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
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JGH_2016-11-01_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JGJ_2016-11-01_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JHN_2016-11-01_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49KHQ_2016-11-01_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50JKN_2016-11-01_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_50KMU_2016-11-01_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JGK_2016-11-01_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_50HPH_2016-11-02_final.stac-item
2016-11-03 11:05:10	ga_s2am_ard_3-2-1_51HYD_2016-11-03_final.stac-item
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49JHN_2016-11-04_final.stac-item
2016-11-04 12:13:19	ga_s2am_ard_3-2-1_49KHP_2016-11-04_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMJ_2016-11-05_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50JQM_2016-11-05_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50KQA_2016-11-05_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51JTJ_2016-11-05_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HMK_2016-11-05_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HQK_2016-11-05_final.stac-item
2016-11-06 11:14:16	ga_s2am_ard_3-2-1_51HXB_2016-11-06_final.stac-item
2016-11-06 11:14:16	ga_s2am_ard_3-2-1_51HXC_2016-11-06_final.stac-item
2016-11-08 11:56:06	ga_s2am_ard_3-2-1_50JLL_2016-11-08_final.stac-item
2016-11-09 11:26:07	ga_s2am_ard_3-2-1_51HUE_2016-11-09_final.stac-item
2016-11-09 11:26:07	ga_s2am_ard_3-2-1_51HVE_2016-11-09_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JGM_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JHN_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKT_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLL_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLQ_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KMA_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50KMU_2016-11-11_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49JHM_2016-11-11_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPK_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51HVE_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HPH_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_50HQH_2016-11-12_final.stac-item
2016-11-13 11:01:05	ga_s2am_ard_3-2-1_51HYD_2016-11-13_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49JHN_2016-11-14_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_50KKA_2016-11-14_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49JFN_2016-11-14_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49JGK_2016-11-14_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49JGN_2016-11-14_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_49KGR_2016-11-14_final.stac-item
2016-11-15 11:34:43	ga_s2am_ard_3-2-1_50KQA_2016-11-15_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50JMM_2016-11-15_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50JQM_2016-11-15_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50JQT_2016-11-15_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HMK_2016-11-15_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HQH_2016-11-15_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HQK_2016-11-15_final.stac-item
2016-11-16 11:11:49	ga_s2am_ard_3-2-1_51HXB_2016-11-16_final.stac-item
2016-11-16 11:11:49	ga_s2am_ard_3-2-1_51HXC_2016-11-16_final.stac-item
2016-11-16 11:11:49	ga_s2am_ard_3-2-1_51HYD_2016-11-16_final.stac-item
2016-11-18 11:43:43	ga_s2am_ard_3-2-1_50KRD_2016-11-18_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JLL_2016-11-18_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JMM_2016-11-18_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JNL_2016-11-18_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50JNS_2016-11-18_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGM_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JHN_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JKT_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50JLL_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50KMA_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50KNC_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JGK_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49JHM_2016-11-21_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_49KHR_2016-11-21_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51JTM_2016-11-22_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HPH_2016-11-22_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HQH_2016-11-22_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_50HQK_2016-11-22_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KHQ_2016-11-24_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49JFM_2016-11-24_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49JFN_2016-11-24_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49JGK_2016-11-24_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49JGN_2016-11-24_final.stac-item
2016-11-24 12:13:20	ga_s2am_ard_3-2-1_49KGR_2016-11-24_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HMJ_2016-11-28_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JKN_2016-11-28_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JMM_2016-11-28_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50JQT_2016-11-28_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50KNC_2016-11-28_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50KNU_2016-11-28_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HMK_2016-11-28_final.stac-item
2016-11-29 11:23:19	ga_s2am_ard_3-2-1_51HUC_2016-11-29_final.stac-item
2016-11-29 11:23:19	ga_s2am_ard_3-2-1_51HUE_2016-11-29_final.stac-item
2016-11-29 11:23:19	ga_s2am_ard_3-2-1_51HVE_2016-11-29_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49JHN_2016-12-01_final.stac-item
2016-12-01 12:03:46	ga_s2am_ard_3-2-1_49KHP_2016-12-01_final.stac-item
2016-12-02 11:36:01	ga_s2am_ard_3-2-1_51HVE_2016-12-02_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49JHN_2016-12-04_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_50KKV_2016-12-04_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49JGK_2016-12-04_final.stac-item
2016-12-04 12:13:41	ga_s2am_ard_3-2-1_49JGN_2016-12-04_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HMJ_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HPK_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50JNR_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50KQA_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HQH_2016-12-05_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_50HQK_2016-12-05_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HPH_2016-12-05_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

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