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
2015-11-25 11:21:29	ga_s2am_ard_3-2-1_51KZS_2015-11-25_final.stac-item
2015-11-29 10:57:18	ga_s2am_ard_3-2-1_52JFR_2015-11-29_final.stac-item
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50JKM_2016-01-16_final.stac-item
2016-03-11 11:12:21	ga_s2am_ard_3-2-1_51HWD_2016-03-11_final.stac-item
2016-05-07 11:02:16	ga_s2am_ard_3-2-1_52KDV_2016-05-07_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50HNH_2016-07-28_final.stac-item
2016-10-29 11:54:20	ga_s2am_ard_3-2-1_50JNT_2016-10-29_final.stac-item
2016-12-06 11:13:53	ga_s2am_ard_3-2-1_52JBT_2016-12-06_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_51JVK_2016-12-12_final.stac-item
2017-01-05 11:12:08	ga_s2am_ard_3-2-1_52KEB_2017-01-05_final.stac-item
2017-01-18 11:19:51	ga_s2am_ard_3-2-1_51JWK_2017-01-18_final.stac-item
2017-03-20 10:53:07	ga_s2am_ard_3-2-1_52JGN_2017-03-20_final.stac-item
2017-03-22 11:35:56	ga_s2am_ard_3-2-1_51JTF_2017-03-22_final.stac-item
2017-11-08 11:02:57	ga_s2am_ard_3-2-1_52KEC_2017-11-08_final.stac-item
2018-02-18 11:42:05	ga_s2am_ard_3-2-1_51KVB_2018-02-18_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51JYL_2018-02-22_final.stac-item
2018-03-20 11:37:46	ga_s2am_ard_3-2-1_50KRD_2018-03-20_final.stac-item
2018-04-05 12:02:49	ga_s2am_ard_3-2-1_50KLA_2018-04-05_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51JWN_2018-06-05_final.stac-item
2018-06-11 11:48:18	ga_s2am_ard_3-2-1_50KRC_2018-06-11_final.stac-item
2018-06-23 10:47:25	ga_s2am_ard_3-2-1_52JEL_2018-06-23_final.stac-item
2018-10-06 11:46:03	ga_s2am_ard_3-2-1_50HPH_2018-10-06_final.stac-item
2019-01-28 11:23:00	ga_s2am_ard_3-2-1_52KCC_2019-01-28_final.stac-item
2019-05-01 11:33:27	ga_s2am_ard_3-2-1_51KXS_2019-05-01_final.stac-item
2019-05-21 11:33:31	ga_s2am_ard_3-2-1_51KWS_2019-05-21_final.stac-item
2019-08-19 11:32:35	ga_s2am_ard_3-2-1_51KVA_2019-08-19_final.stac-item
2019-12-08 11:05:20	ga_s2am_ard_3-2-1_52JCP_2019-12-08_final.stac-item
2019-12-10 11:43:21	ga_s2am_ard_3-2-1_51KVS_2019-12-10_final.stac-item
2020-01-03 11:24:13	ga_s2am_ard_3-2-1_51JZN_2020-01-03_final.stac-item
2020-01-03 11:25:04	ga_s2am_ard_3-2-1_51JXK_2020-01-03_final.stac-item
2020-01-06 11:31:30	ga_s2am_ard_3-2-1_51LZD_2020-01-06_final.stac-item
2020-01-13 11:24:31	ga_s2am_ard_3-2-1_51JYM_2020-01-13_final.stac-item
2020-02-24 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2020-02-24_final.stac-item
2020-02-28 11:46:51	ga_s2am_ard_3-2-1_50HMJ_2020-02-28_final.stac-item
2020-06-14 11:33:33	ga_s2am_ard_3-2-1_51KWS_2020-06-14_final.stac-item
2020-10-02 11:37:08	ga_s2am_ard_3-2-1_50HQH_2020-10-02_final.stac-item
2020-10-03 11:04:59	ga_s2am_ard_3-2-1_52JER_2020-10-03_final.stac-item
2020-12-11 11:32:08	ga_s2am_ard_3-2-1_51KXB_2020-12-11_final.stac-item
2021-03-11 11:36:46	ga_s2am_ard_3-2-1_51HTD_2021-03-11_final.stac-item
2021-03-15 11:12:49	ga_s2am_ard_3-2-1_52KDD_2021-03-15_final.stac-item
2021-03-18 11:23:49	ga_s2am_ard_3-2-1_51KZQ_2021-03-18_final.stac-item
2021-04-03 11:46:30	ga_s2am_ard_3-2-1_50HPK_2021-04-03_final.stac-item
2021-04-09 12:03:51	ga_s2am_ard_3-2-1_50KLA_2021-04-09_final.stac-item
2021-05-24 11:14:06	ga_s2am_ard_3-2-1_52KCU_2021-05-24_final.stac-item
2021-07-07 10:54:29	ga_s2am_ard_3-2-1_52JHS_2021-07-07_final.stac-item
2021-07-12 11:44:37	ga_s2am_ard_3-2-1_50JQT_2021-07-12_final.stac-item
2021-07-19 11:35:04	ga_s2am_ard_3-2-1_51JUL_2021-07-19_final.stac-item
2021-07-21 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2021-07-21_final.stac-item
2021-08-27 12:04:50	ga_s2am_ard_3-2-1_50JMS_2021-08-27_final.stac-item
