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
2019-10-04 11:55:58	ga_s2am_ard_3-2-1_50JLN_2019-10-04_final.stac-item
2019-10-07 12:04:16	ga_s2am_ard_3-2-1_49KHQ_2019-10-07_final.stac-item
2019-10-07 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2019-10-07_final.stac-item
2019-10-07 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-10-07_final.stac-item
2019-10-07 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-10-07_final.stac-item
2019-10-07 12:04:59	ga_s2am_ard_3-2-1_50JKS_2019-10-07_final.stac-item
2019-10-07 12:05:54	ga_s2am_ard_3-2-1_50JLN_2019-10-07_final.stac-item
2019-10-10 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2019-10-10_final.stac-item
2019-10-10 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-10-10_final.stac-item
2019-10-10 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-10-10_final.stac-item
2019-10-10 12:14:33	ga_s2am_ard_3-2-1_49JHN_2019-10-10_final.stac-item
2019-10-10 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-10-10_final.stac-item
2019-10-14 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-10-14_final.stac-item
2019-10-17 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-10-17_final.stac-item
2019-10-17 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2019-10-17_final.stac-item
2019-10-17 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2019-10-17_final.stac-item
2019-10-17 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-10-17_final.stac-item
2019-10-17 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-10-17_final.stac-item
2019-10-17 12:05:04	ga_s2am_ard_3-2-1_49JGM_2019-10-17_final.stac-item
2019-10-17 12:05:11	ga_s2am_ard_3-2-1_49JFM_2019-10-17_final.stac-item
2019-10-17 12:05:15	ga_s2am_ard_3-2-1_50JKR_2019-10-17_final.stac-item
2019-10-17 12:05:18	ga_s2am_ard_3-2-1_49JGL_2019-10-17_final.stac-item
2019-10-17 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-10-17_final.stac-item
2019-10-17 12:05:55	ga_s2am_ard_3-2-1_50JLN_2019-10-17_final.stac-item
2019-10-20 12:13:55	ga_s2am_ard_3-2-1_49KHR_2019-10-20_final.stac-item
2019-10-20 12:14:02	ga_s2am_ard_3-2-1_49KHR_2019-10-20_final.stac-item
2019-10-20 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-10-20_final.stac-item
2019-10-20 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-10-20_final.stac-item
2019-10-20 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-10-20_final.stac-item
2019-10-20 12:14:34	ga_s2am_ard_3-2-1_49JHN_2019-10-20_final.stac-item
2019-10-20 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-10-20_final.stac-item
2019-10-20 12:15:14	ga_s2am_ard_3-2-1_49JGL_2019-10-20_final.stac-item
2019-10-24 11:56:00	ga_s2am_ard_3-2-1_50JLN_2019-10-24_final.stac-item
2019-10-27 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-10-27_final.stac-item
2019-10-27 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2019-10-27_final.stac-item
2019-10-27 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2019-10-27_final.stac-item
2019-10-27 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-10-27_final.stac-item
2019-10-27 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-10-27_final.stac-item
2019-10-27 12:05:04	ga_s2am_ard_3-2-1_49JGM_2019-10-27_final.stac-item
2019-10-27 12:05:12	ga_s2am_ard_3-2-1_49JFM_2019-10-27_final.stac-item
2019-10-27 12:05:47	ga_s2am_ard_3-2-1_49JGJ_2019-10-27_final.stac-item
2019-10-27 12:05:55	ga_s2am_ard_3-2-1_50JLN_2019-10-27_final.stac-item
2019-10-30 12:13:58	ga_s2am_ard_3-2-1_49KHR_2019-10-30_final.stac-item
2019-10-30 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2019-10-30_final.stac-item
2019-10-30 12:14:30	ga_s2am_ard_3-2-1_49KGP_2019-10-30_final.stac-item
2019-10-30 12:14:34	ga_s2am_ard_3-2-1_49JHN_2019-10-30_final.stac-item
2019-10-30 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-10-30_final.stac-item
2019-11-03 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-11-03_final.stac-item
