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
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JML_2015-12-04_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50LRH_2016-03-03_final
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JNS_2016-04-02_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50LQH_2016-09-19_final
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_49JHN_2016-10-02_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50KRA_2016-11-05_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KHP_2016-11-11_final.stac-item
2016-12-11 12:02:45	ga_s2am_ard_3-2-1_50KKU_2016-12-11_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51JUG_2016-12-12_final.stac-item
2016-12-16 11:08:59	ga_s2am_ard_3-2-1_51JZM_2016-12-16_final.stac-item
2017-01-15 11:08:52	ga_s2am_ard_3-2-1_51JYG_2017-01-15_final.stac-item
2017-01-31 11:34:46	ga_s2am_ard_3-2-1_51JUF_2017-01-31_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50KQG_2017-04-07_final
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50KNU_2017-08-05_final.stac-item
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_51KTS_2017-09-01_final.stac-item
2017-09-21 11:40:44	ga_s2am_ard_3-2-1_50KRV_2017-09-21_final.stac-item
2018-03-20 11:37:46	ga_s2am_ard_3-2-1_51KTS_2018-03-20_final.stac-item
2018-05-12 11:53:46	ga_s2am_ard_3-2-1_50KPV_2018-05-12_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_51KUT_2018-09-26_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JMS_2018-09-29_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JMT_2018-09-29_final.stac-item
2018-10-29 11:49:24	ga_s2am_ard_3-2-1_50JNT_2018-10-29_final.stac-item
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_51KTQ_2018-11-05_final.stac-item
2018-12-09 11:23:31	ga_s2am_ard_3-2-1_51KYR_2018-12-09_final.stac-item
2018-12-18 11:53:59	ga_s2am_ard_3-2-1_50KNV_2018-12-18_final.stac-item
2019-01-07 11:55:19	ga_s2am_ard_3-2-1_50JMQ_2019-01-07_final.stac-item
2019-01-28 11:24:08	ga_s2am_ard_3-2-1_51KXP_2019-01-28_final.stac-item
2019-02-17 11:24:52	ga_s2am_ard_3-2-1_51JXL_2019-02-17_final.stac-item
2019-03-12 11:34:42	ga_s2am_ard_3-2-1_51JUM_2019-03-12_final.stac-item
2019-06-06 11:56:42	ga_s2am_ard_3-2-1_50HLK_2019-06-06_final.stac-item
2019-06-27 11:24:31	ga_s2am_ard_3-2-1_51JXN_2019-06-27_final.stac-item
2019-09-01 11:43:48	ga_s2am_ard_3-2-1_51KTR_2019-09-01_final.stac-item
2019-09-05 11:24:37	ga_s2am_ard_3-2-1_51JYM_2019-09-05_final.stac-item
2019-09-28 11:34:30	ga_s2am_ard_3-2-1_51JVN_2019-09-28_final.stac-item
2019-10-01 11:43:49	ga_s2am_ard_3-2-1_51KTR_2019-10-01_final.stac-item
2019-10-17 12:04:46	ga_s2am_ard_3-2-1_50JKT_2019-10-17_final.stac-item
2019-10-27 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-10-27_final.stac-item
2019-11-06 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-11-06_final.stac-item
2019-12-04 11:24:53	ga_s2am_ard_3-2-1_51JXL_2019-12-04_final.stac-item
2019-12-13 11:55:05	ga_s2am_ard_3-2-1_50JMR_2019-12-13_final.stac-item
2019-12-21 11:15:48	ga_s2am_ard_3-2-1_51JYG_2019-12-21_final.stac-item
2020-01-02 11:55:01	ga_s2am_ard_3-2-1_50JNR_2020-01-02_final.stac-item
2020-01-12 11:54:46	ga_s2am_ard_3-2-1_50JNS_2020-01-12_final.stac-item
2020-01-23 11:23:33	ga_s2am_ard_3-2-1_51KYR_2020-01-23_final.stac-item
2020-01-23 11:24:30	ga_s2am_ard_3-2-1_51JYM_2020-01-23_final.stac-item
2020-02-01 11:55:16	ga_s2am_ard_3-2-1_50JMQ_2020-02-01_final.stac-item
2020-03-30 11:15:50	ga_s2am_ard_3-2-1_51JYG_2020-03-30_final.stac-item
2020-04-04 12:03:52	ga_s2am_ard_3-2-1_50KLA_2020-04-04_final.stac-item
