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
2018-11-17 10:41:28	ga_s2am_ard_3-2-1_53LQC_2018-11-17_final
2018-11-17 10:41:32	ga_s2am_ard_3-2-1_53LPC_2018-11-17_final
2018-11-17 10:41:35	ga_s2am_ard_3-2-1_53LNC_2018-11-17_final.stac-item
2018-11-17 10:41:37	ga_s2am_ard_3-2-1_54KTG_2018-11-17_final.stac-item
2018-11-17 10:41:39	ga_s2am_ard_3-2-1_53KRB_2018-11-17_final
2018-11-17 10:41:43	ga_s2am_ard_3-2-1_53KQB_2018-11-17_final
2018-11-17 10:41:46	ga_s2am_ard_3-2-1_53KPB_2018-11-17_final.stac-item
2018-11-17 10:41:49	ga_s2am_ard_3-2-1_53KNB_2018-11-17_final.stac-item
2018-11-18 10:11:13	ga_s2am_ard_3-2-1_55LCC_2018-11-18_final.stac-item
2018-11-18 10:11:16	ga_s2am_ard_3-2-1_55LBC_2018-11-18_final.stac-item
2018-11-18 10:11:18	ga_s2am_ard_3-2-1_54LZH_2018-11-18_final.stac-item
2018-11-18 10:11:21	ga_s2am_ard_3-2-1_54LYH_2018-11-18_final.stac-item
2018-11-18 10:11:27	ga_s2am_ard_3-2-1_55KCB_2018-11-18_final.stac-item
2018-11-18 10:11:31	ga_s2am_ard_3-2-1_55KBB_2018-11-18_final.stac-item
2018-11-18 10:11:32	ga_s2am_ard_3-2-1_54KZG_2018-11-18_final.stac-item
2018-11-18 10:11:35	ga_s2am_ard_3-2-1_54KYG_2018-11-18_final.stac-item
2019-03-19 11:21:44	ga_s2am_ard_3-2-1_52LDH_2019-03-19_final.stac-item
2019-03-19 11:21:47	ga_s2am_ard_3-2-1_52LCH_2019-03-19_final.stac-item
2019-03-19 11:21:51	ga_s2am_ard_3-2-1_52LBH_2019-03-19_final.stac-item
2019-03-19 11:21:52	ga_s2am_ard_3-2-1_51LZC_2019-03-19_final.stac-item
2019-03-19 11:21:56	ga_s2am_ard_3-2-1_51LYC_2019-03-19_final.stac-item
2019-03-19 11:21:58	ga_s2am_ard_3-2-1_52KDG_2019-03-19_final.stac-item
2019-03-19 11:22:02	ga_s2am_ard_3-2-1_52KCG_2019-03-19_final.stac-item
2019-03-19 11:22:05	ga_s2am_ard_3-2-1_52KBG_2019-03-19_final.stac-item
2019-03-19 11:22:06	ga_s2am_ard_3-2-1_51KZB_2019-03-19_final.stac-item
2019-03-19 11:22:09	ga_s2am_ard_3-2-1_51KYB_2019-03-19_final.stac-item
2019-04-01 11:31:49	ga_s2am_ard_3-2-1_51LZC_2019-04-01_final.stac-item
2019-04-01 11:31:53	ga_s2am_ard_3-2-1_51LYC_2019-04-01_final.stac-item
2019-04-01 11:31:57	ga_s2am_ard_3-2-1_51LXC_2019-04-01_final.stac-item
2019-04-01 11:31:59	ga_s2am_ard_3-2-1_51KZB_2019-04-01_final.stac-item
2019-04-01 11:32:00	ga_s2am_ard_3-2-1_51LWC_2019-04-01_final.stac-item
2019-04-01 11:32:05	ga_s2am_ard_3-2-1_51KYB_2019-04-01_final.stac-item
2019-04-01 11:32:07	ga_s2am_ard_3-2-1_51KXB_2019-04-01_final.stac-item
