Abstract

Livestock graze hill country regions worldwide where grassland biomass or structure is important both economically as forage and enviromentally as habitat for wildlife. Manual measurements of biomass in remote and expansive hill country landscapes are time consuming, expensive, and difficult to estimate due to spatiotemporal variability. Pasture areas where livestock utilisation or grassland biomass is exceptionally high or low could be mapped within a topographic framework. A model was developed that integrates several data sources (elevation, spectra and field data) to estimate hill-country biomass. Topographic data were modelled and used to classify biomass, which ranged from low at summits (1493 kg/ha) to high at toe-slopes (2876 kg/ha). These estimates were compared with the current plant height-based model, which ranged from low (2014 kg/ ha) to high (3032 kg/ha). This paper demonstrates how expansive, heterogeneous grassland landscapes can be assessed seasonally using topographic markers within an integrated spatial data framework. Keywords: Remote sensing, DEM, structure, Landsat 8, forage utilisation, graziers

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