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Canberra ACT 2601 Australia 1300 363 400 easi-help@csiro.au none none 1 512 512 text/xml image/png application/json text/html XML EPSG:3857 EPSG:4326 EPSG:3577 EPSG:3111 EPSG:32756 WIKID:102171 fwdet_4_1_monthly FWDET MDB Flood Depth V4.1 [Monthly] [Landsat and Sentinel-2] australia time-series coast land novasar easi satellite water sentinel landsat 138.56 152.5000264 -37.6801216 -24.57 2016-01-01,2016-02-01,2016-03-01,2016-04-01,2016-05-01,2016-06-01,2016-07-01,2016-08-01,2016-09-01,2016-10-01,2016-11-01,2016-12-01,2017-01-01,2017-02-01,2017-03-01,2017-04-01,2017-05-01,2017-06-01,2017-07-01,2017-08-01,2017-09-01,2017-10-01,2017-11-01,2017-12-01,2018-01-01,2018-02-01,2018-03-01,2018-04-01,2018-05-01,2018-06-01,2018-07-01,2018-08-01,2018-09-01,2018-10-01,2018-11-01,2018-12-01,2019-01-01,2019-02-01,2019-03-01,2019-04-01,2019-05-01,2019-06-01,2019-07-01,2019-08-01,2019-09-01,2019-10-01,2019-11-01,2019-12-01,2020-01-01,2020-02-01,2020-03-01,2020-04-01,2020-05-01,2020-06-01,2020-07-01,2020-08-01,2020-09-01,2020-10-01,2020-11-01,2020-12-01,2021-01-01,2021-02-01,2021-03-01,2021-04-01,2021-05-01,2021-06-01,2021-07-01,2021-08-01,2021-09-01,2021-10-01,2021-11-01,2021-12-01,2022-01-01,2022-02-01,2022-03-01,2022-04-01,2022-05-01,2022-06-01,2022-07-01,2022-08-01,2022-09-01,2022-10-01,2022-11-01,2022-12-01,2023-01-01,2023-02-01,2023-03-01,2023-04-01,2023-05-01,2023-06-01,2023-07-01,2023-08-01,2023-09-01,2023-10-01,2023-11-01,2023-12-01,2024-01-01,2024-02-01,2024-03-01,2024-04-01,2024-05-01,2024-06-01 fwdet_4_1_bimonthly FWDET MDB Flood Depth V4.1 [Bimonthly] [Landsat] australia time-series coast land novasar easi satellite water sentinel landsat 138.56 152.5000264 -37.6801216 -24.57 1988-01-01,1988-03-01,1988-05-01,1988-07-01,1988-09-01,1988-11-01,1989-01-01,1989-03-01,1989-05-01,1989-07-01,1989-09-01,1989-11-01,1990-01-01,1990-03-01,1990-05-01,1990-07-01,1990-09-01,1990-11-01,1991-01-01,1991-03-01,1991-05-01,1991-07-01,1991-09-01,1991-11-01,1992-01-01,1992-03-01,1992-05-01,1992-07-01,1992-09-01,1992-11-01,1993-01-01,1993-03-01,1993-05-01,1993-07-01,1993-09-01,1993-11-01,1994-01-01,1994-03-01,1994-05-01,1994-07-01,1994-09-01,1994-11-01,1995-01-01,1995-03-01,1995-05-01,1995-07-01,1995-09-01,1995-11-01,1996-01-01,1996-03-01,1996-05-01,1996-07-01,1996-09-01,1996-11-01,1997-01-01,1997-03-01,1997-05-01,1997-07-01,1997-09-01,1997-11-01,1998-01-01,1998-03-01,1998-05-01,1998-07-01,1998-09-01,1998-11-01,1999-01-01,1999-03-01,1999-05-01,1999-07-01,1999-09-01,1999-11-01,2000-01-01,2000-03-01,2000-05-01,2000-07-01,2000-09-01,2000-11-01,2001-01-01,2001-03-01,2001-05-01,2001-07-01,2001-09-01,2001-11-01,2002-01-01,2002-03-01,2002-05-01,2002-07-01,2002-09-01,2002-11-01,2003-01-01,2003-03-01,2003-05-01,2003-07-01,2003-09-01,2003-11-01,2004-01-01,2004-03-01,2004-05-01,2004-07-01,2004-09-01,2004-11-01,2005-01-01,2005-03-01,2005-05-01,2005-07-01,2005-09-01,2005-11-01,2006-01-01,2006-03-01,2006-05-01,2006-07-01,2006-09-01,2006-11-01,2007-01-01,2007-03-01,2007-05-01,2007-07-01,2007-09-01,2007-11-01,2008-01-01,2008-03-01,2008-05-01,2008-07-01,2008-09-01,2008-11-01,2009-01-01,2009-03-01,2009-05-01,2009-07-01,2009-09-01,2009-11-01,2010-01-01,2010-03-01,2010-05-01,2010-07-01,2010-09-01,2010-11-01,2011-01-01,2011-03-01,2011-05-01,2011-07-01,2011-09-01,2011-11-01,2012-01-01,2012-03-01,2012-05-01,2012-07-01,2012-09-01,2012-11-01,2013-01-01,2013-03-01,2013-05-01,2013-07-01,2013-09-01,2013-11-01,2014-01-01,2014-03-01,2014-05-01,2014-07-01,2014-09-01,2014-11-01,2015-01-01,2015-