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
2016-03-28 11:01:10	ga_s2am_ard_3-2-1_52JDR_2016-03-28_final.stac-item
2016-06-04 12:02:54	ga_s2am_ard_3-2-1_50JLR_2016-06-04_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_50JQP_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KXU_2016-12-22_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51LYD_2016-12-22_final.stac-item
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_50JLP_2017-02-09_final.stac-item
2017-05-18 11:21:00	ga_s2am_ard_3-2-1_51KYT_2017-05-18_final.stac-item
2017-06-28 10:53:13	ga_s2am_ard_3-2-1_52JGR_2017-06-28_final.stac-item
2017-07-22 12:14:43	ga_s2am_ard_3-2-1_49JGL_2017-07-22_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49KHQ_2017-09-07_final.stac-item
2017-09-08 11:29:54	ga_s2am_ard_3-2-1_51HUE_2017-09-08_final.stac-item
2017-09-15 11:22:06	ga_s2am_ard_3-2-1_51KYS_2017-09-15_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51JWN_2017-11-07_final.stac-item
2017-11-27 11:31:32	ga_s2am_ard_3-2-1_51KVU_2017-11-27_final.stac-item
2018-02-19 11:07:09	ga_s2am_ard_3-2-1_51KZR_2018-02-19_final.stac-item
2018-05-16 11:33:00	ga_s2am_ard_3-2-1_51KWT_2018-05-16_final.stac-item
2018-06-01 11:52:21	ga_s2am_ard_3-2-1_50KNV_2018-06-01_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_51KWS_2018-06-15_final.stac-item
2018-06-28 11:40:06	ga_s2am_ard_3-2-1_51KUT_2018-06-28_final.stac-item
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52JER_2018-08-05_final.stac-item
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_51KUT_2018-08-07_final.stac-item
2018-08-14 11:33:08	ga_s2am_ard_3-2-1_51KVT_2018-08-14_final.stac-item
2018-09-30 11:16:55	ga_s2am_ard_3-2-1_51KXQ_2018-09-30_final.stac-item
2018-09-30 11:24:01	ga_s2am_ard_3-2-1_51JVH_2018-09-30_final.stac-item
2018-10-01 10:47:21	ga_s2am_ard_3-2-1_52JFQ_2018-10-01_final.stac-item
2019-01-15 11:15:20	ga_s2am_ard_3-2-1_51JYJ_2019-01-15_final.stac-item
2019-04-01 11:33:56	ga_s2am_ard_3-2-1_51KWQ_2019-04-01_final.stac-item
2019-04-10 12:03:43	ga_s2am_ard_3-2-1_50KLB_2019-04-10_final.stac-item
2019-05-27 11:55:16	ga_s2am_ard_3-2-1_50JLR_2019-05-27_final.stac-item
2019-06-24 11:14:45	ga_s2am_ard_3-2-1_51JYM_2019-06-24_final.stac-item
2019-06-26 11:57:10	ga_s2am_ard_3-2-1_50HMH_2019-06-26_final.stac-item
2019-07-24 11:13:59	ga_s2am_ard_3-2-1_51KZQ_2019-07-24_final.stac-item
2019-08-23 11:16:43	ga_s2am_ard_3-2-1_51HXD_2019-08-23_final.stac-item
2019-08-29 11:33:28	ga_s2am_ard_3-2-1_51KWS_2019-08-29_final.stac-item
2019-10-05 11:23:12	ga_s2am_ard_3-2-1_51KYT_2019-10-05_final.stac-item
2020-01-19 11:43:08	ga_s2am_ard_3-2-1_51KUT_2020-01-19_final.stac-item
2020-01-26 11:33:09	ga_s2am_ard_3-2-1_51KVT_2020-01-26_final.stac-item
2020-02-22 11:23:01	ga_s2am_ard_3-2-1_51KZT_2020-02-22_final.stac-item
2020-02-29 11:13:21	ga_s2am_ard_3-2-1_52KBB_2020-02-29_final.stac-item
2020-05-25 11:33:51	ga_s2am_ard_3-2-1_51KVR_2020-05-25_final.stac-item
2020-07-04 11:33:14	ga_s2am_ard_3-2-1_51KXT_2020-07-04_final.stac-item
2020-07-04 11:33:57	ga_s2am_ard_3-2-1_51KXQ_2020-07-04_final.stac-item
2020-08-09 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2020-08-09_final.stac-item
2020-09-22 11:33:57	ga_s2am_ard_3-2-1_51KXQ_2020-09-22_final.stac-item
2020-12-11 11:32:22	ga_s2am_ard_3-2-1_51KXA_2020-12-11_final.stac-item
2021-01-30 11:32:47	ga_s2am_ard_3-2-1_51KVV_2021-01-30_final.stac-item
2021-02-02 11:44:20	ga_s2am_ard_3-2-1_50KQU_2021-02-02_final.stac-item
2021-02-06 11:27:01	ga_s2am_ard_3-2-1_51HUC_2021-02-06_final.stac-item
