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
2015-12-17 12:07:19	ga_s2am_ard_3-2-1_49JGK_2015-12-17_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50KMC_2016-01-03_final.stac-item
2016-03-06 12:04:37	ga_s2am_ard_3-2-1_49JGL_2016-03-06_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50KQB_2016-04-19_final.stac-item
2016-04-25 12:04:45	ga_s2am_ard_3-2-1_49JGN_2016-04-25_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JNM_2016-04-29_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50KKB_2016-05-15_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49JGN_2016-05-18_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JPQ_2016-05-22_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_50HPJ_2016-06-05_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_50HPG_2016-06-18_final
2016-07-31 11:56:12	ga_s2am_ard_3-2-1_50JMM_2016-07-31_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JNL_2016-10-29_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49JGL_2016-12-24_final.stac-item
2017-01-20 12:02:52	ga_s2am_ard_3-2-1_50KLC_2017-01-20_final.stac-item
2017-01-24 11:44:18	ga_s2am_ard_3-2-1_50HLH_2017-01-24_final.stac-item
2017-02-13 11:44:16	ga_s2am_ard_3-2-1_50HMK_2017-02-13_final.stac-item
2017-06-13 11:43:06	ga_s2am_ard_3-2-1_50JPQ_2017-06-13_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50KKB_2017-09-27_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50JRT_2017-12-10_final.stac-item
2018-04-02 11:53:50	ga_s2am_ard_3-2-1_50HNK_2018-04-02_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_49JGJ_2018-06-24_final.stac-item
2018-12-28 11:56:44	ga_s2am_ard_3-2-1_50HMJ_2018-12-28_final.stac-item
2019-02-02 12:14:24	ga_s2am_ard_3-2-1_49KGP_2019-02-02_final.stac-item
2019-02-09 12:04:57	ga_s2am_ard_3-2-1_49JGM_2019-02-09_final.stac-item
2019-04-04 11:46:23	ga_s2am_ard_3-2-1_50JNL_2019-04-04_final.stac-item
2019-09-04 11:56:14	ga_s2am_ard_3-2-1_50JKM_2019-09-04_final.stac-item
2019-09-04 11:56:18	ga_s2am_ard_3-2-1_50JNL_2019-09-04_final.stac-item
2019-11-06 12:03:26	ga_s2am_ard_3-2-1_50KMC_2019-11-06_final.stac-item
2019-12-07 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2019-12-07_final.stac-item
2020-01-18 12:13:48	ga_s2am_ard_3-2-1_50KKA_2020-01-18_final.stac-item
2020-01-19 11:43:27	ga_s2am_ard_3-2-1_50KRB_2020-01-19_final.stac-item
2020-02-11 11:56:47	ga_s2am_ard_3-2-1_50HLJ_2020-02-11_final.stac-item
2020-03-25 12:04:57	ga_s2am_ard_3-2-1_49JGM_2020-03-25_final.stac-item
2020-04-04 12:04:21	ga_s2am_ard_3-2-1_50KLU_2020-04-04_final.stac-item
2020-04-18 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2020-04-18_final.stac-item
2020-04-21 11:53:18	ga_s2am_ard_3-2-1_50KQC_2020-04-21_final.stac-item
2020-06-07 11:46:44	ga_s2am_ard_3-2-1_50HNK_2020-06-07_final.stac-item
2020-06-23 12:05:35	ga_s2am_ard_3-2-1_49JGK_2020-06-23_final.stac-item
2020-06-26 12:14:00	ga_s2am_ard_3-2-1_50KKA_2020-06-26_final.stac-item
2020-07-06 12:13:59	ga_s2am_ard_3-2-1_50KKA_2020-07-06_final.stac-item
2020-07-16 12:13:59	ga_s2am_ard_3-2-1_50KKA_2020-07-16_final.stac-item
2020-09-05 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2020-09-05_final.stac-item
2020-09-12 11:36:42	ga_s2am_ard_3-2-1_50HPK_2020-09-12_final.stac-item
2020-10-11 12:03:50	ga_s2am_ard_3-2-1_50KKB_2020-10-11_final.stac-item
2020-10-11 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2020-10-11_final.stac-item
2020-10-21 12:05:32	ga_s2am_ard_3-2-1_50JKQ_2020-10-21_final.stac-item
2020-12-13 12:14:42	ga_s2am_ard_3-2-1_49JFN_2020-12-13_final.stac-item
2020-12-17 11:56:49	ga_s2am_ard_3-2-1_50HMJ_2020-12-17_final.stac-item
