Cover condition of the Beetaloo region

\n## **Abstract** \nThe Beetaloo GBA region in the Northern Territory of Australia currently supports a modest gas extraction industry. With the possibility of a significantly expanded industry in the future, it is important to understand the current environmental impacts of the industry. Towards this end, this analysis examines the effects of current gas extraction activities on vegetation cover condition in the Beetaloo GBA region. It does this using the Compere relative benchmarking framework, which has been parameterised here to use ground cover fraction data (which is an excellent proxy for landscape condition) and to separate-out the variability in ground cover associated with natural processes from the variability associated with human activities. Results show that gas extraction wells and gas pipelines had significant negative effects on cover condition at their immediate locations compared to vegetation in the surrounding 1 km of land. Beyond distances of 1 km, pipelines seemed to have no further effect on condition whereas at distances between 1 and 4 km from wells, condition was found to be significantly lower than at the well location itself. The reasons for this are not known. Given that only minimal extraction activities currently occur across the Beetaloo GBA region, this study provides a baseline assessment against which future analyses could be compared if the industry is further developed.\n\n\n## **Attribution** \nCSIRO\n\n\n## **History** \nSix input datasets were used to define biophysical equivalence (locations of similar growing conditions): precipitation, burned area; elevation, available water holding capacity, and long-term average tree foliage cover fraction. Precipitation data were from the monthly data of Jones et al. (2009). Burned area data (MCD64A1, Collection 6) were from Giglio et al. (2009); elevation from Gallant et al. (2011); water holding capacity from Viscarra Rossel et al. 2014 and tree fractional cover were based on the methods of Donohue et al. (2009). Cover condition was assessed using total cover fraction data of Guerschman et al. (2015), which is based on MCD43A4 C6 imagery. Surface Water Points data were used to test results and were sourced from Crossman and Li (2015).\r\n\r\nCrossman S, Li O (2015). Surface Hydrology points (Regional). Geosciences Australia. Canberra. http://pid.geoscience.gov.au/dataset/ga/83132\r\nDonohue RJ, McVicar TR, Roderick ML (2009). Climate-related trends in Australian vegetation cover as inferred from satellite observations, 1981–2006. Global Change Biology, 15, 1025-1039. DOI: 10.1111/j.1365-2486.2008.01746.x \r\nGallant JC, Dowling TI, Read AM, Wilson N, Tickle PK, Inskeep C (2011). 1 second SRTM-derived Digital Elevation Models User Guide. Canberra: Geoscience Australia\r\nGiglio L, Loboda T, Roy DP, Quayle B, Justice CO (2009). An active-fire based burned area mapping algorithm for the MODIS sensor. Remote Sensing of Environment, 113, 408-420. DOI: 10.1016/j.rse.2008.10.006.\r\nGuerschman JP, Scarth PF, McVicar TR, Renzullo LJ, Malthus TJ, Stewart JB, Rickards JE, Trevithick R. (2015). Assessing the effects of site heterogeneity and soil properties when unmixing photosynthetic vegetation, non-photosynthetic vegetation and bare soil fractions from Landsat and MODIS data. Remote Sensing of Environment, 161, 12-26. DOI: 10.1016/j.rse.2015.01.021.\r\nJones DA, Wang W, Fawcett R. (2009). High-quality spatial climate data sets for Australia. Australian Meteorological and Oceanographic Journal, 58, 233-248.\r\nViscarra Rossel R, Chen C, Grundy M, Searle R, Clifford D, Odgers N, Holmes K, Griffin T, Liddicoat C, Kidd D (2014). Available water capacity (3" resolution). Canberra: CSIRO