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
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50KPC_2016-02-02_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50HPH_2016-07-08_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_50JQM_2016-07-08_final.stac-item
2016-08-21 11:26:11	ga_s2am_ard_3-2-1_51JUF_2016-08-21_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_49JGN_2016-08-23_final.stac-item
2016-08-30 11:48:30	ga_s2am_ard_3-2-1_50JLM_2016-08-30_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51KUT_2016-11-12_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_51KUT_2017-01-01_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_51JZM_2017-01-25_final.stac-item
2017-06-20 11:34:58	ga_s2am_ard_3-2-1_51HTC_2017-06-20_final.stac-item
2017-12-30 11:42:34	ga_s2am_ard_3-2-1_51KTS_2017-12-30_final.stac-item
2018-01-20 11:11:55	ga_s2am_ard_3-2-1_51HXD_2018-01-20_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50KQU_2018-03-20_final.stac-item
2018-04-12 11:53:08	ga_s2am_ard_3-2-1_50JLM_2018-04-12_final
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_50KKB_2018-04-15_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51JWN_2018-04-23_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50HLK_2018-05-22_final.stac-item
2018-05-29 11:44:48	ga_s2am_ard_3-2-1_50HNH_2018-05-29_final.stac-item
2018-06-04 12:03:37	ga_s2am_ard_3-2-1_50KKB_2018-06-04_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_51HTC_2018-07-15_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JKM_2018-09-02_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JQM_2018-09-06_final.stac-item
2018-10-29 11:49:24	ga_s2am_ard_3-2-1_50KMC_2018-10-29_final.stac-item
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_51JTM_2018-11-05_final.stac-item
2018-11-18 11:56:05	ga_s2am_ard_3-2-1_50JLM_2018-11-18_final.stac-item
2019-02-09 12:04:36	ga_s2am_ard_3-2-1_50JLT_2019-02-09_final.stac-item
2019-02-19 12:03:37	ga_s2am_ard_3-2-1_50KLB_2019-02-19_final.stac-item
2019-03-04 12:13:49	ga_s2am_ard_3-2-1_50KKA_2019-03-04_final.stac-item
2019-03-05 11:43:13	ga_s2am_ard_3-2-1_50KRC_2019-03-05_final.stac-item
2019-06-03 11:43:21	ga_s2am_ard_3-2-1_50KRC_2019-06-03_final.stac-item
2019-06-20 11:36:47	ga_s2am_ard_3-2-1_51HUD_2019-06-20_final.stac-item
2019-06-29 12:04:29	ga_s2am_ard_3-2-1_50KLU_2019-06-29_final.stac-item
2019-07-10 11:36:39	ga_s2am_ard_3-2-1_50HQK_2019-07-10_final.stac-item
2019-07-13 11:43:23	ga_s2am_ard_3-2-1_50KRC_2019-07-13_final.stac-item
2019-08-09 11:36:18	ga_s2am_ard_3-2-1_51JUF_2019-08-09_final.stac-item
2019-10-11 11:43:21	ga_s2am_ard_3-2-1_50KRC_2019-10-11_final.stac-item
2019-10-18 11:37:04	ga_s2am_ard_3-2-1_51HTC_2019-10-18_final.stac-item
2019-10-20 12:14:04	ga_s2am_ard_3-2-1_49KGR_2019-10-20_final.stac-item
2020-01-13 11:25:36	ga_s2am_ard_3-2-1_51JWH_2020-01-13_final.stac-item
2020-02-18 11:43:45	ga_s2am_ard_3-2-1_50KQA_2020-02-18_final.stac-item
2020-04-05 11:35:56	ga_s2am_ard_3-2-1_51JUG_2020-04-05_final.stac-item
2020-04-22 11:27:03	ga_s2am_ard_3-2-1_51HUC_2020-04-22_final.stac-item
2020-05-04 12:04:17	ga_s2am_ard_3-2-1_50KKV_2020-05-04_final.stac-item
2020-09-01 12:04:18	ga_s2am_ard_3-2-1_50KKV_2020-09-01_final.stac-item
2020-10-31 12:03:25	ga_s2am_ard_3-2-1_50KNC_2020-10-31_final.stac-item
2020-10-31 12:05:02	ga_s2am_ard_3-2-1_50JKS_2020-10-31_final.stac-item
2021-01-09 12:05:01	ga_s2am_ard_3-2-1_49JGM_2021-01-09_final.stac-item
2021-02-18 12:04:27	ga_s2am_ard_3-2-1_49KHP_2021-02-18_final.stac-item
2021-03-27 11:55:57	ga_s2am_ard_3-2-1_50JKN_2021-03-27_final.stac-item
