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
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HNH_2016-02-19_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_50KQC_2016-03-20_final.stac-item
2016-04-19 11:37:58	ga_s2am_ard_3-2-1_50HMJ_2016-04-19_final.stac-item
2016-06-04 12:02:54	ga_s2am_ard_3-2-1_50KLU_2016-06-04_final.stac-item
2016-06-19 11:08:59	ga_s2am_ard_3-2-1_51HYD_2016-06-19_final.stac-item
2016-07-01 11:48:31	ga_s2am_ard_3-2-1_50KPB_2016-07-01_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50HMJ_2016-07-28_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_51HUD_2016-09-13_final.stac-item
2016-12-05 11:36:19	ga_s2am_ard_3-2-1_51KUP_2016-12-05_final.stac-item
2016-12-08 11:44:46	ga_s2am_ard_3-2-1_50KQC_2016-12-08_final.stac-item
2017-01-18 11:19:51	ga_s2am_ard_3-2-1_51JUF_2017-01-18_final.stac-item
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_50JKM_2017-02-09_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_51KUV_2017-02-13_final.stac-item
2017-03-19 11:20:49	ga_s2am_ard_3-2-1_51JVH_2017-03-19_final.stac-item
2017-05-24 11:45:07	ga_s2am_ard_3-2-1_50HNH_2017-05-24_final.stac-item
2017-07-30 11:34:57	ga_s2am_ard_3-2-1_51JTH_2017-07-30_final.stac-item
2017-09-27 12:02:46	ga_s2am_ard_3-2-1_50JKM_2017-09-27_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_50KPV_2017-11-20_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JLQ_2017-12-03_final.stac-item
2017-12-24 11:22:03	ga_s2am_ard_3-2-1_51JWJ_2017-12-24_final.stac-item
2018-01-12 11:50:28	ga_s2am_ard_3-2-1_50KQC_2018-01-12_final.stac-item
2018-02-02 11:24:26	ga_s2am_ard_3-2-1_51JWM_2018-02-02_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51JXK_2018-02-22_final.stac-item
2018-04-22 11:53:56	ga_s2am_ard_3-2-1_50HMH_2018-04-22_final.stac-item
2018-04-22 11:53:56	ga_s2am_ard_3-2-1_50JMQ_2018-04-22_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_51HUC_2018-06-15_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50JKM_2018-07-14_final.stac-item
2018-08-30 11:53:49	ga_s2am_ard_3-2-1_50HLH_2018-08-30_final.stac-item
2018-11-06 11:16:04	ga_s2am_ard_3-2-1_51JYF_2018-11-06_final.stac-item
2018-11-11 12:04:26	ga_s2am_ard_3-2-1_49KGP_2018-11-11_final.stac-item
2018-12-12 11:36:38	ga_s2am_ard_3-2-1_51HTD_2018-12-12_final.stac-item
2019-01-14 11:43:14	ga_s2am_ard_3-2-1_50KRC_2019-01-14_final.stac-item
2019-04-10 12:05:39	ga_s2am_ard_3-2-1_50JLP_2019-04-10_final.stac-item
2019-04-11 11:33:00	ga_s2am_ard_3-2-1_51KWU_2019-04-11_final.stac-item
2019-05-04 11:46:16	ga_s2am_ard_3-2-1_50JMM_2019-05-04_final.stac-item
2019-07-13 11:46:06	ga_s2am_ard_3-2-1_50JQM_2019-07-13_final.stac-item
2019-12-17 11:33:39	ga_s2am_ard_3-2-1_51KVR_2019-12-17_final.stac-item
2020-03-13 11:24:11	ga_s2am_ard_3-2-1_51KWP_2020-03-13_final.stac-item
2020-03-19 11:45:14	ga_s2am_ard_3-2-1_50JQQ_2020-03-19_final.stac-item
2020-04-05 11:36:16	ga_s2am_ard_3-2-1_50JQL_2020-04-05_final.stac-item
2020-05-25 11:35:00	ga_s2am_ard_3-2-1_51JWL_2020-05-25_final.stac-item
2020-05-25 11:36:11	ga_s2am_ard_3-2-1_50JQM_2020-05-25_final.stac-item
2020-08-15 12:13:57	ga_s2am_ard_3-2-1_49KGR_2020-08-15_final.stac-item
2020-08-16 11:46:43	ga_s2am_ard_3-2-1_50HNK_2020-08-16_final.stac-item
2021-01-16 11:53:47	ga_s2am_ard_3-2-1_50KQA_2021-01-16_final.stac-item
2021-05-04 11:16:29	ga_s2am_ard_3-2-1_51HWE_2021-05-04_final.stac-item
2021-05-30 11:33:28	ga_s2am_ard_3-2-1_51KWS_2021-05-30_final.stac-item
2021-05-30 11:35:13	ga_s2am_ard_3-2-1_51JVK_2021-05-30_final.stac-item
