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
2016-02-02 11:48:17	ga_s2am_ard_3-2-1_50KQC_2016-02-02_final.stac-item
2016-08-17 11:40:15	ga_s2am_ard_3-2-1_51KUU_2016-08-17_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_50JLN_2016-11-11_final.stac-item
2016-11-16 11:07:11	ga_s2am_ard_3-2-1_52LGK_2016-11-16_final.stac-item
2016-11-28 11:49:54	ga_s2am_ard_3-2-1_50HLJ_2016-11-28_final.stac-item
2016-12-28 11:45:05	ga_s2am_ard_3-2-1_50KQC_2016-12-28_final.stac-item
2017-02-14 11:07:06	ga_s2am_ard_3-2-1_52LGM_2017-02-14_final.stac-item
2017-05-11 11:28:39	ga_s2am_ard_3-2-1_51KVT_2017-05-11_final.stac-item
2017-05-23 12:14:44	ga_s2am_ard_3-2-1_49JGM_2017-05-23_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_50JKM_2017-05-30_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50HQJ_2017-07-03_final.stac-item
2017-07-23 11:38:36	ga_s2am_ard_3-2-1_51LUE_2017-07-23_final.stac-item
2017-10-10 10:32:09	ga_s2am_ard_3-2-1_53HNB_2017-10-10_final.stac-item
2017-11-08 10:57:14	ga_s2am_ard_3-2-1_52KHF_2017-11-08_final.stac-item
2017-11-08 11:02:57	ga_s2am_ard_3-2-1_52JCL_2017-11-08_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_51KWQ_2018-02-02_final.stac-item
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_52KDG_2018-02-19_final.stac-item
2018-04-16 11:33:46	ga_s2am_ard_3-2-1_51KWQ_2018-04-16_final.stac-item
2018-06-18 11:37:34	ga_s2am_ard_3-2-1_51KVT_2018-06-18_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_51KUT_2018-06-28_final.stac-item
2018-08-07 11:46:07	ga_s2am_ard_3-2-1_50HQJ_2018-08-07_final.stac-item
2018-11-29 11:23:05	ga_s2am_ard_3-2-1_51KXT_2018-11-29_final.stac-item
2018-12-02 11:33:22	ga_s2am_ard_3-2-1_51KVS_2018-12-02_final.stac-item
2019-01-01 11:32:52	ga_s2am_ard_3-2-1_51KWU_2019-01-01_final.stac-item
2019-01-05 11:12:47	ga_s2am_ard_3-2-1_52KCD_2019-01-05_final.stac-item
2019-02-03 11:43:15	ga_s2am_ard_3-2-1_50KRC_2019-02-03_final.stac-item
2019-04-04 11:43:16	ga_s2am_ard_3-2-1_51KUT_2019-04-04_final.stac-item
2019-04-17 11:56:16	ga_s2am_ard_3-2-1_50JKM_2019-04-17_final.stac-item
2019-05-11 11:33:07	ga_s2am_ard_3-2-1_51KWU_2019-05-11_final.stac-item
2019-07-13 11:43:16	ga_s2am_ard_3-2-1_51KVT_2019-07-13_final.stac-item
2019-08-15 11:53:50	ga_s2am_ard_3-2-1_50KQA_2019-08-15_final.stac-item
2019-08-22 11:41:34	ga_s2am_ard_3-2-1_51LUE_2019-08-22_final.stac-item
2019-10-28 11:34:14	ga_s2am_ard_3-2-1_51KWP_2019-10-28_final.stac-item
2019-11-04 11:24:00	ga_s2am_ard_3-2-1_51KXQ_2019-11-04_final.stac-item
2020-01-09 11:42:54	ga_s2am_ard_3-2-1_51KUU_2020-01-09_final.stac-item
2020-01-10 11:15:37	ga_s2am_ard_3-2-1_51JXH_2020-01-10_final.stac-item
2020-01-31 10:45:40	ga_s2am_ard_3-2-1_52JGM_2020-01-31_final.stac-item
2020-02-21 11:55:18	ga_s2am_ard_3-2-1_50JMQ_2020-02-21_final.stac-item
2020-03-20 11:10:58	ga_s2am_ard_3-2-1_52LFL_2020-03-20_final.stac-item
2020-04-02 11:23:56	ga_s2am_ard_3-2-1_51KYQ_2020-04-02_final.stac-item
2020-04-14 12:03:16	ga_s2am_ard_3-2-1_50KMC_2020-04-14_final.stac-item
2020-04-21 11:53:11	ga_s2am_ard_3-2-1_50KRC_2020-04-21_final.stac-item
2020-07-14 11:33:32	ga_s2am_ard_3-2-1_51KWS_2020-07-14_final.stac-item
2020-07-24 11:33:33	ga_s2am_ard_3-2-1_51KWS_2020-07-24_final.stac-item
2020-08-16 11:43:17	ga_s2am_ard_3-2-1_51KVT_2020-08-16_final.stac-item
2020-10-22 11:36:19	ga_s2am_ard_3-2-1_51JUF_2020-10-22_final.stac-item
2021-01-24 11:13:30	ga_s2am_ard_3-2-1_52KEA_2021-01-24_final.stac-item
2021-01-24 11:13:55	ga_s2am_ard_3-2-1_52KBV_2021-01-24_final.stac-item
