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
2015-08-28 10:53:21	ga_s2am_ard_3-2-1_52JGT_2015-08-28_final
2016-01-24 11:19:37	ga_s2am_ard_3-2-1_51KXP_2016-01-24_final.stac-item
2016-07-08 11:40:16	ga_s2am_ard_3-2-1_51LUE_2016-07-08_final.stac-item
2016-07-26 11:02:15	ga_s2am_ard_3-2-1_52KFA_2016-07-26_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_51KWS_2016-08-24_final.stac-item
2016-09-09 11:56:06	ga_s2am_ard_3-2-1_50JLM_2016-09-09_final.stac-item
2017-03-21 12:04:34	ga_s2am_ard_3-2-1_49JGK_2017-03-21_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49JHN_2017-04-20_final.stac-item
2017-05-04 11:45:11	ga_s2am_ard_3-2-1_50JQN_2017-05-04_final.stac-item
2017-05-18 11:21:00	ga_s2am_ard_3-2-1_51JVF_2017-05-18_final.stac-item
2017-12-23 11:53:56	ga_s2am_ard_3-2-1_50HLH_2017-12-23_final.stac-item
2018-02-12 11:16:56	ga_s2am_ard_3-2-1_51KXU_2018-02-12_final.stac-item
2018-02-14 12:02:46	ga_s2am_ard_3-2-1_49KHP_2018-02-14_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51HVC_2018-02-22_final.stac-item
2018-06-21 11:53:43	ga_s2am_ard_3-2-1_50JMM_2018-06-21_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49KHQ_2018-07-24_final.stac-item
2018-08-01 11:17:00	ga_s2am_ard_3-2-1_52LDJ_2018-08-01_final.stac-item
2018-09-17 11:13:02	ga_s2am_ard_3-2-1_51HXD_2018-09-17_final.stac-item
2018-10-07 11:13:21	ga_s2am_ard_3-2-1_51JYM_2018-10-07_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49JGL_2018-11-01_final.stac-item
2018-11-24 12:13:47	ga_s2am_ard_3-2-1_50KKA_2018-11-24_final.stac-item
2018-12-11 12:05:47	ga_s2am_ard_3-2-1_50JKN_2018-12-11_final.stac-item
2018-12-15 11:43:09	ga_s2am_ard_3-2-1_51KTT_2018-12-15_final.stac-item
2018-12-22 11:36:44	ga_s2am_ard_3-2-1_50HPJ_2018-12-22_final.stac-item
2019-01-01 11:32:20	ga_s2am_ard_3-2-1_51KXA_2019-01-01_final.stac-item
2019-02-19 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-02-19_final.stac-item
2019-03-08 11:56:20	ga_s2am_ard_3-2-1_50JLL_2019-03-08_final.stac-item
2019-04-18 11:21:35	ga_s2am_ard_3-2-1_52LDJ_2019-04-18_final.stac-item
2019-05-08 11:24:09	ga_s2am_ard_3-2-1_52KBU_2019-05-08_final.stac-item
2019-05-24 11:45:50	ga_s2am_ard_3-2-1_50JQN_2019-05-24_final.stac-item
2019-06-14 11:13:33	ga_s2am_ard_3-2-1_52KEA_2019-06-14_final.stac-item
2019-07-30 11:33:07	ga_s2am_ard_3-2-1_51KXT_2019-07-30_final.stac-item
2019-08-05 11:56:04	ga_s2am_ard_3-2-1_50JKN_2019-08-05_final.stac-item
2019-12-07 11:36:29	ga_s2am_ard_3-2-1_51HTE_2019-12-07_final.stac-item
2019-12-16 12:04:34	ga_s2am_ard_3-2-1_50JLT_2019-12-16_final.stac-item
2020-02-03 10:53:13	ga_s2am_ard_3-2-1_52KHA_2020-02-03_final.stac-item
2020-02-05 11:31:27	ga_s2am_ard_3-2-1_51LZD_2020-02-05_final.stac-item
2020-02-05 11:36:54	ga_s2am_ard_3-2-1_50HQH_2020-02-05_final.stac-item
2020-03-03 11:24:00	ga_s2am_ard_3-2-1_51KWQ_2020-03-03_final.stac-item
2020-03-13 11:23:24	ga_s2am_ard_3-2-1_51KXS_2020-03-13_final.stac-item
2020-03-18 12:13:50	ga_s2am_ard_3-2-1_50KKA_2020-03-18_final.stac-item
2020-05-03 10:56:00	ga_s2am_ard_3-2-1_52JGL_2020-05-03_final.stac-item
2020-06-03 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-06-03_final.stac-item
2020-06-11 11:24:12	ga_s2am_ard_3-2-1_52KBU_2020-06-11_final.stac-item
2020-06-21 11:23:11	ga_s2am_ard_3-2-1_52KCC_2020-06-21_final.stac-item
2020-08-10 11:23:27	ga_s2am_ard_3-2-1_51KZS_2020-08-10_final.stac-item
2020-09-25 11:43:30	ga_s2am_ard_3-2-1_51KVS_2020-09-25_final.stac-item
2020-10-22 11:33:07	ga_s2am_ard_3-2-1_51KVU_2020-10-22_final.stac-item
2020-11-15 11:11:55	ga_s2am_ard_3-2-1_52LDH_2020-11-15_final.stac-item
