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
2015-11-14 11:47:22	ga_s2am_ard_3-2-1_50KQD_2015-11-14_final
2016-01-14 11:26:24	ga_s2am_ard_3-2-1_51HVE_2016-01-14_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50KKB_2016-01-16_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_50KQA_2016-01-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50JNR_2016-03-20_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50KQB_2016-03-20_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50KNC_2016-04-02_final.stac-item
2016-04-16 11:36:04	ga_s2am_ard_3-2-1_51JTG_2016-04-16_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HLH_2016-04-29_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51JVF_2016-05-03_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_50KQB_2016-05-09_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51JVJ_2016-05-23_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50HNG_2016-05-29_final
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JPS_2016-05-29_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49KHS_2016-07-14_final
2016-09-10 11:26:07	ga_s2am_ard_3-2-1_51JUF_2016-09-10_final.stac-item
2016-11-09 11:26:07	ga_s2am_ard_3-2-1_51HWE_2016-11-09_final.stac-item
2016-12-28 11:55:47	ga_s2am_ard_3-2-1_50HMJ_2016-12-28_final.stac-item
2017-02-27 11:22:43	ga_s2am_ard_3-2-1_51HXD_2017-02-27_final.stac-item
2017-04-13 12:13:43	ga_s2am_ard_3-2-1_49KHQ_2017-04-13_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HMJ_2017-05-24_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50KLC_2017-07-09_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50JNT_2017-08-25_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50KLA_2017-10-07_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_49JGM_2017-10-17_final.stac-item
2017-11-04 11:26:08	ga_s2am_ard_3-2-1_51JUF_2017-11-04_final.stac-item
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_49JHM_2017-12-26_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50HMJ_2018-01-12_final.stac-item
2018-06-18 11:44:07	ga_s2am_ard_3-2-1_50HNH_2018-06-18_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50KRD_2018-08-20_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JNR_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JPT_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50KPU_2018-08-27_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50KMC_2018-09-19_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49JGN_2018-10-05_final.stac-item
2018-10-06 11:40:38	ga_s2am_ard_3-2-1_50JPL_2018-10-06_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51HVC_2018-10-10_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JVF_2018-10-10_final.stac-item
2018-10-26 11:46:33	ga_s2am_ard_3-2-1_50HNK_2018-10-26_final.stac-item
2018-12-01 12:03:18	ga_s2am_ard_3-2-1_50KLC_2018-12-01_final.stac-item
2019-01-27 11:53:14	ga_s2am_ard_3-2-1_50KQC_2019-01-27_final.stac-item
2019-04-30 12:05:04	ga_s2am_ard_3-2-1_49JGM_2019-04-30_final.stac-item
2019-05-08 11:27:02	ga_s2am_ard_3-2-1_51HVC_2019-05-08_final.stac-item
2019-06-19 12:06:13	ga_s2am_ard_3-2-1_50JKM_2019-06-19_final.stac-item
2019-06-26 11:57:14	ga_s2am_ard_3-2-1_50HLH_2019-06-26_final.stac-item
2019-11-23 11:57:08	ga_s2am_ard_3-2-1_50HMH_2019-11-23_final.stac-item
2019-12-10 11:47:11	ga_s2am_ard_3-2-1_50HLH_2019-12-10_final.stac-item
2019-12-30 11:47:04	ga_s2am_ard_3-2-1_50HMH_2019-12-30_final.stac-item
2020-01-19 11:47:04	ga_s2am_ard_3-2-1_50HMH_2020-01-19_final.stac-item
2020-02-01 11:56:46	ga_s2am_ard_3-2-1_50HMJ_2020-02-01_final.stac-item
