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
2024-01-17 12:14:33	ga_s2am_ard_3-2-1_49JGN_2024-01-17_final
2024-01-17 12:14:37	ga_s2am_ard_3-2-1_49JFN_2024-01-17_final
2024-01-17 12:14:48	ga_s2am_ard_3-2-1_49JGM_2024-01-17_final
2024-01-17 12:14:51	ga_s2am_ard_3-2-1_49JFM_2024-01-17_final
2024-01-17 12:15:02	ga_s2am_ard_3-2-1_49JGL_2024-01-17_final
2024-01-17 12:15:06	ga_s2am_ard_3-2-1_49JFL_2024-01-17_final
2024-01-17 12:15:11	ga_s2am_ard_3-2-1_49JGK_2024-01-17_final
2024-01-17 12:15:12	ga_s2am_ard_3-2-1_49JFK_2024-01-17_nrt
2024-01-18 08:24:18	ga_s2am_ard_3-2-1_59JKH_2024-01-17_final
2024-01-18 08:24:19	ga_s2am_ard_3-2-1_58JGN_2024-01-17_final
2024-01-18 08:31:33	ga_s2am_ard_3-2-1_57FVV_2024-01-17_final
2024-01-18 09:59:30	ga_s2am_ard_3-2-1_55LHJ_2024-01-18_nrt
2024-01-18 09:59:35	ga_s2am_ard_3-2-1_55LGJ_2024-01-18_nrt
2024-01-18 09:59:38	ga_s2am_ard_3-2-1_55LFJ_2024-01-18_nrt
2024-01-18 09:59:40	ga_s2am_ard_3-2-1_55LHH_2024-01-18_nrt
2024-01-18 09:59:42	ga_s2am_ard_3-2-1_55LEJ_2024-01-18_nrt
2024-01-18 09:59:49	ga_s2am_ard_3-2-1_55LGH_2024-01-18_nrt
2024-01-18 09:59:53	ga_s2am_ard_3-2-1_55LFH_2024-01-18_nrt
2024-01-18 09:59:56	ga_s2am_ard_3-2-1_55LEH_2024-01-18_nrt
2024-01-18 10:00:00	ga_s2am_ard_3-2-1_55LDH_2024-01-18_nrt
2024-01-18 10:00:04	ga_s2am_ard_3-2-1_55LGG_2024-01-18_nrt
2024-01-18 10:00:07	ga_s2am_ard_3-2-1_55LFG_2024-01-18_nrt
2024-01-18 10:00:11	ga_s2am_ard_3-2-1_55LEG_2024-01-18_nrt
2024-01-18 10:00:14	ga_s2am_ard_3-2-1_55LDG_2024-01-18_nrt
2024-01-18 10:00:18	ga_s2am_ard_3-2-1_55LGF_2024-01-18_nrt
2024-01-18 10:00:22	ga_s2am_ard_3-2-1_55LFF_2024-01-18_nrt
2024-01-18 10:00:25	ga_s2am_ard_3-2-1_55LEF_2024-01-18_nrt
2024-01-18 10:00:28	ga_s2am_ard_3-2-1_55LDF_2024-01-18_nrt
2024-01-18 10:00:32	ga_s2am_ard_3-2-1_55LGE_2024-01-18_nrt
2024-01-18 10:00:36	ga_s2am_ard_3-2-1_55LFE_2024-01-18_nrt
2024-01-18 10:00:40	ga_s2am_ard_3-2-1_55LEE_2024-01-18_nrt
2024-01-18 10:00:43	ga_s2am_ard_3-2-1_55LDE_2024-01-18_nrt
2024-01-18 10:00:43	ga_s2am_ard_3-2-1_55LGD_2024-01-18_nrt
2024-01-18 10:00:51	ga_s2am_ard_3-2-1_55LFD_2024-01-18_nrt
2024-01-18 10:00:54	ga_s2am_ard_3-2-1_55LED_2024-01-18_nrt
2024-01-18 10:00:58	ga_s2am_ard_3-2-1_55LDD_2024-01-18_nrt
2024-01-18 10:01:03	ga_s2am_ard_3-2-1_55LCD_2024-01-18_final
2024-01-18 10:01:05	ga_s2am_ard_3-2-1_55LFC_2024-01-18_final
2024-01-18 10:06:54	ga_s2am_ard_3-2-1_54HYE_2024-01-18_final
2024-01-18 10:07:03	ga_s2am_ard_3-2-1_54HWE_2024-01-18_final
2024-01-18 10:07:06	ga_s2am_ard_3-2-1_54HYD_2024-01-18_final
2024-01-18 10:07:17	ga_s2am_ard_3-2-1_54HWD_2024-01-18_final
2024-01-18 10:07:26	ga_s2am_ard_3-2-1_54HUD_2024-01-18_final
2024-01-18 10:07:32	ga_s2am_ard_3-2-1_54HWC_2024-01-18_final
2024-01-18 10:07:35	ga_s2am_ard_3-2-1_54HVC_2024-01-18_final
2024-01-18 10:07:37	ga_s2am_ard_3-2-1_54HUC_2024-01-18_nrt
2024-01-18 10:07:38	ga_s2am_ard_3-2-1_54HXB_2024-01-18_nrt
2024-01-18 10:07:40	ga_s2am_ard_3-2-1_54HWB_2024-01-18_nrt
2024-01-18 10:07:41	ga_s2am_ard_3-2-1_54HVB_2024-01-18_nrt
2024-01-18 11:40:16	ga_s2am_ard_3-2-1_51LXJ_2024-01-18_nrt