2021-03-08 11:26:18	ga_s2am_ard_3-2-1_51JUF_2021-03-08_final.stac-item
2021-03-11 11:33:45	ga_s2am_ard_3-2-1_51KVR_2021-03-11_final.stac-item
2021-03-23 10:36:57	ga_s2am_ard_3-2-1_53HPA_2021-03-23_final.stac-item
2021-04-17 11:23:51	ga_s2am_ard_3-2-1_51KXQ_2021-04-17_final.stac-item
2021-06-02 11:46:20	ga_s2am_ard_3-2-1_50JPL_2021-06-02_final.stac-item
2021-06-09 11:33:31	ga_s2am_ard_3-2-1_51KVS_2021-06-09_final.stac-item
2021-07-31 10:36:13	ga_s2am_ard_3-2-1_53HME_2021-07-31_final.stac-item
2021-08-18 11:33:15	ga_s2am_ard_3-2-1_51KWT_2021-08-18_final.stac-item
2021-10-04 11:24:02	ga_s2am_ard_3-2-1_51KXQ_2021-10-04_final.stac-item
2021-11-10 11:16:33	ga_s2am_ard_3-2-1_51HWE_2021-11-10_final.stac-item
2021-12-28 12:14:22	ga_s2am_ard_3-2-1_49KHP_2021-12-28_final.stac-item
2022-01-18 11:43:25	ga_s2am_ard_3-2-1_51KVS_2022-01-18_final.stac-item
2022-02-07 11:46:40	ga_s2am_ard_3-2-1_50HMK_2022-02-07_final.stac-item
2022-02-23 12:04:23	ga_s2am_ard_3-2-1_49KHQ_2022-02-23_final.stac-item
2022-03-09 11:42:50	ga_s2am_ard_3-2-1_51KUV_2022-03-09_final.stac-item
2022-04-02 11:26:02	ga_s2am_ard_3-2-1_51JVG_2022-04-02_final.stac-item
2022-05-31 11:54:48	ga_s2am_ard_3-2-1_50JMT_2022-05-31_final.stac-item
2022-08-27 11:11:14	ga_s2am_ard_3-2-1_52LFL_2022-08-27_final.stac-item
2022-09-22 11:33:20	ga_s2am_ard_3-2-1_51KWT_2022-09-22_final.stac-item
2022-09-25 11:41:40	ga_s2am_ard_3-2-1_51LUE_2022-09-25_final.stac-item
2022-10-15 11:43:01	ga_s2am_ard_3-2-1_51KVU_2022-10-15_final.stac-item
2022-10-22 11:33:44	ga_s2am_ard_3-2-1_51KWR_2022-10-22_final.stac-item
2022-11-25 11:14:23	ga_s2am_ard_3-2-1_52JBT_2022-11-25_final.stac-item
2022-11-26 10:45:46	ga_s2am_ard_3-2-1_52JGM_2022-11-26_final.stac-item
2023-01-20 11:33:22	ga_s2am_ard_3-2-1_51KWS_2023-01-20_final.stac-item
2023-02-10 11:01:59	ga_s2am_ard_3-2-1_52KGG_2023-02-10_final.stac-item
2023-02-15 11:56:37	ga_s2am_ard_3-2-1_50HLK_2023-02-15_nrt.stac-item
2023-02-15 11:56:37	ga_s2am_ard_3-2-1_50HLK_2023-02-15_final
2023-02-18 12:05:52	ga_s2am_ard_3-2-1_50JKN_2023-02-18_final
2023-02-19 11:33:35	ga_s2am_ard_3-2-1_51KXR_2023-02-19_final
2023-03-14 11:43:11	ga_s2am_ard_3-2-1_51KUT_2023-03-14_final
2023-04-16 11:53:10	ga_s2am_ard_3-2-1_50KRC_2023-04-16_final
2023-05-20 11:33:33	ga_s2am_ard_3-2-1_51KVS_2023-05-20_final
2023-07-01 10:36:15	ga_s2am_ard_3-2-1_53HME_2023-07-01_final
2023-07-12 11:43:16	ga_s2am_ard_3-2-1_51KVT_2023-07-12_final
2023-08-24 11:57:15	ga_s2am_ard_3-2-1_50HLH_2023-08-24_final
2023-08-27 10:26:56	ga_s2am_ard_3-2-1_53HPB_2023-08-27_final
2023-09-07 11:34:05	ga_s2am_ard_3-2-1_51KVQ_2023-09-07_final
2023-09-10 11:43:30	ga_s2am_ard_3-2-1_51KVS_2023-09-10_final
2023-10-10 11:43:28	ga_s2am_ard_3-2-1_51KUS_2023-10-10_final
2023-10-24 11:23:28	ga_s2am_ard_3-2-1_51KXS_2023-10-24_final
2023-11-26 11:33:32	ga_s2am_ard_3-2-1_51KXR_2023-11-26_final
2023-12-08 10:36:44	ga_s2am_ard_3-2-1_53HNB_2023-12-08_final
2023-12-10 11:15:28	ga_s2am_ard_3-2-1_52JCN_2023-12-10_final
2023-12-16 11:33:23	ga_s2am_ard_3-2-1_51KWS_2023-12-16_final
2023-12-16 11:33:48	ga_s2am_ard_3-2-1_51KXQ_2023-12-16_nrt
2023-12-20 11:11:48	ga_s2am_ard_3-2-1_52LDH_2023-12-20_final
2024-01-05 11:32:55	ga_s2am_ard_3-2-1_51KWU_2024-01-05_final
2024-01-18 11:41:50	ga_s2am_ard_3-2-1_51LVC_2024-01-18_final
2024-01-22 11:23:20	ga_s2am_ard_3-2-1_52KCA_2024-01-22_final
2024-02-15 11:00:42	ga_s2am_ard_3-2-1_52LHM_2024-02-15_final
2024-03-31 11:57:05	ga_s2am_ard_3-2-1_50HMH_2024-03-31_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

All years