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
2019-02-26 11:56:18	ga_s2am_ard_3-2-1_50JML_2019-02-26_final.stac-item
2019-02-26 11:56:21	ga_s2am_ard_3-2-1_50JLL_2019-02-26_final.stac-item
2019-02-26 11:56:25	ga_s2am_ard_3-2-1_50HNK_2019-02-26_final.stac-item
2019-02-26 11:56:32	ga_s2am_ard_3-2-1_50HMK_2019-02-26_final.stac-item
2019-02-26 11:56:36	ga_s2am_ard_3-2-1_50HLK_2019-02-26_final.stac-item
2019-02-26 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2019-02-26_final.stac-item
2019-02-26 11:56:50	ga_s2am_ard_3-2-1_50HLJ_2019-02-26_final.stac-item
2019-02-26 11:57:01	ga_s2am_ard_3-2-1_50HMH_2019-02-26_final.stac-item
2019-02-26 11:57:05	ga_s2am_ard_3-2-1_50HLH_2019-02-26_final.stac-item
2019-02-27 09:41:37	ga_s2am_ard_3-2-1_56KLF_2019-02-27_final.stac-item
2019-02-27 09:41:40	ga_s2am_ard_3-2-1_56KKF_2019-02-27_final.stac-item
2019-02-27 09:41:51	ga_s2am_ard_3-2-1_56KLE_2019-02-27_final.stac-item
2019-02-27 09:42:06	ga_s2am_ard_3-2-1_56KLD_2019-02-27_final.stac-item
2019-02-27 09:42:29	ga_s2am_ard_3-2-1_55KGT_2019-02-27_final.stac-item
2019-02-27 09:42:35	ga_s2am_ard_3-2-1_56KLB_2019-02-27_final.stac-item
2019-02-27 09:42:38	ga_s2am_ard_3-2-1_56KKB_2019-02-27_final.stac-item
2019-02-27 09:42:39	ga_s2am_ard_3-2-1_55KHS_2019-02-27_final.stac-item
2019-02-27 09:42:42	ga_s2am_ard_3-2-1_55KGS_2019-02-27_final.stac-item
2019-02-27 09:42:45	ga_s2am_ard_3-2-1_56KMA_2019-02-27_final.stac-item
2019-02-27 09:42:49	ga_s2am_ard_3-2-1_56KLA_2019-02-27_final.stac-item
2019-02-27 09:42:53	ga_s2am_ard_3-2-1_56KKA_2019-02-27_final.stac-item
2019-02-27 09:42:53	ga_s2am_ard_3-2-1_55KHR_2019-02-27_final.stac-item
2019-02-27 09:42:57	ga_s2am_ard_3-2-1_55KGR_2019-02-27_final.stac-item
2019-02-27 09:43:04	ga_s2am_ard_3-2-1_56KLV_2019-02-27_final.stac-item
2019-02-27 09:43:07	ga_s2am_ard_3-2-1_56KKV_2019-02-27_final.stac-item
2019-02-27 09:43:07	ga_s2am_ard_3-2-1_55KHQ_2019-02-27_final.stac-item
2019-02-27 09:43:11	ga_s2am_ard_3-2-1_55KGQ_2019-02-27_final.stac-item
2019-02-27 09:43:18	ga_s2am_ard_3-2-1_56KLU_2019-02-27_final.stac-item
2019-02-27 09:48:17	ga_s2am_ard_3-2-1_55GEP_2019-02-27_final.stac-item
2019-02-27 09:48:26	ga_s2am_ard_3-2-1_55GDP_2019-02-27_final.stac-item
2019-02-27 09:48:30	ga_s2am_ard_3-2-1_55GCP_2019-02-27_final.stac-item
2019-02-27 09:48:40	ga_s2am_ard_3-2-1_55GDN_2019-02-27_final.stac-item
2019-02-27 09:48:44	ga_s2am_ard_3-2-1_55GCN_2019-02-27_final.stac-item
