Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JKT_2016-03-16_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50KKU_2016-03-16_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50JKT_2016-04-15_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50KKU_2016-04-15_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_49KHP_2016-05-15_final.stac-item
2016-09-19 11:48:24	ga_s2am_ard_3-2-1_50KNA_2016-09-19_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50KLU_2016-10-02_final.stac-item
2016-10-22 12:02:45	ga_s2am_ard_3-2-1_49JHN_2016-10-22_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JHN_2016-11-01_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50KKU_2016-11-21_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49KHP_2016-12-31_final
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50JKT_2017-03-31_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50JLT_2017-07-09_final
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50KLU_2017-09-27_final
2017-10-24 11:52:38	ga_s2am_ard_3-2-1_50JMR_2017-10-24_final
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JMS_2017-12-03_final
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_50JKT_2017-12-16_final
2018-02-24 12:02:46	ga_s2am_ard_3-2-1_50KLV_2018-02-24_final
2018-03-09 12:13:17	ga_s2am_ard_3-2-1_49JFM_2018-03-09_final
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_50JKT_2018-03-16_final
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50JKT_2018-03-26_final
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50KKU_2018-03-26_final
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50JNT_2018-05-22_final
2018-06-07 12:13:28	ga_s2am_ard_3-2-1_49KGR_2018-06-07_final
2018-07-11 11:51:05	ga_s2am_ard_3-2-1_50KNA_2018-07-11_final
2018-08-13 12:04:05	ga_s2am_ard_3-2-1_49KHP_2018-08-13_final
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50JLT_2018-08-23_final
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JLT_2018-09-02_final
2018-12-11 12:04:34	ga_s2am_ard_3-2-1_50JKT_2018-12-11_final
2019-02-09 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-02-09_final
2019-03-01 12:04:38	ga_s2am_ard_3-2-1_50JKT_2019-03-01_final
2019-04-30 12:04:31	ga_s2am_ard_3-2-1_49KHP_2019-04-30_final
2019-05-13 12:15:03	ga_s2am_ard_3-2-1_49JFM_2019-05-13_final
2019-06-23 11:46:23	ga_s2am_ard_3-2-1_50JPL_2019-06-23_final
2019-07-29 12:04:44	ga_s2am_ard_3-2-1_50JLT_2019-07-29_final
2019-08-08 12:04:32	ga_s2am_ard_3-2-1_50KKU_2019-08-08_final
2019-08-08 12:04:46	ga_s2am_ard_3-2-1_50JKT_2019-08-08_final
2019-09-07 12:03:55	ga_s2am_ard_3-2-1_50KLA_2019-09-07_final
2019-10-01 11:44:36	ga_s2am_ard_3-2-1_50JQT_2019-10-01_final
2019-10-27 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-10-27_final
2019-11-06 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-11-06_final
2019-12-13 11:54:33	ga_s2am_ard_3-2-1_50JNT_2019-12-13_final
2020-01-25 12:04:32	ga_s2am_ard_3-2-1_50JLT_2020-01-25_final
2020-01-25 12:04:36	ga_s2am_ard_3-2-1_49JHN_2020-01-25_final
2020-02-14 12:04:36	ga_s2am_ard_3-2-1_49JHN_2020-02-14_final
2020-02-24 12:04:37	ga_s2am_ard_3-2-1_49JHN_2020-02-24_final
2020-04-28 11:44:37	ga_s2am_ard_3-2-1_50JQT_2020-04-28_final
2020-05-21 11:55:15	ga_s2am_ard_3-2-1_50JMR_2020-05-21_final
2020-07-20 11:55:15	ga_s2am_ard_3-2-1_50JMR_2020-07-20_final
2020-07-20 11:55:29	ga_s2am_ard_3-2-1_50JMQ_2020-07-20_final