2019-04-01 11:32:08	ga_s2am_ard_3-2-1_51KWB_2019-04-01_final.stac-item
2019-04-01 11:32:09	ga_s2am_ard_3-2-1_51LWC_2019-04-01_final.stac-item
2019-05-09 10:51:35	ga_s2am_ard_3-2-1_53LPC_2019-05-09_final
2019-05-09 10:51:40	ga_s2am_ard_3-2-1_53LNC_2019-05-09_final.stac-item
2019-05-09 10:51:44	ga_s2am_ard_3-2-1_53LMC_2019-05-09_final.stac-item
2019-05-09 10:51:45	ga_s2am_ard_3-2-1_53KPB_2019-05-09_final.stac-item
2019-05-09 10:51:47	ga_s2am_ard_3-2-1_53LLC_2019-05-09_final.stac-item
2019-05-09 10:51:54	ga_s2am_ard_3-2-1_53KNB_2019-05-09_final.stac-item
2019-05-09 10:51:58	ga_s2am_ard_3-2-1_53KMB_2019-05-09_final.stac-item
2019-05-09 10:52:01	ga_s2am_ard_3-2-1_53KLB_2019-05-09_final.stac-item
2019-05-09 10:52:05	ga_s2am_ard_3-2-1_53KKB_2019-05-09_final.stac-item
2019-05-19 10:51:35	ga_s2am_ard_3-2-1_53LPC_2019-05-19_final
2019-05-19 10:51:40	ga_s2am_ard_3-2-1_53LNC_2019-05-19_final.stac-item
2019-05-19 10:51:43	ga_s2am_ard_3-2-1_53LMC_2019-05-19_final.stac-item
2019-05-19 10:51:45	ga_s2am_ard_3-2-1_53KPB_2019-05-19_final.stac-item
2019-05-19 10:51:47	ga_s2am_ard_3-2-1_53LLC_2019-05-19_final.stac-item
2019-05-19 10:51:54	ga_s2am_ard_3-2-1_53KNB_2019-05-19_final.stac-item
2019-05-19 10:51:58	ga_s2am_ard_3-2-1_53KMB_2019-05-19_final.stac-item
2019-05-19 10:52:01	ga_s2am_ard_3-2-1_53KLB_2019-05-19_final.stac-item
2019-05-19 10:52:05	ga_s2am_ard_3-2-1_53KKB_2019-05-19_final.stac-item
2019-05-29 10:51:34	ga_s2am_ard_3-2-1_53LPC_2019-05-29_final
2019-05-29 10:51:39	ga_s2am_ard_3-2-1_53LNC_2019-05-29_final.stac-item
2019-05-29 10:51:42	ga_s2am_ard_3-2-1_53LMC_2019-05-29_final.stac-item
2019-05-29 10:51:44	ga_s2am_ard_3-2-1_53KPB_2019-05-29_final.stac-item
2019-05-29 10:51:46	ga_s2am_ard_3-2-1_53LLC_2019-05-29_final.stac-item
2019-05-29 10:51:53	ga_s2am_ard_3-2-1_53KNB_2019-05-29_final.stac-item
2019-05-29 10:51:57	ga_s2am_ard_3-2-1_53KMB_2019-05-29_final.stac-item
2019-05-29 10:52:00	ga_s2am_ard_3-2-1_53KLB_2019-05-29_final.stac-item
2019-05-29 10:52:04	ga_s2am_ard_3-2-1_53KKB_2019-05-29_final.stac-item
2021-10-04 09:41:28	ga_s2am_ard_3-2-1_56KMG_2021-10-04_final
2021-10-04 09:41:32	ga_s2am_ard_3-2-1_56KLG_2021-10-04_final
2021-10-04 09:41:34	ga_s2am_ard_3-2-1_56KKG_2021-10-04_final
2021-10-04 09:41:37	ga_s2am_ard_3-2-1_55KHB_2021-10-04_final
2021-10-04 11:21:59	ga_s2am_ard_3-2-1_51LZC_2021-10-04_final.stac-item