2019-02-27 11:21:19	ga_s2am_ard_3-2-1_52LBK_2019-02-27_final.stac-item
2019-02-27 11:21:21	ga_s2am_ard_3-2-1_51LZE_2019-02-27_final.stac-item
2019-02-27 11:21:27	ga_s2am_ard_3-2-1_52LDJ_2019-02-27_final.stac-item
2019-02-27 11:21:31	ga_s2am_ard_3-2-1_52LCJ_2019-02-27_final.stac-item
2019-02-27 11:21:34	ga_s2am_ard_3-2-1_52LBJ_2019-02-27_final.stac-item
2019-02-27 11:21:35	ga_s2am_ard_3-2-1_51LZD_2019-02-27_final.stac-item
2019-02-27 11:21:42	ga_s2am_ard_3-2-1_52LDH_2019-02-27_final.stac-item
2019-02-27 11:21:45	ga_s2am_ard_3-2-1_52LCH_2019-02-27_final.stac-item
2019-02-27 11:21:49	ga_s2am_ard_3-2-1_52LBH_2019-02-27_final.stac-item
2019-02-27 11:21:50	ga_s2am_ard_3-2-1_51LZC_2019-02-27_final.stac-item
2019-02-27 11:21:54	ga_s2am_ard_3-2-1_51LYC_2019-02-27_final.stac-item
2019-02-27 11:21:56	ga_s2am_ard_3-2-1_52KDG_2019-02-27_final.stac-item
2019-02-27 11:22:00	ga_s2am_ard_3-2-1_52KCG_2019-02-27_final.stac-item
2019-02-27 11:22:03	ga_s2am_ard_3-2-1_52KBG_2019-02-27_final.stac-item
2019-02-27 11:22:04	ga_s2am_ard_3-2-1_51KZB_2019-02-27_final.stac-item
2019-02-27 11:22:07	ga_s2am_ard_3-2-1_51KYB_2019-02-27_final.stac-item
2019-02-27 11:22:08	ga_s2am_ard_3-2-1_52KDF_2019-02-27_final.stac-item
2019-02-27 11:22:14	ga_s2am_ard_3-2-1_52KCF_2019-02-27_final.stac-item
2019-02-27 11:22:18	ga_s2am_ard_3-2-1_52KBF_2019-02-27_final.stac-item
2019-02-27 11:22:19	ga_s2am_ard_3-2-1_51KZA_2019-02-27_final.stac-item
2019-02-27 11:22:22	ga_s2am_ard_3-2-1_51KYA_2019-02-27_final.stac-item
2019-02-27 11:22:29	ga_s2am_ard_3-2-1_52KCE_2019-02-27_final.stac-item
2019-02-27 11:22:32	ga_s2am_ard_3-2-1_52KBE_2019-02-27_final.stac-item
2019-02-27 11:22:33	ga_s2am_ard_3-2-1_51KZV_2019-02-27_final.stac-item
2019-02-27 11:22:37	ga_s2am_ard_3-2-1_51KYV_2019-02-27_final.stac-item
2019-02-27 11:22:44	ga_s2am_ard_3-2-1_52KCD_2019-02-27_final.stac-item
2019-02-27 11:22:47	ga_s2am_ard_3-2-1_52KBD_2019-02-27_final.stac-item
2019-02-27 11:22:48	ga_s2am_ard_3-2-1_51KZU_2019-02-27_final.stac-item
2019-02-27 11:22:51	ga_s2am_ard_3-2-1_51KYU_2019-02-27_final.stac-item
2019-02-27 11:22:56	ga_s2am_ard_3-2-1_51KXU_2019-02-27_final.stac-item
2019-02-27 11:22:58	ga_s2am_ard_3-2-1_52KCC_2019-02-27_final.stac-item
2019-02-27 11:23:01	ga_s2am_ard_3-2-1_52KBC_2019-02-27_final.stac-item
2019-02-27 11:23:02	ga_s2am_ard_3-2-1_51KZT_2019-02-27_final.stac-item
2019-02-27 11:23:05	ga_s2am_ard_3-2-1_51KYT_2019-02-27_final.stac-item
