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
2018-12-18 10:10:17	ga_s2am_ard_3-2-1_54LZM_2018-12-18_final.stac-item
2018-12-18 10:10:32	ga_s2am_ard_3-2-1_54LZL_2018-12-18_final.stac-item
2018-12-18 10:10:42	ga_s2am_ard_3-2-1_55LCE_2018-12-18_final.stac-item
2018-12-18 10:10:45	ga_s2am_ard_3-2-1_55LBE_2018-12-18_final.stac-item
2018-12-18 10:10:46	ga_s2am_ard_3-2-1_54LZK_2018-12-18_final.stac-item
2018-12-18 10:10:52	ga_s2am_ard_3-2-1_54LYK_2018-12-18_final.stac-item
2018-12-18 10:10:56	ga_s2am_ard_3-2-1_55LCD_2018-12-18_final.stac-item
2018-12-18 10:10:59	ga_s2am_ard_3-2-1_55LBD_2018-12-18_final.stac-item
2018-12-18 10:11:00	ga_s2am_ard_3-2-1_54LZJ_2018-12-18_final.stac-item
2018-12-18 10:11:04	ga_s2am_ard_3-2-1_54LYJ_2018-12-18_final.stac-item
2018-12-18 10:11:10	ga_s2am_ard_3-2-1_55LCC_2018-12-18_final.stac-item
2018-12-18 10:11:14	ga_s2am_ard_3-2-1_55LBC_2018-12-18_final.stac-item
2018-12-18 10:11:15	ga_s2am_ard_3-2-1_54LZH_2018-12-18_final.stac-item
2018-12-18 10:11:18	ga_s2am_ard_3-2-1_54LYH_2018-12-18_final.stac-item
2018-12-18 10:11:25	ga_s2am_ard_3-2-1_55KCB_2018-12-18_final.stac-item
2018-12-18 10:11:29	ga_s2am_ard_3-2-1_55KBB_2018-12-18_final.stac-item
2018-12-18 10:11:29	ga_s2am_ard_3-2-1_54KZG_2018-12-18_final.stac-item
2018-12-18 10:11:33	ga_s2am_ard_3-2-1_54KYG_2018-12-18_final.stac-item
2018-12-18 10:11:40	ga_s2am_ard_3-2-1_55KCA_2018-12-18_final.stac-item
2018-12-18 10:11:43	ga_s2am_ard_3-2-1_55KBA_2018-12-18_final.stac-item
2018-12-18 10:11:44	ga_s2am_ard_3-2-1_54KZF_2018-12-18_final.stac-item
2018-12-18 10:11:47	ga_s2am_ard_3-2-1_54KYF_2018-12-18_final.stac-item
2018-12-18 10:11:53	ga_s2am_ard_3-2-1_54KXF_2018-12-18_final.stac-item
2018-12-18 10:11:54	ga_s2am_ard_3-2-1_55KCV_2018-12-18_final.stac-item
2018-12-18 10:11:58	ga_s2am_ard_3-2-1_55KBV_2018-12-18_final.stac-item
2018-12-18 10:11:58	ga_s2am_ard_3-2-1_54KZE_2018-12-18_final.stac-item
2018-12-18 10:12:02	ga_s2am_ard_3-2-1_54KYE_2018-12-18_final.stac-item
2018-12-18 10:12:05	ga_s2am_ard_3-2-1_54KXE_2018-12-18_final.stac-item
2018-12-18 10:12:08	ga_s2am_ard_3-2-1_55KCU_2018-12-18_final.stac-item
2018-12-18 10:12:12	ga_s2am_ard_3-2-1_55KBU_2018-12-18_final.stac-item
2018-12-18 10:12:13	ga_s2am_ard_3-2-1_54KZD_2018-12-18_final.stac-item
2018-12-18 10:12:16	ga_s2am_ard_3-2-1_54KYD_2018-12-18_final.stac-item
2018-12-18 10:12:19	ga_s2am_ard_3-2-1_55KCT_2018-12-18_final.stac-item
