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
2016-01-11 11:17:17	ga_s2am_ard_3-2-1_51HXD_2016-01-11_final.stac-item
2016-03-20 11:42:13	ga_s2am_ard_3-2-1_51KVU_2016-03-20_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HPH_2016-04-29_final.stac-item
2016-07-14 12:02:53	ga_s2am_ard_3-2-1_49JGM_2016-07-14_final.stac-item
2016-07-28 11:40:17	ga_s2am_ard_3-2-1_50JNL_2016-07-28_final.stac-item
2016-08-23 12:02:51	ga_s2am_ard_3-2-1_50KKU_2016-08-23_final.stac-item
2016-09-26 11:40:08	ga_s2am_ard_3-2-1_51KVU_2016-09-26_final.stac-item
2016-11-01 12:02:47	ga_s2am_ard_3-2-1_49JGL_2016-11-01_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_50JNN_2016-12-15_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_50HQH_2017-01-01_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_51KVT_2017-02-03_final.stac-item
2017-02-09 12:02:43	ga_s2am_ard_3-2-1_50JKR_2017-02-09_final.stac-item
2017-07-30 11:34:57	ga_s2am_ard_3-2-1_50JQM_2017-07-30_final.stac-item
2017-08-05 11:51:57	ga_s2am_ard_3-2-1_50KQC_2017-08-05_final.stac-item
2017-08-15 11:56:09	ga_s2am_ard_3-2-1_50HMJ_2017-08-15_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_50JQM_2018-02-08_final.stac-item
2018-04-05 12:03:47	ga_s2am_ard_3-2-1_50JKN_2018-04-05_final.stac-item
2018-04-18 12:13:22	ga_s2am_ard_3-2-1_49JGM_2018-04-18_final.stac-item
2018-05-12 11:48:21	ga_s2am_ard_3-2-1_50KNC_2018-05-12_final.stac-item
2018-06-21 11:48:18	ga_s2am_ard_3-2-1_50KRC_2018-06-21_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_51KUU_2018-08-27_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50KQC_2018-09-26_final.stac-item
2018-11-01 12:02:46	ga_s2am_ard_3-2-1_49KGP_2018-11-01_final.stac-item
2018-11-11 12:04:37	ga_s2am_ard_3-2-1_50JKT_2018-11-11_final.stac-item
2018-12-09 11:25:19	ga_s2am_ard_3-2-1_51JWJ_2018-12-09_final.stac-item
2018-12-11 12:05:47	ga_s2am_ard_3-2-1_50JKN_2018-12-11_final.stac-item
2018-12-21 12:04:34	ga_s2am_ard_3-2-1_49JHN_2018-12-21_final.stac-item
2019-01-04 11:43:13	ga_s2am_ard_3-2-1_50KRC_2019-01-04_final.stac-item
2019-01-20 12:04:24	ga_s2am_ard_3-2-1_50KKU_2019-01-20_final.stac-item
2019-02-10 11:33:45	ga_s2am_ard_3-2-1_51KUR_2019-02-10_final.stac-item
2019-02-20 11:36:39	ga_s2am_ard_3-2-1_51HUD_2019-02-20_final.stac-item
2019-03-25 11:45:56	ga_s2am_ard_3-2-1_51JTG_2019-03-25_final.stac-item
2019-04-07 11:53:22	ga_s2am_ard_3-2-1_50KPC_2019-04-07_final.stac-item
2019-07-10 11:37:12	ga_s2am_ard_3-2-1_50HPH_2019-07-10_final.stac-item
2019-07-26 11:56:13	ga_s2am_ard_3-2-1_50JMM_2019-07-26_final.stac-item
2019-08-29 11:34:44	ga_s2am_ard_3-2-1_51JVM_2019-08-29_final.stac-item
2019-10-02 11:14:25	ga_s2am_ard_3-2-1_51JZN_2019-10-02_final.stac-item
2019-11-19 12:14:10	ga_s2am_ard_3-2-1_49KHQ_2019-11-19_final.stac-item
2019-11-20 11:46:35	ga_s2am_ard_3-2-1_50HPK_2019-11-20_final.stac-item
2019-11-26 12:03:44	ga_s2am_ard_3-2-1_50KKB_2019-11-26_final.stac-item
2020-02-11 11:54:40	ga_s2am_ard_3-2-1_50JPS_2020-02-11_final.stac-item
2020-03-29 11:46:39	ga_s2am_ard_3-2-1_50HQJ_2020-03-29_final.stac-item
2020-04-24 12:05:02	ga_s2am_ard_3-2-1_49JGM_2020-04-24_final.stac-item
2020-06-30 11:53:16	ga_s2am_ard_3-2-1_50KRC_2020-06-30_final.stac-item
2020-10-12 11:36:52	ga_s2am_ard_3-2-1_51HTD_2020-10-12_final.stac-item
2020-11-15 11:16:44	ga_s2am_ard_3-2-1_51HXD_2020-11-15_final.stac-item
2020-11-27 11:56:31	ga_s2am_ard_3-2-1_50HNK_2020-11-27_final.stac-item
2020-12-17 11:57:07	ga_s2am_ard_3-2-1_50HLH_2020-12-17_final.stac-item
2020-12-21 11:34:16	ga_s2am_ard_3-2-1_51KUP_2020-12-21_final.stac-item