2020-05-22 11:23:16	ga_s2am_ard_3-2-1_51KYT_2020-05-22_final.stac-item
2020-05-22 11:23:45	ga_s2am_ard_3-2-1_51KYR_2020-05-22_final.stac-item
2020-05-31 11:54:46	ga_s2am_ard_3-2-1_50JMT_2020-05-31_final.stac-item
2020-07-07 11:44:06	ga_s2am_ard_3-2-1_51KTQ_2020-07-07_final.stac-item
2020-07-27 11:44:22	ga_s2am_ard_3-2-1_51KTP_2020-07-27_final.stac-item
2020-07-30 11:54:28	ga_s2am_ard_3-2-1_50KNU_2020-07-30_final.stac-item
2020-07-30 11:54:46	ga_s2am_ard_3-2-1_50JMT_2020-07-30_final.stac-item
2020-08-22 12:05:20	ga_s2am_ard_3-2-1_49JGL_2020-08-22_final.stac-item
2020-08-23 11:35:07	ga_s2am_ard_3-2-1_51JUL_2020-08-23_final.stac-item
2020-08-26 11:44:07	ga_s2am_ard_3-2-1_51KTQ_2020-08-26_final.stac-item
2020-08-26 11:44:21	ga_s2am_ard_3-2-1_50KRU_2020-08-26_final.stac-item
2020-09-02 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-09-02_final.stac-item
2020-09-05 11:44:21	ga_s2am_ard_3-2-1_50KRU_2020-09-05_final.stac-item
2020-10-09 11:23:16	ga_s2am_ard_3-2-1_51KYT_2020-10-09_final.stac-item
2020-10-21 12:04:48	ga_s2am_ard_3-2-1_50JKT_2020-10-21_final.stac-item
2020-10-28 11:55:00	ga_s2am_ard_3-2-1_50JMS_2020-10-28_final.stac-item
2020-11-10 12:04:17	ga_s2am_ard_3-2-1_50KKV_2020-11-10_final.stac-item
2021-04-22 12:14:41	ga_s2am_ard_3-2-1_49JFN_2021-04-22_final.stac-item
2021-06-03 11:14:38	ga_s2am_ard_3-2-1_51JZM_2021-06-03_final.stac-item
2021-06-19 11:37:16	ga_s2am_ard_3-2-1_51HTB_2021-06-19_final
2021-08-31 11:43:34	ga_s2am_ard_3-2-1_50KRB_2021-08-31_final.stac-item
2021-09-10 11:44:02	ga_s2am_ard_3-2-1_51KTQ_2021-09-10_final.stac-item
2021-09-17 11:32:45	ga_s2am_ard_3-2-1_51KWV_2021-09-17_final.stac-item
2021-10-13 11:54:10	ga_s2am_ard_3-2-1_50KPV_2021-10-13_final.stac-item
2021-10-20 11:43:52	ga_s2am_ard_3-2-1_51KTR_2021-10-20_final.stac-item
2022-04-02 11:25:12	ga_s2am_ard_3-2-1_51JXK_2022-04-02_final.stac-item
2022-07-28 11:16:46	ga_s2am_ard_3-2-1_51HYD_2022-07-28_final.stac-item
2022-12-07 11:54:38	ga_s2am_ard_3-2-1_50JNT_2022-12-07_final.stac-item
2022-12-10 12:04:28	ga_s2am_ard_3-2-1_49KHP_2022-12-10_final.stac-item
2022-12-21 11:36:15	ga_s2am_ard_3-2-1_51JTF_2022-12-21_final.stac-item
2022-12-31 11:35:14	ga_s2am_ard_3-2-1_51JUK_2022-12-31_final.stac-item
2023-02-09 11:37:16	ga_s2am_ard_3-2-1_50HQG_2023-02-09_final
2023-03-04 11:45:14	ga_s2am_ard_3-2-1_50JQQ_2023-03-04_final
2023-03-08 11:24:32	ga_s2am_ard_3-2-1_51JYM_2023-03-08_final
2023-08-02 11:16:42	ga_s2am_ard_3-2-1_51HYD_2023-08-02_final
2023-08-07 12:04:00	ga_s2am_ard_3-2-1_50KLA_2023-08-07_final
2023-08-07 12:04:44	ga_s2am_ard_3-2-1_50JLT_2023-08-07_final
2023-08-11 11:43:52	ga_s2am_ard_3-2-1_50KRA_2023-08-11_final
2023-08-21 11:43:53	ga_s2am_ard_3-2-1_50KRA_2023-08-21_final
2023-08-25 11:23:45	ga_s2am_ard_3-2-1_51KYR_2023-08-25_final
2023-08-27 12:04:34	ga_s2am_ard_3-2-1_49KHP_2023-08-27_final
2023-09-26 12:03:14	ga_s2am_ard_3-2-1_50KLD_2023-09-26_nrt
2023-09-29 12:14:18	ga_s2am_ard_3-2-1_49KFQ_2023-09-29_nrt
2023-10-13 11:56:56	ga_s2am_ard_3-2-1_50HKJ_2023-10-13_nrt
2023-10-17 11:33:12	ga_s2am_ard_3-2-1_51KWT_2023-10-17_final
2023-10-19 12:13:47	ga_s2am_ard_3-2-1_49KFS_2023-10-19_nrt
2023-11-09 11:43:32	ga_s2am_ard_3-2-1_51KTS_2023-11-09_final
2023-12-03 11:24:15	ga_s2am_ard_3-2-1_51JYN_2023-12-03_final
2023-12-12 11:53:45	ga_s2am_ard_3-2-1_50KPA_2023-12-12_final
2023-12-12 11:54:47	ga_s2am_ard_3-2-1_50JNS_2023-12-12_final
2023-12-20 11:16:22	ga_s2am_ard_3-2-1_51HXE_2023-12-20_final
2023-12-23 11:24:04	ga_s2am_ard_3-2-1_51KYP_2023-12-23_final

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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