Geography 291: Geospatial Analysis with Desktop GIS

Chapter 1:
At the beginning of chapter 1, the author goes over the uses of GIS and spatial analysis. They discuss that using GIS gives the viewer a unique view of data that can be seen in correlation to geographic features. Modern GIS is host to a swath of information and collaborators that allow for real-time interaction among a large group of people. The Open Data movement has grown in the GIS field from where it took a few specialists to make a map to now anyone can make a map due to the data available. The only data that is being protected is copyrighted or private but primarily all data that is needed is open to anyone who needs it. Then the chapter goes into information that has already been covered in the previous books such as vector or raster maps and attributes. In ArcGIS Pro projects are the spaces that contain your work, in these spaces, you can view multiple maps. Geoprocessing is the tool that is used to do your spatial analysis within ArcGIS Pro. The tutorial in this section gave a general overview of some of the features in ArcGIS and showed use cases such as accidents related to public schools.

I originally started this out by doing a summary for every chapter then I realized that was kind of dumb overall since there is not enough to cover in each chapter. After chapter 1 the book focuses on giving the reader practical uses for ArcGIS Pro. Chapter 2 main goal seems to be to introduce some of the basic features when looking at and manipulating a map in the program. None of the chapters deals with data analysis but rather spatial analysis on a basic level. Chapter 3 starts with a more advanced spatial analysis by removing unnecessary data but then turns in more of the data analytics side of ArcGIS Pro by creating new data sets and adding data to tables. Chapter 4 focuses on how to combine spatial analysis with data analysis, and also shows some basic ways it may be used in real scenarios. Much of chapter 5 is associated with how to streamline processes that you may be doing multiple times in an analysis.

These chapters showed how ideas or concepts in the previous book can be applied to the ArcGIS Pro software. Much of what is happening in these chapters is to show normal or common steps or processes used in GIS analysis to have a basic understanding of these processes. At times I think this book lacks some explanation or practical understanding of some tasks which is partly due to the quickly updating software the book is based on but beyond that none of the tasks were too difficult.

PS: Tell people to read the preface to get the Geospatial scenarios (I did not know about this until Thursday)

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Getting To Know ArcGIS by Michael Law and Amy Collins

Chapter 1: Introducing GIS

Notes and Comments

• A GIS is composed of five interacting parts that include hardware, software, data, procedures, and people.
• Spatial data—…information that represents real-world locations and the shapes of geographic features and the relationships between them—involves using coordinates and a suitable map projection to reference this data to the earth (e.g., the location of a hospital).
• Attribute data—information about spatial data (e.g., information about the hospital).
• Dynamic and interactive maps on the internet, known simply as web maps, are ideal for allowing many users to access and quickly locate features and visualize data.
• The open data movement provides agencies and the public with authoritative data and enables all levels of government to develop new tools and applications.
• Point, line, and polygon data is also called vector data.
• Features of the same type—such as trees, roadways, or buildings—are grouped together and displayed as layers on a map.
• You can record and collect measured values for any location on the earth’s surface to form a digital surface, also known as a raster.
• ArcGIS Pro uses ArcGIS Online basemaps, which provides a backdrop or frame of reference as you add your own layers.

Exercise Notes and Screenshots

• Pay attention to the names of each subject—some of them are very similar.

Getting To Know ArcGIS by Michael Law and Amy Collins

Chapter 2: A first look at ArcGIS Pro

Notes and Comments

• It offers 2D and 3D visualization and analysis within an intuitive, easily navigable interface

Exercise Notes and Screenshots

• Using a project template (.aptx) is usually the quickest way to start a project. Templates are shareable project packages, including the specific basemaps, connections, datasets, toolboxes, or add-ins that are most helpful for your project.
• The countries with the highest PM concentrations are Uruguay, Angola, Sudan, Chad, Niger, Mali, Iraq, Egypt, Pakistan, and Bangladesh.
• If the content pane is missing, I utilize the search bar to return it.
• The city with the largest population is Shanghai, China.
• Symbology refers to the way GIS features are displayed on a map.
• Single symbol—one symbol is used for all features in a layer.
• Unique values—used for categorical data, different symbols represent various attributes.
• Graduated colors—used for quantitative data, different colors represent different value ranges.
• Graduated symbols—used for quantitative data, symbols increase in size with increased values.
• The height of the tallest building is 339.8 meters.
• Extrusion is the process of stretching flat 2D features vertically so that they appear three-dimensional.

Getting To Know ArcGIS by Michael Law and Amy Collins

Chapter 3: Exploring geospatial relationships 

Notes and Comments

• The power of GIS extends far beyond exploring digital maps. You can combine datasets, enrich them with new attributes, derive statistics from them, and obtain new information based on their relationships.

Exercise Notes and Screenshots

• The field name that indicates the state within which the county features are located is “STATE_NAME.” In Wayne, Ohio there is 10,575 people between the ages of 22 and 29 years.
• Definition queries are helpful when you want to work with a subset of data in a map while maintaining the source data.
• Attribute query—a request for features in a table that meet user-defined criteria.
• Using an attribute join operation, you can append the spreadsheet table (the join table) to your existing attribute table (the input table), provided you have a common attribute field in each table—for instance, a feature name or numerical identifier.
• I cannot find the years of data that are represented in the table.
• There are various classification methods:
  • Manual interval classification, equal interval classification, defined interval classification, quantile classification, natural breaks (jenks) classification, geometric interval classification, and standard deviation classification.
• I was not able to verify a correlation between income and 2010 obesity. I believe I messed up with importing symbology from 2009 to 2010.
• The percentage of households that had income of less than $15,000 per year is 17.7%.
• There are 13,115 food deserts in Knox County.
• A spatial join allows you to define a spatial relationship between two layers (a target layer and a join layer) and combine their attributes in a new output layer.