2021-06-13 11:16:37	ga_s2am_ard_3-2-1_51HYD_2021-06-13_final.stac-item
2021-06-18 12:06:10	ga_s2am_ard_3-2-1_50JKM_2021-06-18_final.stac-item
2021-06-28 12:04:33	ga_s2am_ard_3-2-1_49KGP_2021-06-28_final.stac-item
2021-06-28 12:05:31	ga_s2am_ard_3-2-1_49JGK_2021-06-28_final.stac-item
2021-07-03 11:16:39	ga_s2am_ard_3-2-1_51HYD_2021-07-03_final.stac-item
2021-07-19 11:34:50	ga_s2am_ard_3-2-1_51JUM_2021-07-19_final.stac-item
2021-08-07 12:04:02	ga_s2am_ard_3-2-1_50KKA_2021-08-07_final.stac-item
2021-08-22 11:16:39	ga_s2am_ard_3-2-1_51HYD_2021-08-22_final.stac-item
2021-08-27 12:05:57	ga_s2am_ard_3-2-1_50JKN_2021-08-27_final.stac-item
2021-10-06 12:06:15	ga_s2am_ard_3-2-1_50JKM_2021-10-06_final.stac-item
2021-11-02 11:56:00	ga_s2am_ard_3-2-1_50JLN_2021-11-02_final.stac-item
2021-12-03 11:27:01	ga_s2am_ard_3-2-1_51HUC_2021-12-03_final.stac-item
2022-02-14 11:35:01	ga_s2am_ard_3-2-1_51JUL_2022-02-14_final.stac-item
2022-04-05 11:34:15	ga_s2am_ard_3-2-1_51KVP_2022-04-05_final.stac-item
2022-04-05 11:36:40	ga_s2am_ard_3-2-1_50HPK_2022-04-05_final.stac-item
2022-04-12 11:26:28	ga_s2am_ard_3-2-1_51HWE_2022-04-12_final.stac-item
2022-05-11 11:55:13	ga_s2am_ard_3-2-1_50JMR_2022-05-11_final.stac-item
2022-05-11 11:56:00	ga_s2am_ard_3-2-1_50JLN_2022-05-11_final.stac-item
2022-05-29 11:14:45	ga_s2am_ard_3-2-1_51JZM_2022-05-29_final.stac-item
2022-05-31 11:54:34	ga_s2am_ard_3-2-1_50KMU_2022-05-31_final.stac-item
2022-08-23 11:37:13	ga_s2am_ard_3-2-1_51HTC_2022-08-23_final.stac-item
2022-09-04 12:14:19	ga_s2am_ard_3-2-1_50KKV_2022-09-04_final.stac-item
2022-09-05 11:45:58	ga_s2am_ard_3-2-1_50JQN_2022-09-05_final.stac-item
2022-09-05 11:46:27	ga_s2am_ard_3-2-1_50JQL_2022-09-05_final.stac-item
2022-10-12 11:34:30	ga_s2am_ard_3-2-1_51JWN_2022-10-12_final.stac-item
2022-11-21 11:32:47	ga_s2am_ard_3-2-1_51KVV_2022-11-21_final.stac-item
2022-12-31 11:32:28	ga_s2am_ard_3-2-1_51KWA_2022-12-31_final.stac-item
2023-03-04 11:42:24	ga_s2am_ard_3-2-1_51KVA_2023-03-04_final
2023-04-13 11:44:27	ga_s2am_ard_3-2-1_51JUN_2023-04-13_final
2023-06-09 11:36:41	ga_s2am_ard_3-2-1_50HPK_2023-06-09_final
2023-06-26 11:26:18	ga_s2am_ard_3-2-1_51JVF_2023-06-26_final
2023-07-05 11:56:13	ga_s2am_ard_3-2-1_50JMM_2023-07-05_final
2023-07-16 11:25:48	ga_s2am_ard_3-2-1_51JXH_2023-07-16_final
2023-09-04 11:24:20	ga_s2am_ard_3-2-1_51KWP_2023-09-04_final
2023-09-13 11:57:14	ga_s2am_ard_3-2-1_50HLH_2023-09-13_final
2023-10-03 11:56:13	ga_s2am_ard_3-2-1_50JLM_2023-10-03_final
2023-10-19 12:14:56	ga_s2am_ard_3-2-1_49JGM_2023-10-19_final
2023-10-23 11:56:55	ga_s2am_ard_3-2-1_50HLJ_2023-10-23_final
2023-11-22 11:57:11	ga_s2am_ard_3-2-1_49HGC_2023-11-22_nrt
2023-12-06 11:32:13	ga_s2am_ard_3-2-1_51KVB_2023-12-06_final
2023-12-23 11:25:17	ga_s2am_ard_3-2-1_51JYJ_2023-12-23_final
2023-12-23 11:25:20	ga_s2am_ard_3-2-1_51JXJ_2023-12-23_final
2024-01-11 11:54:46	ga_s2am_ard_3-2-1_50JNS_2024-01-11_final
2024-01-11 11:57:07	ga_s2am_ard_3-2-1_50HKH_2024-01-11_final
2024-01-14 12:06:03	ga_s2am_ard_3-2-1_50JKM_2024-01-14_final
2024-02-17 11:43:23	ga_s2am_ard_3-2-1_51KVS_2024-02-17_final
2024-03-08 11:44:35	ga_s2am_ard_3-2-1_50JQT_2024-03-08_final
2024-03-09 11:15:43	ga_s2am_ard_3-2-1_51JXH_2024-03-09_final
2024-03-18 11:45:25	ga_s2am_ard_3-2-1_50JNQ_2024-03-18_final
2024-03-19 11:16:41	ga_s2am_ard_3-2-1_51HXD_2024-03-19_final
2024-03-24 12:03:45	ga_s2am_ard_3-2-1_50KKB_2024-03-24_final
2024-03-29 11:14:41	ga_s2am_ard_3-2-1_51JYM_2024-03-29_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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