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_51KXS_2016-05-03_final.stac-item
2017-10-31 11:42:00	ga_s2am_ard_3-2-1_51KUV_2017-10-31_final.stac-item
2017-12-04 11:22:04	ga_s2am_ard_3-2-1_51HVD_2017-12-04_final.stac-item
2018-02-12 11:16:56	ga_s2am_ard_3-2-1_51KYS_2018-02-12_final.stac-item
2018-03-10 11:39:48	ga_s2am_ard_3-2-1_51KUT_2018-03-10_final.stac-item
2018-03-27 11:33:07	ga_s2am_ard_3-2-1_51KVT_2018-03-27_final.stac-item
2018-05-03 11:21:11	ga_s2am_ard_3-2-1_52KBC_2018-05-03_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_51KXU_2018-06-15_final.stac-item
2018-06-29 11:07:13	ga_s2am_ard_3-2-1_51KZQ_2018-06-29_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_50JKP_2018-07-24_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51JUK_2018-09-23_final.stac-item
2018-11-06 11:13:50	ga_s2am_ard_3-2-1_51KZQ_2018-11-06_final.stac-item
2018-11-15 11:43:04	ga_s2am_ard_3-2-1_51KVT_2018-11-15_final.stac-item
2018-11-29 11:21:31	ga_s2am_ard_3-2-1_51LZD_2018-11-29_final.stac-item
2018-11-29 11:24:18	ga_s2am_ard_3-2-1_51JXN_2018-11-29_final.stac-item
2018-12-19 11:23:05	ga_s2am_ard_3-2-1_51KXT_2018-12-19_final.stac-item
2018-12-29 11:23:32	ga_s2am_ard_3-2-1_51KYR_2018-12-29_final.stac-item
2019-01-08 11:23:08	ga_s2am_ard_3-2-1_51KXT_2019-01-08_final.stac-item
2019-01-08 11:23:45	ga_s2am_ard_3-2-1_52KBV_2019-01-08_final.stac-item
2019-02-27 11:23:05	ga_s2am_ard_3-2-1_51KYT_2019-02-27_final.stac-item
2019-03-19 11:23:18	ga_s2am_ard_3-2-1_51KZS_2019-03-19_final.stac-item
2019-03-29 11:23:33	ga_s2am_ard_3-2-1_51KYR_2019-03-29_final.stac-item
2019-05-18 11:23:53	ga_s2am_ard_3-2-1_52KBV_2019-05-18_final.stac-item
2019-06-30 11:36:57	ga_s2am_ard_3-2-1_50HPJ_2019-06-30_final.stac-item
2019-07-10 11:33:09	ga_s2am_ard_3-2-1_51KWT_2019-07-10_final.stac-item
2019-07-14 11:13:38	ga_s2am_ard_3-2-1_52KDA_2019-07-14_final.stac-item
2019-07-19 12:03:49	ga_s2am_ard_3-2-1_50KKB_2019-07-19_final.stac-item
2019-07-23 11:42:18	ga_s2am_ard_3-2-1_51KVB_2019-07-23_final.stac-item
2019-08-06 11:23:25	ga_s2am_ard_3-2-1_51KZS_2019-08-06_final.stac-item
2019-10-05 11:23:38	ga_s2am_ard_3-2-1_51KZR_2019-10-05_final.stac-item
2019-11-28 11:04:18	ga_s2am_ard_3-2-1_52JET_2019-11-28_final.stac-item
2019-12-27 11:33:54	ga_s2am_ard_3-2-1_51KVQ_2019-12-27_final.stac-item
2020-01-30 11:14:01	ga_s2am_ard_3-2-1_52KBU_2020-01-30_final.stac-item
2020-02-08 11:40:49	ga_s2am_ard_3-2-1_51LWG_2020-02-08_final
2020-02-22 11:23:19	ga_s2am_ard_3-2-1_51KYS_2020-02-22_final.stac-item
2020-04-04 12:03:55	ga_s2am_ard_3-2-1_49KHR_2020-04-04_final.stac-item
2020-05-24 12:04:01	ga_s2am_ard_3-2-1_50KLA_2020-05-24_final.stac-item
2020-05-28 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-05-28_final.stac-item
2020-06-18 11:13:39	ga_s2am_ard_3-2-1_52KDA_2020-06-18_final.stac-item
2020-08-10 11:23:27	ga_s2am_ard_3-2-1_51KZS_2020-08-10_final.stac-item
2020-08-12 12:05:21	ga_s2am_ard_3-2-1_49JGL_2020-08-12_final.stac-item
2020-08-26 11:41:38	ga_s2am_ard_3-2-1_51LUE_2020-08-26_final.stac-item
2020-09-09 11:23:43	ga_s2am_ard_3-2-1_51KYR_2020-09-09_final.stac-item
2020-09-09 11:23:53	ga_s2am_ard_3-2-1_52KBV_2020-09-09_final.stac-item
2020-09-15 11:42:21	ga_s2am_ard_3-2-1_51KUB_2020-09-15_final
2020-11-18 11:23:57	ga_s2am_ard_3-2-1_51KYQ_2020-11-18_final.stac-item
2020-11-28 11:24:09	ga_s2am_ard_3-2-1_51KYP_2020-11-28_final.stac-item
2020-12-07 11:53:19	ga_s2am_ard_3-2-1_50KPC_2020-12-07_final.stac-item
2020-12-18 11:23:33	ga_s2am_ard_3-2-1_51KZR_2020-12-18_final.stac-item
