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
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JLQ_2016-04-02_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HQK_2016-04-19_final.stac-item
2016-05-06 11:36:08	ga_s2am_ard_3-2-1_50JQM_2016-05-06_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HQK_2016-05-29_final.stac-item
2016-07-22 11:22:31	ga_s2am_ard_3-2-1_51JWM_2016-07-22_final
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_51KTU_2016-07-28_final.stac-item
2016-08-04 11:32:03	ga_s2am_ard_3-2-1_51KVT_2016-08-04_final.stac-item
2016-10-09 11:48:21	ga_s2am_ard_3-2-1_50JNN_2016-10-09_final.stac-item
2016-10-15 12:14:37	ga_s2am_ard_3-2-1_49JGM_2016-10-15_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUS_2016-12-22_final.stac-item
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_51KVT_2017-01-31_final.stac-item
2017-05-04 11:38:37	ga_s2am_ard_3-2-1_51KUV_2017-05-04_final.stac-item
2017-06-22 12:13:20	ga_s2am_ard_3-2-1_49KGQ_2017-06-22_final.stac-item
2017-09-01 11:40:44	ga_s2am_ard_3-2-1_50JPL_2017-09-01_final.stac-item
2018-01-20 11:11:55	ga_s2am_ard_3-2-1_51HXD_2018-01-20_final.stac-item
2018-02-07 12:14:38	ga_s2am_ard_3-2-1_49JFM_2018-02-07_final.stac-item
2018-03-14 11:21:15	ga_s2am_ard_3-2-1_51HUD_2018-03-14_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HNK_2018-08-07_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HPH_2018-08-07_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51HUD_2018-08-14_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_51KUT_2018-09-06_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51JXN_2018-09-23_final.stac-item
2018-11-08 11:53:27	ga_s2am_ard_3-2-1_50KQB_2018-11-08_final.stac-item
2018-11-15 11:42:54	ga_s2am_ard_3-2-1_51KUU_2018-11-15_final.stac-item
2018-12-24 12:14:48	ga_s2am_ard_3-2-1_49JGM_2018-12-24_final.stac-item
2019-02-20 11:33:41	ga_s2am_ard_3-2-1_51KVR_2019-02-20_final.stac-item
2019-02-23 11:43:11	ga_s2am_ard_3-2-1_51KUT_2019-02-23_final.stac-item
2019-03-12 11:33:40	ga_s2am_ard_3-2-1_51KVR_2019-03-12_final.stac-item
2019-03-26 11:16:11	ga_s2am_ard_3-2-1_51JXF_2019-03-26_final.stac-item
2019-04-23 12:13:57	ga_s2am_ard_3-2-1_50KKA_2019-04-23_final.stac-item
2019-04-30 12:05:59	ga_s2am_ard_3-2-1_50JKN_2019-04-30_final.stac-item
2019-05-08 11:26:51	ga_s2am_ard_3-2-1_51HUD_2019-05-08_final.stac-item
2019-06-30 11:34:20	ga_s2am_ard_3-2-1_51JXN_2019-06-30_final.stac-item
2019-08-29 11:36:44	ga_s2am_ard_3-2-1_51HUD_2019-08-29_final.stac-item
2019-10-11 11:42:30	ga_s2am_ard_3-2-1_51KVA_2019-10-11_final.stac-item
2019-11-06 12:04:01	ga_s2am_ard_3-2-1_50KKA_2019-11-06_final.stac-item
2019-11-16 12:03:25	ga_s2am_ard_3-2-1_50KMC_2019-11-16_final.stac-item
2019-11-20 11:42:29	ga_s2am_ard_3-2-1_51KVA_2019-11-20_final.stac-item
2019-11-30 11:43:28	ga_s2am_ard_3-2-1_51KUS_2019-11-30_final.stac-item
2020-01-02 11:53:25	ga_s2am_ard_3-2-1_50KMC_2020-01-02_final.stac-item
2020-02-18 11:44:10	ga_s2am_ard_3-2-1_51KTP_2020-02-18_final.stac-item
2020-06-03 12:05:47	ga_s2am_ard_3-2-1_50JKP_2020-06-03_final.stac-item
2020-06-14 11:33:40	ga_s2am_ard_3-2-1_51KUS_2020-06-14_final.stac-item
2020-06-14 11:36:40	ga_s2am_ard_3-2-1_50HQK_2020-06-14_final.stac-item
2020-07-10 11:52:24	ga_s2am_ard_3-2-1_50KQG_2020-07-10_final
2020-09-02 11:33:35	ga_s2am_ard_3-2-1_51KVS_2020-09-02_final.stac-item
2020-11-03 12:15:01	ga_s2am_ard_3-2-1_49JGM_2020-11-03_final.stac-item
2020-11-10 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2020-11-10_final.stac-item
