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
2015-11-14 11:47:22	ga_s2am_ard_3-2-1_50KQC_2015-11-14_final.stac-item
2015-11-25 11:21:29	ga_s2am_ard_3-2-1_51JZM_2015-11-25_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JLL_2016-03-03_final.stac-item
2016-03-06 12:03:43	ga_s2am_ard_3-2-1_49KHR_2016-03-06_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JMM_2016-04-29_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50KMV_2016-07-21_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_51KTT_2016-07-28_final.stac-item
2016-10-03 11:32:06	ga_s2am_ard_3-2-1_50JRT_2016-10-03_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_50HPK_2016-11-05_final.stac-item
2016-12-12 11:29:02	ga_s2am_ard_3-2-1_50JPL_2016-12-12_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51KUR_2016-12-15_final.stac-item
2016-12-26 11:14:08	ga_s2am_ard_3-2-1_51JYN_2016-12-26_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_51KUU_2017-02-13_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_51KVA_2017-11-20_final.stac-item
2018-05-19 11:40:33	ga_s2am_ard_3-2-1_50KQC_2018-05-19_final.stac-item
2018-08-04 11:32:40	ga_s2am_ard_3-2-1_50HPH_2018-08-04_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50JLP_2018-08-30_final.stac-item
2018-10-20 11:23:51	ga_s2am_ard_3-2-1_51HUC_2018-10-20_final.stac-item
2018-11-15 11:42:54	ga_s2am_ard_3-2-1_51KUU_2018-11-15_final.stac-item
2018-11-21 12:05:34	ga_s2am_ard_3-2-1_50JKP_2018-11-21_final.stac-item
2018-11-22 11:35:01	ga_s2am_ard_3-2-1_51JWK_2018-11-22_final.stac-item
2018-11-29 11:24:18	ga_s2am_ard_3-2-1_51JXN_2018-11-29_final.stac-item
2019-01-11 11:36:53	ga_s2am_ard_3-2-1_51HUC_2019-01-11_final.stac-item
2019-01-14 11:43:17	ga_s2am_ard_3-2-1_50KQC_2019-01-14_final.stac-item
2019-01-17 11:53:52	ga_s2am_ard_3-2-1_50KMA_2019-01-17_final.stac-item
2019-01-31 11:36:40	ga_s2am_ard_3-2-1_51HUD_2019-01-31_final.stac-item
2019-02-23 11:47:10	ga_s2am_ard_3-2-1_50HLH_2019-02-23_final.stac-item
2019-04-18 11:27:01	ga_s2am_ard_3-2-1_51HVC_2019-04-18_final.stac-item
2019-06-03 11:42:48	ga_s2am_ard_3-2-1_51KUV_2019-06-03_final.stac-item
2019-06-10 11:37:00	ga_s2am_ard_3-2-1_51HUC_2019-06-10_final.stac-item
2019-07-26 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2019-07-26_final.stac-item
2019-09-18 11:36:37	ga_s2am_ard_3-2-1_50HPK_2019-09-18_final.stac-item
2019-11-17 11:33:24	ga_s2am_ard_3-2-1_51KUT_2019-11-17_final.stac-item
2019-12-04 11:26:16	ga_s2am_ard_3-2-1_51JUF_2019-12-04_final.stac-item
2020-01-02 11:52:14	ga_s2am_ard_3-2-1_50KQG_2020-01-02_final
2020-01-03 11:25:40	ga_s2am_ard_3-2-1_51JVH_2020-01-03_final.stac-item
2020-02-11 11:56:15	ga_s2am_ard_3-2-1_50JML_2020-02-11_final.stac-item
2020-02-15 11:36:56	ga_s2am_ard_3-2-1_50HQH_2020-02-15_final.stac-item
2020-03-19 11:42:13	ga_s2am_ard_3-2-1_51KUB_2020-03-19_final
2020-05-28 11:47:08	ga_s2am_ard_3-2-1_50HPH_2020-05-28_final.stac-item
2020-05-31 11:52:26	ga_s2am_ard_3-2-1_50KQG_2020-05-31_final
2020-06-03 12:03:50	ga_s2am_ard_3-2-1_50KKB_2020-06-03_final.stac-item
2020-07-14 11:36:53	ga_s2am_ard_3-2-1_50HQJ_2020-07-14_final.stac-item
2020-08-30 11:25:33	ga_s2am_ard_3-2-1_51JWJ_2020-08-30_final.stac-item
2020-09-05 11:43:22	ga_s2am_ard_3-2-1_51KTT_2020-09-05_final.stac-item
2020-10-08 11:52:25	ga_s2am_ard_3-2-1_50KQG_2020-10-08_final
2020-10-09 11:26:53	ga_s2am_ard_3-2-1_51HUD_2020-10-09_final.stac-item
2020-10-22 11:36:43	ga_s2am_ard_3-2-1_50HPK_2020-10-22_final.stac-item
2020-11-20 12:04:34	ga_s2am_ard_3-2-1_49KGP_2020-11-20_final.stac-item
