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
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51HXE_2016-05-03_final.stac-item
2016-05-23 11:22:44	ga_s2am_ard_3-2-1_51KYQ_2016-05-23_final.stac-item
2016-06-18 11:40:15	ga_s2am_ard_3-2-1_51KUU_2016-06-18_final
2016-07-16 10:57:59	ga_s2am_ard_3-2-1_52KFF_2016-07-16_final.stac-item
2016-07-26 11:02:15	ga_s2am_ard_3-2-1_52KGV_2016-07-26_final.stac-item
2016-08-24 11:31:54	ga_s2am_ard_3-2-1_51KWR_2016-08-24_final.stac-item
2016-09-20 11:22:33	ga_s2am_ard_3-2-1_52KBA_2016-09-20_final.stac-item
2016-09-23 11:35:58	ga_s2am_ard_3-2-1_50JQL_2016-09-23_final.stac-item
2016-12-03 11:00:41	ga_s2am_ard_3-2-1_52KHC_2016-12-03_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_51KTS_2017-02-03_final.stac-item
2017-06-01 10:57:18	ga_s2am_ard_3-2-1_52KGE_2017-06-01_final.stac-item
2017-07-02 10:36:07	ga_s2am_ard_3-2-1_53HND_2017-07-02_final.stac-item
2017-07-21 11:02:55	ga_s2am_ard_3-2-1_52KFC_2017-07-21_final.stac-item
2017-08-25 11:51:56	ga_s2am_ard_3-2-1_50JNT_2017-08-25_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50JLM_2017-09-27_final.stac-item
2018-01-26 11:29:50	ga_s2am_ard_3-2-1_51KXT_2018-01-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52LHM_2018-02-26_final.stac-item
2018-05-17 10:57:18	ga_s2am_ard_3-2-1_52KGV_2018-05-17_final.stac-item
2018-05-23 11:17:08	ga_s2am_ard_3-2-1_52KBF_2018-05-23_final.stac-item
2018-05-24 10:47:27	ga_s2am_ard_3-2-1_52JFM_2018-05-24_final.stac-item
2018-08-08 11:13:24	ga_s2am_ard_3-2-1_52KEV_2018-08-08_final.stac-item
2018-11-04 10:27:04	ga_s2am_ard_3-2-1_53HPD_2018-11-04_final.stac-item
2018-12-23 11:00:22	ga_s2am_ard_3-2-1_52LHN_2018-12-23_final.stac-item
2019-02-07 11:23:32	ga_s2am_ard_3-2-1_51KZR_2019-02-07_final.stac-item
2019-03-29 11:22:51	ga_s2am_ard_3-2-1_52KBD_2019-03-29_final.stac-item
2019-03-31 12:05:52	ga_s2am_ard_3-2-1_50JLN_2019-03-31_final.stac-item
2019-04-02 11:02:45	ga_s2am_ard_3-2-1_52KGD_2019-04-02_final.stac-item
2019-04-11 11:33:40	ga_s2am_ard_3-2-1_51KVS_2019-04-11_final.stac-item
2019-04-18 11:23:03	ga_s2am_ard_3-2-1_51KXU_2019-04-18_final.stac-item
2019-05-31 11:31:23	ga_s2am_ard_3-2-1_51LZE_2019-05-31_final.stac-item
2019-06-07 11:25:59	ga_s2am_ard_3-2-1_51JWG_2019-06-07_final.stac-item
2019-09-02 11:13:15	ga_s2am_ard_3-2-1_52KEB_2019-09-02_final.stac-item
2019-09-02 11:14:50	ga_s2am_ard_3-2-1_52JCR_2019-09-02_final.stac-item
2019-12-09 10:34:33	ga_s2am_ard_3-2-1_53JPL_2019-12-09_final.stac-item
2020-01-19 11:42:50	ga_s2am_ard_3-2-1_51KVU_2020-01-19_final.stac-item
2020-02-09 11:14:01	ga_s2am_ard_3-2-1_52KBU_2020-02-09_final.stac-item
2020-02-12 11:24:08	ga_s2am_ard_3-2-1_51KWP_2020-02-12_final.stac-item
2020-02-23 10:54:39	ga_s2am_ard_3-2-1_52JGR_2020-02-23_final.stac-item
2020-04-14 12:05:43	ga_s2am_ard_3-2-1_49JGJ_2020-04-14_final.stac-item
2020-04-19 11:14:24	ga_s2am_ard_3-2-1_51JZN_2020-04-19_final.stac-item
2020-04-27 10:34:38	ga_s2am_ard_3-2-1_53JPL_2020-04-27_final.stac-item
2020-04-29 11:15:14	ga_s2am_ard_3-2-1_52JDP_2020-04-29_final.stac-item
2020-05-06 11:06:41	ga_s2am_ard_3-2-1_51HYD_2020-05-06_final.stac-item
2020-05-19 11:10:30	ga_s2am_ard_3-2-1_52LHN_2020-05-19_final.stac-item
2020-06-19 10:46:06	ga_s2am_ard_3-2-1_52JGL_2020-06-19_final.stac-item
2020-08-10 11:21:38	ga_s2am_ard_3-2-1_52LDJ_2020-08-10_final.stac-item
2020-09-19 11:24:34	ga_s2am_ard_3-2-1_51JWN_2020-09-19_final.stac-item
2020-10-12 11:32:06	ga_s2am_ard_3-2-1_51LWC_2020-10-12_final.stac-item
2020-10-29 11:24:13	ga_s2am_ard_3-2-1_51KYP_2020-10-29_final.stac-item