2020-12-18 11:24:00	ga_s2am_ard_3-2-1_51KWQ_2020-12-18_final.stac-item
2021-01-03 11:43:00	ga_s2am_ard_3-2-1_51KUU_2021-01-03_final.stac-item
2021-02-08 12:05:14	ga_s2am_ard_3-2-1_49JGL_2021-02-08_final.stac-item
2021-02-16 11:23:49	ga_s2am_ard_3-2-1_51KZQ_2021-02-16_final.stac-item
2021-04-09 12:05:51	ga_s2am_ard_3-2-1_50JKN_2021-04-09_final.stac-item
2021-04-13 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2021-04-13_final.stac-item
2021-05-29 12:03:24	ga_s2am_ard_3-2-1_50KMC_2021-05-29_final.stac-item
2021-05-30 11:32:59	ga_s2am_ard_3-2-1_51KWU_2021-05-30_final.stac-item
2021-07-09 11:34:08	ga_s2am_ard_3-2-1_51KXP_2021-07-09_final.stac-item
2021-07-11 12:13:57	ga_s2am_ard_3-2-1_50KKA_2021-07-11_final.stac-item
2021-07-26 11:24:18	ga_s2am_ard_3-2-1_51KWP_2021-07-26_final.stac-item
2021-08-08 11:33:12	ga_s2am_ard_3-2-1_51KXT_2021-08-08_final.stac-item
2021-08-22 11:14:11	ga_s2am_ard_3-2-1_51KZP_2021-08-22_final.stac-item
2021-10-01 11:15:52	ga_s2am_ard_3-2-1_52JCM_2021-10-01_final.stac-item
2021-10-11 11:13:59	ga_s2am_ard_3-2-1_52KBV_2021-10-11_final.stac-item
2021-10-30 11:41:02	ga_s2am_ard_3-2-1_51LWG_2021-10-30_final
2021-12-06 11:33:15	ga_s2am_ard_3-2-1_51KVT_2021-12-06_final.stac-item
2021-12-13 11:23:16	ga_s2am_ard_3-2-1_52KCB_2021-12-13_final.stac-item
2022-02-08 11:14:23	ga_s2am_ard_3-2-1_51JZN_2022-02-08_final.stac-item
2022-03-29 11:42:44	ga_s2am_ard_3-2-1_51KVV_2022-03-29_final.stac-item
2022-04-02 11:23:37	ga_s2am_ard_3-2-1_52KBA_2022-04-02_final.stac-item
2022-06-25 11:03:47	ga_s2am_ard_3-2-1_52KEA_2022-06-25_final.stac-item
2022-06-27 11:41:45	ga_s2am_ard_3-2-1_51LUE_2022-06-27_final.stac-item
2022-07-01 11:23:19	ga_s2am_ard_3-2-1_52KBC_2022-07-01_final.stac-item
2022-07-04 11:34:13	ga_s2am_ard_3-2-1_51KVQ_2022-07-04_final.stac-item
2022-07-21 11:23:51	ga_s2am_ard_3-2-1_51KYR_2022-07-21_final.stac-item
2022-08-20 11:23:34	ga_s2am_ard_3-2-1_51KZS_2022-08-20_final.stac-item
2022-12-18 11:23:20	ga_s2am_ard_3-2-1_51KZS_2022-12-18_final.stac-item
2022-12-21 11:33:32	ga_s2am_ard_3-2-1_51KUS_2022-12-21_final.stac-item
2023-01-03 11:43:21	ga_s2am_ard_3-2-1_50KQC_2023-01-03_final.stac-item
2023-01-30 11:32:38	ga_s2am_ard_3-2-1_51KXV_2023-01-30_final.stac-item
2023-02-12 11:43:27	ga_s2am_ard_3-2-1_51KUS_2023-02-12_final
2023-05-23 11:46:37	ga_s2am_ard_3-2-1_50HPK_2023-05-23_final
2023-05-30 11:34:03	ga_s2am_ard_3-2-1_51KVQ_2023-05-30_final
2023-06-08 12:03:48	ga_s2am_ard_3-2-1_50KKB_2023-06-08_final
2023-06-18 12:05:56	ga_s2am_ard_3-2-1_50JLN_2023-06-18_final
2023-07-16 11:23:40	ga_s2am_ard_3-2-1_51KZR_2023-07-16_final
2023-08-20 12:13:46	ga_s2am_ard_3-2-1_50KKB_2023-08-20_final
2023-08-25 11:23:56	ga_s2am_ard_3-2-1_51KZQ_2023-08-25_final
2023-10-14 11:23:48	ga_s2am_ard_3-2-1_52KBV_2023-10-14_final
2023-10-20 11:43:00	ga_s2am_ard_3-2-1_51KUU_2023-10-20_final
2023-11-06 11:33:56	ga_s2am_ard_3-2-1_51KWQ_2023-11-06_final
2023-11-26 11:33:07	ga_s2am_ard_3-2-1_51KWT_2023-11-26_final
2023-12-03 11:22:58	ga_s2am_ard_3-2-1_52KBC_2023-12-03_final
2023-12-08 12:13:34	ga_s2am_ard_3-2-1_50KKB_2023-12-08_final
2023-12-26 11:34:14	ga_s2am_ard_3-2-1_51KUP_2023-12-26_final
2024-01-08 11:42:52	ga_s2am_ard_3-2-1_51KVU_2024-01-08_final
2024-03-08 11:43:19	ga_s2am_ard_3-2-1_50KRC_2024-03-08_final
2024-03-18 11:41:19	ga_s2am_ard_3-2-1_51LUF_2024-03-18_final
2024-04-17 11:43:32	ga_s2am_ard_3-2-1_51KUS_2024-04-17_final
2024-05-11 11:23:38	ga_s2am_ard_3-2-1_52KBA_2024-05-11_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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