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
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50KPB_2015-12-04_final.stac-item
2016-07-15 11:32:03	ga_s2am_ard_3-2-1_51KXV_2016-07-15_final.stac-item
2016-10-07 11:12:10	ga_s2am_ard_3-2-1_52KDE_2016-10-07_final.stac-item
2016-12-30 10:53:16	ga_s2am_ard_3-2-1_52JGN_2016-12-30_final.stac-item
2017-01-16 10:43:08	ga_s2am_ard_3-2-1_53JMM_2017-01-16_final.stac-item
2017-02-24 11:12:09	ga_s2am_ard_3-2-1_52KCA_2017-02-24_final.stac-item
2017-03-19 11:20:49	ga_s2am_ard_3-2-1_51JWG_2017-03-19_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49JGK_2017-03-31_final.stac-item
2017-05-18 11:21:00	ga_s2am_ard_3-2-1_52LBH_2017-05-18_final.stac-item
2017-07-24 11:12:03	ga_s2am_ard_3-2-1_52JCT_2017-07-24_final.stac-item
2017-08-14 10:43:08	ga_s2am_ard_3-2-1_53JLK_2017-08-14_final.stac-item
2017-10-25 11:21:08	ga_s2am_ard_3-2-1_52LBH_2017-10-25_final.stac-item
2017-11-15 10:53:13	ga_s2am_ard_3-2-1_52JFN_2017-11-15_final.stac-item
2017-12-16 12:02:44	ga_s2am_ard_3-2-1_50JLT_2017-12-16_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KPB_2018-01-12_final.stac-item
2018-03-13 11:52:23	ga_s2am_ard_3-2-1_50JMR_2018-03-13_final.stac-item
2018-03-20 11:44:19	ga_s2am_ard_3-2-1_50JQR_2018-03-20_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_51KTQ_2018-06-08_final.stac-item
2018-07-06 10:57:17	ga_s2am_ard_3-2-1_52KHG_2018-07-06_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_51KTS_2018-09-06_final.stac-item
2018-09-08 10:37:24	ga_s2am_ard_3-2-1_53JMJ_2018-09-08_final.stac-item
2018-10-09 11:51:12	ga_s2am_ard_3-2-1_50KNA_2018-10-09_final.stac-item
2018-10-15 10:27:05	ga_s2am_ard_3-2-1_53JPK_2018-10-15_final.stac-item
2018-12-06 11:16:14	ga_s2am_ard_3-2-1_51HYE_2018-12-06_final.stac-item
2019-01-07 11:53:34	ga_s2am_ard_3-2-1_50KNB_2019-01-07_final.stac-item
2019-03-09 11:21:48	ga_s2am_ard_3-2-1_52LBH_2019-03-09_final.stac-item
2019-05-22 11:01:59	ga_s2am_ard_3-2-1_53KKB_2019-05-22_final.stac-item
2019-05-28 11:22:25	ga_s2am_ard_3-2-1_52KBF_2019-05-28_final.stac-item
2019-06-11 11:03:01	ga_s2am_ard_3-2-1_52KGC_2019-06-11_final.stac-item
2019-06-27 11:21:58	ga_s2am_ard_3-2-1_52LBH_2019-06-27_final.stac-item
2019-07-16 11:54:13	ga_s2am_ard_3-2-1_50KNV_2019-07-16_final.stac-item
2019-09-03 10:44:10	ga_s2am_ard_3-2-1_53JMN_2019-09-03_final.stac-item
2019-09-04 11:53:53	ga_s2am_ard_3-2-1_50KNA_2019-09-04_final.stac-item
2019-09-21 11:43:33	ga_s2am_ard_3-2-1_50KRB_2019-09-21_final.stac-item
2019-11-05 10:54:00	ga_s2am_ard_3-2-1_52KHU_2019-11-05_final.stac-item
2019-11-13 11:55:08	ga_s2am_ard_3-2-1_50JNR_2019-11-13_final.stac-item
2020-01-24 10:53:07	ga_s2am_ard_3-2-1_53KKS_2020-01-24_final.stac-item
2020-03-14 10:54:40	ga_s2am_ard_3-2-1_52JGR_2020-03-14_final.stac-item
2020-04-29 11:13:54	ga_s2am_ard_3-2-1_52KCV_2020-04-29_final.stac-item
2020-05-08 11:44:06	ga_s2am_ard_3-2-1_51KTQ_2020-05-08_final.stac-item
2020-06-10 11:54:14	ga_s2am_ard_3-2-1_50KNV_2020-06-10_final.stac-item
2020-09-02 11:35:06	ga_s2am_ard_3-2-1_51JUL_2020-09-02_final.stac-item
2020-09-07 10:44:14	ga_s2am_ard_3-2-1_53JMN_2020-09-07_final.stac-item
2020-11-24 11:45:19	ga_s2am_ard_3-2-1_50JQQ_2020-11-24_final.stac-item
2020-12-13 10:34:18	ga_s2am_ard_3-2-1_53JPM_2020-12-13_final.stac-item
2020-12-17 11:53:51	ga_s2am_ard_3-2-1_50KNA_2020-12-17_final.stac-item
2021-02-16 11:22:07	ga_s2am_ard_3-2-1_52KBG_2021-02-16_final.stac-item
2021-02-22 11:45:17	ga_s2am_ard_3-2-1_50JQQ_2021-02-22_final.stac-item
