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
2016-02-06 11:26:58	ga_s2am_ard_3-2-1_51KWR_2016-02-06_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KWP_2016-04-23_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50HQJ_2016-09-06_final.stac-item
2016-09-22 12:04:37	ga_s2am_ard_3-2-1_49JGM_2016-09-22_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_50HPJ_2016-09-26_final.stac-item
2016-12-05 11:46:51	ga_s2am_ard_3-2-1_50HNH_2016-12-05_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUS_2016-12-22_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50JNL_2017-05-04_final.stac-item
2017-06-20 11:28:36	ga_s2am_ard_3-2-1_51KVQ_2017-06-20_final.stac-item
2017-09-21 11:40:44	ga_s2am_ard_3-2-1_51KVT_2017-09-21_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KGP_2017-09-27_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_51KWS_2017-11-27_final.stac-item
2017-12-17 11:32:07	ga_s2am_ard_3-2-1_50HPK_2017-12-17_final.stac-item
2018-01-05 12:02:42	ga_s2am_ard_3-2-1_50KKB_2018-01-05_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51KUT_2018-01-06_final.stac-item
2018-03-27 11:26:19	ga_s2am_ard_3-2-1_51KXT_2018-03-27_final.stac-item
2018-05-03 11:21:11	ga_s2am_ard_3-2-1_51JZN_2018-05-03_final.stac-item
2018-05-29 11:39:24	ga_s2am_ard_3-2-1_51KVS_2018-05-29_final.stac-item
2018-11-22 11:32:54	ga_s2am_ard_3-2-1_51KVU_2018-11-22_final.stac-item
2018-12-02 11:33:30	ga_s2am_ard_3-2-1_51KXR_2018-12-02_final.stac-item
2019-01-10 12:05:39	ga_s2am_ard_3-2-1_49JGJ_2019-01-10_final.stac-item
2019-04-04 11:42:46	ga_s2am_ard_3-2-1_51KUV_2019-04-04_final.stac-item
2019-04-14 11:46:45	ga_s2am_ard_3-2-1_50HNK_2019-04-14_final.stac-item
2019-08-02 11:42:26	ga_s2am_ard_3-2-1_51KWA_2019-08-02_final.stac-item
2019-08-19 11:32:57	ga_s2am_ard_3-2-1_51KXU_2019-08-19_final.stac-item
2020-02-25 11:32:24	ga_s2am_ard_3-2-1_51KWA_2020-02-25_final.stac-item
2020-03-06 11:32:54	ga_s2am_ard_3-2-1_51KVU_2020-03-06_final.stac-item
2020-04-01 11:53:07	ga_s2am_ard_3-2-1_50KRC_2020-04-01_final.stac-item
2020-04-28 11:42:59	ga_s2am_ard_3-2-1_51KVU_2020-04-28_final.stac-item
2020-04-28 11:43:20	ga_s2am_ard_3-2-1_51KTT_2020-04-28_final.stac-item
2020-08-10 11:25:34	ga_s2am_ard_3-2-1_51JWJ_2020-08-10_final.stac-item
2020-10-25 11:43:22	ga_s2am_ard_3-2-1_51KTT_2020-10-25_final.stac-item
2020-11-11 11:32:51	ga_s2am_ard_3-2-1_51KVV_2020-11-11_final.stac-item
2020-11-18 11:23:16	ga_s2am_ard_3-2-1_51KXT_2020-11-18_final.stac-item
2020-11-21 11:32:46	ga_s2am_ard_3-2-1_51KWV_2020-11-21_final.stac-item
2021-01-13 11:47:22	ga_s2am_ard_3-2-1_50HNG_2021-01-13_final
2021-01-16 11:53:25	ga_s2am_ard_3-2-1_50KNC_2021-01-16_final.stac-item
2021-02-16 11:24:11	ga_s2am_ard_3-2-1_51KXP_2021-02-16_final.stac-item
2021-02-21 12:13:53	ga_s2am_ard_3-2-1_50KKA_2021-02-21_final.stac-item
2021-03-31 11:33:54	ga_s2am_ard_3-2-1_51KVQ_2021-03-31_final.stac-item
2021-04-10 11:37:01	ga_s2am_ard_3-2-1_50HPH_2021-04-10_final.stac-item
2021-04-13 11:43:24	ga_s2am_ard_3-2-1_51KUS_2021-04-13_final.stac-item
2021-04-27 11:23:10	ga_s2am_ard_3-2-1_51KXT_2021-04-27_final.stac-item
2021-05-23 11:46:23	ga_s2am_ard_3-2-1_50JNL_2021-05-23_final.stac-item
2021-05-27 11:23:43	ga_s2am_ard_3-2-1_51KXR_2021-05-27_final.stac-item
2021-06-26 11:23:59	ga_s2am_ard_3-2-1_51KXQ_2021-06-26_final.stac-item
2021-07-31 12:14:59	ga_s2am_ard_3-2-1_49JGM_2021-07-31_final.stac-item
2021-08-15 11:24:00	ga_s2am_ard_3-2-1_51KXQ_2021-08-15_final.stac-item
2021-08-27 12:05:31	ga_s2am_ard_3-2-1_49JGK_2021-08-27_final.stac-item