2021-01-02 12:13:54	ga_s2am_ard_3-2-1_50KKA_2021-01-02_final.stac-item
2021-01-02 12:14:56	ga_s2am_ard_3-2-1_49JGM_2021-01-02_final.stac-item
2021-01-02 12:15:11	ga_s2am_ard_3-2-1_49JGL_2021-01-02_final.stac-item
2021-01-16 11:56:52	ga_s2am_ard_3-2-1_50HMJ_2021-01-16_final.stac-item
2021-01-29 12:03:59	ga_s2am_ard_3-2-1_49KHR_2021-01-29_final.stac-item
2021-03-03 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2021-03-03_final.stac-item
2021-03-30 12:03:57	ga_s2am_ard_3-2-1_49KHR_2021-03-30_final.stac-item
2021-04-02 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2021-04-02_final.stac-item
2021-06-18 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-06-18_final.stac-item
2021-07-18 12:04:31	ga_s2am_ard_3-2-1_50KKU_2021-07-18_final.stac-item
2021-07-21 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-07-21_final.stac-item
2021-08-17 12:06:07	ga_s2am_ard_3-2-1_50JLM_2021-08-17_final.stac-item
2021-08-28 11:36:40	ga_s2am_ard_3-2-1_50HPK_2021-08-28_final.stac-item
2021-10-03 11:56:09	ga_s2am_ard_3-2-1_50JNM_2021-10-03_final.stac-item
2021-10-06 12:03:49	ga_s2am_ard_3-2-1_50KKB_2021-10-06_final.stac-item
2021-11-02 11:52:38	ga_s2am_ard_3-2-1_50KQF_2021-11-02_final
2022-01-07 12:14:00	ga_s2am_ard_3-2-1_49KGR_2022-01-07_final.stac-item
2022-02-10 11:53:23	ga_s2am_ard_3-2-1_50KNC_2022-02-10_final.stac-item
2022-03-12 11:53:14	ga_s2am_ard_3-2-1_50KRC_2022-03-12_final.stac-item
2022-04-01 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2022-04-01_final.stac-item
2022-05-18 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2022-05-18_final.stac-item
2022-05-21 11:56:32	ga_s2am_ard_3-2-1_50JLL_2022-05-21_final.stac-item
2022-06-13 12:04:45	ga_s2am_ard_3-2-1_49KGP_2022-06-13_final.stac-item
2022-06-20 11:56:34	ga_s2am_ard_3-2-1_50JML_2022-06-20_final.stac-item
2022-07-30 11:56:32	ga_s2am_ard_3-2-1_50JML_2022-07-30_final.stac-item
2022-09-01 12:04:43	ga_s2am_ard_3-2-1_49KGP_2022-09-01_final.stac-item
2022-09-01 12:05:56	ga_s2am_ard_3-2-1_49JGJ_2022-09-01_final.stac-item
2022-09-11 12:05:54	ga_s2am_ard_3-2-1_49JGJ_2022-09-11_final.stac-item
2022-09-25 11:46:30	ga_s2am_ard_3-2-1_50JNL_2022-09-25_final.stac-item
2022-10-11 12:03:50	ga_s2am_ard_3-2-1_50KKB_2022-10-11_final.stac-item
2022-12-10 12:03:45	ga_s2am_ard_3-2-1_50KKB_2022-12-10_final.stac-item
2023-01-26 11:56:48	ga_s2am_ard_3-2-1_50HMJ_2023-01-26_final.stac-item
2023-02-18 12:04:57	ga_s2am_ard_3-2-1_49JGM_2023-02-18_nrt.stac-item
2023-04-03 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2023-04-03_final
2023-05-29 12:05:18	ga_s2am_ard_3-2-1_49JGL_2023-05-29_final
2023-06-08 12:03:48	ga_s2am_ard_3-2-1_50KKB_2023-06-08_final
2023-06-22 11:46:26	ga_s2am_ard_3-2-1_50JNL_2023-06-22_final
2023-07-05 11:56:31	ga_s2am_ard_3-2-1_50JLL_2023-07-05_final
2023-07-25 11:55:54	ga_s2am_ard_3-2-1_50JNN_2023-07-25_final
2023-08-04 11:53:16	ga_s2am_ard_3-2-1_50KRC_2023-08-04_final
2023-08-21 11:47:12	ga_s2am_ard_3-2-1_50HNH_2023-08-21_final
2023-09-03 11:55:47	ga_s2am_ard_3-2-1_50JLP_2023-09-03_final
2023-09-03 11:56:13	ga_s2am_ard_3-2-1_50JMM_2023-09-03_final
2023-10-03 11:56:09	ga_s2am_ard_3-2-1_50JMM_2023-10-03_final
2023-10-13 11:55:53	ga_s2am_ard_3-2-1_50JMN_2023-10-13_final
2023-11-15 12:05:39	ga_s2am_ard_3-2-1_50JKP_2023-11-15_final
2024-01-11 11:56:25	ga_s2am_ard_3-2-1_50HNK_2024-01-11_final
2024-02-13 12:03:41	ga_s2am_ard_3-2-1_50KKB_2024-02-13_final
2024-03-01 11:56:25	ga_s2am_ard_3-2-1_50JLL_2024-03-01_final
2024-03-08 11:46:16	ga_s2am_ard_3-2-1_50JQL_2024-03-08_final
2024-04-30 11:56:03	ga_s2am_ard_3-2-1_50JKN_2024-04-30_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