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
2022-12-20 12:03:28	ga_s2am_ard_3-2-1_50KKC_2022-12-20_final
2022-12-20 12:03:28	ga_s2am_ard_3-2-1_49KHT_2022-12-20_nrt.stac-item
2022-12-20 12:03:32	ga_s2am_ard_3-2-1_50KNB_2022-12-20_final.stac-item
2022-12-20 12:03:36	ga_s2am_ard_3-2-1_50KMB_2022-12-20_final.stac-item
2022-12-20 12:03:39	ga_s2am_ard_3-2-1_50KLB_2022-12-20_final.stac-item
2022-12-20 12:03:43	ga_s2am_ard_3-2-1_50KNA_2022-12-20_final.stac-item
2022-12-20 12:03:43	ga_s2am_ard_3-2-1_50KKB_2022-12-20_final.stac-item
2022-12-20 12:03:50	ga_s2am_ard_3-2-1_50KMA_2022-12-20_final.stac-item
2022-12-20 12:03:54	ga_s2am_ard_3-2-1_50KLA_2022-12-20_final.stac-item
2022-12-20 12:03:57	ga_s2am_ard_3-2-1_50KKA_2022-12-20_final.stac-item
2022-12-20 12:03:58	ga_s2am_ard_3-2-1_49KHR_2022-12-20_final.stac-item
2022-12-20 12:04:05	ga_s2am_ard_3-2-1_50KMV_2022-12-20_final.stac-item
2022-12-20 12:04:09	ga_s2am_ard_3-2-1_50KLV_2022-12-20_final.stac-item
2022-12-20 12:04:12	ga_s2am_ard_3-2-1_50KKV_2022-12-20_final.stac-item
2022-12-20 12:04:12	ga_s2am_ard_3-2-1_49KHQ_2022-12-20_final.stac-item
2022-12-20 12:04:17	ga_s2am_ard_3-2-1_49KGQ_2022-12-20_final.stac-item
2022-12-20 12:04:20	ga_s2am_ard_3-2-1_50KMU_2022-12-20_final.stac-item
2022-12-20 12:04:23	ga_s2am_ard_3-2-1_50KLU_2022-12-20_final.stac-item
2022-12-20 12:04:26	ga_s2am_ard_3-2-1_49KHP_2022-12-20_final.stac-item
2022-12-20 12:04:26	ga_s2am_ard_3-2-1_50KKU_2022-12-20_final.stac-item
2022-12-20 12:04:30	ga_s2am_ard_3-2-1_49KGP_2022-12-20_final.stac-item
2022-12-20 12:04:34	ga_s2am_ard_3-2-1_50JMT_2022-12-20_final.stac-item
2022-12-20 12:04:38	ga_s2am_ard_3-2-1_50JLT_2022-12-20_final.stac-item
2022-12-20 12:04:41	ga_s2am_ard_3-2-1_49JHN_2022-12-20_final.stac-item
2022-12-20 12:04:41	ga_s2am_ard_3-2-1_50JKT_2022-12-20_final.stac-item
2022-12-20 12:04:44	ga_s2am_ard_3-2-1_49JGN_2022-12-20_final.stac-item
2022-12-20 12:04:47	ga_s2am_ard_3-2-1_50JMS_2022-12-20_final.stac-item
2022-12-20 12:04:52	ga_s2am_ard_3-2-1_50JLS_2022-12-20_final.stac-item
2022-12-20 12:04:55	ga_s2am_ard_3-2-1_49JHM_2022-12-20_final.stac-item
2022-12-20 12:04:55	ga_s2am_ard_3-2-1_50JKS_2022-12-20_final.stac-item
2022-12-20 12:04:57	ga_s2am_ard_3-2-1_50JMR_2022-12-20_final.stac-item
2022-12-20 12:04:59	ga_s2am_ard_3-2-1_49JGM_2022-12-20_final.stac-item
2022-12-20 12:05:07	ga_s2am_ard_3-2-1_50JLR_2022-12-20_final.stac-item
