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
2018-12-12 09:57:24	ga_s2am_ard_3-2-1_55HCT_2018-12-12_final.stac-item
2018-12-12 09:57:27	ga_s2am_ard_3-2-1_55HBT_2018-12-12_final.stac-item
2018-12-12 09:57:28	ga_s2am_ard_3-2-1_54HYC_2018-12-12_final.stac-item
2018-12-12 09:57:32	ga_s2am_ard_3-2-1_54HXC_2018-12-12_final.stac-item
2018-12-12 09:57:37	ga_s2am_ard_3-2-1_54HWC_2018-12-12_final.stac-item
2018-12-12 09:57:39	ga_s2am_ard_3-2-1_55HCS_2018-12-12_final.stac-item
2018-12-12 09:57:42	ga_s2am_ard_3-2-1_55HBS_2018-12-12_final.stac-item
2018-12-12 09:57:42	ga_s2am_ard_3-2-1_54HYB_2018-12-12_final.stac-item
2018-12-12 09:57:53	ga_s2am_ard_3-2-1_55GCR_2018-12-12_final.stac-item
2018-12-12 09:57:56	ga_s2am_ard_3-2-1_55GBR_2018-12-12_final.stac-item
2018-12-12 09:57:57	ga_s2am_ard_3-2-1_54GYA_2018-12-12_final.stac-item
2018-12-12 09:58:05	ga_s2am_ard_3-2-1_55GCQ_2018-12-12_final.stac-item
2018-12-12 09:58:15	ga_s2am_ard_3-2-1_55GCP_2018-12-12_final.stac-item
2018-12-12 11:31:10	ga_s2am_ard_3-2-1_52LBK_2018-12-12_final.stac-item
2018-12-12 11:31:12	ga_s2am_ard_3-2-1_51LZE_2018-12-12_final.stac-item
2018-12-12 11:31:16	ga_s2am_ard_3-2-1_51LYE_2018-12-12_final.stac-item
2018-12-12 11:31:21	ga_s2am_ard_3-2-1_52LBJ_2018-12-12_final.stac-item
2018-12-12 11:31:22	ga_s2am_ard_3-2-1_51LWE_2018-12-12_final.stac-item
2018-12-12 11:31:27	ga_s2am_ard_3-2-1_51LZD_2018-12-12_final.stac-item
2018-12-12 11:31:30	ga_s2am_ard_3-2-1_51LYD_2018-12-12_final.stac-item
2018-12-12 11:31:34	ga_s2am_ard_3-2-1_51LXD_2018-12-12_final.stac-item
2018-12-12 11:31:40	ga_s2am_ard_3-2-1_51LZC_2018-12-12_final.stac-item
2018-12-12 11:31:45	ga_s2am_ard_3-2-1_51LYC_2018-12-12_final.stac-item
2018-12-12 11:31:48	ga_s2am_ard_3-2-1_51LXC_2018-12-12_final.stac-item
2018-12-12 11:31:51	ga_s2am_ard_3-2-1_51KZB_2018-12-12_final.stac-item
2018-12-12 11:34:20	ga_s2am_ard_3-2-1_51JVN_2018-12-12_final.stac-item
2018-12-12 11:34:23	ga_s2am_ard_3-2-1_51JUN_2018-12-12_final.stac-item
2018-12-12 11:34:28	ga_s2am_ard_3-2-1_51JTN_2018-12-12_final.stac-item
2018-12-12 11:34:28	ga_s2am_ard_3-2-1_50JRT_2018-12-12_final.stac-item
2018-12-12 11:34:35	ga_s2am_ard_3-2-1_51JVM_2018-12-12_final.stac-item
2018-12-12 11:34:38	ga_s2am_ard_3-2-1_51JUM_2018-12-12_final.stac-item
2018-12-12 11:34:41	ga_s2am_ard_3-2-1_50JRS_2018-12-12_final.stac-item
2018-12-12 11:34:41	ga_s2am_ard_3-2-1_51JTM_2018-12-12_final.stac-item
