Learn · AP® Human Geography

Unit 1.6 — Maps, Map Projections, and Geospatial Technology

How every flat map distorts the globe on purpose, the standard thematic map types, and how GPS, remote sensing, and GIS work together as the unit's closing lesson.

16 minUnit 1AP® Human Geography
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Every lesson in this unit has referenced maps in passing — a choropleth map showing income data, a map illustrating a functional region, a map excerpt showing a spatial pattern. This closing lesson finally makes maps themselves the subject: how they distort reality on purpose, what kinds of maps geographers use for different jobs, and the modern digital tools — GIS, GPS, and remote sensing — that have transformed how geographic data is collected and displayed. This is the natural closer for Unit 1, because everything about location, place, region, scale, and human-environment interaction eventually gets represented, and potentially distorted, on a map.

The unavoidable problem: you cannot flatten a sphere without distortion

Earth is (very nearly) a sphere, and any flat map is a projection of that sphere's surface onto a plane — and it is a mathematical certainty that no flat projection can preserve every property of the original sphere at once. Something always gets distorted: shape, area, distance, or direction. Every map projection is therefore a set of trade-offs, sacrificing accuracy in some properties to preserve accuracy in others, and the mapmaker's choice of which properties to sacrifice is rarely neutral — it can shape how the reader perceives the relative size or importance of different regions.

Four projection types, sorted by what they preserve

  • Conformal projections preserve shape and angle accuracy at the cost of area — the Mercator projection is the best-known example. Mercator preserves local shape well enough that it was originally designed for, and remains genuinely useful for, marine navigation, since a straight line drawn on a Mercator map corresponds to a constant compass bearing. Its well-known drawback is severe area distortion that grows worse toward the poles: Greenland appears comparable in size to Africa on a Mercator map, when Africa's actual land area is roughly fourteen times larger. Because Mercator was so widely used as a general-purpose world map for so long, this specific distortion has had a real, documented effect on public perception of the relative size of equatorial versus high-latitude regions.
  • Equal-area projections preserve accurate relative area at the cost of shape — regions are sized correctly relative to each other, but their outlines can look visibly stretched or compressed compared to their true shape. The Gall-Peters projection is the most frequently cited example, and it was explicitly promoted starting in the 1970s as a corrective to Mercator's area distortion, deliberately showing equatorial and Southern Hemisphere landmasses (Africa, South America) at their true, larger relative size — a choice with real political and cultural resonance, since it directly counters a map convention that had visually diminished those regions for centuries.
  • Equidistant projections preserve accurate distance, but typically only along specific lines (such as from the map's center point outward), not for every possible pair of points on the map. These are useful for specialized purposes like measuring flight distances from a single hub airport.
  • Azimuthal (or planar) projections preserve accurate direction from a single central point, and are especially useful for polar-region maps or for showing the shortest ("great circle") flight path between two distant cities, which often looks like a curved line on a Mercator map but a straight line from an azimuthal projection centered correctly.

No projection is simply "more accurate" than another in some absolute sense — the exam wants you to match a projection's known strength to the task a mapmaker is actually trying to accomplish, and to explain what got sacrificed to achieve it.

Types of thematic maps

Beyond the choice of projection, geographers also choose from several standard map formats depending on what kind of data they're displaying:

  • Choropleth maps use shading or color intensity across pre-defined areal units (states, counties, countries) to represent a statistic's value — darker shading typically meaning a higher value. These are the most common map type in this course, used constantly for showing things like population density, income, or election results by region, and they are exactly the map type most vulnerable to the modifiable areal unit problem covered in the previous lesson.
  • Dot-density (or dot-distribution) maps place one dot per fixed quantity of whatever is being measured, scattered across the actual location where that quantity occurs — a population dot map might place one dot for every ten thousand people, positioned roughly where those people actually live, which shows real clustering and empty space in a way a choropleth map (bound to fixed administrative boundaries) cannot.
  • Graduated symbol maps place a symbol, usually a circle, at each specific location being measured, sized larger or smaller according to that location's data value — a city's population might be shown as a circle whose size scales with that city's actual population, letting a reader compare specific point locations directly rather than shaded regions.
  • Isoline (or isopleth) maps use continuous lines connecting points of equal value across a surface, the same principle as elevation contour lines on a topographic map or the isobars on a weather map connecting points of equal air pressure — useful for phenomena that vary continuously across space rather than being tied to fixed administrative units.
  • Cartograms deliberately distort the size or shape of areal units to represent a statistic other than physical land area — a cartogram of the United States sized by electoral votes rather than land area will show a small state like Rhode Island uncomfortably large relative to its true land size if its electoral influence outweighs its physical footprint, which is a genuinely useful (if visually strange) way to represent influence, population, or economic weight rather than physical geography.