2022-12-20 12:05:10	ga_s2am_ard_3-2-1_50JKR_2022-12-20_final.stac-item
2022-12-20 12:05:13	ga_s2am_ard_3-2-1_49JGL_2022-12-20_final.stac-item
2022-12-20 12:05:18	ga_s2am_ard_3-2-1_49JFL_2022-12-20_final
2022-12-20 12:05:21	ga_s2am_ard_3-2-1_50JLQ_2022-12-20_final.stac-item
2022-12-20 12:05:25	ga_s2am_ard_3-2-1_50JKQ_2022-12-20_final.stac-item
2022-12-20 12:05:28	ga_s2am_ard_3-2-1_49JGK_2022-12-20_final.stac-item
2022-12-20 12:05:31	ga_s2am_ard_3-2-1_49JFK_2022-12-20_nrt.stac-item
2022-12-20 12:05:36	ga_s2am_ard_3-2-1_50JLP_2022-12-20_final.stac-item
2022-12-20 12:05:39	ga_s2am_ard_3-2-1_50JKP_2022-12-20_final.stac-item
2022-12-20 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2022-12-20_final.stac-item
2022-12-20 12:05:46	ga_s2am_ard_3-2-1_49JFJ_2022-12-20_nrt.stac-item
2022-12-20 12:05:50	ga_s2am_ard_3-2-1_50JLN_2022-12-20_final.stac-item
2022-12-20 12:05:54	ga_s2am_ard_3-2-1_50JKN_2022-12-20_final.stac-item
2022-12-20 12:06:00	ga_s2am_ard_3-2-1_49JFH_2022-12-20_nrt.stac-item
2022-12-20 12:06:03	ga_s2am_ard_3-2-1_50JLM_2022-12-20_final.stac-item
2022-12-20 12:06:08	ga_s2am_ard_3-2-1_50JKM_2022-12-20_final.stac-item
2022-12-20 12:06:11	ga_s2am_ard_3-2-1_49JGG_2022-12-20_nrt.stac-item
2022-12-20 12:06:13	ga_s2am_ard_3-2-1_50JLL_2022-12-20_final.stac-item
2022-12-20 12:06:15	ga_s2am_ard_3-2-1_49JFG_2022-12-20_nrt.stac-item
2022-12-20 12:06:21	ga_s2am_ard_3-2-1_50JKL_2022-12-20_final
2022-12-20 12:06:22	ga_s2am_ard_3-2-1_49JGF_2022-12-20_nrt.stac-item
2022-12-20 12:06:24	ga_s2am_ard_3-2-1_49JFF_2022-12-20_nrt.stac-item
2022-12-21 09:49:35	ga_s2am_ard_3-2-1_56LMP_2022-12-21_nrt.stac-item
2022-12-21 09:49:38	ga_s2am_ard_3-2-1_56LLP_2022-12-21_nrt.stac-item
2022-12-21 09:58:11	ga_s2am_ard_3-2-1_54GWA_2022-12-21_nrt.stac-item
2022-12-21 09:58:30	ga_s2am_ard_3-2-1_54GVV_2022-12-21_nrt.stac-item
2022-12-21 11:30:57	ga_s2am_ard_3-2-1_51LXG_2022-12-21_nrt.stac-item
2022-12-21 11:31:11	ga_s2am_ard_3-2-1_51LXF_2022-12-21_nrt.stac-item
2022-12-21 11:31:29	ga_s2am_ard_3-2-1_51LWE_2022-12-21_final.stac-item
2022-12-21 11:31:40	ga_s2am_ard_3-2-1_51LXD_2022-12-21_final.stac-item
2022-12-21 11:31:55	ga_s2am_ard_3-2-1_51LXC_2022-12-21_final.stac-item
2022-12-21 11:31:57	ga_s2am_ard_3-2-1_51KZB_2022-12-21_final.stac-item
2022-12-21 11:31:58	ga_s2am_ard_3-2-1_51LWC_2022-12-21_final.stac-item
2022-12-21 11:32:05	ga_s2am_ard_3-2-1_51KYB_2022-12-21_final.stac-item
