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
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50HLH_2015-12-04_final.stac-item
2016-01-19 12:15:17	ga_s2am_ard_3-2-1_49JGM_2016-01-19_final.stac-item
2016-05-05 12:04:47	ga_s2am_ard_3-2-1_49JGM_2016-05-05_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HMJ_2016-11-28_final.stac-item
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_49JHM_2017-02-09_final.stac-item
2017-08-31 12:14:41	ga_s2am_ard_3-2-1_49JGK_2017-08-31_final.stac-item
2017-10-11 11:40:47	ga_s2am_ard_3-2-1_50KRB_2017-10-11_final.stac-item
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_51HUC_2018-04-16_final.stac-item
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_51HUD_2018-04-16_final.stac-item
2018-05-08 12:13:24	ga_s2am_ard_3-2-1_50KKA_2018-05-08_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_51KUT_2018-05-16_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51KUT_2018-06-05_final.stac-item
2018-07-22 11:25:32	ga_s2am_ard_3-2-1_51HUC_2018-07-22_final.stac-item
2018-08-08 11:13:24	ga_s2am_ard_3-2-1_51JYN_2018-08-08_final.stac-item
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_51KUT_2018-08-17_final.stac-item
2018-08-31 11:24:03	ga_s2am_ard_3-2-1_51HVC_2018-08-31_final.stac-item
2018-10-03 11:32:47	ga_s2am_ard_3-2-1_51JTF_2018-10-03_final.stac-item
2018-10-25 12:14:37	ga_s2am_ard_3-2-1_49JFN_2018-10-25_final.stac-item
2018-11-12 11:37:01	ga_s2am_ard_3-2-1_50HPH_2018-11-12_final.stac-item
2019-02-12 12:13:55	ga_s2am_ard_3-2-1_49KGR_2019-02-12_final.stac-item
2019-02-13 11:42:42	ga_s2am_ard_3-2-1_51KUV_2019-02-13_final.stac-item
2019-03-05 11:42:40	ga_s2am_ard_3-2-1_51KUV_2019-03-05_final.stac-item
2019-03-15 11:42:42	ga_s2am_ard_3-2-1_51KUV_2019-03-15_final.stac-item
2019-06-04 11:16:43	ga_s2am_ard_3-2-1_51HXD_2019-06-04_final.stac-item
2019-06-17 11:27:02	ga_s2am_ard_3-2-1_51HVC_2019-06-17_final.stac-item
2019-07-23 11:46:39	ga_s2am_ard_3-2-1_50HPK_2019-07-23_final.stac-item
2019-08-22 11:43:31	ga_s2am_ard_3-2-1_51KUS_2019-08-22_final.stac-item
2019-09-04 11:56:40	ga_s2am_ard_3-2-1_50HLK_2019-09-04_final.stac-item
2019-11-19 12:15:01	ga_s2am_ard_3-2-1_49JFM_2019-11-19_final.stac-item
2020-02-08 11:43:50	ga_s2am_ard_3-2-1_51KUQ_2020-02-08_final.stac-item
2020-04-08 11:42:43	ga_s2am_ard_3-2-1_51KUV_2020-04-08_final.stac-item
2020-04-08 11:42:58	ga_s2am_ard_3-2-1_51KUU_2020-04-08_final.stac-item
2020-05-08 11:42:50	ga_s2am_ard_3-2-1_51KUV_2020-05-08_final.stac-item
2020-09-01 12:06:09	ga_s2am_ard_3-2-1_50JLM_2020-09-01_final.stac-item
2020-09-02 11:33:39	ga_s2am_ard_3-2-1_51KUS_2020-09-02_final.stac-item
2020-10-14 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-10-14_final.stac-item
2020-12-18 11:26:34	ga_s2am_ard_3-2-1_51HXD_2020-12-18_final.stac-item
2020-12-27 11:53:17	ga_s2am_ard_3-2-1_50KQC_2020-12-27_final.stac-item
2021-02-06 11:24:55	ga_s2am_ard_3-2-1_51JXL_2021-02-06_final.stac-item
2021-02-08 12:03:40	ga_s2am_ard_3-2-1_50KLB_2021-02-08_final.stac-item
2021-02-28 12:05:29	ga_s2am_ard_3-2-1_49JGK_2021-02-28_final.stac-item
2021-03-01 11:35:12	ga_s2am_ard_3-2-1_51JVK_2021-03-01_final.stac-item
2021-03-03 12:14:07	ga_s2am_ard_3-2-1_50KKV_2021-03-03_final.stac-item
2021-03-04 11:43:00	ga_s2am_ard_3-2-1_51KUU_2021-03-04_final.stac-item
2021-03-23 12:13:53	ga_s2am_ard_3-2-1_50KKA_2021-03-23_final.stac-item
2021-03-24 11:45:42	ga_s2am_ard_3-2-1_51JTH_2021-03-24_final.stac-item
2021-05-10 11:36:57	ga_s2am_ard_3-2-1_51HUC_2021-05-10_final.stac-item
2021-06-09 11:33:23	ga_s2am_ard_3-2-1_51KUT_2021-06-09_final.stac-item
