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
2018-11-11 10:26:35	ga_s2am_ard_3-2-1_54HUG_2018-11-11_final.stac-item
2018-11-11 10:26:40	ga_s2am_ard_3-2-1_54HTG_2018-11-11_final.stac-item
2018-11-11 10:26:42	ga_s2am_ard_3-2-1_53HQB_2018-11-11_final.stac-item
2018-11-11 10:26:45	ga_s2am_ard_3-2-1_53HPB_2018-11-11_final.stac-item
2018-11-11 10:26:49	ga_s2am_ard_3-2-1_53HNB_2018-11-11_final.stac-item
2018-11-11 10:26:56	ga_s2am_ard_3-2-1_53HQA_2018-11-11_final.stac-item
2018-11-16 09:36:20	ga_s2am_ard_3-2-1_56HKG_2018-11-16_final.stac-item
2018-11-16 09:36:22	ga_s2am_ard_3-2-1_55HGB_2018-11-16_final.stac-item
2018-11-16 09:36:26	ga_s2am_ard_3-2-1_55HFB_2018-11-16_final.stac-item
2018-11-16 09:36:36	ga_s2am_ard_3-2-1_55HGA_2018-11-16_final.stac-item
2019-06-29 10:26:45	ga_s2am_ard_3-2-1_54HUG_2019-06-29_final.stac-item
2019-06-29 10:26:49	ga_s2am_ard_3-2-1_54HTG_2019-06-29_final.stac-item
2019-06-29 10:26:51	ga_s2am_ard_3-2-1_53HQB_2019-06-29_final.stac-item
2019-06-29 10:26:55	ga_s2am_ard_3-2-1_53HPB_2019-06-29_final.stac-item
2019-06-29 10:26:58	ga_s2am_ard_3-2-1_53HNB_2019-06-29_final.stac-item
2019-06-29 10:27:06	ga_s2am_ard_3-2-1_53HQA_2019-06-29_final.stac-item
2019-07-06 10:16:44	ga_s2am_ard_3-2-1_54HWG_2019-07-06_final.stac-item
2019-07-06 10:16:47	ga_s2am_ard_3-2-1_54HVG_2019-07-06_final.stac-item
2019-07-06 10:16:51	ga_s2am_ard_3-2-1_54HUG_2019-07-06_final.stac-item
2019-07-06 10:16:54	ga_s2am_ard_3-2-1_54HTG_2019-07-06_final.stac-item
2019-07-06 10:16:57	ga_s2am_ard_3-2-1_53HQB_2019-07-06_final.stac-item
2019-07-06 10:17:10	ga_s2am_ard_3-2-1_53HQA_2019-07-06_final.stac-item
2019-07-09 10:26:45	ga_s2am_ard_3-2-1_54HUG_2019-07-09_final.stac-item
2019-07-09 10:26:50	ga_s2am_ard_3-2-1_54HTG_2019-07-09_final.stac-item
2019-07-09 10:26:52	ga_s2am_ard_3-2-1_53HQB_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 10:26:59	ga_s2am_ard_3-2-1_53HNB_2019-07-09_final.stac-item
2019-07-09 10:27:06	ga_s2am_ard_3-2-1_53HQA_2019-07-09_final.stac-item
2019-07-19 10:26:45	ga_s2am_ard_3-2-1_54HUG_2019-07-19_final.stac-item
2019-07-19 10:26:50	ga_s2am_ard_3-2-1_54HTG_2019-07-19_final.stac-item
2019-07-19 10:26:52	ga_s2am_ard_3-2-1_53HQB_2019-07-19_final.stac-item
2019-07-19 10:26:55	ga_s2am_ard_3-2-1_53HPB_2019-07-19_final.stac-item
2019-07-19 10:26:59	ga_s2am_ard_3-2-1_53HNB_2019-07-19_final.stac-item
2019-07-19 10:27:06	ga_s2am_ard_3-2-1_53HQA_2019-07-19_final.stac-item
2021-08-22 09:36:28	ga_s2am_ard_3-2-1_56HKG_2021-08-22_final.stac-item
2023-04-30 11:37:12	ga_s2am_ard_3-2-1_51HUB_2023-04-30_final
2023-04-30 11:37:16	ga_s2am_ard_3-2-1_51HTB_2023-04-30_final
2023-04-30 11:37:17	ga_s2am_ard_3-2-1_50HQG_2023-04-30_final
2023-04-30 11:37:21	ga_s2am_ard_3-2-1_50HPG_2023-04-30_final
2023-04-30 11:37:26	ga_s2am_ard_3-2-1_50HNG_2023-04-30_final
2023-04-30 11:37:28	ga_s2am_ard_3-2-1_50HQF_2023-04-30_nrt
2023-05-03 11:47:17	ga_s2am_ard_3-2-1_50HPG_2023-05-03_final
2023-05-03 11:47:21	ga_s2am_ard_3-2-1_50HNG_2023-05-03_final
2023-05-03 11:47:24	ga_s2am_ard_3-2-1_50HMG_2023-05-03_final
2023-05-03 11:47:27	ga_s2am_ard_3-2-1_50HLG_2023-05-03_final
2023-05-07 09:46:27	ga_s2am_ard_3-2-1_55HFB_2023-05-07_final
2023-05-07 09:46:31	ga_s2am_ard_3-2-1_55HEB_2023-05-07_final