2022-12-21 11:32:09	ga_s2am_ard_3-2-1_51KXB_2022-12-21_final.stac-item
2022-12-21 11:34:14	ga_s2am_ard_3-2-1_51JXN_2022-12-21_final.stac-item
2022-12-21 11:34:16	ga_s2am_ard_3-2-1_51KUP_2022-12-21_final.stac-item
2022-12-21 11:34:23	ga_s2am_ard_3-2-1_51JWN_2022-12-21_final.stac-item
2022-12-21 11:34:27	ga_s2am_ard_3-2-1_51JVN_2022-12-21_final.stac-item
2022-12-21 11:34:30	ga_s2am_ard_3-2-1_51JUN_2022-12-21_final.stac-item
2022-12-21 11:34:34	ga_s2am_ard_3-2-1_51JTN_2022-12-21_final.stac-item
2022-12-21 11:34:35	ga_s2am_ard_3-2-1_50JRT_2022-12-21_final.stac-item
2022-12-21 11:34:38	ga_s2am_ard_3-2-1_51JWM_2022-12-21_final.stac-item
2022-12-21 11:34:41	ga_s2am_ard_3-2-1_51JVM_2022-12-21_final.stac-item
2022-12-21 11:34:44	ga_s2am_ard_3-2-1_51JUM_2022-12-21_final.stac-item
2022-12-21 11:34:47	ga_s2am_ard_3-2-1_50JRS_2022-12-21_final.stac-item
2022-12-21 11:34:47	ga_s2am_ard_3-2-1_51JTM_2022-12-21_final.stac-item
2022-12-21 11:34:52	ga_s2am_ard_3-2-1_51JWL_2022-12-21_final.stac-item
2022-12-21 11:34:56	ga_s2am_ard_3-2-1_51JVL_2022-12-21_final.stac-item
2022-12-21 11:34:59	ga_s2am_ard_3-2-1_51JUL_2022-12-21_final.stac-item
2022-12-21 11:35:02	ga_s2am_ard_3-2-1_51JTL_2022-12-21_final.stac-item
2022-12-21 11:35:06	ga_s2am_ard_3-2-1_51JWK_2022-12-21_final.stac-item
2022-12-21 11:35:10	ga_s2am_ard_3-2-1_51JVK_2022-12-21_final.stac-item
2022-12-21 11:35:14	ga_s2am_ard_3-2-1_51JUK_2022-12-21_final.stac-item
2022-12-21 11:35:17	ga_s2am_ard_3-2-1_51JTK_2022-12-21_final.stac-item
2022-12-21 11:35:17	ga_s2am_ard_3-2-1_51JWJ_2022-12-21_final.stac-item
2022-12-21 11:35:25	ga_s2am_ard_3-2-1_51JVJ_2022-12-21_final.stac-item
2022-12-21 11:35:28	ga_s2am_ard_3-2-1_51JUJ_2022-12-21_final.stac-item
2022-12-21 11:35:31	ga_s2am_ard_3-2-1_51JTJ_2022-12-21_final.stac-item
2022-12-21 11:35:35	ga_s2am_ard_3-2-1_50JQP_2022-12-21_final.stac-item
2022-12-21 11:35:39	ga_s2am_ard_3-2-1_51JVH_2022-12-21_final.stac-item
2022-12-21 11:35:43	ga_s2am_ard_3-2-1_51JUH_2022-12-21_final.stac-item
2022-12-21 11:35:46	ga_s2am_ard_3-2-1_51JTH_2022-12-21_final.stac-item
2022-12-21 11:35:48	ga_s2am_ard_3-2-1_50JQN_2022-12-21_final.stac-item
2022-12-21 11:35:54	ga_s2am_ard_3-2-1_51JVG_2022-12-21_final.stac-item
2022-12-21 11:35:57	ga_s2am_ard_3-2-1_51JUG_2022-12-21_final.stac-item
2022-12-21 11:36:01	ga_s2am_ard_3-2-1_51JTG_2022-12-21_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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