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
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50JLN_2016-05-15_final.stac-item
2016-05-18 12:13:27	ga_s2am_ard_3-2-1_49KHS_2016-05-18_final
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JML_2016-05-29_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JNQ_2016-05-29_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_50JMM_2016-09-06_final.stac-item
2016-11-11 12:02:48	ga_s2am_ard_3-2-1_49KGP_2016-11-11_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_50HPG_2016-12-25_final
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_50KRB_2017-02-13_final.stac-item
2017-04-14 11:45:07	ga_s2am_ard_3-2-1_50HPJ_2017-04-14_final.stac-item
2017-09-07 12:02:48	ga_s2am_ard_3-2-1_49JGJ_2017-09-07_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50KRB_2017-12-10_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_50KRC_2017-12-10_final.stac-item
2017-12-13 11:56:02	ga_s2am_ard_3-2-1_50HLK_2017-12-13_final.stac-item
2018-01-26 11:29:50	ga_s2am_ard_3-2-1_50JRT_2018-01-26_final.stac-item
2018-02-17 12:13:18	ga_s2am_ard_3-2-1_49JGL_2018-02-17_final.stac-item
2018-03-16 12:02:45	ga_s2am_ard_3-2-1_50KKB_2018-03-16_final.stac-item
2018-03-23 11:53:37	ga_s2am_ard_3-2-1_50HNK_2018-03-23_final.stac-item
2018-03-29 12:13:20	ga_s2am_ard_3-2-1_49JGM_2018-03-29_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKP_2018-04-05_final.stac-item
2018-04-15 12:02:50	ga_s2am_ard_3-2-1_49JGL_2018-04-15_final.stac-item
2018-04-25 12:02:51	ga_s2am_ard_3-2-1_50JKN_2018-04-25_final.stac-item
2018-05-13 11:26:36	ga_s2am_ard_3-2-1_51HUD_2018-05-13_final.stac-item
2018-06-11 11:48:18	ga_s2am_ard_3-2-1_50KMA_2018-06-11_final.stac-item
2018-06-24 12:03:32	ga_s2am_ard_3-2-1_50KKA_2018-06-24_final.stac-item
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50KRC_2018-07-08_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_50HPH_2018-07-25_final.stac-item
2019-02-13 11:43:15	ga_s2am_ard_3-2-1_50KRC_2019-02-13_final.stac-item
2019-04-17 11:56:57	ga_s2am_ard_3-2-1_50HLJ_2019-04-17_final.stac-item
2019-04-24 11:47:10	ga_s2am_ard_3-2-1_50HNH_2019-04-24_final.stac-item
2019-05-20 12:04:17	ga_s2am_ard_3-2-1_50KKV_2019-05-20_final.stac-item
2019-06-13 11:46:29	ga_s2am_ard_3-2-1_50JML_2019-06-13_final.stac-item
2019-06-22 12:14:31	ga_s2am_ard_3-2-1_49KGP_2019-06-22_final.stac-item
2019-07-06 11:56:41	ga_s2am_ard_3-2-1_50HMK_2019-07-06_final.stac-item
2019-07-12 12:14:00	ga_s2am_ard_3-2-1_49KHR_2019-07-12_final.stac-item
2019-08-18 12:04:42	ga_s2am_ard_3-2-1_50JLT_2019-08-18_final.stac-item
2019-08-31 12:14:42	ga_s2am_ard_3-2-1_49JGN_2019-08-31_final.stac-item
2019-10-14 11:56:39	ga_s2am_ard_3-2-1_50HMK_2019-10-14_final.stac-item
2019-10-27 12:06:07	ga_s2am_ard_3-2-1_50JLM_2019-10-27_final.stac-item
2019-12-03 11:53:16	ga_s2am_ard_3-2-1_50KQC_2019-12-03_final.stac-item
2020-01-02 11:53:12	ga_s2am_ard_3-2-1_50KQC_2020-01-02_final.stac-item
2020-03-18 12:15:16	ga_s2am_ard_3-2-1_49JGK_2020-03-18_final.stac-item
2020-04-21 11:53:25	ga_s2am_ard_3-2-1_50KNC_2020-04-21_final.stac-item
2020-05-04 12:04:31	ga_s2am_ard_3-2-1_50KKU_2020-05-04_final.stac-item
2020-05-11 11:53:26	ga_s2am_ard_3-2-1_50KPC_2020-05-11_final.stac-item
2020-05-21 11:56:05	ga_s2am_ard_3-2-1_50JKN_2020-05-21_final.stac-item
2020-06-04 11:37:04	ga_s2am_ard_3-2-1_51HUC_2020-06-04_final.stac-item
2020-06-13 12:05:03	ga_s2am_ard_3-2-1_50JKS_2020-06-13_final.stac-item
2020-06-14 11:36:26	ga_s2am_ard_3-2-1_50JQL_2020-06-14_final.stac-item
