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
2019-07-23 11:44:39	ga_s2am_ard_3-2-1_50JQT_2019-07-23_final.stac-item
2019-07-23 11:44:50	ga_s2am_ard_3-2-1_50JRS_2019-07-23_final.stac-item
2019-07-23 11:44:54	ga_s2am_ard_3-2-1_50JQS_2019-07-23_final.stac-item
2019-07-23 11:45:05	ga_s2am_ard_3-2-1_51JTL_2019-07-23_final.stac-item
2019-07-23 11:45:08	ga_s2am_ard_3-2-1_50JQR_2019-07-23_final.stac-item
2019-07-23 11:45:19	ga_s2am_ard_3-2-1_51JTK_2019-07-23_final.stac-item
2019-07-23 11:45:23	ga_s2am_ard_3-2-1_50JQQ_2019-07-23_final.stac-item
2019-07-23 11:45:34	ga_s2am_ard_3-2-1_51JTJ_2019-07-23_final.stac-item
2019-07-23 11:45:37	ga_s2am_ard_3-2-1_50JQP_2019-07-23_final.stac-item
2019-07-23 11:45:48	ga_s2am_ard_3-2-1_51JTH_2019-07-23_final.stac-item
2019-07-23 11:45:51	ga_s2am_ard_3-2-1_50JQN_2019-07-23_final.stac-item
2019-07-23 11:46:00	ga_s2am_ard_3-2-1_51JTG_2019-07-23_final.stac-item
2019-07-23 11:46:03	ga_s2am_ard_3-2-1_50JQM_2019-07-23_final.stac-item
2019-07-23 11:46:07	ga_s2am_ard_3-2-1_51JTG_2019-07-23_final.stac-item
2019-07-23 11:46:09	ga_s2am_ard_3-2-1_50JQM_2019-07-23_final.stac-item
2019-07-26 11:53:04	ga_s2am_ard_3-2-1_50KRD_2019-07-26_final.stac-item
2019-08-12 11:43:02	ga_s2am_ard_3-2-1_50KRD_2019-08-12_final.stac-item
2019-08-12 11:45:47	ga_s2am_ard_3-2-1_51JTH_2019-08-12_final.stac-item
2019-08-12 11:45:50	ga_s2am_ard_3-2-1_50JQN_2019-08-12_final.stac-item
2019-08-12 11:46:00	ga_s2am_ard_3-2-1_51JTG_2019-08-12_final.stac-item
2019-08-12 11:46:04	ga_s2am_ard_3-2-1_50JQM_2019-08-12_final.stac-item
2020-02-05 11:35:25	ga_s2am_ard_3-2-1_51JTJ_2020-02-05_final.stac-item
2020-02-05 11:35:29	ga_s2am_ard_3-2-1_50JQP_2020-02-05_final.stac-item
2020-02-05 11:35:39	ga_s2am_ard_3-2-1_51JTH_2020-02-05_final.stac-item
2020-02-05 11:35:42	ga_s2am_ard_3-2-1_50JQN_2020-02-05_final.stac-item
2020-02-05 11:35:54	ga_s2am_ard_3-2-1_51JTG_2020-02-05_final.stac-item
2020-02-05 11:35:57	ga_s2am_ard_3-2-1_50JQM_2020-02-05_final.stac-item
2020-02-05 11:36:09	ga_s2am_ard_3-2-1_51JTF_2020-02-05_final.stac-item
2020-02-05 11:36:11	ga_s2am_ard_3-2-1_50JQL_2020-02-05_final.stac-item
2020-02-15 11:35:24	ga_s2am_ard_3-2-1_51JTJ_2020-02-15_final.stac-item
2020-02-15 11:35:26	ga_s2am_ard_3-2-1_50JQP_2020-02-15_final.stac-item
2020-02-15 11:35:31	ga_s2am_ard_3-2-1_51JTJ_2020-02-15_final.stac-item
2020-02-15 11:35:32	ga_s2am_ard_3-2-1_50JQP_2020-02-15_final.stac-item