Geospatial technology: how modern geographic data actually gets collected and analyzed

Maps used to be drawn entirely by hand from surveyed measurements. Three interconnected digital technologies have transformed both how geographic data is gathered and how it's analyzed:

  • GPS (Global Positioning System) is a network of satellites that lets a receiver calculate its own precise absolute location by measuring the time signals take to arrive from multiple satellites simultaneously. GPS is the technology behind everyday location services on a phone, and it's also the modern method for establishing exact coordinates that feed into other geospatial systems — a task that once required painstaking manual surveying.
  • Remote sensing is the collection of data about Earth's surface from a distance, typically from satellites or aircraft, without physical contact with the area being studied. Remote sensing imagery is what produces the satellite photography behind most modern mapping tools, but it goes well beyond ordinary photographs — sensors can detect wavelengths of light and other energy invisible to the human eye, which allows analysts to track things like vegetation health, soil moisture, deforestation, or urban heat patterns across huge areas repeatedly over time, far faster than any ground survey could manage.
  • GIS (Geographic Information Systems) is software that stores, analyzes, and displays geographic data as a set of layers that can be combined, compared, and queried together — a population layer, a road-network layer, a floodplain layer, and a land-use layer can all be stacked over the same base map and cross-referenced, letting an analyst answer spatial questions (which neighborhoods are both flood-prone and densely populated?) that would be extremely difficult to work out from separate paper maps. GIS is the technology that ties GPS-derived coordinates and remote-sensing imagery together into a single, queryable analytical system, and it underlies most professional geographic analysis today, from urban planning departments to public health agencies tracking a disease outbreak's spread.

These three technologies work as a pipeline in practice: GPS establishes precise coordinates, remote sensing gathers imagery and other data about those coordinates from a distance, and GIS software organizes both into layered, analyzable maps. The exam sometimes asks you to match a real-world scenario (a city planning department deciding where to route emergency services, a research team tracking coastal erosion over a decade) to the specific technology or technologies best suited to it, so it's worth being able to state what each one specifically does rather than treating "geospatial technology" as one undifferentiated tool.

Closing out Unit 1: why the whole unit builds toward this

Every concept introduced across this unit — the five themes, location and region types, spatial patterns and diffusion, scale and the modifiable areal unit problem, and human-environment interaction — is, at bottom, about how geographers describe and analyze the world accurately, and this final lesson is where all of that meets the actual tools and representations used to do it. A choropleth map is only as trustworthy as the scale it was aggregated at; a projection's distortion is only obvious once you know what property it was built to preserve; a GIS analysis is only as useful as the layers a geographer chose to include. Carrying this unit's full vocabulary forward — not just map terms, but region types, diffusion mechanisms, and the possibilism framework — is what will let you read the maps, tables, and data sets in every remaining unit with real precision instead of a surface-level glance.

Practice: Free-Response Questions

Real AP-format prompts for this unit, each with a full model answer and the exact points a College Board reader would award. Click a question to see the answer — not AI-graded, just scored the way the real exam is scored.

LEQ

A small town in the hill country of a southern U.S.

A small town in the hill country of a southern U.S. state is experiencing rapid population growth as remote workers relocate from larger metropolitan areas. Local officials are debating how to plan for the town's future while geographers study the changes using the core concepts of the discipline.

(a) Define the geographic concept of place, and identify one physical characteristic and one human characteristic that could describe the town.

(b) Explain how the town's absolute location differs from its relative location.

(c) Identify the type of region (formal, functional, or perceptual/vernacular) best illustrated by a label such as "hill country," and justify your answer.

(d) Explain how changing the scale of analysis from the town level to the state level would affect a geographer's understanding of the population growth trend.

