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
2018-01-01 10:37:20	ga_s2am_ard_3-2-1_53KNV_2018-01-01_final.stac-item
2018-01-01 10:37:20	ga_s2am_ard_3-2-1_53KPV_2018-01-01_final.stac-item
2018-01-01 10:37:20	ga_s2am_ard_3-2-1_53KQV_2018-01-01_final.stac-item
2018-01-01 10:37:20	ga_s2am_ard_3-2-1_53KRV_2018-01-01_final.stac-item
2018-01-03 09:41:02	ga_s2am_ard_3-2-1_56KLE_2018-01-03_final.stac-item
2018-01-04 10:52:09	ga_s2am_ard_3-2-1_53KKV_2018-01-04_final.stac-item
2018-01-04 10:52:09	ga_s2am_ard_3-2-1_53KLV_2018-01-04_final.stac-item
2018-01-04 10:52:09	ga_s2am_ard_3-2-1_53KMV_2018-01-04_final.stac-item
2018-01-04 10:52:09	ga_s2am_ard_3-2-1_53KNV_2018-01-04_final.stac-item
2018-01-04 10:52:09	ga_s2am_ard_3-2-1_52KHD_2018-01-04_final.stac-item
2018-01-04 10:52:09	ga_s2am_ard_3-2-1_52KHE_2018-01-04_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_51KYU_2018-01-13_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_51KYV_2018-01-13_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_51KZU_2018-01-13_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_51KZV_2018-01-13_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_52KBE_2018-01-13_final.stac-item
2018-01-13 11:19:15	ga_s2am_ard_3-2-1_52KCE_2018-01-13_final.stac-item
2018-01-17 11:02:04	ga_s2am_ard_3-2-1_53KKV_2018-01-17_final.stac-item
2018-01-17 11:02:04	ga_s2am_ard_3-2-1_52KGD_2018-01-17_final.stac-item
2018-01-17 11:02:04	ga_s2am_ard_3-2-1_52KGE_2018-01-17_final.stac-item
2018-01-17 11:02:04	ga_s2am_ard_3-2-1_52KHD_2018-01-17_final.stac-item
2018-01-17 11:02:04	ga_s2am_ard_3-2-1_52KHE_2018-01-17_final.stac-item
2018-01-17 11:02:22	ga_s2am_ard_3-2-1_52KFE_2018-01-17_final.stac-item
2018-01-17 11:02:22	ga_s2am_ard_3-2-1_52KGD_2018-01-17_final.stac-item
2018-01-17 11:02:22	ga_s2am_ard_3-2-1_52KGE_2018-01-17_final.stac-item
2018-01-17 11:02:22	ga_s2am_ard_3-2-1_52KHD_2018-01-17_final.stac-item
2018-01-17 11:02:22	ga_s2am_ard_3-2-1_52KHE_2018-01-17_final.stac-item
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_54KTE_2018-01-18_final.stac-item
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_54KUE_2018-01-18_final.stac-item
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_54KVE_2018-01-18_final.stac-item
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_53KQU_2018-01-18_final.stac-item
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_53KQV_2018-01-18_final.stac-item
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_53KRU_2018-01-18_final.stac-item
2018-01-18 10:27:01	ga_s2am_ard_3-2-1_53KRV_2018-01-18_final.stac-item
2018-01-23 09:41:03	ga_s2am_ard_3-2-1_56KLE_2018-01-23_final.stac-item
2018-01-24 10:52:11	ga_s2am_ard_3-2-1_53KNV_2018-01-24_final.stac-item
2018-01-24 10:52:15	ga_s2am_ard_3-2-1_53KKV_2018-01-24_final.stac-item
2018-01-24 10:52:15	ga_s2am_ard_3-2-1_53KLV_2018-01-24_final.stac-item
2018-01-24 10:52:15	ga_s2am_ard_3-2-1_53KMV_2018-01-24_final.stac-item
2018-01-24 10:52:15	ga_s2am_ard_3-2-1_53KNV_2018-01-24_final.stac-item
2018-01-24 10:52:15	ga_s2am_ard_3-2-1_52KHD_2018-01-24_final.stac-item
2018-01-24 10:52:15	ga_s2am_ard_3-2-1_52KHE_2018-01-24_final.stac-item
2019-03-01 10:21:59	ga_s2am_ard_3-2-1_54KYE_2019-03-01_final.stac-item
2019-03-01 10:22:04	ga_s2am_ard_3-2-1_54KXE_2019-03-01_final.stac-item
2019-03-01 10:22:08	ga_s2am_ard_3-2-1_54KWE_2019-03-01_final.stac-item
2019-03-01 10:22:11	ga_s2am_ard_3-2-1_54KVE_2019-03-01_final.stac-item
2019-03-04 10:32:06	ga_s2am_ard_3-2-1_54KVE_2019-03-04_final.stac-item
2019-03-04 10:32:10	ga_s2am_ard_3-2-1_54KUE_2019-03-04_final.stac-item
