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
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_51KVQ_2016-06-05_final.stac-item
2016-07-10 10:45:19	ga_s2am_ard_3-2-1_53JKF_2016-07-10_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_51KWT_2016-08-24_final.stac-item
2016-09-15 12:13:17	ga_s2am_ard_3-2-1_49KHP_2016-09-15_final.stac-item
2016-11-01 10:22:46	ga_s2am_ard_3-2-1_54HUJ_2016-11-01_final.stac-item
2016-12-13 11:02:39	ga_s2am_ard_3-2-1_52JBL_2016-12-13_final.stac-item
2016-12-27 10:38:37	ga_s2am_ard_3-2-1_53KMT_2016-12-27_final.stac-item
2017-01-12 11:02:04	ga_s2am_ard_3-2-1_52KFD_2017-01-12_final.stac-item
2017-02-19 10:23:19	ga_s2am_ard_3-2-1_54HUH_2017-02-19_final.stac-item
2017-04-13 12:13:43	ga_s2am_ard_3-2-1_49KGR_2017-04-13_final.stac-item
2017-12-17 11:32:07	ga_s2am_ard_3-2-1_51KVT_2017-12-17_final.stac-item
2018-03-28 10:57:14	ga_s2am_ard_3-2-1_52LHN_2018-03-28_final.stac-item
2018-06-11 10:07:04	ga_s2am_ard_3-2-1_54HVG_2018-06-11_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50JKM_2018-06-24_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_51KXS_2018-07-25_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_54HWD_2018-10-26_final.stac-item
2018-11-12 11:36:41	ga_s2am_ard_3-2-1_51HTD_2018-11-12_final.stac-item
2018-11-17 10:43:35	ga_s2am_ard_3-2-1_53KMQ_2018-11-17_final.stac-item
2018-12-02 11:35:22	ga_s2am_ard_3-2-1_51JUJ_2018-12-02_final.stac-item
2019-01-12 11:03:01	ga_s2am_ard_3-2-1_52KEC_2019-01-12_final.stac-item
2019-04-06 10:44:07	ga_s2am_ard_3-2-1_53JNN_2019-04-06_final.stac-item
2019-04-11 11:34:39	ga_s2am_ard_3-2-1_50JRT_2019-04-11_final.stac-item
2019-05-13 10:33:56	ga_s2am_ard_3-2-1_53KPP_2019-05-13_final.stac-item
2019-05-28 11:23:09	ga_s2am_ard_3-2-1_51KZT_2019-05-28_final.stac-item
2019-05-28 11:26:57	ga_s2am_ard_3-2-1_51HVC_2019-05-28_final.stac-item
2019-07-09 10:24:24	ga_s2am_ard_3-2-1_53JRM_2019-07-09_final.stac-item
2019-08-19 11:33:30	ga_s2am_ard_3-2-1_51KWS_2019-08-19_final.stac-item
2019-08-26 11:23:30	ga_s2am_ard_3-2-1_51KXS_2019-08-26_final.stac-item
2019-10-11 11:43:17	ga_s2am_ard_3-2-1_51KUT_2019-10-11_final.stac-item
2019-10-31 11:45:10	ga_s2am_ard_3-2-1_50JPR_2019-10-31_final.stac-item
2019-11-27 11:32:54	ga_s2am_ard_3-2-1_51KXU_2019-11-27_final.stac-item
2019-11-30 11:42:56	ga_s2am_ard_3-2-1_51KVU_2019-11-30_final.stac-item
2019-12-04 11:23:23	ga_s2am_ard_3-2-1_51KYS_2019-12-04_final.stac-item
2019-12-20 11:47:04	ga_s2am_ard_3-2-1_50HMH_2019-12-20_final.stac-item
2020-01-26 11:33:16	ga_s2am_ard_3-2-1_51KXS_2020-01-26_final.stac-item
2020-02-11 11:54:55	ga_s2am_ard_3-2-1_50JPR_2020-02-11_final.stac-item
2020-02-25 11:33:37	ga_s2am_ard_3-2-1_51KWR_2020-02-25_final.stac-item
2020-02-27 10:32:06	ga_s2am_ard_3-2-1_53KQA_2020-02-27_final.stac-item
2020-04-22 11:23:08	ga_s2am_ard_3-2-1_51KZT_2020-04-22_final.stac-item
2020-04-25 11:35:10	ga_s2am_ard_3-2-1_51JWK_2020-04-25_final.stac-item
2020-07-09 10:44:32	ga_s2am_ard_3-2-1_53JPL_2020-07-09_final.stac-item
2020-07-11 11:23:04	ga_s2am_ard_3-2-1_51KXU_2020-07-11_final.stac-item
2020-07-12 10:54:52	ga_s2am_ard_3-2-1_52JFR_2020-07-12_final.stac-item
2020-08-16 11:43:17	ga_s2am_ard_3-2-1_51KVT_2020-08-16_final.stac-item
2020-08-20 11:23:41	ga_s2am_ard_3-2-1_51KZR_2020-08-20_final.stac-item
2020-11-18 11:24:05	ga_s2am_ard_3-2-1_51KWQ_2020-11-18_final.stac-item
2020-12-21 11:33:51	ga_s2am_ard_3-2-1_51KXQ_2020-12-21_final.stac-item
2020-12-22 11:05:37	ga_s2am_ard_3-2-1_52JFM_2020-12-22_final.stac-item
2021-01-28 10:50:49	ga_s2am_ard_3-2-1_53LPF_2021-01-28_final.stac-item