2020-11-24 11:43:02	ga_s2am_ard_3-2-1_51KUU_2020-11-24_final.stac-item
2021-01-20 11:33:49	ga_s2am_ard_3-2-1_51KUR_2021-01-20_final.stac-item
2021-02-05 11:54:57	ga_s2am_ard_3-2-1_50JLS_2021-02-05_final.stac-item
2021-02-21 12:14:26	ga_s2am_ard_3-2-1_49KGP_2021-02-21_final.stac-item
2021-03-01 11:34:29	ga_s2am_ard_3-2-1_51JVN_2021-03-01_final.stac-item
2021-03-21 11:32:31	ga_s2am_ard_3-2-1_51KVA_2021-03-21_final.stac-item
2021-03-24 11:42:34	ga_s2am_ard_3-2-1_51KVA_2021-03-24_final.stac-item
2021-03-24 11:45:42	ga_s2am_ard_3-2-1_51JTH_2021-03-24_final.stac-item
2021-03-30 12:03:57	ga_s2am_ard_3-2-1_49KHR_2021-03-30_final.stac-item
2021-04-10 11:34:59	ga_s2am_ard_3-2-1_51JTL_2021-04-10_final.stac-item
2021-04-23 11:43:39	ga_s2am_ard_3-2-1_51KUR_2021-04-23_final.stac-item
2021-06-09 11:35:48	ga_s2am_ard_3-2-1_51JTH_2021-06-09_final.stac-item
2021-06-16 11:27:02	ga_s2am_ard_3-2-1_51HUC_2021-06-16_final.stac-item
2021-06-23 11:16:13	ga_s2am_ard_3-2-1_51JXF_2021-06-23_final.stac-item
2021-08-11 11:42:48	ga_s2am_ard_3-2-1_51KUV_2021-08-11_final.stac-item
2021-10-26 12:03:28	ga_s2am_ard_3-2-1_50KMC_2021-10-26_final.stac-item
2021-10-26 12:05:06	ga_s2am_ard_3-2-1_49JGM_2021-10-26_final.stac-item
2022-01-07 12:14:57	ga_s2am_ard_3-2-1_49JGM_2022-01-07_final.stac-item
2022-01-15 11:33:23	ga_s2am_ard_3-2-1_51KUT_2022-01-15_final.stac-item
2022-01-28 11:43:15	ga_s2am_ard_3-2-1_51KUT_2022-01-28_final.stac-item
2022-01-28 11:43:29	ga_s2am_ard_3-2-1_51KUS_2022-01-28_final.stac-item
2022-01-29 11:14:41	ga_s2am_ard_3-2-1_51JYM_2022-01-29_final.stac-item
2022-02-08 11:14:23	ga_s2am_ard_3-2-1_51JZN_2022-02-08_final.stac-item
2022-02-10 11:53:16	ga_s2am_ard_3-2-1_50KQC_2022-02-10_final.stac-item
2022-04-14 12:03:47	ga_s2am_ard_3-2-1_50KKB_2022-04-14_final.stac-item
2022-04-15 11:36:41	ga_s2am_ard_3-2-1_50HPK_2022-04-15_final.stac-item
2022-05-18 11:43:09	ga_s2am_ard_3-2-1_51KTU_2022-05-18_final.stac-item
2022-06-14 11:36:01	ga_s2am_ard_3-2-1_50JQN_2022-06-14_final.stac-item
2022-07-07 11:47:01	ga_s2am_ard_3-2-1_50HPJ_2022-07-07_final.stac-item
2022-07-14 11:35:43	ga_s2am_ard_3-2-1_51JUJ_2022-07-14_final.stac-item
2022-07-14 11:37:19	ga_s2am_ard_3-2-1_50HPH_2022-07-14_final.stac-item
2022-10-22 11:33:36	ga_s2am_ard_3-2-1_51KUS_2022-10-22_final.stac-item
2022-11-14 11:42:30	ga_s2am_ard_3-2-1_51KVA_2022-11-14_final.stac-item
2023-01-13 11:43:01	ga_s2am_ard_3-2-1_50KRD_2023-01-13_final.stac-item
2023-01-20 11:34:12	ga_s2am_ard_3-2-1_51KUP_2023-01-20_final.stac-item
2023-02-02 11:43:13	ga_s2am_ard_3-2-1_51KUT_2023-02-02_final
2023-03-27 11:52:18	ga_s2am_ard_3-2-1_50KQG_2023-03-27_final
2023-04-03 11:43:28	ga_s2am_ard_3-2-1_51KUS_2023-04-03_final
2023-04-04 11:16:58	ga_s2am_ard_3-2-1_51HWC_2023-04-04_final
2023-04-10 11:36:47	ga_s2am_ard_3-2-1_51HTD_2023-04-10_final
2023-06-12 11:44:02	ga_s2am_ard_3-2-1_51KUQ_2023-06-12_final
2023-08-21 11:47:08	ga_s2am_ard_3-2-1_50HPH_2023-08-21_final
2023-09-16 12:03:23	ga_s2am_ard_3-2-1_50KNC_2023-09-16_final
2023-11-09 11:42:45	ga_s2am_ard_3-2-1_51KUV_2023-11-09_final
2023-11-29 11:42:55	ga_s2am_ard_3-2-1_51KTU_2023-11-29_final
2023-12-10 11:16:07	ga_s2am_ard_3-2-1_51JXF_2023-12-10_final
2023-12-19 11:42:42	ga_s2am_ard_3-2-1_51KUV_2023-12-19_final
2024-01-25 11:34:43	ga_s2am_ard_3-2-1_51JTM_2024-01-25_final
2024-02-17 11:47:22	ga_s2am_ard_3-2-1_50HMG_2024-02-17_final
2024-03-25 11:34:04	ga_s2am_ard_3-2-1_51KUQ_2024-03-25_final
2024-04-17 11:43:21	ga_s2am_ard_3-2-1_51KTT_2024-04-17_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

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