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
2015-10-28 11:59:52	ga_s2am_ard_3-2-1_50KKB_2015-10-28_final.stac-item
2016-01-23 11:56:39	ga_s2am_ard_3-2-1_50HLK_2016-01-23_final.stac-item
2016-03-24 11:21:55	ga_s2am_ard_3-2-1_51KXQ_2016-03-24_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_50HQK_2016-05-16_final.stac-item
2016-07-09 11:09:03	ga_s2am_ard_3-2-1_52JCS_2016-07-09_final.stac-item
2016-12-21 12:02:43	ga_s2am_ard_3-2-1_49KHR_2016-12-21_final.stac-item
2016-12-29 11:21:06	ga_s2am_ard_3-2-1_51KYU_2016-12-29_final.stac-item
2017-01-07 11:50:33	ga_s2am_ard_3-2-1_50JLM_2017-01-07_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50JKR_2017-01-30_final.stac-item
2017-04-15 11:12:01	ga_s2am_ard_3-2-1_52JDT_2017-04-15_final.stac-item
2017-07-11 11:02:59	ga_s2am_ard_3-2-1_52JFM_2017-07-11_final.stac-item
2017-07-17 11:20:58	ga_s2am_ard_3-2-1_51HXD_2017-07-17_final.stac-item
2017-07-17 11:20:58	ga_s2am_ard_3-2-1_51JXL_2017-07-17_final.stac-item
2017-07-25 10:43:07	ga_s2am_ard_3-2-1_52JGM_2017-07-25_final.stac-item
2017-07-30 11:28:34	ga_s2am_ard_3-2-1_51KVP_2017-07-30_final.stac-item
2017-08-28 12:03:48	ga_s2am_ard_3-2-1_50KKA_2017-08-28_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_50JQM_2017-11-07_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_50JKT_2017-11-26_final.stac-item
2018-02-25 11:27:26	ga_s2am_ard_3-2-1_51KUS_2018-02-25_final.stac-item
2018-03-19 12:13:18	ga_s2am_ard_3-2-1_49JGN_2018-03-19_final.stac-item
2018-03-27 11:33:07	ga_s2am_ard_3-2-1_51KUR_2018-03-27_final.stac-item
2018-05-23 11:17:08	ga_s2am_ard_3-2-1_51KYB_2018-05-23_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HPJ_2018-08-07_final.stac-item
2018-09-20 11:24:00	ga_s2am_ard_3-2-1_51HUE_2018-09-20_final.stac-item
2018-10-12 12:02:46	ga_s2am_ard_3-2-1_49KHR_2018-10-12_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KVP_2018-11-02_final.stac-item
2018-11-25 11:42:20	ga_s2am_ard_3-2-1_51KVA_2018-11-25_final.stac-item
2018-11-29 11:22:57	ga_s2am_ard_3-2-1_52KBC_2018-11-29_final.stac-item
2018-12-15 11:42:05	ga_s2am_ard_3-2-1_51KVB_2018-12-15_final.stac-item
2019-02-10 11:33:49	ga_s2am_ard_3-2-1_51KXQ_2019-02-10_final.stac-item
2019-03-21 12:04:26	ga_s2am_ard_3-2-1_50KKU_2019-03-21_final.stac-item
2019-03-21 12:04:55	ga_s2am_ard_3-2-1_50JKS_2019-03-21_final.stac-item
2019-04-20 12:04:31	ga_s2am_ard_3-2-1_50KKU_2019-04-20_final.stac-item
2019-09-11 11:46:11	ga_s2am_ard_3-2-1_50JMM_2019-09-11_final.stac-item
2019-09-12 11:15:05	ga_s2am_ard_3-2-1_52JBQ_2019-09-12_final.stac-item
2019-09-15 11:23:38	ga_s2am_ard_3-2-1_51KYR_2019-09-15_final.stac-item
2019-09-18 11:32:00	ga_s2am_ard_3-2-1_51LWC_2019-09-18_final.stac-item
2019-10-21 11:46:24	ga_s2am_ard_3-2-1_50JQL_2019-10-21_final.stac-item
2019-11-16 12:04:48	ga_s2am_ard_3-2-1_49JGN_2019-11-16_final.stac-item
2019-11-20 11:46:44	ga_s2am_ard_3-2-1_50HQJ_2019-11-20_final.stac-item
2019-12-07 11:33:50	ga_s2am_ard_3-2-1_51KXQ_2019-12-07_final.stac-item
2019-12-17 11:36:28	ga_s2am_ard_3-2-1_50HQK_2019-12-17_final.stac-item
2020-01-18 12:13:48	ga_s2am_ard_3-2-1_50KKA_2020-01-18_final.stac-item
2020-02-05 11:36:38	ga_s2am_ard_3-2-1_51HTD_2020-02-05_final.stac-item
2020-03-02 11:55:48	ga_s2am_ard_3-2-1_50JMN_2020-03-02_final.stac-item
2020-04-05 11:32:22	ga_s2am_ard_3-2-1_51KXA_2020-04-05_final.stac-item
2020-04-12 11:22:51	ga_s2am_ard_3-2-1_51KZU_2020-04-12_final.stac-item
2020-05-12 11:22:46	ga_s2am_ard_3-2-1_51KYV_2020-05-12_final.stac-item
2020-05-25 11:32:02	ga_s2am_ard_3-2-1_51LXC_2020-05-25_final.stac-item
