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_51JUF_2015-08-30_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49JGM_2016-08-23_final.stac-item
2016-09-12 12:02:46	ga_s2am_ard_3-2-1_50KKU_2016-09-12_final.stac-item
2016-10-12 12:04:37	ga_s2am_ard_3-2-1_49JGM_2016-10-12_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_51KTU_2016-10-26_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_51KVS_2016-12-25_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50KKB_2017-03-31_final.stac-item
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_51KWB_2017-10-11_final.stac-item
2017-12-24 11:22:03	ga_s2am_ard_3-2-1_51KWQ_2017-12-24_final.stac-item
2018-01-13 11:25:27	ga_s2am_ard_3-2-1_51JWH_2018-01-13_final.stac-item
2018-03-30 11:44:57	ga_s2am_ard_3-2-1_50HPJ_2018-03-30_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKN_2018-04-05_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50KKU_2018-04-05_final.stac-item
2018-06-12 11:22:26	ga_s2am_ard_3-2-1_51HVC_2018-06-12_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_51HUC_2018-07-25_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JKT_2018-08-23_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JLN_2018-08-30_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_50KKA_2018-09-05_final.stac-item
2018-09-20 11:24:00	ga_s2am_ard_3-2-1_51JYM_2018-09-20_final.stac-item
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_51KUS_2018-11-05_final.stac-item
2018-11-12 11:35:10	ga_s2am_ard_3-2-1_51JUK_2018-11-12_final.stac-item
2018-11-18 11:53:18	ga_s2am_ard_3-2-1_50KNC_2018-11-18_final.stac-item
2018-12-12 11:32:11	ga_s2am_ard_3-2-1_51KVB_2018-12-12_final.stac-item
2018-12-25 11:43:10	ga_s2am_ard_3-2-1_51KTT_2018-12-25_final.stac-item
2019-03-21 12:04:40	ga_s2am_ard_3-2-1_50JKT_2019-03-21_final.stac-item
2019-04-03 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2019-04-03_final.stac-item
2019-04-21 11:36:55	ga_s2am_ard_3-2-1_50HPJ_2019-04-21_final.stac-item
2019-06-14 11:14:26	ga_s2am_ard_3-2-1_51JZN_2019-06-14_final.stac-item
2019-07-23 11:42:51	ga_s2am_ard_3-2-1_51KUV_2019-07-23_final.stac-item
2019-08-08 12:05:59	ga_s2am_ard_3-2-1_50JKN_2019-08-08_final.stac-item
2019-08-25 11:53:19	ga_s2am_ard_3-2-1_50KQC_2019-08-25_final.stac-item
2019-09-18 11:36:42	ga_s2am_ard_3-2-1_51HUD_2019-09-18_final.stac-item
2019-09-28 11:36:35	ga_s2am_ard_3-2-1_50HQK_2019-09-28_final.stac-item
2019-10-21 11:43:25	ga_s2am_ard_3-2-1_50KQC_2019-10-21_final.stac-item
2019-12-29 12:14:22	ga_s2am_ard_3-2-1_49KGP_2019-12-29_final.stac-item
2020-01-05 12:05:46	ga_s2am_ard_3-2-1_50JLN_2020-01-05_final.stac-item
2020-01-09 11:44:17	ga_s2am_ard_3-2-1_50KPU_2020-01-09_final.stac-item
2020-01-12 11:53:25	ga_s2am_ard_3-2-1_50KMC_2020-01-12_final.stac-item
2020-01-25 12:04:54	ga_s2am_ard_3-2-1_49JGM_2020-01-25_final.stac-item
2020-01-28 12:15:03	ga_s2am_ard_3-2-1_49JGL_2020-01-28_final.stac-item
2020-02-28 11:47:05	ga_s2am_ard_3-2-1_50HMH_2020-02-28_final.stac-item
2020-03-29 11:42:24	ga_s2am_ard_3-2-1_51KVA_2020-03-29_final.stac-item
2020-04-18 11:46:38	ga_s2am_ard_3-2-1_50HNK_2020-04-18_final.stac-item
2020-05-01 11:53:13	ga_s2am_ard_3-2-1_50KRC_2020-05-01_final.stac-item
2020-05-17 12:15:01	ga_s2am_ard_3-2-1_49JGM_2020-05-17_final.stac-item
2020-06-01 11:24:04	ga_s2am_ard_3-2-1_51KWQ_2020-06-01_final.stac-item
2020-07-10 11:56:00	ga_s2am_ard_3-2-1_50JLN_2020-07-10_final.stac-item
2020-07-30 11:53:16	ga_s2am_ard_3-2-1_50KRC_2020-07-30_final.stac-item
2020-08-16 11:46:49	ga_s2am_ard_3-2-1_50HQJ_2020-08-16_final.stac-item