Getting To Know ArcGIS by Michael Law and Amy Collins

Chapter 4: Creating and editing spatial data

Notes and Comments

• A shapefile is a simple, stand-alone data format. It stores geometry and attribute data for one set of features.
• A geodatabase is a storage container, in which sets of features are grouped into feature classes. The geodatabase can also store rasters and special geodatabase elements that facilitate capabilities that are not available with other data formats.

Exercise Notes and Screenshots

• A coordinate system defines features’ positions on the earth’s surface.
• A geographic coordinate system uses latitude and longitude to define the locations of points on the surface of a sphere or spheroid.
• A projected coordinate system uses a mathematical equation (the map projection) to transform latitude and longitude coordinates into Cartesian or planar coordinates for display on a flat map.
• ArcGIS employs on-the-fly projection, which means that it applies the projected coordinate system of the first layer added to all subsequent layers.
• Metadata is textual information about the dataset.
• An attribute domain is a set of valid values, or a numerical range, to which attributes in each field must be limited.
• Snapping allows you to accurately connect features, such as waterlines and values, without impossibly precise sketching.
• There are four vertices on SW 19^th
• The Shape_Area value of the original water pressure zone split in half.

Getting To Know ArcGIS by Michael Law and Amy Collins

Chapter 5: Facilitating workflows

Notes and Comments

• A task item might capture an entire workflow or one piece of a more complex solution.
• Modelbuilder is a geoprocessing environment that allows you to easily link one tool to another and run a set of operations one after another with the click of a button.

Exercise Notes and Screenshots

• Tasks are helpful to standardize business operations and promote best practices for a repeatable workflow.
• Yes, I can name the types of conflict events that are recorded in this dataset.
• A definition query limits the display of features to features that meet user-defined criteria.
• According to ACLED statistics, 14,211 fatalities resulted from conflicts against South Sudanese civilians between 2010 and 2018.
• A model allows you to string multiple geoprocessing tools together and run them automatically with the click of button.
• There were 71 fatalities that resulted from conflicts classified as violence against civilians in Rwanda from 2010 to 2018.
• There were 41 events classified as riots/protests that occurred in Rwanda between 2010 and 2018. As a result of these events, there was 12 fatalities.
• Python is a programming language that, in the GIS context, is used to script geoprocessing workflows and build custom geoprocessing tools.
• The two geoprocessing tools that are combined in this script are Select and Summary Statistics.
• There were 26,323 fatalities that resulted from conflicts classified as violence against civilians in Nigeria from 2010 to 2018.

Chapter 5:

This chapter starts with explaining how to classify specific areas of interest as well as the types of data inside these distinct boundaries. The book gives three types of methods for mapping such phenomena: drawing the area and features, selecting the features inside the area, and overlaying the areas and features. Each are used when specific reasons for mapping or types of data are present. For example, you would want to overlay the areas and features if you wanted a display of all the types of features in many different areas as well as if you had a single area but are dealing with displaying continuous data values. Then, the types of ways that these data or features inside the areas can be displayed was discussed. It talked about how counts, frequencies, and numeric statistics like the means and medians of data can be used to classify how much data is in each area of discussion. Within their explanation of how overlapping data can be displayed, I found it very clever how they were able to overlap a color scale of workers in specific areas with a floodplain by using a transparent type of blue on top of the different shades of orange and red. When they mentioned the two different types of methods of overlaying areas on areas (vector and raster) I was and still am a bit confused on what causes slivers in the vector method. It defines them as small areas where the boarders get slightly offset when overlaying areas, but I am confused how this occurs, as I would assume that the only way this might occur is if the data itself is accurate only within a specific area, and thus if two areas have boundaries that are close enough to each other to make a zone that is ambiguous, that would be a sliver, maybe. Finally, I really like the idea of using histograms to supplement multiple types of data in a single area, which makes comparing the different types of data a lot easier than just having the key to show which values are what.

Chapter 6:

Measuring how close something is by cost is very unique; I did not really think that this was a valid way of measurement, but it does have its uses. Travel cost is a real concern for many people to get from one place to another, but it can vary from person to person (because cars and milage and traffic and stuff). Also, the distinct bands comparison method for distances is really neat too, having ring values within a specific ring arc distance to display the count of specific data is a cool way of displaying it. Personally, I really do not think of distance areas in terms of within, let’s say, 1000-2000 feet in a ring, so this type of display is really interesting. Cost over a surface is one method of finding what is nearby that they explained, and I think that it has some really unique applications, especially with terrain. You would have to need extremely specific raster data of how certain terrain is easier or harder to traverse, indicating that harder terrain will be less cost effective to traverse than the ladder. Spider diagrams are quite the useful tool in determining the relationships and rough distances of two objects from two or more source points in a spiderweb-like formation. Setting travel parameters when using cost as a measurement is shown to be quite tricky, as there are many external factors and assumptions that are needed be made to determine cost quantities. When dealing with time, estimated traffic, turns, and speed limits must be made very precisely and made into a formula to determine how fast or slow a specific road route is. These types of assumptions are also made when creating cost layers, which can give impressions on the ease or cost of moving or building on specific land is by the specific qualities of the land being surveyed.

