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
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51KWB_2016-01-20_final.stac-item
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51KXQ_2016-04-23_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKP_2016-11-11_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51HUD_2016-12-22_final.stac-item
2017-03-25 11:38:25	ga_s2am_ard_3-2-1_51KTT_2017-03-25_final.stac-item
2017-04-28 11:20:48	ga_s2am_ard_3-2-1_51KYP_2017-04-28_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50JML_2017-05-04_final.stac-item
2017-05-17 11:49:48	ga_s2am_ard_3-2-1_50JLL_2017-05-17_final.stac-item
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_51KVU_2017-09-08_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_49KHR_2017-09-27_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_50JLN_2017-10-17_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_51KVU_2018-02-08_final.stac-item
2018-03-30 11:39:33	ga_s2am_ard_3-2-1_51KVU_2018-03-30_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_51KUV_2018-06-08_final.stac-item
2018-06-25 11:32:58	ga_s2am_ard_3-2-1_51KUP_2018-06-25_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50HMK_2018-07-21_final.stac-item
2018-11-12 11:34:27	ga_s2am_ard_3-2-1_51JUN_2018-11-12_final.stac-item
2018-11-12 11:36:26	ga_s2am_ard_3-2-1_51HTE_2018-11-12_final.stac-item
2018-11-22 11:33:17	ga_s2am_ard_3-2-1_51KVT_2018-11-22_final.stac-item
2018-12-02 11:32:54	ga_s2am_ard_3-2-1_51KYT_2018-12-02_final.stac-item
2018-12-04 12:13:31	ga_s2am_ard_3-2-1_50KKB_2018-12-04_final.stac-item
2018-12-31 12:03:52	ga_s2am_ard_3-2-1_50KKA_2018-12-31_final.stac-item
2019-01-01 11:36:55	ga_s2am_ard_3-2-1_51HTC_2019-01-01_final.stac-item
2019-01-14 11:43:39	ga_s2am_ard_3-2-1_51KUR_2019-01-14_final.stac-item
2019-01-23 12:14:53	ga_s2am_ard_3-2-1_49JGM_2019-01-23_final.stac-item
2019-02-13 11:43:32	ga_s2am_ard_3-2-1_51KVR_2019-02-13_final.stac-item
2019-04-10 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2019-04-10_final.stac-item
2019-05-07 11:53:14	ga_s2am_ard_3-2-1_50KRC_2019-05-07_final.stac-item
2019-05-21 11:37:01	ga_s2am_ard_3-2-1_51HUC_2019-05-21_final.stac-item
2019-07-27 11:26:37	ga_s2am_ard_3-2-1_51HUE_2019-07-27_final.stac-item
2019-08-02 11:43:23	ga_s2am_ard_3-2-1_50KRC_2019-08-02_final.stac-item
2019-08-29 11:37:02	ga_s2am_ard_3-2-1_51HTC_2019-08-29_final.stac-item
2019-10-15 11:27:01	ga_s2am_ard_3-2-1_51HVC_2019-10-15_final.stac-item
2019-11-04 11:23:03	ga_s2am_ard_3-2-1_51KXU_2019-11-04_final.stac-item
2019-11-17 11:32:16	ga_s2am_ard_3-2-1_51KWB_2019-11-17_final.stac-item
2019-11-30 11:43:21	ga_s2am_ard_3-2-1_50KQC_2019-11-30_final.stac-item
2019-12-20 11:46:09	ga_s2am_ard_3-2-1_50JQL_2019-12-20_final.stac-item
2020-03-09 11:42:53	ga_s2am_ard_3-2-1_51KVU_2020-03-09_final.stac-item
2020-03-20 11:16:37	ga_s2am_ard_3-2-1_51HXD_2020-03-20_final.stac-item
2020-04-25 11:33:07	ga_s2am_ard_3-2-1_51KVU_2020-04-25_final.stac-item
2020-04-29 11:16:25	ga_s2am_ard_3-2-1_51HYE_2020-04-29_final.stac-item
2020-05-04 12:04:08	ga_s2am_ard_3-2-1_50KKA_2020-05-04_final.stac-item
2020-06-27 11:42:51	ga_s2am_ard_3-2-1_51KUV_2020-06-27_final.stac-item
2020-07-23 12:06:09	ga_s2am_ard_3-2-1_50JLM_2020-07-23_final.stac-item
2020-08-12 12:04:52	ga_s2am_ard_3-2-1_49JGN_2020-08-12_final.stac-item
2020-08-22 12:04:01	ga_s2am_ard_3-2-1_50KLA_2020-08-22_final.stac-item
2020-09-19 11:26:45	ga_s2am_ard_3-2-1_51HWD_2020-09-19_final.stac-item
2020-10-05 11:42:18	ga_s2am_ard_3-2-1_51KVB_2020-10-05_final.stac-item
2020-10-15 11:42:51	ga_s2am_ard_3-2-1_51KUV_2020-10-15_final.stac-item