03-01,2015-05-01,2015-07-01,2015-09-01,2015-11-01,2016-01-01,2016-03-01,2016-05-01,2016-07-01,2016-09-01,2016-11-01,2017-01-01,2017-03-01,2017-05-01,2017-07-01,2017-09-01,2017-11-01,2018-01-01,2018-03-01,2018-05-01,2018-07-01,2018-09-01,2018-11-01,2019-01-01,2019-03-01,2019-05-01,2019-07-01,2019-09-01,2019-11-01,2020-01-01,2020-03-01,2020-05-01,2020-07-01,2020-09-01,2020-11-01,2021-01-01,2021-03-01,2021-05-01,2021-07-01,2021-09-01,2021-11-01,2022-01-01,2022-03-01,2022-05-01,2022-07-01,2022-09-01,2022-11-01,2023-01-01,2023-03-01,2023-05-01,2023-07-01,2023-09-01,2023-11-01,2024-01-01,2024-03-01,2024-05-01 Ground Cover products, Australia EPSG:3857 EPSG:4326 EPSG:3577 EPSG:3111 EPSG:32756 WIKID:102171 Landsat/Sentinel-2 Monthly Medoid Australian Surface Reflectance at 30m ls_s2_sr_rgb Landsat/Sentinel-2, CSIRO Environment algorithm, Australian coverage. Jan 2016 -> present. Monthly Surface Reflectance (unprocessed RGB colour composite). This product is the result of blending available cloud masked Landsat and Sentinel-2 Surface Reflectance using a medoid method into a monthly product. Landsat tiles are masked using the fmask cloud mask and Sentinel-2 tiles are masked using the s2cloudless cloud mask. This product is therefore derived from the following products: Geoscience Australia Landsat 5 Thematic Mapper Analysis Ready Data Collection 3, Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Thematic Mapper Analysis Ready Data Collection 3, Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3, Geoscience Australia Sentinel-2A MSI Analysis Ready Data Collection 3 and Sentinel-2B MSI Analysis Ready Data Collection 3. australia time-series coast land novasar easi satellite water sentinel landsat 112.92099708073 153.638585626237 -43.8607428635722 -9.50379705028454 2016-01-01,2016-02-01,2016-03-01,2016-04-01,2016-05-01,2016-06-01,2016-07-01,2016-08-01,2016-09-01,2016-10-01,2016-11-01,2016-12-01,2017-01-01,2017-02-01,2017-03-01,2017-04-01,2017-05-01,2017-06-01,2017-07-01,2017-08-01,2017-09-01,2017-10-01,2017-11-01,2017-12-01,2018-01-01,2018-02-01,2018-03-01,2018-04-01,2018-05-01,2018-06-01,2018-07-01,2018-08-01,2018-09-01,2018-10-01,2018-11-01,2018-12-01,2019-01-01,2019-02-01,2019-03-01,2019-04-01,2019-05-01,2019-06-01,2019-07-01,2019-08-01,2019-09-01,2019-10-01,2019-11-01,2019-12-01,2020-01-01,2020-02-01,2020-03-01,2020-04-01,2020-05-01,2020-06-01,2020-07-01,2020-08-01,2020-09-01,2020-10-01,2020-11-01,2020-12-01,2021-01-01,2021-02-01,2021-03-01,2021-04-01,2021-05-01,2021-06-01,2021-07-01,2021-08-01,2021-09-01,2021-10-01,2021-11-01,2021-12-01,2022-01-01,2022-02-01,2022-03-01,2022-04-01,2022-05-01,2022-06-01,2022-07-01,2022-08-01,2022-09-01,2022-10-01,2022-11-01,2022-12-01,2023-01-01,2023-02-01,2023-03-01,2023-04-01,2023-05-01,2023-06-01,2023-07-01,2023-08-01,2023-09-01,2023-10-01,2023-11-01,2023-12-01,2024-01-01,2024-02-01,2024-03-01,2024-04-01,2024-05-01,2024-06-01,2024-07-01,2024-08-01,2024-09-01,2024-10-01,2024-11-01,2024-12-01,2025-01-01,2025-02-01,2025-03-01,2025-04-01,2025-05-01,2025-06-01,2025-07-01,2025-08-01,2025-09-01,2025-10-01,2025-11-01,2025-12-01,2026-01-01,2026-02-01 Landsat/Sentinel-2 Monthly Australian Vegetation Cover at 30m ls_s2_fc_tc Landsat/Sentinel-2, CSIRO Environment algorithm, Australian coverage. Jan 2016 -> present. Monthly - Total Vegetation Cover represents the proportion of ground covered by vegetation of any type. This includes photosynthetically active plant material (which is typically green leaves) as well as non-photosynthetically active plant material (dead/senesced leaves, bark, twigs and branches – all either standing or fallen).The sum of Total Vegetation Cover and Bare Soil is 100%. In forested canopies the photosynthetic and non-photosynthetic portions of trees may obscure those of the lower layers and the surface layer (including any bare soil). The monthly Landsat/Sentinel-2 Vegetation Fractional Cover product on which this product is based is the result of blending cloud-masked Landsat and Sentinel-2 Surface Reflectance using a medoid method and applying a waterbody mask before computing fractional cover from the blended surface reflectance. Landsat tiles are masked using the fmask cloud mask and Sentinel-2 tiles are masked using the s2cloudless cloud mask. Waterbodies are masked using GA Landsat Waterbodies Collection 3 (V2). This product is therefore derived from the following products: Geoscience Australia Landsat 5 Thematic Mapper Analysis Ready Data Collection 3, Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Thematic Mapper Analysis Ready Data Collection 3, Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3, Geoscience Australia Sentinel-2A MSI Analysis Ready Data Collection 3, Sentinel-2B MSI Analysis Ready Data Collection 3 and Geoscience Australia Landsat Waterbodies Collection 3 (V2). australia time-series coast land novasar easi satellite water sentinel landsat 112.92099708073 153.638585626237 -43.8607428635722 -9.50370500904841 2016-01-01,2016-02-01,2016-03-01,2016-04-01,2016-05-01,2016-06-01,2016-07-01,2016-08-01,2016-09-01,2016-10-01,2016-11-01,2016-12-01,2017-01-01,2017-02-01,2017-03-01,2017-04-01,2017-05-01,2017-06-01,2017-07-01,2017-08-01,2017-09-01,2017-10-01,2017-11-01,2017-12-01,2018-01-01,2018-02-01,2018-03-01,2018-04-01,2018-05-01,2018-06-01,2018-07-01,2018-08-01,2018-09-01,2018-10-01,2018-11-01,2018-12-01,2019-01-01,2019-02-01,2019-03-01,2019-04-01,2019-05-01,2019-06-01,2019-07-01,2019-08-01,2019-09-01,2019-10-01,2019-11-01,2019-12-01,2020-01-01,2020-02-01,2020-03-01,2020-04-01,2020-05-01,2020-06-01,2020-07-01,2020-08-01,2020-09-01,2020-10-01,2020-11-01,2020-12-01,2021-01-01,2021-02-01,2021-03-01,2021-04-01,2021-05-01,2021-06-01,2021-07-01,2021-08-01,2021-09-01,2021-10-01,2021-11-01,2021-12-01,2022-01-01,2022-02-01,2022-03-01,2022-04-01,2022-05-01,2022-06-01,2022-07-01,2022-08-01,2022-09-01,2022-10-01,2022-11-01,2022-12-01,2023-01-01,2023-02-01,2023-03-01,2023-04-01,2023-05-01,2023-06-01,2023-07-01,2023-08-01,2023-09-01,2023-10-01,2023-11-01,2023-12-01,2024-01-01,2024-02-01,2024-03-01,2024-04-01,2024-05-01,2024-06-01,2024-07-01,2024-08-01,2024-09-01,2024-10-01,2024-11-01,2024-12-01,2025-01-01,2025-02-01,2025-03-01,2025-04-01,2025-05-01,2025-06-01,2025-07-01,2025-08-01,2025-09-01,2025-10-01,2025-11-01,2025-12-01,2026-01-01,2026-02-01 ls_s2_fc_rgb Landsat/Sentinel-2, CSIRO Environment algorithm, Australian coverage. Jan 2016 -> present. Monthly - Vegetation Fractional Cover represents the exposed proportion of Photosynthetic Vegetation (PV), Non-Photosynthetic Vegetation (NPV) and Bare Soil (BS) within each pixel. The sum of the three fractions is 100% (+/- 3%) and shown in Red/Green/Blue colours. In forested canopies the photosynthetic or non-photosynthetic portions of trees may obscure those of the grass layer and/or bare soil. This product is the result of blending cloud masked Landsat and Sentinel-2 Surface Reflectance using a medoid method and applying a waterbody mask before computing fractional cover from the blended surface reflectance. Landsat tiles are masked using the fmask cloud mask and