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
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_54HTE_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_54HTF_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_54HTG_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_54HTH_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_54HTJ_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_53HQA_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_53HQB_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_53HQC_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_53HQD_2016-08-13_final.stac-item
2016-08-13 10:26:07	ga_s2am_ard_3-2-1_53HQV_2016-08-13_final.stac-item
2016-08-16 10:34:31	ga_s2am_ard_3-2-1_53JQG_2016-08-16_final.stac-item
2016-08-16 10:34:31	ga_s2am_ard_3-2-1_53JQH_2016-08-16_final.stac-item
2016-08-16 10:34:31	ga_s2am_ard_3-2-1_53JQJ_2016-08-16_final.stac-item
2016-08-16 10:34:31	ga_s2am_ard_3-2-1_53JQK_2016-08-16_final.stac-item
2016-08-23 10:26:39	ga_s2am_ard_3-2-1_54HTF_2016-08-23_final.stac-item
2016-08-23 10:26:39	ga_s2am_ard_3-2-1_54HTG_2016-08-23_final.stac-item
2016-08-23 10:26:39	ga_s2am_ard_3-2-1_53HQB_2016-08-23_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_54HTE_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_54HTF_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_54HTG_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_54HTH_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_54HTJ_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_53HQA_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_53HQB_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_53HQC_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_53HQD_2016-09-02_final.stac-item
2016-09-02 10:26:04	ga_s2am_ard_3-2-1_53HQV_2016-09-02_final.stac-item
2016-09-05 10:34:24	ga_s2am_ard_3-2-1_53JQG_2016-09-05_final.stac-item
2016-09-05 10:34:24	ga_s2am_ard_3-2-1_53JQH_2016-09-05_final.stac-item
2016-09-05 10:34:24	ga_s2am_ard_3-2-1_53JQJ_2016-09-05_final.stac-item
2016-09-05 10:34:24	ga_s2am_ard_3-2-1_53JQK_2016-09-05_final.stac-item
2016-09-05 10:34:24	ga_s2am_ard_3-2-1_53JQL_2016-09-05_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HTE_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_54HTF_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_53HQA_2016-09-09_final.stac-item
2016-09-09 10:16:54	ga_s2am_ard_3-2-1_53HQV_2016-09-09_final.stac-item
2016-10-15 10:34:20	ga_s2am_ard_3-2-1_53JQG_2016-10-15_final.stac-item
2016-10-15 10:34:20	ga_s2am_ard_3-2-1_53JQH_2016-10-15_final.stac-item
2016-10-15 10:34:20	ga_s2am_ard_3-2-1_53JQJ_2016-10-15_final.stac-item
2016-10-15 10:34:20	ga_s2am_ard_3-2-1_53JQK_2016-10-15_final.stac-item
2016-10-15 10:34:20	ga_s2am_ard_3-2-1_53JQL_2016-10-15_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53KQA_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53KQB_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53KQU_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53KQV_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53KRB_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53LQC_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53LQD_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53LQE_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53LQF_2016-10-18_final.stac-item
2016-10-18 10:39:46	ga_s2am_ard_3-2-1_53LQG_2016-10-18_final
2016-10-19 10:12:09	ga_s2am_ard_3-2-1_54HTE_2016-10-19_final.stac-item
2016-10-19 10:12:09	ga_s2am_ard_3-2-1_54HTF_2016-10-19_final.stac-item
2016-10-19 10:12:09	ga_s2am_ard_3-2-1_53HQA_2016-10-19_final.stac-item
2016-10-22 10:26:33	ga_s2am_ard_3-2-1_53HQA_2016-10-22_final.stac-item
2016-10-29 10:15:44	ga_s2am_ard_3-2-1_54HTE_2016-10-29_final.stac-item
2016-10-29 10:15:44	ga_s2am_ard_3-2-1_54HTF_2016-10-29_final.stac-item
2016-10-29 10:15:44	ga_s2am_ard_3-2-1_53HQA_2016-10-29_final.stac-item
2016-10-29 10:15:44	ga_s2am_ard_3-2-1_53HQV_2016-10-29_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_54HTE_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_54HTF_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_54HTG_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_54HTH_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_54HTJ_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_54HTK_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53HQA_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53HQB_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53HQC_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53HQD_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53HQE_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53HQV_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53JQF_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53JQG_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53JQH_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53JQJ_2016-11-01_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_53JQK_2016-11-01_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53KQA_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53KQP_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53KQQ_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53KQR_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53KQS_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53KQT_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53KQU_2016-11-04_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53KQV_2016-11-04_final.stac-item
2018-05-22 10:07:06	ga_s2am_ard_3-2-1_54HTF_2018-05-22_final.stac-item
2018-05-22 10:07:06	ga_s2am_ard_3-2-1_53HQA_2018-05-22_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_54HTF_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_54HTG_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_54HTH_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_54HTJ_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_54HTK_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53HQA_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53HQB_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53HQC_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53HQD_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53HQE_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53JQF_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53JQG_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53JQH_2018-06-04_final.stac-item
2018-06-04 10:17:06	ga_s2am_ard_3-2-1_53JQJ_2018-06-04_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