Chapter 7:

Mapping change is something that I did in GEOG 122 (whooo) which is super awesome for the cross-ciriculumativity! Mapping areas or things that do not change in location is what I am familiar with (being the changing populations numbers of counties in a state by decade), but mapping moving data like the path and speed, or size of a hurricane is a whole different ballgame than from what I am used to.  The time patterns that are commonly used when displaying change are trends, before and after, and cycles. Time can also be summarized by grouping events that happened in timely proximity to each other together. These can be displayed in cyclic patterns like in the use of many different versions of the same area, denoting the time differences, and also with discrete data by using point locations and different colors to describe the different times of day/year that the events happened at that location. The three specific ways that mapping change can be done is by a time series, tracking map, and measuring change. Tracking maps are really neat as they show the spread of movement of data from an initial start area to newer area boundaries denoted by time. Additionally, measuring change by denoting the amount, percentage, or rate of change is something that I remember doing very briefly in Human Impacts on the Environment. We did color compositions of land data and had to denote changed land with specific colors kind of like the map in the book concerning the change in forest cover after a hurricane, except our map was full of color and every area was assigned a specific label in the color composition. A more similar representation to what we did was like the book example of land cover change in 1914 vs 1988, where the whole map is covered in data categories.

Chapter 5: In this chapter the book really explained how to define a map and how to show the information on the page. The three main things that I got from this was showing a clear boundary, a dataset to show your information and visual appeal which makes it easier for the reader to understand the information on the map. By initially creating a boundary you are then able to find what you are trying to portray whether it is showing information through a data set or physically separating areas based on aerial visuals. In order to show data or try to show the people an issue in the area there needs to be clear data that counteracts the claim of the map. The book uses land cover as an example for one of their maps, you can either separate this the different land uses by acquiring data with locations of areas or if you know the area you can separate and boundary off areas as you see fit. The map using the data would be more precise but I believe one that is separated by humans would have more effect on the people. I say this because the information would be through human experience and they are able to see the use of the land including whether it is a healthy area or not. The data would not be able to do this because it would just be in numbers and locations, there is no human interaction with the data or thought put into their separation. So by creating boundaries around the outside of the map you are able to identify an area then by using data or general knowledge you can create a map to put purpose to the information being portrayed inside. 

 

Chapter 6: I would say this chapter is almost the first chapter that really explains some of the features you can use in ARC. The chapter explained the process of finding a location and what information needs to be available for the software to accurately measure an area. The main point from this part is the fact that you need to have two separate layers one being the source layer and one being the surrounding layer. This means the source layer is the map that you are physically creating and the surrounding layer is the map that you are going to measure off of. The book says that by being able to measure distance you can find the square footage of an area, the distance from point A to point B and you can even create routes for cars and transportation by using this surrounding layer. The surrounding layer is something like google earth, an image that does not have the best resolution which is why the source layer will have the better resolution. Because the google earth map is linked to the correct coordinates when you measure on the source map the measurements will be precise. By being able to have this supporting layer underneath the map that you are creating you are also able to have an image surrounding the study area so people can find landmarks that they know of when creating the map. 

 

Chapter 7: This chapter was really about the different ways you can show data on your maps and how to show data over time and or any changing data. I would say the most important part of this chapter would be the fact that you can show several time periods in one map because you are able to link the data to the map. Being able to create time scale maps you are then able to show people in a short video or gif what is going on in a certain area like, population change, hurricane surge times and even wildfire spread over a several day period. This is a great way to inform the people because you can show them what has been happening in the last couple of years and or even show them the danger they could be in during a natural disaster. There are also ways that you can create singular point time maps which can show things like 911 call locations and their timestamps. These point maps are also very helpful when tracking oil spills, wildfires and really any danger that spreads due to the fact that points would be put on a map for the time the spread reaches that location. These maps can show anything from population change to land use change to vegetation change. All of this information would be linked to data which allows the maps to also show graphs and tables as needed. These tables and graphs can show the change to people in numbers so instead of just showing them with images which can broaden the audience of the map. 

 

Chapter 5

Chapter 5 is concerned with defining and analyzing what’s inside of the areas you’ve created using ArcMap. To begin, the chapter discusses defining analysis, specifically how many areas and what features are inside the areas. If you were to select a single area, you’d be focused on a specific, controlled area which could be something like a manually drawn territory or a natural boundary. Multiple areas would pertain to zip codes, disjunct parks or counties. Then, you have to determine if the features are discrete or continuous, where discrete are unique, identifiable features and continuous are seamless geographic phenomena, either spatially continuous or continuous values. Then, you need either a list, count or summary. With this step, you also need to determine if your values can be partially inside or outside of the boundaries, and how you want to quantify them. The chapter then discusses the three methods of finding what’s inside. These are drawing areas and features (which are good for finding out whether features are inside or outside an area), selecting the features inside the area (getting a list or summary of features inside an area) and overlaying the areas and features (good for finding which features are inside which areas and summarizing how many or how much by area). When you’ve selected features in the area, you can visualize results by count, frequency, or a summary of numeric attributes, using either mean, median or standard deviation. The chapter then finishes with how to overlay areas and features. First, overlaying areas with discrete features then overlaying areas with continuous categories or classes, where GIS tags each feature with a code or the area it falls within and assigns the area’s attribute to each feature. Second, overlaying areas with continuous categories or classes, where GIS uses vector or raster method to overlay areas with continuous categories or classes. Lastly, Mitchell mentions overlaying areas with continuous values, where GIS finds out which cells fall within each area and calculates the statistic for the characteristic you’re interested in and assigns the value to each cell it’s identified.

