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
2015-11-24 11:56:24	ga_s2am_ard_3-2-1_50HLK_2015-11-24_final.stac-item
2015-12-27 12:05:25	ga_s2am_ard_3-2-1_50JKS_2015-12-27_final.stac-item
2016-01-03 11:57:46	ga_s2am_ard_3-2-1_50HMJ_2016-01-03_final.stac-item
2016-01-13 11:56:42	ga_s2am_ard_3-2-1_50HLK_2016-01-13_final.stac-item
2016-04-15 11:55:08	ga_s2am_ard_3-2-1_50KKB_2016-04-15_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JQP_2016-05-29_final.stac-item
2016-06-24 12:02:50	ga_s2am_ard_3-2-1_50JKP_2016-06-24_final.stac-item
2016-06-27 12:13:22	ga_s2am_ard_3-2-1_50KKA_2016-06-27_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JKN_2016-07-01_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50JPS_2016-07-01_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50KKB_2016-08-23_final.stac-item
2016-10-02 12:02:45	ga_s2am_ard_3-2-1_50KMC_2016-10-02_final.stac-item
2016-12-08 11:55:28	ga_s2am_ard_3-2-1_50HLJ_2016-12-08_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50JNN_2017-03-25_final.stac-item
2017-05-31 11:35:01	ga_s2am_ard_3-2-1_50HQJ_2017-05-31_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50HNK_2017-12-03_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49KHR_2018-02-17_final.stac-item
2018-02-18 11:42:05	ga_s2am_ard_3-2-1_50JRS_2018-02-18_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_50HPK_2018-03-10_final.stac-item
2018-03-26 12:02:47	ga_s2am_ard_3-2-1_50KLU_2018-03-26_final.stac-item
2018-04-05 12:02:49	ga_s2am_ard_3-2-1_50KMB_2018-04-05_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_49KHR_2018-04-05_final.stac-item
2018-04-19 11:46:08	ga_s2am_ard_3-2-1_50HMK_2018-04-19_final.stac-item
2018-05-18 12:13:23	ga_s2am_ard_3-2-1_50KKA_2018-05-18_final.stac-item
2018-05-22 11:53:30	ga_s2am_ard_3-2-1_50KMV_2018-05-22_final.stac-item
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_49KGR_2018-06-27_final.stac-item
2018-06-27 12:13:22	ga_s2am_ard_3-2-1_50KKA_2018-06-27_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49JGL_2018-07-14_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNM_2018-07-21_final.stac-item
2018-08-10 11:51:15	ga_s2am_ard_3-2-1_50JLN_2018-08-10_final.stac-item
2018-11-25 11:45:24	ga_s2am_ard_3-2-1_50JQP_2018-11-25_final.stac-item
2019-01-17 11:56:36	ga_s2am_ard_3-2-1_50HLK_2019-01-17_final.stac-item
2019-02-26 11:56:18	ga_s2am_ard_3-2-1_50JML_2019-02-26_final.stac-item
2019-04-04 11:46:38	ga_s2am_ard_3-2-1_50HNK_2019-04-04_final.stac-item
2019-05-07 11:56:15	ga_s2am_ard_3-2-1_50JLM_2019-05-07_final.stac-item
2019-06-06 11:56:06	ga_s2am_ard_3-2-1_50JNM_2019-06-06_final.stac-item
2019-06-20 11:37:07	ga_s2am_ard_3-2-1_50HQH_2019-06-20_final.stac-item
2019-07-22 12:15:01	ga_s2am_ard_3-2-1_49JGM_2019-07-22_final.stac-item
2019-08-11 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2019-08-11_final.stac-item
2019-08-25 11:55:58	ga_s2am_ard_3-2-1_50JLN_2019-08-25_final.stac-item
2019-09-08 11:37:06	ga_s2am_ard_3-2-1_50HPH_2019-09-08_final.stac-item
2019-09-11 11:46:39	ga_s2am_ard_3-2-1_50HMK_2019-09-11_final.stac-item
2019-10-01 11:46:53	ga_s2am_ard_3-2-1_50HNJ_2019-10-01_final.stac-item
2019-11-09 12:14:29	ga_s2am_ard_3-2-1_49KGP_2019-11-09_final.stac-item
2019-12-26 12:04:34	ga_s2am_ard_3-2-1_50JLT_2019-12-26_final.stac-item
2020-01-02 11:56:05	ga_s2am_ard_3-2-1_50JLM_2020-01-02_final.stac-item
2020-01-12 11:54:46	ga_s2am_ard_3-2-1_50JNS_2020-01-12_final.stac-item
2020-01-12 11:55:51	ga_s2am_ard_3-2-1_50JLN_2020-01-12_final.stac-item
2020-01-15 12:03:46	ga_s2am_ard_3-2-1_50KMA_2020-01-15_final.stac-item
