Chapter 4
Chapter 4 further describes the different types of maps one can use when creating maps on GIS. One map listed is the Density map, which is useful for people who want to map areas that vary in size, considering the presence of differing concentrations. On the subject of density maps, the reading makes it clear that there are different types of ways to use a density map, such as mapping specific features or the variables associated with those features. One question that arises from this topic is: Is it possible to combine feature maps and feature value maps to create a larger picture of data? This chapter feels quite relevant to my mapping plans for the class, which is the distribution of a specific insect species, for which I could use a dot map. Dot maps represent density based on how close or far the dots are from each other. GIS seems to make it relatively user-friendly to understand how to read and create density maps, as when it comes to the defined area maps, the higher density areas are within darker colored boundaries, while the lighter areas are lower density locations. Another question that this chapter prompts me to wonder is whether one can toggle between dot maps and shaded maps, as they are both typically pictured together when presented in the textbook. I found it interesting that the application gives the user so much freedom with customization, as you can even determine how many features a single dot represents, which could definitely help simplify a map if the data is immense but congregated. A common theme I have noticed throughout the chapter is that GIS provides a lot of support when it comes to mathematical calculations, as it can aid in the numerical calculation of density for any given feature. One other feature of notability is the choice of cell size, which is how big a plot is on the map, which can help broaden the options between a detailed and broad map.
Chapter 5
Chapter 5 appears to be delving into the boundaries of a map and the relevance of what occurs within those boundaries. I find it important to note the different types of boundaries one can use, such as a single area, a buffer that surrounds a specific zone or feature, and a natural boundary. In consideration of my own future map, if I choose to map an insect with aquatic larvae, then I could use the buffer map type, so that I can observe how far an aquatic insect may migrate from its watershed of origin. Two types of boundaries can be made: discrete, which are clearly defined zones, and continuous, which are more loosely defined and are typically natural structures. The boundaries are frequently determined by the purpose of the data, like the mapping of a floodplain in an urban area, or the distribution of types of trees in protected areas. There are three ways one can go about creating borders: freehand drawing, selecting the features within the boundaries, and overlaying the features. Chapter 5 references previous chapters by bringing up the statistical analysis strategies of count, frequency, as well as bar charts and piecharts. I also find it interesting that it develops on the content of chapter 4 by describing how you can combine overlay and drawn maps for a more complex map. One question that arose when reading this was: Should one use different data analysis techniques for different types of bordered maps? One topic to note is the usage of the raster method, as it can create calculations that deduct what the areal extent is on the map. The vector method is similar, but more precise, which can lead to more effort required on the user’s end. These methods can also aid in analysing data.
Chapter 6
An important factor to consider when collecting or presenting data for a GIS map is what qualities or factors are present within a boundary. A term to monitor this is the travelling range, which can be measured through three different metrics: cost, time, and distance. The travelling distance can be used in conjunction with multiple metrics, such as the time it would take to travel a particular distance within a particular boundary. One question that comes to mind when considering this is: Is this type of GIS method used to track the distance at which particular species migrate, or would the distance and method of travel be too complex to map in this way? Based on the reading, money seems to also be a frequent use of urban mapping, as people calculate how long it will take to travel from one place to another. When calculating the travel distance, two methods can be used: the planar method, which is for smaller, flat parcels of land, and the geodesic method, which is for larger, less linear pieces of land. The chapter specifies that different geometric features within a boundary prompt different statistical methods for data analysis, such as a list, a count, and a summary statistic, also known as a total count. I find it relevant to note that there are also different scales at which you can produce a border to show a range of travelling distances. These can include inclusive rings and district bands, which perform similar functions with just a different viewing option. I think it is interesting that GIS, to some degree, can even calculate the travel costs for the user, according to the textbook. One can also create a feature called a buffer, meaning that they can create an expanse of area around a particular variable on the map.