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
2015-08-28 10:51:18	ga_s2am_ard_3-2-1_52KHB_2015-08-28_final
2016-03-28 11:01:10	ga_s2am_ard_3-2-1_52JDR_2016-03-28_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_51KXV_2016-10-03_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50HPJ_2016-10-26_final.stac-item
2016-12-06 11:07:09	ga_s2am_ard_3-2-1_51KZQ_2016-12-06_final.stac-item
2016-12-13 11:02:39	ga_s2am_ard_3-2-1_52JDL_2016-12-13_final.stac-item
2016-12-26 11:14:08	ga_s2am_ard_3-2-1_51JXH_2016-12-26_final.stac-item
2017-04-07 11:56:31	ga_s2am_ard_3-2-1_50HMH_2017-04-07_final.stac-item
2017-08-31 12:14:41	ga_s2am_ard_3-2-1_49JGN_2017-08-31_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_50KLV_2017-09-07_final.stac-item
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_51HUE_2017-09-08_final.stac-item
2017-09-09 11:02:57	ga_s2am_ard_3-2-1_52JCN_2017-09-09_final.stac-item
2017-10-09 11:02:09	ga_s2am_ard_3-2-1_52JDT_2017-10-09_final.stac-item
2017-11-08 11:02:57	ga_s2am_ard_3-2-1_52KGV_2017-11-08_final.stac-item
2017-12-19 12:13:16	ga_s2am_ard_3-2-1_49JFM_2017-12-19_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_52KCA_2018-02-02_final.stac-item
2018-03-11 11:12:00	ga_s2am_ard_3-2-1_51JYG_2018-03-11_final.stac-item
2018-06-05 11:26:21	ga_s2am_ard_3-2-1_51LXD_2018-06-05_final.stac-item
2018-06-11 11:48:18	ga_s2am_ard_3-2-1_50KNC_2018-06-11_final.stac-item
2018-06-13 10:47:24	ga_s2am_ard_3-2-1_52JFM_2018-06-13_final.stac-item
2018-07-22 11:25:32	ga_s2am_ard_3-2-1_51JWF_2018-07-22_final.stac-item
2018-07-26 11:06:22	ga_s2am_ard_3-2-1_52HBK_2018-07-26_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JYJ_2018-09-30_final.stac-item
2018-10-22 12:02:46	ga_s2am_ard_3-2-1_50JKT_2018-10-22_final.stac-item
2019-02-04 11:15:54	ga_s2am_ard_3-2-1_51JXG_2019-02-04_final.stac-item
2019-02-09 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2019-02-09_final.stac-item
2019-02-17 11:22:48	ga_s2am_ard_3-2-1_52KBD_2019-02-17_final.stac-item
2019-02-20 11:33:44	ga_s2am_ard_3-2-1_51KUR_2019-02-20_final.stac-item
2019-03-02 11:32:06	ga_s2am_ard_3-2-1_51KXB_2019-03-02_final.stac-item
2019-03-25 11:44:29	ga_s2am_ard_3-2-1_50JRT_2019-03-25_final.stac-item
2019-04-28 11:23:00	ga_s2am_ard_3-2-1_52KBD_2019-04-28_final.stac-item
2019-06-20 11:33:38	ga_s2am_ard_3-2-1_51KUS_2019-06-20_final.stac-item
2019-06-24 11:14:50	ga_s2am_ard_3-2-1_52JDR_2019-06-24_final.stac-item
2019-07-29 12:04:47	ga_s2am_ard_3-2-1_50JKT_2019-07-29_final.stac-item
2019-07-30 11:32:24	ga_s2am_ard_3-2-1_51KVB_2019-07-30_final.stac-item
2019-09-05 11:24:01	ga_s2am_ard_3-2-1_51KWQ_2019-09-05_final.stac-item
2019-09-12 11:15:16	ga_s2am_ard_3-2-1_52JCP_2019-09-12_final.stac-item
2019-10-18 11:34:17	ga_s2am_ard_3-2-1_51KVP_2019-10-18_final.stac-item
2019-11-24 11:21:59	ga_s2am_ard_3-2-1_51LYC_2019-11-24_final.stac-item
2020-01-14 10:54:42	ga_s2am_ard_3-2-1_52JFR_2020-01-14_final.stac-item
2020-03-02 11:56:09	ga_s2am_ard_3-2-1_50JKM_2020-03-02_final.stac-item
2020-03-15 12:05:40	ga_s2am_ard_3-2-1_49JGJ_2020-03-15_final.stac-item
2020-04-26 11:06:26	ga_s2am_ard_3-2-1_52HBK_2020-04-26_final.stac-item
2020-05-22 11:22:43	ga_s2am_ard_3-2-1_52KBE_2020-05-22_final.stac-item
2020-05-22 11:24:35	ga_s2am_ard_3-2-1_51JWN_2020-05-22_final.stac-item
2020-05-25 11:35:10	ga_s2am_ard_3-2-1_51JTL_2020-05-25_final.stac-item
2020-07-08 11:13:28	ga_s2am_ard_3-2-1_52KDB_2020-07-08_final.stac-item
2020-07-21 11:26:52	ga_s2am_ard_3-2-1_51HUD_2020-07-21_final.stac-item