2020-10-22 11:33:27	ga_s2am_ard_3-2-1_51KUT_2020-10-22_final.stac-item
2020-10-28 11:56:01	ga_s2am_ard_3-2-1_50JLN_2020-10-28_final.stac-item
2020-11-20 12:05:46	ga_s2am_ard_3-2-1_49JGJ_2020-11-20_final.stac-item
2021-01-03 11:44:13	ga_s2am_ard_3-2-1_51KUP_2021-01-03_final.stac-item
2021-01-26 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-01-26_final.stac-item
2021-04-06 11:52:30	ga_s2am_ard_3-2-1_50KQF_2021-04-06_final
2021-04-06 11:55:38	ga_s2am_ard_3-2-1_50JLP_2021-04-06_final.stac-item
2021-06-02 11:47:03	ga_s2am_ard_3-2-1_50HPH_2021-06-02_final.stac-item
2021-07-29 11:37:06	ga_s2am_ard_3-2-1_50HQH_2021-07-29_final.stac-item
2021-08-08 11:32:25	ga_s2am_ard_3-2-1_51KYA_2021-08-08_final.stac-item
2021-08-17 12:03:26	ga_s2am_ard_3-2-1_50KMC_2021-08-17_final.stac-item
2021-09-07 11:32:41	ga_s2am_ard_3-2-1_51KXV_2021-09-07_final.stac-item
2021-09-17 11:36:40	ga_s2am_ard_3-2-1_50HPK_2021-09-17_final.stac-item
2021-10-17 11:34:36	ga_s2am_ard_3-2-1_51JWN_2021-10-17_final.stac-item
2021-10-20 11:45:59	ga_s2am_ard_3-2-1_50JNN_2021-10-20_final.stac-item
2021-12-03 11:26:35	ga_s2am_ard_3-2-1_51HXD_2021-12-03_final.stac-item
2022-01-12 11:24:05	ga_s2am_ard_3-2-1_51KZP_2022-01-12_final.stac-item
2022-01-25 11:32:51	ga_s2am_ard_3-2-1_51KYU_2022-01-25_final.stac-item
2022-03-13 11:23:26	ga_s2am_ard_3-2-1_51KXS_2022-03-13_final.stac-item
2022-03-29 11:44:40	ga_s2am_ard_3-2-1_50JPT_2022-03-29_final.stac-item
2022-04-08 11:42:57	ga_s2am_ard_3-2-1_51KVU_2022-04-08_final.stac-item
2022-04-25 11:32:24	ga_s2am_ard_3-2-1_51KVB_2022-04-25_final.stac-item
2022-05-21 11:53:24	ga_s2am_ard_3-2-1_50KQC_2022-05-21_final.stac-item
2022-06-04 11:34:13	ga_s2am_ard_3-2-1_51KXP_2022-06-04_final.stac-item
2022-06-17 11:46:49	ga_s2am_ard_3-2-1_50HNK_2022-06-17_final.stac-item
2022-07-10 11:56:02	ga_s2am_ard_3-2-1_50JNN_2022-07-10_final.stac-item
2022-08-06 11:46:37	ga_s2am_ard_3-2-1_50JML_2022-08-06_final.stac-item
2022-10-24 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-10-24_final.stac-item
2022-12-04 11:44:02	ga_s2am_ard_3-2-1_50KRV_2022-12-04_final.stac-item
2023-02-16 11:25:53	ga_s2am_ard_3-2-1_51JWG_2023-02-16_nrt.stac-item
2023-02-22 11:43:30	ga_s2am_ard_3-2-1_51KTS_2023-02-22_nrt.stac-item
2023-02-22 11:43:30	ga_s2am_ard_3-2-1_51KTS_2023-02-22_final
2023-04-23 11:42:40	ga_s2am_ard_3-2-1_51KUV_2023-04-23_final
2023-05-03 11:44:49	ga_s2am_ard_3-2-1_50JQS_2023-05-03_final
2023-06-19 11:32:48	ga_s2am_ard_3-2-1_51KWV_2023-06-19_final
2023-07-15 11:56:09	ga_s2am_ard_3-2-1_50JNM_2023-07-15_final
2023-07-18 12:03:28	ga_s2am_ard_3-2-1_50KMC_2023-07-18_final
2023-08-08 11:32:33	ga_s2am_ard_3-2-1_51KWA_2023-08-08_final
2023-08-28 11:32:46	ga_s2am_ard_3-2-1_51KXV_2023-08-28_final
2023-08-31 11:46:53	ga_s2am_ard_3-2-1_50HPJ_2023-08-31_final
2023-09-23 11:53:12	ga_s2am_ard_3-2-1_50KRC_2023-09-23_final
2023-09-26 12:05:57	ga_s2am_ard_3-2-1_50JKN_2023-09-26_final
2023-10-03 11:57:11	ga_s2am_ard_3-2-1_50HLH_2023-10-03_final
2023-10-26 12:05:15	ga_s2am_ard_3-2-1_49JGL_2023-10-26_final
2023-11-06 11:32:33	ga_s2am_ard_3-2-1_51KWA_2023-11-06_final
2023-11-28 12:13:51	ga_s2am_ard_3-2-1_49KGR_2023-11-28_final
2024-01-25 11:33:54	ga_s2am_ard_3-2-1_51KVQ_2024-01-25_final
2024-01-25 11:33:57	ga_s2am_ard_3-2-1_51KUQ_2024-01-25_final
2024-04-03 12:03:57	ga_s2am_ard_3-2-1_49KHR_2024-04-03_final
2024-04-04 11:33:45	ga_s2am_ard_3-2-1_51KUR_2024-04-04_final
2024-04-17 11:42:49	ga_s2am_ard_3-2-1_51KUV_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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