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
2015-11-20 12:14:39	ga_s2am_ard_3-2-1_49JFM_2015-11-20_final.stac-item
2015-12-21 11:47:51	ga_s2am_ard_3-2-1_50HQK_2015-12-21_final.stac-item
2015-12-30 12:16:05	ga_s2am_ard_3-2-1_49KGQ_2015-12-30_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50HNK_2016-01-03_final.stac-item
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51JZM_2016-01-24_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JPP_2016-03-03_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51JXF_2016-05-03_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51JTG_2016-05-09_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHP_2016-05-18_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_50KKV_2016-08-26_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50HLK_2016-10-29_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_49KGQ_2016-12-11_final.stac-item
2017-02-20 11:36:27	ga_s2am_ard_3-2-1_51HTD_2017-02-20_final.stac-item
2017-02-22 12:13:15	ga_s2am_ard_3-2-1_50KKA_2017-02-22_final.stac-item
2017-03-01 12:03:41	ga_s2am_ard_3-2-1_50KMA_2017-03-01_final.stac-item
2017-03-01 12:03:41	ga_s2am_ard_3-2-1_50KMV_2017-03-01_final.stac-item
2017-03-14 12:13:38	ga_s2am_ard_3-2-1_49KGP_2017-03-14_final.stac-item
2017-03-24 12:13:37	ga_s2am_ard_3-2-1_49KGR_2017-03-24_final.stac-item
2017-05-08 11:26:12	ga_s2am_ard_3-2-1_51HUE_2017-05-08_final.stac-item
2017-07-26 11:56:09	ga_s2am_ard_3-2-1_50JMM_2017-07-26_final.stac-item
2017-07-26 11:56:09	ga_s2am_ard_3-2-1_50JNL_2017-07-26_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KGP_2017-09-27_final.stac-item
2018-03-03 11:52:20	ga_s2am_ard_3-2-1_50KRC_2018-03-03_final.stac-item
2018-12-12 11:36:20	ga_s2am_ard_3-2-1_51HUE_2018-12-12_final.stac-item
2018-12-28 11:56:07	ga_s2am_ard_3-2-1_50JKM_2018-12-28_final.stac-item
2019-01-13 12:14:14	ga_s2am_ard_3-2-1_50KKU_2019-01-13_final.stac-item
2019-01-23 12:14:15	ga_s2am_ard_3-2-1_50KKU_2019-01-23_final.stac-item
2019-01-23 12:14:18	ga_s2am_ard_3-2-1_49KHP_2019-01-23_final.stac-item
2019-01-31 11:36:54	ga_s2am_ard_3-2-1_51HUC_2019-01-31_final.stac-item
2019-02-07 11:26:58	ga_s2am_ard_3-2-1_51HUC_2019-02-07_final.stac-item
2019-02-09 12:03:41	ga_s2am_ard_3-2-1_50KKB_2019-02-09_final.stac-item
2019-02-22 12:13:50	ga_s2am_ard_3-2-1_49KHR_2019-02-22_final.stac-item
2019-03-01 12:03:54	ga_s2am_ard_3-2-1_49KHR_2019-03-01_final.stac-item
2019-03-15 11:46:59	ga_s2am_ard_3-2-1_50HPH_2019-03-15_final.stac-item
2019-04-03 12:13:55	ga_s2am_ard_3-2-1_49KHR_2019-04-03_final.stac-item
2019-04-14 11:43:31	ga_s2am_ard_3-2-1_51KUS_2019-04-14_final.stac-item
2019-05-14 11:44:02	ga_s2am_ard_3-2-1_51KUQ_2019-05-14_final.stac-item
2019-05-18 11:25:42	ga_s2am_ard_3-2-1_51JXH_2019-05-18_final.stac-item
2019-05-20 12:05:01	ga_s2am_ard_3-2-1_50JKS_2019-05-20_final.stac-item
2019-07-09 12:04:10	ga_s2am_ard_3-2-1_50KKA_2019-07-09_final.stac-item
2019-07-17 11:24:24	ga_s2am_ard_3-2-1_51JZN_2019-07-17_final.stac-item
2019-09-18 11:37:00	ga_s2am_ard_3-2-1_51HTC_2019-09-18_final.stac-item
2019-10-27 12:03:47	ga_s2am_ard_3-2-1_50KKB_2019-10-27_final.stac-item
2019-11-20 11:43:04	ga_s2am_ard_3-2-1_51KTU_2019-11-20_final.stac-item
2019-12-07 11:33:45	ga_s2am_ard_3-2-1_51KUR_2019-12-07_final.stac-item
2019-12-07 11:35:45	ga_s2am_ard_3-2-1_51JTH_2019-12-07_final.stac-item
2019-12-10 11:43:00	ga_s2am_ard_3-2-1_51KTU_2019-12-10_final.stac-item
2019-12-20 11:43:12	ga_s2am_ard_3-2-1_50KRC_2019-12-20_final.stac-item
2020-04-05 11:36:54	ga_s2am_ard_3-2-1_51HUC_2020-04-05_final.stac-item
