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|Title:||Using NDVI dynamics as an indicator of native vegetation management in a heterogeneous and highly fragmented landscape|
|Citation:||MODSIM2013: 20th International Congress on Modelling and Simulation. Modelling and Simulation Society of Australia and New Zealand, December 2013 / J. Piantadosi, R. S. Anderssen and J. Boland (eds.): pp.1931-1937|
|Publisher:||Modelling and Simulation Society of Australia and New Zealand|
|Conference Name:||International Congress on Modelling and Simulation (20th : 2013 : Adelaide, South Australia)|
|D. Turner, K. Clarke, M. Lewis and B. Ostendorf|
|Abstract:||Monitoring change and assessing the impact of natural resource management policies is an important task of regional governments. Remote sensing is routinely used to assess vegetation cover. However, spectral indices record variations in vegetation cover and photosynthetic status, and hence vary substantially with weather. Hence observed changes may largely be due to spatio-temporal differences in climatic conditions rather than management. Monitoring small changes in vegetation cover and extent within a large region requires detecting a small signal in a very noisy environment. The aim of this paper is to assess the detectability of revegetation sites in satellite imagery. We use an indextrends approach, developed and applied to Landsat imagery of the Adelaide and Mount Lofty Ranges (AMLR) Natural Resources Management (NRM) region at 30 m resolution. Eleven Landsat images (four Landsat-7 ETM+ and seven Landsat-5 TM images) were chosen for analysis, one each from January or February from 2000 to 2010 inclusive. The Normalized Difference Vegetation Index (NDVI) was calculated for each image. During these summer months the contrast in NDVI between dry pasture and weedy grasses and green perennial shrubs and trees can best be detected: most of the revegetation comprises these perennial indigenous species. We analysed the trends in NDVI, using a linear regression to evaluate the slope of NDVI in the period 2000- 2010. The 10 year trend analysis shows potential to detect changes at the scale of the entire AMLR NRM area of almost a million hectares. Comparison of Landsat NDVI trends with known revegetation patches showed that these increases are not detectable after one year, but both native revegetation and dense forestry plantations were demonstrated to be detectable within 5 years of planting. Revegetation in small linear sections (e.g. along creeks or roadsides) remains obscured.|
|Keywords:||Trend analysis; revegetation; modelling; linear regression|
|Rights:||Copyright status unknown|
|Appears in Collections:||Earth and Environmental Sciences publications|
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