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
2015-08-01 11:04:34	ga_s2am_ard_3-2-1_52JCM_2015-08-01_final.stac-item
2015-12-05 11:26:08	ga_s2am_ard_3-2-1_51HWE_2015-12-05_final.stac-item
2016-01-29 10:30:47	ga_s2am_ard_3-2-1_53HLD_2016-01-29_final.stac-item
2016-09-05 10:28:01	ga_s2am_ard_3-2-1_53KPP_2016-09-05_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_51KTU_2016-09-06_final.stac-item
2016-09-12 10:26:34	ga_s2am_ard_3-2-1_54HTG_2016-09-12_final.stac-item
2016-09-24 11:00:36	ga_s2am_ard_3-2-1_52LGL_2016-09-24_final.stac-item
2017-02-19 10:23:19	ga_s2am_ard_3-2-1_54HTJ_2017-02-19_final
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HQJ_2017-05-24_final
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50KPA_2017-12-03_final
2017-12-11 11:11:56	ga_s2am_ard_3-2-1_52JCP_2017-12-11_final
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51KXU_2018-01-06_final
2018-01-07 10:57:08	ga_s2am_ard_3-2-1_52KFG_2018-01-07_final
2018-02-27 10:27:04	ga_s2am_ard_3-2-1_53KQU_2018-02-27_final
2018-03-09 10:27:04	ga_s2am_ard_3-2-1_53JRM_2018-03-09_final
2018-03-12 10:37:23	ga_s2am_ard_3-2-1_53KMU_2018-03-12_final
2018-04-02 10:07:04	ga_s2am_ard_3-2-1_54HTJ_2018-04-02_final
2018-05-04 10:47:27	ga_s2am_ard_3-2-1_53LNH_2018-05-04_final.stac-item
2018-06-07 10:27:08	ga_s2am_ard_3-2-1_53JPL_2018-06-07_final
2018-08-24 11:26:19	ga_s2am_ard_3-2-1_51KYT_2018-08-24_final
2018-09-05 10:27:05	ga_s2am_ard_3-2-1_53JPL_2018-09-05_final
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51HTC_2018-10-23_final
2018-11-22 11:32:48	ga_s2am_ard_3-2-1_51KXU_2018-11-22_final
2018-12-28 10:16:42	ga_s2am_ard_3-2-1_54HTG_2018-12-28_final
2019-01-31 11:32:51	ga_s2am_ard_3-2-1_51KXU_2019-01-31_final
2019-03-05 11:42:59	ga_s2am_ard_3-2-1_50KRD_2019-03-05_final
2019-06-17 11:23:44	ga_s2am_ard_3-2-1_51KYR_2019-06-17_final
2019-07-16 10:16:04	ga_s2am_ard_3-2-1_54HVK_2019-07-16_final
2019-09-05 11:22:59	ga_s2am_ard_3-2-1_51KYU_2019-09-05_final
2019-09-29 11:05:46	ga_s2am_ard_3-2-1_52JEM_2019-09-29_final
2019-12-18 11:02:20	ga_s2am_ard_3-2-1_52KHE_2019-12-18_final
2020-01-05 10:26:35	ga_s2am_ard_3-2-1_53HNC_2020-01-05_final
2020-01-16 11:32:49	ga_s2am_ard_3-2-1_51KXU_2020-01-16_final
2020-02-01 10:16:56	ga_s2am_ard_3-2-1_54HTF_2020-02-01_final
2020-02-02 11:22:53	ga_s2am_ard_3-2-1_51KXU_2020-02-02_final
2020-03-04 10:52:09	ga_s2am_ard_3-2-1_53KLA_2020-03-04_final
2020-04-06 11:01:29	ga_s2am_ard_3-2-1_52LGJ_2020-04-06_final
2020-04-06 11:05:24	ga_s2am_ard_3-2-1_52JCP_2020-04-06_final
2020-05-20 10:44:30	ga_s2am_ard_3-2-1_53JMM_2020-05-20_final
2020-05-20 10:44:48	ga_s2am_ard_3-2-1_53JLL_2020-05-20_final
2020-07-06 10:36:33	ga_s2am_ard_3-2-1_53HLD_2020-07-06_final
2020-10-07 10:46:04	ga_s2am_ard_3-2-1_53JKF_2020-10-07_final
2020-10-21 12:05:57	ga_s2am_ard_3-2-1_50JLN_2020-10-21_final
2021-01-09 12:05:09	ga_s2am_ard_3-2-1_49JFM_2021-01-09_final
2021-03-02 11:00:29	ga_s2am_ard_3-2-1_53LKH_2021-03-02_final
2021-03-04 11:45:14	ga_s2am_ard_3-2-1_51JTK_2021-03-04_final
2021-05-05 10:43:46	ga_s2am_ard_3-2-1_53KPP_2021-05-05_final
2021-05-27 11:23:36	ga_s2am_ard_3-2-1_52KBA_2021-05-27_final
2021-06-08 12:04:54	ga_s2am_ard_3-2-1_50JLS_2021-06-08_final
2021-07-31 10:34:07	ga_s2am_ard_3-2-1_53JQN_2021-07-31_final
2021-09-11 11:16:44	ga_s2am_ard_3-2-1_51HWD_2021-09-11_final
2021-10-03 10:17:08	ga_s2am_ard_3-2-1_54HWE_2021-10-03_final
