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
2015-11-17 10:22:55	ga_s2am_ard_3-2-1_53HQB_2015-11-17_final.stac-item
2016-04-28 10:28:01	ga_s2am_ard_3-2-1_53JQN_2016-04-28_final.stac-item
2016-06-11 11:48:29	ga_s2am_ard_3-2-1_50HLG_2016-06-11_final
2016-07-14 10:26:41	ga_s2am_ard_3-2-1_53HPB_2016-07-14_final.stac-item
2016-08-16 10:28:09	ga_s2am_ard_3-2-1_53JQN_2016-08-16_final.stac-item
2016-08-28 11:12:16	ga_s2am_ard_3-2-1_52KDU_2016-08-28_final.stac-item
2016-09-14 11:04:50	ga_s2am_ard_3-2-1_52JCL_2016-09-14_final.stac-item
2016-10-08 10:43:03	ga_s2am_ard_3-2-1_53JPM_2016-10-08_final.stac-item
2017-04-21 11:28:37	ga_s2am_ard_3-2-1_51JWL_2017-04-21_final.stac-item
2017-06-27 11:20:55	ga_s2am_ard_3-2-1_51JYL_2017-06-27_final.stac-item
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_50JQM_2017-09-08_final.stac-item
2017-10-09 11:02:09	ga_s2am_ard_3-2-1_52KHC_2017-10-09_final.stac-item
2017-11-19 12:13:18	ga_s2am_ard_3-2-1_49JGK_2017-11-19_final.stac-item
2017-12-02 10:43:02	ga_s2am_ard_3-2-1_53JNN_2017-12-02_final.stac-item
2018-01-20 11:11:55	ga_s2am_ard_3-2-1_52KFE_2018-01-20_final.stac-item
2018-01-22 10:11:25	ga_s2am_ard_3-2-1_53HQB_2018-01-22_final.stac-item
2018-01-27 10:57:11	ga_s2am_ard_3-2-1_52LGL_2018-01-27_final.stac-item
2018-04-28 10:27:10	ga_s2am_ard_3-2-1_53JMH_2018-04-28_final.stac-item
2018-05-08 10:27:10	ga_s2am_ard_3-2-1_53JQL_2018-05-08_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50HQJ_2018-09-26_final.stac-item
2018-10-10 11:24:31	ga_s2am_ard_3-2-1_51JVL_2018-10-10_final.stac-item
2018-11-04 10:27:04	ga_s2am_ard_3-2-1_53HPB_2018-11-04_final.stac-item
2019-03-22 11:32:45	ga_s2am_ard_3-2-1_51KVV_2019-03-22_final.stac-item
2019-04-08 11:24:45	ga_s2am_ard_3-2-1_51JWM_2019-04-08_final.stac-item
2019-06-12 10:35:12	ga_s2am_ard_3-2-1_53JNJ_2019-06-12_final.stac-item
2019-07-15 10:46:03	ga_s2am_ard_3-2-1_53JKF_2019-07-15_final.stac-item
2019-08-24 10:46:23	ga_s2am_ard_3-2-1_53HMD_2019-08-24_final.stac-item
2019-08-29 11:36:44	ga_s2am_ard_3-2-1_51HUD_2019-08-29_final.stac-item
2019-09-20 10:35:01	ga_s2am_ard_3-2-1_53JQJ_2019-09-20_final.stac-item
2019-11-17 11:33:43	ga_s2am_ard_3-2-1_51KWR_2019-11-17_final.stac-item
2019-12-19 10:34:19	ga_s2am_ard_3-2-1_53JNM_2019-12-19_final.stac-item
2020-01-11 10:44:36	ga_s2am_ard_3-2-1_53JML_2020-01-11_final.stac-item
2020-01-30 11:13:40	ga_s2am_ard_3-2-1_52KDV_2020-01-30_final.stac-item
2020-03-03 11:22:37	ga_s2am_ard_3-2-1_51KYV_2020-03-03_final.stac-item
2020-03-18 10:34:00	ga_s2am_ard_3-2-1_53JQN_2020-03-18_final.stac-item
2020-05-05 11:33:45	ga_s2am_ard_3-2-1_51KWR_2020-05-05_final.stac-item
2020-05-23 10:56:02	ga_s2am_ard_3-2-1_52JGL_2020-05-23_final.stac-item
2020-06-01 11:24:02	ga_s2am_ard_3-2-1_51KXQ_2020-06-01_final.stac-item
2020-06-04 11:34:02	ga_s2am_ard_3-2-1_51KWQ_2020-06-04_final.stac-item
2020-07-08 11:13:32	ga_s2am_ard_3-2-1_52KBB_2020-07-08_final.stac-item
2020-07-21 11:24:02	ga_s2am_ard_3-2-1_51KXQ_2020-07-21_final.stac-item
2020-09-04 10:34:30	ga_s2am_ard_3-2-1_53JNM_2020-09-04_final.stac-item
2020-09-05 11:47:19	ga_s2am_ard_3-2-1_50HLH_2020-09-05_final.stac-item
2020-09-22 11:32:24	ga_s2am_ard_3-2-1_51KVB_2020-09-22_final.stac-item
2020-09-22 11:33:20	ga_s2am_ard_3-2-1_51KWT_2020-09-22_final.stac-item
2020-11-18 11:24:05	ga_s2am_ard_3-2-1_51KWQ_2020-11-18_final.stac-item
2021-01-10 11:33:35	ga_s2am_ard_3-2-1_51KUS_2021-01-10_final.stac-item
2021-02-20 11:01:13	ga_s2am_ard_3-2-1_52LHK_2021-02-20_final.stac-item
2021-03-20 10:25:04	ga_s2am_ard_3-2-1_53JQJ_2021-03-20_final.stac-item
