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
2016-04-23 11:20:22	ga_s2am_ard_3-2-1_51HTC_2016-04-23_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50KNB_2016-07-21_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JKP_2016-11-11_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51KTT_2016-12-15_final.stac-item
2017-03-25 11:44:58	ga_s2am_ard_3-2-1_50HNH_2017-03-25_final.stac-item
2017-04-21 11:34:59	ga_s2am_ard_3-2-1_51HTD_2017-04-21_final.stac-item
2018-01-19 11:41:03	ga_s2am_ard_3-2-1_50KRC_2018-01-19_final.stac-item
2018-01-28 12:13:16	ga_s2am_ard_3-2-1_49KHR_2018-01-28_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_51KTU_2018-02-08_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_50JRT_2018-04-09_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_51HUD_2018-05-16_final.stac-item
2018-07-19 11:15:21	ga_s2am_ard_3-2-1_51HXD_2018-07-19_final.stac-item
2018-08-17 11:45:55	ga_s2am_ard_3-2-1_50HNK_2018-08-17_final.stac-item
2018-11-21 12:04:56	ga_s2am_ard_3-2-1_49JGM_2018-11-21_final.stac-item
2018-12-22 11:34:17	ga_s2am_ard_3-2-1_51JWN_2018-12-22_final.stac-item
2018-12-22 11:36:54	ga_s2am_ard_3-2-1_50HQH_2018-12-22_final.stac-item
2018-12-29 11:26:55	ga_s2am_ard_3-2-1_51HUC_2018-12-29_final.stac-item
2019-02-13 11:43:15	ga_s2am_ard_3-2-1_50KRC_2019-02-13_final.stac-item
2019-02-17 11:26:04	ga_s2am_ard_3-2-1_51JXF_2019-02-17_final.stac-item
2019-03-22 11:36:46	ga_s2am_ard_3-2-1_50HQJ_2019-03-22_final.stac-item
2019-04-10 12:04:29	ga_s2am_ard_3-2-1_50KKU_2019-04-10_final.stac-item
2019-04-17 11:53:24	ga_s2am_ard_3-2-1_50KPC_2019-04-17_final.stac-item
2019-07-16 11:53:16	ga_s2am_ard_3-2-1_50KRC_2019-07-16_final.stac-item
2019-08-03 11:15:29	ga_s2am_ard_3-2-1_51JYJ_2019-08-03_final.stac-item
2019-09-05 11:26:47	ga_s2am_ard_3-2-1_51HUD_2019-09-05_final.stac-item
2019-09-15 11:26:17	ga_s2am_ard_3-2-1_51JUF_2019-09-15_final.stac-item
2019-10-21 11:46:08	ga_s2am_ard_3-2-1_50JPM_2019-10-21_final.stac-item
2019-11-06 12:05:03	ga_s2am_ard_3-2-1_49JGM_2019-11-06_final.stac-item
2019-11-23 11:53:25	ga_s2am_ard_3-2-1_50KNC_2019-11-23_final.stac-item
2019-12-16 12:03:53	ga_s2am_ard_3-2-1_50KKA_2019-12-16_final.stac-item
2020-04-15 11:34:57	ga_s2am_ard_3-2-1_51JVL_2020-04-15_final.stac-item
2020-04-21 11:56:19	ga_s2am_ard_3-2-1_50JNL_2020-04-21_final.stac-item
2020-05-15 11:34:22	ga_s2am_ard_3-2-1_51KUP_2020-05-15_final.stac-item
2020-05-25 11:37:12	ga_s2am_ard_3-2-1_50HPH_2020-05-25_final.stac-item
2020-06-20 11:56:14	ga_s2am_ard_3-2-1_50JMM_2020-06-20_final.stac-item
2020-08-23 11:36:23	ga_s2am_ard_3-2-1_51JTF_2020-08-23_final.stac-item
2020-09-02 11:35:42	ga_s2am_ard_3-2-1_50JQP_2020-09-02_final.stac-item
2020-09-12 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2020-09-12_final.stac-item
2020-09-28 11:52:25	ga_s2am_ard_3-2-1_50KQG_2020-09-28_final
2020-11-10 12:05:16	ga_s2am_ard_3-2-1_50JKR_2020-11-10_final.stac-item
2020-11-11 11:36:21	ga_s2am_ard_3-2-1_51JTF_2020-11-11_final.stac-item
2020-11-14 11:43:08	ga_s2am_ard_3-2-1_50KRD_2020-11-14_final.stac-item
2020-11-14 11:43:21	ga_s2am_ard_3-2-1_51KTT_2020-11-14_final.stac-item
2020-12-08 11:26:59	ga_s2am_ard_3-2-1_51HUC_2020-12-08_final.stac-item
2021-01-16 11:52:20	ga_s2am_ard_3-2-1_50KQG_2021-01-16_final
2021-02-09 11:37:00	ga_s2am_ard_3-2-1_51HTC_2021-02-09_final.stac-item
2021-03-03 12:14:41	ga_s2am_ard_3-2-1_49JGN_2021-03-03_final.stac-item
2021-03-10 12:03:19	ga_s2am_ard_3-2-1_50KNC_2021-03-10_final.stac-item
2021-04-10 11:36:23	ga_s2am_ard_3-2-1_51HUE_2021-04-10_final.stac-item