Chapter 6

Chapter 6 moves on to finding what’s nearby. A theme I’ve caught on to with these chapters is that Mitchell always wants to start with defining analysis. For this chapter, he talks about measuring what’s near whether it’s by set distance or travel to feature, cost or distance, or distance over flat plane or using earth’s curvature. Then, he asks us for the necessary information, meaning list, count, summary, distance or cost ranges, specifically inclusive rings or distinct bands. Mitchell goes further with defining three ways of finding what’s nearby. Straight line distance (good for creating a boundary or selecting features at a set distance around a source), distance or cost over a network (good for finding what’s within a travel distance or cost of a location), or cost over a surface (good for calculating overland travel cost). For straight line difference, you can either create a buffer to define a boundary and find what’s inside, select features to find features within a given distance, calculate feature-to-feature distance to find and assign distance to locations near a source, or create a distance surface to calculate continuous distance from a source. For measuring distance or cost over a network, you first specify the network layer, assign street segments to centers and set travel parameters. You can also specify more than one center and select surrounding features to be included in the map. Lastly, with calculating cost over a geographic surface, you begin by specifying the cost (where GIS totals the cost as it crosses each cell from the source, assigning a cumulative cost to each cell in a new layer it creates) and then modify the cost distance.

Chapter 7

The book finishes with mapping change, where we once again define our analysis. Mitchell mentions two types of change: change in location (seeing how features behave so you can predict where they’ll move) and change in character or magnitude (showing how conditions in a given place have changed). The type of features you choose to map also matter. They can either be discrete (physically move) or change in character or magnitude (events that represent geographic phenomena that change location). Additionally, you have to quantify time. It can be a pattern (trend, before and after or cycle) or partition (two or more times or dates or several time periods). Once you’ve determined this, you have to decide what you want to take away from the analysis. It can be how much it has changed (talking about change in magnitude or percent change) or how fast it changed (measuring the rate of change over time). There are three ways of mapping this information. The first is a time series, showing changes in boundaries, values for discrete areas or surfaces which is good for movement of change in character. This is good for strong visual impact, but readers have to visually compare the maps to see where and how much a change has occurred. The second is a tracking map, good for showing movement in discrete locations, linear features or area boundaries. This makes it easier to see movement and rate of change especially when subtle, but can be difficult to read if there are more than a few features. The third is measuring change, showing the amount, percentage, or rate of change in a place which is good for change in character.  This will show actual difference in amounts or values, but doesn’t show actual conditions at each time and is calculated only between two times.

Chapter 5

This Chapter of Mitchells, The ESRI Guide to GIS Analysis, focuses on “Finding What is Inside” of the image you are looking at. Sometimes, you only want to focus on a singular part of the image. Say for example, you have a map of types of agriculture in Ohio, but you only want to focus on Northeast Ohio. You can choose to only analyze a single area in order to get the full picture. You can also section your analysis based on things like county lines, and zip codes. You can also make this analysis discrete or continuous, like Mitchell discussed in earlier chapters. There are three ways of finding what’s inside. By 1, drawing areas and features, 2, selecting the features inside the area, and 3, overlaying the areas and features. Drawing areas and features is good for finding out whether features are inside or outside of the designated area. However, this method is not very specific, and often cannot provide the information needed for a full analysis of the map. Selecting the features within the area is good for summarizing the features inside, but it is only good for evaluating one single area, not a collection of larger areas. Overlaying the areas and features is good for finding out which features are inside, and how dense these features are. However, this process is quite extensive, and requires more processing. Mitchell also describes how it can be good for evaluating the data if layers are overlapped with discrete and continuous data. For example, you could have the discrete layers of land plots overlap with a floodplain. We can directly see which areas are being impacted. We can also do it inversely, by mapping continuous data of types of land, and over laying boundary lines over it. With these overlapping boundaries, you can then get a list of attributes of a given area within the image, whether its number of people, number of species, density of population, etc. We can overlay boundaries in GIS using either a vector or a raster model to ensure that all variables are both together in an image and sorted separately. The vector model is almost the overlaying of 3 separate images mapping different variables, and putting them all together. The raster model is the sort of “cookie cutter” image going into a figure to display the area of interest. 

