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
2015-12-18 11:36:25	ga_s2am_ard_3-2-1_50JPL_2015-12-18_final.stac-item
2016-04-06 11:25:50	ga_s2am_ard_3-2-1_51KXS_2016-04-06_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_51KUR_2016-04-19_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_51KZR_2016-05-10_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_51JTJ_2016-07-28_final.stac-item
2016-10-30 11:18:19	ga_s2am_ard_3-2-1_51KZP_2016-10-30_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51JVJ_2016-11-22_final.stac-item
2016-12-26 11:07:06	ga_s2am_ard_3-2-1_52JBT_2016-12-26_final.stac-item
2017-02-20 11:27:48	ga_s2am_ard_3-2-1_51KWB_2017-02-20_final.stac-item
2017-03-26 11:11:44	ga_s2am_ard_3-2-1_51JYL_2017-03-26_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50JQN_2017-05-04_final.stac-item
2017-09-15 11:22:06	ga_s2am_ard_3-2-1_51JVH_2017-09-15_final.stac-item
2018-04-26 11:26:22	ga_s2am_ard_3-2-1_51KWB_2018-04-26_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_51KVU_2018-06-28_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50KRC_2018-07-21_final.stac-item
2018-07-22 11:25:32	ga_s2am_ard_3-2-1_51JWH_2018-07-22_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JNQ_2018-08-30_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49JGL_2018-11-01_final.stac-item
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_50JPP_2018-11-05_final.stac-item
2018-11-09 11:23:05	ga_s2am_ard_3-2-1_51KYT_2018-11-09_final.stac-item
2019-04-11 11:31:41	ga_s2am_ard_3-2-1_51LYD_2019-04-11_final.stac-item
2019-06-20 11:34:07	ga_s2am_ard_3-2-1_51KUQ_2019-06-20_final.stac-item
2019-06-26 11:57:14	ga_s2am_ard_3-2-1_50HLH_2019-06-26_final.stac-item
2019-09-18 11:32:36	ga_s2am_ard_3-2-1_51KYV_2019-09-18_final.stac-item
2019-11-10 11:42:48	ga_s2am_ard_3-2-1_51KUV_2019-11-10_final.stac-item
2019-12-11 11:13:50	ga_s2am_ard_3-2-1_51KZQ_2019-12-11_final.stac-item
2020-01-03 11:22:55	ga_s2am_ard_3-2-1_51KXU_2020-01-03_final.stac-item
2020-01-10 11:14:26	ga_s2am_ard_3-2-1_52JDS_2020-01-10_final.stac-item
2020-02-15 11:33:02	ga_s2am_ard_3-2-1_51KXT_2020-02-15_final.stac-item
2020-02-24 12:04:23	ga_s2am_ard_3-2-1_49KHP_2020-02-24_final.stac-item
2020-03-03 11:25:09	ga_s2am_ard_3-2-1_51JWK_2020-03-03_final.stac-item
2020-03-22 11:53:07	ga_s2am_ard_3-2-1_50KRC_2020-03-22_final.stac-item
2020-04-08 11:43:15	ga_s2am_ard_3-2-1_51KTT_2020-04-08_final.stac-item
2020-04-24 12:04:00	ga_s2am_ard_3-2-1_50KKA_2020-04-24_final.stac-item
2020-06-01 11:22:59	ga_s2am_ard_3-2-1_51KZU_2020-06-01_final.stac-item
2020-06-03 12:05:15	ga_s2am_ard_3-2-1_49JFM_2020-06-03_final.stac-item
2020-06-07 11:46:44	ga_s2am_ard_3-2-1_50HNK_2020-06-07_final.stac-item
2020-07-06 12:14:46	ga_s2am_ard_3-2-1_49JGN_2020-07-06_final.stac-item
2020-07-31 11:27:07	ga_s2am_ard_3-2-1_51HUC_2020-07-31_final.stac-item
2020-08-19 11:53:16	ga_s2am_ard_3-2-1_50KRC_2020-08-19_final.stac-item
2020-09-09 11:26:22	ga_s2am_ard_3-2-1_51JUF_2020-09-09_final.stac-item
2020-09-11 12:05:04	ga_s2am_ard_3-2-1_49JGM_2020-09-11_final.stac-item
2020-09-24 12:14:00	ga_s2am_ard_3-2-1_49KHR_2020-09-24_final.stac-item
2020-09-25 11:43:02	ga_s2am_ard_3-2-1_51KVU_2020-09-25_final.stac-item
2020-10-15 11:43:02	ga_s2am_ard_3-2-1_51KVU_2020-10-15_final.stac-item
2020-11-04 11:42:18	ga_s2am_ard_3-2-1_51KVB_2020-11-04_final.stac-item
2020-11-18 11:23:57	ga_s2am_ard_3-2-1_51KYQ_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
