Richardson, C, Grigg, AH, Robinson, T & Wardell-Johnson, G 2019, 'Achieving restoration targets and addressing completion criteria with remote sensing', in AB Fourie & M Tibbett (eds), Proceedings of the 13th International Conference on Mine Closure
, Australian Centre for Geomechanics, Perth, pp. 53-62.
Alcoa of Australia has undertaken a progressive post-mining restoration program following bauxite mining in the jarrah forest of south-western Australia since operations began in 1963. Approximately 10,000 ha of restored forest is now of a suitable age for assessment and sign-off against agreed rehabilitation completion criteria. Remote sensing techniques have the potential to efficiently measure a range of attributes of post-mining restoration over areas of this size. We used airborne laser scanning and multispectral imagery from remotely piloted aircraft to estimate a range of forest canopy attributes. We also used these approaches to penetrate established tree canopies and measure understorey and the underlying terrain at very high resolution (e.g. 40 cm). We also used vegetation indices derived from Landsat satellite imagery for chronosequence assessment dating from the early 1970s. This paper describes investigations into the potential of these remote sensing techniques for assessment of older restoration and implementation within a process for sign-off with government. Field-based calibration is an essential component of these studies, and comparisons of on-ground measurement of vegetation structure and cover with remotely sensed indices are presented.
Keywords: remote sensing, restoration trajectory, LiDAR, multispectral imagery, mining restoration, completion criteria, jarrah forest
Abbott, I & Loneragan, OW 1986, Ecology of Jarrah (Eucalyptus marginata) in the Northern Jarrah Forest of Western Australia, Department of Conservation and Land Management, Perth.
Cross, AT, Young, R, Nevill, P, McDonald, T, Prach, K, Aronson, J & Dixon, KW 2018, ‘Appropriate aspirations for effective postmining restoration and rehabilitation: a response to Kaźmierczak et al.’, Environmental Earth Sciences, vol. 77, no. 6, pp. 1–6.
Department of State Development 2015, Completion Criteria and Overview of Area Certification Process, viewed 3 February 2019,
Elliott, P, Gardner, J, Allen, D & Butcher, G 1996, ‘Completion criteria for Alcoa of Australia Limited’s bauxite mine rehabilitation’, Proceedings of the 3rd International 21st Annual Minerals Council of Australia Environment Workshop, Minerals Council of Australia, Kingston, pp. 78–89.
Eysn, L, Hollaus, M, Lindberg, E, Berger, F, Monnet, J, Dalponte, M & Pfeifer, N 2015, ‘A benchmark of lidar-based single tree detection methods using heterogeneous forest data from the alpine space’, Forests, vol. 6, no. 5, pp. 1721–1747.
Grant, C & Koch, J 2007, ‘Decommissioning Western Australia’s first bauxite mine: co-evolving vegetation restoration techniques and targets’, Ecological Management and Restoration, vol. 8, iss. 2, pp. 92–105.
Havel, JJ 1975, Site-Vegetation Mapping in the Northern Jarrah Forest (Darling Range). 1. Definition of Site-Vegetation Types, Forests Department of WA, Perth.
Jaskierniak, D, Kuczera, G, Benyon, R & Wallace, L 2015, ‘Using tree detection algorithms to predict stand sapwood area, basal area and stocking density in Eucalyptus regnans forest’, Remote Sensing, vol. 7, no. 6, pp. 7298–7323.
Jaskierniak, DP, Lane, NJ, Robinson, A & Lucieer, A 2011, ‘Extracting LiDAR indices to characterise multilayered forest structure using mixture distribution functions’, Remote Sensing of Environment, vol. 115, iss. 2, pp. 573–585.
Khosravipour, A, Skidmore, A, Isenburg, M, Wang, T & Hussin, Y 2014, ‘Generating pit-free canopy height models from airborne lidar’, Photogrammetric Engineering & Remote Sensing, vol. 80,no. 9, pp. 863–872.
Koch, JM 2007, ‘Restoring a jarrah forest understorey vegetation after bauxite mining in Western Australia’, Restoration Ecology, vol. 15, iss. s4, pp. S26–S39.
Macfarlane, C, Grigg, A & Daws, M 2017, ‘A standardised Landsat time series (1973-2016) of forest leaf area index using pseudoinvariant features and spectral vegetation index isolines and a catchment hydrology application’, Remote Sensing Applications: Society and Environment, vol. 6,
Macfarlane, C, Grigg, A & Evangelista, C 2007, ‘Estimating forest leaf area using cover and fullframe fisheye photography: Thinking inside the circle’, Agricultural and Forest Meteorology, vol. 146, no. 1–2, pp. 1–12.
Pekin, B & Macfarlane, C 2009, ‘Measurement of crown cover and leaf area index using digital cover photography and its application to remote sensing’, Remote Sensing, vol. 1, pp. 1298–1320.
Pirotti, F, Kobal, M, & Roussel, JR 2017, ‘A comparison of tree segmentation methods using very high density airborne laser scanner data’, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol. 42, pp. 285–290.
Schut, AGT, Wardell-Johnson, GW, Yates, CJ, Keppel, G, Baran, I, Franklin, SE, Hopper, D, Van Niel, KP, Mucina, L & Byrne, M 2014, ‘Rapid characterisation of vegetation structure to predict refugia and climate change impacts across a global biodiversity hotspot’, PLoS ONE, vol. 9, no. 1.
Wardell-Johnson, GW, Calver, M, Burrows, N & Di Virgilio, G 2015, ‘Integrating rehabilitation, restoration and conservation for a sustainable jarrah forest future during climate disruption’, Pacific Conservation Biology, vol. 21, no. 3, pp. 1–11.