Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels.\n\nFor these ARD products, this value comes from the Fmask algorithm.\n to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata\n\n(e.g. ‘epsg:32654’)\n:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n from:

Ground sampling distance of the sensor’s best resolution band\nin metres; represents the size (or spatial resolution) of one pixel.\n to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north\n to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon.\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm\n to (exclusive):

File format (GeoTiff, NetCDF):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres)\n to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider.\nFor Sentinel it is MGRS code.\n:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless\n to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless\n to (exclusive):

Unique identifier for a datastrip relative to a given Datatake.\n\n(e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’)\n:

ESA product URI, with the '.SAFE' ending removed.\n\n(e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845')\n:

Granule ID according to the ESA naming convention\n\n(e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’)\n:

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2015-08-30 11:36:03	ga_s2am_ard_3-2-1_50HQK_2015-08-30_final.stac-item
2015-10-20 11:05:17	ga_s2am_ard_3-2-1_52JCM_2015-10-20_final.stac-item
2015-10-22 11:38:10	ga_s2am_ard_3-2-1_50HQH_2015-10-22_final.stac-item
2015-11-22 11:12:12	ga_s2am_ard_3-2-1_51KZS_2015-11-22_final.stac-item
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_50JLS_2015-12-17_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51HWD_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51JXF_2015-12-25_final.stac-item
2015-12-25 11:27:34	ga_s2am_ard_3-2-1_51KXP_2015-12-25_final.stac-item
2016-01-06 12:05:24	ga_s2am_ard_3-2-1_50JLQ_2016-01-06_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JLT_2016-01-16_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51JTJ_2016-01-20_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JXH_2016-01-24_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_51JVG_2016-02-06_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_51JVJ_2016-02-06_final.stac-item
2016-11-19 11:19:19	ga_s2am_ard_3-2-1_51JXG_2016-11-19_final.stac-item
2016-11-26 11:10:57	ga_s2am_ard_3-2-1_52JDT_2016-11-26_final.stac-item
2016-12-09 11:21:01	ga_s2am_ard_3-2-1_51JXF_2016-12-09_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50JLM_2016-12-11_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_50JRS_2016-12-12_final.stac-item
2016-12-14 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2016-12-14_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51JTK_2016-12-15_final.stac-item
2016-12-16 11:08:59	ga_s2am_ard_3-2-1_51JXH_2016-12-16_final.stac-item
2016-12-16 11:08:59	ga_s2am_ard_3-2-1_52JET_2016-12-16_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51HVD_2016-12-22_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49JGN_2016-12-24_final.stac-item
2017-01-15 11:08:52	ga_s2am_ard_3-2-1_52JCL_2017-01-15_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_51HXE_2017-01-25_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_52JBM_2017-01-25_final.stac-item
2017-02-04 11:08:11	ga_s2am_ard_3-2-1_51JYG_2017-02-04_final.stac-item
2017-02-14 11:07:06	ga_s2am_ard_3-2-1_52JET_2017-02-14_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50KNA_2017-02-19_final.stac-item
2017-02-19 12:02:47	ga_s2am_ard_3-2-1_50KNB_2017-02-19_final.stac-item
2017-02-27 11:22:43	ga_s2am_ard_3-2-1_51JXH_2017-02-27_final.stac-item
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_51LUF_2017-09-01_final.stac-item
2018-02-28 11:38:46	ga_s2am_ard_3-2-1_51LUF_2018-02-28_final.stac-item
2019-02-04 11:14:04	ga_s2am_ard_3-2-1_52JET_2019-02-04_final.stac-item
2019-02-04 11:15:06	ga_s2am_ard_3-2-1_52JDP_2019-02-04_final.stac-item
2019-02-04 11:15:09	ga_s2am_ard_3-2-1_52JDP_2019-02-04_final.stac-item
2019-02-19 12:03:23	ga_s2am_ard_3-2-1_50KLC_2019-02-19_final.stac-item
2019-02-24 11:15:58	ga_s2am_ard_3-2-1_52JCL_2019-02-24_final.stac-item