2018-12-12 11:34:46	ga_s2am_ard_3-2-1_51JWL_2018-12-12_final.stac-item
2018-12-12 11:34:49	ga_s2am_ard_3-2-1_51JVL_2018-12-12_final.stac-item
2018-12-12 11:34:53	ga_s2am_ard_3-2-1_51JUL_2018-12-12_final.stac-item
2018-12-12 11:34:56	ga_s2am_ard_3-2-1_51JTL_2018-12-12_final.stac-item
2018-12-12 11:34:59	ga_s2am_ard_3-2-1_51JWK_2018-12-12_final.stac-item
2018-12-12 11:35:04	ga_s2am_ard_3-2-1_51JVK_2018-12-12_final.stac-item
2018-12-12 11:35:07	ga_s2am_ard_3-2-1_51JUK_2018-12-12_final.stac-item
2018-12-12 11:35:10	ga_s2am_ard_3-2-1_51JTK_2018-12-12_final.stac-item
2018-12-12 11:35:11	ga_s2am_ard_3-2-1_51JWJ_2018-12-12_final.stac-item
2018-12-12 11:35:18	ga_s2am_ard_3-2-1_51JVJ_2018-12-12_final.stac-item
2018-12-12 11:35:22	ga_s2am_ard_3-2-1_51JUJ_2018-12-12_final.stac-item
2018-12-12 11:35:25	ga_s2am_ard_3-2-1_51JTJ_2018-12-12_final.stac-item
2018-12-12 11:35:29	ga_s2am_ard_3-2-1_50JQP_2018-12-12_final.stac-item
2018-12-12 11:35:33	ga_s2am_ard_3-2-1_51JVH_2018-12-12_final.stac-item
2018-12-12 11:35:36	ga_s2am_ard_3-2-1_51JUH_2018-12-12_final.stac-item
2018-12-12 11:35:39	ga_s2am_ard_3-2-1_51JTH_2018-12-12_final.stac-item
2018-12-12 11:35:42	ga_s2am_ard_3-2-1_50JQN_2018-12-12_final.stac-item
2018-12-12 11:35:47	ga_s2am_ard_3-2-1_51JVG_2018-12-12_final.stac-item
2018-12-12 11:35:51	ga_s2am_ard_3-2-1_51JUG_2018-12-12_final.stac-item
2018-12-12 11:35:54	ga_s2am_ard_3-2-1_51JTG_2018-12-12_final.stac-item
2018-12-12 11:35:57	ga_s2am_ard_3-2-1_50JQM_2018-12-12_final.stac-item
2018-12-12 11:36:02	ga_s2am_ard_3-2-1_51JVF_2018-12-12_final.stac-item
2018-12-12 11:36:05	ga_s2am_ard_3-2-1_51JUF_2018-12-12_final.stac-item
2018-12-12 11:36:09	ga_s2am_ard_3-2-1_51JTF_2018-12-12_final.stac-item
2018-12-12 11:36:11	ga_s2am_ard_3-2-1_50JQL_2018-12-12_final.stac-item
2018-12-12 11:36:15	ga_s2am_ard_3-2-1_51HVE_2018-12-12_final.stac-item
2018-12-12 11:36:18	ga_s2am_ard_3-2-1_50JPL_2018-12-12_final.stac-item
2018-12-12 11:36:20	ga_s2am_ard_3-2-1_51HUE_2018-12-12_final.stac-item
2018-12-12 11:36:23	ga_s2am_ard_3-2-1_51HTE_2018-12-12_final.stac-item
2018-12-12 11:36:25	ga_s2am_ard_3-2-1_51HVD_2018-12-12_final.stac-item
2018-12-12 11:36:25	ga_s2am_ard_3-2-1_50HQK_2018-12-12_final.stac-item
2018-12-12 11:36:29	ga_s2am_ard_3-2-1_50HPK_2018-12-12_final.stac-item
2018-12-12 11:36:34	ga_s2am_ard_3-2-1_51HUD_2018-12-12_final.stac-item
2018-12-12 11:36:38	ga_s2am_ard_3-2-1_51HTD_2018-12-12_final.stac-item