2019-11-03 11:56:08	ga_s2am_ard_3-2-1_50JLN_2019-11-03_final.stac-item
2019-11-06 12:04:02	ga_s2am_ard_3-2-1_49KHR_2019-11-06_final.stac-item
2019-11-06 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-11-06_final.stac-item
2019-11-06 12:05:54	ga_s2am_ard_3-2-1_50JLN_2019-11-06_final.stac-item
2019-11-09 12:14:11	ga_s2am_ard_3-2-1_49KHQ_2019-11-09_final.stac-item
2019-11-09 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2019-11-09_final.stac-item
2019-11-09 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-11-09_final.stac-item
2019-11-09 12:14:33	ga_s2am_ard_3-2-1_49JHN_2019-11-09_final.stac-item
2019-11-09 12:14:48	ga_s2am_ard_3-2-1_49JFN_2019-11-09_final.stac-item
2019-11-13 11:55:58	ga_s2am_ard_3-2-1_50JLN_2019-11-13_final.stac-item
2019-11-16 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2019-11-16_final.stac-item
2019-11-16 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2019-11-16_final.stac-item
2019-11-16 12:04:33	ga_s2am_ard_3-2-1_49KGP_2019-11-16_final.stac-item
2019-11-16 12:04:44	ga_s2am_ard_3-2-1_49JHN_2019-11-16_final.stac-item
2019-11-16 12:05:53	ga_s2am_ard_3-2-1_50JLN_2019-11-16_final.stac-item
2019-11-19 12:13:56	ga_s2am_ard_3-2-1_49KHR_2019-11-19_final.stac-item
2019-11-19 12:14:10	ga_s2am_ard_3-2-1_49KHQ_2019-11-19_final.stac-item
2019-11-19 12:14:14	ga_s2am_ard_3-2-1_49KGQ_2019-11-19_final.stac-item
2019-11-19 12:14:28	ga_s2am_ard_3-2-1_49KGP_2019-11-19_final.stac-item
2019-11-19 12:14:32	ga_s2am_ard_3-2-1_49JHN_2019-11-19_final.stac-item
2019-11-19 12:14:47	ga_s2am_ard_3-2-1_49JFN_2019-11-19_final.stac-item
2019-11-23 11:54:58	ga_s2am_ard_3-2-1_50JLS_2019-11-23_final.stac-item
2019-11-23 11:55:57	ga_s2am_ard_3-2-1_50JLN_2019-11-23_final.stac-item
2019-11-26 12:04:13	ga_s2am_ard_3-2-1_49KHQ_2019-11-26_final.stac-item
2019-11-26 12:04:18	ga_s2am_ard_3-2-1_49KGQ_2019-11-26_final.stac-item
2019-11-26 12:04:31	ga_s2am_ard_3-2-1_49KGP_2019-11-26_final.stac-item
2019-11-26 12:04:42	ga_s2am_ard_3-2-1_49JHN_2019-11-26_final.stac-item
2019-11-26 12:05:51	ga_s2am_ard_3-2-1_50JLN_2019-11-26_final.stac-item
2019-11-29 12:13:54	ga_s2am_ard_3-2-1_49KHR_2019-11-29_final.stac-item
2019-11-29 12:14:08	ga_s2am_ard_3-2-1_49KHQ_2019-11-29_final.stac-item
2019-11-29 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2019-11-29_final.stac-item
2019-11-29 12:14:26	ga_s2am_ard_3-2-1_49KGP_2019-11-29_final.stac-item
2019-11-29 12:14:30	ga_s2am_ard_3-2-1_49JHN_2019-11-29_final.stac-item
2019-11-29 12:14:45	ga_s2am_ard_3-2-1_49JFN_2019-11-29_final.stac-item
2019-12-03 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2019-12-03_final.stac-item
2019-12-03 11:57:04	ga_s2am_ard_3-2-1_50HMH_2019-12-03_final.stac-item
2019-12-07 11:36:45	ga_s2am_ard_3-2-1_50HPJ_2019-12-07_final.stac-item
2019-12-07 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2019-12-07_final.stac-item
2019-12-10 11:46:44	ga_s2am_ard_3-2-1_50HPJ_2019-12-10_final.stac-item
2019-12-10 11:46:52	ga_s2am_ard_3-2-1_50HMJ_2019-12-10_final.stac-item
2019-12-10 11:47:06	ga_s2am_ard_3-2-1_50HMH_2019-12-10_final.stac-item
2019-12-13 11:56:47	ga_s2am_ard_3-2-1_50HMJ_2019-12-13_final.stac-item
2019-12-13 11:57:01	ga_s2am_ard_3-2-1_50HMH_2019-12-13_final.stac-item
2019-12-17 11:36:46	ga_s2am_ard_3-2-1_50HPJ_2019-12-17_final.stac-item
2019-12-20 11:46:42	ga_s2am_ard_3-2-1_50HPJ_2019-12-20_final.stac-item
2019-12-20 11:46:49	ga_s2am_ard_3-2-1_50HMJ_2019-12-20_final.stac-item
2019-12-20 11:47:04	ga_s2am_ard_3-2-1_50HMH_2019-12-20_final.stac-item
2019-12-23 11:56:45	ga_s2am_ard_3-2-1_50HMJ_2019-12-23_final.stac-item
2019-12-23 11:57:00	ga_s2am_ard_3-2-1_50HMH_2019-12-23_final.stac-item
2019-12-27 11:36:46	ga_s2am_ard_3-2-1_50HPJ_2019-12-27_final.stac-item
2019-12-30 11:46:43	ga_s2am_ard_3-2-1_50HPJ_2019-12-30_final.stac-item
2019-12-30 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2019-12-30_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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