2020-07-13 12:05:45	ga_s2am_ard_3-2-1_50JKP_2020-07-13_final.stac-item
2020-08-02 12:04:48	ga_s2am_ard_3-2-1_50JKT_2020-08-02_final.stac-item
2020-08-09 11:53:37	ga_s2am_ard_3-2-1_50KMC_2020-08-09_final.stac-item
2020-08-22 12:04:04	ga_s2am_ard_3-2-1_50KKA_2020-08-22_final.stac-item
2020-09-05 11:46:31	ga_s2am_ard_3-2-1_50HPK_2020-09-05_final.stac-item
2020-09-11 12:04:22	ga_s2am_ard_3-2-1_49KGQ_2020-09-11_final.stac-item
2020-11-20 12:05:58	ga_s2am_ard_3-2-1_50JKN_2020-11-20_final.stac-item
2020-12-20 12:04:41	ga_s2am_ard_3-2-1_49JHN_2020-12-20_final.stac-item
2021-01-09 12:04:28	ga_s2am_ard_3-2-1_50KKU_2021-01-09_final.stac-item
2021-02-05 11:52:19	ga_s2am_ard_3-2-1_50KQG_2021-02-05_final
2021-03-07 11:53:10	ga_s2am_ard_3-2-1_50KRC_2021-03-07_final.stac-item
2021-04-02 12:13:51	ga_s2am_ard_3-2-1_49KHR_2021-04-02_final.stac-item
2021-04-16 11:52:28	ga_s2am_ard_3-2-1_50KQF_2021-04-16_final
2021-06-02 11:44:03	ga_s2am_ard_3-2-1_50KRV_2021-06-02_final.stac-item
2021-07-02 11:46:36	ga_s2am_ard_3-2-1_50HPK_2021-07-02_final.stac-item
2021-07-28 12:03:23	ga_s2am_ard_3-2-1_50KNC_2021-07-28_final.stac-item
2021-08-21 11:47:19	ga_s2am_ard_3-2-1_50HPG_2021-08-21_final
2021-09-16 12:04:47	ga_s2am_ard_3-2-1_49JGN_2021-09-16_final.stac-item
2021-11-05 12:05:44	ga_s2am_ard_3-2-1_50JKP_2021-11-05_final.stac-item
2022-01-14 12:04:00	ga_s2am_ard_3-2-1_50KKA_2022-01-14_final.stac-item
2022-01-14 12:04:43	ga_s2am_ard_3-2-1_50JKT_2022-01-14_final.stac-item
2022-04-11 11:53:23	ga_s2am_ard_3-2-1_50KPC_2022-04-11_final.stac-item
2022-06-10 11:54:53	ga_s2am_ard_3-2-1_50JLT_2022-06-10_final.stac-item
2022-07-03 12:05:51	ga_s2am_ard_3-2-1_50JLP_2022-07-03_final.stac-item
2022-08-03 11:36:39	ga_s2am_ard_3-2-1_51HUE_2022-08-03_final.stac-item
2022-10-28 11:56:14	ga_s2am_ard_3-2-1_50JLM_2022-10-28_final.stac-item
2022-11-01 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-11-01_final.stac-item
2022-11-18 11:26:49	ga_s2am_ard_3-2-1_51HUD_2022-11-18_final.stac-item
2022-12-13 12:14:56	ga_s2am_ard_3-2-1_49JGM_2022-12-13_final.stac-item
2023-02-05 11:55:51	ga_s2am_ard_3-2-1_50JKN_2023-02-05_final
2023-02-25 11:57:10	ga_s2am_ard_3-2-1_50HKH_2023-02-25_nrt
2023-03-10 12:03:39	ga_s2am_ard_3-2-1_50KKB_2023-03-10_final
2023-04-06 11:52:37	ga_s2am_ard_3-2-1_50KPF_2023-04-06_final
2023-04-19 12:04:45	ga_s2am_ard_3-2-1_49JGN_2023-04-19_final
2023-04-29 12:04:28	ga_s2am_ard_3-2-1_50KKU_2023-04-29_final
2023-06-11 12:13:58	ga_s2am_ard_3-2-1_50KKA_2023-06-11_final
2023-08-11 11:43:23	ga_s2am_ard_3-2-1_50KRC_2023-08-11_final
2023-08-18 11:36:58	ga_s2am_ard_3-2-1_50HPJ_2023-08-18_final
2023-10-19 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2023-10-19_final
2023-10-29 12:13:54	ga_s2am_ard_3-2-1_49KHR_2023-10-29_final
2023-10-29 12:14:56	ga_s2am_ard_3-2-1_49JGM_2023-10-29_final
2023-11-19 11:44:03	ga_s2am_ard_3-2-1_50KQV_2023-11-19_final
2023-11-19 11:46:31	ga_s2am_ard_3-2-1_50HPK_2023-11-19_final
2023-11-22 11:56:14	ga_s2am_ard_3-2-1_50JNL_2023-11-22_final
2023-12-19 11:44:41	ga_s2am_ard_3-2-1_50JRS_2023-12-19_final
2023-12-28 12:14:38	ga_s2am_ard_3-2-1_49JGN_2023-12-28_final
2024-01-07 12:14:23	ga_s2am_ard_3-2-1_49KGP_2024-01-07_final
2024-01-27 12:13:49	ga_s2am_ard_3-2-1_49KHR_2024-01-27_final
2024-01-27 12:14:50	ga_s2am_ard_3-2-1_49JGM_2024-01-27_final
2024-02-13 12:04:10	ga_s2am_ard_3-2-1_50KKV_2024-02-13_final
2024-02-13 12:05:51	ga_s2am_ard_3-2-1_50JLN_2024-02-13_final
2024-03-21 11:53:18	ga_s2am_ard_3-2-1_50KQC_2024-03-21_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