2020-08-06 11:46:04	ga_s2am_ard_3-2-1_50JQM_2020-08-06_final.stac-item
2020-11-11 11:32:36	ga_s2am_ard_3-2-1_51KVA_2020-11-11_final.stac-item
2021-02-05 11:56:13	ga_s2am_ard_3-2-1_50JKM_2021-02-05_final.stac-item
2021-02-10 11:02:32	ga_s2am_ard_3-2-1_52KFE_2021-02-10_final.stac-item
2021-04-13 11:44:47	ga_s2am_ard_3-2-1_50JPS_2021-04-13_final.stac-item
2021-05-13 11:46:08	ga_s2am_ard_3-2-1_50JNM_2021-05-13_final.stac-item
2021-07-13 11:13:22	ga_s2am_ard_3-2-1_52KDB_2021-07-13_final.stac-item
2021-10-31 11:12:46	ga_s2am_ard_3-2-1_52KFD_2021-10-31_final.stac-item
2021-12-14 10:55:45	ga_s2am_ard_3-2-1_52JFM_2021-12-14_final.stac-item
2022-01-15 11:32:08	ga_s2am_ard_3-2-1_51KYB_2022-01-15_final.stac-item
2022-01-16 11:03:06	ga_s2am_ard_3-2-1_52KEC_2022-01-16_final.stac-item
2022-01-22 11:23:57	ga_s2am_ard_3-2-1_51KXQ_2022-01-22_final.stac-item
2022-02-28 11:14:32	ga_s2am_ard_3-2-1_51JYN_2022-02-28_final.stac-item
2022-03-29 11:46:22	ga_s2am_ard_3-2-1_50JPL_2022-03-29_final.stac-item
2022-04-05 11:36:12	ga_s2am_ard_3-2-1_51JVF_2022-04-05_final.stac-item
2022-04-28 11:42:26	ga_s2am_ard_3-2-1_51KVB_2022-04-28_final.stac-item
2022-04-29 11:13:40	ga_s2am_ard_3-2-1_52KBA_2022-04-29_final.stac-item
2022-05-21 11:53:17	ga_s2am_ard_3-2-1_50KRC_2022-05-21_final.stac-item
2022-06-01 11:23:00	ga_s2am_ard_3-2-1_51KZU_2022-06-01_final.stac-item
2022-08-13 11:33:21	ga_s2am_ard_3-2-1_51KXT_2022-08-13_final.stac-item
2022-08-31 10:54:29	ga_s2am_ard_3-2-1_52JHT_2022-08-31_final.stac-item
2022-09-02 11:34:04	ga_s2am_ard_3-2-1_51KXQ_2022-09-02_final.stac-item
2022-09-08 11:55:24	ga_s2am_ard_3-2-1_50JLR_2022-09-08_final.stac-item
2022-10-05 11:42:53	ga_s2am_ard_3-2-1_51KUV_2022-10-05_final.stac-item
2022-10-10 10:55:37	ga_s2am_ard_3-2-1_52JFN_2022-10-10_final.stac-item
2022-10-28 11:56:33	ga_s2am_ard_3-2-1_50HNK_2022-10-28_final.stac-item
2023-02-01 12:15:18	ga_s2am_ard_3-2-1_49JGK_2023-02-01_final
2023-02-19 11:34:11	ga_s2am_ard_3-2-1_51KVP_2023-02-19_final
2023-03-01 11:32:09	ga_s2am_ard_3-2-1_51KXB_2023-03-01_final
2023-03-03 12:14:57	ga_s2am_ard_3-2-1_49JFM_2023-03-03_final
2023-04-03 11:41:54	ga_s2am_ard_3-2-1_51LWC_2023-04-03_final
2023-04-24 11:13:07	ga_s2am_ard_3-2-1_52KCC_2023-04-24_final
2023-05-31 11:05:05	ga_s2am_ard_3-2-1_52JEQ_2023-05-31_final
2023-06-16 11:23:20	ga_s2am_ard_3-2-1_52KBB_2023-06-16_final
2023-06-19 11:33:17	ga_s2am_ard_3-2-1_51KWT_2023-06-19_final
2023-06-19 11:33:38	ga_s2am_ard_3-2-1_51KUS_2023-06-19_final
2023-07-12 11:45:52	ga_s2am_ard_3-2-1_50JQN_2023-07-12_final
2023-07-26 11:26:37	ga_s2am_ard_3-2-1_51HUE_2023-07-26_final
2023-09-27 11:33:33	ga_s2am_ard_3-2-1_51KVS_2023-09-27_final
2023-11-13 11:22:59	ga_s2am_ard_3-2-1_51KXU_2023-11-13_final
2024-01-01 11:56:37	ga_s2am_ard_3-2-1_50HLK_2024-01-01_final
2024-01-03 10:53:43	ga_s2am_ard_3-2-1_52KGV_2024-01-03_final
2024-01-06 11:03:04	ga_s2am_ard_3-2-1_52KGB_2024-01-06_final
2024-01-13 10:53:08	ga_s2am_ard_3-2-1_52KHB_2024-01-13_final
2024-01-22 11:23:27	ga_s2am_ard_3-2-1_51KYR_2024-01-22_final
2024-02-14 11:32:55	ga_s2am_ard_3-2-1_51KXU_2024-02-14_final
2024-03-06 11:05:05	ga_s2am_ard_3-2-1_52JDQ_2024-03-06_final
2024-03-08 11:42:10	ga_s2am_ard_3-2-1_51KWB_2024-03-08_final
2024-03-08 11:44:02	ga_s2am_ard_3-2-1_51KTQ_2024-03-08_final
2024-03-09 11:16:20	ga_s2am_ard_3-2-1_52HBK_2024-03-09_final
2024-03-22 11:23:17	ga_s2am_ard_3-2-1_52KCB_2024-03-22_final
2024-04-12 10:56:01	ga_s2am_ard_3-2-1_52JFL_2024-04-12_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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