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
2022-04-01 11:54:46	ga_s2am_ard_3-2-1_50JLT_2022-04-01_final.stac-item
2022-04-01 11:55:29	ga_s2am_ard_3-2-1_50JLQ_2022-04-01_final.stac-item
2022-04-04 12:04:01	ga_s2am_ard_3-2-1_49KHR_2022-04-04_final.stac-item
2022-04-04 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2022-04-04_final.stac-item
2022-04-04 12:04:33	ga_s2am_ard_3-2-1_49KGP_2022-04-04_final.stac-item
2022-04-04 12:04:41	ga_s2am_ard_3-2-1_50JLT_2022-04-04_final.stac-item
2022-04-04 12:04:59	ga_s2am_ard_3-2-1_50JKS_2022-04-04_final.stac-item
2022-04-04 12:05:06	ga_s2am_ard_3-2-1_50JKS_2022-04-04_final.stac-item
2022-04-04 12:05:06	ga_s2am_ard_3-2-1_50JKR_2022-04-04_final.stac-item
2022-04-04 12:05:08	ga_s2am_ard_3-2-1_49JGM_2022-04-04_final.stac-item
2022-04-04 12:05:13	ga_s2am_ard_3-2-1_50JKR_2022-04-04_final.stac-item
2022-04-04 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-04-04_final.stac-item
2022-04-07 12:13:55	ga_s2am_ard_3-2-1_49KHR_2022-04-07_final.stac-item
2022-04-07 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-04-07_final.stac-item
2022-04-07 12:14:28	ga_s2am_ard_3-2-1_49KGP_2022-04-07_final.stac-item
2022-04-07 12:14:57	ga_s2am_ard_3-2-1_49JGM_2022-04-07_final.stac-item
2022-04-07 12:15:00	ga_s2am_ard_3-2-1_49JFM_2022-04-07_final.stac-item
2022-04-11 11:54:46	ga_s2am_ard_3-2-1_50JLT_2022-04-11_final.stac-item
2022-04-11 11:55:29	ga_s2am_ard_3-2-1_50JLQ_2022-04-11_final.stac-item
2022-04-14 12:04:02	ga_s2am_ard_3-2-1_49KHR_2022-04-14_final.stac-item
2022-04-14 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2022-04-14_final.stac-item
2022-04-14 12:04:34	ga_s2am_ard_3-2-1_49KGP_2022-04-14_final.stac-item
2022-04-14 12:04:42	ga_s2am_ard_3-2-1_50JLT_2022-04-14_final.stac-item
2022-04-14 12:05:00	ga_s2am_ard_3-2-1_50JKS_2022-04-14_final.stac-item
2022-04-14 12:05:02	ga_s2am_ard_3-2-1_49JGM_2022-04-14_final.stac-item
2022-04-14 12:05:07	ga_s2am_ard_3-2-1_50JKS_2022-04-14_final.stac-item
2022-04-14 12:05:07	ga_s2am_ard_3-2-1_50JKR_2022-04-14_final.stac-item
2022-04-14 12:05:09	ga_s2am_ard_3-2-1_49JGM_2022-04-14_final.stac-item
2022-04-14 12:05:11	ga_s2am_ard_3-2-1_49JFM_2022-04-14_final.stac-item
2022-04-14 12:05:15	ga_s2am_ard_3-2-1_50JKR_2022-04-14_final.stac-item
2022-04-14 12:05:26	ga_s2am_ard_3-2-1_50JLQ_2022-04-14_final.stac-item
2022-04-14 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2022-04-14_final.stac-item
2022-04-17 12:13:58	ga_s2am_ard_3-2-1_49KHR_2022-04-17_final.stac-item
2022-04-17 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-04-17_final.stac-item
2022-04-17 12:14:30	ga_s2am_ard_3-2-1_49KGP_2022-04-17_final.stac-item
2022-04-17 12:15:00	ga_s2am_ard_3-2-1_49JGM_2022-04-17_final.stac-item
2022-04-17 12:15:03	ga_s2am_ard_3-2-1_49JFM_2022-04-17_final.stac-item
2022-04-21 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2022-04-21_final.stac-item
2022-04-24 12:04:04	ga_s2am_ard_3-2-1_49KHR_2022-04-24_final.stac-item
2022-04-24 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2022-04-24_final.stac-item
2022-04-24 12:04:36	ga_s2am_ard_3-2-1_49KGP_2022-04-24_final.stac-item
2022-04-24 12:04:44	ga_s2am_ard_3-2-1_50JLT_2022-04-24_final.stac-item
2022-04-24 12:05:02	ga_s2am_ard_3-2-1_50JKS_2022-04-24_final.stac-item
2022-04-24 12:05:03	ga_s2am_ard_3-2-1_50JMR_2022-04-24_final.stac-item
2022-04-24 12:05:05	ga_s2am_ard_3-2-1_49JGM_2022-04-24_final.stac-item
2022-04-24 12:05:13	ga_s2am_ard_3-2-1_49JFM_2022-04-24_final.stac-item
2022-04-24 12:05:17	ga_s2am_ard_3-2-1_50JKR_2022-04-24_final.stac-item
2022-04-24 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2022-04-24_final.stac-item
2022-04-24 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2022-04-24_final.stac-item
