Tutorial 2: How to interpret land health dashboards

Reading indicators, colours, and trends without getting lost.

2.1 The basic layout of a dashboard

  • Most land health dashboards follow a similar structure:
    • Header / controls: filters for country, region, time period, and indicator.
    • Summary cards: key numbers for the selected area (e.g., mean SOC, % degraded land).
    • Map panels: spatial distribution of indicators across the region.
    • Charts and time series: how indicators change over time or differ between areas.
  • The K4GGWA dashboards aim to:
    • Provide a quick overview of conditions and trends.
    • Allow users to zoom in from GGW-wide patterns to specific landscapes.

2.2 Understanding indicators and units

  • Each indicator represents a specific aspect of land health or climate context:
    • Examples: SOC (Mg C/ha), erosion risk (index or probability), tree cover (%), rainfall (mm), vegetation indices (unitless index).
  • Important points:
    • Always read the indicator description and units (often accessible via info icons or documentation).
    • Values may look similar but mean different things depending on the indicator:
      • A value of “0.6” in a vegetation index is interpreted differently from “0.6” in a probability of erosion.
  • Good practice:
    • Check how “low” and “high” values are defined for each indicator.
    • Note any thresholds used to define categories (e.g., “high erosion risk” above a certain probability).

2.3 Reading maps: colours, legends, and scale

  • Maps translate numbers into colours so patterns are easier to see:
    • Continuous colour scales show gradual changes (e.g., SOC from low to high).
    • Categorical scales show classes (e.g., land cover types, risk levels).
  • To interpret correctly:
    • Always look at the legend to see what each colour means.
    • Note the range of values (e.g., minimum and maximum) represented on the map.
    • Identify whether the map shows:
      • A snapshot (one year or period), or
      • A change (difference between two dates or a trend over time).
  • Scale matters:
    • Colours may look dramatic at GGW scale but less extreme when zoomed into a smaller region.
    • Use zoom and different views to avoid misreading small local variations as large-scale trends.

2.4 Combining multiple indicators

  • Effective decisions often require more than one indicator:
    • Example: combining SOC, erosion risk, and tree cover to identify priority restoration areas.
    • Example: combining rainfall trends with vegetation indices to understand drought impacts.
  • When viewing multiple layers:
    • Start by understanding each indicator individually.
    • Then look for areas where several indicators send a similar signal (e.g., low SOC and high erosion risk).
    • Be cautious about over-interpreting:
      • A single pixel, or
      • Areas where indicators disagree (this may highlight the need for local knowledge or further analysis).
  • Dashboards can help by:
    • Providing side-by-side maps or linked charts.
    • Allowing users to toggle layers on and off.

2.5 Spatial and temporal scale: choosing the right view

  • Dashboards often allow you to:
    • Aggregate indicators at different levels (e.g., GGW, country, region, district).
    • Change the time window (single year vs. multi-year averages vs. trends).
  • Choosing the right scale:
    • GGW / regional scale: good for strategic planning and donor dialogue.
    • National / subnational scale: good for program design and targeting.
    • Local scale: good for site-level interventions and community engagement.
  • Interpreting time:
    • A single year may show short-term variability (e.g., a drought year).
    • Multi-year averages highlight typical conditions.
    • Trends or anomalies help identify change and emerging risks.

2.6 Using dashboards as a starting point for discussion

  • Dashboards are tools to support decision-making, not to replace it:
    • Use maps and charts to generate questions:
      • Why is this region consistently low in vegetation recovery?
      • Why is erosion risk higher in some districts despite similar rainfall?
    • Bring local knowledge into the interpretation:
      • Community experiences, land-use history, policy changes, and infrastructure development.
  • In practice:
    • Use dashboards in workshops, planning meetings, and monitoring sessions.
    • Capture feedback from local stakeholders about where the maps align or disagree with their experience.
  • The key message:
    • Dashboards help make complex spatial data visible and shareable.
    • They are most powerful when combined with local knowledge, field verification, and transparent discussion.
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