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
2015-09-29 11:36:06	ga_s2am_ard_3-2-1_50JPL_2015-09-29_final.stac-item
2015-11-20 12:13:41	ga_s2am_ard_3-2-1_50KKV_2015-11-20_final.stac-item
2015-11-21 11:41:49	ga_s2am_ard_3-2-1_51JTJ_2015-11-21_final.stac-item
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JMN_2015-12-04_final.stac-item
2016-01-17 11:36:22	ga_s2am_ard_3-2-1_50HQK_2016-01-17_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50JRS_2016-02-06_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_51JTG_2016-02-06_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50JNM_2016-03-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50KQU_2016-03-20_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HNK_2016-04-29_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50JPS_2016-05-09_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50KKV_2016-05-15_final.stac-item
2016-06-14 12:04:45	ga_s2am_ard_3-2-1_49JGL_2016-06-14_final.stac-item
2016-09-02 12:04:42	ga_s2am_ard_3-2-1_50JLR_2016-09-02_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50KKB_2016-10-02_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_51HUC_2016-10-03_final.stac-item
2016-11-02 11:32:48	ga_s2am_ard_3-2-1_51HVE_2016-11-02_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50KKB_2017-05-30_final.stac-item
2017-07-27 11:26:10	ga_s2am_ard_3-2-1_51HVE_2017-07-27_final.stac-item
2017-09-18 11:36:00	ga_s2am_ard_3-2-1_50JPL_2017-09-18_final.stac-item
2018-01-16 11:35:56	ga_s2am_ard_3-2-1_50JQL_2018-01-16_final.stac-item
2018-11-28 11:56:57	ga_s2am_ard_3-2-1_50HMH_2018-11-28_final.stac-item
2019-01-17 11:56:32	ga_s2am_ard_3-2-1_50HMK_2019-01-17_final.stac-item
2019-01-18 11:26:14	ga_s2am_ard_3-2-1_51JUF_2019-01-18_final.stac-item
2019-01-27 11:56:26	ga_s2am_ard_3-2-1_50HNK_2019-01-27_final.stac-item
2019-01-27 11:56:33	ga_s2am_ard_3-2-1_50HMK_2019-01-27_final.stac-item
2019-02-20 11:36:24	ga_s2am_ard_3-2-1_51HUE_2019-02-20_final.stac-item
2019-04-03 12:14:08	ga_s2am_ard_3-2-1_50KKV_2019-04-03_final.stac-item
2019-04-04 11:45:30	ga_s2am_ard_3-2-1_51JTJ_2019-04-04_final.stac-item
2019-06-12 12:14:59	ga_s2am_ard_3-2-1_49JGM_2019-06-12_final.stac-item
2019-08-21 12:13:42	ga_s2am_ard_3-2-1_50KKB_2019-08-21_final.stac-item
2019-09-18 11:36:28	ga_s2am_ard_3-2-1_51HUE_2019-09-18_final.stac-item
2019-10-11 11:45:32	ga_s2am_ard_3-2-1_51JTJ_2019-10-11_final.stac-item
2019-10-14 11:56:39	ga_s2am_ard_3-2-1_50HMK_2019-10-14_final.stac-item
2019-10-14 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2019-10-14_final.stac-item
2019-10-18 11:36:17	ga_s2am_ard_3-2-1_51JUF_2019-10-18_final.stac-item
2019-10-20 12:13:43	ga_s2am_ard_3-2-1_50KKB_2019-10-20_final.stac-item
2019-10-24 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2019-10-24_final.stac-item
2019-10-28 11:36:27	ga_s2am_ard_3-2-1_51HVE_2019-10-28_final.stac-item
2019-11-20 11:47:11	ga_s2am_ard_3-2-1_50HMH_2019-11-20_final.stac-item
2019-11-23 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2019-11-23_final.stac-item
2019-12-03 11:56:53	ga_s2am_ard_3-2-1_50HLJ_2019-12-03_final.stac-item
2020-01-19 11:46:49	ga_s2am_ard_3-2-1_50HMJ_2020-01-19_final.stac-item
2020-02-01 11:56:29	ga_s2am_ard_3-2-1_50HMK_2020-02-01_final.stac-item
2020-02-05 11:36:06	ga_s2am_ard_3-2-1_51JUF_2020-02-05_final.stac-item
2020-02-08 11:46:47	ga_s2am_ard_3-2-1_50HMJ_2020-02-08_final.stac-item
2020-06-06 12:14:04	ga_s2am_ard_3-2-1_49KGR_2020-06-06_final.stac-item
2020-06-06 12:14:14	ga_s2am_ard_3-2-1_50KKV_2020-06-06_final.stac-item
2020-09-12 11:36:18	ga_s2am_ard_3-2-1_51JUF_2020-09-12_final.stac-item
