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Project 4.10

railway over river from drone. railway remote sensing and quality analysis

Optimising ecosystem management in mining areas: Integrating ground validation with remote sensing for enhanced solutions

Research Program

Data Integration, Forecasting and Scale

Project Leader

Associate Professor Peter Erskine, The University of Queensland

Project ID

4.10

Summary

The Australian continent’s vastness poses challenges for effective mine rehabilitation and monitoring, requiring more comprehensive ecological data than currently available. Traditional field methods cover less than 1% of mine areas, necessitating scalable solutions. Using satellite data and drones, remote sensing offers cost-effective and regular data collection, capturing crucial ecological attributes. This project aims to develop a centralised repository of hyperspectral and structural data for species identification, enhancing mine rehabilitation outcomes. The project will advance remote sensing technologies by standardising protocols, sharing data, improving stakeholder confidence, and supporting better closure management and ecological monitoring across mine sites.

Project Partners

The University of Queensland; Department of Climate Change, Energy, the Environment and Water, Fortescue, Rio Tinto, Roy Hill Iron Ore, Geoscience Australia, MMG Australia, BHP, CSIRO

Duration

36 months