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
2022-04-23 10:54:04	ga_s2am_ard_3-2-1_53JMN_2022-04-23_final.stac-item
2022-04-23 10:54:13	ga_s2am_ard_3-2-1_53JLN_2022-04-23_final.stac-item
2022-04-23 10:54:17	ga_s2am_ard_3-2-1_53JKN_2022-04-23_final.stac-item
2022-04-23 10:54:26	ga_s2am_ard_3-2-1_52JFT_2022-04-23_final.stac-item
2022-04-23 10:54:28	ga_s2am_ard_3-2-1_53JLM_2022-04-23_final.stac-item
2022-04-23 10:54:31	ga_s2am_ard_3-2-1_53JKM_2022-04-23_final.stac-item
2022-04-23 10:54:38	ga_s2am_ard_3-2-1_52JFS_2022-04-23_final.stac-item
2022-04-23 10:54:42	ga_s2am_ard_3-2-1_53JLL_2022-04-23_final.stac-item
2022-04-23 10:54:46	ga_s2am_ard_3-2-1_53JKL_2022-04-23_final.stac-item
2022-04-23 10:54:52	ga_s2am_ard_3-2-1_52JFR_2022-04-23_final.stac-item
2022-04-23 10:54:57	ga_s2am_ard_3-2-1_53JLK_2022-04-23_final.stac-item
2022-04-23 10:55:00	ga_s2am_ard_3-2-1_53JKK_2022-04-23_final.stac-item
2022-04-23 10:55:07	ga_s2am_ard_3-2-1_52JFQ_2022-04-23_final.stac-item
2022-04-23 10:55:10	ga_s2am_ard_3-2-1_53JLJ_2022-04-23_final.stac-item
2022-04-23 10:55:15	ga_s2am_ard_3-2-1_53JKJ_2022-04-23_final.stac-item
2022-04-23 10:55:18	ga_s2am_ard_3-2-1_52JGP_2022-04-23_final.stac-item
2022-04-23 10:55:20	ga_s2am_ard_3-2-1_53JLH_2022-04-23_final.stac-item
2022-04-23 10:55:21	ga_s2am_ard_3-2-1_52JFP_2022-04-23_final.stac-item
2022-04-23 10:55:27	ga_s2am_ard_3-2-1_52JEP_2022-04-23_final.stac-item
2022-04-23 10:55:29	ga_s2am_ard_3-2-1_53JKH_2022-04-23_final.stac-item
2022-04-23 10:55:32	ga_s2am_ard_3-2-1_52JGN_2022-04-23_final.stac-item
2022-04-23 10:55:36	ga_s2am_ard_3-2-1_52JFN_2022-04-23_final.stac-item
2022-04-23 10:55:39	ga_s2am_ard_3-2-1_52JEN_2022-04-23_final.stac-item
2022-04-23 10:55:44	ga_s2am_ard_3-2-1_53JKG_2022-04-23_final.stac-item
2022-04-23 10:55:47	ga_s2am_ard_3-2-1_52JGM_2022-04-23_final.stac-item
2022-04-23 10:55:50	ga_s2am_ard_3-2-1_52JFM_2022-04-23_final.stac-item
2022-04-23 10:55:54	ga_s2am_ard_3-2-1_52JEM_2022-04-23_final.stac-item
2022-04-23 10:55:59	ga_s2am_ard_3-2-1_53JKF_2022-04-23_final.stac-item
2022-04-23 10:56:01	ga_s2am_ard_3-2-1_52JGL_2022-04-23_final.stac-item
2022-04-23 10:56:05	ga_s2am_ard_3-2-1_52JFL_2022-04-23_final.stac-item
2022-04-23 10:56:08	ga_s2am_ard_3-2-1_52JEL_2022-04-23_final.stac-item
2022-04-24 10:19:43	ga_s2am_ard_3-2-1_54LZQ_2022-04-24_final.stac-item
2022-04-24 10:19:57	ga_s2am_ard_3-2-1_54LZP_2022-04-24_final.stac-item