2021-03-01 11:36:46	ga_s2am_ard_3-2-1_51HTD_2021-03-01_final.stac-item
2021-03-14 11:44:34	ga_s2am_ard_3-2-1_50JQT_2021-03-14_final.stac-item
2021-04-22 10:33:59	ga_s2am_ard_3-2-1_53JQN_2021-04-22_final.stac-item
2021-04-29 12:04:25	ga_s2am_ard_3-2-1_50KKU_2021-04-29_final.stac-item
2021-04-29 12:04:37	ga_s2am_ard_3-2-1_50JLT_2021-04-29_final.stac-item
2021-05-13 11:44:01	ga_s2am_ard_3-2-1_51KTQ_2021-05-13_final.stac-item
2021-06-07 10:52:13	ga_s2am_ard_3-2-1_53KLA_2021-06-07_final.stac-item
2021-07-02 11:44:04	ga_s2am_ard_3-2-1_51KTQ_2021-07-02_final.stac-item
2021-07-20 11:05:52	ga_s2am_ard_3-2-1_52JDM_2021-07-20_final.stac-item
2021-07-26 11:26:00	ga_s2am_ard_3-2-1_51JWG_2021-07-26_final.stac-item
2021-08-04 11:55:42	ga_s2am_ard_3-2-1_50JMP_2021-08-04_final.stac-item
2021-09-21 11:11:51	ga_s2am_ard_3-2-1_52LEH_2021-09-21_final.stac-item
2021-09-22 10:44:27	ga_s2am_ard_3-2-1_53JMM_2021-09-22_final.stac-item
2021-10-13 11:54:13	ga_s2am_ard_3-2-1_50KNV_2021-10-13_final.stac-item
2021-10-16 12:04:33	ga_s2am_ard_3-2-1_50KKU_2021-10-16_final.stac-item
2021-12-11 10:44:23	ga_s2am_ard_3-2-1_53JMM_2021-12-11_final.stac-item
2022-01-31 11:55:24	ga_s2am_ard_3-2-1_50JMQ_2022-01-31_final.stac-item
2022-02-18 11:15:23	ga_s2am_ard_3-2-1_52JBP_2022-02-18_final.stac-item
2022-04-23 10:52:17	ga_s2am_ard_3-2-1_53KLA_2022-04-23_final.stac-item
2022-05-16 11:01:47	ga_s2am_ard_3-2-1_52LHH_2022-05-16_final.stac-item
2022-06-23 12:04:08	ga_s2am_ard_3-2-1_50KLA_2022-06-23_final.stac-item
2022-07-07 11:47:05	ga_s2am_ard_3-2-1_50HNJ_2022-07-07_final.stac-item
2022-11-27 11:55:23	ga_s2am_ard_3-2-1_50JMQ_2022-11-27_final.stac-item
2022-12-22 11:00:57	ga_s2am_ard_3-2-1_52LHL_2022-12-22_final.stac-item
2022-12-22 11:01:26	ga_s2am_ard_3-2-1_52LHJ_2022-12-22_final.stac-item
2023-04-15 10:44:06	ga_s2am_ard_3-2-1_53JNN_2023-04-15_final
2023-04-15 10:44:10	ga_s2am_ard_3-2-1_53JMN_2023-04-15_final
2023-04-22 10:35:36	ga_s2am_ard_3-2-1_53JNG_2023-04-22_final
2023-06-02 11:43:37	ga_s2am_ard_3-2-1_50KRB_2023-06-02_final
2023-06-21 10:35:52	ga_s2am_ard_3-2-1_53JPF_2023-06-21_final
2023-07-04 10:45:16	ga_s2am_ard_3-2-1_53JLJ_2023-07-04_final
2023-07-21 12:13:48	ga_s2am_ard_3-2-1_49KGS_2023-07-21_interim
2023-08-08 11:34:33	ga_s2am_ard_3-2-1_51JVN_2023-08-08_final
2023-08-15 11:22:29	ga_s2am_ard_3-2-1_51KZA_2023-08-15_final
2023-08-18 11:34:52	ga_s2am_ard_3-2-1_51JUM_2023-08-18_final
2023-08-25 11:20:55	ga_s2am_ard_3-2-1_52LDM_2023-08-25_nrt
2023-09-04 11:22:14	ga_s2am_ard_3-2-1_51KZB_2023-09-04_final
2023-09-11 11:11:39	ga_s2am_ard_3-2-1_52LEJ_2023-09-11_final
2023-09-18 11:02:00	ga_s2am_ard_3-2-1_52KHG_2023-09-18_final
2023-10-23 11:53:39	ga_s2am_ard_3-2-1_50KNB_2023-10-23_final
2023-11-11 10:45:10	ga_s2am_ard_3-2-1_53JLJ_2023-11-11_final
2023-11-12 11:54:07	ga_s2am_ard_3-2-1_50KNV_2023-11-12_final
2023-11-22 11:56:54	ga_s2am_ard_3-2-1_50HKJ_2023-11-22_nrt
2024-01-28 11:43:27	ga_s2am_ard_3-2-1_51KTS_2024-01-28_final
2024-01-31 11:55:19	ga_s2am_ard_3-2-1_50JMQ_2024-01-31_final
2024-02-06 12:14:27	ga_s2am_ard_3-2-1_49KFP_2024-02-06_nrt
2024-02-10 11:54:19	ga_s2am_ard_3-2-1_50KNU_2024-02-10_final
2024-02-10 11:55:20	ga_s2am_ard_3-2-1_50JMQ_2024-02-10_final
2024-02-17 11:44:00	ga_s2am_ard_3-2-1_50KRV_2024-02-17_final
2024-02-25 11:05:00	ga_s2am_ard_3-2-1_52JEQ_2024-02-25_final
2024-04-20 11:55:27	ga_s2am_ard_3-2-1_50JMQ_2024-04-20_final
2024-05-27 11:43:34	ga_s2am_ard_3-2-1_50KRB_2024-05-27_nrt

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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