2019-02-27 11:25:40	ga_s2am_ard_3-2-1_51JYG_2019-02-27_final.stac-item
2019-03-03 11:05:58	ga_s2am_ard_3-2-1_52JDL_2019-03-03_final.stac-item
2019-05-18 11:26:11	ga_s2am_ard_3-2-1_51JXF_2019-05-18_final.stac-item
2019-08-06 11:25:57	ga_s2am_ard_3-2-1_51JXG_2019-08-06_final.stac-item
2019-10-19 11:06:01	ga_s2am_ard_3-2-1_52JCL_2019-10-19_final.stac-item
2019-12-14 11:25:48	ga_s2am_ard_3-2-1_51JXG_2019-12-14_final.stac-item
2020-02-29 11:15:08	ga_s2am_ard_3-2-1_52JDP_2020-02-29_final.stac-item
2020-02-29 11:15:28	ga_s2am_ard_3-2-1_52JCN_2020-02-29_final.stac-item
2020-07-20 11:53:51	ga_s2am_ard_3-2-1_50KPA_2020-07-20_final.stac-item
2020-08-02 12:03:50	ga_s2am_ard_3-2-1_50KNA_2020-08-02_final.stac-item
2020-09-19 11:26:27	ga_s2am_ard_3-2-1_51HXE_2020-09-19_final.stac-item
2020-09-23 11:05:13	ga_s2am_ard_3-2-1_52JCQ_2020-09-23_final.stac-item
2020-09-23 11:05:54	ga_s2am_ard_3-2-1_52JDM_2020-09-23_final.stac-item
2020-09-28 11:53:50	ga_s2am_ard_3-2-1_50KPA_2020-09-28_final.stac-item
2020-10-01 12:03:32	ga_s2am_ard_3-2-1_50KLC_2020-10-01_final.stac-item
2021-04-06 11:52:16	ga_s2am_ard_3-2-1_50KQG_2021-04-06_final
2021-08-25 11:26:09	ga_s2am_ard_3-2-1_51JXF_2021-08-25_final.stac-item
2021-08-25 11:26:42	ga_s2am_ard_3-2-1_51HWD_2021-08-25_final.stac-item
2021-11-13 11:25:54	ga_s2am_ard_3-2-1_51JXG_2021-11-13_final.stac-item
2021-12-20 11:15:54	ga_s2am_ard_3-2-1_51JYG_2021-12-20_final.stac-item
2021-12-22 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-12-22_final.stac-item
2021-12-23 11:25:54	ga_s2am_ard_3-2-1_51JXG_2021-12-23_final.stac-item
2022-02-18 11:15:58	ga_s2am_ard_3-2-1_51JXG_2022-02-18_final.stac-item
2022-03-09 11:46:57	ga_s2am_ard_3-2-1_50HQH_2022-03-09_final.stac-item
2022-03-20 11:16:01	ga_s2am_ard_3-2-1_51JXG_2022-03-20_final.stac-item
2022-04-19 11:16:01	ga_s2am_ard_3-2-1_51JXG_2022-04-19_final.stac-item
2022-07-05 11:05:08	ga_s2am_ard_3-2-1_52JCR_2022-07-05_final.stac-item
2022-08-10 11:26:05	ga_s2am_ard_3-2-1_51JXG_2022-08-10_final.stac-item
2022-08-10 11:26:19	ga_s2am_ard_3-2-1_51JXF_2022-08-10_final.stac-item
2022-10-19 11:26:43	ga_s2am_ard_3-2-1_51HUD_2022-10-19_final.stac-item
2022-11-05 11:16:01	ga_s2am_ard_3-2-1_51JXG_2022-11-05_final.stac-item
2022-12-25 11:15:55	ga_s2am_ard_3-2-1_51JXG_2022-12-25_final.stac-item
2022-12-28 11:25:51	ga_s2am_ard_3-2-1_51JXG_2022-12-28_final.stac-item
2023-01-03 11:46:52	ga_s2am_ard_3-2-1_50HQH_2023-01-03_final.stac-item
2023-01-04 11:15:56	ga_s2am_ard_3-2-1_51JXG_2023-01-04_final.stac-item
2023-01-07 11:25:51	ga_s2am_ard_3-2-1_51JXG_2023-01-07_final.stac-item
2023-02-06 11:26:04	ga_s2am_ard_3-2-1_51JUG_2023-02-06_final
2023-02-12 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-02-12_nrt.stac-item
2023-02-12 11:46:51	ga_s2am_ard_3-2-1_50HQH_2023-02-12_final
2023-03-04 11:44:48	ga_s2am_ard_3-2-1_51JUL_2023-03-04_final
2023-03-08 11:26:01	ga_s2am_ard_3-2-1_51JUG_2023-03-08_final
2023-03-15 11:15:54	ga_s2am_ard_3-2-1_51JXG_2023-03-15_final
2023-04-14 11:16:20	ga_s2am_ard_3-2-1_51JWF_2023-04-14_final
2023-05-17 11:26:37	ga_s2am_ard_3-2-1_51HXD_2023-05-17_final
2023-07-15 11:57:11	ga_s2am_ard_3-2-1_50HMH_2023-07-15_final
2023-08-15 11:26:41	ga_s2am_ard_3-2-1_51HXD_2023-08-15_final
2023-08-25 11:26:11	ga_s2am_ard_3-2-1_51JUG_2023-08-25_final
2023-09-24 11:26:07	ga_s2am_ard_3-2-1_51JUG_2023-09-24_final
2023-12-03 11:25:45	ga_s2am_ard_3-2-1_51JXG_2023-12-03_final
2023-12-12 11:55:11	ga_s2am_ard_3-2-1_50JPQ_2023-12-12_final
2023-12-12 11:55:21	ga_s2am_ard_3-2-1_50JPP_2023-12-12_final
2023-12-20 11:15:53	ga_s2am_ard_3-2-1_51JXG_2023-12-20_final
2024-02-05 11:04:52	ga_s2am_ard_3-2-1_52JCR_2024-02-05_final
2024-02-11 11:25:49	ga_s2am_ard_3-2-1_51JXG_2024-02-11_final
2024-02-28 11:15:53	ga_s2am_ard_3-2-1_51JYG_2024-02-28_final
2024-03-27 12:14:21	ga_s2am_ard_3-2-1_49KHP_2024-03-27_final
2024-03-29 11:15:57	ga_s2am_ard_3-2-1_51JXG_2024-03-29_final
2024-04-11 11:25:53	ga_s2am_ard_3-2-1_51JXG_2024-04-11_final
2024-04-27 11:46:55	ga_s2am_ard_3-2-1_50HQH_2024-04-27_final
2024-05-28 11:15:43	ga_s2am_ard_3-2-1_52JCM_2024-05-28_nrt

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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