2024-01-18 11:40:19	ga_s2am_ard_3-2-1_51LWJ_2024-01-18_nrt
2024-01-18 11:40:23	ga_s2am_ard_3-2-1_51LVJ_2024-01-18_nrt
2024-01-18 11:40:26	ga_s2am_ard_3-2-1_51LUJ_2024-01-18_nrt
2024-01-18 11:40:30	ga_s2am_ard_3-2-1_51LXH_2024-01-18_nrt
2024-01-18 11:40:34	ga_s2am_ard_3-2-1_51LWH_2024-01-18_nrt
2024-01-18 11:40:37	ga_s2am_ard_3-2-1_51LVH_2024-01-18_nrt
2024-01-18 11:40:40	ga_s2am_ard_3-2-1_51LUH_2024-01-18_nrt
2024-01-18 11:40:45	ga_s2am_ard_3-2-1_51LXG_2024-01-18_nrt
2024-01-18 11:40:48	ga_s2am_ard_3-2-1_51LWG_2024-01-18_final
2024-01-18 11:40:55	ga_s2am_ard_3-2-1_51LUG_2024-01-18_nrt
2024-01-18 11:40:58	ga_s2am_ard_3-2-1_51LXF_2024-01-18_nrt
2024-01-18 11:41:17	ga_s2am_ard_3-2-1_51LWE_2024-01-18_final
2024-01-18 11:41:24	ga_s2am_ard_3-2-1_51LUE_2024-01-18_final
2024-01-18 11:41:29	ga_s2am_ard_3-2-1_51LTE_2024-01-18_nrt
2024-01-18 11:41:38	ga_s2am_ard_3-2-1_51LUD_2024-01-18_final
2024-01-18 11:41:42	ga_s2am_ard_3-2-1_51LTD_2024-01-18_nrt
2024-01-18 11:41:46	ga_s2am_ard_3-2-1_51LWC_2024-01-18_final
2024-01-18 11:41:50	ga_s2am_ard_3-2-1_51LVC_2024-01-18_final
2024-01-18 11:41:53	ga_s2am_ard_3-2-1_51LUC_2024-01-18_final
2024-01-18 11:41:56	ga_s2am_ard_3-2-1_51LTC_2024-01-18_nrt
2024-01-18 11:41:59	ga_s2am_ard_3-2-1_50LRH_2024-01-18_nrt
2024-01-18 11:42:00	ga_s2am_ard_3-2-1_51KWB_2024-01-18_final
2024-01-18 11:42:04	ga_s2am_ard_3-2-1_51KVB_2024-01-18_final
2024-01-18 11:42:08	ga_s2am_ard_3-2-1_51KUB_2024-01-18_final
2024-01-18 11:42:11	ga_s2am_ard_3-2-1_51KTB_2024-01-18_nrt
2024-01-18 11:42:12	ga_s2am_ard_3-2-1_50KRG_2024-01-18_nrt
2024-01-18 11:42:13	ga_s2am_ard_3-2-1_51KWA_2024-01-18_final
2024-01-18 11:42:19	ga_s2am_ard_3-2-1_51KVA_2024-01-18_final
2024-01-18 11:42:22	ga_s2am_ard_3-2-1_51KUA_2024-01-18_final
2024-01-18 11:42:23	ga_s2am_ard_3-2-1_51KWV_2024-01-18_final
2024-01-18 11:42:25	ga_s2am_ard_3-2-1_51KTA_2024-01-18_nrt
2024-01-18 11:42:26	ga_s2am_ard_3-2-1_50KRF_2024-01-18_nrt
2024-01-18 11:42:33	ga_s2am_ard_3-2-1_51KVV_2024-01-18_final
2024-01-18 11:42:37	ga_s2am_ard_3-2-1_51KUV_2024-01-18_final
2024-01-18 11:42:40	ga_s2am_ard_3-2-1_51KTV_2024-01-18_nrt
2024-01-18 11:42:41	ga_s2am_ard_3-2-1_50KRE_2024-01-18_nrt
2024-01-18 11:42:48	ga_s2am_ard_3-2-1_51KVU_2024-01-18_final
2024-01-18 11:42:51	ga_s2am_ard_3-2-1_51KUU_2024-01-18_final
2024-01-18 11:42:54	ga_s2am_ard_3-2-1_51KTU_2024-01-18_final
2024-01-18 11:42:55	ga_s2am_ard_3-2-1_50KRD_2024-01-18_final
2024-01-18 11:43:00	ga_s2am_ard_3-2-1_50KQD_2024-01-18_final
2024-01-18 11:43:02	ga_s2am_ard_3-2-1_51KVT_2024-01-18_final
2024-01-18 11:43:06	ga_s2am_ard_3-2-1_51KUT_2024-01-18_final
2024-01-18 11:43:09	ga_s2am_ard_3-2-1_51KTT_2024-01-18_final
2024-01-18 11:43:09	ga_s2am_ard_3-2-1_50KRC_2024-01-18_final
2024-01-18 11:43:13	ga_s2am_ard_3-2-1_50KQC_2024-01-18_final
2024-01-18 11:43:16	ga_s2am_ard_3-2-1_51KVS_2024-01-18_final
2024-01-18 11:43:20	ga_s2am_ard_3-2-1_51KUS_2024-01-18_final
2024-01-18 11:43:24	ga_s2am_ard_3-2-1_51KTS_2024-01-18_final
2024-01-18 11:43:24	ga_s2am_ard_3-2-1_50KRB_2024-01-18_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

All years