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
2015-11-30 10:27:39	ga_s2am_ard_3-2-1_54LXM_2015-11-30_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51KVA_2016-01-20_final.stac-item
2016-02-15 11:59:34	ga_s2am_ard_3-2-1_49JGM_2016-02-15_final.stac-item
2016-04-13 11:26:08	ga_s2am_ard_3-2-1_51HVE_2016-04-13_final.stac-item
2016-07-07 10:28:09	ga_s2am_ard_3-2-1_53JNN_2016-07-07_final.stac-item
2016-07-14 10:18:58	ga_s2am_ard_3-2-1_54LXJ_2016-07-14_final.stac-item
2016-07-14 10:26:41	ga_s2am_ard_3-2-1_54HTG_2016-07-14_final.stac-item
2016-10-15 10:27:57	ga_s2am_ard_3-2-1_53JNN_2016-10-15_final.stac-item
2016-11-04 10:31:19	ga_s2am_ard_3-2-1_53JPM_2016-11-04_final.stac-item
2017-01-19 10:47:10	ga_s2am_ard_3-2-1_53KLA_2017-01-19_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_50JLQ_2017-09-07_final.stac-item
2017-10-23 10:43:07	ga_s2am_ard_3-2-1_53KNP_2017-10-23_final.stac-item
2017-12-12 10:43:01	ga_s2am_ard_3-2-1_53JKG_2017-12-12_final.stac-item
2018-02-11 11:50:47	ga_s2am_ard_3-2-1_50JPR_2018-02-11_final.stac-item
2018-03-19 10:27:04	ga_s2am_ard_3-2-1_54LWK_2018-03-19_final.stac-item
2018-05-01 10:37:29	ga_s2am_ard_3-2-1_53LNC_2018-05-01_final.stac-item
2018-05-28 10:27:09	ga_s2am_ard_3-2-1_54JTS_2018-05-28_final.stac-item
2018-06-08 11:40:20	ga_s2am_ard_3-2-1_50KRV_2018-06-08_final.stac-item
2018-07-17 10:27:09	ga_s2am_ard_3-2-1_54KTU_2018-07-17_final.stac-item
2018-09-15 10:27:04	ga_s2am_ard_3-2-1_53JPL_2018-09-15_final.stac-item
2018-10-28 10:37:24	ga_s2am_ard_3-2-1_52JGL_2018-10-28_final.stac-item
2018-12-02 11:32:46	ga_s2am_ard_3-2-1_51KXU_2018-12-02_final.stac-item
2019-01-13 10:31:59	ga_s2am_ard_3-2-1_54KTF_2019-01-13_final.stac-item
2019-04-04 11:46:44	ga_s2am_ard_3-2-1_50HQJ_2019-04-04_final.stac-item
2019-06-08 10:51:02	ga_s2am_ard_3-2-1_53LLF_2019-06-08_final.stac-item
2019-07-20 11:33:27	ga_s2am_ard_3-2-1_51KUT_2019-07-20_final.stac-item
2019-07-22 10:36:15	ga_s2am_ard_3-2-1_53HME_2019-07-22_final.stac-item
2019-08-24 10:44:30	ga_s2am_ard_3-2-1_53JPL_2019-08-24_final.stac-item
2019-09-08 11:33:44	ga_s2am_ard_3-2-1_51KVR_2019-09-08_final.stac-item
2019-09-11 11:43:10	ga_s2am_ard_3-2-1_51KVT_2019-09-11_final.stac-item
2019-10-08 11:33:01	ga_s2am_ard_3-2-1_51KWU_2019-10-08_final.stac-item
2019-10-15 11:23:16	ga_s2am_ard_3-2-1_51KXT_2019-10-15_final.stac-item
2019-10-20 10:34:39	ga_s2am_ard_3-2-1_53JPL_2019-10-20_final.stac-item
2019-12-17 11:33:32	ga_s2am_ard_3-2-1_51KXR_2019-12-17_final.stac-item
2020-02-07 10:34:06	ga_s2am_ard_3-2-1_54JTS_2020-02-07_final.stac-item
2020-05-22 11:23:12	ga_s2am_ard_3-2-1_52KBC_2020-05-22_final.stac-item
2020-07-04 11:33:14	ga_s2am_ard_3-2-1_51KXT_2020-07-04_final.stac-item
2020-08-23 11:33:00	ga_s2am_ard_3-2-1_51KXU_2020-08-23_final.stac-item
2020-08-25 10:34:09	ga_s2am_ard_3-2-1_53JQN_2020-08-25_final.stac-item
2020-10-22 11:33:14	ga_s2am_ard_3-2-1_51KXT_2020-10-22_final.stac-item
2020-10-22 11:33:33	ga_s2am_ard_3-2-1_51KWS_2020-10-22_final.stac-item
2020-11-25 11:13:27	ga_s2am_ard_3-2-1_52KBB_2020-11-25_final.stac-item
2020-12-20 10:21:13	ga_s2am_ard_3-2-1_54LWJ_2020-12-20_final.stac-item
2020-12-25 11:13:53	ga_s2am_ard_3-2-1_52KBV_2020-12-25_final.stac-item
2021-01-20 11:33:03	ga_s2am_ard_3-2-1_51KYT_2021-01-20_final.stac-item
2021-03-04 11:42:45	ga_s2am_ard_3-2-1_51KUV_2021-03-04_final.stac-item
2021-04-17 11:23:04	ga_s2am_ard_3-2-1_51KYT_2021-04-17_final.stac-item
2021-05-09 10:24:18	ga_s2am_ard_3-2-1_53JRM_2021-05-09_final.stac-item