2020-03-12 11:54:04	ga_s2am_ard_3-2-1_50KNV_2020-03-12_final.stac-item
2020-04-24 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2020-04-24_final.stac-item
2020-06-23 12:05:35	ga_s2am_ard_3-2-1_49JGK_2020-06-23_final.stac-item
2020-06-30 11:56:23	ga_s2am_ard_3-2-1_50JNL_2020-06-30_final.stac-item
2020-08-12 12:03:47	ga_s2am_ard_3-2-1_50KLB_2020-08-12_final.stac-item
2020-09-28 11:55:58	ga_s2am_ard_3-2-1_50JMN_2020-09-28_final.stac-item
2020-10-31 12:04:04	ga_s2am_ard_3-2-1_49KHR_2020-10-31_final.stac-item
2021-01-03 11:44:38	ga_s2am_ard_3-2-1_50JPT_2021-01-03_final.stac-item
2021-01-06 11:56:41	ga_s2am_ard_3-2-1_50HLK_2021-01-06_final.stac-item
2021-01-19 12:05:42	ga_s2am_ard_3-2-1_50JKP_2021-01-19_final.stac-item
2021-07-08 12:03:26	ga_s2am_ard_3-2-1_50KMC_2021-07-08_final.stac-item
2021-08-11 11:46:28	ga_s2am_ard_3-2-1_50JML_2021-08-11_final.stac-item
2021-08-30 12:14:20	ga_s2am_ard_3-2-1_50KKU_2021-08-30_final.stac-item
2021-09-26 12:04:31	ga_s2am_ard_3-2-1_49KHP_2021-09-26_final.stac-item
2021-10-10 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2021-10-10_final.stac-item
2021-10-19 12:15:16	ga_s2am_ard_3-2-1_49JGL_2021-10-19_final.stac-item
2021-12-29 11:47:22	ga_s2am_ard_3-2-1_50HNG_2021-12-29_final
2022-01-01 11:56:01	ga_s2am_ard_3-2-1_50JKN_2022-01-01_final.stac-item
2022-01-27 12:15:10	ga_s2am_ard_3-2-1_49JGL_2022-01-27_final.stac-item
2022-02-07 11:44:30	ga_s2am_ard_3-2-1_50JRT_2022-02-07_final.stac-item
2022-02-14 11:36:20	ga_s2am_ard_3-2-1_50JQL_2022-02-14_final.stac-item
2022-04-24 12:04:04	ga_s2am_ard_3-2-1_49KHR_2022-04-24_final.stac-item
2022-06-03 12:05:08	ga_s2am_ard_3-2-1_49JGM_2022-06-03_final.stac-item
2022-07-06 12:15:09	ga_s2am_ard_3-2-1_49JGM_2022-07-06_final.stac-item
2022-07-30 11:53:31	ga_s2am_ard_3-2-1_50KPC_2022-07-30_final.stac-item
2022-10-15 11:46:52	ga_s2am_ard_3-2-1_50HPJ_2022-10-15_final.stac-item
2022-10-28 11:56:58	ga_s2am_ard_3-2-1_50HLJ_2022-10-28_final.stac-item
2022-11-24 11:47:02	ga_s2am_ard_3-2-1_50HPH_2022-11-24_final.stac-item
2022-12-07 11:55:57	ga_s2am_ard_3-2-1_50JLN_2022-12-07_final.stac-item
2023-01-23 11:44:30	ga_s2am_ard_3-2-1_50JQT_2023-01-23_final.stac-item
2023-02-18 12:05:38	ga_s2am_ard_3-2-1_50JKP_2023-02-18_nrt.stac-item
2023-02-22 11:45:44	ga_s2am_ard_3-2-1_50JQN_2023-02-22_nrt.stac-item
2023-04-19 12:04:12	ga_s2am_ard_3-2-1_50KKV_2023-04-19_final
2023-04-29 12:06:10	ga_s2am_ard_3-2-1_50JKM_2023-04-29_final
2023-05-23 11:47:09	ga_s2am_ard_3-2-1_50HNH_2023-05-23_final
2023-08-10 12:14:17	ga_s2am_ard_3-2-1_49KGQ_2023-08-10_final
2023-09-06 12:03:46	ga_s2am_ard_3-2-1_50KLB_2023-09-06_final
2023-09-06 12:04:04	ga_s2am_ard_3-2-1_50KKA_2023-09-06_final
2023-09-06 12:04:33	ga_s2am_ard_3-2-1_50KKU_2023-09-06_final
2023-09-29 12:13:56	ga_s2am_ard_3-2-1_50KKA_2023-09-29_final
2023-10-29 12:14:59	ga_s2am_ard_3-2-1_49JFM_2023-10-29_final
2023-12-22 11:56:14	ga_s2am_ard_3-2-1_50JNL_2023-12-22_final
2024-01-24 12:03:34	ga_s2am_ard_3-2-1_50KLB_2024-01-24_final
2024-01-31 11:55:55	ga_s2am_ard_3-2-1_50JKN_2024-01-31_final
2024-02-23 12:04:11	ga_s2am_ard_3-2-1_49KHQ_2024-02-23_final
2024-03-08 11:46:38	ga_s2am_ard_3-2-1_50HNK_2024-03-08_final
2024-03-08 11:46:48	ga_s2am_ard_3-2-1_50HPJ_2024-03-08_final
2024-03-27 12:14:57	ga_s2am_ard_3-2-1_49JGM_2024-03-27_final
2024-03-31 11:55:45	ga_s2am_ard_3-2-1_50JKP_2024-03-31_final
2024-05-13 12:04:31	ga_s2am_ard_3-2-1_49KHP_2024-05-13_final
2024-05-27 11:47:03	ga_s2am_ard_3-2-1_50HPH_2024-05-27_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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