2021-04-07 11:26:37	ga_s2am_ard_3-2-1_51HUD_2021-04-07_final.stac-item
2021-04-12 12:14:51	ga_s2am_ard_3-2-1_49JGM_2021-04-12_final.stac-item
2021-05-22 10:34:37	ga_s2am_ard_3-2-1_53JPL_2021-05-22_final.stac-item
2021-05-31 11:06:04	ga_s2am_ard_3-2-1_52JDL_2021-05-31_final.stac-item
2021-06-08 12:05:56	ga_s2am_ard_3-2-1_50JKN_2021-06-08_final.stac-item
2021-07-12 11:44:19	ga_s2am_ard_3-2-1_50KRU_2021-07-12_final.stac-item
2021-09-29 10:36:00	ga_s2am_ard_3-2-1_53JMF_2021-09-29_final.stac-item
2021-12-08 12:13:57	ga_s2am_ard_3-2-1_49KGR_2021-12-08_final.stac-item
2021-12-14 10:55:41	ga_s2am_ard_3-2-1_52JGM_2021-12-14_final.stac-item
2021-12-19 11:41:33	ga_s2am_ard_3-2-1_51LUE_2021-12-19_final.stac-item
2022-02-03 10:25:05	ga_s2am_ard_3-2-1_53JQJ_2022-02-03_final.stac-item
2022-04-01 11:54:35	ga_s2am_ard_3-2-1_50JPT_2022-04-01_final.stac-item
2022-05-15 11:34:01	ga_s2am_ard_3-2-1_51KWQ_2022-05-15_final.stac-item
2022-06-18 11:15:11	ga_s2am_ard_3-2-1_52JDQ_2022-06-18_final.stac-item
2022-07-14 11:34:05	ga_s2am_ard_3-2-1_51KXQ_2022-07-14_final.stac-item
2022-08-03 11:33:56	ga_s2am_ard_3-2-1_51KVR_2022-08-03_final.stac-item
2022-08-23 11:33:25	ga_s2am_ard_3-2-1_51KWT_2022-08-23_final
2022-08-26 11:42:58	ga_s2am_ard_3-2-1_51KUV_2022-08-26_final
2022-09-07 10:46:35	ga_s2am_ard_3-2-1_53HLD_2022-09-07_final.stac-item
2022-11-04 11:42:32	ga_s2am_ard_3-2-1_51KVA_2022-11-04_final.stac-item
2022-11-09 10:52:48	ga_s2am_ard_3-2-1_52KHD_2022-11-09_final.stac-item
2022-11-15 11:11:47	ga_s2am_ard_3-2-1_52LFH_2022-11-15_final.stac-item
2022-12-02 11:05:02	ga_s2am_ard_3-2-1_52JEQ_2022-12-02_final.stac-item
2023-01-04 11:16:25	ga_s2am_ard_3-2-1_51HXE_2023-01-04_final.stac-item
2023-01-14 11:14:26	ga_s2am_ard_3-2-1_51JYN_2023-01-14_final.stac-item
2023-01-24 11:11:30	ga_s2am_ard_3-2-1_52LEJ_2023-01-24_final.stac-item
2023-04-14 11:15:29	ga_s2am_ard_3-2-1_52JCN_2023-04-14_final
2023-05-22 10:34:16	ga_s2am_ard_3-2-1_53JNN_2023-05-22_final
2023-05-22 10:36:31	ga_s2am_ard_3-2-1_53HLD_2023-05-22_final
2023-06-01 12:14:22	ga_s2am_ard_3-2-1_50KKU_2023-06-01_final
2023-06-19 11:33:06	ga_s2am_ard_3-2-1_51KYT_2023-06-19_final
2023-06-27 10:55:06	ga_s2am_ard_3-2-1_52JFQ_2023-06-27_final
2023-07-16 11:24:07	ga_s2am_ard_3-2-1_51KWQ_2023-07-16_final
2023-07-29 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2023-07-29_final
2023-10-10 11:41:32	ga_s2am_ard_3-2-1_51LUE_2023-10-10_final
2023-11-10 11:11:26	ga_s2am_ard_3-2-1_52LGJ_2023-11-10_final
2023-11-11 10:44:16	ga_s2am_ard_3-2-1_53JPM_2023-11-11_final
2023-11-20 11:11:56	ga_s2am_ard_3-2-1_52KFG_2023-11-20_final
2023-12-09 11:40:52	ga_s2am_ard_3-2-1_51LWG_2023-12-09_final
2023-12-30 11:11:02	ga_s2am_ard_3-2-1_52LEL_2023-12-30_final
2024-01-02 11:23:25	ga_s2am_ard_3-2-1_51KXS_2024-01-02_final
2024-01-04 12:05:37	ga_s2am_ard_3-2-1_50JKP_2024-01-04_final
2024-01-10 10:44:12	ga_s2am_ard_3-2-1_53JPM_2024-01-10_final
2024-01-15 11:33:38	ga_s2am_ard_3-2-1_51KVR_2024-01-15_final
2024-01-16 11:02:47	ga_s2am_ard_3-2-1_52KHC_2024-01-16_final
2024-01-28 11:42:40	ga_s2am_ard_3-2-1_51KUV_2024-01-28_final
2024-02-23 12:03:39	ga_s2am_ard_3-2-1_50KLB_2024-02-23_final
2024-02-26 12:14:55	ga_s2am_ard_3-2-1_49JGM_2024-02-26_final
2024-03-06 11:05:05	ga_s2am_ard_3-2-1_52JDQ_2024-03-06_final
2024-04-17 11:43:18	ga_s2am_ard_3-2-1_51KUT_2024-04-17_final
2024-04-21 11:24:00	ga_s2am_ard_3-2-1_51KXQ_2024-04-21_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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