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
2018-10-23 11:26:17	ga_s2am_ard_3-2-1_51KXS_2018-10-23_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KUS_2018-10-23_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KVS_2018-10-23_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KWS_2018-10-23_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KXS_2018-10-23_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_53KKS_2018-10-24_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_52KEB_2018-10-24_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_52KFB_2018-10-24_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_52KGB_2018-10-24_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_52KHB_2018-10-24_final.stac-item
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_53KKS_2018-11-03_final.stac-item
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_52KEB_2018-11-03_final.stac-item
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_52KFB_2018-11-03_final.stac-item
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_52KGB_2018-11-03_final.stac-item
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_52KHB_2018-11-03_final.stac-item
2018-11-11 12:03:28	ga_s2am_ard_3-2-1_50KNB_2018-11-11_final.stac-item
2018-11-11 12:03:33	ga_s2am_ard_3-2-1_50KMB_2018-11-11_final.stac-item
2018-11-11 12:03:36	ga_s2am_ard_3-2-1_50KLB_2018-11-11_final.stac-item
2018-11-11 12:03:39	ga_s2am_ard_3-2-1_50KKB_2018-11-11_final.stac-item
2018-11-11 12:03:54	ga_s2am_ard_3-2-1_49KHR_2018-11-11_final.stac-item
2019-07-22 12:13:45	ga_s2am_ard_3-2-1_50KKB_2019-07-22_final.stac-item
2019-07-23 10:02:50	ga_s2am_ard_3-2-1_55KES_2019-07-23_final.stac-item
2019-07-23 10:02:53	ga_s2am_ard_3-2-1_55KDS_2019-07-23_final.stac-item
2019-07-23 10:02:56	ga_s2am_ard_3-2-1_55KCS_2019-07-23_final.stac-item
2019-07-23 10:02:59	ga_s2am_ard_3-2-1_55KBS_2019-07-23_final.stac-item
2019-07-23 10:03:00	ga_s2am_ard_3-2-1_54KZB_2019-07-23_final.stac-item
2019-07-23 10:03:14	ga_s2am_ard_3-2-1_54KZA_2019-07-23_final.stac-item
2019-07-25 10:43:06	ga_s2am_ard_3-2-1_53KQS_2019-07-25_final.stac-item
2019-07-25 10:43:10	ga_s2am_ard_3-2-1_53KPS_2019-07-25_final.stac-item
2019-07-25 10:43:13	ga_s2am_ard_3-2-1_53KNS_2019-07-25_final.stac-item
2019-07-25 10:43:16	ga_s2am_ard_3-2-1_53KMS_2019-07-25_final.stac-item
2019-08-02 10:02:49	ga_s2am_ard_3-2-1_55KES_2019-08-02_final.stac-item
2019-08-02 10:02:53	ga_s2am_ard_3-2-1_55KDS_2019-08-02_final.stac-item
2019-08-02 10:02:56	ga_s2am_ard_3-2-1_55KCS_2019-08-02_final.stac-item
2019-08-02 10:02:59	ga_s2am_ard_3-2-1_55KBS_2019-08-02_final.stac-item
2019-08-02 10:02:59	ga_s2am_ard_3-2-1_54KZB_2019-08-02_final.stac-item
2019-08-02 10:03:14	ga_s2am_ard_3-2-1_54KZA_2019-08-02_final.stac-item
2019-08-11 12:13:43	ga_s2am_ard_3-2-1_50KKB_2019-08-11_final.stac-item
2019-08-12 10:02:48	ga_s2am_ard_3-2-1_55KES_2019-08-12_final.stac-item
2019-08-12 10:02:52	ga_s2am_ard_3-2-1_55KDS_2019-08-12_final.stac-item
2019-08-12 10:02:55	ga_s2am_ard_3-2-1_55KCS_2019-08-12_final.stac-item
2019-08-12 10:02:58	ga_s2am_ard_3-2-1_55KBS_2019-08-12_final.stac-item
2019-08-12 10:02:58	ga_s2am_ard_3-2-1_54KZB_2019-08-12_final.stac-item
2019-08-12 10:03:13	ga_s2am_ard_3-2-1_54KZA_2019-08-12_final.stac-item
2019-08-13 11:13:19	ga_s2am_ard_3-2-1_52KEB_2019-08-13_final.stac-item
2019-08-13 11:13:22	ga_s2am_ard_3-2-1_52KDB_2019-08-13_final.stac-item
2019-08-13 11:13:25	ga_s2am_ard_3-2-1_52KCB_2019-08-13_final.stac-item
2019-08-13 11:13:29	ga_s2am_ard_3-2-1_52KBB_2019-08-13_final.stac-item
2019-08-13 11:13:32	ga_s2am_ard_3-2-1_51KZS_2019-08-13_final.stac-item
2019-08-13 11:13:44	ga_s2am_ard_3-2-1_51KZR_2019-08-13_final.stac-item