Sentinel-2 tiles are masked using the s2cloudless cloud mask. Waterbodies are masked using GA Landsat Waterbodies Collection 3 (V2). This product is therefore derived from the following products: Geoscience Australia Landsat 5 Thematic Mapper Analysis Ready Data Collection 3, Geoscience Australia Landsat 7 Enhanced Thematic Mapper Plus Thematic Mapper Analysis Ready Data Collection 3, Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3, Geoscience Australia Sentinel-2A MSI Analysis Ready Data Collection 3, Sentinel-2B MSI Analysis Ready Data Collection 3 and Geoscience Australia Landsat Waterbodies Collection 3 (V2). australia time-series coast land novasar easi satellite water sentinel landsat 112.92099708073 153.638585626237 -43.8607428635722 -9.50370500904841 2016-01-01,2016-02-01,2016-03-01,2016-04-01,2016-05-01,2016-06-01,2016-07-01,2016-08-01,2016-09-01,2016-10-01,2016-11-01,2016-12-01,2017-01-01,2017-02-01,2017-03-01,2017-04-01,2017-05-01,2017-06-01,2017-07-01,2017-08-01,2017-09-01,2017-10-01,2017-11-01,2017-12-01,2018-01-01,2018-02-01,2018-03-01,2018-04-01,2018-05-01,2018-06-01,2018-07-01,2018-08-01,2018-09-01,2018-10-01,2018-11-01,2018-12-01,2019-01-01,2019-02-01,2019-03-01,2019-04-01,2019-05-01,2019-06-01,2019-07-01,2019-08-01,2019-09-01,2019-10-01,2019-11-01,2019-12-01,2020-01-01,2020-02-01,2020-03-01,2020-04-01,2020-05-01,2020-06-01,2020-07-01,2020-08-01,2020-09-01,2020-10-01,2020-11-01,2020-12-01,2021-01-01,2021-02-01,2021-03-01,2021-04-01,2021-05-01,2021-06-01,2021-07-01,2021-08-01,2021-09-01,2021-10-01,2021-11-01,2021-12-01,2022-01-01,2022-02-01,2022-03-01,2022-04-01,2022-05-01,2022-06-01,2022-07-01,2022-08-01,2022-09-01,2022-10-01,2022-11-01,2022-12-01,2023-01-01,2023-02-01,2023-03-01,2023-04-01,2023-05-01,2023-06-01,2023-07-01,2023-08-01,2023-09-01,2023-10-01,2023-11-01,2023-12-01,2024-01-01,2024-02-01,2024-03-01,2024-04-01,2024-05-01,2024-06-01,2024-07-01,2024-08-01,2024-09-01,2024-10-01,2024-11-01,2024-12-01,2025-01-01,2025-02-01,2025-03-01,2025-04-01,2025-05-01,2025-06-01,2025-07-01,2025-08-01,2025-09-01,2025-10-01,2025-11-01,2025-12-01,2026-01-01,2026-02-01 MODIS Accumulated Antecedent Rainfall, Australia, Monthly, ~500m modis_fc_ante_rain_anom_conf MODIS Accumulated Antecedent Rainfall Anomaly Confidence, Australian coverage. Jan 2001 -> present. This layer shows if the monthly total cover of a pixel has a high (95%) anomaly for the accumulated antecedent precipitation (AAP) it has received. That is, is the cover present above (upper 95% confidence interval) or below (lower 95% confidence interval) what would be expected for the AAP of the pixel? AAP is determined for each pixel by testing monthly accumulation (1–60 months) of rainfall for each month (January to December) since 2001, plotted against total vegetative cover (described below). NOTE: Jan-2001 to Dec-2022 uses MODIS FC based on MCD43A4v006 whereas Jan-2023 to present uses MODIS FC based on MCD43A4v061. MODIS FC data prior to January 2023 will be progressively reprocessed with v6.1. After running all regressions, the accumulation period with the highest R2 is chosen for the pixel. Pixels with High confidence have R2 above 0.7, Medium confidence: 0.5 - 0.7 and Low confidence: below 0.5. The previous research of Guerschman et al. 2020 reported the photosynthetic (PV) and non-photosynthetic vegetation (NPV) fractions with AAP. This layer uses the same method but sums PV and NPV to give a total vegetation cover (Ftot) output. Reference Guerschman, J.P., Hill, M.J., Leys, J., and Heidenreich, S. (2020). Vegetation