2020-10-02 11:36:23	ga_s2am_ard_3-2-1_51JTF_2020-10-02_final.stac-item
2020-10-04 12:14:22	ga_s2am_ard_3-2-1_50KKU_2020-10-04_final.stac-item
2020-10-09 11:26:28	ga_s2am_ard_3-2-1_51JUF_2020-10-09_final.stac-item
2020-10-12 11:36:34	ga_s2am_ard_3-2-1_51HUE_2020-10-12_final.stac-item
2020-10-28 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2020-10-28_final.stac-item
2020-12-17 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2020-12-17_final.stac-item
2021-01-03 11:47:14	ga_s2am_ard_3-2-1_50HLH_2021-01-03_final.stac-item
2021-01-06 11:56:51	ga_s2am_ard_3-2-1_50HMJ_2021-01-06_final.stac-item
2021-01-13 11:47:15	ga_s2am_ard_3-2-1_50HLH_2021-01-13_final.stac-item
2021-01-30 11:36:25	ga_s2am_ard_3-2-1_51HUE_2021-01-30_final.stac-item
2021-02-15 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2021-02-15_final.stac-item
2021-05-19 12:03:20	ga_s2am_ard_3-2-1_50KNC_2021-05-19_final.stac-item
2021-06-01 12:13:55	ga_s2am_ard_3-2-1_49KHR_2021-06-01_final.stac-item
2021-07-29 11:37:14	ga_s2am_ard_3-2-1_50HQG_2021-07-29_final
2021-08-01 11:45:50	ga_s2am_ard_3-2-1_50JQN_2021-08-01_final.stac-item
2021-09-10 11:46:15	ga_s2am_ard_3-2-1_50JQL_2021-09-10_final.stac-item
2021-09-13 11:57:10	ga_s2am_ard_3-2-1_50HLH_2021-09-13_final.stac-item
2021-09-20 11:46:03	ga_s2am_ard_3-2-1_50JQM_2021-09-20_final.stac-item
2021-09-26 12:05:15	ga_s2am_ard_3-2-1_50JKR_2021-09-26_final.stac-item
2021-09-27 11:36:21	ga_s2am_ard_3-2-1_51JTF_2021-09-27_final.stac-item
2021-09-27 11:36:35	ga_s2am_ard_3-2-1_51HTE_2021-09-27_final.stac-item
2021-09-30 11:46:34	ga_s2am_ard_3-2-1_50HQK_2021-09-30_final.stac-item
2021-10-03 11:57:03	ga_s2am_ard_3-2-1_50HLJ_2021-10-03_final.stac-item
2021-10-04 11:26:34	ga_s2am_ard_3-2-1_51HVE_2021-10-04_final.stac-item
2021-10-14 11:26:31	ga_s2am_ard_3-2-1_51HWE_2021-10-14_final.stac-item
2021-12-03 11:26:25	ga_s2am_ard_3-2-1_51HWE_2021-12-03_final.stac-item
2022-04-04 12:04:37	ga_s2am_ard_3-2-1_50JMT_2022-04-04_final.stac-item
2022-04-08 11:45:30	ga_s2am_ard_3-2-1_51JTJ_2022-04-08_final.stac-item
2022-06-16 12:14:05	ga_s2am_ard_3-2-1_49KHR_2022-06-16_final.stac-item
2022-07-31 11:26:36	ga_s2am_ard_3-2-1_51HWE_2022-07-31_final.stac-item
2022-09-01 12:05:11	ga_s2am_ard_3-2-1_50JMR_2022-09-01_final.stac-item
2022-09-01 12:05:24	ga_s2am_ard_3-2-1_50JKR_2022-09-01_final.stac-item
2022-09-08 11:56:01	ga_s2am_ard_3-2-1_50JNN_2022-09-08_final.stac-item
2022-09-11 12:05:51	ga_s2am_ard_3-2-1_50JKP_2022-09-11_final.stac-item
2022-09-24 12:14:02	ga_s2am_ard_3-2-1_49KHR_2022-09-24_final.stac-item
2022-09-25 11:46:59	ga_s2am_ard_3-2-1_50HNJ_2022-09-25_final.stac-item
2022-10-15 11:46:19	ga_s2am_ard_3-2-1_50JQL_2022-10-15_final.stac-item
2023-03-04 11:47:06	ga_s2am_ard_3-2-1_50HMH_2023-03-04_final
2023-04-03 11:45:56	ga_s2am_ard_3-2-1_51JTG_2023-04-03_final
2023-04-03 11:47:09	ga_s2am_ard_3-2-1_50HMH_2023-04-03_final
2023-04-07 11:26:58	ga_s2am_ard_3-2-1_51HVC_2023-04-07_final
2023-06-16 11:26:26	ga_s2am_ard_3-2-1_51HXE_2023-06-16_final
2023-06-16 11:26:40	ga_s2am_ard_3-2-1_51HXD_2023-06-16_final
2023-06-19 11:36:36	ga_s2am_ard_3-2-1_51HTE_2023-06-19_final
2023-09-07 11:35:53	ga_s2am_ard_3-2-1_51JTH_2023-09-07_final
2023-09-10 11:45:51	ga_s2am_ard_3-2-1_50JQN_2023-09-10_final
2023-09-16 12:05:41	ga_s2am_ard_3-2-1_50JLP_2023-09-16_final
2023-09-20 11:46:36	ga_s2am_ard_3-2-1_50HPK_2023-09-20_final
2023-09-29 12:14:10	ga_s2am_ard_3-2-1_50KKV_2023-09-29_final
2023-12-02 11:56:58	ga_s2am_ard_3-2-1_50HMH_2023-12-02_final
2024-01-21 11:57:01	ga_s2am_ard_3-2-1_50HLH_2024-01-21_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