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
2015-11-23 10:43:19	ga_s2am_ard_3-2-1_53KQQ_2015-11-23_final.stac-item
2015-11-26 10:52:15	ga_s2am_ard_3-2-1_52KHF_2015-11-26_final.stac-item
2015-12-22 11:14:14	ga_s2am_ard_3-2-1_52JET_2015-12-22_final.stac-item
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_51KXR_2016-03-07_final.stac-item
2016-04-15 10:22:04	ga_s2am_ard_3-2-1_54KYD_2016-04-15_final.stac-item
2016-04-21 10:42:05	ga_s2am_ard_3-2-1_53KQU_2016-04-21_final.stac-item
2016-05-10 11:10:18	ga_s2am_ard_3-2-1_52KEB_2016-05-10_final.stac-item
2016-07-21 10:15:58	ga_s2am_ard_3-2-1_54HUF_2016-07-21_final.stac-item
2016-11-26 11:10:57	ga_s2am_ard_3-2-1_51KZP_2016-11-26_final.stac-item
2016-12-12 09:55:50	ga_s2am_ard_3-2-1_54HWC_2016-12-12_final.stac-item
2017-01-02 10:57:17	ga_s2am_ard_3-2-1_52LHK_2017-01-02_final.stac-item
2017-01-17 10:08:19	ga_s2am_ard_3-2-1_54KZC_2017-01-17_final.stac-item
2017-02-01 10:57:59	ga_s2am_ard_3-2-1_52LGK_2017-02-01_final.stac-item
2017-02-16 10:07:16	ga_s2am_ard_3-2-1_54KZF_2017-02-16_final.stac-item
2017-03-14 12:13:13	ga_s2am_ard_3-2-1_50KKA_2017-03-14_final.stac-item
2017-04-09 10:47:23	ga_s2am_ard_3-2-1_53KKU_2017-04-09_final.stac-item
2017-04-16 10:37:27	ga_s2am_ard_3-2-1_54KTG_2017-04-16_final.stac-item
2017-05-03 10:32:13	ga_s2am_ard_3-2-1_53HME_2017-05-03_final.stac-item
2017-05-04 11:38:37	ga_s2am_ard_3-2-1_51KUS_2017-05-04_final.stac-item
2017-08-25 10:15:54	ga_s2am_ard_3-2-1_53HQB_2017-08-25_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51KVU_2017-11-07_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_51KXU_2017-11-27_final.stac-item
2018-05-03 09:41:11	ga_s2am_ard_3-2-1_54HYB_2018-05-03_final.stac-item
2018-06-29 11:07:13	ga_s2am_ard_3-2-1_52KBV_2018-06-29_final.stac-item
2018-08-11 11:19:45	ga_s2am_ard_3-2-1_51KZR_2018-08-11_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_51LUF_2018-10-26_final.stac-item
2019-01-11 11:32:32	ga_s2am_ard_3-2-1_51KYV_2019-01-11_final.stac-item
2019-02-04 11:11:31	ga_s2am_ard_3-2-1_52LEJ_2019-02-04_final.stac-item
2019-02-20 11:33:49	ga_s2am_ard_3-2-1_51KXQ_2019-02-20_final.stac-item
2019-04-24 11:43:00	ga_s2am_ard_3-2-1_51KVU_2019-04-24_final.stac-item
2019-05-11 11:33:06	ga_s2am_ard_3-2-1_51KXU_2019-05-11_final.stac-item
2019-05-24 11:43:32	ga_s2am_ard_3-2-1_51KUS_2019-05-24_final.stac-item
2019-05-31 11:33:37	ga_s2am_ard_3-2-1_51KUS_2019-05-31_final.stac-item
2019-07-27 11:27:12	ga_s2am_ard_3-2-1_51HTC_2019-07-27_final.stac-item
2019-09-19 11:03:19	ga_s2am_ard_3-2-1_52KEB_2019-09-19_final.stac-item
2019-09-21 11:42:21	ga_s2am_ard_3-2-1_51KWA_2019-09-21_final.stac-item
2019-09-29 11:03:18	ga_s2am_ard_3-2-1_52KFB_2019-09-29_final.stac-item
2019-12-22 10:40:34	ga_s2am_ard_3-2-1_53LPG_2019-12-22_final.stac-item
2019-12-24 11:23:19	ga_s2am_ard_3-2-1_51KYS_2019-12-24_final.stac-item
2020-01-16 11:34:05	ga_s2am_ard_3-2-1_51KWP_2020-01-16_final.stac-item
2020-02-24 10:22:37	ga_s2am_ard_3-2-1_54KWC_2020-02-24_final.stac-item
2020-05-02 11:23:38	ga_s2am_ard_3-2-1_52KBA_2020-05-02_final.stac-item
2020-06-02 10:55:48	ga_s2am_ard_3-2-1_52JGM_2020-06-02_final.stac-item
2020-07-08 11:13:18	ga_s2am_ard_3-2-1_52KBC_2020-07-08_final.stac-item
2020-07-17 11:43:20	ga_s2am_ard_3-2-1_51KUT_2020-07-17_final.stac-item
2020-08-17 11:13:13	ga_s2am_ard_3-2-1_52KCC_2020-08-17_final.stac-item
2020-12-01 11:33:23	ga_s2am_ard_3-2-1_51KXS_2020-12-01_final.stac-item
2020-12-13 10:31:57	ga_s2am_ard_3-2-1_54KUF_2020-12-13_final.stac-item
2020-12-15 11:13:11	ga_s2am_ard_3-2-1_52KBC_2020-12-15_final.stac-item