2021-11-28 10:32:19	ga_s2am_ard_3-2-1_53KRV_2021-11-28_final
2021-12-16 11:32:55	ga_s2am_ard_3-2-1_51KXU_2021-12-16_final
2022-01-12 11:26:53	ga_s2am_ard_3-2-1_51HVC_2022-01-12_final
2022-01-24 10:25:05	ga_s2am_ard_3-2-1_53JQJ_2022-01-24_final
2022-01-29 11:10:37	ga_s2am_ard_3-2-1_52LHM_2022-01-29_final
2022-03-26 11:33:26	ga_s2am_ard_3-2-1_51KUT_2022-03-26_final
2022-06-07 11:43:33	ga_s2am_ard_3-2-1_51KVS_2022-06-07_final
2022-06-17 11:44:38	ga_s2am_ard_3-2-1_51JUN_2022-06-17_final
2022-06-24 09:58:18	ga_s2am_ard_3-2-1_54GYA_2022-06-24_final
2022-07-18 11:16:19	ga_s2am_ard_3-2-1_51JYF_2022-07-18_final
2022-07-24 09:58:16	ga_s2am_ard_3-2-1_54GYA_2022-07-24_final
2022-08-05 12:13:51	ga_s2am_ard_3-2-1_50KKB_2022-08-05_final
2022-08-23 11:37:13	ga_s2am_ard_3-2-1_51HTC_2022-08-23_final
2022-08-24 11:06:30	ga_s2am_ard_3-2-1_52HDK_2022-08-24_final.stac-item
2022-09-29 11:23:57	ga_s2am_ard_3-2-1_52KBV_2022-09-29_final.stac-item
2022-10-12 11:35:13	ga_s2am_ard_3-2-1_51JWK_2022-10-12_final.stac-item
2022-10-13 11:00:53	ga_s2am_ard_3-2-1_52LGM_2022-10-13_final.stac-item
2022-11-15 11:13:54	ga_s2am_ard_3-2-1_52KCV_2022-11-15_final.stac-item
2023-01-16 10:16:30	ga_s2am_ard_3-2-1_54HTH_2023-01-16_final.stac-item
2023-01-29 10:26:01	ga_s2am_ard_3-2-1_53HQE_2023-01-29_final.stac-item
2023-03-02 11:01:53	ga_s2am_ard_3-2-1_53KKB_2023-03-02_final.stac-item
2023-03-30 12:04:33	ga_s2am_ard_3-2-1_49KGP_2023-03-30_final.stac-item
2023-04-15 10:43:04	ga_s2am_ard_3-2-1_53KNS_2023-04-15_final.stac-item
2023-04-30 11:33:53	ga_s2am_ard_3-2-1_51KXQ_2023-04-30_final.stac-item
2023-05-14 11:16:32	ga_s2am_ard_3-2-1_51HXE_2023-05-14_final.stac-item
2023-05-20 11:33:44	ga_s2am_ard_3-2-1_51KWR_2023-05-20_final.stac-item
2023-05-30 11:33:27	ga_s2am_ard_3-2-1_51KXS_2023-05-30_final.stac-item
2023-05-30 11:37:01	ga_s2am_ard_3-2-1_51HUC_2023-05-30_final.stac-item
2023-06-01 10:34:17	ga_s2am_ard_3-2-1_53JNN_2023-06-01_final.stac-item
2023-07-06 11:21:37	ga_s2am_ard_3-2-1_52LDJ_2023-07-06_final.stac-item
2023-07-16 11:23:11	ga_s2am_ard_3-2-1_52KBC_2023-07-16_final.stac-item
2023-07-19 11:33:28	ga_s2am_ard_3-2-1_51KXS_2023-07-19_final.stac-item
2023-08-25 11:23:31	ga_s2am_ard_3-2-1_51KYS_2023-08-25_final.stac-item
2023-09-02 10:46:03	ga_s2am_ard_3-2-1_53JKF_2023-09-02_final.stac-item
2023-09-20 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2023-09-20_final.stac-item
2023-09-22 10:43:50	ga_s2am_ard_3-2-1_53KPP_2023-09-22_final.stac-item
2023-10-01 11:13:56	ga_s2am_ard_3-2-1_51KZQ_2023-10-01_final.stac-item
2023-10-06 10:24:41	ga_s2am_ard_3-2-1_53JQL_2023-10-06_final.stac-item
2023-11-16 11:33:43	ga_s2am_ard_3-2-1_51KVR_2023-11-16_final.stac-item
2023-11-17 11:05:29	ga_s2am_ard_3-2-1_52JEN_2023-11-17_final.stac-item
2023-12-16 11:33:09	ga_s2am_ard_3-2-1_51KWT_2023-12-16_final.stac-item
2024-01-03 10:52:30	ga_s2am_ard_3-2-1_53KNU_2024-01-03_final.stac-item
2024-01-03 10:54:59	ga_s2am_ard_3-2-1_52JFQ_2024-01-03_final.stac-item
2024-01-16 11:01:56	ga_s2am_ard_3-2-1_53KLA_2024-01-16_final.stac-item
2024-01-19 12:50:50	ga_s2am_ard_3-2-1_48LWP_2024-01-19_final.stac-item
2024-02-04 11:36:39	ga_s2am_ard_3-2-1_51HUD_2024-02-04_final.stac-item
2024-02-14 09:58:03	ga_s2am_ard_3-2-1_54GYA_2024-02-14_final.stac-item
2024-03-05 11:33:48	ga_s2am_ard_3-2-1_51KUR_2024-03-05_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