6.6单元 — 综合:比较并应用城市结构模型

(a) Urbanization is the process by which an increasing proportion of a population comes to live in cities and towns rather than in rural areas, accompanied by the physical growth and increasing economic/social importance of urban areas.

(b) In the concentric zone model, land uses are arranged as a series of rings that grow outward from a central business district (CBD) at the core. The lowest-income housing (along with the oldest and most deteriorated housing stock) sits in the zone immediately surrounding the CBD — the "zone in transition" — while household income generally increases as distance from the CBD increases, with the highest-income housing located in the outermost ring.

(c) The sector model differs by arranging land uses as wedges (sectors) radiating outward from the CBD along transportation routes, rather than as concentric rings. This means a single land-use type — such as a high-income residential district — extends the full distance from the center to the city's edge along one axis, instead of being confined to an outer ring, because high-value land uses grow outward along the same corridor over time once they are established near a route.

(d) The multiple-nuclei model holds that a city develops around several separate nodes (nuclei) of activity — such as a port, a university, an industrial park, and an outlying retail center — rather than a single dominant CBD. This happens because different activities have different locational needs and some activities benefit from clustering together (agglomeration) while others are incompatible and repel each other, so as a city grows, distinct specialized centers emerge independently around the features that attract them.

(e) Threshold is the minimum number of people (or minimum market size) needed to support a particular good or service being offered profitably at a location. Range is the maximum distance people are willing to travel to obtain that good or service. Together, threshold and range determine which goods a settlement of a given size can support: a good with a low threshold and short range (e.g., a convenience store) can be supported by many small settlements, while a good with a high threshold and long range (e.g., a specialty hospital) can only be supported by a large settlement that draws customers from a wide surrounding area.

(f) A country follows the rank-size rule when its cities' populations form a predictable, roughly even hierarchy: the nth-largest city has approximately 1/n the population of the largest city. This pattern typically reflects a well-developed, diversified national economy with functions distributed across many regional centers. A primate city, by contrast, is a country's largest city that is disproportionately larger than all other cities in the country (often more than twice the size of the second-largest) and dominates the country's economic, political, and cultural life. A primate-city distribution is common in countries with a colonial history or a highly centralized economy, where investment, infrastructure, and opportunity were concentrated in a single dominant city rather than spread among regional centers.

(g) This city's layout best fits the sector model. In the sector model, distinct land uses extend outward from the CBD as wedges along transportation corridors rather than as concentric rings, and the scenario describes exactly that pattern: high-income housing forms a wedge following a linear amenity corridor (the river) outward from downtown, while industrial land use forms a separate wedge following a different linear corridor (the rail line) on the opposite side. This is inconsistent with the concentric zone model, which would predict income increasing uniformly with distance from the CBD in all directions rather than concentrating along one specific corridor, and it does not describe multiple, functionally independent nuclei, so the sector model is the best fit.

(a) The rank-size rule is a pattern observed in some countries' urban hierarchies in which the population of a city is inversely proportional to its rank among all cities in the country — the population of the nth-ranked city is approximately equal to the population of the largest city divided by n.

(b) Under the rank-size rule, the rank-2 city's expected population = (population of rank-1 city) / 2 = 8,400,000 / 2 = 4,200,000.

(c) San Marcos's actual population (950,000) is far below the 4,200,000 that the rank-size rule would predict — it is only roughly one-ninth of Rivera's population rather than one-half. Because Rivera is dramatically larger than would be expected relative to the rest of the country's cities, Country Y displays a primate-city pattern rather than a rank-size distribution: Rivera dominates the urban hierarchy instead of the city sizes stepping down in the smooth, predictable way the rank-size rule describes.

(d) A primate-city pattern like this typically indicates that Country Y's economic development is uneven and centralized rather than diversified — investment, industry, government administration, transportation infrastructure, and job opportunities are concentrated heavily in Rivera rather than spread among regional centers. This pattern is common in countries with a colonial history (where the colonial power built up a single administrative/export hub) or in countries where post-independence government and economic policy continued to funnel resources into one dominant city, leaving secondary cities comparatively underdeveloped and lacking the infrastructure or economic base to grow into true regional counterweights.

