University of Wollongong
Browse

High-Resolution Topographic Data for Subsidence Impact Assessment and SMP Preparation: Methods and Considerations

Download (1.86 MB)
conference contribution
posted on 2024-11-13, 14:28 authored by Daniel Palamara, G Brassington, Phillip Flentje, Ernest BaafiErnest Baafi
Corporate and social requirements relating to sustainable mining practices have resulted in an increasing need for identification and assessment of natural features that may be susceptible to coalmine-induced subsidence. Natural features such as, cliff lines, watercourses and steep slopes, that are typically susceptible to subsidence-induced impacts can often be identified and quantified using high-resolution topographic data and a geographic information system (GIS). Once identified, digital representations of these features can be used in the impact assessment process and for Subsidence Management Plan (SMP) preparation. This paper demonstrates the use of topographic data for site characterisation and feature identification purposes by mapping susceptible areas for a study site, including valley floors, steep slopes, drainage lines, and erosion-prone areas. It also discusses the potential use of topographic data and GIS for assessing subsidence impacts through knowledge- and data-driven approaches. The assessment of pre- and post-subsidence hydrological conditions is also shown for two swamps within the study area. The area over the proposed Dendrobium Area 2 operation in the Southern Coalfield was chosen as a case study site, and high-resolution airborne laser scan data were acquired for the site from BHP Billiton.

History

Citation

This conference paper was originally published as Palamara, D, Brassington, G, Flentje, P and Baafi, E, High-Resolution Topographic Data for Subsidence Impact Assessment and SMP Preparation: Methods and Considerations, in Aziz, N (ed), Coal 2006: Coal Operators' Conference, University of Wollongong & the Australasian Institute of Mining and Metallurgy, 2006, 276-292.

Pagination

276-292

Language

English

RIS ID

18065

Usage metrics

    Categories

    Keywords

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC