Ch.1<\/p>\n
Not everyone can just go into GIS, but you need to understand the proper tools and structure for your intended analysis. I think it is interesting how a lot of GIS users become advanced analysts, so that is another possible career path.<\/span><\/p>\n GIS Analysis: a process for observing geographic patterns in a set of data and at relationships between different features.<\/span><\/p>\n It is important that you understand your data and be able to find the proper way to develop it.<\/span><\/p>\n Important Steps to GIS Analysis<\/span><\/p>\n Frame the question > Understand your data > Choose a method > Process the data > Look at the results > Understanding geographic features<\/span><\/p>\n Geographic features are discrete, continuous phenomena, or summarized areas.<\/span><\/p>\n Discrete features: are discrete locations and lines, the actual location can be pinpointed. At any given spot, the feature is either present or not.<\/span><\/p>\n Continuous Phenomena: examples are precipitation or temperature and can be found or measured anywhere. You can determine a value at any given location.\u00a0<\/span><\/p>\n It is important to note that continuous data often starts out as a series of sample points, either regularly spaced or irregularly spaced.<\/span><\/p>\n Example of regular spaced: sampled elevation data<\/span><\/p>\n Example of irregularly spaced: weather stations<\/span><\/p>\n Interpolation: Where GIS can use sample points to assign values to the area between points.<\/span><\/p>\n Sometimes non continuous data can be treated as continuous in order to create maps showing how a quantity varies across the place. Continuous data can also be represented by areas enclosed by boundaries-if everything inside the boundary is the same type- such as a type of soil or vegetation.\u00a0<\/span><\/p>\n Important Note: \u201cIf the features aren\u2019t tagged with the codes for the areas by which you want to summarize them, the GIS lets you overlay the areas with the features to identify which ones lie within each area and to tag them with the appropriate code\u201d.<\/span><\/p>\n Vector and raster are the two ways geographic features can be shown in GIS. It is important to use the right size when dealing with these models. Continuous categories are represented by vector or raster models. Continuous numeric values use raster models only.<\/span><\/p>\n Geographic features have specific attributes that go with them.<\/span><\/p>\n Examples: categories, ranks, counts, amounts, ratios<\/span><\/p>\n Categories are groups of similar things. (not continuous)<\/span><\/p>\n Ranks put features in order, from high to low. (not continuous)<\/span><\/p>\n Counts and amounts show you total numbers. (are continuous)<\/span><\/p>\n Ratios show you the relationship between two quantities and are created by dividing one quantity by another for each feature. (are continuous)<\/span><\/p>\n Important: working with tables that contain the attribute values and summary stats is a vital part of GIS analysis. Three common operations you perform on features and values within tables are SELECTING, CALCULATING, and SUMMARIZING.<\/span><\/p>\n Select attribute= value<\/span><\/p>\n Select Landuse= com<\/span><\/p>\n Select Landuse= com and acres > 2<\/span><\/p>\n CH.2<\/p>\n A lot of people use maps, use them to see where, or what, an individual feature is. Patterns are often seen. Individual features vs distribution of features.\u00a0<\/span><\/p>\n GIS can tell police officers where to assign patrols based on crimes that occur.<\/span><\/p>\n Step 1: Need to decide what to map<\/span><\/p>\n Step 2: What info do you need from the analysis?<\/span><\/p>\n Step 3: How will you use the map?<\/span><\/p>\n Step 4: Preparing your data<\/span><\/p>\n Step 5: Assigning geographic coordinates<\/span><\/p>\n Step 6: Assigning category values<\/span><\/p>\n Step 7: Making your map(finally!)<\/span><\/p>\n Mapping a single type<\/span><\/p>\n You can map all features in a data layer or a subset you\u2019ve selected based on a category value.<\/span><\/p>\n Using a subset could reveal patterns that aren\u2019t always apparent.<\/span><\/p>\n Step 8: Mapping by category<\/span><\/p>\n How many categories? Want to display no more than seven categories and grouping them could make it easier to understand\/distinguish. Example: 18 categories grouped into 5<\/span><\/p>\n Just know that GIS is very complicated, complex and delicate<\/span><\/p>\n You can group categories in several different ways.<\/span><\/p>\n Choosing symbols: make sure the symbols you choose are chosen carefully(combination of color and shape)<\/span><\/p>\n The map you create will be more understandable if you display recognizable symbols. Include a map reference if you think there is a chance that people won\u2019t get it.<\/span><\/p>\n Step 9: Analyzing geographic patterns<\/span><\/p>\n CH.3<\/p>\n Why map the most and least?<\/span><\/p>\n In order to do this\u2026 your map features must be based on quantity associated with each.<\/span><\/p>\n Mapping features based on quantities adds an additional level of info beyond simply mapping the locations of features.\u00a0<\/span><\/p>\n To map?