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
2015-12-04 11:50:12	ga_s2am_ard_3-2-1_50JLM_2015-12-04_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_51KUT_2016-05-29_final.stac-item
2016-07-07 12:13:46	ga_s2am_ard_3-2-1_50KKA_2016-07-07_final.stac-item
2016-10-26 11:39:44	ga_s2am_ard_3-2-1_50KPU_2016-10-26_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_50KKB_2016-11-14_final.stac-item
2016-12-24 12:13:15	ga_s2am_ard_3-2-1_49KHR_2016-12-24_final.stac-item
2017-01-24 11:35:42	ga_s2am_ard_3-2-1_51KTS_2017-01-24_final.stac-item
2017-02-03 11:41:40	ga_s2am_ard_3-2-1_50KRC_2017-02-03_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_51KTU_2017-02-13_final.stac-item
2017-06-02 12:13:37	ga_s2am_ard_3-2-1_49JGM_2017-06-02_final.stac-item
2017-07-12 12:13:35	ga_s2am_ard_3-2-1_50KKA_2017-07-12_final.stac-item
2017-08-29 11:36:08	ga_s2am_ard_3-2-1_51HUE_2017-08-29_final.stac-item
2017-12-10 11:42:24	ga_s2am_ard_3-2-1_51JTG_2017-12-10_final.stac-item
2018-05-25 12:03:34	ga_s2am_ard_3-2-1_49KGP_2018-05-25_final.stac-item
2018-06-11 11:53:43	ga_s2am_ard_3-2-1_50JKN_2018-06-11_final.stac-item
2018-11-25 11:43:07	ga_s2am_ard_3-2-1_51KUT_2018-11-25_final.stac-item
2018-12-11 12:05:47	ga_s2am_ard_3-2-1_50JKN_2018-12-11_final.stac-item
2018-12-15 11:42:52	ga_s2am_ard_3-2-1_51KUU_2018-12-15_final.stac-item
2019-01-03 12:14:50	ga_s2am_ard_3-2-1_49JGM_2019-01-03_final.stac-item
2019-01-04 11:42:55	ga_s2am_ard_3-2-1_51KUU_2019-01-04_final.stac-item
2019-01-24 11:43:40	ga_s2am_ard_3-2-1_51KUR_2019-01-24_final.stac-item
2019-02-03 11:42:57	ga_s2am_ard_3-2-1_51KUU_2019-02-03_final.stac-item
2019-03-04 12:13:49	ga_s2am_ard_3-2-1_50KKA_2019-03-04_final.stac-item
2019-03-05 11:46:46	ga_s2am_ard_3-2-1_50HNJ_2019-03-05_final.stac-item
2019-05-31 11:33:37	ga_s2am_ard_3-2-1_51KUS_2019-05-31_final.stac-item
2019-05-31 11:37:00	ga_s2am_ard_3-2-1_51HUC_2019-05-31_final.stac-item
2019-08-05 11:56:30	ga_s2am_ard_3-2-1_50JLL_2019-08-05_final.stac-item
2019-09-01 11:43:18	ga_s2am_ard_3-2-1_51KTT_2019-09-01_final.stac-item
2019-09-11 11:43:01	ga_s2am_ard_3-2-1_51KTU_2019-09-11_final.stac-item
2019-12-11 11:15:50	ga_s2am_ard_3-2-1_51JYG_2019-12-11_final.stac-item
2019-12-20 11:44:25	ga_s2am_ard_3-2-1_50JRT_2019-12-20_final.stac-item
2020-01-12 11:52:28	ga_s2am_ard_3-2-1_50KQF_2020-01-12_final
2020-02-21 11:57:00	ga_s2am_ard_3-2-1_50HMH_2020-02-21_final.stac-item
2020-03-19 11:47:03	ga_s2am_ard_3-2-1_50HNH_2020-03-19_final.stac-item
2020-03-23 11:24:33	ga_s2am_ard_3-2-1_51JYM_2020-03-23_final.stac-item
2020-03-30 11:14:25	ga_s2am_ard_3-2-1_51JYN_2020-03-30_final.stac-item
2020-04-05 11:36:54	ga_s2am_ard_3-2-1_51HUC_2020-04-05_final.stac-item
2020-04-17 12:13:54	ga_s2am_ard_3-2-1_50KKA_2020-04-17_final.stac-item
2020-06-14 11:36:11	ga_s2am_ard_3-2-1_50JQM_2020-06-14_final.stac-item
2020-06-20 11:52:26	ga_s2am_ard_3-2-1_50KQG_2020-06-20_final
2020-08-12 12:05:43	ga_s2am_ard_3-2-1_50JLP_2020-08-12_final.stac-item
2020-08-22 12:04:48	ga_s2am_ard_3-2-1_49JHN_2020-08-22_final.stac-item
2020-09-05 11:42:21	ga_s2am_ard_3-2-1_51KUB_2020-09-05_final
2020-10-05 11:46:49	ga_s2am_ard_3-2-1_50HQJ_2020-10-05_final.stac-item
2020-12-04 11:44:12	ga_s2am_ard_3-2-1_51KUP_2020-12-04_final.stac-item
2020-12-10 12:06:01	ga_s2am_ard_3-2-1_50JLM_2020-12-10_final.stac-item
