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
2022-06-23 12:05:09	ga_s2am_ard_3-2-1_49JHM_2022-06-23_final.stac-item
2022-06-23 12:05:09	ga_s2am_ard_3-2-1_50JKS_2022-06-23_final.stac-item
2022-06-23 12:05:10	ga_s2am_ard_3-2-1_50JMR_2022-06-23_final.stac-item
2022-06-23 12:05:13	ga_s2am_ard_3-2-1_49JGM_2022-06-23_final.stac-item
2022-06-23 12:05:20	ga_s2am_ard_3-2-1_50JLR_2022-06-23_final.stac-item
2022-06-23 12:05:20	ga_s2am_ard_3-2-1_49JFM_2022-06-23_final.stac-item
2022-06-23 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-06-23_final.stac-item
2022-06-23 12:05:27	ga_s2am_ard_3-2-1_49JGL_2022-06-23_final.stac-item
2022-06-23 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-06-23_final.stac-item
2022-06-23 12:05:38	ga_s2am_ard_3-2-1_50JKQ_2022-06-23_final.stac-item
2022-06-23 12:05:41	ga_s2am_ard_3-2-1_49JGK_2022-06-23_final.stac-item
2022-06-23 12:05:50	ga_s2am_ard_3-2-1_50JLP_2022-06-23_final.stac-item
2022-06-23 12:05:53	ga_s2am_ard_3-2-1_50JKP_2022-06-23_final.stac-item
2022-06-23 12:05:56	ga_s2am_ard_3-2-1_49JGJ_2022-06-23_final.stac-item
2022-06-23 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-06-23_final.stac-item
2022-06-23 12:06:07	ga_s2am_ard_3-2-1_50JKN_2022-06-23_final.stac-item
2022-06-23 12:06:10	ga_s2am_ard_3-2-1_49JGH_2022-06-23_final
2022-06-23 12:06:16	ga_s2am_ard_3-2-1_50JLM_2022-06-23_final.stac-item
2022-06-23 12:06:22	ga_s2am_ard_3-2-1_50JKM_2022-06-23_final.stac-item
2022-06-24 09:57:27	ga_s2am_ard_3-2-1_55HBV_2022-06-24_final.stac-item
2022-06-24 09:57:27	ga_s2am_ard_3-2-1_54HYE_2022-06-24_final.stac-item
2022-06-24 09:57:29	ga_s2am_ard_3-2-1_54HXE_2022-06-24_final.stac-item
2022-06-24 09:57:32	ga_s2am_ard_3-2-1_55HCU_2022-06-24_final.stac-item
2022-06-24 09:57:34	ga_s2am_ard_3-2-1_55HBU_2022-06-24_final.stac-item
2022-06-24 09:57:35	ga_s2am_ard_3-2-1_54HYD_2022-06-24_final.stac-item
2022-06-24 09:57:39	ga_s2am_ard_3-2-1_54HXD_2022-06-24_final.stac-item
2022-06-24 09:57:45	ga_s2am_ard_3-2-1_55HCT_2022-06-24_final.stac-item
2022-06-24 09:57:48	ga_s2am_ard_3-2-1_55HBT_2022-06-24_final.stac-item
2022-06-24 09:57:49	ga_s2am_ard_3-2-1_54HYC_2022-06-24_final.stac-item
2022-06-24 09:57:53	ga_s2am_ard_3-2-1_54HXC_2022-06-24_final.stac-item
2022-06-24 09:57:58	ga_s2am_ard_3-2-1_54HWC_2022-06-24_final.stac-item
2022-06-24 09:57:59	ga_s2am_ard_3-2-1_55HCS_2022-06-24_final.stac-item
2022-06-24 09:58:03	ga_s2am_ard_3-2-1_55HBS_2022-06-24_final.stac-item