2023-05-07 09:46:35	ga_s2am_ard_3-2-1_55HDB_2023-05-07_final
2023-05-07 09:46:39	ga_s2am_ard_3-2-1_55HCB_2023-05-07_final
2023-05-10 09:56:30	ga_s2am_ard_3-2-1_55HDB_2023-05-10_final
2023-05-10 09:56:34	ga_s2am_ard_3-2-1_55HCB_2023-05-10_final
2023-05-10 09:56:37	ga_s2am_ard_3-2-1_55HBB_2023-05-10_final
2023-05-10 09:56:39	ga_s2am_ard_3-2-1_54HYG_2023-05-10_final
2023-05-10 09:56:45	ga_s2am_ard_3-2-1_54HXG_2023-05-10_final
2023-05-10 09:56:53	ga_s2am_ard_3-2-1_54HYF_2023-05-10_final
2023-05-10 11:37:12	ga_s2am_ard_3-2-1_51HUB_2023-05-10_final
2023-05-10 11:37:15	ga_s2am_ard_3-2-1_51HTB_2023-05-10_final
2023-05-10 11:37:17	ga_s2am_ard_3-2-1_50HQG_2023-05-10_final
2023-05-10 11:37:19	ga_s2am_ard_3-2-1_50HPG_2023-05-10_final
2023-05-10 11:37:24	ga_s2am_ard_3-2-1_51HTB_2023-05-10_final
2023-05-10 11:37:24	ga_s2am_ard_3-2-1_50HQG_2023-05-10_final
2023-05-10 11:37:24	ga_s2am_ard_3-2-1_50HQF_2023-05-10_nrt
2023-05-10 11:37:26	ga_s2am_ard_3-2-1_50HPG_2023-05-10_final
2023-05-10 11:37:28	ga_s2am_ard_3-2-1_50HNG_2023-05-10_final
2023-05-13 10:06:32	ga_s2am_ard_3-2-1_55HBB_2023-05-13_final
2023-05-13 10:06:34	ga_s2am_ard_3-2-1_54HYG_2023-05-13_final
2023-05-13 10:06:39	ga_s2am_ard_3-2-1_54HXG_2023-05-13_final
2023-05-13 10:06:42	ga_s2am_ard_3-2-1_54HWG_2023-05-13_final
2023-05-13 10:06:46	ga_s2am_ard_3-2-1_54HVG_2023-05-13_final
2023-05-14 09:36:22	ga_s2am_ard_3-2-1_56HLG_2023-05-14_final
2023-05-14 09:36:26	ga_s2am_ard_3-2-1_56HKG_2023-05-14_final
2024-04-21 11:27:12	ga_s2am_ard_3-2-1_51HWB_2024-04-21_final
2024-04-21 11:27:14	ga_s2am_ard_3-2-1_51HVB_2024-04-21_final
2024-04-25 09:26:21	ga_s2am_ard_3-2-1_56HNG_2024-04-24_nrt
2024-04-25 09:26:25	ga_s2am_ard_3-2-1_56HMG_2024-04-24_nrt
2024-04-25 09:26:29	ga_s2am_ard_3-2-1_56HLG_2024-04-24_final
2024-04-25 09:26:34	ga_s2am_ard_3-2-1_56HKG_2024-04-24_final
2024-04-26 10:36:48	ga_s2am_ard_3-2-1_53HPB_2024-04-26_final
2024-04-26 10:36:52	ga_s2am_ard_3-2-1_53HNB_2024-04-26_final
2024-04-26 10:36:56	ga_s2am_ard_3-2-1_53HMB_2024-04-26_final
2024-04-26 10:36:59	ga_s2am_ard_3-2-1_53HLB_2024-04-26_nrt
2024-04-27 10:06:35	ga_s2am_ard_3-2-1_55HBB_2024-04-27_final
2024-04-27 10:06:37	ga_s2am_ard_3-2-1_54HYG_2024-04-27_final
2024-04-27 10:06:41	ga_s2am_ard_3-2-1_54HXG_2024-04-27_final
2024-04-27 10:06:45	ga_s2am_ard_3-2-1_54HWG_2024-04-27_final
2024-04-27 10:06:48	ga_s2am_ard_3-2-1_54HVG_2024-04-27_final
2024-04-27 11:47:19	ga_s2am_ard_3-2-1_50HPG_2024-04-27_final
2024-04-27 11:47:23	ga_s2am_ard_3-2-1_50HNG_2024-04-27_final
2024-04-27 11:47:26	ga_s2am_ard_3-2-1_50HMG_2024-04-27_final
2024-04-27 11:47:29	ga_s2am_ard_3-2-1_50HLG_2024-04-27_final
2024-05-04 09:56:56	ga_s2am_ard_3-2-1_54HYF_2024-05-04_final
2024-05-04 11:37:15	ga_s2am_ard_3-2-1_51HUB_2024-05-04_final
2024-05-04 11:37:18	ga_s2am_ard_3-2-1_51HTB_2024-05-04_final
2024-05-04 11:37:20	ga_s2am_ard_3-2-1_50HQG_2024-05-04_final
2024-05-04 11:37:24	ga_s2am_ard_3-2-1_50HPG_2024-05-04_final
2024-05-04 11:37:29	ga_s2am_ard_3-2-1_50HNG_2024-05-04_final
2024-05-04 11:37:31	ga_s2am_ard_3-2-1_50HQF_2024-05-04_nrt
2024-05-05 09:26:22	ga_s2am_ard_3-2-1_56HNG_2024-05-04_nrt
2024-05-05 09:26:26	ga_s2am_ard_3-2-1_56HMG_2024-05-04_nrt
2024-05-05 09:26:29	ga_s2am_ard_3-2-1_56HLG_2024-05-04_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