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
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_54HVH_2016-09-16_final.stac-item
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_54HWG_2016-09-16_final.stac-item
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_54HWH_2016-09-16_final.stac-item
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_54HXG_2016-09-16_final.stac-item
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_54HXH_2016-09-16_final.stac-item
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_54HYG_2016-09-16_final.stac-item
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_54HYH_2016-09-16_final.stac-item
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_55HBB_2016-09-16_final.stac-item
2016-09-16 10:01:37	ga_s2am_ard_3-2-1_55HBC_2016-09-16_final.stac-item
2016-09-19 10:15:49	ga_s2am_ard_3-2-1_54HTG_2016-09-19_final.stac-item
2016-09-19 10:15:49	ga_s2am_ard_3-2-1_54HTH_2016-09-19_final.stac-item
2016-09-19 10:15:49	ga_s2am_ard_3-2-1_54HUG_2016-09-19_final.stac-item
2016-09-19 10:15:49	ga_s2am_ard_3-2-1_54HUH_2016-09-19_final.stac-item
2016-09-19 10:15:49	ga_s2am_ard_3-2-1_54HVG_2016-09-19_final.stac-item
2016-09-19 10:15:49	ga_s2am_ard_3-2-1_54HVH_2016-09-19_final.stac-item
2016-09-19 10:15:49	ga_s2am_ard_3-2-1_54HWH_2016-09-19_final.stac-item
2016-09-19 10:15:49	ga_s2am_ard_3-2-1_53HQB_2016-09-19_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50HMG_2016-09-19_final
2016-10-02 10:26:33	ga_s2am_ard_3-2-1_53HNB_2016-10-02_final.stac-item
2016-10-02 10:26:33	ga_s2am_ard_3-2-1_53HNC_2016-10-02_final.stac-item
2016-10-02 10:26:33	ga_s2am_ard_3-2-1_53HPB_2016-10-02_final.stac-item
2016-10-02 10:26:33	ga_s2am_ard_3-2-1_53HPC_2016-10-02_final.stac-item
2016-10-09 10:15:49	ga_s2am_ard_3-2-1_54HTG_2016-10-09_final.stac-item
2016-10-09 10:15:49	ga_s2am_ard_3-2-1_54HTH_2016-10-09_final.stac-item
2016-10-09 10:15:49	ga_s2am_ard_3-2-1_54HUG_2016-10-09_final.stac-item
2016-10-09 10:15:49	ga_s2am_ard_3-2-1_54HUH_2016-10-09_final.stac-item
2016-10-09 10:15:49	ga_s2am_ard_3-2-1_54HVG_2016-10-09_final.stac-item
2016-10-09 10:15:49	ga_s2am_ard_3-2-1_54HVH_2016-10-09_final.stac-item
2016-10-09 10:15:49	ga_s2am_ard_3-2-1_54HWH_2016-10-09_final.stac-item
2016-10-09 10:15:49	ga_s2am_ard_3-2-1_53HQB_2016-10-09_final.stac-item
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_54HYG_2018-03-27_final.stac-item
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_54HYH_2018-03-27_final.stac-item
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_55HBB_2018-03-27_final.stac-item
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_55HBC_2018-03-27_final.stac-item
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_55HCB_2018-03-27_final.stac-item
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_55HCC_2018-03-27_final.stac-item
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_55HDB_2018-03-27_final.stac-item
2018-03-27 09:50:53	ga_s2am_ard_3-2-1_55HDC_2018-03-27_final.stac-item
2018-03-29 10:30:36	ga_s2am_ard_3-2-1_53HNB_2018-03-29_final.stac-item
2018-03-29 10:30:36	ga_s2am_ard_3-2-1_53HNC_2018-03-29_final.stac-item
2018-03-29 10:30:36	ga_s2am_ard_3-2-1_53HPB_2018-03-29_final.stac-item
2018-03-29 10:30:36	ga_s2am_ard_3-2-1_53HPC_2018-03-29_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_54HVH_2018-03-30_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_54HWG_2018-03-30_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_54HWH_2018-03-30_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_54HXG_2018-03-30_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_54HXH_2018-03-30_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_54HYG_2018-03-30_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_54HYH_2018-03-30_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_55HBB_2018-03-30_final.stac-item
