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
2018-11-29 09:47:24	ga_s2am_ard_3-2-1_55HDT_2018-11-29_final.stac-item
2018-11-29 09:47:27	ga_s2am_ard_3-2-1_55HCT_2018-11-29_final.stac-item
2018-11-29 09:47:32	ga_s2am_ard_3-2-1_55HBT_2018-11-29_final.stac-item
2018-11-29 09:47:35	ga_s2am_ard_3-2-1_55HES_2018-11-29_final.stac-item
2018-11-29 09:47:36	ga_s2am_ard_3-2-1_54HYC_2018-11-29_final.stac-item
2018-11-29 09:47:38	ga_s2am_ard_3-2-1_55HDS_2018-11-29_final.stac-item
2018-11-29 09:47:42	ga_s2am_ard_3-2-1_55HCS_2018-11-29_final.stac-item
2018-11-29 09:47:45	ga_s2am_ard_3-2-1_55HBS_2018-11-29_final.stac-item
2018-11-29 09:47:46	ga_s2am_ard_3-2-1_54HYB_2018-11-29_final.stac-item
2018-11-29 09:47:49	ga_s2am_ard_3-2-1_55GER_2018-11-29_final.stac-item
2018-11-29 09:47:53	ga_s2am_ard_3-2-1_55GDR_2018-11-29_final.stac-item
2018-11-29 09:47:57	ga_s2am_ard_3-2-1_55GCR_2018-11-29_final.stac-item
2018-11-29 09:48:00	ga_s2am_ard_3-2-1_55GBR_2018-11-29_final.stac-item
2018-11-29 09:48:00	ga_s2am_ard_3-2-1_54GYA_2018-11-29_final.stac-item
2018-11-29 09:48:03	ga_s2am_ard_3-2-1_55GEQ_2018-11-29_final.stac-item
2018-11-29 09:48:07	ga_s2am_ard_3-2-1_55GDQ_2018-11-29_final.stac-item
2018-11-29 09:48:11	ga_s2am_ard_3-2-1_55GCQ_2018-11-29_final.stac-item
2018-11-29 09:48:13	ga_s2am_ard_3-2-1_55GEP_2018-11-29_final.stac-item
2018-11-29 09:48:22	ga_s2am_ard_3-2-1_55GDP_2018-11-29_final.stac-item
2018-11-29 09:48:26	ga_s2am_ard_3-2-1_55GCP_2018-11-29_final.stac-item
2018-11-29 09:48:36	ga_s2am_ard_3-2-1_55GDN_2018-11-29_final.stac-item
2018-11-29 09:48:40	ga_s2am_ard_3-2-1_55GCN_2018-11-29_final.stac-item
2018-11-29 11:21:15	ga_s2am_ard_3-2-1_52LBK_2018-11-29_final.stac-item
2018-11-29 11:21:17	ga_s2am_ard_3-2-1_51LZE_2018-11-29_final.stac-item
2018-11-29 11:21:23	ga_s2am_ard_3-2-1_52LDJ_2018-11-29_final.stac-item
2018-11-29 11:21:27	ga_s2am_ard_3-2-1_52LCJ_2018-11-29_final.stac-item
2018-11-29 11:21:30	ga_s2am_ard_3-2-1_52LBJ_2018-11-29_final.stac-item
2018-11-29 11:21:31	ga_s2am_ard_3-2-1_51LZD_2018-11-29_final.stac-item
2018-11-29 11:21:38	ga_s2am_ard_3-2-1_52LDH_2018-11-29_final.stac-item
2018-11-29 11:21:41	ga_s2am_ard_3-2-1_52LCH_2018-11-29_final.stac-item
2018-11-29 11:21:45	ga_s2am_ard_3-2-1_52LBH_2018-11-29_final.stac-item
2018-11-29 11:21:46	ga_s2am_ard_3-2-1_51LZC_2018-11-29_final.stac-item
2018-11-29 11:21:50	ga_s2am_ard_3-2-1_51LYC_2018-11-29_final.stac-item