2021-06-09 11:36:49	ga_s2am_ard_3-2-1_50HQJ_2021-06-09_final.stac-item
2021-06-18 12:03:20	ga_s2am_ard_3-2-1_50KNC_2021-06-18_final.stac-item
2021-07-09 11:33:37	ga_s2am_ard_3-2-1_51KUS_2021-07-09_final.stac-item
2021-07-18 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-07-18_final.stac-item
2021-11-08 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-11-08_final.stac-item
2021-12-06 11:37:02	ga_s2am_ard_3-2-1_50HQH_2021-12-06_final.stac-item
2021-12-26 11:36:44	ga_s2am_ard_3-2-1_51HUD_2021-12-26_final.stac-item
2022-01-01 11:52:21	ga_s2am_ard_3-2-1_50KQG_2022-01-01_final
2022-02-13 12:04:42	ga_s2am_ard_3-2-1_49JHN_2022-02-13_final.stac-item
2022-03-19 11:42:49	ga_s2am_ard_3-2-1_51KUV_2022-03-19_final.stac-item
2022-04-07 12:14:42	ga_s2am_ard_3-2-1_49JGN_2022-04-07_final.stac-item
2022-05-08 11:43:26	ga_s2am_ard_3-2-1_50KQC_2022-05-08_final.stac-item
2022-06-06 12:14:06	ga_s2am_ard_3-2-1_49KGR_2022-06-06_final.stac-item
2022-06-11 11:26:35	ga_s2am_ard_3-2-1_51HWE_2022-06-11_final.stac-item
2022-06-30 11:52:47	ga_s2am_ard_3-2-1_50KQF_2022-06-30_final
2022-07-14 11:33:34	ga_s2am_ard_3-2-1_51KUT_2022-07-14_final.stac-item
2022-07-27 11:43:13	ga_s2am_ard_3-2-1_51KTU_2022-07-27_final.stac-item
2022-07-28 11:16:32	ga_s2am_ard_3-2-1_51HYE_2022-07-28_final.stac-item
2022-09-02 11:36:46	ga_s2am_ard_3-2-1_50HQK_2022-09-02_final.stac-item
2022-09-29 11:24:44	ga_s2am_ard_3-2-1_51JYM_2022-09-29_final.stac-item
2022-10-05 11:43:36	ga_s2am_ard_3-2-1_51KUS_2022-10-05_final.stac-item
2022-10-25 11:42:48	ga_s2am_ard_3-2-1_51KUV_2022-10-25_final.stac-item
2022-11-21 11:34:03	ga_s2am_ard_3-2-1_51KUQ_2022-11-21_final.stac-item
2022-11-28 11:27:01	ga_s2am_ard_3-2-1_51HUC_2022-11-28_final.stac-item
2022-12-01 11:33:34	ga_s2am_ard_3-2-1_51KUS_2022-12-01_final.stac-item
2022-12-24 11:46:21	ga_s2am_ard_3-2-1_50JNL_2022-12-24_final.stac-item
2022-12-30 12:03:22	ga_s2am_ard_3-2-1_50KMC_2022-12-30_final.stac-item
2023-01-10 11:34:35	ga_s2am_ard_3-2-1_50JRT_2023-01-10_final.stac-item
2023-02-02 11:42:26	ga_s2am_ard_3-2-1_51KVA_2023-02-02_final
2023-02-02 13:21:44	ga_s2am_ard_3-2-1_46LHM_2023-02-02_interim
2023-03-01 11:34:13	ga_s2am_ard_3-2-1_51JXN_2023-03-01_final
2023-03-27 11:55:58	ga_s2am_ard_3-2-1_50JKN_2023-03-27_final
2023-04-26 11:55:59	ga_s2am_ard_3-2-1_50JKN_2023-04-26_final
2023-05-03 11:43:04	ga_s2am_ard_3-2-1_51KTU_2023-05-03_final
2023-06-18 12:05:01	ga_s2am_ard_3-2-1_50JKS_2023-06-18_final
2023-08-30 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2023-08-30_final
2023-09-04 11:25:15	ga_s2am_ard_3-2-1_51JXK_2023-09-04_final
2023-09-06 12:03:49	ga_s2am_ard_3-2-1_50KKB_2023-09-06_final
2023-09-30 11:47:19	ga_s2am_ard_3-2-1_50HPG_2023-09-30_final
2023-10-09 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-10-09_final
2023-10-10 11:47:09	ga_s2am_ard_3-2-1_50HMH_2023-10-10_final
2023-10-13 11:55:51	ga_s2am_ard_3-2-1_50JNN_2023-10-13_final
2023-10-19 12:14:26	ga_s2am_ard_3-2-1_49KGP_2023-10-19_final
2023-10-27 11:36:57	ga_s2am_ard_3-2-1_51HUC_2023-10-27_final
2023-11-02 11:56:10	ga_s2am_ard_3-2-1_50JLM_2023-11-02_final
2023-11-12 11:57:05	ga_s2am_ard_3-2-1_50HMH_2023-11-12_final
2023-11-19 11:42:57	ga_s2am_ard_3-2-1_51KUU_2023-11-19_final
2023-12-05 12:05:22	ga_s2am_ard_3-2-1_49JGK_2023-12-05_final
2023-12-20 11:16:37	ga_s2am_ard_3-2-1_51HXD_2023-12-20_final
2024-01-24 12:03:53	ga_s2am_ard_3-2-1_49KHR_2024-01-24_final
2024-05-07 11:46:45	ga_s2am_ard_3-2-1_50HQJ_2024-05-07_final
2024-05-10 11:56:02	ga_s2am_ard_3-2-1_50JKN_2024-05-10_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