(e) Describe the process of relocation diffusion and explain how it applies to the remote workers moving into the town. (f) Identify one theme from the five themes of geography, other than location, that is relevant to studying the town's growth, and explain how it applies to this situation. (g) Explain one way the growing population is likely to alter human-environment interaction in the surrounding landscape.

Model answer

(a) Place refers to the physical and human characteristics that give a location its identity and distinguish it from other locations. A physical characteristic of the town might be its position within a hilly, limestone-based landscape with seasonal streams; a human characteristic might be its historic downtown square or its small-town street grid built around a central courthouse.

(b) Absolute location is the fixed, precise position of the town described using a coordinate system such as latitude and longitude. Relative location describes the town's position in relation to other places, such as its distance and travel time from a nearby metropolitan area. The town's absolute location never changes, but its relative location can become more or less significant as connections to other places (highways, broadband, commuter patterns) develop.

(c) The label illustrates a perceptual (vernacular) region, because "hill country" is not defined by a single measurable government boundary (as a formal region would be) or by a shared functional link to a central node (as a functional region would be). Instead, it reflects a shared mental image or cultural perception of an area's identity held by the people who live in or near it, and its boundaries are fuzzy and vary from person to person.

(d) At the town scale, the growth might appear as a dramatic, highly visible surge because the town's population base is small, so even a modest number of new residents produces a large percentage change. At the state scale, however, that same number of new residents would represent a negligible fraction of the state's total population, and the growth might not appear significant at all when averaged across many other counties and cities. Changing scale therefore changes which patterns are visible and how significant a given trend appears.

(e) Relocation diffusion is the spread of an idea, practice, or in this case a population, that occurs when the people carrying the trait physically move from one location to a new one, leaving the origin location behind. It applies to the remote workers because they are not simply visiting or communicating remotely; they are permanently uprooting their households from the metropolitan area of origin and re-establishing residence in the town, carrying their habits, spending patterns, and cultural preferences with them to the new location.

(f) One relevant theme is human-environment interaction, which examines how people modify, adapt to, and depend on their physical surroundings. As new residents settle in the hill country, they interact with the landscape by building new housing developments, drilling wells or extending water infrastructure, and altering natural drainage patterns, all of which reflect the reciprocal relationship between people and their environment.

(g) The growing population is likely to increase demand for groundwater and surface water, potentially straining the town's aquifer and seasonal streams, and to accelerate the conversion of open rangeland or wooded hillsides into residential lots, which increases impervious surface area, alters natural drainage, and raises the risk of local flooding after heavy rainfall.

Scoring · 7 points
1. Awards the point for correctly defining place AND providing one accurate physical characteristic and one accurate human characteristic of the town.
2. Awards the point for correctly distinguishing absolute location (a fixed coordinate position) from relative location (position described in relation to other places).
3. Awards the point for correctly identifying "perceptual/vernacular region" and justifying it with reference to shared perception/fuzzy boundaries rather than a formal legal boundary or a functional node-based link.
4. Awards the point for explaining that a smaller scale of analysis (state level) would make the same absolute growth appear less significant/visible than at the larger scale (town level), or an equivalent correct scale-effect explanation.
5. Awards the point for correctly defining relocation diffusion as physical movement of people/traits away from the origin AND correctly applying it to the remote workers' permanent move.
6. Awards the point for correctly naming a theme of geography other than location (e.g., human-environment interaction, place, region, or movement) AND explaining its relevance to the scenario.
7. Awards the point for describing a plausible, specific way population growth alters human-environment interaction in the hill country landscape (e.g., water demand, land conversion, drainage/flooding effects).
LEQ

Source: Field data collected by a regional economic geographer tracking the spread of a specialty coffee shop chain outward from its origin in City A.

Town | Distance from City A (miles) | Year chain arrived Town B | 15 | 2018 Town C | 40 | 2020 Town D | 90 | 2023 Town E | 150 | has not arrived as of 2026

(a) Using the data in the table, identify the type of diffusion illustrated by the coffee chain's spread, and justify your answer with evidence from the table.

Source: Field data collected by a regional economic geographer tracking the spread of a specialty coffee shop chain outward from its origin in City A.

Town | Distance from City A (miles) | Year chain arrived Town B | 15 | 2018 Town C | 40 | 2020 Town D | 90 | 2023 Town E | 150 | has not arrived as of 2026

(a) Using the data in the table, identify the type of diffusion illustrated by the coffee chain's spread, and justify your answer with evidence from the table.

