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
2019-06-25 10:41:24	ga_s2am_ard_3-2-1_53LQD_2019-06-25_final.stac-item
2019-06-25 10:41:39	ga_s2am_ard_3-2-1_53LQC_2019-06-25_final
2019-06-29 10:25:44	ga_s2am_ard_3-2-1_53JPG_2019-06-29_final.stac-item
2019-07-09 10:25:45	ga_s2am_ard_3-2-1_53JPG_2019-07-09_final.stac-item
2019-07-09 10:25:57	ga_s2am_ard_3-2-1_53JPF_2019-07-09_final.stac-item
2019-07-09 10:26:12	ga_s2am_ard_3-2-1_53HPE_2019-07-09_final.stac-item
2019-07-09 10:26:27	ga_s2am_ard_3-2-1_53HPD_2019-07-09_final.stac-item
2019-07-09 10:26:41	ga_s2am_ard_3-2-1_53HPC_2019-07-09_final.stac-item
2019-07-09 10:26:55	ga_s2am_ard_3-2-1_53HPB_2019-07-09_final.stac-item
2019-07-09 10:27:10	ga_s2am_ard_3-2-1_53HPA_2019-07-09_final.stac-item
2022-12-26 10:40:06	ga_s2am_ard_3-2-1_53LQJ_2022-12-26_nrt.stac-item
2022-12-26 10:40:20	ga_s2am_ard_3-2-1_53LQH_2022-12-26_nrt.stac-item
2022-12-26 10:41:18	ga_s2am_ard_3-2-1_53LQD_2022-12-26_final.stac-item
2022-12-26 10:41:33	ga_s2am_ard_3-2-1_53LQC_2022-12-26_final.stac-item
2022-12-26 10:41:47	ga_s2am_ard_3-2-1_53KQB_2022-12-26_final.stac-item
2022-12-26 10:42:02	ga_s2am_ard_3-2-1_53KQA_2022-12-26_final.stac-item
2022-12-26 10:42:16	ga_s2am_ard_3-2-1_53KQV_2022-12-26_final.stac-item
2022-12-26 10:42:30	ga_s2am_ard_3-2-1_53KQU_2022-12-26_final.stac-item
2022-12-26 10:42:45	ga_s2am_ard_3-2-1_53KQT_2022-12-26_final.stac-item
2022-12-26 10:42:59	ga_s2am_ard_3-2-1_53KQS_2022-12-26_final.stac-item
2022-12-26 10:43:13	ga_s2am_ard_3-2-1_53KQR_2022-12-26_final.stac-item
2023-01-22 10:33:01	ga_s2am_ard_3-2-1_53KQS_2023-01-22_final.stac-item
2023-01-22 10:33:16	ga_s2am_ard_3-2-1_53KQR_2023-01-22_final.stac-item
2023-01-22 10:33:30	ga_s2am_ard_3-2-1_53KQQ_2023-01-22_final.stac-item
2023-01-22 10:33:45	ga_s2am_ard_3-2-1_53KQP_2023-01-22_final.stac-item
2023-01-22 10:33:48	ga_s2am_ard_3-2-1_53KPP_2023-01-22_final.stac-item
2023-01-22 10:33:59	ga_s2am_ard_3-2-1_53JQN_2023-01-22_final.stac-item
2023-01-22 10:34:03	ga_s2am_ard_3-2-1_53JPN_2023-01-22_final.stac-item
2023-01-22 10:34:14	ga_s2am_ard_3-2-1_53JQM_2023-01-22_final.stac-item
2023-01-22 10:34:16	ga_s2am_ard_3-2-1_53JPM_2023-01-22_final.stac-item
2023-01-22 10:34:22	ga_s2am_ard_3-2-1_53JQM_2023-01-22_final.stac-item