cover dependence on accumulated antecedent precipitation in Australia: Relationships with photosynthetic and non-photosynthetic vegetation fractions. Remote Sensing of Environment 240, 111670. doi:https://doi.org/10.1016/j.rse.2020.111670 australia time-series coast land novasar easi satellite water sentinel landsat 112.912273741684 153.63513 -43.6350767593232 -10.0 2001-01-01,2001-02-01,2001-03-01,2001-04-01,2001-05-01,2001-06-01,2001-07-01,2001-08-01,2001-09-01,2001-10-01,2001-11-01,2001-12-01,2002-01-01,2002-02-01,2002-03-01,2002-04-01,2002-05-01,2002-06-01,2002-07-01,2002-08-01,2002-09-01,2002-10-01,2002-11-01,2002-12-01,2003-01-01,2003-02-01,2003-03-01,2003-04-01,2003-05-01,2003-06-01,2003-07-01,2003-08-01,2003-09-01,2003-10-01,2003-11-01,2003-12-01,2004-01-01,2004-02-01,2004-03-01,2004-04-01,2004-05-01,2004-06-01,2004-07-01,2004-08-01,2004-09-01,2004-10-01,2004-11-01,2004-12-01,2005-01-01,2005-02-01,2005-03-01,2005-04-01,2005-05-01,2005-06-01,2005-07-01,2005-08-01,2005-09-01,2005-10-01,2005-11-01,2005-12-01,2006-01-01,2006-02-01,2006-03-01,2006-04-01,2006-05-01,2006-06-01,2006-07-01,2006-08-01,2006-09-01,2006-10-01,2006-11-01,2006-12-01,2007-01-01,2007-02-01,2007-03-01,2007-04-01,2007-05-01,2007-06-01,2007-07-01,2007-08-01,2007-09-01,2007-10-01,2007-11-01,2007-12-01,2008-01-01,2008-02-01,2008-03-01,2008-04-01,2008-05-01,2008-06-01,2008-07-01,2008-08-01,2008-09-01,2008-10-01,2008-11-01,2008-12-01,2009-01-01,2009-02-01,2009-03-01,2009-04-01,2009-05-01,2009-06-01,2009-07-01,2009-08-01,2009-09-01,2009-10-01,2009-11-01,2009-12-01,2010-01-01,2010-02-01,2010-03-01,2010-04-01,2010-05-01,2010-06-01,2010-07-01,2010-08-01,2010-09-01,2010-10-01,2010-11-01,2010-12-01,2011-01-01,2011-02-01,2011-03-01,2011-04-01,2011-05-01,2011-06-01,2011-07-01,2011-08-01,2011-09-01,2011-10-01,2011-11-01,2011-12-01,2012-01-01,2012-02-01,2012-03-01,2012-04-01,2012-05-01,2012-06-01,2012-07-01,2012-08-01,2012-09-01,2012-10-01,2012-11-01,2012-12-01,2013-01-01,2013-02-01,2013-03-01,2013-04-01,2013-05-01,2013-06-01,2013-07-01,2013-08-01,2013-09-01,2013-10-01,2013-11-01,2013-12-01,2014-01-01,2014-02-01,2014-03-01,2014-04-01,2014-05-01,2014-06-01,2014-07-01,2014-08-01,2014-09-01,2014-10-01,2014-11-01,2014-12-01,2015-01-01,2015-02-01,2015-03-01,2015-04-01,2015-05-01,2015-06-01,2015-07-01,2015-08-01,2015-09-01,2015-10-01,2015-11-01,2015-12-01,2016-01-01,2016-02-01,2016-03-01,2016-04-01,2016-05-01,2016-06-01,2016-07-01,2016-08-01,2016-09-01,2016-10-01,2016-11-01,2016-12-01,2017-01-01,2017-02-01,2017-03-01,2017-04-01,2017-05-01,2017-06-01,2017-07-01,2017-08-01,2017-09-01,2017-10-01,2017-11-01,2017-12-01,2018-01-01,2018-02-01,2018-03-01,2018-04-01,2018-05-01,2018-06-01,2018-07-01,2018-08-01,2018-09-01,2018-10-01,2018-11-01,2018-12-01,2019-01-01,2019-02-01,2019-03-01,2019-04-01,2019-05-01,2019-06-01,2019-07-01,2019-08-01,2019-09-01,2019-10-01,2019-11-01,2019-12-01,2020-01-01,2020-02-01,2020-03-01,2020-04-01,2020-05-01,2020-06-01,2020-07-01,2020-08-01,2020-09-01,2020-10-01,2020-11-01,2020-12-01,2021-01-01,2021-02-01,2021-03-01,2021-04-01,2021-05-01,2021-06-01,2021-07-01,2021-08-01,2021-09-01,2021-10-01,2021-11-01,2021-12-01,2022-01-01,2022-02-01,2022-03-01,2022-04-01,2022-05-01,2022-06-01,2022-07-01,2022-08-01,2022-09-01,2022-10-01,2022-11-01,2022-12-01,2023-01-01,2023-02-01,2023-03-01,2023-04-01,2023-05-01,2023-06-01,2023-07-01,2023-08-01,2023-09-01,2023-10-01,2023-11-01,2023-12-01,2024-01-01,2024-02-01,2024-03-01,2024-04-01,2024-05-01,2024-06-01,2024-07-01,2024-08-01,2024-09-01,2024-10-01,2024-11-01,2024-12-01,2025-01-01,2025-02-01,2025-03-01,2025-04-01,2025-05-01,2025-06-01,2025-07-01,2025-08-01,2025-09-01,2025-10-01,2025-11-01,2025-12-01,2026-01-01,2026-02-01 