2020-04-12 11:27:00	ga_s2am_ard_3-2-1_51HUC_2020-04-12_final.stac-item
2020-06-03 12:03:50	ga_s2am_ard_3-2-1_50KKB_2020-06-03_final.stac-item
2020-06-30 11:53:16	ga_s2am_ard_3-2-1_50KRC_2020-06-30_final.stac-item
2020-10-02 11:33:58	ga_s2am_ard_3-2-1_51KUR_2020-10-02_final.stac-item
2020-10-05 11:43:49	ga_s2am_ard_3-2-1_51KUR_2020-10-05_final.stac-item
2020-11-21 11:37:03	ga_s2am_ard_3-2-1_51HTC_2020-11-21_final.stac-item
2021-04-20 11:36:41	ga_s2am_ard_3-2-1_51HTD_2021-04-20_final.stac-item
2021-07-15 11:53:14	ga_s2am_ard_3-2-1_50KRC_2021-07-15_final.stac-item
2021-08-25 11:27:00	ga_s2am_ard_3-2-1_51HVC_2021-08-25_final.stac-item
2021-08-31 11:43:30	ga_s2am_ard_3-2-1_51KUS_2021-08-31_final.stac-item
2021-09-07 11:37:18	ga_s2am_ard_3-2-1_50HQG_2021-09-07_final
2021-10-03 11:56:04	ga_s2am_ard_3-2-1_50JKN_2021-10-03_final.stac-item
2021-12-06 11:37:02	ga_s2am_ard_3-2-1_50HQH_2021-12-06_final.stac-item
2022-02-27 11:47:05	ga_s2am_ard_3-2-1_50HPH_2022-02-27_final.stac-item
2022-03-06 11:37:05	ga_s2am_ard_3-2-1_51HTC_2022-03-06_final.stac-item
2022-03-08 12:13:58	ga_s2am_ard_3-2-1_50KKA_2022-03-08_final.stac-item
2022-03-22 11:54:14	ga_s2am_ard_3-2-1_50KNV_2022-03-22_final.stac-item
2022-05-22 11:27:08	ga_s2am_ard_3-2-1_51HUC_2022-05-22_final.stac-item
2022-06-23 12:04:46	ga_s2am_ard_3-2-1_50JKT_2022-06-23_final.stac-item
2022-07-01 11:26:59	ga_s2am_ard_3-2-1_51HVD_2022-07-01_final.stac-item
2022-07-14 11:33:44	ga_s2am_ard_3-2-1_51KUS_2022-07-14_final.stac-item
2022-08-27 11:16:49	ga_s2am_ard_3-2-1_51HYD_2022-08-27_final
2022-09-15 11:46:10	ga_s2am_ard_3-2-1_50JQM_2022-09-15_final.stac-item
2022-10-12 11:33:39	ga_s2am_ard_3-2-1_51KUS_2022-10-12_final.stac-item
2022-10-15 11:46:58	ga_s2am_ard_3-2-1_50HQH_2022-10-15_final.stac-item
2023-02-28 12:05:20	ga_s2am_ard_3-2-1_50JLQ_2023-02-28_final
2023-04-27 11:25:38	ga_s2am_ard_3-2-1_51JXH_2023-04-27_final
2023-05-13 11:43:29	ga_s2am_ard_3-2-1_51KUS_2023-05-13_final
2023-06-25 11:55:49	ga_s2am_ard_3-2-1_50JKP_2023-06-25_final
2023-07-22 11:43:22	ga_s2am_ard_3-2-1_51KTT_2023-07-22_final
2023-09-20 11:47:09	ga_s2am_ard_3-2-1_50HNH_2023-09-20_final
2023-11-15 12:03:22	ga_s2am_ard_3-2-1_50KMC_2023-11-15_final
2023-11-16 11:34:14	ga_s2am_ard_3-2-1_51JXN_2023-11-16_final
2023-12-09 11:47:15	ga_s2am_ard_3-2-1_50HNG_2023-12-09_final
2023-12-20 11:14:25	ga_s2am_ard_3-2-1_51JYN_2023-12-20_final
2024-01-11 11:56:06	ga_s2am_ard_3-2-1_50JLM_2024-01-11_final
2024-01-21 11:53:03	ga_s2am_ard_3-2-1_50KRC_2024-01-21_final
2024-02-14 11:33:45	ga_s2am_ard_3-2-1_51KUR_2024-02-14_final
2024-02-17 11:46:51	ga_s2am_ard_3-2-1_50HQH_2024-02-17_final
2024-03-08 11:45:25	ga_s2am_ard_3-2-1_50JNQ_2024-03-08_final
2024-03-08 11:47:03	ga_s2am_ard_3-2-1_50HPH_2024-03-08_final
2024-03-25 11:37:03	ga_s2am_ard_3-2-1_51HUC_2024-03-25_final
2024-03-27 12:14:08	ga_s2am_ard_3-2-1_50KKV_2024-03-27_final
2024-03-27 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2024-03-27_final
2024-04-03 12:03:42	ga_s2am_ard_3-2-1_50KNA_2024-04-03_final
2024-04-23 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2024-04-23_final
2024-05-01 11:25:27	ga_s2am_ard_3-2-1_51JXJ_2024-05-01_final
2024-05-27 11:46:42	ga_s2am_ard_3-2-1_50HMK_2024-05-27_nrt
2024-05-28 11:15:47	ga_s2am_ard_3-2-1_51JXH_2024-05-28_nrt
2024-05-30 11:55:44	ga_s2am_ard_3-2-1_50JLP_2024-05-30_nrt
2024-05-30 11:56:28	ga_s2am_ard_3-2-1_50JLL_2024-05-30_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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