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
2015-12-03 10:41:05	ga_s2am_ard_3-2-1_53KRV_2015-12-03_final.stac-item
2015-12-07 10:22:23	ga_s2am_ard_3-2-1_53JQK_2015-12-07_final.stac-item
2016-05-01 10:43:19	ga_s2am_ard_3-2-1_53JPL_2016-05-01_final.stac-item
2016-05-04 10:47:30	ga_s2am_ard_3-2-1_53KLA_2016-05-04_final.stac-item
2016-08-16 10:28:09	ga_s2am_ard_3-2-1_54JTT_2016-08-16_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_51HUE_2016-09-13_final.stac-item
2016-12-30 10:48:09	ga_s2am_ard_3-2-1_53LMF_2016-12-30_final.stac-item
2017-04-10 10:23:05	ga_s2am_ard_3-2-1_54HTJ_2017-04-10_final.stac-item
2017-05-23 10:32:14	ga_s2am_ard_3-2-1_53JQL_2017-05-23_final.stac-item
2017-06-20 11:28:36	ga_s2am_ard_3-2-1_51KWA_2017-06-20_final.stac-item
2017-08-31 12:14:41	ga_s2am_ard_3-2-1_49JFM_2017-08-31_final.stac-item
2017-09-23 10:43:02	ga_s2am_ard_3-2-1_53JNN_2017-09-23_final.stac-item
2018-03-29 10:30:36	ga_s2am_ard_3-2-1_53HNB_2018-03-29_final.stac-item
2018-03-29 10:30:36	ga_s2am_ard_3-2-1_54KVF_2018-03-29_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_51KVT_2018-05-16_final.stac-item
2018-05-18 10:27:10	ga_s2am_ard_3-2-1_54JTT_2018-05-18_final.stac-item
2018-07-07 10:27:09	ga_s2am_ard_3-2-1_54KTV_2018-07-07_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50HLK_2018-07-21_final.stac-item
2018-08-26 10:27:07	ga_s2am_ard_3-2-1_54JUT_2018-08-26_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_50HPJ_2018-10-13_final.stac-item
2018-12-25 11:41:25	ga_s2am_ard_3-2-1_51LUE_2018-12-25_final.stac-item
2019-01-13 10:33:48	ga_s2am_ard_3-2-1_53KPP_2019-01-13_final.stac-item
2019-01-26 10:44:03	ga_s2am_ard_3-2-1_53JNN_2019-01-26_final.stac-item
2019-02-13 11:42:10	ga_s2am_ard_3-2-1_51KVB_2019-02-13_final.stac-item
2019-02-15 10:43:44	ga_s2am_ard_3-2-1_53KPP_2019-02-15_final.stac-item
2019-02-25 10:44:02	ga_s2am_ard_3-2-1_53JNN_2019-02-25_final.stac-item
2019-03-04 10:33:54	ga_s2am_ard_3-2-1_53JRN_2019-03-04_final.stac-item
2019-03-24 10:34:17	ga_s2am_ard_3-2-1_53JQM_2019-03-24_final.stac-item
2019-05-01 09:56:43	ga_s2am_ard_3-2-1_54HYG_2019-05-01_final.stac-item
2019-08-11 10:34:36	ga_s2am_ard_3-2-1_53JQL_2019-08-11_final.stac-item
2019-10-31 11:47:10	ga_s2am_ard_3-2-1_50HNH_2019-10-31_final.stac-item
2019-11-06 10:24:36	ga_s2am_ard_3-2-1_54JTR_2019-11-06_final.stac-item
2019-11-07 11:33:37	ga_s2am_ard_3-2-1_51KUS_2019-11-07_final.stac-item
2020-01-29 11:43:18	ga_s2am_ard_3-2-1_51KVS_2020-01-29_final.stac-item
2020-02-27 10:34:13	ga_s2am_ard_3-2-1_53JQM_2020-02-27_final.stac-item
2020-03-05 10:24:37	ga_s2am_ard_3-2-1_54JVQ_2020-03-05_final.stac-item
2020-03-08 10:34:00	ga_s2am_ard_3-2-1_53JQN_2020-03-08_final.stac-item
2020-03-25 10:25:32	ga_s2am_ard_3-2-1_54JVL_2020-03-25_final.stac-item
2020-04-07 10:33:46	ga_s2am_ard_3-2-1_53KQP_2020-04-07_final.stac-item
2020-05-28 11:43:21	ga_s2am_ard_3-2-1_51KUT_2020-05-28_final.stac-item
2020-06-14 11:33:22	ga_s2am_ard_3-2-1_51KVT_2020-06-14_final.stac-item
2020-06-26 10:33:57	ga_s2am_ard_3-2-1_54JUT_2020-06-26_final.stac-item
2020-07-04 11:33:35	ga_s2am_ard_3-2-1_51KVS_2020-07-04_final.stac-item
2020-07-29 10:46:11	ga_s2am_ard_3-2-1_53HME_2020-07-29_final.stac-item
2020-08-22 10:26:56	ga_s2am_ard_3-2-1_53HPB_2020-08-22_final.stac-item
2020-09-14 10:34:37	ga_s2am_ard_3-2-1_53JQL_2020-09-14_final.stac-item
2020-10-09 11:21:38	ga_s2am_ard_3-2-1_52LDJ_2020-10-09_final.stac-item
2020-10-24 10:33:58	ga_s2am_ard_3-2-1_53KPP_2020-10-24_final.stac-item