<\/span><\/p>\n You can map quantities associated with discrete features, continuous phenomena, or data summarized by the area.<\/span><\/p>\n Locations can be dotes<\/span><\/p>\n Lines can be rivers<\/span><\/p>\n You might want to present your map in a specific way, but must explore the data first.<\/span><\/p>\n Knowing quantities(counts and amounts), will be important or could be when presenting your map. You can map counts and amounts for discrete figures.\u00a0<\/span><\/p>\n Might need to show ratios to get your point across\u2026averages are good and so are proportions.<\/span><\/p>\n Proportions are often presented ias percentages. Densities show you where features are concentrated.\u00a0<\/span><\/p>\n Ranks: poor-fair-good-excellent or 1-8<\/span><\/p>\n Once you\u2019ve determined the type of quantities, need to decide how to best represent them on the map.<\/span><\/p>\n Might need to make trade-offs when doing this.<\/span><\/p>\n Mapping individual values could be very important in order to present a more accurate picture.<\/span><\/p>\n You will need to keep in mind classes and how to create them manually.<\/span><\/p>\n The four most common schemes are natural breaks, quantile, equal interval, and standard deviation. GIS can compare these different classification schemes.<\/span><\/p>\n Good: mapping data values that are not evenly distributed<\/span><\/p>\n Bad: difficult to compare the map with other maps.<\/span><\/p>\n There are pros and cons to each different common scheme.<\/span><\/p>\n You might need to deal with outliers in your data, so know how to deal with them.<\/span><\/p>\n Note: might have to decide how many classes to include and make them easier to read using GIS<\/span><\/p>\n Towards the end of chapter 3. Talks more into detail about features and details about maps.<\/span><\/p>\n Might need to use charts, contour lines to map data.\u00a0<\/span><\/p>\n GIS can create 3D perspective views! How awesome!<\/span><\/p>\n","protected":false},"excerpt":{"rendered":" Ch.1 Not everyone can just go into GIS, but you need to understand the proper tools and structure for your intended analysis. I think it is interesting how a lot of GIS users become advanced analysts, so that is another possible career path. GIS Analysis: a process for observing geographic patterns in a set of data and at relationships between different features. It is important that you understand your data and be able to find the proper way to develop it. Important Steps to GIS Analysis Frame the question > Understand your data > Choose a method > Process the data > Look at the results > Understanding geographic features Geographic features are discrete, continuous phenomena, or summarized areas. Discrete features: are discrete locations and lines, the actual location can be pinpointed. At any given spot, the feature is either present or not. Continuous Phenomena: examples are precipitation or temperature and can be found or measured anywhere. You can determine a value at any given location.\u00a0 It is important to note that continuous data often starts out as a series of sample points, either regularly spaced or irregularly spaced. Example of regular spaced: sampled elevation data Example of irregularly spaced: weather stations Interpolation: Where GIS can use sample points to assign values to the area between points. Sometimes non continuous data can be treated as continuous in order to create maps showing how a quantity varies across the place. Continuous data can also be represented by areas enclosed by boundaries-if everything inside the boundary is the same type- such as a type of soil or vegetation.\u00a0 Important Note: \u201cIf the features aren\u2019t tagged with the codes for the areas by which you want to summarize them, the GIS lets you overlay the areas with the features to identify which ones lie within each area and to tag them with the appropriate code\u201d. Vector and raster are the two ways geographic features can be shown in GIS. It is important to use the right size when dealing with these models. Continuous categories are represented by vector or raster models. Continuous numeric values use raster models only. Geographic features have specific attributes that go with them. Examples: categories, ranks, counts, amounts, ratios Categories are groups of similar things. (not continuous) Ranks put features in order, from high to low. (not continuous) Counts and amounts show you total numbers. (are continuous) Ratios show you the relationship between two quantities and are created by dividing one quantity by another for each feature. (are continuous) Important: working with tables that contain the attribute values and summary stats is a vital part of GIS analysis. Three common operations you perform on features and values within tables are SELECTING, CALCULATING, and SUMMARIZING. Select attribute= value Select Landuse= com Select Landuse= com and acres > 2 CH.2 A lot of people use maps, use them to see where, or what, an individual feature is. Patterns are often seen. Individual features vs distribution of features.