(e) This pattern contradicts the concentric zone model. In the concentric zone model, the zone immediately surrounding the CBD is the "zone in transition," associated with the oldest housing stock and the lowest-income residents, with income rising as distance from the CBD increases outward toward the city's edge. Rivera's description is the reverse of that — high-income housing is closest to the CBD and income falls with distance — so it does not fit the concentric zone model's predicted income gradient.

(f) One likely sustainability challenge is severe strain on housing, infrastructure, and services: because so much of the national population and economic activity is concentrated in Rivera, the city is likely to face overcrowding, informal/unplanned settlement growth on its periphery, traffic congestion, inadequate sanitation and water systems, and air pollution, as infrastructure investment struggles to keep pace with population growth concentrated in one place rather than being distributed across multiple smaller, more manageable urban centers.

(g) Rivera's government could adopt a policy of decentralization — deliberately relocating government offices, universities, or incentivizing private industry to open new offices/factories in secondary cities such as San Marcos or Belmar. This would help by redirecting job opportunities and investment away from Rivera toward the smaller cities, reducing migration pressure into Rivera, easing the strain on its housing and infrastructure, and helping the country's urban hierarchy move toward the more balanced, rank-size pattern described in part (a).

(a) Harlow's internal spatial structure best fits the sector model.

(b) Source 1 describes land uses forming wedges that extend outward from downtown along transportation and amenity corridors — manufacturing along the rail line and upper-income housing along the ridge/highway corridor — rather than as concentric rings around the CBD. This wedge-along-a-corridor pattern, with middle-income housing filling the space between the two sectors, is the defining characteristic of the sector model, in which land uses grow outward from the center along a fixed axis once established near a transportation route.

(c) The sector model, as classically described, does not fully explain why manufacturing/warehousing (an industrial use) and upper-income housing (a residential use) each cluster into their OWN separate, specialized wedge rather than simply being separated by income alone — the presence of two functionally distinct specialized wedges (one industrial, one residential) organized around different infrastructure (rail vs. highway/ridge) is better explained by the multiple-nuclei model's idea that different activities cluster around different specialized nodes/corridors based on their own locational needs.

(d) Over the twenty-year period, Harlow's metro population grew by about 44% (from 480,000 to 690,000), while its built-up land area grew by about 121% (from 140 to 310 square miles) — the land area consumed by development grew more than twice as fast, proportionally, as the population did.

(e) This pattern is called urban sprawl — low-density outward expansion of a metropolitan area's built-up footprint at a rate that outpaces its population growth. One specific consequence of sprawl is the loss of farmland and open space at the metropolitan periphery, as low-density subdivisions, roads, and commercial strips consume land that was previously used for agriculture; another common consequence is increased automobile dependence and traffic congestion, since low-density, spread-out development is difficult to serve efficiently with public transit and forces most trips to be made by car.

(f) The wedge-shaped growth pattern in Source 1 is organized around linear transportation corridors (the rail line, the highway), and because sector-model growth extends outward along a corridor rather than filling in a compact ring around downtown, new development can continue stretching farther and farther from the CBD along each corridor. This corridor-driven, linear growth is inherently land-extensive rather than land-efficient, which helps explain why Harlow's built-up area expanded so much faster than its population — growth was not being absorbed through denser infill closer to downtown but was instead consuming new land at the leading edge of each wedge.

(g) Harlow could adopt a smart-growth or urban growth boundary policy — for example, establishing a boundary that limits new large-lot development beyond a certain distance from downtown while incentivizing higher-density, mixed-use infill development closer to the existing built-up area and along transit corridors. This would help by directing new population growth into already-developed areas rather than allowing it to consume additional peripheral land, which would slow the rate of built-up land expansion relative to population growth and help preserve remaining farmland and open space at the metro edge.