2020-10-24 10:35:57	ga_s2am_ard_3-2-1_53JNF_2020-10-24_final.stac-item
2020-11-26 10:41:35	ga_s2am_ard_3-2-1_53LQC_2020-11-26_final
2020-12-05 11:10:23	ga_s2am_ard_3-2-1_52LHN_2020-12-05_final.stac-item
2020-12-12 11:00:41	ga_s2am_ard_3-2-1_52LHM_2020-12-12_final.stac-item
2020-12-15 11:10:30	ga_s2am_ard_3-2-1_52LFN_2020-12-15_final
2020-12-30 10:26:30	ga_s2am_ard_3-2-1_54HTH_2020-12-30_final.stac-item
2021-01-19 10:27:02	ga_s2am_ard_3-2-1_53HQA_2021-01-19_final.stac-item
2021-04-30 11:33:13	ga_s2am_ard_3-2-1_51KVT_2021-04-30_final.stac-item
2021-05-30 11:32:15	ga_s2am_ard_3-2-1_51KWB_2021-05-30_final.stac-item
2021-06-25 10:17:16	ga_s2am_ard_3-2-1_54HUE_2021-06-25_final
2021-07-14 10:41:12	ga_s2am_ard_3-2-1_53LPE_2021-07-14_final.stac-item
2021-08-23 10:41:44	ga_s2am_ard_3-2-1_53LNC_2021-08-23_final.stac-item
2021-08-30 10:35:03	ga_s2am_ard_3-2-1_53JQJ_2021-08-30_final.stac-item
2021-10-01 11:15:52	ga_s2am_ard_3-2-1_52JCM_2021-10-01_final.stac-item
2021-10-19 10:35:06	ga_s2am_ard_3-2-1_53JQJ_2021-10-19_final.stac-item
2021-12-06 11:37:02	ga_s2am_ard_3-2-1_50HQH_2021-12-06_final.stac-item
2022-02-08 11:14:08	ga_s2am_ard_3-2-1_52KBU_2022-02-08_final.stac-item
2022-02-25 11:01:00	ga_s2am_ard_3-2-1_53LKF_2022-02-25_final.stac-item
2022-04-24 10:22:06	ga_s2am_ard_3-2-1_54KVF_2022-04-24_final.stac-item
2022-05-17 10:34:05	ga_s2am_ard_3-2-1_54JTT_2022-05-17_final.stac-item
2022-06-02 10:53:36	ga_s2am_ard_3-2-1_53KKR_2022-06-02_final.stac-item
2022-06-16 10:34:43	ga_s2am_ard_3-2-1_53JQL_2022-06-16_final.stac-item
2022-07-03 10:24:53	ga_s2am_ard_3-2-1_53JQL_2022-07-03_final.stac-item
2022-07-14 11:36:12	ga_s2am_ard_3-2-1_51JUG_2022-07-14_final.stac-item
2022-07-26 10:34:24	ga_s2am_ard_3-2-1_53JRM_2022-07-26_final.stac-item
2022-09-06 11:16:23	ga_s2am_ard_3-2-1_51JXF_2022-09-06_final.stac-item
2022-09-22 11:32:26	ga_s2am_ard_3-2-1_51KVB_2022-09-22_final.stac-item
2022-10-11 12:05:03	ga_s2am_ard_3-2-1_50JKS_2022-10-11_final.stac-item
2022-12-28 11:21:39	ga_s2am_ard_3-2-1_51LZD_2022-12-28_final.stac-item
2023-01-02 10:33:30	ga_s2am_ard_3-2-1_54KTV_2023-01-02_final.stac-item
2023-01-22 10:33:59	ga_s2am_ard_3-2-1_53JQN_2023-01-22_final.stac-item
2023-04-14 11:12:32	ga_s2am_ard_3-2-1_52KEE_2023-04-14_final
2023-04-29 10:24:19	ga_s2am_ard_3-2-1_54JTS_2023-04-29_final
2023-05-03 10:07:16	ga_s2am_ard_3-2-1_54HVE_2023-05-03_final
2023-05-09 10:26:53	ga_s2am_ard_3-2-1_53HNB_2023-05-09_final
2023-06-11 10:33:49	ga_s2am_ard_3-2-1_54KTU_2023-06-11_final
2023-07-03 11:12:40	ga_s2am_ard_3-2-1_52KDE_2023-07-03_final
2023-07-12 10:06:55	ga_s2am_ard_3-2-1_54HYF_2023-07-12_final
2023-07-16 11:24:07	ga_s2am_ard_3-2-1_51KWQ_2023-07-16_final
2023-07-24 10:45:56	ga_s2am_ard_3-2-1_53JMF_2023-07-24_final
2023-08-07 10:25:40	ga_s2am_ard_3-2-1_54JUL_2023-08-07_final
2023-09-16 10:26:36	ga_s2am_ard_3-2-1_53HQC_2023-09-16_final
2023-10-11 11:10:42	ga_s2am_ard_3-2-1_52LGM_2023-10-11_final
2023-10-11 11:16:57	ga_s2am_ard_3-2-1_51HWC_2023-10-11_final
2023-12-18 10:33:41	ga_s2am_ard_3-2-1_53KRP_2023-12-18_final
2024-01-20 10:43:58	ga_s2am_ard_3-2-1_53JNN_2024-01-20_final
2024-01-23 10:52:20	ga_s2am_ard_3-2-1_53KLV_2024-01-23_final
2024-03-16 11:01:17	ga_s2am_ard_3-2-1_52LGK_2024-03-16_final
2024-03-18 11:42:46	ga_s2am_ard_3-2-1_51KUV_2024-03-18_final
2024-03-19 11:11:17	ga_s2am_ard_3-2-1_52LFK_2024-03-19_final
2024-03-25 11:32:41	ga_s2am_ard_3-2-1_51KXV_2024-03-25_final
2024-04-06 10:31:48	ga_s2am_ard_3-2-1_53KRB_2024-04-06_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