2018-11-29 11:21:52	ga_s2am_ard_3-2-1_52KDG_2018-11-29_final.stac-item
2018-11-29 11:21:56	ga_s2am_ard_3-2-1_52KCG_2018-11-29_final.stac-item
2018-11-29 11:21:59	ga_s2am_ard_3-2-1_52KBG_2018-11-29_final.stac-item
2018-11-29 11:22:00	ga_s2am_ard_3-2-1_51KZB_2018-11-29_final.stac-item
2018-11-29 11:22:03	ga_s2am_ard_3-2-1_51KYB_2018-11-29_final.stac-item
2018-11-29 11:22:04	ga_s2am_ard_3-2-1_52KDF_2018-11-29_final.stac-item
2018-11-29 11:22:10	ga_s2am_ard_3-2-1_52KCF_2018-11-29_final.stac-item
2018-11-29 11:22:14	ga_s2am_ard_3-2-1_52KBF_2018-11-29_final.stac-item
2018-11-29 11:22:15	ga_s2am_ard_3-2-1_51KZA_2018-11-29_final.stac-item
2018-11-29 11:22:18	ga_s2am_ard_3-2-1_51KYA_2018-11-29_final.stac-item
2018-11-29 11:22:25	ga_s2am_ard_3-2-1_52KCE_2018-11-29_final.stac-item
2018-11-29 11:22:28	ga_s2am_ard_3-2-1_52KBE_2018-11-29_final.stac-item
2018-11-29 11:22:29	ga_s2am_ard_3-2-1_51KZV_2018-11-29_final.stac-item
2018-11-29 11:22:33	ga_s2am_ard_3-2-1_51KYV_2018-11-29_final.stac-item
2018-11-29 11:22:39	ga_s2am_ard_3-2-1_52KCD_2018-11-29_final.stac-item
2018-11-29 11:22:43	ga_s2am_ard_3-2-1_52KBD_2018-11-29_final.stac-item
2018-11-29 11:22:44	ga_s2am_ard_3-2-1_51KZU_2018-11-29_final.stac-item
2018-11-29 11:22:47	ga_s2am_ard_3-2-1_51KYU_2018-11-29_final.stac-item
2018-11-29 11:22:52	ga_s2am_ard_3-2-1_51KXU_2018-11-29_final.stac-item
2018-11-29 11:22:54	ga_s2am_ard_3-2-1_52KCC_2018-11-29_final.stac-item
2018-11-29 11:22:57	ga_s2am_ard_3-2-1_52KBC_2018-11-29_final.stac-item
2018-11-29 11:22:58	ga_s2am_ard_3-2-1_51KZT_2018-11-29_final.stac-item
2018-11-29 11:23:01	ga_s2am_ard_3-2-1_51KYT_2018-11-29_final.stac-item
2018-11-29 11:23:05	ga_s2am_ard_3-2-1_51KXT_2018-11-29_final.stac-item
2018-11-29 11:23:08	ga_s2am_ard_3-2-1_52KCB_2018-11-29_final.stac-item
2018-11-29 11:23:12	ga_s2am_ard_3-2-1_52KBB_2018-11-29_final.stac-item
2018-11-29 11:23:12	ga_s2am_ard_3-2-1_51KZS_2018-11-29_final.stac-item
2018-11-29 11:23:16	ga_s2am_ard_3-2-1_51KYS_2018-11-29_final.stac-item
2018-11-29 11:23:19	ga_s2am_ard_3-2-1_52KCA_2018-11-29_final.stac-item
2018-11-29 11:23:19	ga_s2am_ard_3-2-1_51KXS_2018-11-29_final.stac-item
2018-11-29 11:23:26	ga_s2am_ard_3-2-1_52KBA_2018-11-29_final.stac-item
2018-11-29 11:23:27	ga_s2am_ard_3-2-1_51KZR_2018-11-29_final.stac-item
2018-11-29 11:23:30	ga_s2am_ard_3-2-1_51KYR_2018-11-29_final.stac-item
2018-11-29 11:23:34	ga_s2am_ard_3-2-1_51KXR_2018-11-29_final.stac-item