2021-04-12 12:14:14	ga_s2am_ard_3-2-1_50KKU_2021-04-12_final.stac-item
2021-04-29 12:03:56	ga_s2am_ard_3-2-1_49KHR_2021-04-29_final.stac-item
2021-05-13 11:42:16	ga_s2am_ard_3-2-1_51KUB_2021-05-13_final
2021-05-26 11:57:21	ga_s2am_ard_3-2-1_50HMG_2021-05-26_final
2021-06-09 11:34:26	ga_s2am_ard_3-2-1_51JWN_2021-06-09_final.stac-item
2021-06-09 11:35:34	ga_s2am_ard_3-2-1_51JTJ_2021-06-09_final.stac-item
2021-06-26 11:27:00	ga_s2am_ard_3-2-1_51HVC_2021-06-26_final.stac-item
2021-07-05 11:56:43	ga_s2am_ard_3-2-1_50HLK_2021-07-05_final.stac-item
2021-08-11 11:47:09	ga_s2am_ard_3-2-1_50HNH_2021-08-11_final.stac-item
2021-08-12 11:14:26	ga_s2am_ard_3-2-1_51JZN_2021-08-12_final.stac-item
2021-08-17 12:04:34	ga_s2am_ard_3-2-1_49KGP_2021-08-17_final.stac-item
2021-09-26 12:04:17	ga_s2am_ard_3-2-1_49KHQ_2021-09-26_final.stac-item
2021-09-30 11:46:30	ga_s2am_ard_3-2-1_50JML_2021-09-30_final.stac-item
2021-10-14 11:26:52	ga_s2am_ard_3-2-1_51HUD_2021-10-14_final.stac-item
2021-10-23 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2021-10-23_final.stac-item
2021-11-10 11:14:44	ga_s2am_ard_3-2-1_51JYM_2021-11-10_final.stac-item
2021-11-20 11:16:26	ga_s2am_ard_3-2-1_51HXE_2021-11-20_final.stac-item
2022-01-07 12:13:56	ga_s2am_ard_3-2-1_49KHR_2022-01-07_final.stac-item
2022-02-21 11:24:34	ga_s2am_ard_3-2-1_51JZM_2022-02-21_final.stac-item
2022-04-01 11:52:22	ga_s2am_ard_3-2-1_50KQG_2022-04-01_final
2022-04-07 12:14:42	ga_s2am_ard_3-2-1_49JGN_2022-04-07_final.stac-item
2022-04-18 11:43:55	ga_s2am_ard_3-2-1_50KQA_2022-04-18_final.stac-item
2022-04-22 11:26:45	ga_s2am_ard_3-2-1_51HWD_2022-04-22_final.stac-item
2022-04-28 11:46:35	ga_s2am_ard_3-2-1_50HQK_2022-04-28_final.stac-item
2022-05-02 11:25:00	ga_s2am_ard_3-2-1_51JXL_2022-05-02_final.stac-item
2022-05-25 11:37:05	ga_s2am_ard_3-2-1_51HUC_2022-05-25_final.stac-item
2022-06-04 11:37:11	ga_s2am_ard_3-2-1_50HQH_2022-06-04_final.stac-item
2022-06-27 11:44:11	ga_s2am_ard_3-2-1_51KUQ_2022-06-27_final.stac-item
2022-07-08 11:15:09	ga_s2am_ard_3-2-1_51JYL_2022-07-08_final.stac-item
2022-08-09 11:53:36	ga_s2am_ard_3-2-1_50KNC_2022-08-09_final.stac-item
2022-09-22 11:35:08	ga_s2am_ard_3-2-1_51JUL_2022-09-22_final.stac-item
2022-10-09 11:25:48	ga_s2am_ard_3-2-1_51JWH_2022-10-09_final.stac-item
2022-10-15 11:45:58	ga_s2am_ard_3-2-1_50JNN_2022-10-15_final.stac-item
2022-11-01 11:34:21	ga_s2am_ard_3-2-1_51KUP_2022-11-01_final.stac-item
2022-11-18 11:24:38	ga_s2am_ard_3-2-1_51JYM_2022-11-18_final.stac-item
2022-11-18 11:27:03	ga_s2am_ard_3-2-1_51HUC_2022-11-18_final.stac-item
2022-12-20 12:05:13	ga_s2am_ard_3-2-1_49JGL_2022-12-20_final.stac-item
2022-12-25 11:16:39	ga_s2am_ard_3-2-1_51HXD_2022-12-25_final.stac-item
2023-02-19 11:34:46	ga_s2am_ard_3-2-1_51JTM_2023-02-19_nrt.stac-item
2023-02-19 11:36:45	ga_s2am_ard_3-2-1_50HQJ_2023-02-19_final
2023-04-06 11:53:45	ga_s2am_ard_3-2-1_50KQA_2023-04-06_final
2023-05-09 12:05:14	ga_s2am_ard_3-2-1_49JGL_2023-05-09_final
2023-05-26 11:53:14	ga_s2am_ard_3-2-1_50KRC_2023-05-26_final
2023-09-20 11:46:17	ga_s2am_ard_3-2-1_50JQL_2023-09-20_final
2023-10-14 11:27:00	ga_s2am_ard_3-2-1_51HUC_2023-10-14_final
2023-10-24 11:24:55	ga_s2am_ard_3-2-1_51JXL_2023-10-24_final
2023-11-29 11:43:10	ga_s2am_ard_3-2-1_50KRC_2023-11-29_final
2024-02-13 12:03:38	ga_s2am_ard_3-2-1_50KLB_2024-02-13_final
2024-04-04 11:34:22	ga_s2am_ard_3-2-1_51JWN_2024-04-04_final
2024-04-06 12:13:52	ga_s2am_ard_3-2-1_49KHR_2024-04-06_final
2024-04-07 11:47:23	ga_s2am_ard_3-2-1_50HMG_2024-04-07_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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