what’s inside-
  • One- drawing areas and features. This method is good for seeing whether one or a few features are inside or outside a single area.
  • Two- Selecting the features inside the area. This method is good for getting a list or summary of features inside a single area or areas. It’s also good for finding what is in a certain radius of another feature. 
  • Three- Overlaying the areas and features. This method is good for finding which features are in each of several areas or finding out how much of something is in one or more areas.
• Drawing areas and features:
  • Locations and lines- draw them using a single symbol or symbolize them by category or quantity. After, draw the boundary of the area on top.
  • Discrete areas- (1) Shade the outer area with a light color and draw the boundaries of the area features on top. (2) Fill the outer area with a translucent color or a pattern on top of the discrete area boundaries. (3) Draw the outer area boundary with a thick line, and the discrete area boundaries with a thin line in a lighter shade or different color.
  • Continuous features- Draw the areas symbolized by category or quantity (as a class range), and then draw the boundary of the area or areas on top.
• Selecting features inside an area- 
  • specify the features and the area. 
  • GIS checks the location of each feature to see if it’s inside the area and flags the ones that are.
  • It then highlights the selected features on the map and selects the corresponding rows in the feature set’s data table. 
• The 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.
• The rastor method- GIS compares each cell on the area layer to the corresponding cell on the layer containing the categories. It counts the number of cells of each category within 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-
  • An area of influence is measured by a straight line distance.
  • Travel to or from a feature is measured using distance or travel cost.
  • Travel can be measured over a geometric network, such as streets or deer walking to a stream.
  • Can also measure nearness using time it takes to travel there (ie. through heavy traffic would warrant more time).
  • You can measure distance as the Earth being flat (planar method) or you can use the curvature of the Earth (geodesic method).
  • You can get distance information on several features, not just one. 
  • Inclusive rings are useful for finding out how the total amount increases as the distance increases.
  • Distinct bands are useful if you want to compare distance to other characteristics.
• Using straight line distance-
  • (1) Create a buffer to define a boundary and find what’s inside it.
  • (2) Select features to find features within a given distance.
  • (3) Calculate feature-to-feature distance to find and assign distance to locations near a source.
  • (4) Create a distance surface to calculate continuous distance from a source.
• Centers- Source locations in networks. Usually represent centers that people, goods, or services travel to or from.
• Geometric network- composed of edges, junctions (points where edges meet), and turns. To get accurate costs to travel through a junction, make sure that (1) edges are in the right place, (2) edges actually exist, (3) edges connect to other segments accurately, and (4) there are correct attributes for each edge.
• Impedance value- the cost to travel between the center and surrounding locations for a street segment.
• Creating a boundary-
  • List all individual locations.
  • Get a count of locations in the area covered by the selected segments.
  • Have data summarized by area. ie. you want to total the number of households per census block to find out how many households are within a 15-minute drive of a recycling center.
  • Get a list, count, or amount for linear features or areas, ie. the total length of salmon streams within a half-hour drive of the town.
• “You can limit the area for which the GIS calculates cost distance values by specifying a maximum cost. The GIS stops calculating cost distance when all cells within the specified cost have been assigned a value. Any remaining cells are not assigned a value on the output layer. If you don’t specify a maximum cost, the GIS calculates a value for all cells in the study area” (Mitchell, 2020). 

This week, I read chapters 1-3 of the Esri Guide to GIS Analysis by Andy Mitchell. Here are some of the key takeaways from each chapter:

Chapter 1-

-GIS analysis looks at geographic patterns and relationships between features.
-Start analysis by deciding what information you need. How will the analysis be used and by who?
-The type of data and features present determines what method of analysis you use. You may need to create more data depending on what information you already possess.
-By looking at the results of your analysis, you may decide that you need different parameters than the ones you started with because the information they provide may or may not be useful.
-Discrete features- “For discrete locations and lines, the actual location can be pinpointed. At any given spot, the feature is either present or not.”
-Continuous phenomena- like precipitation or temperature. Can be measured anywhere. They happen across the entire area being observed.
-Features summarized by area- “represents the counts or density of individual features within area boundaries.” Examples include the number of businesses in each zip code, the total length of streams in each watershed, or the number of households in each county (obtained by summing the number of households in each census tract). The data applies to an area, but with no specific location.
-Geographic features can be represented by either vectors or rasters. A row in a table with x and y locations demonstrates a vector, while a raster is represented by a matrix of cells in a continuous space.
-Discrete features and features summarized by area are typically represented using vectors and continuous phenomena are usually represented by both, and continuous numeric values by raster.
-Types of attribute values- categories, ranks, counts, amounts, ratios.
-Categories are types of similar things like roads or crimes. Not continuous
-Ranks put features in order, like when direct measures are hard to quantify (when several things factor in), such as scenic value. Not continuous
-Counts and amounts show total numbers. A count shows the actual number of features and amount can be any measurable quantity within the represented feature. For example, a count would be the number of businesses and the amount would be the number of employees each business has. continuous
-Ratios show the relationship between two quantities, such as the average number of people per household. Continuous
-When working with data tables, you are commonly summarizing values of attributes, calculating attribute values, and selecting features.