2018-12-12 11:36:40	ga_s2am_ard_3-2-1_50HQJ_2018-12-12_final.stac-item
2018-12-12 11:36:43	ga_s2am_ard_3-2-1_50HPJ_2018-12-12_final.stac-item
2018-12-12 11:36:47	ga_s2am_ard_3-2-1_51HUC_2018-12-12_final.stac-item
2018-12-12 11:36:49	ga_s2am_ard_3-2-1_51HTC_2018-12-12_final.stac-item
2018-12-12 11:36:50	ga_s2am_ard_3-2-1_50HQH_2018-12-12_final.stac-item
2018-12-12 11:36:52	ga_s2am_ard_3-2-1_50HPH_2018-12-12_final.stac-item
2018-12-12 11:36:54	ga_s2am_ard_3-2-1_51HUC_2018-12-12_final.stac-item
2018-12-12 11:36:56	ga_s2am_ard_3-2-1_51HTC_2018-12-12_final.stac-item
2018-12-12 11:36:57	ga_s2am_ard_3-2-1_50HQH_2018-12-12_final.stac-item
2018-12-12 11:36:59	ga_s2am_ard_3-2-1_50HPH_2018-12-12_final.stac-item
2018-12-13 09:23:31	ga_s2am_ard_3-2-1_56JNT_2018-12-12_final.stac-item
2018-12-13 09:23:46	ga_s2am_ard_3-2-1_56JNS_2018-12-12_final.stac-item
2018-12-13 09:24:20	ga_s2am_ard_3-2-1_56JMQ_2018-12-12_final.stac-item
2018-12-13 09:24:33	ga_s2am_ard_3-2-1_56JMP_2018-12-12_final.stac-item
2018-12-13 09:24:44	ga_s2am_ard_3-2-1_56JNN_2018-12-12_final.stac-item
2018-12-13 09:24:47	ga_s2am_ard_3-2-1_56JMN_2018-12-12_final.stac-item
2018-12-13 09:24:59	ga_s2am_ard_3-2-1_56JNM_2018-12-12_final.stac-item
2018-12-13 09:25:02	ga_s2am_ard_3-2-1_56JMM_2018-12-12_final.stac-item
2018-12-13 09:25:13	ga_s2am_ard_3-2-1_56JNL_2018-12-12_final.stac-item
2018-12-13 09:25:17	ga_s2am_ard_3-2-1_56JML_2018-12-12_final.stac-item
2018-12-13 09:25:21	ga_s2am_ard_3-2-1_56JLL_2018-12-12_final.stac-item
2018-12-13 09:25:31	ga_s2am_ard_3-2-1_56HMK_2018-12-12_final.stac-item
2018-12-13 09:25:34	ga_s2am_ard_3-2-1_56HLK_2018-12-12_final.stac-item
2018-12-13 09:25:46	ga_s2am_ard_3-2-1_56HMJ_2018-12-12_final.stac-item
2018-12-13 09:25:49	ga_s2am_ard_3-2-1_56HLJ_2018-12-12_final.stac-item
2018-12-13 09:26:23	ga_s2am_ard_3-2-1_56HKG_2018-12-12_final.stac-item
2018-12-13 09:26:36	ga_s2am_ard_3-2-1_56HKF_2018-12-12_final.stac-item
2018-12-13 09:26:52	ga_s2am_ard_3-2-1_55HGV_2018-12-12_final.stac-item
2018-12-13 09:27:53	ga_s2am_ard_3-2-1_55GFR_2018-12-12_final.stac-item
2018-12-13 09:28:07	ga_s2am_ard_3-2-1_55GFQ_2018-12-12_final.stac-item
2018-12-13 09:28:22	ga_s2am_ard_3-2-1_55GFP_2018-12-12_final.stac-item
2018-12-13 09:28:29	ga_s2am_ard_3-2-1_55GEP_2018-12-12_final.stac-item
2018-12-13 09:28:36	ga_s2am_ard_3-2-1_55GFN_2018-12-12_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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