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
2015-12-04 11:57:46	ga_s2am_ard_3-2-1_50LRK_2015-12-04_final
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_51KUR_2015-12-21_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50KQV_2016-01-03_final.stac-item
2016-02-19 11:36:40	ga_s2am_ard_3-2-1_51KUS_2016-02-19_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50HNG_2016-03-20_final
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50HPH_2016-05-09_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51JTH_2016-05-09_final.stac-item
2016-05-12 11:56:32	ga_s2am_ard_3-2-1_50HMK_2016-05-12_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JLN_2016-05-15_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51JVH_2016-05-16_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49JGN_2016-06-07_final.stac-item
2016-06-07 12:13:25	ga_s2am_ard_3-2-1_49KGP_2016-06-07_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50JNL_2016-07-08_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51KUQ_2016-11-05_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51KUS_2016-11-05_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51KUT_2016-11-12_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51KVQ_2016-11-22_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51KVV_2016-11-22_final.stac-item
2016-11-29 11:23:19	ga_s2am_ard_3-2-1_51KWQ_2016-11-29_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51KVT_2016-12-12_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51KWQ_2016-12-12_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KVQ_2016-12-22_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_51KUS_2016-12-25_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49KGQ_2016-12-31_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_51KVP_2017-01-01_final.stac-item
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_51KVU_2017-01-31_final.stac-item
2017-02-10 11:32:51	ga_s2am_ard_3-2-1_51KUS_2017-02-10_final.stac-item
2017-02-10 11:32:51	ga_s2am_ard_3-2-1_51KWQ_2017-02-10_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_51JUN_2017-02-13_final.stac-item
2017-02-20 11:27:48	ga_s2am_ard_3-2-1_51KUP_2017-02-20_final.stac-item
2017-03-12 11:27:30	ga_s2am_ard_3-2-1_51KVR_2017-03-12_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_51KVU_2017-11-20_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_51KUT_2017-11-27_final.stac-item
2018-01-26 11:29:50	ga_s2am_ard_3-2-1_51KUT_2018-01-26_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_51KVR_2018-02-08_final.stac-item
2018-02-15 11:30:37	ga_s2am_ard_3-2-1_51KWP_2018-02-15_final.stac-item
2018-02-28 11:38:46	ga_s2am_ard_3-2-1_51KUQ_2018-02-28_final.stac-item
2018-11-15 11:42:54	ga_s2am_ard_3-2-1_51KUU_2018-11-15_final.stac-item
2018-11-22 11:34:03	ga_s2am_ard_3-2-1_51KWP_2018-11-22_final.stac-item
2018-12-12 11:33:14	ga_s2am_ard_3-2-1_51KUT_2018-12-12_final.stac-item
2018-12-12 11:33:26	ga_s2am_ard_3-2-1_51KUS_2018-12-12_final.stac-item
2018-12-25 11:42:56	ga_s2am_ard_3-2-1_51KTU_2018-12-25_final.stac-item
2019-01-01 11:34:30	ga_s2am_ard_3-2-1_51JTN_2019-01-01_final.stac-item
2019-01-05 11:14:18	ga_s2am_ard_3-2-1_51JZN_2019-01-05_final.stac-item
2019-01-31 11:33:42	ga_s2am_ard_3-2-1_51KVR_2019-01-31_final.stac-item
2019-02-13 11:43:08	ga_s2am_ard_3-2-1_51KVT_2019-02-13_final.stac-item
2019-02-20 11:33:27	ga_s2am_ard_3-2-1_51KVS_2019-02-20_final.stac-item
2019-02-20 11:33:59	ga_s2am_ard_3-2-1_51KUQ_2019-02-20_final.stac-item
2019-10-28 11:33:05	ga_s2am_ard_3-2-1_51KVU_2019-10-28_final.stac-item
