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
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53HLE_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53JLF_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53JLG_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53JLH_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53JLK_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53JLL_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53HMC_2016-10-18_final
2016-10-24 10:57:12	ga_s2am_ard_3-2-1_53LLE_2016-10-24_final.stac-item
2016-10-24 10:57:12	ga_s2am_ard_3-2-1_53LLF_2016-10-24_final.stac-item
2016-10-24 10:57:12	ga_s2am_ard_3-2-1_53LLG_2016-10-24_final.stac-item
2016-10-24 10:57:12	ga_s2am_ard_3-2-1_53LLH_2016-10-24_final
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53HLD_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53HLE_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53HMD_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53HME_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLF_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLG_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLH_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLJ_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLK_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLL_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLM_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53JLN_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53KLP_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53KLQ_2016-10-28_final.stac-item
2016-10-28 10:42:31	ga_s2am_ard_3-2-1_53HMC_2016-10-28_final
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53JLN_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLP_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLQ_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLR_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLS_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLT_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLA_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLB_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLU_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53KLV_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53LLC_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53LLD_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53LLE_2016-10-31_final.stac-item
2016-10-31 10:50:37	ga_s2am_ard_3-2-1_53LLF_2016-10-31_final.stac-item
2018-03-22 10:37:24	ga_s2am_ard_3-2-1_53HLD_2018-03-22_final.stac-item
2018-03-22 10:37:24	ga_s2am_ard_3-2-1_53HMD_2018-03-22_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLA_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLB_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLU_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLV_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53LLC_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53LLD_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53LLE_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53LLF_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53JLN_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLP_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLQ_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLR_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLS_2018-03-25_final.stac-item
2018-03-25 10:47:23	ga_s2am_ard_3-2-1_53KLT_2018-03-25_final.stac-item
2018-04-04 10:47:25	ga_s2am_ard_3-2-1_53KLA_2018-04-04_final.stac-item
2018-04-04 10:47:25	ga_s2am_ard_3-2-1_53KLB_2018-04-04_final.stac-item
2018-04-04 10:47:25	ga_s2am_ard_3-2-1_53KLV_2018-04-04_final.stac-item
2018-04-04 10:47:25	ga_s2am_ard_3-2-1_53LLC_2018-04-04_final.stac-item
2018-04-04 10:47:25	ga_s2am_ard_3-2-1_53LLD_2018-04-04_final.stac-item
2018-04-04 10:47:25	ga_s2am_ard_3-2-1_53LLE_2018-04-04_final.stac-item
2018-04-04 10:47:25	ga_s2am_ard_3-2-1_53LLF_2018-04-04_final.stac-item
2018-04-08 10:27:08	ga_s2am_ard_3-2-1_53HLD_2018-04-08_final.stac-item
2018-04-08 10:27:08	ga_s2am_ard_3-2-1_53HLE_2018-04-08_final.stac-item
2018-04-08 10:27:08	ga_s2am_ard_3-2-1_53HMD_2018-04-08_final.stac-item
2018-04-08 10:27:08	ga_s2am_ard_3-2-1_53HME_2018-04-08_final.stac-item
2018-04-18 10:34:18	ga_s2am_ard_3-2-1_53HLD_2018-04-18_final.stac-item
2018-04-18 10:34:18	ga_s2am_ard_3-2-1_53HLE_2018-04-18_final.stac-item
2018-04-18 10:34:18	ga_s2am_ard_3-2-1_53HMD_2018-04-18_final.stac-item
2018-04-18 10:34:18	ga_s2am_ard_3-2-1_53HME_2018-04-18_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_53LLE_2018-10-24_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_53LLF_2018-10-24_final.stac-item
2018-10-24 10:59:59	ga_s2am_ard_3-2-1_53LLG_2018-10-24_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLA_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLB_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLU_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLV_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53LLC_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53LLD_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53LLE_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53LLF_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53JLN_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLP_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLQ_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLR_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLS_2018-10-31_final.stac-item
2018-10-31 10:47:21	ga_s2am_ard_3-2-1_53KLT_2018-10-31_final.stac-item
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_53LLE_2018-11-03_final.stac-item
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_53LLF_2018-11-03_final.stac-item
2018-11-03 10:57:12	ga_s2am_ard_3-2-1_53LLG_2018-11-03_final.stac-item
2018-11-13 11:00:35	ga_s2am_ard_3-2-1_53LLG_2018-11-13_final.stac-item
2018-11-13 11:00:49	ga_s2am_ard_3-2-1_53LLF_2018-11-13_final.stac-item
2018-11-13 11:01:03	ga_s2am_ard_3-2-1_53LLE_2018-11-13_final.stac-item
2018-11-14 10:36:05	ga_s2am_ard_3-2-1_53HME_2018-11-14_final.stac-item
2018-11-14 10:36:11	ga_s2am_ard_3-2-1_53HLE_2018-11-14_final.stac-item
2018-11-14 10:36:19	ga_s2am_ard_3-2-1_53HMD_2018-11-14_final.stac-item
2018-11-14 10:36:23	ga_s2am_ard_3-2-1_53HLD_2018-11-14_final.stac-item
2019-07-01 11:00:45	ga_s2am_ard_3-2-1_53LLG_2019-07-01_final.stac-item
2019-07-01 11:00:59	ga_s2am_ard_3-2-1_53LLF_2019-07-01_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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