2020-06-07 11:41:04	ga_s2am_ard_3-2-1_51LWG_2020-06-07_final
2020-06-27 11:43:05	ga_s2am_ard_3-2-1_51KUU_2020-06-27_final.stac-item
2020-07-03 12:03:49	ga_s2am_ard_3-2-1_50KNA_2020-07-03_final.stac-item
2020-07-04 11:37:07	ga_s2am_ard_3-2-1_50HQH_2020-07-04_final.stac-item
2020-08-30 11:23:59	ga_s2am_ard_3-2-1_51KYQ_2020-08-30_final.stac-item
2020-09-15 11:42:50	ga_s2am_ard_3-2-1_51KUV_2020-09-15_final.stac-item
2020-10-04 12:15:05	ga_s2am_ard_3-2-1_49JFM_2020-10-04_final.stac-item
2020-11-08 11:27:06	ga_s2am_ard_3-2-1_51HUC_2020-11-08_final.stac-item
2020-11-28 11:25:10	ga_s2am_ard_3-2-1_51JXK_2020-11-28_final.stac-item
2020-12-04 11:43:28	ga_s2am_ard_3-2-1_51KUS_2020-12-04_final.stac-item
2020-12-30 12:05:55	ga_s2am_ard_3-2-1_50JKN_2020-12-30_final.stac-item
2021-01-31 11:04:21	ga_s2am_ard_3-2-1_52JDT_2021-01-31_final.stac-item
2021-02-01 12:14:41	ga_s2am_ard_3-2-1_49JGN_2021-02-01_final.stac-item
2021-03-08 11:22:56	ga_s2am_ard_3-2-1_51KYU_2021-03-08_final.stac-item
2021-07-03 11:15:12	ga_s2am_ard_3-2-1_51JYK_2021-07-03_final.stac-item
2021-07-22 11:42:17	ga_s2am_ard_3-2-1_51KVB_2021-07-22_final.stac-item
2021-08-15 11:22:54	ga_s2am_ard_3-2-1_52KBD_2021-08-15_final.stac-item
2021-10-14 11:23:11	ga_s2am_ard_3-2-1_52KBC_2021-10-14_final.stac-item
2021-10-27 11:32:34	ga_s2am_ard_3-2-1_51KWA_2021-10-27_final.stac-item
2021-11-05 12:05:04	ga_s2am_ard_3-2-1_49JGM_2021-11-05_final.stac-item
2021-12-06 11:32:46	ga_s2am_ard_3-2-1_51KVV_2021-12-06_final.stac-item
2022-01-11 11:56:56	ga_s2am_ard_3-2-1_50HLJ_2022-01-11_final.stac-item
2022-01-15 11:34:44	ga_s2am_ard_3-2-1_51JVM_2022-01-15_final.stac-item
2022-04-12 11:25:41	ga_s2am_ard_3-2-1_51JXH_2022-04-12_final.stac-item
2022-04-28 11:42:00	ga_s2am_ard_3-2-1_51LWC_2022-04-28_final.stac-item
2022-05-28 11:46:55	ga_s2am_ard_3-2-1_50HPJ_2022-05-28_final.stac-item
2022-07-21 11:25:02	ga_s2am_ard_3-2-1_51JYL_2022-07-21_final.stac-item
2022-10-12 11:32:52	ga_s2am_ard_3-2-1_51KVV_2022-10-12_final.stac-item
2022-11-01 11:37:01	ga_s2am_ard_3-2-1_51HUC_2022-11-01_final.stac-item
2022-12-01 11:36:43	ga_s2am_ard_3-2-1_51HUD_2022-12-01_final.stac-item
2022-12-28 11:24:13	ga_s2am_ard_3-2-1_51KWP_2022-12-28_final.stac-item
2023-03-30 12:03:50	ga_s2am_ard_3-2-1_50KMA_2023-03-30_final
2023-03-30 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2023-03-30_final
2023-05-07 11:25:42	ga_s2am_ard_3-2-1_51JWH_2023-05-07_final
2023-05-26 11:56:54	ga_s2am_ard_3-2-1_50HMJ_2023-05-26_final
2023-05-31 11:04:36	ga_s2am_ard_3-2-1_52JES_2023-05-31_final
2023-06-15 11:56:30	ga_s2am_ard_3-2-1_50JLL_2023-06-15_final
2023-07-12 11:43:49	ga_s2am_ard_3-2-1_51KUR_2023-07-12_final
2023-07-29 11:35:03	ga_s2am_ard_3-2-1_51JVL_2023-07-29_final
2023-08-22 11:15:10	ga_s2am_ard_3-2-1_52JCQ_2023-08-22_final
2023-09-09 12:14:03	ga_s2am_ard_3-2-1_49KGR_2023-09-09_final
2023-09-23 11:53:23	ga_s2am_ard_3-2-1_50KPC_2023-09-23_final
2023-10-04 11:23:08	ga_s2am_ard_3-2-1_52KBC_2023-10-04_final
2023-11-06 11:31:59	ga_s2am_ard_3-2-1_51LWC_2023-11-06_final
2023-11-29 11:40:49	ga_s2am_ard_3-2-1_51LWG_2023-11-29_final
2024-03-18 11:41:56	ga_s2am_ard_3-2-1_51LWC_2024-03-18_final
2024-04-11 11:23:07	ga_s2am_ard_3-2-1_52KBC_2024-04-11_final
2024-04-13 12:04:01	ga_s2am_ard_3-2-1_49KHR_2024-04-13_final
2024-05-01 11:26:08	ga_s2am_ard_3-2-1_51JUG_2024-05-01_final
2024-05-07 11:41:58	ga_s2am_ard_3-2-1_51LWC_2024-05-07_final
2024-05-23 12:06:03	ga_s2am_ard_3-2-1_50JLM_2024-05-23_nrt

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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