 

Chapter 6 

This Chapter of Mitchells, The ESRI Guide to GIS Analysis, focuses on “Finding What’s Nearby”. This is useful for knowing what is in the general area of the location you are concerned with, and if surrounding areas could be impacted by what you are surveying. For example, we could look at nearby floodplains that are near a body of water that are at risk of floods, or houses near intersections of the highway that could be susceptible to effects of eminent domain. Measuring how near something is can be used in distance, or in cost, or “travel costs”. If something is very far away from the desired location, things like heavy traffic and gas prices could be a barrier of distance. For example, if you are mapping how close streets and homes are to a fire station, the streets that are within ¾ of a mile, and are within a 3 minute drive of the fire station represent very different parts of the town. You also need to account for the size of the area you are looking at. For smaller areas, you can look at this on a planar method. But if you are looking at something larger like a continent or the world, then you need to use a geodesic method, based on the curve of the earth. You are able to summarize what is within this nearby area and turn these variables into quantified data as well. You should use the straight line distance method “if you are defining an area of influence or want a quick estimate of travel range”.  You should use the cost or distance method if you are “measuring travel over a fixed infrastructure to or from a source.” You should use the cost over a surface if you are measuring overland travel. It is also helpful to use color coding legends in the figure to depict the distance from the point you are evaluating. 

 

Chapter 7 

This final chapter of Mitchells, The ESRI Guide to GIS Analysis, focuses on “Mapping Change”. This section specifically focuses on how to represent data of change over time, and how the characteristics of the area change as time progresses. An example of this, could be a representation of sea level rise over time. The first image that you show might depict sea levels in the 1950s, and then sea levels today, and then where sea levels are expected to be in the coming decades. A large reason for this according to Mitchell is to “anticipate future needs” and to “gain insight on the behavior of a certain event or region”. You can also use mapping change to show how a certain object or thing is moving locations over time – an example of this might be a representation of how the migration patterns of certain bird species are evolving due to the changing climate and weather patterns. This might show us two completely different regions of the world, but is still mapping the change in some variables. You can represent a change in a figure through three different types of time patterns: a trend – a change between two (or more) dates and times, before and after – conditions preceding and following an event, or a cycle – change over a recurring time period such as a day, month, or year. However, you do not want to use too broad of a time frame, nor do you want to use too many data points of comparison, because the main difference between the change in figures might be lost, and the message of the data may not be as clear as you desired. Mapping the change in a set of data is very important in order to understand how we are evolving, and what the trends are for future expectations.

Chapter Five:

Chapter five focuses on mapping what’s inside a particular area. In the broad spectrum of things, this idea of mapping what’s inside seemed a bit irrelevant to me, but the chapter made it seem very important. People map what’s inside an area to monitor or to compare several areas to each other. It becomes easier for people to know whether to take action by observing what’s occurring in a region. The chapter also mentions that the first thing that we need to do is define our analysis and identify the type of our data. We can choose a single area or multiple areas for analysis. I think in places like India, where areas are divided into multiple sections(like pavements), it might be easier to get started with a single one and then move to multiple regions. Multiple areas include continuous (geographic phenomena) and discrete(unique, identifiable), like zipcodes and state parks. The mathematical terms, like list, summary, and count, used in Chapter three were also mentioned here as a way to use GIS to analyze information. Another thing the user can choose is whether to include features that fall completely outside/inside or partially a part of the area boundary. We can use GIS to overlay the protected area and the land cover areas.

Mitchell mentions the three ways of finding what’s inside, namely:

• Drawing areas and futures.

• Selecting the features inside the area. 

• Overlaying the areas and climate. 

Initially, each one of them is divided into their pros and cons using the compare table shown in chapter three. The chapter then elaborates on these three types throughout till the end and how they are related to discrete features. frequency, count, and how their results can be used. 

 

Chapter Six: 

 

Chapter six focuses on what’s nearby. Similar to chapter five, it goes in on the importance of certain aspects of geographic locations. GIS helps find out what’s occurring within a set distance of a feature. It helps identify the area and the elements inside that area that are affected by an event or an activity. Finding a traveling range which is measured using distance, time, or cost, helps define an area served by a facility. The chapter starts by asking the reader to define their analysis and identify their type of data. The author mentions that it’s also essential to choose if “what’s nearby” is set by distance or some other range. Distance is one way of deciding nearness, but it can also be measured using cost. In my mind, the word cost is always associated with money, but here it is used for time. One of the interesting things mentioned in the textbook is choosing whether to use a flat plane or use the curvature of the earth. 

The terms list, count, and summary from chapter three were mentioned again here to help the reader choose the best method of analysis. Distance and cost can be single or multiple ranges. Multiple ranges can either use inclusive rings or distinct bands. Like chapter five, There are three ways to find what’s nearby: 

• Straight line distance — Specifying the source feature and distance
• Distance or cost over a network — Specifying the source locations and a distance or travel cost along each linear feature. 
• Cost over a surface — Specifying the location of source features and a travel cost. 

The pros and cons are also mentioned to compare the methods and choose whatever is best for the reader. These three types were then further elaborated throughout the end by mentioning their subtypes and instructions, how GIS can be used for this, and how the result obtained can be analyzed. To me, this chapter was heavily similar to chapter five in the way it was structured. 

