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
2015-11-25 11:21:29	ga_s2am_ard_3-2-1_51JYJ_2015-11-25_final.stac-item
2015-11-25 11:21:29	ga_s2am_ard_3-2-1_51KXP_2015-11-25_final.stac-item
2016-03-24 11:21:55	ga_s2am_ard_3-2-1_51JYH_2016-03-24_final.stac-item
2016-07-23 10:48:23	ga_s2am_ard_3-2-1_52JFR_2016-07-23_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50HMK_2016-09-09_final.stac-item
2016-12-03 11:00:41	ga_s2am_ard_3-2-1_52JFT_2016-12-03_final.stac-item
2017-01-04 11:46:21	ga_s2am_ard_3-2-1_50HNJ_2017-01-04_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_51JZN_2017-01-25_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50JNN_2017-02-26_final.stac-item
2017-03-20 10:53:07	ga_s2am_ard_3-2-1_52JFM_2017-03-20_final.stac-item
2017-04-14 11:38:34	ga_s2am_ard_3-2-1_51KUS_2017-04-14_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50HPK_2017-05-04_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_51HUC_2017-11-27_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_51KVV_2017-12-10_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51KXS_2018-01-06_final.stac-item
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_51JYK_2018-02-19_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_51LZE_2018-02-25_final.stac-item
2018-04-22 11:53:56	ga_s2am_ard_3-2-1_50JLM_2018-04-22_final.stac-item
2018-04-22 11:53:56	ga_s2am_ard_3-2-1_50JLN_2018-04-22_final.stac-item
2018-05-07 10:57:18	ga_s2am_ard_3-2-1_52JEL_2018-05-07_final.stac-item
2018-06-02 11:23:55	ga_s2am_ard_3-2-1_51HXE_2018-06-02_final.stac-item
2018-10-30 11:24:52	ga_s2am_ard_3-2-1_51HVD_2018-10-30_final.stac-item
2018-11-22 11:33:09	ga_s2am_ard_3-2-1_51KVT_2018-11-22_final.stac-item
2019-01-15 11:16:36	ga_s2am_ard_3-2-1_51HXD_2019-01-15_final.stac-item
2019-03-16 11:14:38	ga_s2am_ard_3-2-1_51JYM_2019-03-16_final.stac-item
2019-04-14 11:45:27	ga_s2am_ard_3-2-1_50JNQ_2019-04-14_final.stac-item
2019-05-27 11:54:47	ga_s2am_ard_3-2-1_50JLT_2019-05-27_final.stac-item
2019-06-04 11:16:25	ga_s2am_ard_3-2-1_51HYE_2019-06-04_final.stac-item
2019-06-18 10:56:07	ga_s2am_ard_3-2-1_52JEL_2019-06-18_final.stac-item
2019-08-26 11:24:46	ga_s2am_ard_3-2-1_51JWM_2019-08-26_final.stac-item
2019-09-11 11:47:12	ga_s2am_ard_3-2-1_50HLH_2019-09-11_final.stac-item
2019-10-04 11:57:11	ga_s2am_ard_3-2-1_50HLH_2019-10-04_final.stac-item
2019-10-25 11:23:26	ga_s2am_ard_3-2-1_51KXS_2019-10-25_final.stac-item
2020-01-03 11:24:21	ga_s2am_ard_3-2-1_51JXN_2020-01-03_final.stac-item
2020-01-16 11:33:10	ga_s2am_ard_3-2-1_51KVT_2020-01-16_final.stac-item
2020-01-26 11:33:16	ga_s2am_ard_3-2-1_51KXS_2020-01-26_final.stac-item
2020-02-05 11:32:38	ga_s2am_ard_3-2-1_51KVV_2020-02-05_final.stac-item
2020-04-05 11:33:20	ga_s2am_ard_3-2-1_51KXS_2020-04-05_final.stac-item
2020-05-12 11:24:05	ga_s2am_ard_3-2-1_51KYP_2020-05-12_final.stac-item
2020-05-25 11:33:03	ga_s2am_ard_3-2-1_51KWU_2020-05-25_final.stac-item
2020-11-04 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2020-11-04_final.stac-item
2020-12-04 11:46:22	ga_s2am_ard_3-2-1_50JQL_2020-12-04_final.stac-item
2020-12-21 11:32:42	ga_s2am_ard_3-2-1_51KWV_2020-12-21_final.stac-item
2021-01-14 11:16:03	ga_s2am_ard_3-2-1_52JCL_2021-01-14_final.stac-item
2021-01-24 11:14:56	ga_s2am_ard_3-2-1_51JYL_2021-01-24_final.stac-item
2021-01-28 10:55:42	ga_s2am_ard_3-2-1_52JGM_2021-01-28_final.stac-item
2021-01-30 11:32:15	ga_s2am_ard_3-2-1_51KWB_2021-01-30_final.stac-item
2021-04-27 11:23:07	ga_s2am_ard_3-2-1_51KYT_2021-04-27_final.stac-item
