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
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49KGP_2016-01-16_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_52KDF_2016-05-10_final.stac-item
2016-10-04 10:57:51	ga_s2am_ard_3-2-1_52KEU_2016-10-04_final.stac-item
2016-12-09 11:21:01	ga_s2am_ard_3-2-1_51JYN_2016-12-09_final.stac-item
2016-12-11 10:25:20	ga_s2am_ard_3-2-1_53HNC_2016-12-11_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51KWB_2016-12-12_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_51KUS_2017-06-13_final.stac-item
2017-06-20 11:28:36	ga_s2am_ard_3-2-1_51KXU_2017-06-20_final.stac-item
2017-08-10 11:02:13	ga_s2am_ard_3-2-1_52JDT_2017-08-10_final.stac-item
2017-08-20 11:03:00	ga_s2am_ard_3-2-1_52KFV_2017-08-20_final.stac-item
2017-10-18 11:30:06	ga_s2am_ard_3-2-1_51KWA_2017-10-18_final.stac-item
2017-12-21 11:12:09	ga_s2am_ard_3-2-1_52KCF_2017-12-21_final.stac-item
2018-01-20 11:07:06	ga_s2am_ard_3-2-1_52LGL_2018-01-20_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_51KVB_2018-02-08_final.stac-item
2018-04-03 11:16:59	ga_s2am_ard_3-2-1_51KZT_2018-04-03_final.stac-item
2018-04-08 10:27:08	ga_s2am_ard_3-2-1_53JMF_2018-04-08_final.stac-item
2018-05-09 10:02:56	ga_s2am_ard_3-2-1_54HXD_2018-05-09_final.stac-item
2018-06-07 10:27:08	ga_s2am_ard_3-2-1_53KQQ_2018-06-07_final.stac-item
2018-07-30 10:37:28	ga_s2am_ard_3-2-1_53LPE_2018-07-30_final.stac-item
2018-09-15 12:13:40	ga_s2am_ard_3-2-1_49KHQ_2018-09-15_final.stac-item
2018-09-27 11:12:40	ga_s2am_ard_3-2-1_52KDA_2018-09-27_final.stac-item
2018-10-02 10:17:02	ga_s2am_ard_3-2-1_53KRP_2018-10-02_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_51JYM_2018-10-30_final.stac-item
2018-11-20 10:54:27	ga_s2am_ard_3-2-1_52JFS_2018-11-20_final.stac-item
2018-12-15 11:43:35	ga_s2am_ard_3-2-1_51KUR_2018-12-15_final.stac-item
2019-01-05 11:13:02	ga_s2am_ard_3-2-1_52KCC_2019-01-05_final.stac-item
2019-02-17 11:23:21	ga_s2am_ard_3-2-1_51KYS_2019-02-17_final.stac-item
2019-03-05 11:42:22	ga_s2am_ard_3-2-1_51KVA_2019-03-05_final.stac-item
2019-05-21 11:34:18	ga_s2am_ard_3-2-1_51KVP_2019-05-21_final.stac-item
2019-06-30 11:34:04	ga_s2am_ard_3-2-1_51KVQ_2019-06-30_final.stac-item
2019-07-05 10:41:54	ga_s2am_ard_3-2-1_53KQB_2019-07-05_final
2019-08-24 10:45:45	ga_s2am_ard_3-2-1_53JKG_2019-08-24_final.stac-item
2019-09-18 11:36:51	ga_s2am_ard_3-2-1_50HPJ_2019-09-18_final.stac-item
2019-11-07 11:32:43	ga_s2am_ard_3-2-1_51KXV_2019-11-07_final.stac-item
2019-11-07 11:33:55	ga_s2am_ard_3-2-1_51KXQ_2019-11-07_final.stac-item
2020-02-03 10:51:23	ga_s2am_ard_3-2-1_53LPC_2020-02-03_final
2020-02-08 11:42:01	ga_s2am_ard_3-2-1_51KWB_2020-02-08_final.stac-item
2020-03-03 11:23:54	ga_s2am_ard_3-2-1_51KWQ_2020-03-03_final.stac-item
2020-03-09 10:07:04	ga_s2am_ard_3-2-1_54HXE_2020-03-09_final.stac-item
2020-03-20 11:13:15	ga_s2am_ard_3-2-1_52KCB_2020-03-20_final.stac-item
2020-03-21 10:45:54	ga_s2am_ard_3-2-1_53JKF_2020-03-21_final.stac-item
2020-03-28 10:36:55	ga_s2am_ard_3-2-1_53HPA_2020-03-28_final.stac-item
2020-05-14 12:05:05	ga_s2am_ard_3-2-1_49JGM_2020-05-14_final.stac-item
2020-05-22 11:23:33	ga_s2am_ard_3-2-1_52KCA_2020-05-22_final.stac-item
2020-05-23 10:51:37	ga_s2am_ard_3-2-1_53LPC_2020-05-23_final
2020-07-07 11:42:17	ga_s2am_ard_3-2-1_51KVB_2020-07-07_final.stac-item
2020-08-04 11:03:01	ga_s2am_ard_3-2-1_52KHC_2020-08-04_final.stac-item
2020-08-09 11:55:04	ga_s2am_ard_3-2-1_50JLS_2020-08-09_final.stac-item
2020-09-06 11:13:29	ga_s2am_ard_3-2-1_52KBB_2020-09-06_final.stac-item
