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
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_49JGL_2016-01-16_final.stac-item
2016-03-16 11:57:24	ga_s2am_ard_3-2-1_50JLP_2016-03-16_final.stac-item
2016-04-30 11:14:04	ga_s2am_ard_3-2-1_51HXD_2016-04-30_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51HUC_2016-05-03_final.stac-item
2016-05-13 11:26:15	ga_s2am_ard_3-2-1_51HUE_2016-05-13_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JKN_2016-05-15_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_51JYL_2016-05-30_final.stac-item
2016-08-20 11:56:10	ga_s2am_ard_3-2-1_50JLM_2016-08-20_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51KUV_2016-11-05_final.stac-item
2016-11-16 11:11:49	ga_s2am_ard_3-2-1_51HWC_2016-11-16_final
2017-02-12 12:13:15	ga_s2am_ard_3-2-1_49JGN_2017-02-12_final.stac-item
2017-04-14 11:38:34	ga_s2am_ard_3-2-1_51KTT_2017-04-14_final.stac-item
2017-07-26 11:56:09	ga_s2am_ard_3-2-1_50HNK_2017-07-26_final.stac-item
2017-07-29 12:02:51	ga_s2am_ard_3-2-1_50KMC_2017-07-29_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49KGP_2017-09-07_final.stac-item
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_50JQN_2017-09-08_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_50KKA_2017-12-19_final.stac-item
2018-02-01 11:49:16	ga_s2am_ard_3-2-1_50KQC_2018-02-01_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-03-06_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50HLH_2018-03-13_final.stac-item
2018-03-20 11:37:46	ga_s2am_ard_3-2-1_51KUU_2018-03-20_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51JZM_2018-04-23_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JKN_2018-06-11_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_51KUT_2018-08-27_final.stac-item
2018-09-06 11:45:53	ga_s2am_ard_3-2-1_50JPL_2018-09-06_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51JUG_2018-10-13_final.stac-item
2018-12-25 11:42:53	ga_s2am_ard_3-2-1_51KUU_2018-12-25_final.stac-item
2019-01-20 12:03:55	ga_s2am_ard_3-2-1_49KHR_2019-01-20_final.stac-item
2019-02-03 11:42:57	ga_s2am_ard_3-2-1_51KUU_2019-02-03_final.stac-item
2019-02-06 11:56:04	ga_s2am_ard_3-2-1_50JMM_2019-02-06_final.stac-item
2019-03-02 11:33:17	ga_s2am_ard_3-2-1_51KUT_2019-03-02_final.stac-item
2019-03-02 11:33:43	ga_s2am_ard_3-2-1_51KUR_2019-03-02_final.stac-item
2019-04-14 11:43:24	ga_s2am_ard_3-2-1_50KQC_2019-04-14_final.stac-item
2019-04-17 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-04-17_final.stac-item
2019-05-17 11:53:14	ga_s2am_ard_3-2-1_50KRC_2019-05-17_final.stac-item
2019-07-12 12:13:59	ga_s2am_ard_3-2-1_50KKA_2019-07-12_final.stac-item
2019-10-04 11:56:06	ga_s2am_ard_3-2-1_50JNM_2019-10-04_final.stac-item
2019-10-31 11:42:31	ga_s2am_ard_3-2-1_51KVA_2019-10-31_final.stac-item
2019-12-04 11:26:16	ga_s2am_ard_3-2-1_51JUF_2019-12-04_final.stac-item
2020-03-16 11:34:45	ga_s2am_ard_3-2-1_51JVM_2020-03-16_final.stac-item
2020-05-01 11:53:13	ga_s2am_ard_3-2-1_50KRC_2020-05-01_final.stac-item
2020-05-08 11:46:09	ga_s2am_ard_3-2-1_50JPM_2020-05-08_final.stac-item
2020-08-16 11:43:09	ga_s2am_ard_3-2-1_51KTU_2020-08-16_final.stac-item
2020-08-26 11:47:12	ga_s2am_ard_3-2-1_50HNH_2020-08-26_final.stac-item
2020-10-02 11:36:54	ga_s2am_ard_3-2-1_50HQJ_2020-10-02_final.stac-item
2020-11-14 11:43:07	ga_s2am_ard_3-2-1_51KTU_2020-11-14_final.stac-item
2020-12-04 11:47:08	ga_s2am_ard_3-2-1_50HMH_2020-12-04_final.stac-item
2021-01-03 11:43:31	ga_s2am_ard_3-2-1_51KUS_2021-01-03_final.stac-item
2021-01-03 11:44:13	ga_s2am_ard_3-2-1_51KUP_2021-01-03_final.stac-item