2020-08-20 11:26:42	ga_s2am_ard_3-2-1_51HXD_2020-08-20_final.stac-item
2020-08-23 11:36:29	ga_s2am_ard_3-2-1_51HVE_2020-08-23_final.stac-item
2020-10-08 11:56:28	ga_s2am_ard_3-2-1_50JML_2020-10-08_final.stac-item
2020-12-24 11:43:43	ga_s2am_ard_3-2-1_51KUR_2020-12-24_final.stac-item
2021-01-03 11:42:13	ga_s2am_ard_3-2-1_51KVB_2021-01-03_final.stac-item
2021-01-07 11:24:45	ga_s2am_ard_3-2-1_51JWM_2021-01-07_final.stac-item
2021-01-10 11:36:35	ga_s2am_ard_3-2-1_50HQK_2021-01-10_final.stac-item
2021-02-19 11:33:41	ga_s2am_ard_3-2-1_51KWR_2021-02-19_final.stac-item
2021-03-04 11:42:27	ga_s2am_ard_3-2-1_51KVA_2021-03-04_final.stac-item
2021-04-26 11:53:27	ga_s2am_ard_3-2-1_50KMC_2021-04-26_final.stac-item
2021-05-13 11:46:33	ga_s2am_ard_3-2-1_50HPK_2021-05-13_final.stac-item
2021-05-17 11:26:58	ga_s2am_ard_3-2-1_51HVC_2021-05-17_final.stac-item
2021-08-20 12:13:57	ga_s2am_ard_3-2-1_49KHR_2021-08-20_final.stac-item
2021-08-27 12:05:17	ga_s2am_ard_3-2-1_49JGL_2021-08-27_final.stac-item
2021-11-26 11:37:15	ga_s2am_ard_3-2-1_50HQG_2021-11-26_final
2021-12-05 12:03:22	ga_s2am_ard_3-2-1_50KMC_2021-12-05_final.stac-item
2021-12-05 12:05:55	ga_s2am_ard_3-2-1_50JKN_2021-12-05_final.stac-item
2022-01-02 11:25:47	ga_s2am_ard_3-2-1_51JVH_2022-01-02_final.stac-item
2022-03-03 11:24:22	ga_s2am_ard_3-2-1_51JZN_2022-03-03_final.stac-item
2022-03-29 11:45:32	ga_s2am_ard_3-2-1_51JTJ_2022-03-29_final.stac-item
2022-05-05 11:37:11	ga_s2am_ard_3-2-1_50HPH_2022-05-05_final.stac-item
2022-05-15 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2022-05-15_final.stac-item
2022-07-01 11:26:51	ga_s2am_ard_3-2-1_51HWD_2022-07-01_final.stac-item
2022-07-03 12:03:36	ga_s2am_ard_3-2-1_50KMC_2022-07-03_final.stac-item
2022-07-20 11:53:29	ga_s2am_ard_3-2-1_50KQC_2022-07-20_final.stac-item
2022-08-03 11:36:53	ga_s2am_ard_3-2-1_51HUD_2022-08-03_final.stac-item
2022-08-06 11:46:52	ga_s2am_ard_3-2-1_50HMK_2022-08-06_final.stac-item
2022-08-25 12:14:07	ga_s2am_ard_3-2-1_50KKA_2022-08-25_final.stac-item
2022-11-01 11:36:38	ga_s2am_ard_3-2-1_50HQK_2022-11-01_final.stac-item
2022-12-04 11:42:42	ga_s2am_ard_3-2-1_51KVV_2022-12-04_final.stac-item
2023-01-27 11:24:12	ga_s2am_ard_3-2-1_51KWP_2023-01-27_final.stac-item
2023-02-18 12:03:55	ga_s2am_ard_3-2-1_50KKA_2023-02-18_nrt.stac-item
2023-03-31 11:33:25	ga_s2am_ard_3-2-1_51KWS_2023-03-31_final
2023-04-20 11:34:09	ga_s2am_ard_3-2-1_51KWP_2023-04-20_final
2023-04-29 12:03:23	ga_s2am_ard_3-2-1_50KMC_2023-04-29_final
2023-05-16 11:53:18	ga_s2am_ard_3-2-1_50KQC_2023-05-16_final
2023-05-20 11:37:05	ga_s2am_ard_3-2-1_50HQH_2023-05-20_final
2023-06-15 11:53:40	ga_s2am_ard_3-2-1_50KPB_2023-06-15_final
2023-07-08 12:04:04	ga_s2am_ard_3-2-1_49KHR_2023-07-08_final
2023-08-08 11:34:15	ga_s2am_ard_3-2-1_51KWP_2023-08-08_final
2023-09-10 11:42:47	ga_s2am_ard_3-2-1_51KVV_2023-09-10_final
2023-09-30 11:44:53	ga_s2am_ard_3-2-1_51JUL_2023-09-30_final
2023-10-06 12:04:43	ga_s2am_ard_3-2-1_49JHN_2023-10-06_final
2023-11-02 11:53:09	ga_s2am_ard_3-2-1_50KRC_2023-11-02_final
2023-11-26 11:33:42	ga_s2am_ard_3-2-1_51KUR_2023-11-26_final
2023-12-09 11:42:58	ga_s2am_ard_3-2-1_51KTU_2023-12-09_final
2024-01-22 11:24:48	ga_s2am_ard_3-2-1_51JXL_2024-01-22_final
2024-02-20 11:56:23	ga_s2am_ard_3-2-1_50JLL_2024-02-20_final
2024-03-01 11:55:56	ga_s2am_ard_3-2-1_50JLN_2024-03-01_final
2024-03-08 11:43:37	ga_s2am_ard_3-2-1_50KQB_2024-03-08_final
2024-04-17 11:46:33	ga_s2am_ard_3-2-1_50HQK_2024-04-17_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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