2020-09-30 10:55:33	ga_s2am_ard_3-2-1_52JGN_2020-09-30_final.stac-item
2020-11-03 10:36:37	ga_s2am_ard_3-2-1_53HPC_2020-11-03_final.stac-item
2020-11-25 11:15:38	ga_s2am_ard_3-2-1_52JBN_2020-11-25_final.stac-item
2020-12-02 11:01:26	ga_s2am_ard_3-2-1_53LKD_2020-12-02_final.stac-item
2020-12-07 10:16:18	ga_s2am_ard_3-2-1_54HTJ_2020-12-07_final.stac-item
2020-12-15 11:13:23	ga_s2am_ard_3-2-1_52KBB_2020-12-15_final.stac-item
2021-01-11 11:03:20	ga_s2am_ard_3-2-1_52KEB_2021-01-11_final.stac-item
2021-02-08 10:27:04	ga_s2am_ard_3-2-1_53HPA_2021-02-08_final.stac-item
2021-02-26 11:23:49	ga_s2am_ard_3-2-1_51KZQ_2021-02-26_final.stac-item
2021-03-02 11:03:49	ga_s2am_ard_3-2-1_52KEV_2021-03-02_final.stac-item
2021-03-07 10:17:11	ga_s2am_ard_3-2-1_54HVE_2021-03-07_final.stac-item
2021-04-08 10:54:25	ga_s2am_ard_3-2-1_52JGS_2021-04-08_final.stac-item
2021-05-25 10:42:54	ga_s2am_ard_3-2-1_53KNT_2021-05-25_final.stac-item
2021-10-04 11:24:09	ga_s2am_ard_3-2-1_52KBU_2021-10-04_final.stac-item
2021-10-08 11:06:23	ga_s2am_ard_3-2-1_52HDK_2021-10-08_final
2021-11-13 11:27:00	ga_s2am_ard_3-2-1_51HVC_2021-11-13_final.stac-item
2021-11-22 11:57:09	ga_s2am_ard_3-2-1_50HLH_2021-11-22_final.stac-item
2021-12-23 11:21:54	ga_s2am_ard_3-2-1_52LBH_2021-12-23_final.stac-item
2022-01-19 11:13:37	ga_s2am_ard_3-2-1_52KCA_2022-01-19_final.stac-item
2022-01-27 10:34:47	ga_s2am_ard_3-2-1_53JQK_2022-01-27_final.stac-item
2022-02-21 11:21:27	ga_s2am_ard_3-2-1_51LZE_2022-02-21_final.stac-item
2022-02-26 12:15:23	ga_s2am_ard_3-2-1_49JGK_2022-02-26_final.stac-item
2022-05-08 10:07:01	ga_s2am_ard_3-2-1_54HWF_2022-05-08_final.stac-item
2022-06-04 11:32:54	ga_s2am_ard_3-2-1_51KVV_2022-06-04_final.stac-item
2022-07-06 10:35:18	ga_s2am_ard_3-2-1_53JPJ_2022-07-06_final.stac-item
2022-09-22 11:32:47	ga_s2am_ard_3-2-1_51KXV_2022-09-22_final.stac-item
2022-10-22 11:34:19	ga_s2am_ard_3-2-1_51KUP_2022-10-22_final.stac-item
2022-11-17 11:55:29	ga_s2am_ard_3-2-1_50JLQ_2022-11-17_final.stac-item
2022-12-02 11:02:59	ga_s2am_ard_3-2-1_52KGC_2022-12-02_final.stac-item
2022-12-14 11:47:02	ga_s2am_ard_3-2-1_50HPH_2022-12-14_final.stac-item
2023-01-04 11:15:06	ga_s2am_ard_3-2-1_52JBQ_2023-01-04_final.stac-item
2023-01-23 11:41:14	ga_s2am_ard_3-2-1_51LUF_2023-01-23_final.stac-item
2023-01-30 11:34:27	ga_s2am_ard_3-2-1_51JVN_2023-01-30_final.stac-item
2023-02-10 11:02:10	ga_s2am_ard_3-2-1_52KHF_2023-02-10_final.stac-item
2023-02-12 10:07:28	ga_s2am_ard_3-2-1_54HVD_2023-02-12_final
2023-03-01 11:32:38	ga_s2am_ard_3-2-1_51KXV_2023-03-01_final
2023-03-11 11:35:36	ga_s2am_ard_3-2-1_51JVH_2023-03-11_final
2023-03-15 11:14:21	ga_s2am_ard_3-2-1_51JZN_2023-03-15_final
2023-04-18 10:50:19	ga_s2am_ard_3-2-1_53LPH_2023-04-18_final
2023-05-25 10:40:43	ga_s2am_ard_3-2-1_53LPG_2023-05-25_final
2023-06-08 10:25:56	ga_s2am_ard_3-2-1_53JPF_2023-06-08_final
2023-07-21 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-07-21_final
2023-07-31 10:33:43	ga_s2am_ard_3-2-1_53KPQ_2023-07-31_final
2023-08-27 12:05:21	ga_s2am_ard_3-2-1_49JGL_2023-08-27_final
2023-09-01 11:13:38	ga_s2am_ard_3-2-1_52KDA_2023-09-01_final
2023-10-08 11:04:47	ga_s2am_ard_3-2-1_52JER_2023-10-08_final
2023-10-29 10:34:14	ga_s2am_ard_3-2-1_53JRM_2023-10-29_final
2024-01-17 10:34:42	ga_s2am_ard_3-2-1_53JQK_2024-01-17_final
2024-02-05 11:00:41	ga_s2am_ard_3-2-1_52LHM_2024-02-05_final
2024-03-11 11:55:56	ga_s2am_ard_3-2-1_50JLN_2024-03-11_final
2024-04-28 11:11:54	ga_s2am_ard_3-2-1_52LDH_2024-04-28_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

All years