APHUG 1.4

Spatial Patterns

  • Clustered Pattern

    • Definition: Features are grouped closely together on Earth’s surface.
    • Significance: Indicates a shared attraction (e.g.
      resources, labor, markets) or a central organizing force.
    • Example: Silicon Valley’s tech firms clustering around venture‐capital hubs and research universities.

  • Agglomeration

    • Deliberate form of clustering around a central point or economic growth pole.
    • Encourages economies of scale, knowledge spillovers, and shared infrastructure.
    • Real‐world relevance: Automobile manufacturing in Detroit historically; multimedia studios in Hollywood.

  • Random Pattern

    • Distribution shows no discernible logic or systematic ordering.
    • Often implies minimal human planning or the dominance of natural factors.
    • Hypothetical scenario: Lightning strikes mapped over a year may show random spatial distribution.

  • Scattered Pattern

    • Objects that are normally ordered instead appear dispersed.
    • May signal declining cohesion, e.g.
      suburban sprawl where homes are built far apart instead of in compact blocks.

  • Linear Pattern

    • Features align in a straight line.
    • Common along rivers, railroads, or roads ("strip development").

  • Sinuous Pattern

    • Features follow a wavy/curving line.
    • Often mirrors natural landforms such as meandering rivers.

  • Influence of Land‐Survey Systems on Patterns

    • Property lines and political boundaries frequently trace survey systems.
    • Until the 1830s: Metes and Bounds relied on natural features (trees, streams, boulders) to demarcate land—causing irregular parcel shapes.
    • Post‐1830s (U.S.): Township and Range
    • Rectilinear grid based on \text{latitude} and \text{longitude}.
    • Produces uniform square/rectangular parcels.
    • Long‐Lot System
    • Narrow frontage along a road/river with elongated back lot.
    • Example: French colonial areas in Québec and Louisiana.

Density Measures

  • Arithmetic Density

    • Standard calculation: \text{Arithmetic Density}=\frac{\text{Number of objects or people}}{\text{Total land area (km^2 or mi^2)}}
    • Used for broad comparisons (e.g.
      national population density).

  • Physiological Density

    • Focus: Number of people per unit of arable land.
    • Formula: \text{Physiological Density}=\frac{\text{Population}}{\text{Arable Land Area}}
    • Indicates potential pressure on productive land (food security).

  • Agricultural Density

    • Measures farmers per unit of arable land.
    • Formula: \text{Agricultural Density}=\frac{\text{Number of Farmers}}{\text{Arable Land Area}}
    • Lower values in highly mechanized regions (e.g.
      U.S., Canada) vs.
      higher in subsistence‐farming regions (e.g.
      parts of Sub‐Saharan Africa).

Diffusion Patterns

  • Hearth (Point of Origin)

    • Starting location of an innovation or cultural trait.
    • Examples: Mesopotamia for agriculture; Silicon Valley for modern computing innovations.

  • General Spatial Diffusion Modes (mentioned indirectly for future lectures)

    • Expect discussion of contagious, hierarchical, stimulus, and relocation diffusion.
    • Key idea: Phenomena move outward from hearths in identifiable patterns.

Practical / Ethical Considerations

  • Understanding pattern, density, and diffusion helps planners address urban sprawl, resource allocation, and environmental impact.
  • Ethical implication: High physiological density may require equitable food distribution policies.