2021-08-28 11:32:21	ga_s2am_ard_3-2-1_51KVB_2021-08-28_final.stac-item
2021-09-04 11:24:27	ga_s2am_ard_3-2-1_51JXN_2021-09-04_final.stac-item
2021-09-17 11:34:07	ga_s2am_ard_3-2-1_51KXP_2021-09-17_final.stac-item
2021-09-27 11:36:35	ga_s2am_ard_3-2-1_51HTE_2021-09-27_final.stac-item
2021-10-07 11:32:52	ga_s2am_ard_3-2-1_51KVV_2021-10-07_final.stac-item
2021-11-26 11:33:52	ga_s2am_ard_3-2-1_51KXQ_2021-11-26_final.stac-item
2021-11-26 11:33:56	ga_s2am_ard_3-2-1_51KWQ_2021-11-26_final.stac-item
2021-12-16 11:32:29	ga_s2am_ard_3-2-1_51KWA_2021-12-16_final.stac-item
2021-12-19 11:42:57	ga_s2am_ard_3-2-1_51KVU_2021-12-19_final.stac-item
2021-12-23 11:23:01	ga_s2am_ard_3-2-1_51KXU_2021-12-23_final.stac-item
2022-02-14 11:33:34	ga_s2am_ard_3-2-1_51KUS_2022-02-14_final.stac-item
2022-02-24 11:37:09	ga_s2am_ard_3-2-1_50HPH_2022-02-24_final.stac-item
2022-04-15 11:33:26	ga_s2am_ard_3-2-1_51KXS_2022-04-15_final.stac-item
2022-04-28 11:42:26	ga_s2am_ard_3-2-1_51KVB_2022-04-28_final.stac-item
2022-06-04 11:33:53	ga_s2am_ard_3-2-1_51KVR_2022-06-04_final.stac-item
2022-06-11 11:24:07	ga_s2am_ard_3-2-1_51KXQ_2022-06-11_final.stac-item
2022-06-18 11:16:19	ga_s2am_ard_3-2-1_51JYF_2022-06-18_final.stac-item
2022-06-24 11:33:10	ga_s2am_ard_3-2-1_51KWU_2022-06-24_final.stac-item
2022-06-24 11:33:57	ga_s2am_ard_3-2-1_51KVR_2022-06-24_final.stac-item
2022-07-04 11:33:58	ga_s2am_ard_3-2-1_51KVR_2022-07-04_final.stac-item
2022-07-30 11:53:20	ga_s2am_ard_3-2-1_50KRC_2022-07-30_final.stac-item
2022-08-13 11:33:07	ga_s2am_ard_3-2-1_51KXU_2022-08-13_final.stac-item
2022-08-13 11:33:36	ga_s2am_ard_3-2-1_51KXS_2022-08-13_final.stac-item
2022-09-05 11:45:04	ga_s2am_ard_3-2-1_50JPS_2022-09-05_final.stac-item
2022-09-12 11:36:39	ga_s2am_ard_3-2-1_51HUE_2022-09-12_final.stac-item
2022-10-25 11:42:59	ga_s2am_ard_3-2-1_51KVU_2022-10-25_final.stac-item
2022-11-17 11:57:11	ga_s2am_ard_3-2-1_50HLH_2022-11-17_final.stac-item
2022-11-18 11:25:44	ga_s2am_ard_3-2-1_51JWH_2022-11-18_final.stac-item
2023-02-15 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-02-15_nrt.stac-item
2023-02-15 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-02-15_final
2023-02-19 11:33:24	ga_s2am_ard_3-2-1_51KWS_2023-02-19_nrt.stac-item
2023-04-07 11:23:13	ga_s2am_ard_3-2-1_51KXT_2023-04-07_final
2023-04-13 11:46:52	ga_s2am_ard_3-2-1_50HNJ_2023-04-13_final
2023-05-30 11:32:50	ga_s2am_ard_3-2-1_51KVV_2023-05-30_final
2023-06-12 11:47:21	ga_s2am_ard_3-2-1_50HPG_2023-06-12_final
2023-07-21 12:13:58	ga_s2am_ard_3-2-1_50KKA_2023-07-21_final
2023-07-22 11:42:32	ga_s2am_ard_3-2-1_51KVA_2023-07-22_final
2023-09-03 11:56:09	ga_s2am_ard_3-2-1_50JNM_2023-09-03_final
2023-09-07 11:34:16	ga_s2am_ard_3-2-1_51KWP_2023-09-07_final
2023-09-13 11:53:15	ga_s2am_ard_3-2-1_50KRC_2023-09-13_final
2023-10-17 11:33:55	ga_s2am_ard_3-2-1_51KWQ_2023-10-17_final
2023-10-27 11:33:23	ga_s2am_ard_3-2-1_51KXS_2023-10-27_final
2024-01-05 11:34:11	ga_s2am_ard_3-2-1_51KVP_2024-01-05_final
2024-02-07 11:42:56	ga_s2am_ard_3-2-1_51KUU_2024-02-07_final
2024-03-01 11:53:10	ga_s2am_ard_3-2-1_50KRC_2024-03-01_final
2024-03-08 11:44:06	ga_s2am_ard_3-2-1_50KQV_2024-03-08_final
2024-03-11 11:56:00	ga_s2am_ard_3-2-1_50JKN_2024-03-11_final
2024-03-18 11:43:12	ga_s2am_ard_3-2-1_51KVT_2024-03-18_final
2024-04-14 11:33:00	ga_s2am_ard_3-2-1_51KWU_2024-04-14_final
2024-04-17 11:44:54	ga_s2am_ard_3-2-1_51JUL_2024-04-17_final
2024-04-24 11:33:59	ga_s2am_ard_3-2-1_51KWQ_2024-04-24_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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