2022-06-24 09:58:03	ga_s2am_ard_3-2-1_54HYB_2022-06-24_final.stac-item
2022-06-24 09:58:13	ga_s2am_ard_3-2-1_55GCR_2022-06-24_final.stac-item
2022-06-24 09:58:17	ga_s2am_ard_3-2-1_55GBR_2022-06-24_final.stac-item
2022-06-24 09:58:18	ga_s2am_ard_3-2-1_54GYA_2022-06-24_final.stac-item
2022-06-24 09:58:26	ga_s2am_ard_3-2-1_55GCQ_2022-06-24_final.stac-item
2022-06-24 09:58:32	ga_s2am_ard_3-2-1_54GYV_2022-06-24_final
2022-06-24 11:31:30	ga_s2am_ard_3-2-1_52LBK_2022-06-24_final.stac-item
2022-06-24 11:31:33	ga_s2am_ard_3-2-1_51LZE_2022-06-24_final.stac-item
2022-06-24 11:32:44	ga_s2am_ard_3-2-1_51KVA_2022-06-24_final.stac-item
2022-06-24 11:33:34	ga_s2am_ard_3-2-1_51KUT_2022-06-24_final.stac-item
2022-06-24 11:33:46	ga_s2am_ard_3-2-1_51KUS_2022-06-24_final.stac-item
2022-06-24 11:34:00	ga_s2am_ard_3-2-1_51KUR_2022-06-24_final.stac-item
2022-06-24 11:34:15	ga_s2am_ard_3-2-1_51KUQ_2022-06-24_final.stac-item
2022-06-24 11:34:27	ga_s2am_ard_3-2-1_51JXN_2022-06-24_final.stac-item
2022-06-24 11:34:30	ga_s2am_ard_3-2-1_51KUP_2022-06-24_final.stac-item
2022-06-24 11:34:37	ga_s2am_ard_3-2-1_51KTP_2022-06-24_final.stac-item
2022-06-24 11:34:37	ga_s2am_ard_3-2-1_51JWN_2022-06-24_final.stac-item
2022-06-24 11:34:41	ga_s2am_ard_3-2-1_51JVN_2022-06-24_final.stac-item
2022-06-24 11:34:44	ga_s2am_ard_3-2-1_51JUN_2022-06-24_final.stac-item
2022-06-24 11:34:48	ga_s2am_ard_3-2-1_51JTN_2022-06-24_final.stac-item
2022-06-24 11:34:49	ga_s2am_ard_3-2-1_50JRT_2022-06-24_final.stac-item
2022-06-24 11:34:52	ga_s2am_ard_3-2-1_51JWM_2022-06-24_final.stac-item
2022-06-24 11:34:55	ga_s2am_ard_3-2-1_51JVM_2022-06-24_final.stac-item
2022-06-24 11:34:59	ga_s2am_ard_3-2-1_51JUM_2022-06-24_final.stac-item
2022-06-24 11:35:01	ga_s2am_ard_3-2-1_50JRS_2022-06-24_final.stac-item
2022-06-24 11:35:02	ga_s2am_ard_3-2-1_51JTM_2022-06-24_final.stac-item
2022-06-24 11:35:07	ga_s2am_ard_3-2-1_51JWL_2022-06-24_final.stac-item
2022-06-24 11:35:10	ga_s2am_ard_3-2-1_51JVL_2022-06-24_final.stac-item
2022-06-24 11:35:13	ga_s2am_ard_3-2-1_51JUL_2022-06-24_final.stac-item
2022-06-24 11:35:16	ga_s2am_ard_3-2-1_51JTL_2022-06-24_final.stac-item
2022-06-24 11:35:20	ga_s2am_ard_3-2-1_51JWK_2022-06-24_final.stac-item
2022-06-24 11:35:24	ga_s2am_ard_3-2-1_51JVK_2022-06-24_final.stac-item
2022-06-24 11:35:28	ga_s2am_ard_3-2-1_51JUK_2022-06-24_final.stac-item
2022-06-24 11:35:31	ga_s2am_ard_3-2-1_51JTK_2022-06-24_final.stac-item
