A Level H2 Geography Map Graph Data Skills Quiz

A-Level Geography H2 Quiz - Map Graph Data Skills (Answer Key)

Total Marks: 45

Section A: Climate and Physical Data Interpretation

1. Identify the Köppen-Geiger climate classification for Station A. Support with two data points. [4]

• Identification: Af (Tropical Rainforest) [1]
• Supporting Data 1: All monthly temperatures are above 18°C (specifically 26–28°C), indicating a tropical climate (A). [1]
• Supporting Data 2: Precipitation in the driest month is greater than 60mm (no dry season), which distinguishes it from Am or Aw. [1]
• Clarity/Terminology: Correct use of Köppen codes and data citation. [1]

2. Describe the vegetation structure of the tropical rainforest. Refer to three layers. [3]

• Emergent Layer: Tallest trees (45m+), scattered, exposed to wind/sun. [1]
• Canopy Layer: Dense, continuous layer (25–35m), intercepts most sunlight/rain, highest biomass. [1]
• Understory/Shrub Layer: Sparse vegetation due to low light penetration, consists of shade-tolerant plants. [1]
  (Note: Accept description of Forest Floor as the 3rd layer if described as dark/humid with little vegetation.)

3. Explain the relationship between vegetation structure and biomass distribution. [3]

• Light Interception: The dense canopy and emergent layers capture the majority of solar energy for photosynthesis. [1]
• Biomass Concentration: Consequently, the greatest biomass (trunks, branches, leaves) is concentrated in the upper layers (canopy/emergent). [1]
• Lower Layers: The understory and floor have lower biomass due to limited light availability for growth. [1]

4. Calculate the range of river discharge. Show working. [2]

• Highest Value: 310 cumecs (June) [1]
• Lowest Value: 115 cumecs (Feb) [1]
• Calculation: $310 - 115 = 195$ cumecs.
  (Award 1 mark for correct answer even if working is missing, but 2 marks require working or clear identification of max/min.)

5. Suggest one physical factor for peak discharge in June/July. [2]

• Factor: Monsoon rainfall / Heavy seasonal precipitation. [1]
• Explanation: The peak corresponds to the wet season in a monsoon tropical climate, leading to increased surface runoff and river volume. [1]

Section B: Statistical Skills and Data Analysis

6. Describe the relationship shown in Resource 4. [2]

• Type: Negative / Inverse correlation. [1]
• Detail: As access to improved sanitation increases, the infant mortality rate decreases. [1]

7. Identify an outlier and suggest a geographical reason. [3]

• Identification: A country with high sanitation access but unexpectedly high infant mortality. [1]
• Reason 1: Poor quality of healthcare services despite infrastructure. [1]
• Reason 2: High prevalence of specific diseases (e.g., malaria/HIV) not addressed by sanitation. [1]
  (Accept other valid geographical reasons such as data reliability issues or recent conflict.)

8. Calculate the mean pedestrian flow. [2]

• Sum: $120 + 45 + 210 + 30 = 405$ [1]
• Mean: $405 / 4 = 101.25$ pedestrians per 10 mins. [1]

9. Explain why the mean might not be appropriate with an outlier. [2]

• Skewing: The mean is sensitive to extreme values; a single very high value (1000) would disproportionately raise the average. [1]
• Misrepresentation: It would not accurately reflect the "typical" pedestrian flow for the majority of sites. [1]
  (Accept reference to Median being more robust.)

10. State one appropriate statistical test and explain why. [3]

• Test: Spearman’s Rank Correlation Coefficient. [1]
• Reason 1: It tests for the strength and direction of association between two variables (distance and flow). [1]
• Reason 2: It is suitable for data that may not be normally distributed or is ordinal/ranked. [1]

Section C: Map Skills and Spatial Patterns

11. Calculate the gradient between Point X and Point Y. [3]

• Change in Height: $100m - 20m = 80m$ [1]
• Horizontal Distance: 800m [1]
• Gradient: $80 / 800 = 1/10$ or $1:10$ or $0.1$. [1]

12. Describe the relief characteristics at Grid Ref 460790. [2]

• Characteristic: Flat / Low-lying land. [1]
• Evidence: Contour lines are widely spaced (or absent), indicating gentle slope. [1]

13. Suggest why the mangrove swamp is located at this position. [3]

• Protection: Located at the river mouth/coast, providing shelter from strong wave action. [1]
• Sediment: Deposition of fine alluvial sediments from the river creates suitable muddy substrate. [1]
• Salinity: Brackish water conditions (mix of fresh river water and sea water) suit mangrove species. [1]

14. Describe the spatial pattern of population distribution. [2]

• Pattern: Uneven / Peripheral concentration. [1]
• Detail: High density along the coast (connected by roads) and low density in the interior highlands. [1]

15. Evaluate choropleth vs. dot distribution maps. [4]

• Advantage of Choropleth: Clearly shows regional trends and patterns of density; easy to read at a glance. [1]
• Disadvantage of Choropleth: Assumes uniform density within each unit, masking internal variations (e.g., urban clusters within a rural district). [1]
• Advantage of Dot Map: Shows exact location of individuals/clusters; reveals internal variation. [1]
• Disadvantage of Dot Map: Can become cluttered/hard to read in high-density areas; difficult to quantify exact numbers without counting. [1]

Section D: Synthesis and Evaluation of Geographical Data

16. Compare trends in Graph A and B. Draw an inference. [3]

• Trend A: Global temperatures have risen steadily since 1980. [1]
• Trend B: CO2 emissions are high, with Energy being the dominant sector. [1]
• Inference: There is a strong positive correlation/causal link between high CO2 emissions (particularly from energy) and rising global temperatures (Greenhouse Effect). [1]

17. Assess the validity of the student's claim. [3]

• Assessment: The statement is partially valid but exaggerated/incorrect. [1]
• Evidence: While Energy is the largest contributor, Graph B shows significant contributions from Industry, Agriculture, and Waste. [1]
• Conclusion: Ignoring other sectors overlooks substantial sources of emissions (e.g., methane from agriculture), making the claim invalid. [1]

18. Compare sustainability profiles of City P and City Q. [4]

• City P Strengths: Performs better in Green Space and Public Transport, suggesting good urban planning for livability and reduced car dependency. [1]
• City P Weakness: Poor Waste Recycling indicates issues with circular economy or waste management infrastructure. [1]
• City Q Strengths: Excels in Waste Recycling and Air Quality, suggesting effective environmental regulation and waste policies. [1]
• City Q Weakness: Low Green Space suggests potential urban heat island effects or lower quality of life regarding recreation. [1]
  (Must compare both cities to get full marks.)

19. Discuss limitations of using a single composite index/radar chart. [3]

• Weighting Issues: Different indicators may be weighted equally despite having different impacts on sustainability. [1]
• Data Aggregation: Masks specific failures; a high score in one area can compensate for a critical failure in another. [1]
• Subjectivity: Selection of indicators is subjective and may not capture all aspects of sustainability (e.g., social equity). [1]

20. Propose primary and secondary data methods for Urban Heat Island investigation. [4]

• Primary Method: Field measurement of air temperature using thermometers/data loggers at various sites (CBD vs. Rural) at the same time. [1]
• Contribution: Provides real-time, specific data for the study area. [1]
• Secondary Source: Satellite imagery (e.g., Landsat) showing Land Surface Temperature (LST). [1]
• Contribution: Allows for broad spatial analysis and identification of hotspots over a larger area/historical comparison. [1]