2021-08-27 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2021-08-27_final.stac-item
2021-08-28 11:37:08	ga_s2am_ard_3-2-1_50HPH_2021-08-28_final.stac-item
2021-10-31 11:13:18	ga_s2am_ard_3-2-1_52KBC_2021-10-31_final.stac-item
2021-10-31 11:14:57	ga_s2am_ard_3-2-1_52JBR_2021-10-31_final.stac-item
2021-11-10 11:15:10	ga_s2am_ard_3-2-1_52JBQ_2021-11-10_final.stac-item
2021-11-10 11:16:08	ga_s2am_ard_3-2-1_52JBL_2021-11-10_final.stac-item
2022-01-15 11:33:10	ga_s2am_ard_3-2-1_51KXT_2022-01-15_final.stac-item
2022-02-01 11:23:07	ga_s2am_ard_3-2-1_51KZT_2022-02-01_final.stac-item
2022-03-14 10:54:25	ga_s2am_ard_3-2-1_52JFT_2022-03-14_final.stac-item
2022-03-25 12:04:34	ga_s2am_ard_3-2-1_49KGP_2022-03-25_final.stac-item
2022-03-25 12:05:32	ga_s2am_ard_3-2-1_49JGK_2022-03-25_final.stac-item
2022-03-30 11:16:39	ga_s2am_ard_3-2-1_51HYD_2022-03-30_final.stac-item
2022-05-11 11:54:48	ga_s2am_ard_3-2-1_50JLT_2022-05-11_final.stac-item
2022-05-11 11:55:45	ga_s2am_ard_3-2-1_50JLP_2022-05-11_final.stac-item
2022-05-29 11:14:54	ga_s2am_ard_3-2-1_52JDR_2022-05-29_final.stac-item
2022-07-14 11:36:55	ga_s2am_ard_3-2-1_51HUD_2022-07-14_final.stac-item
2022-08-16 11:47:04	ga_s2am_ard_3-2-1_50HNJ_2022-08-16_final.stac-item
2022-08-27 11:13:46	ga_s2am_ard_3-2-1_52KDA_2022-08-27_final.stac-item
2022-09-05 11:44:17	ga_s2am_ard_3-2-1_50KQV_2022-09-05_final.stac-item
2022-09-05 11:45:44	ga_s2am_ard_3-2-1_50JQP_2022-09-05_final.stac-item
2022-10-02 11:33:38	ga_s2am_ard_3-2-1_51KVS_2022-10-02_final.stac-item
2022-10-26 11:15:42	ga_s2am_ard_3-2-1_51JYH_2022-10-26_final.stac-item
2022-10-26 11:15:50	ga_s2am_ard_3-2-1_52JCM_2022-10-26_final.stac-item
2022-11-22 11:04:29	ga_s2am_ard_3-2-1_52JFS_2022-11-22_final.stac-item
2023-01-03 11:43:35	ga_s2am_ard_3-2-1_50KQB_2023-01-03_final.stac-item
2023-01-03 11:46:04	ga_s2am_ard_3-2-1_50JPM_2023-01-03_final.stac-item
2023-01-04 11:16:33	ga_s2am_ard_3-2-1_52HBJ_2023-01-04_nrt.stac-item
2023-01-26 11:55:00	ga_s2am_ard_3-2-1_50JPR_2023-01-26_final.stac-item
2023-01-28 10:55:52	ga_s2am_ard_3-2-1_52JGL_2023-01-28_final.stac-item
2023-04-01 11:04:42	ga_s2am_ard_3-2-1_52JFR_2023-04-01_final
2023-04-13 11:44:34	ga_s2am_ard_3-2-1_50JQT_2023-04-13_final
2023-04-30 11:33:56	ga_s2am_ard_3-2-1_51KWQ_2023-04-30_final
2023-05-24 11:16:40	ga_s2am_ard_3-2-1_51HYD_2023-05-24_final
2023-05-27 11:24:08	ga_s2am_ard_3-2-1_52KBU_2023-05-27_final
2023-06-02 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2023-06-02_final
2023-06-15 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2023-06-15_final
2023-06-16 11:23:32	ga_s2am_ard_3-2-1_51KXS_2023-06-16_final
2023-06-19 11:33:31	ga_s2am_ard_3-2-1_51KWS_2023-06-19_final
2023-07-25 11:56:01	ga_s2am_ard_3-2-1_50JLN_2023-07-25_final
2023-11-17 11:05:43	ga_s2am_ard_3-2-1_52JEM_2023-11-17_final
2023-11-30 11:16:26	ga_s2am_ard_3-2-1_52HBJ_2023-11-30_final
2024-01-22 11:22:19	ga_s2am_ard_3-2-1_51KYA_2024-01-22_final
2024-01-22 11:23:34	ga_s2am_ard_3-2-1_51KYR_2024-01-22_final
2024-01-29 11:15:05	ga_s2am_ard_3-2-1_51JYK_2024-01-29_final
2024-02-16 12:14:19	ga_s2am_ard_3-2-1_49KHP_2024-02-16_final
2024-03-02 11:23:25	ga_s2am_ard_3-2-1_51KYS_2024-03-02_final
2024-03-06 11:03:54	ga_s2am_ard_3-2-1_52KDV_2024-03-06_final
2024-03-09 11:16:41	ga_s2am_ard_3-2-1_51HXD_2024-03-09_final
2024-03-15 11:36:52	ga_s2am_ard_3-2-1_50HPJ_2024-03-15_final
2024-03-22 11:22:42	ga_s2am_ard_3-2-1_51KYV_2024-03-22_final
2024-03-22 11:26:48	ga_s2am_ard_3-2-1_51HUD_2024-03-22_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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