2021-01-30 11:33:24	ga_s2am_ard_3-2-1_51KXS_2021-01-30_final.stac-item
2021-02-11 10:34:17	ga_s2am_ard_3-2-1_53JQM_2021-02-11_final.stac-item
2021-03-17 11:52:19	ga_s2am_ard_3-2-1_50KQG_2021-03-17_final
2021-04-22 10:34:21	ga_s2am_ard_3-2-1_53JNM_2021-04-22_final.stac-item
2021-04-27 11:23:07	ga_s2am_ard_3-2-1_51KYT_2021-04-27_final.stac-item
2021-05-20 11:33:28	ga_s2am_ard_3-2-1_51KWS_2021-05-20_final.stac-item
2021-07-06 11:24:00	ga_s2am_ard_3-2-1_51KXQ_2021-07-06_final.stac-item
2021-07-11 10:36:31	ga_s2am_ard_3-2-1_53HLD_2021-07-11_final.stac-item
2021-08-08 11:33:37	ga_s2am_ard_3-2-1_51KUS_2021-08-08_final.stac-item
2021-08-21 11:42:48	ga_s2am_ard_3-2-1_51KUV_2021-08-21_final.stac-item
2021-10-14 11:24:07	ga_s2am_ard_3-2-1_51KWQ_2021-10-14_final.stac-item
2021-12-26 09:57:42	ga_s2am_ard_3-2-1_54HXC_2021-12-26_final.stac-item
2022-01-15 11:33:03	ga_s2am_ard_3-2-1_51KYT_2022-01-15_final.stac-item
2022-01-30 10:42:10	ga_s2am_ard_3-2-1_53KNA_2022-01-30_final.stac-item
2022-01-31 11:56:14	ga_s2am_ard_3-2-1_50JKM_2022-01-31_final.stac-item
2022-02-26 10:34:16	ga_s2am_ard_3-2-1_53JNN_2022-02-26_final.stac-item
2022-04-13 10:55:56	ga_s2am_ard_3-2-1_53JKF_2022-04-13_final.stac-item
2022-06-11 11:25:13	ga_s2am_ard_3-2-1_51JVL_2022-06-11_final.stac-item
2022-07-11 11:23:23	ga_s2am_ard_3-2-1_51KYT_2022-07-11_final.stac-item
2022-08-03 11:33:23	ga_s2am_ard_3-2-1_51KWT_2022-08-03_final.stac-item
2022-08-15 10:34:02	ga_s2am_ard_3-2-1_53KQP_2022-08-15_final.stac-item
2022-08-25 10:34:26	ga_s2am_ard_3-2-1_53JNN_2022-08-25_final.stac-item
2022-08-27 11:13:28	ga_s2am_ard_3-2-1_52KEB_2022-08-27_final.stac-item
2022-09-07 10:43:31	ga_s2am_ard_3-2-1_53KPR_2022-09-07_final.stac-item
2022-09-09 11:24:30	ga_s2am_ard_3-2-1_52JBT_2022-09-09_final.stac-item
2022-09-19 11:25:42	ga_s2am_ard_3-2-1_51JYH_2022-09-19_final.stac-item
2022-09-25 11:47:17	ga_s2am_ard_3-2-1_50HMH_2022-09-25_final.stac-item
2022-11-28 11:23:28	ga_s2am_ard_3-2-1_51KXS_2022-11-28_final.stac-item
2022-12-22 11:05:10	ga_s2am_ard_3-2-1_52JFP_2022-12-22_final.stac-item
2022-12-29 10:52:30	ga_s2am_ard_3-2-1_52KHE_2022-12-29_final.stac-item
2023-01-05 10:42:35	ga_s2am_ard_3-2-1_53KPU_2023-01-05_final.stac-item
2023-01-10 11:33:36	ga_s2am_ard_3-2-1_51KXR_2023-01-10_final.stac-item
2023-02-11 10:33:51	ga_s2am_ard_3-2-1_53KPP_2023-02-11_final
2023-03-27 11:57:11	ga_s2am_ard_3-2-1_50HKH_2023-03-27_nrt
2023-03-28 11:24:30	ga_s2am_ard_3-2-1_51JZM_2023-03-28_final
2023-04-22 10:33:48	ga_s2am_ard_3-2-1_53KQP_2023-04-22_final
2023-07-16 11:23:25	ga_s2am_ard_3-2-1_52KBB_2023-07-16_final
2023-07-23 12:51:04	ga_s2am_ard_3-2-1_48LWP_2023-07-23_final
2023-08-29 11:06:41	ga_s2am_ard_3-2-1_52HBJ_2023-08-29_final
2023-10-04 11:23:12	ga_s2am_ard_3-2-1_51KYT_2023-10-04_final
2023-11-03 11:23:09	ga_s2am_ard_3-2-1_51KXT_2023-11-03_final
2023-11-16 11:32:57	ga_s2am_ard_3-2-1_51KWU_2023-11-16_final
2023-12-02 11:56:06	ga_s2am_ard_3-2-1_50JKM_2023-12-02_final
2023-12-23 11:26:32	ga_s2am_ard_3-2-1_51HXD_2023-12-23_final
2023-12-29 11:42:57	ga_s2am_ard_3-2-1_51KUU_2023-12-29_final
2024-01-15 11:33:06	ga_s2am_ard_3-2-1_51KWT_2024-01-15_final
2024-01-15 11:33:23	ga_s2am_ard_3-2-1_51KVS_2024-01-15_final
2024-01-28 11:42:51	ga_s2am_ard_3-2-1_51KVU_2024-01-28_final
2024-03-12 11:23:35	ga_s2am_ard_3-2-1_52KBA_2024-03-12_final
2024-03-21 11:56:00	ga_s2am_ard_3-2-1_50JKN_2024-03-21_final
2024-03-30 10:41:41	ga_s2am_ard_3-2-1_53LNC_2024-03-30_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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