Surface Energy Balance, Australia EPSG:3857 EPSG:4326 EPSG:3577 EPSG:3111 EPSG:32756 WIKID:102171 MODIS Surface Energy Balance, Monthly, Australian at ~500m modis_seb_ae MODIS Surface Energy Balance Actual Evapotranspiration, Australian coverage. Mar 2000 -> May 2023. australia time-series coast land novasar easi satellite water sentinel landsat 112.0 154.0 -44.0 -10.0 2000-03-01,2000-04-01,2000-05-01,2000-06-01,2000-07-01,2000-08-01,2000-09-01,2000-10-01,2000-11-01,2000-12-01,2001-01-01,2001-02-01,2001-03-01,2001-04-01,2001-05-01,2001-06-01,2001-07-01,2001-08-01,2001-09-01,2001-10-01,2001-11-01,2001-12-01,2002-01-01,2002-02-01,2002-03-01,2002-04-01,2002-05-01,2002-06-01,2002-07-01,2002-08-01,2002-09-01,2002-10-01,2002-11-01,2002-12-01,2003-01-01,2003-02-01,2003-03-01,2003-04-01,2003-05-01,2003-06-01,2003-07-01,2003-08-01,2003-09-01,2003-10-01,2003-11-01,2003-12-01,2004-01-01,2004-02-01,2004-03-01,2004-04-01,2004-05-01,2004-06-01,2004-07-01,2004-08-01,2004-09-01,2004-10-01,2004-11-01,2004-12-01,2005-01-01,2005-02-01,2005-03-01,2005-04-01,2005-05-01,2005-06-01,2005-07-01,2005-08-01,2005-09-01,2005-10-01,2005-11-01,2005-12-01,2006-01-01,2006-02-01,2006-03-01,2006-04-01,2006-05-01,2006-06-01,2006-07-01,2006-08-01,2006-09-01,2006-10-01,2006-11-01,2006-12-01,2007-01-01,2007-02-01,2007-03-01,2007-04-01,2007-05-01,2007-06-01,2007-07-01,2007-08-01,2007-09-01,2007-10-01,2007-11-01,2007-12-01,2008-01-01,2008-02-01,2008-03-01,2008-04-01,2008-05-01,2008-06-01,2008-07-01,2008-08-01,2008-09-01,2008-10-01,2008-11-01,2008-12-01,2009-01-01,2009-02-01,2009-03-01,2009-04-01,2009-05-01,2009-06-01,2009-07-01,2009-08-01,2009-09-01,2009-10-01,2009-11-01,2009-12-01,2010-01-01,2010-02-01,2010-03-01,2010-04-01,2010-05-01,2010-06-01,2010-07-01,2010-08-01,2010-09-01,2010-10-01,2010-11-01,2010-12-01,2011-01-01,2011-02-01,2011-03-01,2011-04-01,2011-05-01,2011-06-01,2011-07-01,2011-08-01,2011-09-01,2011-10-01,2011-11-01,2011-12-01,2012-01-01,2012-02-01,2012-03-01,2012-04-01,2012-05-01,2012-06-01,2012-07-01,2012-08-01,2012-09-01,2012-10-01,2012-11-01,2012-12-01,2013-01-01,2013-02-01,2013-03-01,2013-04-01,2013-05-01,2013-06-01,2013-07-01,2013-08-01,2013-09-01,2013-10-01,2013-11-01,2013-12-01,2014-01-01,2014-02-01,2014-03-01,2014-04-01,2014-05-01,2014-06-01,2014-07-01,2014-08-01,2014-09-01,2014-10-01,2014-11-01,2014-12-01,2015-01-01,2015-02-01,2015-03-01,2015-04-01,2015-05-01,2015-06-01,2015-07-01,2015-08-01,2015-09-01,2015-10-01,2015-11-01,2015-12-01,2016-01-01,2016-02-01,2016-03-01,2016-04-01,2016-05-01,2016-06-01,2016-07-01,2016-08-01,2016-09-01,2016-10-01,2016-11-01,2016-12-01,2017-01-01,2017-02-01,2017-03-01,2017-04-01,2017-05-01,2017-06-01,2017-07-01,2017-08-01,2017-09-01,2017-10-01,2017-11-01,2017-12-01,2018-01-01,2018-02-01,2018-03-01,2018-04-01,2018-05-01,2018-06-01,2018-07-01,2018-08-01,2018-09-01,2018-10-01,2018-11-01,2018-12-01,2019-01-01,2019-02-01,2019-03-01,2019-04-01,2019-05-01,2019-06-01,2019-07-01,2019-08-01,2019-09-01,2019-10-01,2019-11-01,2019-12-01,2020-01-01,2020-02-01,2020-03-01,2020-04-01,2020-05-01,2020-06-01,2020-07-01,2020-08-01,2020-09-01,2020-10-01,2020-11-01,2020-12-01,2021-01-01,2021-02-01,2021-03-01,2021-04-01,2021-05-01,2021-06-01,2021-07-01,2021-08-01,2021-09-01,2021-10-01,2021-11-01,2021-12-01,2022-01-01,2022-02-01,2022-03-01,2022-04-01,2022-05-01,2022-06-01,2022-07-01,2022-08-01,2022-09-01,2022-10-01,2022-11-01,2022-12-01,2023-01-01,2023-02-01,2023-03-01,2023-04-01,2023-05-01 