2021-01-29 12:03:41	ga_s2am_ard_3-2-1_50KLB_2021-01-29_final.stac-item
2021-03-21 11:35:18	ga_s2am_ard_3-2-1_51JWJ_2021-03-21_final.stac-item
2021-03-21 11:37:20	ga_s2am_ard_3-2-1_50HPG_2021-03-21_final
2021-04-16 11:57:14	ga_s2am_ard_3-2-1_50HMG_2021-04-16_final
2021-04-23 11:40:53	ga_s2am_ard_3-2-1_51LWG_2021-04-23_final
2021-07-16 11:26:08	ga_s2am_ard_3-2-1_51JUG_2021-07-16_final.stac-item
2021-07-22 11:46:26	ga_s2am_ard_3-2-1_50JNL_2021-07-22_final.stac-item
2021-08-11 11:42:45	ga_s2am_ard_3-2-1_51KVV_2021-08-11_final.stac-item
2021-08-18 11:33:00	ga_s2am_ard_3-2-1_51KWU_2021-08-18_final.stac-item
2021-08-18 11:33:04	ga_s2am_ard_3-2-1_51KVU_2021-08-18_final.stac-item
2021-10-10 11:43:08	ga_s2am_ard_3-2-1_51KTU_2021-10-10_final.stac-item
2021-11-05 12:04:31	ga_s2am_ard_3-2-1_49KHP_2021-11-05_final.stac-item
2021-11-13 11:24:10	ga_s2am_ard_3-2-1_51KYP_2021-11-13_final.stac-item
2021-12-10 11:15:20	ga_s2am_ard_3-2-1_52JBP_2021-12-10_final.stac-item
2021-12-13 11:22:52	ga_s2am_ard_3-2-1_51KZU_2021-12-13_final.stac-item
2021-12-29 11:41:34	ga_s2am_ard_3-2-1_51LUE_2021-12-29_final.stac-item
2022-02-24 11:33:11	ga_s2am_ard_3-2-1_51KXT_2022-02-24_final.stac-item
2022-05-05 11:35:17	ga_s2am_ard_3-2-1_51JVK_2022-05-05_final.stac-item
2022-05-17 12:14:32	ga_s2am_ard_3-2-1_49KGP_2022-05-17_final.stac-item
2022-05-18 11:42:19	ga_s2am_ard_3-2-1_51KVB_2022-05-18_final.stac-item
2022-06-04 11:34:13	ga_s2am_ard_3-2-1_51KXP_2022-06-04_final.stac-item
2022-06-04 11:37:05	ga_s2am_ard_3-2-1_51HUC_2022-06-04_final.stac-item
2022-08-06 11:44:27	ga_s2am_ard_3-2-1_50KRU_2022-08-06_final.stac-item
2022-10-02 11:32:54	ga_s2am_ard_3-2-1_51KVV_2022-10-02_final.stac-item
2022-10-15 11:43:29	ga_s2am_ard_3-2-1_51KVS_2022-10-15_final.stac-item
2022-11-15 11:15:06	ga_s2am_ard_3-2-1_52JCQ_2022-11-15_final.stac-item
2022-12-04 11:43:01	ga_s2am_ard_3-2-1_51KUU_2022-12-04_final.stac-item
2022-12-31 11:34:14	ga_s2am_ard_3-2-1_51JXN_2022-12-31_final.stac-item
2023-02-19 11:32:37	ga_s2am_ard_3-2-1_51KXV_2023-02-19_final
2023-02-19 11:34:02	ga_s2am_ard_3-2-1_51KXP_2023-02-19_nrt.stac-item
2023-02-25 11:54:45	ga_s2am_ard_3-2-1_50JPS_2023-02-25_final
2023-03-01 11:32:41	ga_s2am_ard_3-2-1_51KWV_2023-03-01_final
2023-03-31 11:33:00	ga_s2am_ard_3-2-1_51KVU_2023-03-31_final
2023-04-09 12:03:44	ga_s2am_ard_3-2-1_50KKB_2023-04-09_final
2023-04-23 11:43:17	ga_s2am_ard_3-2-1_51KTT_2023-04-23_final
2023-06-01 12:14:25	ga_s2am_ard_3-2-1_49KHP_2023-06-01_final
2023-06-16 11:27:06	ga_s2am_ard_3-2-1_51HUC_2023-06-16_final
2023-07-06 11:23:05	ga_s2am_ard_3-2-1_51KXU_2023-07-06_final
2023-07-08 12:04:51	ga_s2am_ard_3-2-1_49JGN_2023-07-08_final
2023-08-01 11:43:23	ga_s2am_ard_3-2-1_51KTT_2023-08-01_final
2023-08-17 12:05:35	ga_s2am_ard_3-2-1_49JGK_2023-08-17_final
2023-09-24 11:24:04	ga_s2am_ard_3-2-1_51KWQ_2023-09-24_final
2023-10-24 11:23:39	ga_s2am_ard_3-2-1_51KYR_2023-10-24_final
2023-11-03 11:25:04	ga_s2am_ard_3-2-1_51JYK_2023-11-03_final
2023-11-16 11:36:18	ga_s2am_ard_3-2-1_50JQL_2023-11-16_final
2023-12-29 11:41:15	ga_s2am_ard_3-2-1_51LUF_2023-12-29_final
2024-01-15 11:32:08	ga_s2am_ard_3-2-1_51KWB_2024-01-15_final
2024-02-04 11:33:50	ga_s2am_ard_3-2-1_51KVQ_2024-02-04_final
2024-02-23 12:05:39	ga_s2am_ard_3-2-1_50JKP_2024-02-23_final
2024-03-28 11:43:25	ga_s2am_ard_3-2-1_51KVS_2024-03-28_final
2024-04-14 11:32:52	ga_s2am_ard_3-2-1_51KYU_2024-04-14_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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