2021-05-10 11:33:26	ga_s2am_ard_3-2-1_51KWS_2021-05-10_final.stac-item
2021-05-24 11:16:23	ga_s2am_ard_3-2-1_51HYE_2021-05-24_final.stac-item
2021-05-27 11:23:22	ga_s2am_ard_3-2-1_51KZS_2021-05-27_final.stac-item
2021-05-30 11:33:56	ga_s2am_ard_3-2-1_51KWQ_2021-05-30_final.stac-item
2021-06-09 11:34:29	ga_s2am_ard_3-2-1_51JVN_2021-06-09_final.stac-item
2021-07-12 11:45:46	ga_s2am_ard_3-2-1_51JTH_2021-07-12_final.stac-item
2021-10-30 11:43:23	ga_s2am_ard_3-2-1_50KRC_2021-10-30_final.stac-item
2022-02-01 11:23:10	ga_s2am_ard_3-2-1_51KYT_2022-02-01_final.stac-item
2022-02-01 11:24:26	ga_s2am_ard_3-2-1_51JXN_2022-02-01_final.stac-item
2022-02-11 11:23:06	ga_s2am_ard_3-2-1_51KZT_2022-02-11_final.stac-item
2022-02-15 11:05:38	ga_s2am_ard_3-2-1_52JCN_2022-02-15_final.stac-item
2022-03-30 11:15:56	ga_s2am_ard_3-2-1_51JYG_2022-03-30_final.stac-item
2022-04-05 11:34:12	ga_s2am_ard_3-2-1_51KWP_2022-04-05_final.stac-item
2022-05-27 12:14:16	ga_s2am_ard_3-2-1_49KHQ_2022-05-27_final.stac-item
2022-07-11 11:23:23	ga_s2am_ard_3-2-1_51KYT_2022-07-11_final.stac-item
2022-07-13 12:06:22	ga_s2am_ard_3-2-1_50JKM_2022-07-13_final.stac-item
2022-07-21 11:25:32	ga_s2am_ard_3-2-1_51JYJ_2022-07-21_final.stac-item
2022-09-05 13:21:56	ga_s2am_ard_3-2-1_47LKG_2022-09-05_interim
2022-10-29 11:24:22	ga_s2am_ard_3-2-1_52JBT_2022-10-29_final.stac-item
2022-11-21 11:32:37	ga_s2am_ard_3-2-1_51KYV_2022-11-21_final.stac-item
2022-12-22 11:06:32	ga_s2am_ard_3-2-1_52HBJ_2022-12-22_final
2023-01-04 11:14:16	ga_s2am_ard_3-2-1_52JDT_2023-01-04_final.stac-item
2023-01-06 11:57:08	ga_s2am_ard_3-2-1_50HLH_2023-01-06_final.stac-item
2023-01-29 12:06:08	ga_s2am_ard_3-2-1_50JKM_2023-01-29_final.stac-item
2023-02-23 11:16:09	ga_s2am_ard_3-2-1_51JXF_2023-02-23_final
2023-03-28 11:24:21	ga_s2am_ard_3-2-1_51JYN_2023-03-28_final
2023-03-31 11:34:27	ga_s2am_ard_3-2-1_51JVN_2023-03-31_final
2023-04-01 11:04:46	ga_s2am_ard_3-2-1_52JER_2023-04-01_final
2023-04-20 11:33:21	ga_s2am_ard_3-2-1_51KUT_2023-04-20_final
2023-04-30 11:31:06	ga_s2am_ard_3-2-1_51LZF_2023-04-30_final
2023-04-30 11:33:27	ga_s2am_ard_3-2-1_51KWS_2023-04-30_final
2023-05-30 11:33:13	ga_s2am_ard_3-2-1_51KXT_2023-05-30_final
2023-06-26 11:23:42	ga_s2am_ard_3-2-1_51KYR_2023-06-26_final
2023-07-26 11:26:31	ga_s2am_ard_3-2-1_51HWE_2023-07-26_final
2023-08-01 11:44:07	ga_s2am_ard_3-2-1_51KTQ_2023-08-01_final
2023-09-10 11:46:46	ga_s2am_ard_3-2-1_50HMK_2023-09-10_final
2023-10-10 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2023-10-10_final
2023-11-10 11:16:36	ga_s2am_ard_3-2-1_51HYD_2023-11-10_final
2023-11-16 11:35:11	ga_s2am_ard_3-2-1_51JVK_2023-11-16_final
2023-11-26 11:33:25	ga_s2am_ard_3-2-1_51KVS_2023-11-26_final
2023-12-03 11:23:02	ga_s2am_ard_3-2-1_51KYT_2023-12-03_final
2023-12-06 11:32:55	ga_s2am_ard_3-2-1_51KVU_2023-12-06_final
2023-12-17 11:05:12	ga_s2am_ard_3-2-1_52JEP_2023-12-17_final
2023-12-23 11:22:57	ga_s2am_ard_3-2-1_51KXU_2023-12-23_final
2023-12-29 11:47:03	ga_s2am_ard_3-2-1_50HNH_2023-12-29_final
2024-01-22 11:23:57	ga_s2am_ard_3-2-1_51KZP_2024-01-22_final
2024-02-04 11:35:55	ga_s2am_ard_3-2-1_51JUG_2024-02-04_final
2024-03-12 11:25:20	ga_s2am_ard_3-2-1_51JYJ_2024-03-12_final
2024-04-10 11:54:23	ga_s2am_ard_3-2-1_50KNU_2024-04-10_final
2024-04-17 11:44:34	ga_s2am_ard_3-2-1_51JTN_2024-04-17_final
2024-04-18 11:16:38	ga_s2am_ard_3-2-1_52HBJ_2024-04-18_nrt
2024-04-25 11:06:05	ga_s2am_ard_3-2-1_52JDL_2024-04-25_final

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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