2022-04-24 10:23:45	ga_s2am_ard_3-2-1_53KRQ_2022-04-24_final.stac-item
2022-04-24 10:23:45	ga_s2am_ard_3-2-1_54KWU_2022-04-24_final.stac-item
2022-04-24 10:23:48	ga_s2am_ard_3-2-1_54KVU_2022-04-24_final.stac-item
2022-04-24 10:23:51	ga_s2am_ard_3-2-1_54KUU_2022-04-24_final.stac-item
2022-04-24 10:23:55	ga_s2am_ard_3-2-1_54KTU_2022-04-24_final.stac-item
2022-04-24 10:23:55	ga_s2am_ard_3-2-1_53KRP_2022-04-24_final.stac-item
2022-04-24 10:23:59	ga_s2am_ard_3-2-1_54JWT_2022-04-24_final.stac-item
2022-04-24 10:24:03	ga_s2am_ard_3-2-1_54JVT_2022-04-24_final.stac-item
2022-04-24 10:24:06	ga_s2am_ard_3-2-1_54JUT_2022-04-24_final.stac-item
2022-04-24 10:24:09	ga_s2am_ard_3-2-1_53JRN_2022-04-24_final.stac-item
2022-04-24 10:24:09	ga_s2am_ard_3-2-1_54JTT_2022-04-24_final.stac-item
2022-04-24 10:24:13	ga_s2am_ard_3-2-1_54JWS_2022-04-24_final.stac-item
2022-04-24 10:24:17	ga_s2am_ard_3-2-1_54JVS_2022-04-24_final.stac-item
2022-04-24 10:24:21	ga_s2am_ard_3-2-1_54JUS_2022-04-24_final.stac-item
2022-04-24 10:24:24	ga_s2am_ard_3-2-1_53JRM_2022-04-24_final.stac-item
2022-04-24 10:24:24	ga_s2am_ard_3-2-1_54JTS_2022-04-24_final.stac-item
2022-04-24 10:24:26	ga_s2am_ard_3-2-1_54JWR_2022-04-24_final.stac-item
2022-04-24 10:24:32	ga_s2am_ard_3-2-1_54JVR_2022-04-24_final.stac-item
2022-04-24 10:24:35	ga_s2am_ard_3-2-1_54JUR_2022-04-24_final.stac-item
2022-04-24 10:24:38	ga_s2am_ard_3-2-1_54JTR_2022-04-24_final.stac-item
2022-04-24 10:24:45	ga_s2am_ard_3-2-1_53JQL_2022-04-24_final.stac-item
2022-04-24 10:24:46	ga_s2am_ard_3-2-1_54JVQ_2022-04-24_final.stac-item
2022-04-24 10:24:50	ga_s2am_ard_3-2-1_54JUQ_2022-04-24_final.stac-item
2022-04-24 10:24:53	ga_s2am_ard_3-2-1_54JTQ_2022-04-24_final.stac-item
2022-04-24 10:24:56	ga_s2am_ard_3-2-1_53JQK_2022-04-24_final.stac-item
2022-04-24 10:25:01	ga_s2am_ard_3-2-1_54JVP_2022-04-24_final.stac-item
2022-04-24 10:25:04	ga_s2am_ard_3-2-1_54JUP_2022-04-24_final.stac-item
2022-04-24 10:25:07	ga_s2am_ard_3-2-1_54JTP_2022-04-24_final.stac-item
2022-04-24 10:25:10	ga_s2am_ard_3-2-1_53JQJ_2022-04-24_final.stac-item
2022-04-24 10:25:16	ga_s2am_ard_3-2-1_54JVN_2022-04-24_final.stac-item
2022-04-24 10:25:19	ga_s2am_ard_3-2-1_54JUN_2022-04-24_final.stac-item
2022-04-24 10:25:22	ga_s2am_ard_3-2-1_54JTN_2022-04-24_final.stac-item
2022-04-24 10:25:25	ga_s2am_ard_3-2-1_53JQH_2022-04-24_final.stac-item
2022-04-24 10:25:29	ga_s2am_ard_3-2-1_54JVM_2022-04-24_final.stac-item
