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
2017-04-03 12:14:19	ga_s2am_ard_3-2-1_49JFM_2017-04-03_final.stac-item
2017-04-03 12:14:19	ga_s2am_ard_3-2-1_49JFN_2017-04-03_final.stac-item
2017-04-03 12:14:19	ga_s2am_ard_3-2-1_49JGM_2017-04-03_final.stac-item
2017-04-04 10:01:13	ga_s2am_ard_3-2-1_54JYS_2017-04-04_final.stac-item
2017-04-04 10:01:13	ga_s2am_ard_3-2-1_54JZS_2017-04-04_final.stac-item
2017-04-04 10:01:13	ga_s2am_ard_3-2-1_55JBM_2017-04-04_final.stac-item
2017-04-04 10:01:13	ga_s2am_ard_3-2-1_55JBN_2017-04-04_final.stac-item
2017-04-04 10:01:13	ga_s2am_ard_3-2-1_55JCM_2017-04-04_final.stac-item
2017-04-04 10:01:13	ga_s2am_ard_3-2-1_55JCN_2017-04-04_final.stac-item
2017-04-04 10:01:13	ga_s2am_ard_3-2-1_55JDM_2017-04-04_final.stac-item
2017-04-04 10:01:13	ga_s2am_ard_3-2-1_55JDN_2017-04-04_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_50JKS_2017-04-10_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_50JKT_2017-04-10_final.stac-item
2017-04-10 12:04:40	ga_s2am_ard_3-2-1_50JLS_2017-04-10_final.stac-item
2017-04-16 10:43:06	ga_s2am_ard_3-2-1_53JLN_2017-04-16_final.stac-item
2017-04-16 10:43:06	ga_s2am_ard_3-2-1_53JMM_2017-04-16_final.stac-item
2017-04-16 10:43:06	ga_s2am_ard_3-2-1_53JNN_2017-04-16_final.stac-item
2017-04-16 10:43:06	ga_s2am_ard_3-2-1_53JPN_2017-04-16_final.stac-item
2017-04-18 09:42:56	ga_s2am_ard_3-2-1_56JKS_2017-04-18_final.stac-item
2017-04-18 09:42:56	ga_s2am_ard_3-2-1_56JKT_2017-04-18_final.stac-item
2017-04-18 09:42:56	ga_s2am_ard_3-2-1_56JLS_2017-04-18_final.stac-item
2017-04-18 09:42:56	ga_s2am_ard_3-2-1_56JLT_2017-04-18_final.stac-item
2017-04-18 09:42:56	ga_s2am_ard_3-2-1_55JFM_2017-04-18_final.stac-item
2017-04-18 09:42:56	ga_s2am_ard_3-2-1_55JFN_2017-04-18_final.stac-item
2017-04-18 09:42:56	ga_s2am_ard_3-2-1_55JGM_2017-04-18_final.stac-item
2017-04-18 09:42:56	ga_s2am_ard_3-2-1_55JHM_2017-04-18_final.stac-item
2017-04-22 09:22:46	ga_s2am_ard_3-2-1_56JNS_2017-04-21_final.stac-item
2017-04-22 09:22:46	ga_s2am_ard_3-2-1_56JNT_2017-04-21_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_56JKS_2017-04-25_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_56JKT_2017-04-25_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_56JLS_2017-04-25_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_56JLT_2017-04-25_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_56JMS_2017-04-25_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_56JMT_2017-04-25_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_56JNS_2017-04-25_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_56JNT_2017-04-25_final.stac-item
2017-04-25 09:32:55	ga_s2am_ard_3-2-1_55JHM_2017-04-25_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JCM_2017-05-01_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JCN_2017-05-01_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JDM_2017-05-01_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JDN_2017-05-01_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JEM_2017-05-01_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JEN_2017-05-01_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JFM_2017-05-01_final.stac-item
2017-05-01 09:52:37	ga_s2am_ard_3-2-1_55JFN_2017-05-01_final.stac-item
2017-05-02 09:22:47	ga_s2am_ard_3-2-1_56JNS_2017-05-01_final.stac-item
2017-05-02 09:22:47	ga_s2am_ard_3-2-1_56JNT_2017-05-01_final.stac-item
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_53JLM_2017-05-06_final.stac-item
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_53JLN_2017-05-06_final.stac-item
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_53JMM_2017-05-06_final.stac-item
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_53JMN_2017-05-06_final.stac-item
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_53JNM_2017-05-06_final.stac-item
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_53JNN_2017-05-06_final.stac-item
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_53JPM_2017-05-06_final.stac-item
2017-05-06 10:43:09	ga_s2am_ard_3-2-1_53JPN_2017-05-06_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWM_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JWN_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXM_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JXN_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYM_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JZM_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_52JBS_2018-09-30_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKS_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JKT_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JLS_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JLT_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JMS_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_50JMT_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JGM_2018-10-12_final.stac-item
2018-10-12 12:04:05	ga_s2am_ard_3-2-1_49JHM_2018-10-12_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50JRS_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JTM_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JTN_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JUM_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JUN_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JVM_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JVN_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JWM_2018-10-13_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JWN_2018-10-13_final.stac-item
2023-03-25 09:33:28	ga_s2am_ard_3-2-1_56JPT_2023-03-25_nrt
2023-03-25 09:33:34	ga_s2am_ard_3-2-1_56JNT_2023-03-25_final
2023-03-25 09:33:38	ga_s2am_ard_3-2-1_56JMT_2023-03-25_final
2023-03-25 09:33:38	ga_s2am_ard_3-2-1_56JPS_2023-03-25_nrt
2023-03-25 09:33:41	ga_s2am_ard_3-2-1_56JLT_2023-03-25_final
2023-03-25 09:33:48	ga_s2am_ard_3-2-1_56JKT_2023-03-25_final
2023-03-25 09:33:48	ga_s2am_ard_3-2-1_56JNS_2023-03-25_final
2023-03-25 09:33:52	ga_s2am_ard_3-2-1_56JMS_2023-03-25_final
2023-03-25 09:33:55	ga_s2am_ard_3-2-1_56JLS_2023-03-25_final
2023-03-25 09:33:59	ga_s2am_ard_3-2-1_55JHM_2023-03-25_final
2023-03-25 09:33:59	ga_s2am_ard_3-2-1_56JKS_2023-03-25_final
2023-03-28 11:24:24	ga_s2am_ard_3-2-1_51JXN_2023-03-28_final
2023-03-28 11:24:27	ga_s2am_ard_3-2-1_51JWN_2023-03-28_final
2023-03-28 11:24:30	ga_s2am_ard_3-2-1_51JZM_2023-03-28_final
2023-03-28 11:24:30	ga_s2am_ard_3-2-1_52JBS_2023-03-28_final
2023-03-28 11:24:35	ga_s2am_ard_3-2-1_51JYM_2023-03-28_final
2023-03-28 11:24:39	ga_s2am_ard_3-2-1_51JXM_2023-03-28_final
2023-03-28 11:24:42	ga_s2am_ard_3-2-1_51JWM_2023-03-28_final
2023-04-01 09:23:35	ga_s2am_ard_3-2-1_56JPT_2023-03-31_nrt
2023-04-01 09:23:38	ga_s2am_ard_3-2-1_56JNT_2023-03-31_final
2023-04-01 09:23:50	ga_s2am_ard_3-2-1_56JPS_2023-03-31_nrt

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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