2023-01-22 10:34:22	ga_s2am_ard_3-2-1_53JQL_2023-01-22_final.stac-item
2023-01-22 10:34:23	ga_s2am_ard_3-2-1_53JPL_2023-01-22_final.stac-item
2023-01-22 10:34:23	ga_s2am_ard_3-2-1_53JPM_2023-01-22_final.stac-item
2023-01-22 10:34:29	ga_s2am_ard_3-2-1_53JQL_2023-01-22_final.stac-item
2023-01-22 10:34:32	ga_s2am_ard_3-2-1_53JPL_2023-01-22_final.stac-item
2023-01-22 10:34:43	ga_s2am_ard_3-2-1_53JQK_2023-01-22_final.stac-item
2023-01-22 10:34:46	ga_s2am_ard_3-2-1_53JPK_2023-01-22_final.stac-item
2023-01-22 10:34:57	ga_s2am_ard_3-2-1_53JQJ_2023-01-22_final.stac-item
2023-01-22 10:35:01	ga_s2am_ard_3-2-1_53JPJ_2023-01-22_final.stac-item
2023-01-22 10:35:11	ga_s2am_ard_3-2-1_53JQH_2023-01-22_final.stac-item
2023-01-22 10:35:15	ga_s2am_ard_3-2-1_53JPH_2023-01-22_final.stac-item
2023-01-22 10:35:30	ga_s2am_ard_3-2-1_53JPG_2023-01-22_final.stac-item
2023-01-22 10:35:44	ga_s2am_ard_3-2-1_53JPF_2023-01-22_final.stac-item
2023-01-22 10:35:58	ga_s2am_ard_3-2-1_53HPE_2023-01-22_final.stac-item
2023-01-22 10:36:13	ga_s2am_ard_3-2-1_53HPD_2023-01-22_final.stac-item
2023-01-25 10:40:04	ga_s2am_ard_3-2-1_53LQJ_2023-01-25_nrt.stac-item
2023-01-25 10:40:19	ga_s2am_ard_3-2-1_53LQH_2023-01-25_nrt.stac-item
2023-01-25 10:40:33	ga_s2am_ard_3-2-1_53LQG_2023-01-25_final
2023-01-25 10:41:17	ga_s2am_ard_3-2-1_53LQD_2023-01-25_final.stac-item
2023-01-25 10:41:31	ga_s2am_ard_3-2-1_53LQC_2023-01-25_final.stac-item
2023-01-25 10:41:46	ga_s2am_ard_3-2-1_53KQB_2023-01-25_final.stac-item
2023-01-25 10:42:00	ga_s2am_ard_3-2-1_53KQA_2023-01-25_final.stac-item
2023-01-25 10:42:14	ga_s2am_ard_3-2-1_53KQV_2023-01-25_final.stac-item
2023-01-25 10:42:24	ga_s2am_ard_3-2-1_53KQU_2023-01-25_final.stac-item
2023-01-25 10:42:30	ga_s2am_ard_3-2-1_53KQU_2023-01-25_final.stac-item
2023-01-25 10:42:43	ga_s2am_ard_3-2-1_53KQT_2023-01-25_final.stac-item
2023-01-25 10:42:58	ga_s2am_ard_3-2-1_53KQS_2023-01-25_final.stac-item
2023-01-28 10:50:00	ga_s2am_ard_3-2-1_53LQJ_2023-01-28_final
2023-01-28 10:50:14	ga_s2am_ard_3-2-1_53LQH_2023-01-28_final
2023-03-03 10:33:03	ga_s2am_ard_3-2-1_53KQS_2023-03-03_final
2024-05-23 10:25:39	ga_s2am_ard_3-2-1_53JPG_2024-05-23_nrt
2024-05-23 10:25:51	ga_s2am_ard_3-2-1_53JPF_2024-05-23_nrt
2024-05-23 10:26:06	ga_s2am_ard_3-2-1_53HPE_2024-05-23_nrt