2021-01-03 11:43:04	ga_s2am_ard_3-2-1_50KRD_2021-01-03_final.stac-item
2021-01-10 11:36:11	ga_s2am_ard_3-2-1_51JVF_2021-01-10_final.stac-item
2021-01-19 12:04:25	ga_s2am_ard_3-2-1_50KLU_2021-01-19_final.stac-item
2021-02-15 11:55:55	ga_s2am_ard_3-2-1_50JLN_2021-02-15_final.stac-item
2021-03-04 11:45:46	ga_s2am_ard_3-2-1_50JQN_2021-03-04_final.stac-item
2021-03-07 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2021-03-07_final.stac-item
2021-03-18 11:25:38	ga_s2am_ard_3-2-1_51JXH_2021-03-18_final.stac-item
2021-03-28 11:25:36	ga_s2am_ard_3-2-1_51JXH_2021-03-28_final.stac-item
2021-04-23 11:47:20	ga_s2am_ard_3-2-1_50HMG_2021-04-23_final
2021-05-13 11:46:00	ga_s2am_ard_3-2-1_50JQM_2021-05-13_final.stac-item
2021-05-22 12:14:42	ga_s2am_ard_3-2-1_49JGN_2021-05-22_final.stac-item
2021-08-10 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-08-10_final.stac-item
2021-08-31 11:43:05	ga_s2am_ard_3-2-1_51KTU_2021-08-31_final.stac-item
2021-10-23 11:56:16	ga_s2am_ard_3-2-1_50JLM_2021-10-23_final.stac-item
2021-12-06 11:37:00	ga_s2am_ard_3-2-1_51HTC_2021-12-06_final.stac-item
2022-01-02 11:25:07	ga_s2am_ard_3-2-1_51JYK_2022-01-02_final.stac-item
2022-01-05 11:36:44	ga_s2am_ard_3-2-1_51HUD_2022-01-05_final.stac-item
2022-02-07 11:46:37	ga_s2am_ard_3-2-1_50HNK_2022-02-07_final.stac-item
2022-02-14 11:37:03	ga_s2am_ard_3-2-1_50HQH_2022-02-14_final.stac-item
2022-05-12 11:24:55	ga_s2am_ard_3-2-1_51JYL_2022-05-12_final.stac-item
2022-08-03 11:35:52	ga_s2am_ard_3-2-1_51JVH_2022-08-03_final.stac-item
2022-08-03 11:36:42	ga_s2am_ard_3-2-1_51HTE_2022-08-03_final.stac-item
2022-08-25 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-08-25_final
2022-09-08 11:53:32	ga_s2am_ard_3-2-1_50KPC_2022-09-08_final.stac-item
2022-09-08 11:56:15	ga_s2am_ard_3-2-1_50JNM_2022-09-08_final.stac-item
2022-09-15 11:46:47	ga_s2am_ard_3-2-1_50HNK_2022-09-15_final.stac-item
2022-09-22 11:35:05	ga_s2am_ard_3-2-1_51JVL_2022-09-22_final.stac-item
2022-09-28 11:56:07	ga_s2am_ard_3-2-1_50JKN_2022-09-28_final.stac-item
2022-10-22 11:32:48	ga_s2am_ard_3-2-1_51KVV_2022-10-22_final.stac-item
2022-11-17 11:55:18	ga_s2am_ard_3-2-1_50JPQ_2022-11-17_final.stac-item
2022-11-21 11:33:48	ga_s2am_ard_3-2-1_51KUR_2022-11-21_final.stac-item
2022-12-30 12:03:58	ga_s2am_ard_3-2-1_50KKA_2022-12-30_final.stac-item
2023-02-09 11:33:58	ga_s2am_ard_3-2-1_51KVQ_2023-02-09_final.stac-item
2023-02-18 12:04:39	ga_s2am_ard_3-2-1_49JHN_2023-02-18_nrt.stac-item
2023-03-28 11:24:53	ga_s2am_ard_3-2-1_51JXL_2023-03-28_final
2023-03-30 12:05:42	ga_s2am_ard_3-2-1_49JGJ_2023-03-30_final
2023-04-27 11:26:47	ga_s2am_ard_3-2-1_51HUD_2023-04-27_final
2023-05-26 11:52:23	ga_s2am_ard_3-2-1_50KQG_2023-05-26_final
2023-06-29 11:37:05	ga_s2am_ard_3-2-1_51HTC_2023-06-29_final
2023-07-19 11:35:31	ga_s2am_ard_3-2-1_51JVJ_2023-07-19_final
2023-08-07 12:04:18	ga_s2am_ard_3-2-1_50KKV_2023-08-07_final
2023-09-23 11:53:19	ga_s2am_ard_3-2-1_50KQC_2023-09-23_final
2023-11-10 11:16:40	ga_s2am_ard_3-2-1_51HXD_2023-11-10_final
2023-11-19 11:46:35	ga_s2am_ard_3-2-1_50HNK_2023-11-19_final
2023-12-12 11:53:16	ga_s2am_ard_3-2-1_50KPC_2023-12-12_final
2023-12-16 11:37:13	ga_s2am_ard_3-2-1_50HQG_2023-12-16_final
2023-12-25 12:05:34	ga_s2am_ard_3-2-1_50JLP_2023-12-25_final
2024-01-31 11:53:13	ga_s2am_ard_3-2-1_50KQC_2024-01-31_final
2024-03-11 11:55:21	ga_s2am_ard_3-2-1_50JNQ_2024-03-11_final
2024-04-27 11:43:46	ga_s2am_ard_3-2-1_51KUR_2024-04-27_final
2024-05-01 11:24:58	ga_s2am_ard_3-2-1_51JXL_2024-05-01_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

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