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
2016-01-16 12:07:17	ga_s2am_ard_3-2-1_50KNC_2016-01-16_final.stac-item
2016-03-19 12:14:38	ga_s2am_ard_3-2-1_49JGM_2016-03-19_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_51KVA_2016-06-18_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51KUS_2016-11-05_final.stac-item
2017-01-08 11:18:08	ga_s2am_ard_3-2-1_51HXD_2017-01-08_final.stac-item
2017-04-28 11:20:48	ga_s2am_ard_3-2-1_51KYR_2017-04-28_final.stac-item
2017-10-05 11:21:56	ga_s2am_ard_3-2-1_51KWP_2017-10-05_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_51KVS_2017-11-20_final.stac-item
2017-12-30 11:37:45	ga_s2am_ard_3-2-1_51KVB_2017-12-30_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51KWV_2018-01-06_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51KXU_2018-02-22_final.stac-item
2018-03-06 12:02:46	ga_s2am_ard_3-2-1_50KKB_2018-03-06_final.stac-item
2018-06-05 11:31:35	ga_s2am_ard_3-2-1_51KVU_2018-06-05_final.stac-item
2018-06-22 11:20:28	ga_s2am_ard_3-2-1_51KXT_2018-06-22_final.stac-item
2018-08-31 11:16:57	ga_s2am_ard_3-2-1_51KXS_2018-08-31_final.stac-item
2018-09-10 11:16:56	ga_s2am_ard_3-2-1_51LZE_2018-09-10_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HUC_2018-10-13_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_51KUT_2018-10-26_final.stac-item
2018-11-06 11:14:05	ga_s2am_ard_3-2-1_51KZP_2018-11-06_final.stac-item
2018-11-18 11:56:48	ga_s2am_ard_3-2-1_50HLJ_2018-11-18_final.stac-item
2018-12-15 11:42:52	ga_s2am_ard_3-2-1_51KUU_2018-12-15_final.stac-item
2019-01-21 11:32:29	ga_s2am_ard_3-2-1_51KVA_2019-01-21_final.stac-item
2019-02-10 11:31:53	ga_s2am_ard_3-2-1_51LXC_2019-02-10_final.stac-item
2019-03-29 11:26:33	ga_s2am_ard_3-2-1_51HXD_2019-03-29_final.stac-item
2019-07-19 12:03:49	ga_s2am_ard_3-2-1_50KKB_2019-07-19_final.stac-item
2019-08-12 11:46:37	ga_s2am_ard_3-2-1_50HPK_2019-08-12_final.stac-item
2019-09-05 11:23:06	ga_s2am_ard_3-2-1_51KZT_2019-09-05_final.stac-item
2019-11-24 11:23:40	ga_s2am_ard_3-2-1_51KYR_2019-11-24_final.stac-item
2019-11-27 11:31:39	ga_s2am_ard_3-2-1_51LYD_2019-11-27_final.stac-item
2019-12-24 11:23:01	ga_s2am_ard_3-2-1_51KZT_2019-12-24_final.stac-item
2020-02-24 12:03:36	ga_s2am_ard_3-2-1_50KLB_2020-02-24_final.stac-item
2020-02-25 11:32:24	ga_s2am_ard_3-2-1_51KWA_2020-02-25_final.stac-item
2020-04-05 11:32:54	ga_s2am_ard_3-2-1_51KWU_2020-04-05_final.stac-item
2020-04-29 11:14:11	ga_s2am_ard_3-2-1_51KZP_2020-04-29_final.stac-item
2020-05-18 11:43:02	ga_s2am_ard_3-2-1_51KVU_2020-05-18_final.stac-item
2020-06-07 11:42:23	ga_s2am_ard_3-2-1_51KUB_2020-06-07_final
2020-06-27 11:43:41	ga_s2am_ard_3-2-1_51KVR_2020-06-27_final.stac-item
2020-07-01 11:24:20	ga_s2am_ard_3-2-1_51KWP_2020-07-01_final.stac-item
2020-07-11 11:24:09	ga_s2am_ard_3-2-1_51KZP_2020-07-11_final.stac-item
2020-07-14 11:34:19	ga_s2am_ard_3-2-1_51KVP_2020-07-14_final.stac-item
2020-07-17 11:43:02	ga_s2am_ard_3-2-1_51KVU_2020-07-17_final.stac-item
2020-10-02 11:33:44	ga_s2am_ard_3-2-1_51KXR_2020-10-02_final.stac-item
2020-10-22 11:33:43	ga_s2am_ard_3-2-1_51KXR_2020-10-22_final.stac-item
2020-11-10 12:05:19	ga_s2am_ard_3-2-1_49JGL_2020-11-10_final.stac-item
2020-12-01 11:33:23	ga_s2am_ard_3-2-1_51KXS_2020-12-01_final.stac-item
2020-12-15 11:14:06	ga_s2am_ard_3-2-1_51KZP_2020-12-15_final.stac-item
2021-02-06 11:23:06	ga_s2am_ard_3-2-1_51KZT_2021-02-06_final.stac-item
2021-02-26 11:23:28	ga_s2am_ard_3-2-1_51KXS_2021-02-26_final.stac-item
2021-03-04 11:43:03	ga_s2am_ard_3-2-1_51KTU_2021-03-04_final.stac-item