Chapter 2-

-Preparing data- make sure that coordinates have been given to each feature you are mapping and make sure that you have a category attribute with a value for each feature as well.
-If you have data that is already in the GIS database, then you do not need to assign coordinates because they are already given to you. However, if you have brought in data from another program or if you are entering it by hand, then you need to assign geographic coordinates by filling in information such as a street address, or latitude–longitude values, which will allow the system to assign geographic coordinates.
-You may need to add information (code) to each feature that identifies its type.
-In order to add a category, a new attribute must be created in the layer’s data table. Then, you have to assign values to each feature.
-“In some cases, a single code indicates both the major type and subtype. For example, all crimes with a value between 500 and 599 are burglaries, but the type of burglary is indicated by the specific value.”
-Mapping a single type- draw all features as the same symbol.
-Using a subset of features- Book uses the example of mapping all crimes, as well as specifically all burglaries, or only commercial burglaries.
-Mapping by category- draw features using different symbols. The book gives an example of mapping all major roads by road type.
-Displaying features by type- Book uses the example of mapping burglaries by the type of building entered (residential or commercial) or by the type of entry (forced or non-forced).
-Do not display more than 7 categories. Most people can distinguish up to seven colors or patterns on a map. Displaying any more than 7 makes a map harder to read and patterns harder to find.
-Grouping categories- If you have more than 7 categories, group them.
-When using symbols, colors are easier to distinguish than shapes.
-Mapping reference features also make a map easier to understand and read.
-Zooming out may help you distinguish patterns.

Chapter 3-

-Mapping patterns of features with similar values shows where the most and least are. This is important for finding places that are in critical need of action.
-Continuous phenomena are typically mapped as shaded areas to show quantity.
-A count is the actual number of features on the map.
-An amount is the total of a value associated with each feature.
-Using counts and amounts when summarizing areas can mess up patterns that you’re trying to discover.
-Ratios show the relationship between quantities. They are created by dividing one quantity over another. (most common are densities, proportions, and averages).
-Ranks put features in order (high to low). They give relative values instead of precise ones.
-Grouping values into classes helps audiences to compare features quickly.
-To create classes, you can do so manually or by using a standard classification scheme. These methods assign the same symbol to different features to group them.
-A class break is where there is a jump in values (between bars).
-Understand quantiles, standard deviation, and natural breaks, and equal intervals.
-Using natural breaks can isolate outliers and avoid skewing your patterns.
-GIS gives these methods for creating maps to show quantities: Graduated symbols, graduated colors, charts, contours, and 3D perspective views.
-Discrete locations or lines, use- Graduated colors or symbols to show value ranges, charts to show both categories and quantities, and a 3D view to show relative magnitude.
-Discrete areas or data summarized by area, use: Graduated colors or symbols to show value ranges, charts to show both categories and quantities, and a 3D view to show relative magnitude.
-Spatially continuous phenomenon, use: Graduated colors to show value ranges, contours to show the rate of change, and a 3D view to show relative magnitude.

My name is Megan Tooill and I am a junior. I am majoring in zoology, environmental science, and environmental studies, and I play softball here at OWU.

After taking the GEOG 291 quiz, I read Chapter 1. This chapter focused on introducing what GIS is by differentiating between GIScience and GISystems. It defines GISystems as an answer to “what” and “where” with practical applications, like mapping, spatial analysis, and data management. In contrast, GIScience is defined as an answer to “how,” specifically how do we know what we know and how to validate the information that has been displayed. With this differentiation, the chapter describes how GIS developed as an outcome of both social and technological developments, arising as the need for better data and visualization methods increased. Schuurman discusses how GIS initially emerged from military, government, and scientific needs, but it has since evolved into a versatile tool used widely in fields such as urban planning, environmental management, and public health. Its rise coincides with broader cultural trends toward visual data, digital decision-making, and the increasing reliance on technology to solve complex problems.

GIS increases accessibility to people and better communicates information because, according to recent studies, people tend to “reason” more effectively using imagery rather than numbers and texts alone. This highlights how maps not only display information but also actively influence decisions and shape perception. Schuurman challenges the common assumption that maps are neutral representations of space and claims that GIS is inherently ideological. Depending on how models are created, they can emphasize different aspects of a specific space. The creator of the model decides what information they want to portray and how to present it, a process known as ontology, which inevitably removes complete objectivity. This makes GIS a powerful tool, but also one that requires critical awareness of its limitations and biases.

One application of GIS that I found was for determining heterogeneity in disease distribution. In other words, how diseases vary and appear throughout a population. Using GIS can link disease processes and explanatory spatial variables to find ways to combat the spread of disease. A second application of GIS that I found designated critical habitats for endangered and threatened species. Using GIS helps create an image of what regions are in need of the most help and emphasizes the severity of problems associated with loss of biodiversity.

Fig. 1. Critical habitat areas for endangered and threatened species. Red depicts the most important areas to conserve, while green depicts areas that are of less concern. 

Work cited: 

FLETCHER-LARTEY, S. M., & CAPRARELLI, G. (2016). Application of GIS technology in Public Health: Successes and challenges. Parasitology, 143(4), 401–415. https://doi.org/10.1017/s0031182015001869 

Sabesan, A. (2018, March 4). Aarthy Sabesan publishes article on spatially designating endangered and Threatened Species – BSC Group. BSC Group – Shaping New England’s future together. https://www.bscgroup.com/news/aarthy-sabesan-publishes-article-spatially-designating-endangered-threatened-species/