(b) Define distance decay and explain how the data in the table illustrate this concept.

(c) Identify one physical or human barrier that could explain why the chain has not yet reached Town E despite Town E being within the same region.

(d) Explain how a geographer could use GIS to visualize and analyze the pattern shown in the table.

(e) Distinguish between GIS and GPS, and explain which of the two technologies would be more useful for recording the exact location of each new coffee shop as it opens. (f) Explain how changing the scale of analysis from local (town-by-town) to regional would change a geographer's interpretation of the chain's spread. (g) Propose one field study method a geographer could use to verify or refine the diffusion pattern suggested by the table.

Model answer

(a) The data illustrate expansion diffusion, specifically a pattern consistent with contagious (or hierarchical-contagious) expansion diffusion, because the trait (the coffee chain) spreads outward from its origin in City A while remaining present there, and it reaches nearer towns first (Town B, 15 miles, 2018) before reaching farther towns later (Town D, 90 miles, 2023), showing a continuous outward wave rather than a sudden jump to a distant, unconnected location.

(b) Distance decay is the principle that the interaction, influence, or likelihood of adoption between two places decreases as the distance between them increases. The table illustrates this because the towns closest to City A (Town B at 15 miles) received the chain earliest, while towns farther away (Town D at 90 miles) received it later, and the farthest town (Town E at 150 miles) has not received it at all, showing that the chain's influence weakens as distance from the origin grows.

(c) A physical barrier could be a mountain range, river, or lack of a direct highway connection that increases the effective travel time and cost between City A and Town E, discouraging expansion. A human barrier could be a difference in local zoning regulations, a lack of sufficient population density or disposable income in Town E to support the chain, or the presence of an established local competitor that reduces the profitability of entering that market.

(d) A geographer could use GIS to plot each town as a point layer with its distance from City A and year of arrival stored as attribute data, then create a choropleth or graduated-symbol map layer to visually display how arrival year changes with distance, overlay additional layers (roads, population density, income) to test for correlated factors, and use spatial analysis tools to model or predict where and when the chain might expand next.

(e) GIS (Geographic Information Systems) is software used to store, analyze, and visually display spatial data in layers, while GPS (Global Positioning System) is a satellite-based technology used to determine a precise real-time location on Earth's surface. GPS would be more useful for recording the exact location of each new coffee shop as it opens, because that task requires capturing a precise coordinate in the field, whereas GIS is the tool used afterward to store, analyze, and map that coordinate data alongside other layers.

(f) At the local, town-by-town scale, the spread might appear somewhat irregular, since specific site factors, such as an individual town's road access or local competition, cause year-to-year variation in when each town received the chain. At the regional scale, however, those local irregularities average out and the broader, more regular pattern of outward, distance-based diffusion becomes clearer, since the overall trend of increasing distance corresponding to later arrival years is more visible when many towns are considered together.

(g) A geographer could conduct field interviews or surveys with residents and business owners in Town E and the surrounding area to ask directly whether they are aware of the chain, whether they have expressed interest in it, or whether they perceive specific obstacles to its arrival, and could supplement this with direct on-site observation of local infrastructure, competing businesses, and consumer traffic patterns to test whether the barriers identified in part

(c) are actually present.

Scoring · 7 points
1. Awards the point for correctly identifying expansion (contagious/hierarchical) diffusion AND justifying it using the table's distance-and-year pattern.
2. Awards the point for correctly defining distance decay AND connecting it to the table's pattern of nearer towns receiving the chain earlier than farther towns.
3. Awards the point for identifying one plausible physical OR human barrier that could explain Town E's non-adoption.
4. Awards the point for explaining a specific, correct GIS application (layers, attribute data, spatial analysis, or mapping) to visualize the diffusion pattern.
5. Awards the point for correctly distinguishing GIS from GPS AND correctly identifying GPS as more useful for recording exact real-time shop locations.
6. Awards the point for explaining how the local scale shows more irregularity/local variation while the regional scale reveals the broader distance-decay pattern more clearly (or an equivalent correct scale-effect explanation).
7. Awards the point for proposing a specific, plausible field study method (e.g., interviews, surveys, direct observation) to verify the pattern.
LEQ

Source 1: Population density by county in a hypothetical state, 2025.