2021-03-11 11:33:27	ga_s2am_ard_3-2-1_51KWS_2021-03-11_final.stac-item
2021-03-11 11:33:38	ga_s2am_ard_3-2-1_51KXR_2021-03-11_final.stac-item
2021-04-06 11:55:52	ga_s2am_ard_3-2-1_50JLN_2021-04-06_final.stac-item
2021-04-12 12:14:22	ga_s2am_ard_3-2-1_49KGP_2021-04-12_final.stac-item
2021-05-10 11:33:33	ga_s2am_ard_3-2-1_51KUS_2021-05-10_final.stac-item
2021-05-23 11:40:58	ga_s2am_ard_3-2-1_51LWG_2021-05-23_final
2021-06-22 11:43:05	ga_s2am_ard_3-2-1_50KRD_2021-06-22_final.stac-item
2021-08-04 11:53:06	ga_s2am_ard_3-2-1_50KQD_2021-08-04_final
2021-08-18 11:33:25	ga_s2am_ard_3-2-1_51KUT_2021-08-18_final.stac-item
2021-09-07 11:33:39	ga_s2am_ard_3-2-1_51KXR_2021-09-07_final.stac-item
2021-10-24 11:23:19	ga_s2am_ard_3-2-1_51KXT_2021-10-24_final.stac-item
2021-11-03 11:23:17	ga_s2am_ard_3-2-1_51KXT_2021-11-03_final.stac-item
2021-11-03 11:24:08	ga_s2am_ard_3-2-1_51KZP_2021-11-03_final.stac-item
2021-12-06 11:33:01	ga_s2am_ard_3-2-1_51KVU_2021-12-06_final.stac-item
2022-01-22 11:24:04	ga_s2am_ard_3-2-1_51KZP_2022-01-22_final.stac-item
2022-01-25 11:33:13	ga_s2am_ard_3-2-1_51KWT_2022-01-25_final.stac-item
2022-02-14 11:32:58	ga_s2am_ard_3-2-1_51KWU_2022-02-14_final.stac-item
2022-02-27 11:43:00	ga_s2am_ard_3-2-1_51KVU_2022-02-27_final.stac-item
2022-03-06 11:33:02	ga_s2am_ard_3-2-1_51KWU_2022-03-06_final.stac-item
2022-03-16 11:33:20	ga_s2am_ard_3-2-1_51KVT_2022-03-16_final.stac-item
2022-04-08 11:43:44	ga_s2am_ard_3-2-1_51KUR_2022-04-08_final.stac-item
2022-04-11 11:52:21	ga_s2am_ard_3-2-1_50KQG_2022-04-11_final
2022-06-01 11:27:09	ga_s2am_ard_3-2-1_51HUC_2022-06-01_final.stac-item
2022-06-04 11:34:51	ga_s2am_ard_3-2-1_51JVM_2022-06-04_final.stac-item
2022-06-27 11:43:31	ga_s2am_ard_3-2-1_51KTT_2022-06-27_final.stac-item
2022-07-01 11:23:52	ga_s2am_ard_3-2-1_51KYR_2022-07-01_final.stac-item
2022-07-07 11:43:22	ga_s2am_ard_3-2-1_51KTT_2022-07-07_final.stac-item
2022-07-17 11:42:11	ga_s2am_ard_3-2-1_51LVC_2022-07-17_final.stac-item
2022-08-07 11:14:20	ga_s2am_ard_3-2-1_51KZP_2022-08-07_final.stac-item
2022-10-12 11:36:43	ga_s2am_ard_3-2-1_50HPK_2022-10-12_final.stac-item
2022-11-11 11:34:00	ga_s2am_ard_3-2-1_51KWQ_2022-11-11_final.stac-item
2022-11-18 11:23:41	ga_s2am_ard_3-2-1_51KYR_2022-11-18_final.stac-item
2022-12-28 11:22:22	ga_s2am_ard_3-2-1_51KZA_2022-12-28_final.stac-item
2023-01-13 11:43:12	ga_s2am_ard_3-2-1_51KUT_2023-01-13_final.stac-item
2023-01-14 11:13:37	ga_s2am_ard_3-2-1_51KZR_2023-01-14_final.stac-item
2023-03-15 11:13:51	ga_s2am_ard_3-2-1_51KZQ_2023-03-15_final
2023-03-17 11:56:52	ga_s2am_ard_3-2-1_50HLJ_2023-03-17_final
2023-05-10 11:32:58	ga_s2am_ard_3-2-1_51KWU_2023-05-10_final
2023-05-30 11:33:02	ga_s2am_ard_3-2-1_51KWU_2023-05-30_final
2023-06-25 11:55:45	ga_s2am_ard_3-2-1_50JLP_2023-06-25_final
2023-06-25 11:57:23	ga_s2am_ard_3-2-1_50HMG_2023-06-25_final
2023-08-18 11:35:30	ga_s2am_ard_3-2-1_51JUJ_2023-08-18_final
2023-09-17 11:33:34	ga_s2am_ard_3-2-1_51KVS_2023-09-17_final
2023-10-07 11:33:23	ga_s2am_ard_3-2-1_51KUT_2023-10-07_final
2023-10-11 11:13:39	ga_s2am_ard_3-2-1_51KZR_2023-10-11_final
2023-10-30 11:40:57	ga_s2am_ard_3-2-1_51LWG_2023-10-30_final
2023-11-16 11:33:58	ga_s2am_ard_3-2-1_51KVQ_2023-11-16_final
2023-12-09 11:42:36	ga_s2am_ard_3-2-1_51KVV_2023-12-09_final
2023-12-29 11:46:34	ga_s2am_ard_3-2-1_50HNK_2023-12-29_final
2024-03-18 11:42:46	ga_s2am_ard_3-2-1_51KUV_2024-03-18_final
2024-04-17 11:42:19	ga_s2am_ard_3-2-1_51KUB_2024-04-17_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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