2018-12-18 10:12:20	ga_s2am_ard_3-2-1_54KXD_2018-12-18_final.stac-item
2018-12-18 10:12:26	ga_s2am_ard_3-2-1_55KBT_2018-12-18_final.stac-item
2018-12-18 10:12:27	ga_s2am_ard_3-2-1_54KZC_2018-12-18_final.stac-item
2018-12-18 10:12:31	ga_s2am_ard_3-2-1_54KYC_2018-12-18_final.stac-item
2018-12-18 10:12:34	ga_s2am_ard_3-2-1_54KXC_2018-12-18_final.stac-item
2018-12-18 10:12:41	ga_s2am_ard_3-2-1_55KBS_2018-12-18_final.stac-item
2018-12-18 10:12:41	ga_s2am_ard_3-2-1_54KZB_2018-12-18_final.stac-item
2018-12-18 10:12:45	ga_s2am_ard_3-2-1_54KYB_2018-12-18_final.stac-item
2018-12-18 10:12:49	ga_s2am_ard_3-2-1_54KXB_2018-12-18_final.stac-item
2018-12-18 10:12:55	ga_s2am_ard_3-2-1_54KWB_2018-12-18_final.stac-item
2018-12-18 10:12:56	ga_s2am_ard_3-2-1_55KBR_2018-12-18_final.stac-item
2018-12-18 10:12:56	ga_s2am_ard_3-2-1_54KZA_2018-12-18_final.stac-item
2018-12-18 10:13:00	ga_s2am_ard_3-2-1_54KYA_2018-12-18_final.stac-item
2018-12-18 10:13:03	ga_s2am_ard_3-2-1_54KXA_2018-12-18_final.stac-item
2018-12-18 10:13:07	ga_s2am_ard_3-2-1_54KWA_2018-12-18_final.stac-item
2018-12-18 10:13:10	ga_s2am_ard_3-2-1_55KBQ_2018-12-18_final.stac-item
2018-12-18 10:13:11	ga_s2am_ard_3-2-1_54KZV_2018-12-18_final.stac-item
2018-12-18 10:13:14	ga_s2am_ard_3-2-1_54KYV_2018-12-18_final.stac-item
2018-12-18 10:13:18	ga_s2am_ard_3-2-1_54KXV_2018-12-18_final.stac-item
2018-12-18 10:13:21	ga_s2am_ard_3-2-1_54KWV_2018-12-18_final.stac-item
2018-12-18 10:13:24	ga_s2am_ard_3-2-1_55KBP_2018-12-18_final.stac-item
2018-12-18 10:13:25	ga_s2am_ard_3-2-1_54KZU_2018-12-18_final.stac-item
2018-12-18 10:13:29	ga_s2am_ard_3-2-1_54KYU_2018-12-18_final.stac-item
2018-12-18 10:13:32	ga_s2am_ard_3-2-1_54KXU_2018-12-18_final.stac-item
2018-12-18 10:13:35	ga_s2am_ard_3-2-1_55JBN_2018-12-18_final.stac-item
2018-12-18 10:13:36	ga_s2am_ard_3-2-1_54KWU_2018-12-18_final.stac-item
2018-12-18 10:13:37	ga_s2am_ard_3-2-1_54JZT_2018-12-18_final.stac-item
2018-12-18 10:13:43	ga_s2am_ard_3-2-1_54JYT_2018-12-18_final.stac-item
2018-12-18 10:13:47	ga_s2am_ard_3-2-1_54JXT_2018-12-18_final.stac-item
2018-12-18 10:13:50	ga_s2am_ard_3-2-1_54JWT_2018-12-18_final.stac-item
2018-12-18 10:13:57	ga_s2am_ard_3-2-1_54JVT_2018-12-18_final.stac-item
2018-12-18 10:13:57	ga_s2am_ard_3-2-1_54JYS_2018-12-18_final.stac-item
2018-12-18 10:14:01	ga_s2am_ard_3-2-1_54JXS_2018-12-18_final.stac-item
2018-12-18 10:14:05	ga_s2am_ard_3-2-1_54JWS_2018-12-18_final.stac-item
