Data

Australian Drought Monitor

University of Southern Queensland
Cobon, David ; Gacenga, Francis ; An-Vo, Duc-Anh ; Pudmenzky, Christa ; Nguyen-Huy, Thong ; Stone, Roger ; Guillory, Laura ; McCulloch, Jillian ; Svoboda, M. ; Swigart, J. ; Meat & Livestock Australia, Meat & Livestock Australia ; Pudmenzky, Christa
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ctx_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rfr_id=info%3Asid%2FANDS&rft_id=info:doi10.26192/dmek-v625&rft.title=Australian Drought Monitor&rft.identifier=http://doi.org/10.26192/dmek-v625&rft.description=Drought is one of the most severe natural disasters Australia faces, inflicting serious impacts on the agricultural industry. An Australia-wide drought monitor is being developed to provide detailed and timely data regarding drought conditions that will aid producers and policy makers alike. The Drought Monitor development is an integral part of the Northern Australia Climate Program (NACP),a major partnership between Meat & Livestock Australia, the Queensland Government and the University of Southern Queensland. The Australian Drought Monitor is based on the U.S. Drought Monitor (USDM) concept, which was developed by Mark Svoboda and his team at the National Drought Mitigation Center at the University of Nebraska-Lincoln in the late 1990s. The Composite Drought Indicator (CDI) used for the NACP project is a scaled down version of the U.S. Drought Monitor, using only four selected indices. While the U.S. Drought Monitor depends on observations from more than 350 contributors around the U.S, the Australian Drought Monitor is designed to limit the impact of human opinion on its results. The CDI is based on the combination of four different indices/indicators: 3-month Standard Precipitation Index (SPI), Soil Moisture (SM), Evapotranspiration (ET) and normalised Difference Vegetation Index (NDVI). Each dataset is percentile ranked over a baseline period and the results combined using a weighted average. Principal Component Analysis (PCA) is used to determine the optimal weighting for the CDI for each grid cell for every month over Australia.&rft.creator=Cobon, David &rft.creator=Gacenga, Francis &rft.creator=An-Vo, Duc-Anh &rft.creator=Pudmenzky, Christa &rft.creator=Nguyen-Huy, Thong &rft.creator=Stone, Roger &rft.creator=Guillory, Laura &rft.creator=McCulloch, Jillian &rft.creator=Svoboda, M. &rft.creator=Swigart, J. &rft.creator=Meat & Livestock Australia, Meat & Livestock Australia &rft.creator=Pudmenzky, Christa &rft.date=2022&rft.coverage=Australian Continent&rft_rights=https://creativecommons.org/licenses/by/4.0/&rft_subject=Drought; Standard Precipitation Index; Soil Moisture, Evapotranspiration; Normalised Difference vegetation Index; Principal Component Analysis&rft.type=dataset&rft.language=English Access the data

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Drought is one of the most severe natural disasters Australia faces, inflicting serious impacts on the agricultural industry. An Australia-wide drought monitor is being developed to provide detailed and timely data regarding drought conditions that will aid producers and policy makers alike. The Drought Monitor development is an integral part of the Northern Australia Climate Program (NACP),a major partnership between Meat & Livestock Australia, the Queensland Government and the University of Southern Queensland. The Australian Drought Monitor is based on the U.S. Drought Monitor (USDM) concept, which was developed by Mark Svoboda and his team at the National Drought Mitigation Center at the University of Nebraska-Lincoln in the late 1990s. The Composite Drought Indicator (CDI) used for the NACP project is a scaled down version of the U.S. Drought Monitor, using only four selected indices. While the U.S. Drought Monitor depends on observations from more than 350 contributors around the U.S, the Australian Drought Monitor is designed to limit the impact of human opinion on its results. The CDI is based on the combination of four different indices/indicators: 3-month Standard Precipitation Index (SPI), Soil Moisture (SM), Evapotranspiration (ET) and normalised Difference Vegetation Index (NDVI). Each dataset is percentile ranked over a baseline period and the results combined using a weighted average. Principal Component Analysis (PCA) is used to determine the optimal weighting for the CDI for each grid cell for every month over Australia.

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text: Australian Continent

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