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Article Classification

Sustainable Development

Abstract

Conserving land capability is a pillar of sustainable development strategy. Land units comprising unique combinations of native vegetation, soils, geology, and landforms are used to interpret local environmental processes and land capabilities. An emerging practice is extrapolation modeling of edaphic parameter surfaces in Digital Soil Mapping (DSM) using statistical correlation. Commercial studies of land capability for sustainable development, including a mine closure in a national park, another closure for grazing land restoral, urban stormwater flood mitigation, and wind farm development in plantation forestry, are presented to illustrate applications and review the utility of DSM data. The first case, a mine closure plan in Kakadu National Park in the Arnhem Land region of Australia’s Northern Territory, involved the application of ecological methods to identify land unit patterns and design soil covers to support land capability for biodiversity. Species distribution models with good predictive performance (Receiver Operating Characteristic, ROC > 0.8) were used to assess biodiversity outcomes in the conceptual mine landform design. The second case, a coal project near Rockhampton in Central Queensland, assessed land capability from routine soil surveys and land unit mapping to plan mine rehabilitation for grazing land use. The third case, an end-of-pipe stormwater detention basin in Darwin, discussed the justification for capital works and low impact urban development practices. The fourth case involved the decommissioning of a wind farm project on a forestry plantation near Maryborough, Central Queensland. The study used surveyed soil and landscape properties and modeled DSM data with plant-available soil water capacity to three meters depth to evaluate the forest site quality and quantify the potential production loss. Applications of land capability for sustainability planning are demonstrated, and the utility of edaphic modeling is discussed. Uncertainty in DSM data and the implications for interpreting land capability need to be more clearly communicated.

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