2019-02-27 11:23:09	ga_s2am_ard_3-2-1_51KXT_2019-02-27_final.stac-item
2019-02-27 11:23:12	ga_s2am_ard_3-2-1_52KCB_2019-02-27_final.stac-item
2019-02-27 11:23:16	ga_s2am_ard_3-2-1_52KBB_2019-02-27_final.stac-item
2019-02-27 11:23:16	ga_s2am_ard_3-2-1_51KZS_2019-02-27_final.stac-item
2019-02-27 11:23:20	ga_s2am_ard_3-2-1_51KYS_2019-02-27_final.stac-item
2019-02-27 11:23:23	ga_s2am_ard_3-2-1_52KCA_2019-02-27_final.stac-item
2019-02-27 11:23:23	ga_s2am_ard_3-2-1_51KXS_2019-02-27_final.stac-item
2019-02-27 11:23:30	ga_s2am_ard_3-2-1_52KBA_2019-02-27_final.stac-item
2019-02-27 11:23:31	ga_s2am_ard_3-2-1_51KZR_2019-02-27_final.stac-item
2019-02-27 11:23:34	ga_s2am_ard_3-2-1_51KYR_2019-02-27_final.stac-item
2019-02-27 11:23:38	ga_s2am_ard_3-2-1_51KXR_2019-02-27_final.stac-item
2019-02-27 11:23:45	ga_s2am_ard_3-2-1_52KBV_2019-02-27_final.stac-item
2019-02-27 11:23:45	ga_s2am_ard_3-2-1_51KZQ_2019-02-27_final.stac-item
2019-02-27 11:23:49	ga_s2am_ard_3-2-1_51KYQ_2019-02-27_final.stac-item
2019-02-27 11:23:53	ga_s2am_ard_3-2-1_51KXQ_2019-02-27_final.stac-item
2019-02-27 11:23:57	ga_s2am_ard_3-2-1_51KWQ_2019-02-27_final.stac-item
2019-02-27 11:24:00	ga_s2am_ard_3-2-1_51KZP_2019-02-27_final.stac-item
2019-02-27 11:24:00	ga_s2am_ard_3-2-1_52KBU_2019-02-27_final.stac-item
2019-02-27 11:24:03	ga_s2am_ard_3-2-1_51KYP_2019-02-27_final.stac-item
2019-02-27 11:24:07	ga_s2am_ard_3-2-1_51KXP_2019-02-27_final.stac-item
2019-02-27 11:24:10	ga_s2am_ard_3-2-1_51KWP_2019-02-27_final.stac-item
2019-02-27 11:24:14	ga_s2am_ard_3-2-1_51JZN_2019-02-27_final.stac-item
2019-02-27 11:24:14	ga_s2am_ard_3-2-1_52JBT_2019-02-27_final.stac-item
2019-02-27 11:24:18	ga_s2am_ard_3-2-1_51JYN_2019-02-27_final.stac-item
2019-02-27 11:24:22	ga_s2am_ard_3-2-1_51JXN_2019-02-27_final.stac-item
2019-02-27 11:24:25	ga_s2am_ard_3-2-1_51JWN_2019-02-27_final.stac-item
2019-02-27 11:24:28	ga_s2am_ard_3-2-1_51JZM_2019-02-27_final.stac-item
2019-02-27 11:24:28	ga_s2am_ard_3-2-1_52JBS_2019-02-27_final.stac-item
2019-02-27 11:24:32	ga_s2am_ard_3-2-1_51JYM_2019-02-27_final.stac-item
2019-02-27 11:24:36	ga_s2am_ard_3-2-1_51JXM_2019-02-27_final.stac-item
2019-02-27 11:24:39	ga_s2am_ard_3-2-1_52JBR_2019-02-27_final.stac-item
2019-02-27 11:24:40	ga_s2am_ard_3-2-1_51JWM_2019-02-27_final.stac-item
2019-02-27 11:24:46	ga_s2am_ard_3-2-1_51JYL_2019-02-27_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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