Source 1: Population density by county in a hypothetical state, 2025.

County | Population Density (people per square mile) North County | 850 East County | 120 South County | 45 West County | 900

Source 2: Percentage of households with broadband internet access, same four counties, 2025.

County | Broadband Access (%) North County | 92 East County | 61 South County | 38 West County | 89

(a) Using Source 1, identify which county has the lowest population density.

(b) Using both sources together, describe the spatial pattern that emerges when population density is compared with broadband access across the four counties.

(c) Identify the type of thematic map (for example, choropleth) a geographer would most likely use to display the data in Source 2, and explain why that map type is appropriate for this data.

(d) Explain how using a Mercator projection instead of an equal-area projection could distort a geographer's visual comparison of the four counties' land areas on a map.

(e) Using evidence from both sources, explain one human factor (economic, infrastructural, or political) that could help account for South County's low broadband access. (f) Explain how remote sensing could be used to gather additional data relevant to understanding the pattern shown across the two sources. (g) Propose one policy recommendation, supported by evidence from both sources, that could help address the disparity in broadband access shown in Source 2.

Model answer

(a) South County has the lowest population density, at 45 people per square mile.

(b) When the two sources are compared, a clear positive spatial relationship emerges between population density and broadband access: the two counties with the highest population density, West County (900) and North County (850), also have the highest broadband access rates (89% and 92%), while the two counties with the lowest population density, South County (45) and East County (120), also have the lowest broadband access rates (38% and 61%). This suggests that more densely populated counties are more likely to have widespread broadband infrastructure, while sparsely populated, rural counties lag behind.

(c) A geographer would most likely use a choropleth map to display the data in Source 2, because choropleth maps use graduated shading or color to represent a data value (such as percentage of broadband access) aggregated by enumeration unit, in this case counties, making it easy to visually compare the intensity of a variable across a set of defined areas.

(d) A Mercator projection preserves angles and shapes for navigation but severely distorts area, especially at higher latitudes, meaning that if the four counties differ in latitude, the Mercator projection could make a county's true land area look larger or smaller than it actually is relative to the others, misleading a geographer's visual comparison. An equal-area projection, by contrast, sacrifices some shape accuracy in order to preserve the true relative size of each county, so a geographer comparing the counties' land areas would get an accurate visual comparison only from an equal-area projection.

(e) One human factor is that internet service providers often prioritize infrastructure investment, such as running fiber-optic or cable lines, in areas with higher population density because the cost of building that infrastructure can be spread across more paying customers per mile of line, making it more profitable. Since South County has the lowest population density of the four counties, it likely represents a less profitable market for providers, resulting in less infrastructure investment and, consequently, lower broadband access.

(f) Remote sensing, the collection of data about Earth's surface from satellites or aircraft without direct physical contact, could be used to identify existing physical infrastructure such as cell towers, cable lines, or newly cleared land for construction, to measure land cover and terrain that might make infrastructure installation more difficult or costly in a county like South County, and to track changes in infrastructure development over time by comparing images from different years.

(g) One policy recommendation would be for the state or federal government to offer targeted subsidies or grants to internet service providers to offset the cost of extending broadband infrastructure into low-density, low-access counties such as South County and East County, since the data in both sources show that low population density correlates with low broadband access, indicating that market forces alone are unlikely to close the gap without outside financial incentive.

Scoring · 7 points
1. Awards the point for correctly identifying South County as the lowest-density county using Source 1.
2. Awards the point for correctly describing the positive relationship between population density and broadband access using specific evidence from both sources.
3. Awards the point for correctly identifying choropleth mapping AND explaining why it fits data aggregated by enumeration unit (county-level percentages).
4. Awards the point for correctly explaining that a Mercator projection distorts area (especially at higher latitudes) while an equal-area projection preserves true relative size, applied to comparing the counties.
5. Awards the point for identifying a plausible human factor (e.g., infrastructure investment economics, profitability per customer, policy/funding priorities) AND connecting it to South County's low density using evidence from the sources.
6. Awards the point for explaining a specific, correct remote sensing application relevant to studying infrastructure or land cover related to broadband access.
7. Awards the point for proposing a specific, plausible policy recommendation that is explicitly supported by evidence drawn from both sources.
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