2020-09-11 12:04:46	ga_s2am_ard_3-2-1_49JHN_2020-09-11_final
2020-10-01 12:04:45	ga_s2am_ard_3-2-1_50JLT_2020-10-01_final
2020-10-11 12:04:45	ga_s2am_ard_3-2-1_50JLT_2020-10-11_final
2020-10-21 12:04:45	ga_s2am_ard_3-2-1_50JLT_2020-10-21_final
2020-11-30 12:04:25	ga_s2am_ard_3-2-1_50KLU_2020-11-30_final
2020-11-30 12:04:42	ga_s2am_ard_3-2-1_49JHN_2020-11-30_final
2020-12-07 11:54:35	ga_s2am_ard_3-2-1_50JNT_2020-12-07_final
2020-12-24 11:45:02	ga_s2am_ard_3-2-1_50JQR_2020-12-24_final
2021-01-29 12:04:43	ga_s2am_ard_3-2-1_49JHN_2021-01-29_final
2021-03-20 12:04:38	ga_s2am_ard_3-2-1_50JLT_2021-03-20_final
2021-04-16 11:53:33	ga_s2am_ard_3-2-1_50KNB_2021-04-16_final
2021-07-02 11:45:05	ga_s2am_ard_3-2-1_50JQR_2021-07-02_final
2021-08-27 12:04:44	ga_s2am_ard_3-2-1_49JHN_2021-08-27_final
2021-09-30 11:45:08	ga_s2am_ard_3-2-1_50JQR_2021-09-30_final
2021-10-13 11:54:42	ga_s2am_ard_3-2-1_50JNT_2021-10-13_final
2021-10-30 11:45:22	ga_s2am_ard_3-2-1_50JQQ_2021-10-30_final
2021-12-09 11:45:16	ga_s2am_ard_3-2-1_50JQQ_2021-12-09_final
2021-12-19 11:45:18	ga_s2am_ard_3-2-1_50JQQ_2021-12-19_final
2021-12-25 12:04:41	ga_s2am_ard_3-2-1_50JLT_2021-12-25_final
2021-12-25 12:04:44	ga_s2am_ard_3-2-1_50JKT_2021-12-25_final
2022-01-18 11:45:18	ga_s2am_ard_3-2-1_50JQQ_2022-01-18_final
2022-01-24 12:04:43	ga_s2am_ard_3-2-1_50JKT_2022-01-24_final
2022-04-14 12:03:58	ga_s2am_ard_3-2-1_50KLA_2022-04-14_final
2022-05-28 11:44:42	ga_s2am_ard_3-2-1_50JQT_2022-05-28_final
2022-06-27 11:45:49	ga_s2am_ard_3-2-1_50JPP_2022-06-27_final
2022-07-26 12:15:10	ga_s2am_ard_3-2-1_49JFM_2022-07-26_final
2022-10-01 12:05:36	ga_s2am_ard_3-2-1_49JGK_2022-10-01_final.stac-item
2022-10-31 12:04:43	ga_s2am_ard_3-2-1_50JLT_2022-10-31_final.stac-item
2022-11-20 12:04:29	ga_s2am_ard_3-2-1_50KKU_2022-11-20_final.stac-item
2022-12-07 11:55:24	ga_s2am_ard_3-2-1_50JMQ_2022-12-07_final.stac-item
2023-01-09 12:04:12	ga_s2am_ard_3-2-1_50KKV_2023-01-09_final.stac-item
2023-02-08 12:04:38	ga_s2am_ard_3-2-1_50JLT_2023-02-08_final.stac-item
2023-02-15 11:54:34	ga_s2am_ard_3-2-1_50JNT_2023-02-15_final.stac-item
2023-02-15 11:55:07	ga_s2am_ard_3-2-1_50JMR_2023-02-15_final.stac-item
2023-03-07 11:55:05	ga_s2am_ard_3-2-1_50JMR_2023-03-07_final.stac-item
2023-04-09 12:04:42	ga_s2am_ard_3-2-1_49JHN_2023-04-09_final.stac-item
2023-04-22 12:14:58	ga_s2am_ard_3-2-1_49JFM_2023-04-22_final.stac-item
2023-05-12 12:14:15	ga_s2am_ard_3-2-1_49KFQ_2023-05-12_nrt.stac-item
2023-05-19 12:04:30	ga_s2am_ard_3-2-1_50KKU_2023-05-19_final.stac-item
2023-08-27 12:04:34	ga_s2am_ard_3-2-1_49KHP_2023-08-27_final.stac-item
2023-08-30 12:14:36	ga_s2am_ard_3-2-1_49KFP_2023-08-30_nrt.stac-item
2023-08-30 12:15:05	ga_s2am_ard_3-2-1_49JFM_2023-08-30_final.stac-item
2023-08-31 11:45:23	ga_s2am_ard_3-2-1_50JQQ_2023-08-31_final.stac-item
2023-10-16 12:04:24	ga_s2am_ard_3-2-1_50KLU_2023-10-16_final.stac-item
2023-10-16 12:04:38	ga_s2am_ard_3-2-1_50JLT_2023-10-16_final.stac-item
2023-10-23 11:54:40	ga_s2am_ard_3-2-1_50JMT_2023-10-23_final.stac-item
2023-11-02 11:53:52	ga_s2am_ard_3-2-1_50KNA_2023-11-02_final.stac-item
2023-12-19 11:45:14	ga_s2am_ard_3-2-1_50JQQ_2023-12-19_final.stac-item
2023-12-25 12:04:21	ga_s2am_ard_3-2-1_50KLU_2023-12-25_final.stac-item
2024-02-13 12:04:22	ga_s2am_ard_3-2-1_50KLU_2024-02-13_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years