2020-12-24 11:42:56	ga_s2am_ard_3-2-1_51KVU_2020-12-24_final.stac-item
2021-01-20 11:33:42	ga_s2am_ard_3-2-1_51KWR_2021-01-20_final.stac-item
2021-02-02 11:43:11	ga_s2am_ard_3-2-1_51KVT_2021-02-02_final.stac-item
2021-02-09 11:32:57	ga_s2am_ard_3-2-1_51KWU_2021-02-09_final.stac-item
2021-02-19 11:32:25	ga_s2am_ard_3-2-1_51KXA_2021-02-19_final.stac-item
2021-07-09 11:33:30	ga_s2am_ard_3-2-1_51KWS_2021-07-09_final.stac-item
2021-08-02 11:11:22	ga_s2am_ard_3-2-1_52LEK_2021-08-02_final
2021-08-28 11:37:02	ga_s2am_ard_3-2-1_51HTC_2021-08-28_final.stac-item
2021-09-29 12:15:14	ga_s2am_ard_3-2-1_49JGL_2021-09-29_final.stac-item
2021-10-04 11:23:44	ga_s2am_ard_3-2-1_51KYR_2021-10-04_final.stac-item
2021-10-11 11:13:59	ga_s2am_ard_3-2-1_52KBV_2021-10-11_final.stac-item
2021-11-03 11:21:32	ga_s2am_ard_3-2-1_52LDJ_2021-11-03_final.stac-item
2021-11-13 11:22:39	ga_s2am_ard_3-2-1_52KBE_2021-11-13_final.stac-item
2021-12-10 11:13:32	ga_s2am_ard_3-2-1_52KDA_2021-12-10_final.stac-item
2022-01-29 11:14:38	ga_s2am_ard_3-2-1_51JZM_2022-01-29_final.stac-item
2022-02-28 11:11:51	ga_s2am_ard_3-2-1_52LEH_2022-02-28_final.stac-item
2022-03-15 12:03:37	ga_s2am_ard_3-2-1_50KNB_2022-03-15_final.stac-item
2022-03-29 11:46:25	ga_s2am_ard_3-2-1_50JNL_2022-03-29_final.stac-item
2022-04-13 10:54:50	ga_s2am_ard_3-2-1_52JFR_2022-04-13_final.stac-item
2022-07-01 11:23:29	ga_s2am_ard_3-2-1_52KCB_2022-07-01_final.stac-item
2022-07-18 11:14:50	ga_s2am_ard_3-2-1_51JZM_2022-07-18_final.stac-item
2022-08-21 10:56:09	ga_s2am_ard_3-2-1_52JGL_2022-08-21_final.stac-item
2022-09-02 11:34:12	ga_s2am_ard_3-2-1_51KVQ_2022-09-02_final.stac-item
2022-09-02 11:37:04	ga_s2am_ard_3-2-1_50HPJ_2022-09-02_final.stac-item
2022-09-06 11:14:32	ga_s2am_ard_3-2-1_52JCT_2022-09-06_final.stac-item
2022-09-15 11:46:29	ga_s2am_ard_3-2-1_50JPL_2022-09-15_final.stac-item
2022-11-14 11:42:48	ga_s2am_ard_3-2-1_51KUV_2022-11-14_final.stac-item
2022-12-04 11:43:15	ga_s2am_ard_3-2-1_51KUT_2022-12-04_final.stac-item
2023-02-09 11:36:42	ga_s2am_ard_3-2-1_51HUD_2023-02-09_final.stac-item
2023-02-12 11:46:06	ga_s2am_ard_3-2-1_50JNM_2023-02-12_nrt.stac-item
2023-02-16 11:26:55	ga_s2am_ard_3-2-1_51HVC_2023-02-16_nrt.stac-item
2023-03-28 11:23:48	ga_s2am_ard_3-2-1_51KZQ_2023-03-28_final
2023-04-27 11:26:58	ga_s2am_ard_3-2-1_51HVC_2023-04-27_final
2023-05-10 11:32:58	ga_s2am_ard_3-2-1_51KWU_2023-05-10_final
2023-05-21 11:04:21	ga_s2am_ard_3-2-1_52JET_2023-05-21_final
2023-06-03 11:14:09	ga_s2am_ard_3-2-1_52KCU_2023-06-03_final
2023-08-28 11:34:08	ga_s2am_ard_3-2-1_51KUQ_2023-08-28_final
2023-09-13 11:53:15	ga_s2am_ard_3-2-1_50KRC_2023-09-13_final
2023-09-13 11:53:26	ga_s2am_ard_3-2-1_50KPC_2023-09-13_final
2023-10-03 11:53:12	ga_s2am_ard_3-2-1_50KRC_2023-10-03_final
2023-11-05 12:04:38	ga_s2am_ard_3-2-1_50JLT_2023-11-05_final
2023-11-23 11:26:32	ga_s2am_ard_3-2-1_51HXD_2023-11-23_final
2024-01-15 11:33:16	ga_s2am_ard_3-2-1_51KXS_2024-01-15_final
2024-02-11 11:21:42	ga_s2am_ard_3-2-1_52LCH_2024-02-11_final
2024-02-11 11:24:37	ga_s2am_ard_3-2-1_51JXM_2024-02-11_final
2024-02-27 11:42:59	ga_s2am_ard_3-2-1_51KUU_2024-02-27_final
2024-03-07 12:15:00	ga_s2am_ard_3-2-1_49JFM_2024-03-07_final
2024-03-08 11:43:22	ga_s2am_ard_3-2-1_50KQC_2024-03-08_final
2024-03-08 11:46:30	ga_s2am_ard_3-2-1_50HQK_2024-03-08_final
2024-03-29 11:12:35	ga_s2am_ard_3-2-1_52KDE_2024-03-29_final
2024-04-21 11:23:39	ga_s2am_ard_3-2-1_51KZR_2024-04-21_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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