2021-02-16 11:22:11	ga_s2am_ard_3-2-1_51KYB_2021-02-16_final.stac-item
2021-05-13 11:43:11	ga_s2am_ard_3-2-1_51KVT_2021-05-13_final.stac-item
2021-05-14 11:15:47	ga_s2am_ard_3-2-1_52JCM_2021-05-14_final.stac-item
2021-06-13 11:16:37	ga_s2am_ard_3-2-1_51HYD_2021-06-13_final.stac-item
2021-07-06 11:24:00	ga_s2am_ard_3-2-1_51KXQ_2021-07-06_final.stac-item
2021-07-20 11:05:52	ga_s2am_ard_3-2-1_52JDM_2021-07-20_final.stac-item
2021-09-17 11:33:29	ga_s2am_ard_3-2-1_51KWS_2021-09-17_final.stac-item
2021-11-06 11:34:21	ga_s2am_ard_3-2-1_51KUP_2021-11-06_final.stac-item
2021-11-10 11:15:42	ga_s2am_ard_3-2-1_51JYH_2021-11-10_final.stac-item
2021-11-22 11:55:49	ga_s2am_ard_3-2-1_50JNN_2021-11-22_final.stac-item
2022-05-12 11:25:42	ga_s2am_ard_3-2-1_51JXH_2022-05-12_final.stac-item
2022-05-18 11:44:29	ga_s2am_ard_3-2-1_50KPU_2022-05-18_final.stac-item
2022-05-22 11:24:29	ga_s2am_ard_3-2-1_51JYN_2022-05-22_final.stac-item
2022-05-28 11:45:00	ga_s2am_ard_3-2-1_50JPS_2022-05-28_final.stac-item
2022-06-14 11:33:49	ga_s2am_ard_3-2-1_51KXR_2022-06-14_final.stac-item
2022-07-01 11:23:33	ga_s2am_ard_3-2-1_52KBB_2022-07-01_final.stac-item
2022-07-24 11:33:52	ga_s2am_ard_3-2-1_51KWR_2022-07-24_final.stac-item
2022-07-30 11:54:18	ga_s2am_ard_3-2-1_50KNV_2022-07-30_final.stac-item
2022-08-18 10:46:13	ga_s2am_ard_3-2-1_52JGL_2022-08-18_final.stac-item
2022-08-26 11:43:27	ga_s2am_ard_3-2-1_51KUT_2022-08-26_final
2022-09-05 11:45:48	ga_s2am_ard_3-2-1_50JPP_2022-09-05_final.stac-item
2022-09-06 11:13:37	ga_s2am_ard_3-2-1_52KBB_2022-09-06_final.stac-item
2022-09-29 11:24:04	ga_s2am_ard_3-2-1_51KXQ_2022-09-29_final.stac-item
2022-10-29 11:21:14	ga_s2am_ard_3-2-1_51LZF_2022-10-29_nrt.stac-item
2022-11-11 11:36:46	ga_s2am_ard_3-2-1_51HUD_2022-11-11_final.stac-item
2022-11-25 11:14:16	ga_s2am_ard_3-2-1_52JDT_2022-11-25_final.stac-item
2022-12-21 11:33:00	ga_s2am_ard_3-2-1_51KYT_2022-12-21_final.stac-item
2023-01-04 11:13:53	ga_s2am_ard_3-2-1_51KZQ_2023-01-04_final.stac-item
2023-01-14 11:15:27	ga_s2am_ard_3-2-1_51JXJ_2023-01-14_final.stac-item
2023-01-30 11:33:07	ga_s2am_ard_3-2-1_51KXT_2023-01-30_final.stac-item
2023-02-06 11:26:43	ga_s2am_ard_3-2-1_51HVD_2023-02-06_final
2023-04-03 11:44:57	ga_s2am_ard_3-2-1_50JQR_2023-04-03_final
2023-04-09 12:04:29	ga_s2am_ard_3-2-1_49KGP_2023-04-09_final
2023-06-02 11:43:15	ga_s2am_ard_3-2-1_51KVT_2023-06-02_final
2023-07-09 11:34:01	ga_s2am_ard_3-2-1_51KWQ_2023-07-09_final
2023-08-07 12:05:02	ga_s2am_ard_3-2-1_50JKS_2023-08-07_final
2023-08-08 11:34:54	ga_s2am_ard_3-2-1_50JRS_2023-08-08_final
2023-09-03 11:55:15	ga_s2am_ard_3-2-1_50JMR_2023-09-03_final
2023-09-06 12:05:46	ga_s2am_ard_3-2-1_50JKP_2023-09-06_final
2023-11-19 11:43:22	ga_s2am_ard_3-2-1_51KVS_2023-11-19_final
2023-11-29 11:42:14	ga_s2am_ard_3-2-1_51KWA_2023-11-29_final
2023-11-29 11:42:49	ga_s2am_ard_3-2-1_51KVU_2023-11-29_final
2023-12-02 11:55:38	ga_s2am_ard_3-2-1_50JKP_2023-12-02_final
2024-01-22 11:23:06	ga_s2am_ard_3-2-1_51KXT_2024-01-22_final
2024-01-26 11:06:27	ga_s2am_ard_3-2-1_52HBJ_2024-01-26_final
2024-02-04 11:36:53	ga_s2am_ard_3-2-1_51HUC_2024-02-04_final
2024-02-14 11:33:50	ga_s2am_ard_3-2-1_51KXQ_2024-02-14_final
2024-02-24 11:33:43	ga_s2am_ard_3-2-1_51KVR_2024-02-24_final
2024-02-24 11:35:58	ga_s2am_ard_3-2-1_51JUG_2024-02-24_final
2024-02-26 12:14:13	ga_s2am_ard_3-2-1_49KFQ_2024-02-26_nrt
2024-04-01 11:23:19	ga_s2am_ard_3-2-1_52KBB_2024-04-01_final
2024-04-04 11:34:03	ga_s2am_ard_3-2-1_51KXP_2024-04-04_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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