2021-01-04 11:14:24	ga_s2am_ard_3-2-1_51JZN_2021-01-04_final.stac-item
2021-01-06 11:54:09	ga_s2am_ard_3-2-1_50KNV_2021-01-06_final.stac-item
2021-02-01 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-02-01_final.stac-item
2021-02-05 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2021-02-05_final.stac-item
2021-03-03 12:14:27	ga_s2am_ard_3-2-1_49KGP_2021-03-03_final.stac-item
2021-03-31 11:37:04	ga_s2am_ard_3-2-1_50HPH_2021-03-31_final.stac-item
2021-06-09 11:36:32	ga_s2am_ard_3-2-1_51HTE_2021-06-09_final.stac-item
2021-07-12 11:43:32	ga_s2am_ard_3-2-1_51KUS_2021-07-12_final.stac-item
2021-07-19 11:33:25	ga_s2am_ard_3-2-1_51KUT_2021-07-19_final.stac-item
2021-07-19 11:34:35	ga_s2am_ard_3-2-1_51JUN_2021-07-19_final.stac-item
2021-07-31 12:13:58	ga_s2am_ard_3-2-1_49KHR_2021-07-31_final.stac-item
2021-07-31 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-07-31_final.stac-item
2021-09-03 11:53:18	ga_s2am_ard_3-2-1_50KQC_2021-09-03_final.stac-item
2021-09-04 11:24:27	ga_s2am_ard_3-2-1_51JXN_2021-09-04_final.stac-item
2021-09-27 11:36:27	ga_s2am_ard_3-2-1_51HVE_2021-09-27_final.stac-item
2021-10-10 11:42:51	ga_s2am_ard_3-2-1_51KUV_2021-10-10_final.stac-item
2021-11-16 11:36:25	ga_s2am_ard_3-2-1_51HVE_2021-11-16_final.stac-item
2022-01-01 11:57:07	ga_s2am_ard_3-2-1_50HMH_2022-01-01_final.stac-item
2022-01-07 12:14:57	ga_s2am_ard_3-2-1_49JGM_2022-01-07_final.stac-item
2022-01-17 12:13:55	ga_s2am_ard_3-2-1_50KKA_2022-01-17_final.stac-item
2022-02-24 11:37:09	ga_s2am_ard_3-2-1_50HPH_2022-02-24_final.stac-item
2022-03-15 12:03:48	ga_s2am_ard_3-2-1_50KKB_2022-03-15_final.stac-item
2022-04-28 11:47:07	ga_s2am_ard_3-2-1_50HPH_2022-04-28_final.stac-item
2022-05-12 11:25:13	ga_s2am_ard_3-2-1_51JXK_2022-05-12_final.stac-item
2022-07-14 11:33:34	ga_s2am_ard_3-2-1_51KUT_2022-07-14_final.stac-item
2022-08-22 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-08-22_final.stac-item
2022-09-11 12:06:06	ga_s2am_ard_3-2-1_50JKN_2022-09-11_final.stac-item
2022-10-05 11:46:55	ga_s2am_ard_3-2-1_50HPJ_2022-10-05_final.stac-item
2022-11-03 12:13:58	ga_s2am_ard_3-2-1_50KKA_2022-11-03_final.stac-item
2022-12-31 11:36:37	ga_s2am_ard_3-2-1_50HPK_2022-12-31_final.stac-item
2023-01-30 11:33:32	ga_s2am_ard_3-2-1_51KUS_2023-01-30_final.stac-item
2023-02-12 11:42:44	ga_s2am_ard_3-2-1_51KUV_2023-02-12_final
2023-04-03 11:43:14	ga_s2am_ard_3-2-1_51KUT_2023-04-03_final
2023-04-23 11:42:40	ga_s2am_ard_3-2-1_51KUV_2023-04-23_final
2023-05-30 11:33:26	ga_s2am_ard_3-2-1_51KUT_2023-05-30_final
2023-06-25 11:55:56	ga_s2am_ard_3-2-1_50JMN_2023-06-25_final
2023-08-01 11:43:24	ga_s2am_ard_3-2-1_50KRC_2023-08-01_final
2023-08-01 11:43:34	ga_s2am_ard_3-2-1_51KUS_2023-08-01_final
2023-08-11 11:47:07	ga_s2am_ard_3-2-1_50HPH_2023-08-11_final
2023-09-14 11:26:15	ga_s2am_ard_3-2-1_51JWF_2023-09-14_final
2023-09-20 11:42:48	ga_s2am_ard_3-2-1_51KUV_2023-09-20_final
2023-10-26 12:05:55	ga_s2am_ard_3-2-1_50JKN_2023-10-26_final
2023-11-19 11:42:25	ga_s2am_ard_3-2-1_51KVA_2023-11-19_final
2023-11-22 11:52:16	ga_s2am_ard_3-2-1_50KQG_2023-11-22_final
2023-12-08 12:13:49	ga_s2am_ard_3-2-1_49KHR_2023-12-08_final
2023-12-16 11:36:48	ga_s2am_ard_3-2-1_50HPJ_2023-12-16_final
2023-12-26 11:32:16	ga_s2am_ard_3-2-1_51KVB_2023-12-26_final
2024-01-28 11:42:58	ga_s2am_ard_3-2-1_51KTU_2024-01-28_final
2024-02-07 11:42:23	ga_s2am_ard_3-2-1_51KVA_2024-02-07_final
2024-02-23 12:05:27	ga_s2am_ard_3-2-1_49JGK_2024-02-23_final
2024-02-26 12:13:53	ga_s2am_ard_3-2-1_50KKA_2024-02-26_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