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
2016-01-06 12:05:24	ga_s2am_ard_3-2-1_49JGM_2016-01-06_final.stac-item
2016-04-25 12:05:14	ga_s2am_ard_3-2-1_50JLQ_2016-04-25_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50JPL_2016-04-29_final.stac-item
2016-06-12 11:22:42	ga_s2am_ard_3-2-1_51HUD_2016-06-12_final.stac-item
2016-08-26 12:13:22	ga_s2am_ard_3-2-1_50KKA_2016-08-26_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_51HUE_2016-09-13_final.stac-item
2016-09-22 12:03:42	ga_s2am_ard_3-2-1_50KKA_2016-09-22_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HPH_2016-12-25_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50KKA_2017-01-30_final.stac-item
2017-02-13 11:44:16	ga_s2am_ard_3-2-1_50HNK_2017-02-13_final.stac-item
2017-03-06 11:11:54	ga_s2am_ard_3-2-1_51HYD_2017-03-06_final.stac-item
2017-04-28 11:20:48	ga_s2am_ard_3-2-1_51JUF_2017-04-28_final.stac-item
2017-05-10 12:02:52	ga_s2am_ard_3-2-1_50KNC_2017-05-10_final.stac-item
2017-05-30 12:02:52	ga_s2am_ard_3-2-1_49JGJ_2017-05-30_final.stac-item
2017-06-19 12:02:49	ga_s2am_ard_3-2-1_50KKB_2017-06-19_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50JLN_2017-08-05_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_50JQP_2017-09-28_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51JXN_2017-09-28_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51HUC_2018-04-23_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51JZM_2018-04-23_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50JKS_2018-07-04_final.stac-item
2018-08-20 11:52:33	ga_s2am_ard_3-2-1_50JNN_2018-08-20_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-10-05_final.stac-item
2018-10-06 11:46:03	ga_s2am_ard_3-2-1_50JNM_2018-10-06_final.stac-item
2018-11-05 11:38:57	ga_s2am_ard_3-2-1_51KTU_2018-11-05_final.stac-item
2018-12-11 12:03:51	ga_s2am_ard_3-2-1_49KHR_2018-12-11_final.stac-item
2018-12-15 11:42:55	ga_s2am_ard_3-2-1_51KTU_2018-12-15_final.stac-item
2018-12-25 11:43:10	ga_s2am_ard_3-2-1_51KTT_2018-12-25_final.stac-item
2019-01-04 11:45:12	ga_s2am_ard_3-2-1_50JQQ_2019-01-04_final.stac-item
2019-01-08 11:26:42	ga_s2am_ard_3-2-1_51HUD_2019-01-08_final.stac-item
2019-05-04 11:42:49	ga_s2am_ard_3-2-1_51KUV_2019-05-04_final.stac-item
2019-05-28 11:24:22	ga_s2am_ard_3-2-1_51JZN_2019-05-28_final.stac-item
2019-06-03 11:43:02	ga_s2am_ard_3-2-1_51KUU_2019-06-03_final.stac-item
2019-06-13 11:47:09	ga_s2am_ard_3-2-1_50HNH_2019-06-13_final.stac-item
2019-07-03 11:42:51	ga_s2am_ard_3-2-1_51KUV_2019-07-03_final.stac-item
2019-07-03 11:44:03	ga_s2am_ard_3-2-1_51KUQ_2019-07-03_final.stac-item
2019-08-22 11:42:48	ga_s2am_ard_3-2-1_51KUV_2019-08-22_final.stac-item
2019-10-20 12:14:02	ga_s2am_ard_3-2-1_49KHR_2019-10-20_final.stac-item
2019-12-10 11:43:14	ga_s2am_ard_3-2-1_51KTT_2019-12-10_final.stac-item
2020-01-03 11:26:53	ga_s2am_ard_3-2-1_51HVC_2020-01-03_final.stac-item
2020-01-15 12:03:53	ga_s2am_ard_3-2-1_50KKA_2020-01-15_final.stac-item
2020-04-01 11:52:15	ga_s2am_ard_3-2-1_50KQG_2020-04-01_final
2020-09-02 11:36:33	ga_s2am_ard_3-2-1_51HUE_2020-09-02_final.stac-item
2020-09-11 12:03:48	ga_s2am_ard_3-2-1_50KKB_2020-09-11_final.stac-item
2020-10-05 11:43:09	ga_s2am_ard_3-2-1_51KTU_2020-10-05_final.stac-item
2020-10-08 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-10-08_final.stac-item
2020-10-15 11:43:09	ga_s2am_ard_3-2-1_51KTU_2020-10-15_final.stac-item
2020-12-18 11:24:24	ga_s2am_ard_3-2-1_51JXN_2020-12-18_final.stac-item
2021-01-10 11:33:23	ga_s2am_ard_3-2-1_51KUT_2021-01-10_final.stac-item
