@article {BF-3090,
	title = {A simple method for field-based grassland curing assessment},
	journal = {International Journal of Wildland Fire},
	volume = {20},
	year = {2011},
	month = {2011},
	pages = {804},
	abstract = {The degree of grassland curing represents the proportion of dead material in a grassland fuel complex, expressed as a percentage. It is an important input for models to predict rate of fire spread and determine fire danger levels in grasslands. The degree of curing is currently determined in Australia and New Zealand using a combination of satellite imagery and ground-based visual observations by operational personnel. Both methods present problems. The satellite imagery technique requires updating to accommodate newer satellite technology, as well as extension and validation across all of the major grasslands in both countries. Visual assessments are often both inaccurate and spatially inadequate across the landscape. This paper describes the development of a field-based method to accurately and easily determine curing levels in the field, based on modification of an existing point quadrat method of pasture assessment. This alternative technique minimises subjective assessment by field observers, and involves tallying the number of live and dead touches on a thin steel rod driven into the ground. The average error across sites was lower for exotic improved pastures than native grasslands. Results suggest that this method can be applied across Australasia more accurately than current methods.},
	doi = {10.1071/WF10069},
	author = {Stuart AJ Anderson and Wendy R. Anderson and Jennifer J Hollis and Botha, Elizabeth J.}
}
@article {BF-2406,
	title = {Estimating fractional cover of photosynthetic vegetation, non-photosynthetic vegetation and bare soil in the Australian tropical savanna region upscaling the EO-1 Hyperion and MODIS sensors},
	journal = {Remote Sensing of Environment},
	volume = {113},
	year = {2009},
	month = {05/2009},
	pages = {928 - 945},
	abstract = {Quantitative estimation of fractional cover of photosynthetic vegetation (fPV), non-photosynthetic vegetation (fNPV) and bare soil (fBS) is critical for natural resource management and for modeling carbon dynamics. Accurate estimation of fractional cover is especially important for monitoring and modeling savanna systems, subject to highly seasonal rainfall and drought, grazing by domestic and native animals, and frequent burning. This paper describes a method for resolving fPV, fNPV and fBS across the ~ 2 million km2 Australian tropical savanna zone with hyperspectral and multispectral imagery. A spectral library compiled from field campaigns in 2005 and 2006, together with three EO-1 Hyperion scenes acquired during the 2005 growing season were used to explore the spectral response space for fPV, fNPV and fBS. A linear unmixing approach was developed using the Normalized Difference Vegetation Index (NDVI) and the Cellulose Absorption Index (CAI). Translation of this approach to MODerate resolution Imaging Spectroradiometer (MODIS) scale was assessed by comparing multiple linear regression models of NDVI and CAI with a range of indices based on the seven MODIS bands in the visible and shortwave infrared region (SWIR) using synthesized MODIS surface reflectance data on the same dates as the Hyperion acquisitions. The best resulting model, which used NDVI and the simple ratio of MODIS bands 7 and 6 (SWIR3/SWIR2), was used to generate a time series of fractional cover from 16 day MODIS nadir bidirectional reflectance distribution function-adjusted reflectance (NBAR) data from 2000{\textendash}2006. The results obtained with MODIS NBAR were validated against grass curing measurement at ten sites with good agreement at six sites, but some underestimation of fNPV proportions at four other sites due to substantial sub-pixel heterogeneity. The model was also compared with remote sensing measurements of fire scars and showed a good matching in the spatio-temporal patterns of grass senescence and posterior burning. The fractional cover profiles for major grassland cover types showed significant differences in relative proportions of fPV, fNPV and fBS, as well as large intra-annual seasonal variation in response to monsoonal rainfall gradients and soil type. The methodology proposed here can be applied to other mixed tree-grass ecosystems across the world.
},
	doi = {10.1016/j.rse.2009.01.006},
	author = {Guerschman, Juan Pablo and Hill, Michael J. and Luigi J. Renzullo and Damian J. Barrett and Marks, Alan S. and Botha, Elizabeth J.}
}