2020-11-14 11:42:17	ga_s2am_ard_3-2-1_51KVB_2020-11-14_final.stac-item
2021-03-27 11:55:57	ga_s2am_ard_3-2-1_50JKN_2021-03-27_final.stac-item
2021-04-14 11:16:35	ga_s2am_ard_3-2-1_51HXD_2021-04-14_final.stac-item
2021-05-23 11:42:28	ga_s2am_ard_3-2-1_51KVA_2021-05-23_final.stac-item
2021-06-22 11:43:16	ga_s2am_ard_3-2-1_51KUT_2021-06-22_final.stac-item
2021-07-01 12:13:56	ga_s2am_ard_3-2-1_50KKA_2021-07-01_final.stac-item
2021-07-29 11:37:06	ga_s2am_ard_3-2-1_50HQH_2021-07-29_final.stac-item
2021-08-01 11:43:14	ga_s2am_ard_3-2-1_51KVT_2021-08-01_final.stac-item
2021-08-17 12:05:58	ga_s2am_ard_3-2-1_50JKN_2021-08-17_final.stac-item
2021-08-28 11:32:21	ga_s2am_ard_3-2-1_51KVB_2021-08-28_final.stac-item
2021-09-03 11:52:21	ga_s2am_ard_3-2-1_50KQG_2021-09-03_final
2021-09-30 11:43:29	ga_s2am_ard_3-2-1_51KVS_2021-09-30_final.stac-item
2021-11-16 11:33:31	ga_s2am_ard_3-2-1_51KVS_2021-11-16_final.stac-item
2021-11-16 11:33:35	ga_s2am_ard_3-2-1_51KUS_2021-11-16_final.stac-item
2021-12-29 11:43:02	ga_s2am_ard_3-2-1_51KUU_2021-12-29_final.stac-item
2021-12-29 11:43:19	ga_s2am_ard_3-2-1_50KQC_2021-12-29_final.stac-item
2022-01-07 12:13:56	ga_s2am_ard_3-2-1_49KHR_2022-01-07_final.stac-item
2022-01-08 11:43:30	ga_s2am_ard_3-2-1_51KUS_2022-01-08_final.stac-item
2022-03-08 12:13:58	ga_s2am_ard_3-2-1_50KKA_2022-03-08_final.stac-item
2022-03-23 11:25:19	ga_s2am_ard_3-2-1_51JVK_2022-03-23_final.stac-item
2022-06-14 11:36:01	ga_s2am_ard_3-2-1_50JQN_2022-06-14_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 11:36:59	ga_s2am_ard_3-2-1_50HQJ_2022-08-03_final.stac-item
2022-08-06 11:43:36	ga_s2am_ard_3-2-1_51KVS_2022-08-06_final.stac-item
2022-09-12 11:36:24	ga_s2am_ard_3-2-1_51JUF_2022-09-12_final.stac-item
2022-09-15 11:43:34	ga_s2am_ard_3-2-1_51KVS_2022-09-15_final.stac-item
2022-09-22 11:36:39	ga_s2am_ard_3-2-1_51HTE_2022-09-22_final.stac-item
2022-12-01 11:33:16	ga_s2am_ard_3-2-1_51KVT_2022-12-01_final.stac-item
2022-12-14 11:43:25	ga_s2am_ard_3-2-1_51KVS_2022-12-14_final.stac-item
2022-12-21 11:34:16	ga_s2am_ard_3-2-1_51KUP_2022-12-21_final.stac-item
2023-01-13 11:47:14	ga_s2am_ard_3-2-1_50HPG_2023-01-13_final
2023-01-23 11:44:27	ga_s2am_ard_3-2-1_51JTN_2023-01-23_final.stac-item
2023-02-22 11:46:31	ga_s2am_ard_3-2-1_50HPK_2023-02-22_final
2023-03-11 11:33:40	ga_s2am_ard_3-2-1_51KVR_2023-03-11_final
2023-03-31 11:32:30	ga_s2am_ard_3-2-1_51KVA_2023-03-31_final
2023-03-31 11:33:58	ga_s2am_ard_3-2-1_51KVQ_2023-03-31_final
2023-06-11 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-06-11_final
2023-06-29 11:34:58	ga_s2am_ard_3-2-1_51JWL_2023-06-29_final
2023-07-19 11:37:11	ga_s2am_ard_3-2-1_50HPH_2023-07-19_final
2023-07-26 11:26:52	ga_s2am_ard_3-2-1_51HUD_2023-07-26_final
2023-07-31 12:13:45	ga_s2am_ard_3-2-1_50KKB_2023-07-31_final
2023-09-23 11:53:12	ga_s2am_ard_3-2-1_50KRC_2023-09-23_final
2023-11-29 11:47:02	ga_s2am_ard_3-2-1_50HMH_2023-11-29_final
2024-01-05 11:33:56	ga_s2am_ard_3-2-1_51KVQ_2024-01-05_final
2024-01-08 11:42:23	ga_s2am_ard_3-2-1_51KVA_2024-01-08_final
2024-01-08 11:42:56	ga_s2am_ard_3-2-1_51KUU_2024-01-08_final
2024-01-24 12:03:38	ga_s2am_ard_3-2-1_50KKB_2024-01-24_final
2024-03-14 12:03:44	ga_s2am_ard_3-2-1_50KKB_2024-03-14_final
2024-03-18 11:43:15	ga_s2am_ard_3-2-1_51KUT_2024-03-18_final
2024-03-25 11:32:20	ga_s2am_ard_3-2-1_51KVB_2024-03-25_final
2024-04-30 11:56:14	ga_s2am_ard_3-2-1_50JLM_2024-04-30_final
2024-05-01 11:26:50	ga_s2am_ard_3-2-1_51HUD_2024-05-01_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