2018-11-29 11:23:41	ga_s2am_ard_3-2-1_52KBV_2018-11-29_final.stac-item
2018-11-29 11:23:41	ga_s2am_ard_3-2-1_51KZQ_2018-11-29_final.stac-item
2018-11-29 11:23:45	ga_s2am_ard_3-2-1_51KYQ_2018-11-29_final.stac-item
2018-11-29 11:23:48	ga_s2am_ard_3-2-1_51KXQ_2018-11-29_final.stac-item
2018-11-29 11:23:53	ga_s2am_ard_3-2-1_51KWQ_2018-11-29_final.stac-item
2018-11-29 11:23:55	ga_s2am_ard_3-2-1_51KZP_2018-11-29_final.stac-item
2018-11-29 11:23:56	ga_s2am_ard_3-2-1_52KBU_2018-11-29_final.stac-item
2018-11-29 11:23:59	ga_s2am_ard_3-2-1_51KYP_2018-11-29_final.stac-item
2018-11-29 11:24:03	ga_s2am_ard_3-2-1_51KXP_2018-11-29_final.stac-item
2018-11-29 11:24:06	ga_s2am_ard_3-2-1_51KWP_2018-11-29_final.stac-item
2018-11-29 11:24:10	ga_s2am_ard_3-2-1_51JZN_2018-11-29_final.stac-item
2018-11-29 11:24:10	ga_s2am_ard_3-2-1_52JBT_2018-11-29_final.stac-item
2018-11-29 11:24:14	ga_s2am_ard_3-2-1_51JYN_2018-11-29_final.stac-item
2018-11-29 11:24:18	ga_s2am_ard_3-2-1_51JXN_2018-11-29_final.stac-item
2018-11-29 11:24:55	ga_s2am_ard_3-2-1_51JVL_2018-11-29_final.stac-item
2018-11-29 11:25:08	ga_s2am_ard_3-2-1_51JVK_2018-11-29_final.stac-item
2018-11-29 11:25:22	ga_s2am_ard_3-2-1_51JVJ_2018-11-29_final.stac-item
2018-11-29 11:25:37	ga_s2am_ard_3-2-1_51JVH_2018-11-29_final.stac-item
2018-11-29 11:25:51	ga_s2am_ard_3-2-1_51JVG_2018-11-29_final.stac-item
2018-11-29 11:25:57	ga_s2am_ard_3-2-1_51JUG_2018-11-29_final.stac-item
2018-11-29 11:26:02	ga_s2am_ard_3-2-1_51JWF_2018-11-29_final.stac-item
2018-11-29 11:26:06	ga_s2am_ard_3-2-1_51JVF_2018-11-29_final.stac-item
2018-11-29 11:26:09	ga_s2am_ard_3-2-1_51JUF_2018-11-29_final.stac-item
2018-11-29 11:26:13	ga_s2am_ard_3-2-1_51HXE_2018-11-29_final.stac-item
2018-11-29 11:26:17	ga_s2am_ard_3-2-1_51HWE_2018-11-29_final.stac-item
2018-11-29 11:26:20	ga_s2am_ard_3-2-1_51HVE_2018-11-29_final.stac-item
2018-11-29 11:26:24	ga_s2am_ard_3-2-1_51HUE_2018-11-29_final.stac-item
2018-11-29 11:26:27	ga_s2am_ard_3-2-1_51HXD_2018-11-29_final.stac-item
2018-11-29 11:26:31	ga_s2am_ard_3-2-1_51HWD_2018-11-29_final.stac-item
2018-11-29 11:26:35	ga_s2am_ard_3-2-1_51HVD_2018-11-29_final.stac-item
2018-11-29 11:26:38	ga_s2am_ard_3-2-1_51HUD_2018-11-29_final.stac-item
2018-11-29 11:26:50	ga_s2am_ard_3-2-1_51HVC_2018-11-29_final.stac-item
2018-11-29 11:26:53	ga_s2am_ard_3-2-1_51HUC_2018-11-29_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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