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 11:54:02	ga_s2am_ard_3-2-1_50JLP_2015-11-14_final.stac-item
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50KNC_2016-02-02_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_50KKB_2016-02-15_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50JNN_2016-02-19_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50JNM_2016-08-10_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_50KKA_2016-09-15_final.stac-item
2016-10-23 11:29:20	ga_s2am_ard_3-2-1_50HQG_2016-10-23_final
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JLL_2016-10-29_final.stac-item
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50HLG_2016-11-18_final
2017-03-05 11:37:45	ga_s2am_ard_3-2-1_50KRC_2017-03-05_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_49JGL_2017-03-21_final.stac-item
2017-04-21 11:34:59	ga_s2am_ard_3-2-1_50HPJ_2017-04-21_final.stac-item
2017-07-09 12:02:49	ga_s2am_ard_3-2-1_50JLM_2017-07-09_final.stac-item
2017-07-10 11:34:59	ga_s2am_ard_3-2-1_50HQJ_2017-07-10_final.stac-item
2017-07-16 11:49:46	ga_s2am_ard_3-2-1_50JMN_2017-07-16_final.stac-item
2017-08-28 12:04:42	ga_s2am_ard_3-2-1_50JKS_2017-08-28_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_50JKR_2017-09-07_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50JLP_2017-09-27_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_50KLB_2017-11-26_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JMM_2017-12-03_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JMN_2017-12-03_final.stac-item
2017-12-13 11:56:02	ga_s2am_ard_3-2-1_50JNM_2017-12-13_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_49JGK_2017-12-16_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_50JQM_2018-05-06_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_50HQH_2018-05-16_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_50KKA_2018-05-18_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKB_2018-07-14_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_51HTD_2018-08-04_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JMP_2018-08-30_final.stac-item
2018-10-29 11:49:24	ga_s2am_ard_3-2-1_50KPC_2018-10-29_final.stac-item
2019-01-18 11:27:03	ga_s2am_ard_3-2-1_51HTC_2019-01-18_final.stac-item
2019-01-23 12:14:53	ga_s2am_ard_3-2-1_49JGM_2019-01-23_final.stac-item
2019-02-16 11:53:14	ga_s2am_ard_3-2-1_50KQC_2019-02-16_final.stac-item
2019-04-14 11:46:28	ga_s2am_ard_3-2-1_50JML_2019-04-14_final.stac-item
2019-05-10 12:04:03	ga_s2am_ard_3-2-1_49KHR_2019-05-10_final.stac-item
2019-07-16 11:56:09	ga_s2am_ard_3-2-1_50JNM_2019-07-16_final.stac-item
2019-08-08 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2019-08-08_final.stac-item
2019-08-29 11:36:39	ga_s2am_ard_3-2-1_50HPK_2019-08-29_final.stac-item
2019-10-08 11:36:51	ga_s2am_ard_3-2-1_50HQJ_2019-10-08_final.stac-item
2019-11-17 11:37:02	ga_s2am_ard_3-2-1_51HTC_2019-11-17_final.stac-item
2019-12-03 11:55:58	ga_s2am_ard_3-2-1_50JKN_2019-12-03_final.stac-item
2020-01-09 11:46:10	ga_s2am_ard_3-2-1_50JQL_2020-01-09_final.stac-item
2020-03-05 12:03:19	ga_s2am_ard_3-2-1_50KMC_2020-03-05_final.stac-item
2020-03-09 11:43:14	ga_s2am_ard_3-2-1_50KRC_2020-03-09_final.stac-item
2020-03-18 12:13:51	ga_s2am_ard_3-2-1_49KHR_2020-03-18_final.stac-item
2020-03-19 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2020-03-19_final.stac-item
2020-04-18 11:46:38	ga_s2am_ard_3-2-1_50HNK_2020-04-18_final.stac-item
2020-05-15 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2020-05-15_final.stac-item
2020-06-03 12:05:44	ga_s2am_ard_3-2-1_50JLP_2020-06-03_final.stac-item