2021-01-13 11:43:19	ga_s2am_ard_3-2-1_51KTT_2021-01-13_final.stac-item
2021-01-13 11:43:44	ga_s2am_ard_3-2-1_51KUR_2021-01-13_final.stac-item
2021-02-16 11:24:18	ga_s2am_ard_3-2-1_51JZN_2021-02-16_final.stac-item
2021-02-16 11:24:22	ga_s2am_ard_3-2-1_51JYN_2021-02-16_final.stac-item
2021-04-30 11:36:44	ga_s2am_ard_3-2-1_51HTD_2021-04-30_final.stac-item
2021-05-13 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2021-05-13_final.stac-item
2021-05-19 12:03:44	ga_s2am_ard_3-2-1_50KKB_2021-05-19_final.stac-item
2021-06-01 12:13:40	ga_s2am_ard_3-2-1_50KKB_2021-06-01_final.stac-item
2021-06-09 11:36:32	ga_s2am_ard_3-2-1_51HTE_2021-06-09_final.stac-item
2021-06-19 11:37:21	ga_s2am_ard_3-2-1_50HPG_2021-06-19_final
2021-07-19 11:35:19	ga_s2am_ard_3-2-1_51JUK_2021-07-19_final.stac-item
2021-07-19 11:36:50	ga_s2am_ard_3-2-1_51HTD_2021-07-19_final.stac-item
2021-07-25 11:56:43	ga_s2am_ard_3-2-1_50HLK_2021-07-25_final.stac-item
2021-07-28 12:03:47	ga_s2am_ard_3-2-1_50KKB_2021-07-28_final.stac-item
2021-08-01 11:47:27	ga_s2am_ard_3-2-1_50HMG_2021-08-01_final
2021-08-08 11:35:22	ga_s2am_ard_3-2-1_51JWJ_2021-08-08_final.stac-item
2021-08-18 11:35:39	ga_s2am_ard_3-2-1_50JQP_2021-08-18_final.stac-item
2021-08-31 11:47:18	ga_s2am_ard_3-2-1_50HPG_2021-08-31_final
2021-10-07 11:33:27	ga_s2am_ard_3-2-1_51KUT_2021-10-07_final.stac-item
2021-11-23 11:24:23	ga_s2am_ard_3-2-1_51JYN_2021-11-23_final.stac-item
2021-11-26 11:33:48	ga_s2am_ard_3-2-1_51KUR_2021-11-26_final.stac-item
2021-12-12 11:53:10	ga_s2am_ard_3-2-1_50KRC_2021-12-12_final.stac-item
2021-12-12 11:57:22	ga_s2am_ard_3-2-1_50HLG_2021-12-12_final
2022-02-03 12:03:44	ga_s2am_ard_3-2-1_50KKB_2022-02-03_final.stac-item
2022-03-12 11:52:24	ga_s2am_ard_3-2-1_50KQG_2022-03-12_final
2022-03-29 11:43:06	ga_s2am_ard_3-2-1_51KTU_2022-03-29_final.stac-item
2022-04-21 11:53:29	ga_s2am_ard_3-2-1_50KNC_2022-04-21_final.stac-item
2022-05-24 12:05:48	ga_s2am_ard_3-2-1_50JKP_2022-05-24_final.stac-item
2022-05-28 11:43:26	ga_s2am_ard_3-2-1_50KRC_2022-05-28_final.stac-item
2022-06-27 11:42:29	ga_s2am_ard_3-2-1_51KUB_2022-06-27_final
2022-07-27 11:46:58	ga_s2am_ard_3-2-1_50HPJ_2022-07-27_final.stac-item
2022-08-06 11:46:30	ga_s2am_ard_3-2-1_50JPL_2022-08-06_final.stac-item
2022-08-09 11:56:48	ga_s2am_ard_3-2-1_50HMK_2022-08-09_final.stac-item
2022-09-18 11:56:26	ga_s2am_ard_3-2-1_50JNL_2022-09-18_final.stac-item
2022-10-18 11:53:20	ga_s2am_ard_3-2-1_50KQC_2022-10-18_final.stac-item
2023-02-28 12:03:24	ga_s2am_ard_3-2-1_50KLC_2023-02-28_final
2023-02-28 12:03:42	ga_s2am_ard_3-2-1_50KKB_2023-02-28_final
2023-03-14 11:43:26	ga_s2am_ard_3-2-1_51KUS_2023-03-14_final
2023-05-07 11:25:24	ga_s2am_ard_3-2-1_51JXJ_2023-05-07_final
2023-06-22 11:46:26	ga_s2am_ard_3-2-1_50JNL_2023-06-22_final
2023-06-29 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2023-06-29_final
2023-07-19 11:36:56	ga_s2am_ard_3-2-1_50HPJ_2023-07-19_final
2023-08-01 11:43:23	ga_s2am_ard_3-2-1_51KTT_2023-08-01_final
2023-08-21 11:43:24	ga_s2am_ard_3-2-1_51KTT_2023-08-21_final
2023-09-03 11:57:05	ga_s2am_ard_3-2-1_50HLJ_2023-09-03_final
2023-09-23 11:53:12	ga_s2am_ard_3-2-1_50KRC_2023-09-23_final
2023-10-11 11:16:57	ga_s2am_ard_3-2-1_51HWC_2023-10-11_final
2023-11-16 11:37:05	ga_s2am_ard_3-2-1_50HPH_2023-11-16_final
2024-02-07 11:43:14	ga_s2am_ard_3-2-1_51KTT_2024-02-07_final
2024-02-27 11:43:28	ga_s2am_ard_3-2-1_51KUS_2024-02-27_final
2024-03-01 11:53:10	ga_s2am_ard_3-2-1_50KRC_2024-03-01_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

All years