2019-08-14 10:43:04	ga_s2am_ard_3-2-1_53KQS_2019-08-14_final.stac-item
2019-08-14 10:43:08	ga_s2am_ard_3-2-1_53KPS_2019-08-14_final.stac-item
2019-08-14 10:43:12	ga_s2am_ard_3-2-1_53KNS_2019-08-14_final.stac-item
2019-08-14 10:43:15	ga_s2am_ard_3-2-1_53KMS_2019-08-14_final.stac-item
2022-09-14 10:33:08	ga_s2am_ard_3-2-1_54KUB_2022-09-14_final.stac-item
2022-09-14 10:33:12	ga_s2am_ard_3-2-1_54KTB_2022-09-14_final.stac-item
2022-09-14 10:33:12	ga_s2am_ard_3-2-1_53KRS_2022-09-14_final.stac-item
2022-09-14 10:33:16	ga_s2am_ard_3-2-1_53KQS_2022-09-14_final.stac-item
2022-09-14 10:33:22	ga_s2am_ard_3-2-1_53KPS_2022-09-14_final.stac-item
2022-09-14 10:33:27	ga_s2am_ard_3-2-1_53KRR_2022-09-14_final.stac-item
2022-09-16 11:13:24	ga_s2am_ard_3-2-1_52KEB_2022-09-16_final.stac-item
2022-09-16 11:13:28	ga_s2am_ard_3-2-1_52KDB_2022-09-16_final.stac-item
2022-09-16 11:13:31	ga_s2am_ard_3-2-1_52KCB_2022-09-16_final.stac-item
2022-09-16 11:13:35	ga_s2am_ard_3-2-1_52KBB_2022-09-16_final.stac-item
2022-09-16 11:13:38	ga_s2am_ard_3-2-1_51KZS_2022-09-16_final.stac-item
2022-09-16 11:13:49	ga_s2am_ard_3-2-1_51KZR_2022-09-16_final.stac-item
2022-09-17 10:43:10	ga_s2am_ard_3-2-1_53KQS_2022-09-17_final.stac-item
2022-09-17 10:43:14	ga_s2am_ard_3-2-1_53KPS_2022-09-17_final.stac-item
2022-09-17 10:43:17	ga_s2am_ard_3-2-1_53KNS_2022-09-17_final.stac-item
2022-09-17 10:43:20	ga_s2am_ard_3-2-1_53KMS_2022-09-17_final.stac-item
2022-09-22 09:52:49	ga_s2am_ard_3-2-1_55KGS_2022-09-22_final.stac-item
2022-09-22 09:52:53	ga_s2am_ard_3-2-1_55KFS_2022-09-22_final.stac-item
2022-09-22 09:52:56	ga_s2am_ard_3-2-1_55KES_2022-09-22_final.stac-item
2022-09-22 09:53:02	ga_s2am_ard_3-2-1_55KDS_2022-09-22_final.stac-item
2022-09-23 09:22:46	ga_s2am_ard_3-2-1_56KQB_2022-09-22_interim
2022-09-23 11:03:14	ga_s2am_ard_3-2-1_53KKS_2022-09-23_final.stac-item
2022-09-23 11:03:16	ga_s2am_ard_3-2-1_52KHB_2022-09-23_final.stac-item
2022-09-23 11:03:20	ga_s2am_ard_3-2-1_52KGB_2022-09-23_final.stac-item
2022-09-23 11:03:23	ga_s2am_ard_3-2-1_52KFB_2022-09-23_final.stac-item
2022-09-23 11:03:27	ga_s2am_ard_3-2-1_52KEB_2022-09-23_final.stac-item
2022-09-26 11:13:22	ga_s2am_ard_3-2-1_52KEB_2022-09-26_final.stac-item
2022-09-26 11:13:26	ga_s2am_ard_3-2-1_52KDB_2022-09-26_final.stac-item
2022-09-26 11:13:29	ga_s2am_ard_3-2-1_52KCB_2022-09-26_final.stac-item
2022-09-26 11:13:33	ga_s2am_ard_3-2-1_52KBB_2022-09-26_final.stac-item
2022-09-26 11:13:36	ga_s2am_ard_3-2-1_51KZS_2022-09-26_final.stac-item
2022-09-26 11:13:47	ga_s2am_ard_3-2-1_51KZR_2022-09-26_final.stac-item
2022-09-28 10:12:57	ga_s2am_ard_3-2-1_55KBS_2022-09-28_final.stac-item
2022-09-28 10:12:57	ga_s2am_ard_3-2-1_54KZB_2022-09-28_final.stac-item
2022-09-28 10:13:01	ga_s2am_ard_3-2-1_54KYB_2022-09-28_final.stac-item
2022-09-28 10:13:05	ga_s2am_ard_3-2-1_54KXB_2022-09-28_final.stac-item
2022-09-28 10:13:11	ga_s2am_ard_3-2-1_54KWB_2022-09-28_final.stac-item
2022-09-30 10:53:28	ga_s2am_ard_3-2-1_52KGB_2022-09-30_final.stac-item
2023-01-01 11:03:07	ga_s2am_ard_3-2-1_53KKS_2023-01-01_final.stac-item
2023-01-01 11:03:08	ga_s2am_ard_3-2-1_52KHB_2023-01-01_final.stac-item
2023-01-01 11:03:12	ga_s2am_ard_3-2-1_52KGB_2023-01-01_final.stac-item
2023-01-01 11:03:15	ga_s2am_ard_3-2-1_52KFB_2023-01-01_final.stac-item
2023-01-01 11:03:19	ga_s2am_ard_3-2-1_52KEB_2023-01-01_final.stac-item
2023-01-05 10:43:00	ga_s2am_ard_3-2-1_53KQS_2023-01-05_final.stac-item
2023-01-05 10:43:04	ga_s2am_ard_3-2-1_53KPS_2023-01-05_final.stac-item
2023-01-05 10:43:07	ga_s2am_ard_3-2-1_53KNS_2023-01-05_final.stac-item

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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