2020-02-15 11:35:41	ga_s2am_ard_3-2-1_51JTH_2020-02-15_final.stac-item
2020-02-15 11:35:44	ga_s2am_ard_3-2-1_50JQN_2020-02-15_final.stac-item
2020-02-15 11:35:56	ga_s2am_ard_3-2-1_51JTG_2020-02-15_final.stac-item
2020-02-15 11:35:58	ga_s2am_ard_3-2-1_50JQM_2020-02-15_final.stac-item
2020-02-15 11:36:11	ga_s2am_ard_3-2-1_51JTF_2020-02-15_final.stac-item
2020-02-15 11:36:13	ga_s2am_ard_3-2-1_50JQL_2020-02-15_final.stac-item
2020-02-15 11:36:25	ga_s2am_ard_3-2-1_51HTE_2020-02-15_final.stac-item
2020-02-15 11:36:27	ga_s2am_ard_3-2-1_50HQK_2020-02-15_final.stac-item
2020-02-15 11:36:40	ga_s2am_ard_3-2-1_51HTD_2020-02-15_final.stac-item
2020-02-15 11:36:42	ga_s2am_ard_3-2-1_50HQJ_2020-02-15_final.stac-item
2020-02-15 11:36:54	ga_s2am_ard_3-2-1_51HTC_2020-02-15_final.stac-item
2020-02-15 11:36:56	ga_s2am_ard_3-2-1_50HQH_2020-02-15_final.stac-item
2020-02-15 11:37:09	ga_s2am_ard_3-2-1_51HTB_2020-02-15_final
2020-08-03 11:37:07	ga_s2am_ard_3-2-1_51HTC_2020-08-03_final.stac-item
2020-08-03 11:37:09	ga_s2am_ard_3-2-1_50HQH_2020-08-03_final.stac-item
2020-08-03 11:37:21	ga_s2am_ard_3-2-1_51HTB_2020-08-03_final
2020-08-06 11:45:24	ga_s2am_ard_3-2-1_50JQQ_2020-08-06_final.stac-item
2020-08-06 11:45:35	ga_s2am_ard_3-2-1_51JTJ_2020-08-06_final.stac-item
2020-08-06 11:45:38	ga_s2am_ard_3-2-1_50JQP_2020-08-06_final.stac-item
2020-08-06 11:45:49	ga_s2am_ard_3-2-1_51JTH_2020-08-06_final.stac-item
2020-08-06 11:45:52	ga_s2am_ard_3-2-1_50JQN_2020-08-06_final.stac-item
2020-08-06 11:46:01	ga_s2am_ard_3-2-1_51JTG_2020-08-06_final.stac-item
2020-08-06 11:46:04	ga_s2am_ard_3-2-1_50JQM_2020-08-06_final.stac-item
2020-08-06 11:46:08	ga_s2am_ard_3-2-1_51JTG_2020-08-06_final.stac-item
2020-08-06 11:46:10	ga_s2am_ard_3-2-1_50JQM_2020-08-06_final.stac-item
2020-08-09 11:53:05	ga_s2am_ard_3-2-1_50KRD_2020-08-09_final.stac-item
2020-08-09 11:53:16	ga_s2am_ard_3-2-1_50KRC_2020-08-09_final.stac-item
2020-08-16 11:43:10	ga_s2am_ard_3-2-1_50KRD_2020-08-16_final.stac-item
2020-08-16 11:43:24	ga_s2am_ard_3-2-1_50KRC_2020-08-16_final.stac-item
2020-08-16 11:43:39	ga_s2am_ard_3-2-1_50KRB_2020-08-16_final.stac-item
2020-08-16 11:43:42	ga_s2am_ard_3-2-1_50KQB_2020-08-16_final.stac-item
2020-08-16 11:43:53	ga_s2am_ard_3-2-1_50KRA_2020-08-16_final.stac-item
2020-08-16 11:43:57	ga_s2am_ard_3-2-1_50KQA_2020-08-16_final.stac-item
2020-08-16 11:44:08	ga_s2am_ard_3-2-1_50KRV_2020-08-16_final.stac-item
2020-08-16 11:44:11	ga_s2am_ard_3-2-1_50KQV_2020-08-16_final.stac-item