Chapter Seven:

Chapter seven focuses on mapping the change. Mapping change is very important as it helps find predictions that can be further used to take action. My TPG Draft Proposal Project for ENVS110 was based on predicting change(flood risk), so additional policies could be made to protect marginalized communities. To define the analysis, we need to understand the types of change. Geographic features can change in location or magnitude. Change in the location usually helps us see how features behave so we can predict where they will move next, for example, by forecasting hurricane patterns. Change in magnitude helps understand how conditions in a particular place have changed, for example, to observe land cover or vegetation in an area. Knowing the type of feature also helps choose the best method for mapping. There are two types of features — features that move and features that change in character or magnitude. Discrete features that can be tracked as they move through space and events that represent geographic phenomena are the two subtypes of moving features. Discrete features that change in the quantity of an attribute associated with them, Data summarized by areas that are quantities are associated with features within a defined area, Continous categories that show the type of features in a place, Continous values that are continuous quantities, for example, pollution levels, these are all subtypes of magnitude changing features. Three types of time patterns can be measured: 

• A trend that indicates whether something is increasing or decreasing. 
• Mapping conditions before and after an event lets us see the impact. 
•  Cycles show recurring patterns that reveal information about the behavior of the features. 

A snapshot or a summary can be used to display feature locations or characteristics two or more times. To map trends, determining an interval, the number of dates, and the total period can help. It is important to know how much and how fast the magnitude has changed after the analysis. There are three ways of mapping change: 

• Time Series – Good for showing the change in boundaries, values for discrete values or surfaces 
• Tracking Map – Good for showing movement in discrete locations, linear features, or area boundaries. 
• Measuring Change — Good for showing the amount, percentage, rate, or place. 

Similar to chapter five, the methods were laid down in a comparison table with their pros and cons to help the reader choose the best method for themselves. Next, the chapter gave instructions on creating a time series by showing the change in character or location. To create a tracking map, we can map individual features, linear features, contiguous features, or events. To measure and map changes types of character-changing features can be used. The chapter provides detailed instructions even for complicated situations, like mapping when there are negative values or if the boundary or category of definitions has changed.                                                              

 

Chapter 5: 

Chapter 5 deals with mapping what’s on the inside a designated area. Sometimes you will already have boundaries available in ArcMap but other times you will need to draw this area or areas on top of the features manually. The chapter lists several reasons you might want to map data inside a boundary, but as always it is important to keep in mind what you are trying to accomplish and how that will affect your approach. Mapping a single area will be different than mapping multiple areas while handling discrete or continuous data will affect your approach. Mitchell also notes that it is important to have some type of label whether it is a number or a unique name for each area mapped. The three ways of finding what’s inside are described as drawing areas and features, selecting the features inside an area, and overlaying the areas and features. Drawing areas and features are the easiest and most simple method, but it really only gives you a visual representation and not information about the features inside. Selecting the features inside an area allows you to get info on what is happening in a single area, but you are not able to see what is happening in each of several areas. For example, a map of parcels within a watershed using this method will let you see which parcels are within the watershed, but may not distinguish the type of parcels. With this method, you can use GIS to create a report of the selected features or statistical summaries. This data can come in the form of a count, frequency, or as a summary of a numeric value (i.e. sum, average, median, or standard deviation). Overlaying the areas and features avoids this by allowing you to see what is within each of several areas (i.e. parcel type), but it requires more time and processing than the other methods. Overall, I really liked this chapter and the examples provided. 

Chapter 6:

Chapter 6 deals with mapping what’s nearby a feature. There are many reasons why you might want to find out what is occurring within a set distance of a feature or to find out what is within traveling range. Reasons could involve legal policy decisions, business or environmental precautions, or simply a scientific analysis of an area. While distance can define or measure the proximity or features, travel costs may also be used. Travel costs, which may include time and money, may vary even if the distance between a set of features is the same due to other factors. For instance, it will cost a car more gas money to traverse a highly trafficked area rather than a relatively low trafficked area. It would also take less time for a deer to cross a valley to get to a stream than it would to cross a deeply forested area. In this way, the valley has a lower travel cost. Something to keep in mind is whether you are considering the curvature of the earth in your distance calculations or not. The planar method is used for smaller areas that can generally be observed as flat, while the geodesic method is used for larger areas where the curvature of the earth is taken into account. You may not think the curvature of the earth would need to be considered when dealing with relatively small areas, but major bridge constructions sometimes have to account for the earth’s curvature as the tips of supporting structures will be further apart from each other than they are at their respective bases. Information from an analysis can come in the form of a list, a count, or a summary of statistics.The reading describes three ways of finding what’s nearby: straight line distance, distance or cost over a network, and cost over a surface. As always, each method has its own uses, pros, and cons. Straight-line distance is used for defining areas of influence near a feature or selecting features at a set distance around a source, which gives an approximation of travel distance. Distance or cost over a network measures travel distance or cost of location over a fixed network or infrastructure, but requires a network layer. Cost over a surface is used for measuring overland travel costs and determines how much area is within the travel range. The rest of the chapter goes over these methods and guides you through making and modifying distance maps. Overall, I liked this chapter even though distance cost was a new concept for me. The chapter does a good job of describing why it might be important to calculate the distance between features (with the respect of area). 