2022-04-27 12:14:00	ga_s2am_ard_3-2-1_49KHR_2022-04-27_final.stac-item
2022-04-27 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2022-04-27_final.stac-item
2022-04-27 12:14:32	ga_s2am_ard_3-2-1_49KGP_2022-04-27_final.stac-item
2022-04-27 12:14:50	ga_s2am_ard_3-2-1_49JFN_2022-04-27_final.stac-item
2022-04-27 12:15:01	ga_s2am_ard_3-2-1_49JGM_2022-04-27_final.stac-item
2022-04-27 12:15:05	ga_s2am_ard_3-2-1_49JFM_2022-04-27_final.stac-item
2022-04-27 12:15:13	ga_s2am_ard_3-2-1_49JFM_2022-04-27_final.stac-item
2022-05-01 11:56:16	ga_s2am_ard_3-2-1_50JLM_2022-05-01_final.stac-item
2022-05-01 11:56:19	ga_s2am_ard_3-2-1_50JKM_2022-05-01_final.stac-item
2022-05-01 11:56:41	ga_s2am_ard_3-2-1_50HMK_2022-05-01_final.stac-item
2022-05-01 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2022-05-01_final.stac-item
2022-05-01 11:57:14	ga_s2am_ard_3-2-1_50HLH_2022-05-01_final.stac-item
2022-05-01 11:57:23	ga_s2am_ard_3-2-1_50HLH_2022-05-01_final.stac-item
2022-05-04 12:06:09	ga_s2am_ard_3-2-1_50JLM_2022-05-04_final.stac-item
2022-05-04 12:06:15	ga_s2am_ard_3-2-1_50JKM_2022-05-04_final.stac-item
2022-05-05 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-05-05_final.stac-item
2022-05-05 11:37:11	ga_s2am_ard_3-2-1_50HPH_2022-05-05_final.stac-item
2022-05-08 11:46:45	ga_s2am_ard_3-2-1_50HMK_2022-05-08_final.stac-item
2022-05-08 11:46:58	ga_s2am_ard_3-2-1_50HQH_2022-05-08_final.stac-item
2022-05-08 11:47:06	ga_s2am_ard_3-2-1_50HPH_2022-05-08_final.stac-item
2022-05-08 11:47:18	ga_s2am_ard_3-2-1_50HLH_2022-05-08_final.stac-item
2022-05-11 11:56:15	ga_s2am_ard_3-2-1_50JLM_2022-05-11_final.stac-item
2022-05-11 11:56:17	ga_s2am_ard_3-2-1_50JKM_2022-05-11_final.stac-item
2022-05-11 11:56:40	ga_s2am_ard_3-2-1_50HMK_2022-05-11_final.stac-item
2022-05-11 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2022-05-11_final.stac-item
2022-05-11 11:57:13	ga_s2am_ard_3-2-1_50HLH_2022-05-11_final.stac-item
2022-05-14 12:06:08	ga_s2am_ard_3-2-1_50JLM_2022-05-14_final.stac-item
2022-05-14 12:06:14	ga_s2am_ard_3-2-1_50JKM_2022-05-14_final.stac-item
2022-05-15 11:37:07	ga_s2am_ard_3-2-1_50HQH_2022-05-15_final.stac-item
2022-05-15 11:37:11	ga_s2am_ard_3-2-1_50HPH_2022-05-15_final.stac-item
2022-05-18 11:46:46	ga_s2am_ard_3-2-1_50HMK_2022-05-18_final.stac-item
2022-05-18 11:46:59	ga_s2am_ard_3-2-1_50HQH_2022-05-18_final.stac-item
2022-05-18 11:47:08	ga_s2am_ard_3-2-1_50HPH_2022-05-18_final.stac-item
2022-05-18 11:47:20	ga_s2am_ard_3-2-1_50HLH_2022-05-18_final.stac-item
2022-05-21 11:56:17	ga_s2am_ard_3-2-1_50JLM_2022-05-21_final.stac-item
2022-05-21 11:56:20	ga_s2am_ard_3-2-1_50JKM_2022-05-21_final.stac-item
2022-05-21 11:56:43	ga_s2am_ard_3-2-1_50HMK_2022-05-21_final.stac-item
2022-05-21 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-05-21_final.stac-item
2022-05-21 11:57:16	ga_s2am_ard_3-2-1_50HLH_2022-05-21_final.stac-item
2022-05-24 12:06:11	ga_s2am_ard_3-2-1_50JLM_2022-05-24_final.stac-item
2022-05-24 12:06:17	ga_s2am_ard_3-2-1_50JKM_2022-05-24_final.stac-item
2022-05-25 11:37:10	ga_s2am_ard_3-2-1_50HQH_2022-05-25_final.stac-item
2022-05-25 11:37:14	ga_s2am_ard_3-2-1_50HPH_2022-05-25_final.stac-item
2022-05-28 11:46:48	ga_s2am_ard_3-2-1_50HMK_2022-05-28_final.stac-item
2022-05-28 11:47:01	ga_s2am_ard_3-2-1_50HQH_2022-05-28_final.stac-item
2022-05-28 11:47:10	ga_s2am_ard_3-2-1_50HPH_2022-05-28_final.stac-item
2022-05-28 11:47:22	ga_s2am_ard_3-2-1_50HLH_2022-05-28_final.stac-item
2022-05-31 11:56:19	ga_s2am_ard_3-2-1_50JLM_2022-05-31_final.stac-item
2022-05-31 11:56:22	ga_s2am_ard_3-2-1_50JKM_2022-05-31_final.stac-item
2022-05-31 11:56:44	ga_s2am_ard_3-2-1_50HMK_2022-05-31_final.stac-item
2022-05-31 11:57:02	ga_s2am_ard_3-2-1_50HLJ_2022-05-31_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

All years