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
2015-11-30 10:30:39	ga_s2am_ard_3-2-1_53JPK_2015-11-30_final.stac-item
2015-12-19 11:04:17	ga_s2am_ard_3-2-1_52KGC_2015-12-19_final.stac-item
2015-12-21 10:06:32	ga_s2am_ard_3-2-1_54HWH_2015-12-21_final.stac-item
2015-12-26 10:54:12	ga_s2am_ard_3-2-1_52KHD_2015-12-26_final.stac-item
2016-01-15 10:56:39	ga_s2am_ard_3-2-1_52JGS_2016-01-15_final.stac-item
2016-04-06 11:25:50	ga_s2am_ard_3-2-1_51KVA_2016-04-06_final.stac-item
2016-04-11 10:43:06	ga_s2am_ard_3-2-1_53KNP_2016-04-11_final.stac-item
2016-05-08 10:34:29	ga_s2am_ard_3-2-1_53JQF_2016-05-08_final.stac-item
2016-06-17 10:34:26	ga_s2am_ard_3-2-1_53JMG_2016-06-17_final.stac-item
2016-07-24 12:03:52	ga_s2am_ard_3-2-1_50KLA_2016-07-24_final.stac-item
2016-07-26 11:02:15	ga_s2am_ard_3-2-1_52KFB_2016-07-26_final.stac-item
2016-12-10 10:47:57	ga_s2am_ard_3-2-1_53KNV_2016-12-10_final.stac-item
2017-01-12 11:02:04	ga_s2am_ard_3-2-1_52KFE_2017-01-12_final.stac-item
2017-01-14 11:34:53	ga_s2am_ard_3-2-1_50KQB_2017-01-14_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JKP_2017-01-30_final.stac-item
2017-04-22 10:57:17	ga_s2am_ard_3-2-1_52KHB_2017-04-22_final.stac-item
2017-05-03 12:14:44	ga_s2am_ard_3-2-1_49JFM_2017-05-03_final.stac-item
2017-11-19 10:28:06	ga_s2am_ard_3-2-1_53KQU_2017-11-19_final.stac-item
2017-12-13 10:16:51	ga_s2am_ard_3-2-1_53HQA_2017-12-13_final.stac-item
2017-12-22 10:43:02	ga_s2am_ard_3-2-1_53JNN_2017-12-22_final.stac-item
2018-01-05 12:05:28	ga_s2am_ard_3-2-1_50JKM_2018-01-05_final.stac-item
2018-01-24 10:52:15	ga_s2am_ard_3-2-1_53KLV_2018-01-24_final.stac-item
2018-01-27 10:57:11	ga_s2am_ard_3-2-1_52KGG_2018-01-27_final.stac-item
2018-01-30 11:12:10	ga_s2am_ard_3-2-1_52KDD_2018-01-30_final.stac-item
2018-02-15 09:51:52	ga_s2am_ard_3-2-1_54HXC_2018-02-15_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51JWK_2018-02-22_final.stac-item
2018-03-29 10:30:36	ga_s2am_ard_3-2-1_53JQM_2018-03-29_final.stac-item
2019-02-14 11:11:33	ga_s2am_ard_3-2-1_52LDJ_2019-02-14_final.stac-item
2019-04-11 11:34:01	ga_s2am_ard_3-2-1_51KVQ_2019-04-11_final.stac-item
2019-04-29 10:50:53	ga_s2am_ard_3-2-1_53LPF_2019-04-29_final.stac-item
2019-05-26 10:43:51	ga_s2am_ard_3-2-1_53KPP_2019-05-26_final.stac-item
2019-10-10 10:35:17	ga_s2am_ard_3-2-1_53JMJ_2019-10-10_final.stac-item
2019-11-13 10:16:59	ga_s2am_ard_3-2-1_54HVF_2019-11-13_final.stac-item
2019-11-13 10:17:13	ga_s2am_ard_3-2-1_54HVE_2019-11-13_final.stac-item
2020-01-21 10:41:35	ga_s2am_ard_3-2-1_53LNC_2020-01-21_final.stac-item
2020-01-25 10:26:23	ga_s2am_ard_3-2-1_54HTH_2020-01-25_final.stac-item
2020-02-11 10:16:57	ga_s2am_ard_3-2-1_53HQA_2020-02-11_final.stac-item
2020-03-12 11:53:47	ga_s2am_ard_3-2-1_50KQA_2020-03-12_final.stac-item
2020-03-20 11:13:20	ga_s2am_ard_3-2-1_52KDB_2020-03-20_final.stac-item
2020-04-24 10:26:42	ga_s2am_ard_3-2-1_53HNC_2020-04-24_final.stac-item
2020-05-14 10:26:55	ga_s2am_ard_3-2-1_53HPB_2020-05-14_final.stac-item
2020-08-22 12:05:35	ga_s2am_ard_3-2-1_49JGK_2020-08-22_final.stac-item
2020-09-17 10:44:07	ga_s2am_ard_3-2-1_53JPN_2020-09-17_final.stac-item
2020-10-17 10:45:31	ga_s2am_ard_3-2-1_53JLH_2020-10-17_final.stac-item
2020-11-25 11:14:42	ga_s2am_ard_3-2-1_51JYM_2020-11-25_final.stac-item
2021-02-03 11:16:20	ga_s2am_ard_3-2-1_52HBK_2021-02-03_final.stac-item
2021-02-05 10:17:10	ga_s2am_ard_3-2-1_54HVE_2021-02-05_final.stac-item
2021-02-20 11:02:03	ga_s2am_ard_3-2-1_53KLA_2021-02-20_final.stac-item
2021-03-14 11:43:18	ga_s2am_ard_3-2-1_50KRC_2021-03-14_final.stac-item