2021-05-19 10:24:19	ga_s2am_ard_3-2-1_53JRM_2021-05-19_final.stac-item
2021-06-06 11:23:07	ga_s2am_ard_3-2-1_52KBC_2021-06-06_final.stac-item
2021-06-17 10:53:32	ga_s2am_ard_3-2-1_52KGA_2021-06-17_final.stac-item
2021-06-30 11:03:18	ga_s2am_ard_3-2-1_52KFB_2021-06-30_final.stac-item
2021-07-23 11:10:28	ga_s2am_ard_3-2-1_52LHN_2021-07-23_final.stac-item
2021-07-23 11:13:17	ga_s2am_ard_3-2-1_52KBC_2021-07-23_final.stac-item
2021-07-31 10:35:48	ga_s2am_ard_3-2-1_53JQF_2021-07-31_final.stac-item
2021-08-08 11:37:00	ga_s2am_ard_3-2-1_51HUC_2021-08-08_final.stac-item
2021-08-10 10:34:17	ga_s2am_ard_3-2-1_54JTS_2021-08-10_final.stac-item
2021-08-20 10:35:58	ga_s2am_ard_3-2-1_53JMF_2021-08-20_final.stac-item
2021-09-09 10:34:14	ga_s2am_ard_3-2-1_53JNN_2021-09-09_final.stac-item
2021-09-10 11:42:13	ga_s2am_ard_3-2-1_51KVB_2021-09-10_final.stac-item
2022-05-15 11:33:35	ga_s2am_ard_3-2-1_51KVS_2022-05-15_final.stac-item
2022-05-25 11:33:38	ga_s2am_ard_3-2-1_51KVS_2022-05-25_final.stac-item
2022-05-27 10:33:53	ga_s2am_ard_3-2-1_53KRP_2022-05-27_final.stac-item
2022-06-09 10:40:56	ga_s2am_ard_3-2-1_53LPF_2022-06-09_final.stac-item
2022-06-14 11:33:49	ga_s2am_ard_3-2-1_51KXR_2022-06-14_final.stac-item
2022-07-19 10:45:43	ga_s2am_ard_3-2-1_53JNG_2022-07-19_final.stac-item
2022-08-30 11:23:18	ga_s2am_ard_3-2-1_52KBC_2022-08-30_final.stac-item
2022-10-12 11:33:18	ga_s2am_ard_3-2-1_51KWT_2022-10-12_final.stac-item
2022-10-13 11:06:29	ga_s2am_ard_3-2-1_52HBK_2022-10-13_final.stac-item
2022-12-22 11:01:07	ga_s2am_ard_3-2-1_53LLE_2022-12-22_final.stac-item
2023-01-31 11:00:47	ga_s2am_ard_3-2-1_52LGM_2023-01-31_final.stac-item
2023-02-19 11:33:42	ga_s2am_ard_3-2-1_51KVR_2023-02-19_nrt.stac-item
2023-03-07 10:13:26	ga_s2am_ard_3-2-1_54KWV_2023-03-07_final
2023-03-30 10:20:58	ga_s2am_ard_3-2-1_54LWK_2023-03-30_final
2023-04-19 10:24:32	ga_s2am_ard_3-2-1_54JTR_2023-04-19_final
2023-04-22 10:34:12	ga_s2am_ard_3-2-1_53JNN_2023-04-22_final
2023-04-26 10:15:58	ga_s2am_ard_3-2-1_54HVK_2023-04-26_final
2023-05-06 10:16:00	ga_s2am_ard_3-2-1_54HXJ_2023-05-06_final
2023-06-03 11:13:34	ga_s2am_ard_3-2-1_52KEA_2023-06-03_final
2023-06-06 11:22:59	ga_s2am_ard_3-2-1_51KYU_2023-06-06_final
2023-06-07 10:50:59	ga_s2am_ard_3-2-1_53LMF_2023-06-07_final
2023-06-14 10:46:02	ga_s2am_ard_3-2-1_53JKF_2023-06-14_final
2023-06-18 10:24:38	ga_s2am_ard_3-2-1_54JTR_2023-06-18_final
2023-06-20 11:05:30	ga_s2am_ard_3-2-1_52JFN_2023-06-20_final
2023-06-23 11:15:25	ga_s2am_ard_3-2-1_52JBP_2023-06-23_final
2023-07-24 10:46:14	ga_s2am_ard_3-2-1_53HLE_2023-07-24_final
2023-08-08 11:34:54	ga_s2am_ard_3-2-1_51JTM_2023-08-08_final
2023-08-28 11:33:36	ga_s2am_ard_3-2-1_51KVS_2023-08-28_final
2023-09-02 10:44:12	ga_s2am_ard_3-2-1_53JNN_2023-09-02_final
2023-09-22 10:41:31	ga_s2am_ard_3-2-1_54LTH_2023-09-22_nrt
2023-12-11 10:41:26	ga_s2am_ard_3-2-1_53LRC_2023-12-11_final
2023-12-11 10:43:58	ga_s2am_ard_3-2-1_53JPN_2023-12-11_final
2024-01-16 11:01:21	ga_s2am_ard_3-2-1_52LHJ_2024-01-16_final
2024-02-06 10:34:14	ga_s2am_ard_3-2-1_53JQM_2024-02-06_final
2024-02-23 10:26:44	ga_s2am_ard_3-2-1_53HQB_2024-02-23_final
2024-02-26 10:34:35	ga_s2am_ard_3-2-1_53JPL_2024-02-26_final
2024-03-06 11:04:07	ga_s2am_ard_3-2-1_52KDU_2024-03-06_final
2024-03-24 10:25:12	ga_s2am_ard_3-2-1_54JVN_2024-03-24_final
2024-05-18 11:13:56	ga_s2am_ard_3-2-1_52KBV_2024-05-18_final
2024-05-27 10:05:34	ga_s2am_ard_3-2-1_54JWM_2024-05-27_nrt

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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