2021-10-04 11:22:03	ga_s2am_ard_3-2-1_51LYC_2021-10-04_final.stac-item
2021-10-04 11:22:05	ga_s2am_ard_3-2-1_52KDG_2021-10-04_final.stac-item
2021-10-04 11:22:09	ga_s2am_ard_3-2-1_52KCG_2021-10-04_final.stac-item
2021-10-04 11:22:13	ga_s2am_ard_3-2-1_52KBG_2021-10-04_final.stac-item
2021-10-04 11:22:14	ga_s2am_ard_3-2-1_51KZB_2021-10-04_final.stac-item
2021-10-04 11:22:17	ga_s2am_ard_3-2-1_51KYB_2021-10-04_final.stac-item
2021-10-07 09:51:17	ga_s2am_ard_3-2-1_55LHC_2021-10-07_final
2021-10-07 09:51:21	ga_s2am_ard_3-2-1_55LGC_2021-10-07_final.stac-item
2021-10-07 09:51:24	ga_s2am_ard_3-2-1_55LFC_2021-10-07_final.stac-item
2021-10-07 09:51:30	ga_s2am_ard_3-2-1_56KKG_2021-10-07_final
2021-10-07 09:51:31	ga_s2am_ard_3-2-1_55KHB_2021-10-07_final
2021-10-07 09:51:35	ga_s2am_ard_3-2-1_55KGB_2021-10-07_final.stac-item
2021-10-07 09:51:38	ga_s2am_ard_3-2-1_55KFB_2021-10-07_final.stac-item
2021-10-14 09:41:29	ga_s2am_ard_3-2-1_56KMG_2021-10-14_final
2021-10-14 09:41:32	ga_s2am_ard_3-2-1_56KLG_2021-10-14_final
2021-10-14 09:41:35	ga_s2am_ard_3-2-1_56KKG_2021-10-14_final
2021-10-14 09:41:37	ga_s2am_ard_3-2-1_55KHB_2021-10-14_final
2021-10-14 11:21:52	ga_s2am_ard_3-2-1_52LDH_2021-10-14_final.stac-item
2021-10-14 11:21:55	ga_s2am_ard_3-2-1_52LCH_2021-10-14_final.stac-item
2021-10-14 11:21:59	ga_s2am_ard_3-2-1_52LBH_2021-10-14_final.stac-item
2021-10-14 11:22:00	ga_s2am_ard_3-2-1_51LZC_2021-10-14_final.stac-item
2021-10-14 11:22:04	ga_s2am_ard_3-2-1_51LYC_2021-10-14_final.stac-item
2021-10-14 11:22:06	ga_s2am_ard_3-2-1_52KDG_2021-10-14_final.stac-item
2021-10-14 11:22:10	ga_s2am_ard_3-2-1_52KCG_2021-10-14_final.stac-item
2021-10-14 11:22:13	ga_s2am_ard_3-2-1_52KBG_2021-10-14_final.stac-item
2021-10-14 11:22:14	ga_s2am_ard_3-2-1_51KZB_2021-10-14_final.stac-item
2021-10-14 11:22:17	ga_s2am_ard_3-2-1_51KYB_2021-10-14_final.stac-item
2021-10-17 09:51:17	ga_s2am_ard_3-2-1_55LHC_2021-10-17_final
2021-10-17 09:51:21	ga_s2am_ard_3-2-1_55LGC_2021-10-17_final.stac-item
2021-10-17 09:51:24	ga_s2am_ard_3-2-1_55LFC_2021-10-17_final.stac-item
2021-10-17 09:51:30	ga_s2am_ard_3-2-1_56KKG_2021-10-17_final
2021-10-17 09:51:32	ga_s2am_ard_3-2-1_55KHB_2021-10-17_final
2021-10-17 09:51:35	ga_s2am_ard_3-2-1_55KGB_2021-10-17_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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