How do monitoring, modelling and remote sensing support resource management decisions?
Explain how monitoring, modelling and remote sensing inform sustainable resource management
A focused answer to the WACE Year 12 Earth and Environmental Science dot point on monitoring, modelling and remote sensing. Covers indicators and baselines, the role of models in prediction, satellite and field monitoring, and how data feeds adaptive management across scales, with Australian examples.
Reviewed by: AI editorial process; not yet individually human-reviewed
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What this dot point is asking
SCSA wants you to explain how these three tools support sustainable management of renewable resources at local, regional and global scales. The thread is evidence: you cannot manage what you cannot measure, and you cannot plan without predicting.
Monitoring
Monitoring is the systematic, repeated measurement of a resource and its environment.
- A baseline is the starting condition against which change is measured.
- Indicators are the measurable variables chosen to represent resource health, such as water-table level, fish stock size, vegetation cover or water quality.
- Repeated measurement reveals trends, distinguishing real change from natural variation.
For example, groundwater management on Perth's Gnangara Mound relies on a network of bores monitoring water-table levels over decades.
Modelling
A model is a simplified representation of a system used to predict its behaviour.
- Models take monitoring data and project how a resource will respond to different scenarios, such as different extraction rates or rainfall futures.
- They let managers test choices safely before acting, for example estimating whether a quota will allow a fish stock to recover.
- Model reliability depends on data quality and on how well the model captures the real system, so predictions carry uncertainty.
Remote sensing
Remote sensing collects data from a distance, mainly using satellites and aircraft.
- It covers large and inaccessible areas efficiently and repeatedly.
- It tracks changes such as land clearing, vegetation health, water extent, algal blooms and sea-surface temperature.
- It complements ground-based monitoring, which provides detailed local measurements that calibrate the remote data.
Putting it together: adaptive management
The three tools form a cycle. Monitoring measures the current state, models predict the outcome of options, a management decision is made, and continued monitoring checks whether the prediction held. If it did not, the decision is revised. This adaptive management cycle lets managers respond to uncertainty and change, and it operates across scales, from a single mine site or aquifer, to a regional fishery, to global monitoring of forests and oceans.