Chapter 7:

Chapter 7 informs why it may be important to map change over time. Mapping changes over time is one of my favorite uses of GIS technology as it can be applied to countless environmental questions. Mapping changes over time is a great way to visualize patterns and predict future changes. This could involve examining weather patterns, changes in land use, or changes in population density. When mapping change it is important to remember the types of changes that exist. For instance, the book outlines changes in location, character, or magnitude, which all can describe geographic phenomena. Recognizing the types of features, such as discrete or continuous, is vital for choosing the appropriate method to map change. Measuring the time pattern is also key to mapping change. The three types of time patterns described are trends, before and after events, and cycles. Snapshots may be used to capture a set of conditions at one point in time, such as land cover or population data. Summarizing can be used to map discrete events that are not continuous in time. An example of this would be summarizing the daily precipitation for a region into monthly averages, which may show trends in weather patterns and may allude to the overall climate of the region. When mapping trends it is necessary to consider intervals, the number of dates, or total period. For instance, depicting urban sprawl annually may have as much of an impact when comparing the sprawl across several decades. For mapping cycles, a snapshot or summarization over a period can be used depending on whether the data is continuous or discrete. The chapter also lists three ways of mapping change. A time series is good for depicting changes in boundaries, surfaces, or values of discrete areas, which can lead to a strong visual impact. Tracking maps are great for showing movement in discrete locations, area boundaries, or linear features. These maps can become cluttered and difficult to read if there are more than a few features. The measuring change method involves showing the actual difference in values or amounts between two times only. This type of map only shows the change and not the actual conditions at either time. The rest of the chapter delves deeper into these methodologies and how to apply them appropriately. In conclusion, I don’t think the book could have ended on a better chapter since the earth and its features are constantly changing. As human beings, we are fascinated by change, so being able to map change is really rewarding and can lead to new insights to our behavior and geographical phenomena.

Chapter 5:

Chapter 5 built off a lot of what was learned in chapters 1-4. It reaffirms the importance of knowing whether your features are continuous or discrete when mapping. Mitchell notes that when dealing with discrete areas you can represent features with several different methods. This includes drawing boundaries on top of each other, on top of a color-coded area, or shading and labeling the boundaries. The reading then details for continuous features you should draw areas symbolized by category and quantity and then draw the boundary on top. I think the difference here is important as continuous data must be represented differently, in this way almost separately for the map to accurately show features and help the viewer get a sense of the range of continuous values.

The chapter then goes on to talk about what kind of data you can get from maps like lists and summary statistics before it gets into what I thought was the most important part of the chapter. This was the portion discussing overlaying areas and features. I talked about two different methods of doing this – the vector method and the raster method – this reaffirmed the difference between vector and raster layers while providing a new mechanism for producing maps and representing features. Briefly, with vector overlay splits category or class boundaries where they cross areas and create a new dataset with resulting areas. Vector is more precise, but it has one problem – slivers. As I understand it, slivers are where borders are offset. If these slivers are so small, it is important to merge them with surrounding data. This brings us to the raster overlay. Raster overlay combines raster layers and counts the number of cells in each category within each area then calculates aerial extent by multiplying the number of cells by the area of a call. This can ultimately be less efficient depending on cell size, but it does prevent slivers.

 

Chapter 6:

Chapter 6 was all about finding out what’s near and relevant to your feature(s). It talks about how travel is often measured by cost, which is time, money, effort (referred to as travel costs), and distance. The chapter then moved on to outline 3 different ways to find what’s nearby. The first and probably simplest of these is straight-line distance. Essentially, given a source feature and distance, the GIS will find features within the distance. The next method is distance or cost over a network in which GIS finds segments within the distance or cost given source locations and a distance or travel cost along each linear feature. Finally, there is cost over a surface in which you specify the location of the source feature and a travel cost, GIS creates a new layer showing the travel cost from each source feature.

This brings us to some new vocabulary from the chapter. First off, source locations are often referred to as centers. An impedance value is the cost to travel between the center and surrounding locations. Edges are lines, Junctions are where edges meet, and turns are used to specify the cost to travel through a junction check that these exist, are correct, and are in the right spot. These all help to define the network layer.

Another part of defining the network layer is cost. You can specify street direction or more than one center (rural vs urban areas) as these details can change the cost by lengthening travel. The GIS also checks and tags each distance of each segment keeping a cumulative total of cost or distance. One thing I did not understand about cost was the calculation. To find the monetary value the book gives the equation of Cents = length*(cost per mile/5280), but I feel as though travel costs are dependent on many other factors like traffic, gas prices, etc. So, I am slightly confused about how the given cost is an accurate reflection without some way of factoring those in.

 

Chapter 7:

Chapter 7 discussed mapping changes over time and how it can help predict future needs. It talked about mapping features previously discussed such as discrete features, data summarized by area, continuous categories, and continuous values. Specifically, it talked about how these features can change in character and magnitude. A change in character might be something like a physical movement of a feature, whereas a change in magnitude might be something like a hurricane or storm getting “worse” or “better”.

The chapter then moves on to talk about time. There are 3 ways to measure time: trends, before and after, and cycles. A trend is a change between 2 or more dates and times. This shows increases, decreases, and direction of movement. Before and after are conditions preceding and following an event. This lets you see the event’s impact. Finally, a cycle shows change over a recurring period and can give about the behavior of the features you are mapping. There are two ways to represent these changes in time as well. The first is a snapshot, which shows the condition at any given moment and is used to map continuous phenomena. The second is a summary where an event either is or isn’t occurring at a given time and is used for mapping discrete events. For cycles, you can use a snapshot or summary, for discrete events use a summary, and for continuous data use a snapshot.