2019-03-04 10:32:13	ga_s2am_ard_3-2-1_54KTE_2019-03-04_final.stac-item
2019-03-04 10:32:13	ga_s2am_ard_3-2-1_53KRV_2019-03-04_final.stac-item
2019-03-04 10:32:17	ga_s2am_ard_3-2-1_53KQV_2019-03-04_final.stac-item
2019-03-08 10:11:57	ga_s2am_ard_3-2-1_55KCV_2019-03-08_final.stac-item
2019-03-08 10:12:01	ga_s2am_ard_3-2-1_55KBV_2019-03-08_final.stac-item
2019-03-08 10:12:01	ga_s2am_ard_3-2-1_54KZE_2019-03-08_final.stac-item
2019-03-08 10:12:05	ga_s2am_ard_3-2-1_54KYE_2019-03-08_final.stac-item
2019-03-08 10:12:08	ga_s2am_ard_3-2-1_54KXE_2019-03-08_final.stac-item
2019-03-08 10:12:16	ga_s2am_ard_3-2-1_54KZD_2019-03-08_final.stac-item
2019-03-08 10:12:19	ga_s2am_ard_3-2-1_54KYD_2019-03-08_final.stac-item
2019-03-13 11:02:21	ga_s2am_ard_3-2-1_53KKV_2019-03-13_final.stac-item
2019-03-13 11:02:22	ga_s2am_ard_3-2-1_52KHE_2019-03-13_final.stac-item
2019-03-13 11:02:25	ga_s2am_ard_3-2-1_52KGE_2019-03-13_final.stac-item
2019-03-13 11:02:29	ga_s2am_ard_3-2-1_52KFE_2019-03-13_final.stac-item
2019-03-13 11:02:36	ga_s2am_ard_3-2-1_52KHD_2019-03-13_final.stac-item
2019-03-13 11:02:40	ga_s2am_ard_3-2-1_52KGD_2019-03-13_final.stac-item
2019-03-14 10:32:07	ga_s2am_ard_3-2-1_54KVE_2019-03-14_final.stac-item
2019-03-14 10:32:11	ga_s2am_ard_3-2-1_54KUE_2019-03-14_final.stac-item
2019-03-14 10:32:14	ga_s2am_ard_3-2-1_54KTE_2019-03-14_final.stac-item
2019-03-14 10:32:15	ga_s2am_ard_3-2-1_53KRV_2019-03-14_final.stac-item
2019-03-14 10:32:19	ga_s2am_ard_3-2-1_53KQV_2019-03-14_final.stac-item
2019-03-14 10:32:29	ga_s2am_ard_3-2-1_53KRU_2019-03-14_final.stac-item
2019-03-14 10:32:32	ga_s2am_ard_3-2-1_53KQU_2019-03-14_final.stac-item
2023-06-22 10:01:59	ga_s2am_ard_3-2-1_55KFV_2023-06-22_nrt
2023-06-22 10:02:05	ga_s2am_ard_3-2-1_55KEV_2023-06-22_final
2023-06-22 10:02:08	ga_s2am_ard_3-2-1_55KDV_2023-06-22_final
2023-06-22 10:02:11	ga_s2am_ard_3-2-1_55KCV_2023-06-22_final
2023-06-22 10:02:18	ga_s2am_ard_3-2-1_55KBV_2023-06-22_final
2023-06-29 09:51:58	ga_s2am_ard_3-2-1_56KKE_2023-06-29_nrt
2023-06-29 09:52:03	ga_s2am_ard_3-2-1_55KGV_2023-06-29_nrt
2023-06-30 11:02:29	ga_s2am_ard_3-2-1_53KKV_2023-06-30_final
2023-06-30 11:02:30	ga_s2am_ard_3-2-1_52KHE_2023-06-30_final
2023-06-30 11:02:34	ga_s2am_ard_3-2-1_52KGE_2023-06-30_final
2023-06-30 11:02:37	ga_s2am_ard_3-2-1_52KFE_2023-06-30_final
2023-06-30 11:02:44	ga_s2am_ard_3-2-1_52KHD_2023-06-30_final
2023-06-30 11:02:48	ga_s2am_ard_3-2-1_52KGD_2023-06-30_final
2023-07-03 11:12:33	ga_s2am_ard_3-2-1_52KFE_2023-07-03_final
2023-07-03 11:12:37	ga_s2am_ard_3-2-1_52KEE_2023-07-03_final
2023-07-03 11:12:40	ga_s2am_ard_3-2-1_52KDE_2023-07-03_final
2023-07-03 11:12:43	ga_s2am_ard_3-2-1_52KCE_2023-07-03_final
2023-07-05 11:52:48	ga_s2am_ard_3-2-1_51KTV_2023-07-05_nrt
2023-07-05 11:52:50	ga_s2am_ard_3-2-1_50KRE_2023-07-05_nrt
2023-07-05 11:52:54	ga_s2am_ard_3-2-1_50KQE_2023-07-05_final
2023-07-05 11:52:57	ga_s2am_ard_3-2-1_50KPE_2023-07-05_nrt
2023-07-05 11:53:00	ga_s2am_ard_3-2-1_50KNE_2023-07-05_nrt
2023-07-05 11:53:04	ga_s2am_ard_3-2-1_50KRD_2023-07-05_final
2023-07-05 11:53:08	ga_s2am_ard_3-2-1_50KQD_2023-07-05_final
2023-07-07 10:52:25	ga_s2am_ard_3-2-1_53KNV_2023-07-07_final
2023-07-07 10:52:29	ga_s2am_ard_3-2-1_53KMV_2023-07-07_final
2023-07-07 10:52:32	ga_s2am_ard_3-2-1_53KLV_2023-07-07_final
2023-07-07 10:52:35	ga_s2am_ard_3-2-1_53KKV_2023-07-07_final
2023-07-07 10:52:36	ga_s2am_ard_3-2-1_52KHE_2023-07-07_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

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