2020-11-28 11:22:52	ga_s2am_ard_3-2-1_52KBD_2020-11-28_final.stac-item
2020-11-30 12:05:15	ga_s2am_ard_3-2-1_49JGL_2020-11-30_final.stac-item
2020-12-14 11:47:03	ga_s2am_ard_3-2-1_50HNH_2020-12-14_final.stac-item
2020-12-28 11:23:02	ga_s2am_ard_3-2-1_52KCC_2020-12-28_final.stac-item
2021-01-14 11:10:33	ga_s2am_ard_3-2-1_52LFN_2021-01-14_final
2021-01-23 11:42:57	ga_s2am_ard_3-2-1_51KVU_2021-01-23_final.stac-item
2021-02-01 10:36:16	ga_s2am_ard_3-2-1_53HLE_2021-02-01_final.stac-item
2021-02-16 11:21:59	ga_s2am_ard_3-2-1_52KDG_2021-02-16_final.stac-item
2021-02-20 11:03:45	ga_s2am_ard_3-2-1_52KFV_2021-02-20_final.stac-item
2021-04-27 11:23:03	ga_s2am_ard_3-2-1_51KZT_2021-04-27_final.stac-item
2021-07-18 12:04:02	ga_s2am_ard_3-2-1_50KKA_2021-07-18_final.stac-item
2021-08-18 11:35:21	ga_s2am_ard_3-2-1_51JTK_2021-08-18_final.stac-item
2021-08-22 11:15:20	ga_s2am_ard_3-2-1_52JCP_2021-08-22_final.stac-item
2021-08-29 11:04:45	ga_s2am_ard_3-2-1_52JFR_2021-08-29_final.stac-item
2021-08-31 11:42:58	ga_s2am_ard_3-2-1_51KVU_2021-08-31_final.stac-item
2021-09-17 11:33:04	ga_s2am_ard_3-2-1_51KYT_2021-09-17_final.stac-item
2021-11-15 12:04:00	ga_s2am_ard_3-2-1_49KHR_2021-11-15_final.stac-item
2022-02-13 10:26:32	ga_s2am_ard_3-2-1_53HQC_2022-02-13_final.stac-item
2022-02-28 11:13:07	ga_s2am_ard_3-2-1_52KDC_2022-02-28_final.stac-item
2022-05-05 11:33:27	ga_s2am_ard_3-2-1_51KUT_2022-05-05_final.stac-item
2022-08-17 11:15:45	ga_s2am_ard_3-2-1_52JBN_2022-08-17_final.stac-item
2022-08-19 11:56:38	ga_s2am_ard_3-2-1_50JLL_2022-08-19_final.stac-item
2022-09-13 11:03:59	ga_s2am_ard_3-2-1_52KEV_2022-09-13_final.stac-item
2022-09-19 11:23:22	ga_s2am_ard_3-2-1_51KXT_2022-09-19_final.stac-item
2022-10-14 10:34:18	ga_s2am_ard_3-2-1_53JNN_2022-10-14_final.stac-item
2022-10-19 11:23:12	ga_s2am_ard_3-2-1_51KYT_2022-10-19_final.stac-item
2022-11-01 11:32:33	ga_s2am_ard_3-2-1_51KWA_2022-11-01_final.stac-item
2022-11-30 10:26:54	ga_s2am_ard_3-2-1_53HNB_2022-11-30_final.stac-item
2022-12-08 11:23:35	ga_s2am_ard_3-2-1_52KBA_2022-12-08_final.stac-item
2022-12-10 10:25:49	ga_s2am_ard_3-2-1_53JQF_2022-12-10_final.stac-item
2023-01-20 11:32:35	ga_s2am_ard_3-2-1_51KXV_2023-01-20_final.stac-item
2023-02-06 11:23:05	ga_s2am_ard_3-2-1_52KBC_2023-02-06_final
2023-02-12 11:43:09	ga_s2am_ard_3-2-1_51KVT_2023-02-12_final
2023-04-27 11:24:29	ga_s2am_ard_3-2-1_51JWN_2023-04-27_final
2023-07-05 11:56:09	ga_s2am_ard_3-2-1_50JNM_2023-07-05_final
2023-08-08 11:33:52	ga_s2am_ard_3-2-1_51KUR_2023-08-08_final
2023-08-10 10:36:29	ga_s2am_ard_3-2-1_53HMD_2023-08-10_final
2023-08-17 10:26:46	ga_s2am_ard_3-2-1_53HNC_2023-08-17_final
2023-08-20 12:15:25	ga_s2am_ard_3-2-1_49JGK_2023-08-20_final
2023-09-04 11:26:02	ga_s2am_ard_3-2-1_51JWG_2023-09-04_final
2023-09-08 11:04:52	ga_s2am_ard_3-2-1_52JER_2023-09-08_final
2023-09-24 11:26:49	ga_s2am_ard_3-2-1_51HUD_2023-09-24_final
2023-11-17 11:04:59	ga_s2am_ard_3-2-1_52JEQ_2023-11-17_final
2023-11-20 11:13:19	ga_s2am_ard_3-2-1_52KCB_2023-11-20_final
2023-11-30 11:15:13	ga_s2am_ard_3-2-1_52JBP_2023-11-30_final
2023-12-05 10:26:00	ga_s2am_ard_3-2-1_53HPE_2023-12-05_final
2023-12-09 11:43:06	ga_s2am_ard_3-2-1_51KUT_2023-12-09_final
2024-01-02 11:23:59	ga_s2am_ard_3-2-1_51KWQ_2024-01-02_final
2024-01-12 11:22:47	ga_s2am_ard_3-2-1_51KZU_2024-01-12_final
2024-02-07 11:42:56	ga_s2am_ard_3-2-1_51KUU_2024-02-07_final
2024-03-12 11:22:41	ga_s2am_ard_3-2-1_51KYV_2024-03-12_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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