2019-12-10 11:44:09	ga_s2am_ard_3-2-1_51KUP_2019-12-10_final.stac-item
2019-12-24 11:24:09	ga_s2am_ard_3-2-1_51KWP_2019-12-24_final.stac-item
2020-02-15 11:33:50	ga_s2am_ard_3-2-1_51KWQ_2020-02-15_final.stac-item
2020-02-15 11:34:29	ga_s2am_ard_3-2-1_51JTN_2020-02-15_final.stac-item
2020-03-13 11:25:09	ga_s2am_ard_3-2-1_51JWK_2020-03-13_final.stac-item
2020-10-19 11:24:07	ga_s2am_ard_3-2-1_51KWQ_2020-10-19_final.stac-item
2020-12-18 11:24:17	ga_s2am_ard_3-2-1_51JZN_2020-12-18_final.stac-item
2021-01-04 11:15:30	ga_s2am_ard_3-2-1_51JXJ_2021-01-04_final.stac-item
2021-01-07 11:24:45	ga_s2am_ard_3-2-1_51JWM_2021-01-07_final.stac-item
2021-01-20 11:33:17	ga_s2am_ard_3-2-1_51KVT_2021-01-20_final.stac-item
2021-01-20 11:34:18	ga_s2am_ard_3-2-1_51KUP_2021-01-20_final.stac-item
2021-02-02 11:43:03	ga_s2am_ard_3-2-1_51KTU_2021-02-02_final.stac-item
2021-02-09 11:33:29	ga_s2am_ard_3-2-1_51KVS_2021-02-09_final.stac-item
2021-02-09 11:33:44	ga_s2am_ard_3-2-1_51KVR_2021-02-09_final.stac-item
2021-08-17 12:03:47	ga_s2am_ard_3-2-1_49KHS_2021-08-17_final
2021-10-27 11:33:50	ga_s2am_ard_3-2-1_51KVR_2021-10-27_final.stac-item
2021-11-06 11:32:50	ga_s2am_ard_3-2-1_51KVV_2021-11-06_final.stac-item
2021-11-16 11:33:02	ga_s2am_ard_3-2-1_51KVU_2021-11-16_final.stac-item
2021-11-19 11:43:15	ga_s2am_ard_3-2-1_51KUT_2021-11-19_final.stac-item
2021-11-26 11:34:11	ga_s2am_ard_3-2-1_51KWP_2021-11-26_final.stac-item
2021-12-16 11:34:00	ga_s2am_ard_3-2-1_51KVQ_2021-12-16_final.stac-item
2021-12-16 11:34:37	ga_s2am_ard_3-2-1_50JRT_2021-12-16_final.stac-item
2021-12-19 11:44:28	ga_s2am_ard_3-2-1_51JUN_2021-12-19_final.stac-item
2022-01-18 11:44:13	ga_s2am_ard_3-2-1_51KUP_2022-01-18_final.stac-item
2022-02-17 11:43:12	ga_s2am_ard_3-2-1_51KVT_2022-02-17_final.stac-item
2022-02-17 11:43:16	ga_s2am_ard_3-2-1_51KUT_2022-02-17_final.stac-item
2022-03-06 11:34:00	ga_s2am_ard_3-2-1_51KWQ_2022-03-06_final.stac-item
2022-03-06 11:34:21	ga_s2am_ard_3-2-1_51KUP_2022-03-06_final.stac-item
2022-03-19 11:43:08	ga_s2am_ard_3-2-1_50KRD_2022-03-19_final.stac-item
2022-10-22 11:34:05	ga_s2am_ard_3-2-1_51KUQ_2022-10-22_final.stac-item
2022-11-11 11:33:51	ga_s2am_ard_3-2-1_51KUR_2022-11-11_final.stac-item
2023-01-20 11:33:40	ga_s2am_ard_3-2-1_51KVR_2023-01-20_final.stac-item
2023-01-30 11:33:28	ga_s2am_ard_3-2-1_51KVS_2023-01-30_final.stac-item
2023-01-30 11:37:15	ga_s2am_ard_3-2-1_50HQG_2023-01-30_final
2023-02-09 11:33:55	ga_s2am_ard_3-2-1_51KWQ_2023-02-09_final.stac-item
2023-02-19 11:34:00	ga_s2am_ard_3-2-1_51KUQ_2023-02-19_final
2023-03-01 11:33:13	ga_s2am_ard_3-2-1_51KVT_2023-03-01_final
2023-11-16 11:34:18	ga_s2am_ard_3-2-1_51KVP_2023-11-16_final
2023-11-29 11:43:50	ga_s2am_ard_3-2-1_51KUQ_2023-11-29_final
2023-12-09 11:43:53	ga_s2am_ard_3-2-1_51KUQ_2023-12-09_final
2023-12-19 11:43:24	ga_s2am_ard_3-2-1_51KUS_2023-12-19_final
2023-12-23 11:26:51	ga_s2am_ard_3-2-1_51HWC_2023-12-23_final
2023-12-26 11:33:57	ga_s2am_ard_3-2-1_51KVQ_2023-12-26_final
2023-12-29 11:44:24	ga_s2am_ard_3-2-1_51JUN_2023-12-29_final
2024-01-15 11:34:25	ga_s2am_ard_3-2-1_51JUN_2024-01-15_final
2024-01-18 11:43:49	ga_s2am_ard_3-2-1_51KUQ_2024-01-18_final
2024-02-04 11:34:06	ga_s2am_ard_3-2-1_51KWP_2024-02-04_final
2024-02-07 11:43:54	ga_s2am_ard_3-2-1_51KUQ_2024-02-07_final
2024-02-28 11:15:13	ga_s2am_ard_3-2-1_51JYK_2024-02-28_final
2024-03-05 11:33:16	ga_s2am_ard_3-2-1_51KVT_2024-03-05_final
2024-03-05 11:33:22	ga_s2am_ard_3-2-1_51KUT_2024-03-05_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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