The final portion of the chapter discussed the 3 ways of mapping time. The first is a time series. This represents movement or change in character. It can use a trend, cycle, before and after, and shows conditions at each date/time, but it can be hard for readers to compare visually. You should use this for a snapshot when you have 2 or more times. The second is a tracking map which is used for movement and can represent a trend, cycle, or before and after. It is easier to see subtle movement but can be difficult to read if there are many features. You should use this method when you have feature movement over 2 or more times. Finally, Measuring Change measures a change in character. This can represent a trend or before and after and shows the actual difference in amounts or values. However, it doesn’t show any actual conditions and only uses 2 times. The chapter then goes into thorough detail on the process of creating each of these maps. Overall, I thought this chapter was straightforward and I don’t have any questions about it.

Chapter 5:

Mapping what’s inside can be used to decide if action needs to be taken. For example in times of emergencies, maps can be used to show what areas are at risk. You can also use multiple maps to compare what is “inside” of different areas. Using an area boundary allows you to select features that you will be mapping and therefore create the “stuff” that you are mapping inside. Understanding your data is once again an important part of the process of mapping what’s inside. You must know whether you are mapping what’s inside a single area or several areas, because this will affect how to best map the data. If it’s a single area you can easily monitor activity or summarize information within that area. If it’s multiple areas, you can see how much of a specific thing is specific areas and compare them. There are also three different ways to find what’s inside an area, drawing areas and features, selecting the features inside the area, and overlaying the areas and features. Drawing areas and features allows you to find out whether features exist within the area or not, but only give you surface level information (you can’t get information about the features inside an area). Selecting the features inside the area results in a list or summary of features inside an area, but doesn’t separate information by area (you only get a list of features inside all areas combined together). Overlaying the areas and features allows you to find out which features are inside each area, and summarizes how many or how much is in each area. This gets the most expansive information, and solves the issues from the other two methods, but takes the most time and effort processing. The choosing a method section on page 148 will be useful for choosing a method if I ever have to do this in the future. The section on selecting features inside an area shows a bunch of example maps that look to me like they show the data very well and are “good” maps. The map and section on page 177 about overlaying areas with continuous values is really cool. I like the way that the GIS is able to combine elevation surface and a watershed layer and show how the elevation and watershed mesh together.

Chapter 6:

This chapter highlights why it can be important to map what’s nearby. Traveling range is an important component of doing this, and is defined by distance, time, and cost. Understanding what’s within the traveling range of an area can help you better understand how that area can be used and serve important purposes. The first step in the process of mapping what’s nearby is figuring out how to define and measure “near”. Making a definition like this feels important because “near” can mean a lot of things and a baseline definition would make things a lot easier. This nearness can be defined by either a set measurable distance, or by travel to and from a specific feature. You can find what’s nearby using straight-line distance,  or by measure cost over a network or over a surface. Using straight-line distance is the simplest and in my opinion most intuitive. Cost over a network and over a surface seemingly gets more complicated and involves more thinking/understanding. Useful ways to choose a method are found on page 191 and involve thinking about if you can define an area of influence, need a quick estimate of travel time, are measuring travel over fixed infrastructure, or are measuring overland travel. I think the way that you can use straight-line distance around a specific feature to find distance is really cool. I liked the example map of the selected parcels surrounding or within 100 feet of the road. I also think creating a buffer feature could be really useful and is something I’d like to practice doing. Once you have point-to-point information, you can create a map that color-codes locations by distance from the source (and closest to the source), make a spider diagram, or map source features using graduated point symbols. A spider diagram is when the GIS draws a line between each location and the nearest source. You can do this with multiple different sources and create a map that resembles a multicolored spider-web, comparing and representing the different patterns between source features.

Chapter 7:

Mapping change feels like a different thing than what we’ve been reading about because it’s a future phenomenon. This can be useful because it allows people to anticipate future conditions. You’re able to map expected conditions by looking at historical conditions and to eventually anticipate future needs. In order to best map change, you need to understand the types of features you are mapping. Features that move can be mapped using discrete features. These features can be tracked as they move through space. They include features you can map paths for (like hurricanes, a vehicle or animal), linear features (like a changing stream channel), or an area feature (like a fire boundary or oil spill). You can map change in three ways, time series, single tracking map, or map the differences in values between two times or dates. Time series show movement or change in character and have a strong visual impact. Tracking maps show movement and better show subtle change. Mapping change shows changes in character and shows the actual difference in amounts or values. If you generate multiple maps over different dates, it can be important to correctly decide the number of maps to show. By showing fewer maps, farther apart in time you can make the change in values easier to show, but less nuanced. Showing a bunch of maps with dates more closely together in time, you can reveal more detailed patterns about the change. Also, it can be helpful to include tables and charts that summarize data along with your maps. A tracking map is a map where the movement of individual features is mapped using a series of contiguous points. You can add a line connected points to emphasize the path the feature followed or even map the points at equal intervals to see how far the feature moved in a set time. Mapping continuous categories or classes is more complicated than mapping other features because it involves combining two layers, for both date and time. I get a little bit confused when it starts talking about raster data and areal extent. I feel like I’m going to have to do some more reading and investigating to understand this.