2018-12-18 10:14:08	ga_s2am_ard_3-2-1_54JVS_2018-12-18_final.stac-item
2018-12-18 10:14:12	ga_s2am_ard_3-2-1_54JYR_2018-12-18_final.stac-item
2018-12-18 10:14:16	ga_s2am_ard_3-2-1_54JXR_2018-12-18_final.stac-item
2018-12-18 10:14:19	ga_s2am_ard_3-2-1_54JWR_2018-12-18_final.stac-item
2018-12-18 10:14:22	ga_s2am_ard_3-2-1_54JVR_2018-12-18_final.stac-item
2018-12-18 10:14:26	ga_s2am_ard_3-2-1_54JYQ_2018-12-18_final.stac-item
2018-12-18 10:14:30	ga_s2am_ard_3-2-1_54JXQ_2018-12-18_final.stac-item
2018-12-18 10:14:34	ga_s2am_ard_3-2-1_54JWQ_2018-12-18_final.stac-item
2018-12-18 10:14:37	ga_s2am_ard_3-2-1_54JVQ_2018-12-18_final.stac-item
2018-12-18 10:14:39	ga_s2am_ard_3-2-1_54JYP_2018-12-18_final.stac-item
2018-12-18 10:15:32	ga_s2am_ard_3-2-1_54JWL_2018-12-18_final
2018-12-18 10:15:46	ga_s2am_ard_3-2-1_54HWK_2018-12-18_final.stac-item
2018-12-18 10:15:50	ga_s2am_ard_3-2-1_54HVK_2018-12-18_final.stac-item
2018-12-18 10:15:51	ga_s2am_ard_3-2-1_54HXJ_2018-12-18_final.stac-item
2018-12-18 10:15:53	ga_s2am_ard_3-2-1_54HUK_2018-12-18_final.stac-item
2018-12-18 10:16:01	ga_s2am_ard_3-2-1_54HWJ_2018-12-18_final.stac-item
2018-12-18 10:16:05	ga_s2am_ard_3-2-1_54HVJ_2018-12-18_final.stac-item
2018-12-18 10:16:08	ga_s2am_ard_3-2-1_54HUJ_2018-12-18_final.stac-item
2018-12-18 10:16:12	ga_s2am_ard_3-2-1_54HTJ_2018-12-18_final.stac-item
2018-12-18 10:16:15	ga_s2am_ard_3-2-1_54HWH_2018-12-18_final.stac-item
2018-12-18 10:16:19	ga_s2am_ard_3-2-1_54HVH_2018-12-18_final.stac-item
2018-12-18 10:16:22	ga_s2am_ard_3-2-1_54HUH_2018-12-18_final.stac-item
2018-12-18 10:16:25	ga_s2am_ard_3-2-1_54HTH_2018-12-18_final.stac-item
2018-12-18 10:16:30	ga_s2am_ard_3-2-1_54HWG_2018-12-18_final.stac-item
2018-12-18 10:16:33	ga_s2am_ard_3-2-1_54HVG_2018-12-18_final.stac-item
2018-12-18 10:16:37	ga_s2am_ard_3-2-1_54HUG_2018-12-18_final.stac-item
2018-12-18 10:16:40	ga_s2am_ard_3-2-1_54HTG_2018-12-18_final.stac-item
2018-12-18 10:16:43	ga_s2am_ard_3-2-1_54HWF_2018-12-18_final.stac-item
2018-12-18 10:16:48	ga_s2am_ard_3-2-1_54HVF_2018-12-18_final.stac-item
2018-12-18 10:16:51	ga_s2am_ard_3-2-1_54HUF_2018-12-18_final.stac-item
2018-12-18 10:16:55	ga_s2am_ard_3-2-1_54HTF_2018-12-18_final.stac-item
2018-12-18 10:16:55	ga_s2am_ard_3-2-1_54HWE_2018-12-18_final.stac-item
2018-12-18 10:17:02	ga_s2am_ard_3-2-1_54HVE_2018-12-18_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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