2022-06-24 11:35:31	ga_s2am_ard_3-2-1_51JWJ_2022-06-24_final.stac-item
2022-06-24 11:35:39	ga_s2am_ard_3-2-1_51JVJ_2022-06-24_final.stac-item
2022-06-24 11:35:43	ga_s2am_ard_3-2-1_51JUJ_2022-06-24_final.stac-item
2022-06-24 11:35:46	ga_s2am_ard_3-2-1_51JTJ_2022-06-24_final.stac-item
2022-06-24 11:35:49	ga_s2am_ard_3-2-1_50JQP_2022-06-24_final.stac-item
2022-06-24 11:35:53	ga_s2am_ard_3-2-1_51JVH_2022-06-24_final.stac-item
2022-06-24 11:35:57	ga_s2am_ard_3-2-1_51JUH_2022-06-24_final.stac-item
2022-06-24 11:36:00	ga_s2am_ard_3-2-1_51JTH_2022-06-24_final.stac-item
2022-06-24 11:36:03	ga_s2am_ard_3-2-1_50JQN_2022-06-24_final.stac-item
2022-06-24 11:36:08	ga_s2am_ard_3-2-1_51JVG_2022-06-24_final.stac-item
2022-06-24 11:36:12	ga_s2am_ard_3-2-1_51JUG_2022-06-24_final.stac-item
2022-06-24 11:36:15	ga_s2am_ard_3-2-1_51JTG_2022-06-24_final.stac-item
2022-06-24 11:36:17	ga_s2am_ard_3-2-1_50JQM_2022-06-24_final.stac-item
2022-06-24 11:36:23	ga_s2am_ard_3-2-1_51JVF_2022-06-24_final.stac-item
2022-06-24 11:36:26	ga_s2am_ard_3-2-1_51JUF_2022-06-24_final.stac-item
2022-06-24 11:36:29	ga_s2am_ard_3-2-1_51JTF_2022-06-24_final.stac-item
2022-06-24 11:36:32	ga_s2am_ard_3-2-1_50JQL_2022-06-24_final.stac-item
2022-06-24 11:36:36	ga_s2am_ard_3-2-1_51HVE_2022-06-24_final.stac-item
2022-06-24 11:36:39	ga_s2am_ard_3-2-1_50JPL_2022-06-24_final.stac-item
2022-06-24 11:36:41	ga_s2am_ard_3-2-1_51HUE_2022-06-24_final.stac-item
2022-06-24 11:36:44	ga_s2am_ard_3-2-1_51HTE_2022-06-24_final.stac-item
2022-06-24 11:36:46	ga_s2am_ard_3-2-1_51HVD_2022-06-24_final.stac-item
2022-06-24 11:36:46	ga_s2am_ard_3-2-1_50HQK_2022-06-24_final.stac-item
2022-06-24 11:36:50	ga_s2am_ard_3-2-1_50HPK_2022-06-24_final.stac-item
2022-06-24 11:36:55	ga_s2am_ard_3-2-1_51HUD_2022-06-24_final.stac-item
2022-06-24 11:36:59	ga_s2am_ard_3-2-1_51HTD_2022-06-24_final.stac-item
2022-06-24 11:37:01	ga_s2am_ard_3-2-1_50HQJ_2022-06-24_final.stac-item
2022-06-24 11:37:04	ga_s2am_ard_3-2-1_50HPJ_2022-06-24_final.stac-item
2022-06-24 11:37:10	ga_s2am_ard_3-2-1_51HUC_2022-06-24_final.stac-item
2022-06-24 11:37:13	ga_s2am_ard_3-2-1_51HTC_2022-06-24_final.stac-item
2022-06-24 11:37:15	ga_s2am_ard_3-2-1_50HQH_2022-06-24_final.stac-item
2022-06-24 11:37:19	ga_s2am_ard_3-2-1_50HPH_2022-06-24_final.stac-item
2022-06-24 11:37:25	ga_s2am_ard_3-2-1_51HUB_2022-06-24_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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