modis_seb_h MODIS Surface Energy Balance Sensible Heat Flux, Australian coverage. Mar 2000 -> May 2023. australia time-series coast land novasar easi satellite water sentinel landsat 112.0 154.0 -44.0 -10.0 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Advanced Very High Resolution Radiometer (AVHRR), Australia/New Zealand EPSG:3857 EPSG:4326 EPSG:3577 EPSG:3111 EPSG:32756 WIKID:102171 Advanced Very High Resolution Radiometer (AVHRR), TOA Stitched, Australia/New Zealand at ~0.01deg avhrr_toa_pseudo Advanced Very High Resolution Radiometer (AVHRR), TOA Stitched, Pseudo Colour RGB (NREF2, NREF2, NREF1), Australia/New Zealand coverage. australia time-series coast land novasar easi satellite water sentinel landsat 89.995 180.005 -60.005 5.005 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NovaSAR Mosaic, Australia EPSG:3857 EPSG:4326 EPSG:3577 EPSG:3111 EPSG:32756 WIKID:102171 NovaSAR Backscatter (gamma0) Australian Mosaic v2023 ns_mosaic_nofill The NovaSAR-1 Australia National Mosaic is an amalgamation of 349 NovaSAR-1 S-band radar images acquired between 2020 and 2023 in tri-polarisation mode (HH, VV, HV) from descending-pass orbits. The procedure used in generating the mosaic is documented in https://research.csiro.au/cceo/wp-content/uploads/sites/252/2024/11/NovaSAR-1_Mosaic_Procedure_1.0.pdf. CSIRO does not recommend the NovaSAR-1 Australia National Mosaic for detailed quantitative analysis, but rather as a qualitative reconnaissance product for exploring relative variations of S-band radar backscatter across large spatial areas in Australia. australia time-series coast land novasar easi satellite water sentinel landsat 112.91 153.65 -43.7502 -9.0 ns_mosaic_fill The NovaSAR-1 Australia National Mosaic is an amalgamation of 349 NovaSAR-1 S-band radar images acquired between 2020 and 2023 in tri-polarisation mode (HH, VV, HV) from descending-pass orbits. The procedure used in generating the mosaic is documented in https://research.csiro.au/cceo/wp-content/uploads/sites/252/2024/11/NovaSAR-1_Mosaic_Procedure_1.0.pdf. CSIRO does not recommend the NovaSAR-1 Australia National Mosaic for detailed quantitative analysis, but rather as a qualitative reconnaissance product for exploring relative variations of S-band radar backscatter across large spatial areas in Australia. This version of the mosaic is gap-filled with Sentinel-1. australia time-series coast land novasar easi satellite water sentinel landsat 112.91 153.65 -43.7502 -9.0 Ecosystem Condition, Australia EPSG:3857 EPSG:4326 EPSG:3577 EPSG:3111 EPSG:32756 WIKID:102171 ecosystem_condition The ecosystem condition maps for terrestrial ecosystems of Australia annually were compiled with the FACTE framework (Yang et al. in submission). These maps provide a way to identify the temporal change in ecosystem condition from the natural dynamics of ecosystems and the spatial change from alternative natural states of ecosystems. The maps show annual ecosystem condition scores at 100m resolution for Australia (2013–2022). Each pixel is compared to environmentally similar training sites with known conditions using 16 Landsat-derived variables describing ecosystem structure, composition, and function. Environmental similarity is based on ten variables linked to vascular plant biodiversity. A probability of good condition is estimated and converted to a score from 0 (complete biodiversity loss) to 100 (full biodiversity capacity). Methods are detailed in Yang et al. (in submission) and in the code