2022-04-24 10:25:33	ga_s2am_ard_3-2-1_54JUM_2022-04-24_final.stac-item
2022-04-24 10:25:37	ga_s2am_ard_3-2-1_54JTM_2022-04-24_final.stac-item
2022-04-24 10:25:39	ga_s2am_ard_3-2-1_53JQG_2022-04-24_final.stac-item
2022-04-24 10:25:40	ga_s2am_ard_3-2-1_54JVL_2022-04-24_final.stac-item
2022-04-24 10:25:45	ga_s2am_ard_3-2-1_53JPG_2022-04-24_final.stac-item
2022-04-24 10:25:48	ga_s2am_ard_3-2-1_54JUL_2022-04-24_final.stac-item
2022-04-24 10:25:51	ga_s2am_ard_3-2-1_54JTL_2022-04-24_final.stac-item
2022-04-24 10:25:54	ga_s2am_ard_3-2-1_53JQF_2022-04-24_final.stac-item
2022-04-24 10:25:57	ga_s2am_ard_3-2-1_53JPF_2022-04-24_final.stac-item
2022-04-24 10:26:02	ga_s2am_ard_3-2-1_54HUK_2022-04-24_final.stac-item
2022-04-24 10:26:06	ga_s2am_ard_3-2-1_54HTK_2022-04-24_final.stac-item
2022-04-24 10:26:08	ga_s2am_ard_3-2-1_53HQE_2022-04-24_final.stac-item
2022-04-24 10:26:12	ga_s2am_ard_3-2-1_53HPE_2022-04-24_final.stac-item
2022-04-24 10:26:17	ga_s2am_ard_3-2-1_54HUJ_2022-04-24_final.stac-item
2022-04-24 10:26:20	ga_s2am_ard_3-2-1_54HTJ_2022-04-24_final.stac-item
2022-04-24 10:26:23	ga_s2am_ard_3-2-1_53HQD_2022-04-24_final.stac-item
2022-04-24 10:26:26	ga_s2am_ard_3-2-1_53HPD_2022-04-24_final.stac-item
2022-04-24 10:26:32	ga_s2am_ard_3-2-1_54HUH_2022-04-24_final.stac-item
2022-04-24 10:26:35	ga_s2am_ard_3-2-1_54HTH_2022-04-24_final.stac-item
2022-04-24 10:26:37	ga_s2am_ard_3-2-1_53HQC_2022-04-24_final.stac-item
2022-04-24 10:26:41	ga_s2am_ard_3-2-1_53HPC_2022-04-24_final.stac-item
2022-04-24 10:26:45	ga_s2am_ard_3-2-1_54HUG_2022-04-24_final.stac-item
2022-04-24 10:26:45	ga_s2am_ard_3-2-1_53HNC_2022-04-24_final.stac-item
2022-04-24 10:26:50	ga_s2am_ard_3-2-1_54HTG_2022-04-24_final.stac-item
2022-04-24 10:26:51	ga_s2am_ard_3-2-1_53HQB_2022-04-24_final.stac-item
2022-04-24 10:26:55	ga_s2am_ard_3-2-1_53HPB_2022-04-24_final.stac-item
2022-04-24 10:26:55	ga_s2am_ard_3-2-1_54HUF_2022-04-24_final.stac-item
2022-04-24 10:26:59	ga_s2am_ard_3-2-1_53HNB_2022-04-24_final.stac-item
2022-04-24 10:27:04	ga_s2am_ard_3-2-1_54HTF_2022-04-24_final.stac-item
2022-04-24 10:27:06	ga_s2am_ard_3-2-1_53HQA_2022-04-24_final.stac-item
2022-04-24 10:27:10	ga_s2am_ard_3-2-1_53HPA_2022-04-24_final.stac-item
2022-04-24 10:27:17	ga_s2am_ard_3-2-1_54HTE_2022-04-24_final
2022-04-24 10:27:18	ga_s2am_ard_3-2-1_53HQV_2022-04-24_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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