2021-05-22 10:34:14	ga_s2am_ard_3-2-1_53JRM_2021-05-22_final.stac-item
2021-05-24 11:14:09	ga_s2am_ard_3-2-1_52KBU_2021-05-24_final.stac-item
2021-06-13 11:13:30	ga_s2am_ard_3-2-1_52KEA_2021-06-13_final.stac-item
2021-07-21 10:34:21	ga_s2am_ard_3-2-1_53JQM_2021-07-21_final.stac-item
2021-07-28 10:27:08	ga_s2am_ard_3-2-1_53HPA_2021-07-28_final.stac-item
2021-09-22 10:43:51	ga_s2am_ard_3-2-1_53KPP_2021-09-22_final.stac-item
2021-10-12 10:44:08	ga_s2am_ard_3-2-1_53JPN_2021-10-12_final.stac-item
2021-12-15 10:25:05	ga_s2am_ard_3-2-1_53JQJ_2021-12-15_final.stac-item
2022-01-30 10:45:14	ga_s2am_ard_3-2-1_53JKJ_2022-01-30_final.stac-item
2022-02-01 11:22:27	ga_s2am_ard_3-2-1_51KYA_2022-02-01_final.stac-item
2022-02-08 11:13:53	ga_s2am_ard_3-2-1_52KBV_2022-02-08_final.stac-item
2022-02-25 11:00:31	ga_s2am_ard_3-2-1_53LKH_2022-02-25_final.stac-item
2022-04-28 11:44:07	ga_s2am_ard_3-2-1_50KRV_2022-04-28_final.stac-item
2022-05-21 10:16:01	ga_s2am_ard_3-2-1_54HWK_2022-05-21_final.stac-item
2022-05-30 10:43:41	ga_s2am_ard_3-2-1_53KPQ_2022-05-30_final.stac-item
2022-06-02 10:52:28	ga_s2am_ard_3-2-1_53KMV_2022-06-02_final.stac-item
2022-06-11 11:26:50	ga_s2am_ard_3-2-1_51HWD_2022-06-11_final.stac-item
2022-06-29 10:43:21	ga_s2am_ard_3-2-1_53KNS_2022-06-29_final.stac-item
2022-08-22 10:24:52	ga_s2am_ard_3-2-1_53JQL_2022-08-22_final.stac-item
2022-09-04 10:34:19	ga_s2am_ard_3-2-1_53JPN_2022-09-04_final.stac-item
2022-10-02 09:57:53	ga_s2am_ard_3-2-1_54HWC_2022-10-02_final.stac-item
2022-10-25 13:21:47	ga_s2am_ard_3-2-1_47LKG_2022-10-25_interim
2022-11-04 13:21:49	ga_s2am_ard_3-2-1_46LHM_2022-11-04_interim
2022-11-18 11:26:19	ga_s2am_ard_3-2-1_51JUF_2022-11-18_final.stac-item
2022-11-25 11:14:16	ga_s2am_ard_3-2-1_52JDT_2022-11-25_final.stac-item
2022-12-08 11:26:41	ga_s2am_ard_3-2-1_51HWD_2022-12-08_final.stac-item
2022-12-18 11:25:52	ga_s2am_ard_3-2-1_51JXG_2022-12-18_final.stac-item
2022-12-25 11:11:10	ga_s2am_ard_3-2-1_52LGK_2022-12-25_final
2022-12-26 10:42:59	ga_s2am_ard_3-2-1_53KQS_2022-12-26_final.stac-item
2023-01-08 10:54:31	ga_s2am_ard_3-2-1_52JFS_2023-01-08_final.stac-item
2023-01-31 11:02:42	ga_s2am_ard_3-2-1_52KGD_2023-01-31_final.stac-item
2023-02-26 11:21:48	ga_s2am_ard_3-2-1_52LCH_2023-02-26_final
2023-02-27 10:51:48	ga_s2am_ard_3-2-1_53KNB_2023-02-27_final
2023-03-11 09:56:53	ga_s2am_ard_3-2-1_54HXF_2023-03-11_final
2023-04-22 12:14:30	ga_s2am_ard_3-2-1_49KFP_2023-04-22_nrt
2023-05-02 10:33:38	ga_s2am_ard_3-2-1_53KPQ_2023-05-02_final
2023-05-12 10:36:58	ga_s2am_ard_3-2-1_53HPA_2023-05-12_final
2023-05-16 11:55:47	ga_s2am_ard_3-2-1_50JKP_2023-05-16_final
2023-05-30 11:37:06	ga_s2am_ard_3-2-1_50HQH_2023-05-30_final
2023-06-26 11:24:18	ga_s2am_ard_3-2-1_51KWP_2023-06-26_final
2023-06-30 11:02:30	ga_s2am_ard_3-2-1_52KHE_2023-06-30_final
2023-08-14 10:16:57	ga_s2am_ard_3-2-1_53HQB_2023-08-14_final
2023-09-20 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2023-09-20_final
2023-09-28 11:03:56	ga_s2am_ard_3-2-1_52KDV_2023-09-28_final
2023-12-25 10:26:24	ga_s2am_ard_3-2-1_54HUH_2023-12-25_final
2023-12-27 11:05:49	ga_s2am_ard_3-2-1_52JCM_2023-12-27_final
2024-01-14 10:26:26	ga_s2am_ard_3-2-1_53HQC_2024-01-14_final
2024-01-18 11:42:00	ga_s2am_ard_3-2-1_51KWB_2024-01-18_final
2024-01-22 11:22:59	ga_s2am_ard_3-2-1_52KBC_2024-01-22_final
2024-01-24 10:24:33	ga_s2am_ard_3-2-1_53JQL_2024-01-24_final
2024-02-14 11:32:53	ga_s2am_ard_3-2-1_51KYU_2024-02-14_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

All years