2021-04-10 11:33:48	ga_s2am_ard_3-2-1_51KXQ_2021-04-10_final.stac-item
2021-04-13 11:44:25	ga_s2am_ard_3-2-1_51JTN_2021-04-13_final.stac-item
2021-06-03 11:16:38	ga_s2am_ard_3-2-1_51HYD_2021-06-03_final.stac-item
2021-07-08 10:26:53	ga_s2am_ard_3-2-1_53HPB_2021-07-08_final.stac-item
2021-07-18 12:05:18	ga_s2am_ard_3-2-1_49JGL_2021-07-18_final.stac-item
2021-09-01 11:13:15	ga_s2am_ard_3-2-1_52KBC_2021-09-01_final.stac-item
2021-10-07 11:32:05	ga_s2am_ard_3-2-1_51LWC_2021-10-07_final.stac-item
2021-10-24 11:23:48	ga_s2am_ard_3-2-1_51KXR_2021-10-24_final.stac-item
2021-11-07 11:00:32	ga_s2am_ard_3-2-1_53LKH_2021-11-07_final.stac-item
2021-11-13 11:23:41	ga_s2am_ard_3-2-1_51KYR_2021-11-13_final.stac-item
2021-11-30 11:11:04	ga_s2am_ard_3-2-1_52LEL_2021-11-30_final
2022-01-10 10:45:45	ga_s2am_ard_3-2-1_53JKG_2022-01-10_final.stac-item
2022-01-22 11:24:04	ga_s2am_ard_3-2-1_52KBU_2022-01-22_final.stac-item
2022-02-06 10:34:07	ga_s2am_ard_3-2-1_53JPN_2022-02-06_final.stac-item
2022-02-08 11:12:37	ga_s2am_ard_3-2-1_52KCE_2022-02-08_final.stac-item
2022-02-10 11:52:33	ga_s2am_ard_3-2-1_50KQF_2022-02-10_final
2022-02-14 11:33:23	ga_s2am_ard_3-2-1_51KXS_2022-02-14_final.stac-item
2022-03-13 11:22:56	ga_s2am_ard_3-2-1_52KBD_2022-03-13_final.stac-item
2022-03-13 11:25:14	ga_s2am_ard_3-2-1_51JXK_2022-03-13_final.stac-item
2022-04-30 10:46:11	ga_s2am_ard_3-2-1_53HME_2022-04-30_final.stac-item
2022-05-13 10:56:00	ga_s2am_ard_3-2-1_52JGL_2022-05-13_final.stac-item
2022-05-15 11:32:24	ga_s2am_ard_3-2-1_51KVB_2022-05-15_final.stac-item
2022-05-24 10:26:57	ga_s2am_ard_3-2-1_53HPB_2022-05-24_final.stac-item
2022-05-28 11:43:19	ga_s2am_ard_3-2-1_51KVT_2022-05-28_final.stac-item
2022-05-31 11:56:01	ga_s2am_ard_3-2-1_50JMN_2022-05-31_final.stac-item
2022-07-14 11:33:07	ga_s2am_ard_3-2-1_51KXU_2022-07-14_final.stac-item
2022-07-20 11:52:31	ga_s2am_ard_3-2-1_50KQG_2022-07-20_final
2022-08-03 11:35:29	ga_s2am_ard_3-2-1_51JTK_2022-08-03_final.stac-item
2022-10-26 11:13:17	ga_s2am_ard_3-2-1_52KBC_2022-10-26_final.stac-item
2022-11-11 11:32:54	ga_s2am_ard_3-2-1_51KYU_2022-11-11_final.stac-item
2022-11-29 10:50:34	ga_s2am_ard_3-2-1_53LPG_2022-11-29_final.stac-item
2023-01-16 10:15:57	ga_s2am_ard_3-2-1_54HXJ_2023-01-16_final.stac-item
2023-01-30 09:57:43	ga_s2am_ard_3-2-1_54HWC_2023-01-30_final.stac-item
2023-02-02 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2023-02-02_final
2023-03-01 11:33:54	ga_s2am_ard_3-2-1_51KWQ_2023-03-01_final
2023-04-11 11:06:18	ga_s2am_ard_3-2-1_52HDK_2023-04-11_final
2023-04-24 11:14:07	ga_s2am_ard_3-2-1_52JET_2023-04-24_final
2023-05-20 09:57:39	ga_s2am_ard_3-2-1_54HYC_2023-05-20_final
2023-05-27 11:23:17	ga_s2am_ard_3-2-1_51KXT_2023-05-27_final
2023-05-27 11:23:32	ga_s2am_ard_3-2-1_51KXS_2023-05-27_final
2023-06-16 11:23:47	ga_s2am_ard_3-2-1_51KXR_2023-06-16_final
2023-06-27 10:51:11	ga_s2am_ard_3-2-1_53LNE_2023-06-27_final
2023-07-19 11:37:11	ga_s2am_ard_3-2-1_50HPH_2023-07-19_final
2023-09-04 11:27:07	ga_s2am_ard_3-2-1_51HUC_2023-09-04_final
2023-11-08 10:34:25	ga_s2am_ard_3-2-1_53JNM_2023-11-08_final
2023-11-11 10:42:53	ga_s2am_ard_3-2-1_53KNT_2023-11-11_final
2023-12-29 11:43:21	ga_s2am_ard_3-2-1_51KVS_2023-12-29_final
2024-02-05 11:04:57	ga_s2am_ard_3-2-1_52JEQ_2024-02-05_final
2024-02-11 11:23:18	ga_s2am_ard_3-2-1_51KZS_2024-02-11_final
2024-03-04 10:26:33	ga_s2am_ard_3-2-1_53HQC_2024-03-04_final
2024-03-06 11:01:51	ga_s2am_ard_3-2-1_52LFH_2024-03-06_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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