2024-05-23 10:26:21	ga_s2am_ard_3-2-1_53HPD_2024-05-23_nrt
2024-05-23 10:26:35	ga_s2am_ard_3-2-1_53HPC_2024-05-23_nrt
2024-05-23 10:26:44	ga_s2am_ard_3-2-1_53HPB_2024-05-23_nrt
2024-05-23 10:26:51	ga_s2am_ard_3-2-1_53HPB_2024-05-23_nrt
2024-05-23 10:27:04	ga_s2am_ard_3-2-1_53HPA_2024-05-23_nrt
2024-05-23 10:27:13	ga_s2am_ard_3-2-1_53HPV_2024-05-23_nrt
2024-05-26 10:33:06	ga_s2am_ard_3-2-1_53KQS_2024-05-26_nrt
2024-05-26 10:33:20	ga_s2am_ard_3-2-1_53KQR_2024-05-26_nrt
2024-05-26 10:33:35	ga_s2am_ard_3-2-1_53KQQ_2024-05-26_nrt
2024-05-26 10:33:49	ga_s2am_ard_3-2-1_53KQP_2024-05-26_nrt
2024-05-26 10:33:53	ga_s2am_ard_3-2-1_53KPP_2024-05-26_nrt
2024-05-26 10:34:04	ga_s2am_ard_3-2-1_53JQN_2024-05-26_nrt
2024-05-26 10:34:07	ga_s2am_ard_3-2-1_53JPN_2024-05-26_nrt
2024-05-26 10:34:18	ga_s2am_ard_3-2-1_53JQM_2024-05-26_nrt
2024-05-26 10:34:22	ga_s2am_ard_3-2-1_53JPM_2024-05-26_nrt
2024-05-26 10:34:33	ga_s2am_ard_3-2-1_53JQL_2024-05-26_nrt
2024-05-26 10:34:36	ga_s2am_ard_3-2-1_53JPL_2024-05-26_nrt
2024-05-26 10:34:59	ga_s2am_ard_3-2-1_53JQJ_2024-05-26_nrt
2024-05-26 10:35:01	ga_s2am_ard_3-2-1_53JPJ_2024-05-26_nrt
2024-05-26 10:35:20	ga_s2am_ard_3-2-1_53JPH_2024-05-26_nrt
2024-05-26 10:35:34	ga_s2am_ard_3-2-1_53JPG_2024-05-26_nrt
2024-05-26 10:36:03	ga_s2am_ard_3-2-1_53HPE_2024-05-26_nrt
2024-05-26 10:36:17	ga_s2am_ard_3-2-1_53HPD_2024-05-26_nrt
2024-05-29 10:40:09	ga_s2am_ard_3-2-1_53LQJ_2024-05-29_nrt
2024-05-29 10:40:24	ga_s2am_ard_3-2-1_53LQH_2024-05-29_nrt
2024-05-29 10:40:38	ga_s2am_ard_3-2-1_53LQG_2024-05-29_nrt
2024-06-01 10:50:06	ga_s2am_ard_3-2-1_53LQJ_2024-06-01_nrt
2024-06-01 10:50:20	ga_s2am_ard_3-2-1_53LQH_2024-06-01_nrt
2024-06-02 10:25:44	ga_s2am_ard_3-2-1_53JPG_2024-06-02_nrt
2024-06-02 10:25:56	ga_s2am_ard_3-2-1_53JPF_2024-06-02_nrt
2024-06-02 10:26:11	ga_s2am_ard_3-2-1_53HPE_2024-06-02_nrt
2024-06-02 10:26:26	ga_s2am_ard_3-2-1_53HPD_2024-06-02_nrt
2024-06-02 10:26:40	ga_s2am_ard_3-2-1_53HPC_2024-06-02_nrt
2024-06-02 10:26:49	ga_s2am_ard_3-2-1_53HPB_2024-06-02_nrt
2024-06-02 10:26:56	ga_s2am_ard_3-2-1_53HPB_2024-06-02_nrt
2024-06-02 10:27:09	ga_s2am_ard_3-2-1_53HPA_2024-06-02_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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