\u00a0 GIS can tell police officers where to assign patrols based on crimes that occur. Step 1: Need to decide what to map Decide what features to display Step 2: What info do you need from the analysis? Might need to know where features are or are not? The question. Patterns. Step 3: How will you use the map? Appropriate audience Make sure issue is being addressed Make sure to add just\u00a0 the right amount of info(no unnecessary details) Step 4: Preparing your data Make sure the features you\u2019re mapping have geographic coordinates assigned and, optionally, have a category attribute with a value for each feature before mapping Step 5: Assigning geographic coordinates Each feature needs a location in geographic coordinates Step 6: Assigning category values Each feature must have a code that identifies its type, when your map FEATURES BY TYPE, example is whether a crime is burglary or assault In some cases, a single code indicates both the major type and subtype Step 7: Making your map(finally!) Tell GIS which features you want to display and what symbols to use to draw them You can do this by creating a layer for either single type or categories Mapping a single type Must draw all features using the same symbol You can map all features in a data layer or a subset you\u2019ve selected based on a category value. Using a subset could reveal patterns that aren\u2019t always apparent. Step 8: Mapping by category You can understand how a place functions when mapping by a category(roads like freeway and highway) How many categories? Want to display no more than seven categories and grouping them could make it easier to understand\/distinguish. Example: 18 categories grouped into 5 Just know that GIS is very complicated, complex and delicate You can group categories in several different ways. Assign a general code to each record in the database Create a linked table to match detailed codes with general codes Assign categories on the fly by specifying symbols Choosing symbols: make sure the symbols you choose are chosen carefully(combination of color and shape) The map you create will be more understandable if you display recognizable symbols. Include a map reference if you think there is a chance that people won\u2019t get it. Step 9: Analyzing geographic patterns Pretty self explanatory(look for patterns) CH.3 Why map the most and least? Lets you compare places based on quantities, so you can see which places meet your criteria In order to do this\u2026 your map features must be based on quantity associated with each. Mapping features based on quantities adds an additional level of info beyond simply mapping the locations of features.\u00a0 To map? Need to know the type of feature Know the purpose of your map You can map quantities associated with discrete features, continuous phenomena, or data summarized by the area. Locations can be dotes Lines can be rivers You might want to present your map in a specific way, but must explore the data first. Knowing quantities(counts and amounts), will be important or could be when presenting your map. You can map counts and amounts for discrete figures.\u00a0 Might need to summarize by area\u2019 Might need to show ratios to get your point across\u2026averages are good and so are proportions. Proportions are often presented ias percentages. Densities show you where features are concentrated.\u00a0 Ranks: poor-fair-good-excellent or 1-8 Once you\u2019ve determined the type of quantities, need to decide how to best represent them on the map. Might need to make trade-offs when doing this. Mapping individual values could be very important in order to present a more accurate picture. You will need to keep in mind classes and how to create them manually. The four most common schemes are natural breaks, quantile, equal interval, and standard deviation. GIS can compare these different classification schemes. Good: mapping data values that are not evenly distributed Bad: difficult to compare the map with other maps. There are pros and cons to each different common scheme. You might need to deal with outliers in your data, so know how to deal with them. Note: might have to decide how many classes to include and make them easier to read using GIS Towards the end of chapter 3. Talks more into detail about features and details about maps. Might need to use charts, contour lines to map data.\u00a0 GIS can create 3D perspective views! How awesome!<\/p>\n","protected":false},"author":2209,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[4],"tags":[],"class_list":["post-1380","post","type-post","status-publish","format-standard","hentry","category-course-student-work"],"_links":{"self":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/1380","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/users\/2209"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/comments?post=1380"}],"version-history":[{"count":1,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/1380\/revisions"}],"predecessor-version":[{"id":1381,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/posts\/1380\/revisions\/1381"}],"wp:attachment":[{"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/media?parent=1380"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/categories?post=1380"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/sites.owu.edu\/geog-291\/wp-json\/wp\/v2\/tags?post=1380"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}\n
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