provided in Yang et al. (2024). Reference: Yang et al. (in submission) A framework for dynamic assessments of terrestrial ecosystem condition. Yang et al. (2024) FACTE: A framework for dynamic assessments of terrestrial ecosystem condition. https://data.csiro.au/collection/csiro:62663 australia time-series coast land novasar easi satellite water sentinel landsat 112.99189307 153.636168896507 -43.64285145 -10.0180120181347 2013-01-01,2014-01-01,2015-01-01,2016-01-01,2017-01-01,2018-01-01,2019-01-01,2020-01-01,2021-01-01,2022-01-01 OzTreeMap, Australia EPSG:3857 EPSG:4326 EPSG:3577 EPSG:3111 EPSG:32756 WIKID:102171 Australian-calibrated Canopy Height data oztreemap_chm_best_pick This dataset is part of the OzTreeMap project and provides two new 30 m spatial resolution canopy height products for continental Australia: (1) the best-pick canopy height model; and (2) the median canopy height model. Both products were generated and validated as part of the study titled “Accuracy of Machine Learning-Derived Canopy Height Models at Continental Scale.” The "Best pick CHM" is a composite model in which each 30 m pixel adopts the most accurate canopy height value among four publicly available machine learning-derived CHMs [Tolan et al. (2024), Lang et al. (2023), Potapov et al. (2021), and Liao et al. (2020)] based on the vegetation class (Scarth et al., 2019) that the pixel represents and our vegetation-specific accuracy assessment. The "Median CHM" represents a pixel-wise ensemble (median) composite of the same four CHMs and achieved the highest overall accuracy when validated against 22,967 km² of reference airborne point cloud data across 16 Australian vegetation classes. These CHMs offer improved accuracy and spatial consistency compared to the individual global products supporting continental-scale applications in forest structure monitoring, carbon accounting, and ecosystem assessment. DOI: https://hdl.handle.net/102.100.100/710836 australia time-series coast land novasar easi satellite water sentinel landsat 112.92066107303 154.098290918363 -43.7647978980696 -9.86115283407226 oztreemap_chm_median This dataset is part of the OzTreeMap project and provides two new 30 m spatial resolution canopy height products for continental Australia: (1) the best-pick canopy height model; and (2) the median canopy height model. Both products were generated and validated as part of the study titled “Accuracy of Machine Learning-Derived Canopy Height Models at Continental Scale.” The "Best pick CHM" is a composite model in which each 30 m pixel adopts the most accurate canopy height value among four publicly available machine learning-derived CHMs [Tolan et al. (2024), Lang et al. (2023), Potapov et al. (2021), and Liao et al. (2020)] based on the vegetation class (Scarth et al., 2019) that the pixel represents and our vegetation-specific accuracy assessment. The "Median CHM" represents a pixel-wise ensemble (median) composite of the same four CHMs and achieved the highest overall accuracy when validated against 22,967 km² of reference airborne point cloud data across 16 Australian vegetation classes. These CHMs offer improved accuracy and spatial consistency compared to the individual global products supporting continental-scale applications in forest structure monitoring, carbon accounting, and ecosystem assessment. DOI: https://hdl.handle.net/102.100.100/710836 australia time-series coast land novasar easi satellite water sentinel landsat 112.92066107303 154.098290918363 -43.7647978980696 -9.86115283407226