2018-03-30 09:57:06	ga_s2am_ard_3-2-1_55HBC_2018-03-30_final.stac-item
2018-04-06 09:50:54	ga_s2am_ard_3-2-1_54HYG_2018-04-06_final.stac-item
2018-04-06 09:50:54	ga_s2am_ard_3-2-1_54HYH_2018-04-06_final.stac-item
2018-04-06 09:50:54	ga_s2am_ard_3-2-1_55HBB_2018-04-06_final.stac-item
2018-04-06 09:50:54	ga_s2am_ard_3-2-1_55HBC_2018-04-06_final.stac-item
2018-04-06 09:50:54	ga_s2am_ard_3-2-1_55HCB_2018-04-06_final.stac-item
2018-04-06 09:50:54	ga_s2am_ard_3-2-1_55HCC_2018-04-06_final.stac-item
2018-04-06 09:50:54	ga_s2am_ard_3-2-1_55HDB_2018-04-06_final.stac-item
2018-04-06 09:50:54	ga_s2am_ard_3-2-1_55HDC_2018-04-06_final.stac-item
2018-04-07 09:22:45	ga_s2am_ard_3-2-1_56HKG_2018-04-06_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HLH_2018-08-17_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HMH_2018-08-17_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HNH_2018-08-17_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HPH_2018-08-17_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_54HVH_2018-08-27_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_54HWG_2018-08-27_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_54HWH_2018-08-27_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_54HXG_2018-08-27_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_54HXH_2018-08-27_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_54HYG_2018-08-27_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_54HYH_2018-08-27_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_55HBB_2018-08-27_final.stac-item
2018-08-27 09:57:06	ga_s2am_ard_3-2-1_55HBC_2018-08-27_final.stac-item
2018-08-30 10:07:03	ga_s2am_ard_3-2-1_54HTG_2018-08-30_final.stac-item
2018-08-30 10:07:03	ga_s2am_ard_3-2-1_54HTH_2018-08-30_final.stac-item
2018-08-30 10:07:03	ga_s2am_ard_3-2-1_54HUG_2018-08-30_final.stac-item
2018-08-30 10:07:03	ga_s2am_ard_3-2-1_54HUH_2018-08-30_final.stac-item
2018-08-30 10:07:03	ga_s2am_ard_3-2-1_54HVG_2018-08-30_final.stac-item
2018-08-30 10:07:03	ga_s2am_ard_3-2-1_54HVH_2018-08-30_final.stac-item
2018-08-30 10:07:03	ga_s2am_ard_3-2-1_54HWH_2018-08-30_final.stac-item
2018-08-30 10:07:03	ga_s2am_ard_3-2-1_53HQB_2018-08-30_final.stac-item
2022-10-09 11:27:08	ga_s2am_ard_3-2-1_51HUC_2022-10-09_final.stac-item
2022-10-09 11:27:14	ga_s2am_ard_3-2-1_51HTC_2022-10-09_final.stac-item
2022-10-15 10:06:23	ga_s2am_ard_3-2-1_55HBC_2022-10-15_final.stac-item
2022-10-15 10:06:24	ga_s2am_ard_3-2-1_54HYH_2022-10-15_final.stac-item
2022-10-15 10:06:29	ga_s2am_ard_3-2-1_54HXH_2022-10-15_final.stac-item
2022-10-15 10:06:32	ga_s2am_ard_3-2-1_54HWH_2022-10-15_final.stac-item
2023-01-02 10:36:35	ga_s2am_ard_3-2-1_53HNC_2023-01-02_final.stac-item
2023-01-02 10:36:38	ga_s2am_ard_3-2-1_53HMC_2023-01-02_final
2023-01-02 10:36:41	ga_s2am_ard_3-2-1_53HLC_2023-01-02_nrt.stac-item
2023-01-02 10:36:45	ga_s2am_ard_3-2-1_53HPB_2023-01-02_final.stac-item
2023-01-02 10:36:49	ga_s2am_ard_3-2-1_53HNB_2023-01-02_final.stac-item
2023-01-02 10:36:56	ga_s2am_ard_3-2-1_53HLB_2023-01-02_nrt.stac-item
2023-01-10 09:56:14	ga_s2am_ard_3-2-1_55HDC_2023-01-10_final.stac-item
2023-01-10 09:56:18	ga_s2am_ard_3-2-1_55HCC_2023-01-10_final.stac-item
2023-01-10 09:56:21	ga_s2am_ard_3-2-1_55HBC_2023-01-10_final.stac-item
2023-01-10 09:56:23	ga_s2am_ard_3-2-1_54HYH_2023-01-10_final.stac-item
2023-01-10 09:56:29	ga_s2am_ard_3-2-1_55HDB_2023-01-10_final.stac-item
2023-01-10 09:56:32	ga_s2am_ard_3-2-1_55HCB_2023-01-10_final.stac-item
2023-01-10 09:56:36	ga_s2am_ard_3-2-1_55HBB_2023-01-10_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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