2020-02-14 12:03:52	ga_s2am_ard_3-2-1_49KHR_2020-02-14_final.stac-item
2020-04-27 12:13:56	ga_s2am_ard_3-2-1_50KKA_2020-04-27_final.stac-item
2020-04-28 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2020-04-28_final.stac-item
2020-05-08 11:46:17	ga_s2am_ard_3-2-1_50JMM_2020-05-08_final.stac-item
2020-06-24 11:36:52	ga_s2am_ard_3-2-1_51HTD_2020-06-24_final.stac-item
2020-08-06 11:46:32	ga_s2am_ard_3-2-1_50JML_2020-08-06_final.stac-item
2020-08-09 11:54:39	ga_s2am_ard_3-2-1_50KLU_2020-08-09_final.stac-item
2020-10-14 12:15:16	ga_s2am_ard_3-2-1_49JGL_2020-10-14_final.stac-item
2020-10-22 11:36:25	ga_s2am_ard_3-2-1_50JQL_2020-10-22_final.stac-item
2020-11-21 11:34:39	ga_s2am_ard_3-2-1_50JRT_2020-11-21_final.stac-item
2021-01-03 11:47:28	ga_s2am_ard_3-2-1_50HLG_2021-01-03_final
2021-02-05 11:56:50	ga_s2am_ard_3-2-1_50HMJ_2021-02-05_final.stac-item
2021-02-05 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-02-05_final.stac-item
2021-02-06 11:25:03	ga_s2am_ard_3-2-1_51JVL_2021-02-06_final.stac-item
2021-03-27 11:52:18	ga_s2am_ard_3-2-1_50KQG_2021-03-27_final
2021-05-23 11:46:20	ga_s2am_ard_3-2-1_50JPL_2021-05-23_final.stac-item
2021-06-11 12:14:42	ga_s2am_ard_3-2-1_49JGN_2021-06-11_final.stac-item
2021-06-18 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-06-18_final.stac-item
2021-07-05 11:55:49	ga_s2am_ard_3-2-1_50JKP_2021-07-05_final.stac-item
2021-07-18 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-07-18_final
2021-07-28 12:03:48	ga_s2am_ard_3-2-1_49KHS_2021-07-28_final
2021-07-31 12:14:21	ga_s2am_ard_3-2-1_50KKU_2021-07-31_final.stac-item
2021-08-17 12:03:43	ga_s2am_ard_3-2-1_50KLB_2021-08-17_final.stac-item
2021-08-21 11:44:12	ga_s2am_ard_3-2-1_50KPV_2021-08-21_final.stac-item
2021-08-31 11:43:05	ga_s2am_ard_3-2-1_50KRD_2021-08-31_final.stac-item
2021-09-03 11:52:21	ga_s2am_ard_3-2-1_50KQG_2021-09-03_final
2021-09-07 11:36:34	ga_s2am_ard_3-2-1_51HVD_2021-09-07_final.stac-item
2021-09-21 11:17:01	ga_s2am_ard_3-2-1_51HWC_2021-09-21_final
2021-10-03 11:53:08	ga_s2am_ard_3-2-1_50KQD_2021-10-03_final
2021-12-12 11:56:03	ga_s2am_ard_3-2-1_50JNM_2021-12-12_final.stac-item
2022-01-31 11:57:06	ga_s2am_ard_3-2-1_50HMH_2022-01-31_final.stac-item
2022-07-27 11:46:58	ga_s2am_ard_3-2-1_50HPJ_2022-07-27_final.stac-item
2022-09-02 11:36:22	ga_s2am_ard_3-2-1_51JVF_2022-09-02_final.stac-item
2022-09-15 11:46:06	ga_s2am_ard_3-2-1_51JTG_2022-09-15_final.stac-item
2022-12-27 11:55:58	ga_s2am_ard_3-2-1_50JKN_2022-12-27_final.stac-item
2023-02-02 11:47:12	ga_s2am_ard_3-2-1_50HNH_2023-02-02_final
2023-03-01 11:37:15	ga_s2am_ard_3-2-1_50HQG_2023-03-01_final
2023-04-26 11:55:59	ga_s2am_ard_3-2-1_50JKN_2023-04-26_final
2023-04-29 12:03:45	ga_s2am_ard_3-2-1_49KHS_2023-04-29_final
2023-05-14 11:16:59	ga_s2am_ard_3-2-1_51HWC_2023-05-14_final
2023-06-21 12:15:00	ga_s2am_ard_3-2-1_49JGM_2023-06-21_final
2023-07-31 12:13:45	ga_s2am_ard_3-2-1_50KKB_2023-07-31_final
2023-09-09 12:15:01	ga_s2am_ard_3-2-1_49JGM_2023-09-09_final
2023-09-27 11:36:12	ga_s2am_ard_3-2-1_51JVF_2023-09-27_final
2023-09-30 11:47:29	ga_s2am_ard_3-2-1_50HLG_2023-09-30_final
2023-10-03 11:56:27	ga_s2am_ard_3-2-1_50JLL_2023-10-03_final
2023-11-22 11:52:16	ga_s2am_ard_3-2-1_50KQG_2023-11-22_final
2023-11-30 11:16:50	ga_s2am_ard_3-2-1_51HXC_2023-11-30_final
2024-04-16 12:14:59	ga_s2am_ard_3-2-1_49JGM_2024-04-16_final
2024-05-10 11:52:22	ga_s2am_ard_3-2-1_50KQG_2024-05-10_interim

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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