2020-07-04 11:36:51	ga_s2am_ard_3-2-1_51HTD_2020-07-04_final.stac-item
2020-07-17 11:44:57	ga_s2am_ard_3-2-1_50JPS_2020-07-17_final.stac-item
2020-08-12 12:04:05	ga_s2am_ard_3-2-1_49KHR_2020-08-12_final.stac-item
2020-10-21 12:05:17	ga_s2am_ard_3-2-1_50JKR_2020-10-21_final.stac-item
2020-11-30 12:04:57	ga_s2am_ard_3-2-1_49JHM_2020-11-30_final.stac-item
2021-01-10 11:36:20	ga_s2am_ard_3-2-1_50JQL_2021-01-10_final.stac-item
2021-01-29 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-01-29_final.stac-item
2021-02-15 11:53:23	ga_s2am_ard_3-2-1_50KNC_2021-02-15_final.stac-item
2021-03-30 12:04:11	ga_s2am_ard_3-2-1_50KKV_2021-03-30_final.stac-item
2021-05-23 11:46:43	ga_s2am_ard_3-2-1_50HQJ_2021-05-23_final.stac-item
2021-06-05 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-06-05_final
2021-07-18 12:04:02	ga_s2am_ard_3-2-1_49KHR_2021-07-18_final.stac-item
2021-07-18 12:04:46	ga_s2am_ard_3-2-1_50JKT_2021-07-18_final.stac-item
2021-07-19 11:36:23	ga_s2am_ard_3-2-1_50JQL_2021-07-19_final.stac-item
2021-07-25 11:54:51	ga_s2am_ard_3-2-1_50JPS_2021-07-25_final.stac-item
2021-11-29 11:46:19	ga_s2am_ard_3-2-1_50JPL_2021-11-29_final.stac-item
2022-01-05 11:36:35	ga_s2am_ard_3-2-1_50HQK_2022-01-05_final.stac-item
2022-01-18 11:43:37	ga_s2am_ard_3-2-1_50KQB_2022-01-18_final.stac-item
2022-02-20 11:54:24	ga_s2am_ard_3-2-1_50KNU_2022-02-20_final.stac-item
2022-02-27 11:46:46	ga_s2am_ard_3-2-1_50HQJ_2022-02-27_final.stac-item
2022-03-05 12:04:02	ga_s2am_ard_3-2-1_50KKA_2022-03-05_final.stac-item
2022-04-24 12:05:02	ga_s2am_ard_3-2-1_49JHM_2022-04-24_final.stac-item
2022-05-11 11:54:58	ga_s2am_ard_3-2-1_50JMS_2022-05-11_final.stac-item
2022-05-28 11:46:45	ga_s2am_ard_3-2-1_50HNK_2022-05-28_final.stac-item
2022-07-24 11:36:57	ga_s2am_ard_3-2-1_51HTD_2022-07-24_final.stac-item
2022-08-13 11:34:49	ga_s2am_ard_3-2-1_50JRT_2022-08-13_final.stac-item
2022-10-24 12:14:44	ga_s2am_ard_3-2-1_49JGN_2022-10-24_final.stac-item
2022-11-10 12:03:27	ga_s2am_ard_3-2-1_50KMC_2022-11-10_final.stac-item
2022-11-20 12:04:32	ga_s2am_ard_3-2-1_49KGP_2022-11-20_final.stac-item
2022-12-04 11:46:16	ga_s2am_ard_3-2-1_50JQL_2022-12-04_final.stac-item
2023-01-16 11:53:17	ga_s2am_ard_3-2-1_50KPC_2023-01-16_final.stac-item
2023-02-15 11:56:23	ga_s2am_ard_3-2-1_50JLL_2023-02-15_nrt.stac-item
2023-02-15 11:56:23	ga_s2am_ard_3-2-1_50JLL_2023-02-15_final
2023-03-10 12:05:59	ga_s2am_ard_3-2-1_50JLM_2023-03-10_final
2023-04-19 12:04:30	ga_s2am_ard_3-2-1_49KGP_2023-04-19_final
2023-06-05 11:53:25	ga_s2am_ard_3-2-1_50KPC_2023-06-05_final
2023-06-22 11:46:41	ga_s2am_ard_3-2-1_50HNK_2023-06-22_final
2023-07-08 12:04:04	ga_s2am_ard_3-2-1_50KKA_2023-07-08_final
2023-07-25 11:55:54	ga_s2am_ard_3-2-1_50JNN_2023-07-25_final
2023-08-01 11:46:21	ga_s2am_ard_3-2-1_50JQL_2023-08-01_final
2023-08-24 11:57:05	ga_s2am_ard_3-2-1_50HMH_2023-08-24_final
2023-09-06 12:04:04	ga_s2am_ard_3-2-1_49KHR_2023-09-06_final
2023-10-21 12:50:59	ga_s2am_ard_3-2-1_48LWP_2023-10-21_final
2023-12-06 11:35:44	ga_s2am_ard_3-2-1_50JQN_2023-12-06_final
2023-12-22 11:56:07	ga_s2am_ard_3-2-1_50JLM_2023-12-22_final
2023-12-25 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-12-25_final
2024-02-10 11:53:17	ga_s2am_ard_3-2-1_50KPC_2024-02-10_final
2024-02-13 12:04:58	ga_s2am_ard_3-2-1_49JGM_2024-02-13_final
2024-02-27 11:46:37	ga_s2am_ard_3-2-1_50HNK_2024-02-27_final
2024-03-08 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2024-03-08_final
2024-04-27 11:47:26	ga_s2am_ard_3-2-1_50HMG_2024-04-27_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

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