2020-08-16 11:44:22	ga_s2am_ard_3-2-1_50KRU_2020-08-16_final.stac-item
2020-08-16 11:44:26	ga_s2am_ard_3-2-1_50KQU_2020-08-16_final.stac-item
2020-08-16 11:44:36	ga_s2am_ard_3-2-1_50JRT_2020-08-16_final.stac-item
2020-08-16 11:44:40	ga_s2am_ard_3-2-1_50JQT_2020-08-16_final.stac-item
2020-08-16 11:44:51	ga_s2am_ard_3-2-1_50JRS_2020-08-16_final.stac-item
2020-08-16 11:44:55	ga_s2am_ard_3-2-1_50JQS_2020-08-16_final.stac-item
2020-08-19 11:53:04	ga_s2am_ard_3-2-1_50KRD_2020-08-19_final.stac-item
2020-08-19 11:53:16	ga_s2am_ard_3-2-1_50KRC_2020-08-19_final.stac-item
2022-05-05 11:35:38	ga_s2am_ard_3-2-1_51JTJ_2022-05-05_final.stac-item
2022-05-05 11:35:42	ga_s2am_ard_3-2-1_50JQP_2022-05-05_final.stac-item
2022-05-05 11:35:53	ga_s2am_ard_3-2-1_51JTH_2022-05-05_final.stac-item
2022-05-05 11:35:55	ga_s2am_ard_3-2-1_50JQN_2022-05-05_final.stac-item
2022-05-15 11:35:38	ga_s2am_ard_3-2-1_51JTJ_2022-05-15_final.stac-item
2022-05-15 11:35:41	ga_s2am_ard_3-2-1_50JQP_2022-05-15_final.stac-item
2022-05-15 11:35:52	ga_s2am_ard_3-2-1_51JTH_2022-05-15_final.stac-item
2022-05-15 11:35:55	ga_s2am_ard_3-2-1_50JQN_2022-05-15_final.stac-item
2022-05-15 11:36:07	ga_s2am_ard_3-2-1_51JTG_2022-05-15_final.stac-item
2022-05-15 11:36:09	ga_s2am_ard_3-2-1_50JQM_2022-05-15_final.stac-item
2022-05-15 11:36:21	ga_s2am_ard_3-2-1_51JTF_2022-05-15_final.stac-item
2022-05-15 11:36:24	ga_s2am_ard_3-2-1_50JQL_2022-05-15_final.stac-item
2022-05-15 11:36:36	ga_s2am_ard_3-2-1_51HTE_2022-05-15_final.stac-item
2022-05-15 11:36:38	ga_s2am_ard_3-2-1_50HQK_2022-05-15_final.stac-item
2022-05-15 11:36:51	ga_s2am_ard_3-2-1_51HTD_2022-05-15_final.stac-item
2022-05-15 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2022-05-15_final.stac-item
2022-05-15 11:37:05	ga_s2am_ard_3-2-1_51HTC_2022-05-15_final.stac-item
2022-05-15 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-05-15_final.stac-item
2022-05-15 11:37:20	ga_s2am_ard_3-2-1_51HTB_2022-05-15_final
2023-02-12 11:45:16	ga_s2am_ard_3-2-1_50JQQ_2023-02-12_nrt.stac-item
2023-02-12 11:45:30	ga_s2am_ard_3-2-1_50JQP_2023-02-12_nrt.stac-item
2023-02-12 11:45:42	ga_s2am_ard_3-2-1_51JTH_2023-02-12_nrt.stac-item
2023-02-12 11:45:45	ga_s2am_ard_3-2-1_50JQN_2023-02-12_nrt.stac-item
2023-02-12 11:45:55	ga_s2am_ard_3-2-1_51JTG_2023-02-12_nrt.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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