2021-04-10 11:36:44	ga_s2am_ard_3-2-1_50HQJ_2021-04-10_final.stac-item
2021-04-22 12:14:22	ga_s2am_ard_3-2-1_49KGP_2021-04-22_final.stac-item
2021-04-30 11:35:34	ga_s2am_ard_3-2-1_50JQP_2021-04-30_final.stac-item
2021-05-13 11:46:19	ga_s2am_ard_3-2-1_50JPL_2021-05-13_final.stac-item
2021-05-17 11:25:42	ga_s2am_ard_3-2-1_51JWH_2021-05-17_final.stac-item
2021-06-13 11:15:43	ga_s2am_ard_3-2-1_51JXH_2021-06-13_final.stac-item
2021-06-26 11:27:03	ga_s2am_ard_3-2-1_51HUC_2021-06-26_final.stac-item
2021-07-15 11:52:37	ga_s2am_ard_3-2-1_50KQF_2021-07-15_final
2021-07-18 12:03:47	ga_s2am_ard_3-2-1_50KKB_2021-07-18_final.stac-item
2021-08-01 11:44:01	ga_s2am_ard_3-2-1_51KUQ_2021-08-01_final.stac-item
2021-08-31 11:47:18	ga_s2am_ard_3-2-1_50HPG_2021-08-31_final
2021-09-03 11:56:31	ga_s2am_ard_3-2-1_50HNK_2021-09-03_final.stac-item
2021-11-22 11:52:34	ga_s2am_ard_3-2-1_50KQF_2021-11-22_final
2021-11-23 11:26:00	ga_s2am_ard_3-2-1_51JVG_2021-11-23_final.stac-item
2021-11-26 11:33:22	ga_s2am_ard_3-2-1_51KUT_2021-11-26_final.stac-item
2021-12-12 11:53:10	ga_s2am_ard_3-2-1_50KRC_2021-12-12_final.stac-item
2022-01-08 11:44:14	ga_s2am_ard_3-2-1_51KUP_2022-01-08_final.stac-item
2022-01-24 12:05:55	ga_s2am_ard_3-2-1_50JKN_2022-01-24_final.stac-item
2022-01-28 11:43:18	ga_s2am_ard_3-2-1_50KRC_2022-01-28_final.stac-item
2022-03-10 11:14:27	ga_s2am_ard_3-2-1_51JZN_2022-03-10_final.stac-item
2022-03-23 11:26:30	ga_s2am_ard_3-2-1_51HVE_2022-03-23_final.stac-item
2022-03-26 11:33:51	ga_s2am_ard_3-2-1_51KUR_2022-03-26_final.stac-item
2022-04-04 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-04-04_final.stac-item
2022-04-12 11:25:08	ga_s2am_ard_3-2-1_51JYK_2022-04-12_final.stac-item
2022-05-01 11:54:01	ga_s2am_ard_3-2-1_50KMA_2022-05-01_final.stac-item
2022-06-04 11:37:14	ga_s2am_ard_3-2-1_50HPH_2022-06-04_final.stac-item
2022-07-17 11:46:06	ga_s2am_ard_3-2-1_50JNN_2022-07-17_final.stac-item
2022-07-30 11:53:20	ga_s2am_ard_3-2-1_50KRC_2022-07-30_final.stac-item
2022-08-03 11:37:17	ga_s2am_ard_3-2-1_50HPH_2022-08-03_final.stac-item
2022-09-05 11:43:16	ga_s2am_ard_3-2-1_50KRD_2022-09-05_final.stac-item
2022-09-14 12:14:08	ga_s2am_ard_3-2-1_49KGR_2022-09-14_final.stac-item
2022-09-19 11:25:03	ga_s2am_ard_3-2-1_51JXL_2022-09-19_final.stac-item
2022-09-25 11:46:55	ga_s2am_ard_3-2-1_50HPJ_2022-09-25_final.stac-item
2023-01-09 12:03:57	ga_s2am_ard_3-2-1_50KKA_2023-01-09_final.stac-item
2023-01-23 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2023-01-23_final.stac-item
2023-02-15 11:53:28	ga_s2am_ard_3-2-1_50KMC_2023-02-15_nrt.stac-item
2023-03-11 11:33:29	ga_s2am_ard_3-2-1_51KUS_2023-03-11_final
2023-04-10 11:34:43	ga_s2am_ard_3-2-1_51JVM_2023-04-10_final
2023-04-12 12:13:54	ga_s2am_ard_3-2-1_50KKA_2023-04-12_final
2023-05-13 11:43:04	ga_s2am_ard_3-2-1_50KRD_2023-05-13_final
2023-05-24 11:14:26	ga_s2am_ard_3-2-1_51JZN_2023-05-24_final
2023-07-21 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-07-21_final
2023-11-22 11:55:49	ga_s2am_ard_3-2-1_50JMN_2023-11-22_final
2023-12-09 11:44:00	ga_s2am_ard_3-2-1_50KQV_2023-12-09_final
2024-02-08 11:15:06	ga_s2am_ard_3-2-1_51JYK_2024-02-08_final
2024-02-13 12:05:51	ga_s2am_ard_3-2-1_50JLN_2024-02-13_final
2024-02-26 12:14:18	ga_s2am_ard_3-2-1_49KGP_2024-02-26_final
2024-03-05 11:36:00	ga_s2am_ard_3-2-1_51JUG_2024-03-05_final
2024-03-15 11:34:39	ga_s2am_ard_3-2-1_51JWM_2024-03-15_final
2024-03-17 12:13:55	ga_s2am_ard_3-2-1_49KHR_2024-03-17_final
2024-03-18 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2024-03-18_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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