🎯 Learning Objectives

By the end of this class, students will be able to:

  • Understand the purpose and interpretation of key landscape metrics.
  • Use the landscapemetrics package in R to analyze spatial urban data.
  • Evaluate urbanization patterns (e.g., fragmented) through spatial metrics.
  • Relate ecological patterns to urban planning.

🗂️ Class Components

1. Introduction (20 min)

  • Ecological Implications of Urban Form

    • Habitat loss, patch isolation, ecological corridors

  • Planning Relevance

    • Green spaces connectivity as landscape outcomes

  • Scale and Metric Selection

    • Aggregation vs. fragmentation (PD, AREA_MN)
    • Shape and connectivity (SHAPE_MN, ENN_MN, COHESION)

2. Hands-on R Workshop (1 hr 10 min)

Using the class_stuttgart.Rmd and provided dataset (shapefile):

  • Load and visualize raster/landscape data

  • Calculate landscape metrics:

    • Patch-based: PD, AREA_MN, ENN_MN, SHAPE_MN, COHESION

  • Interpret metrics using real urban district maps

    • Discuss types of urban pattern: compact, nodal, fragmented, etc.
  • Export tables and maps for planning communication

Tools: RStudio, landscapemetrics, raster, ggplot2

3. Interpretation & Scenario Design (Out-of-Class Engagement)

Using the following table:

Metric Expected Interpretation in Urban Green Areas
pd (patch density) Fragmentation: high values indicate spatial dispersion
shape_mn (mean shape index) Irregularity of shape: more complex or elongated patches
cohesion Degree of physical connectivity between patches
enn_mn (mean Euclidean nearest-neighbor distance) Isolation: average distance to the nearest similar patch
area_mn (mean patch area) Average size of green space fragments
  • Interpret the metrics for the selected urban district

  • Design 2 planning scenarios:

    • Compact Densification
    • Interconnected Green Corridors
  • Predict how metrics would change

📂 Deliverables

  • Metric interpretation table (worksheet)

🧰 Materials Required

  • R/RStudio installed with the following packages:

    install.packages(c("landscapemetrics", "terra", "raster", "sf", "ggplot2"))
  • Urban shapefile classification of public parks of one Peruvian municipality (La Molina,)
  • Digital worksheets