2021-01-13 11:43:01	ga_s2am_ard_3-2-1_51KUU_2021-01-13_final.stac-item
2021-01-16 11:56:00	ga_s2am_ard_3-2-1_50JKN_2021-01-16_final.stac-item
2021-03-20 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2021-03-20_final.stac-item
2021-04-09 12:03:40	ga_s2am_ard_3-2-1_50KKB_2021-04-09_final.stac-item
2021-05-09 12:03:58	ga_s2am_ard_3-2-1_49KHR_2021-05-09_final.stac-item
2021-05-10 11:37:05	ga_s2am_ard_3-2-1_50HPH_2021-05-10_final.stac-item
2021-06-18 12:05:41	ga_s2am_ard_3-2-1_50JKP_2021-06-18_final.stac-item
2021-07-05 11:55:59	ga_s2am_ard_3-2-1_50JLN_2021-07-05_final.stac-item
2021-07-12 11:42:49	ga_s2am_ard_3-2-1_51KUV_2021-07-12_final.stac-item
2021-08-11 11:43:32	ga_s2am_ard_3-2-1_51KUS_2021-08-11_final.stac-item
2021-08-21 11:43:31	ga_s2am_ard_3-2-1_51KUS_2021-08-21_final.stac-item
2021-09-10 11:43:18	ga_s2am_ard_3-2-1_51KTT_2021-09-10_final.stac-item
2021-10-29 12:13:44	ga_s2am_ard_3-2-1_50KKB_2021-10-29_final.stac-item
2021-11-06 11:36:52	ga_s2am_ard_3-2-1_50HQJ_2021-11-06_final.stac-item
2021-11-16 11:33:35	ga_s2am_ard_3-2-1_51KUS_2021-11-16_final.stac-item
2021-12-12 11:56:54	ga_s2am_ard_3-2-1_50HLJ_2021-12-12_final.stac-item
2022-01-29 11:14:38	ga_s2am_ard_3-2-1_51JZM_2022-01-29_final.stac-item
2022-03-08 12:14:45	ga_s2am_ard_3-2-1_49JGN_2022-03-08_final.stac-item
2022-03-29 11:44:01	ga_s2am_ard_3-2-1_51KUQ_2022-03-29_final.stac-item
2022-04-05 11:34:04	ga_s2am_ard_3-2-1_51KUQ_2022-04-05_final.stac-item
2022-04-05 11:35:09	ga_s2am_ard_3-2-1_51JWK_2022-04-05_final.stac-item
2022-04-22 11:26:40	ga_s2am_ard_3-2-1_51HXD_2022-04-22_final.stac-item
2022-06-03 12:04:50	ga_s2am_ard_3-2-1_49JHN_2022-06-03_final.stac-item
2022-06-23 12:03:56	ga_s2am_ard_3-2-1_50KKB_2022-06-23_final.stac-item
2022-07-23 12:05:37	ga_s2am_ard_3-2-1_50JKQ_2022-07-23_final.stac-item
2022-10-31 12:04:50	ga_s2am_ard_3-2-1_49JGN_2022-10-31_final.stac-item
2022-11-10 12:04:35	ga_s2am_ard_3-2-1_49KGP_2022-11-10_final.stac-item
2022-11-15 11:14:26	ga_s2am_ard_3-2-1_51JZN_2022-11-15_final.stac-item
2023-01-17 11:26:43	ga_s2am_ard_3-2-1_51HUD_2023-01-17_final.stac-item
2023-02-08 12:05:36	ga_s2am_ard_3-2-1_50JLP_2023-02-08_final
2023-02-15 11:53:08	ga_s2am_ard_3-2-1_50KRC_2023-02-15_nrt.stac-item
2023-02-15 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-02-15_nrt.stac-item
2023-02-15 11:55:56	ga_s2am_ard_3-2-1_50JKN_2023-02-15_final
2023-02-19 11:34:12	ga_s2am_ard_3-2-1_51JXN_2023-02-19_nrt.stac-item
2023-02-19 11:34:12	ga_s2am_ard_3-2-1_51JXN_2023-02-19_final
2023-04-06 11:53:24	ga_s2am_ard_3-2-1_50KNC_2023-04-06_final
2023-04-26 11:52:19	ga_s2am_ard_3-2-1_50KQG_2023-04-26_final
2023-05-29 12:05:44	ga_s2am_ard_3-2-1_50JKP_2023-05-29_final
2023-06-02 11:46:12	ga_s2am_ard_3-2-1_50JNM_2023-06-02_final
2023-07-05 11:55:54	ga_s2am_ard_3-2-1_50JNN_2023-07-05_final
2023-09-19 12:13:57	ga_s2am_ard_3-2-1_50KKA_2023-09-19_final
2023-10-07 11:36:58	ga_s2am_ard_3-2-1_51HUC_2023-10-07_final
2023-10-16 12:03:58	ga_s2am_ard_3-2-1_50KKA_2023-10-16_final
2023-10-24 11:27:02	ga_s2am_ard_3-2-1_51HUC_2023-10-24_final
2023-12-25 12:05:38	ga_s2am_ard_3-2-1_50JKP_2023-12-25_final
2023-12-26 11:36:58	ga_s2am_ard_3-2-1_51HTC_2023-12-26_final
2023-12-29 11:43:01	ga_s2am_ard_3-2-1_50KRD_2023-12-29_final
2024-01-01 11:57:06	ga_s2am_ard_3-2-1_50HLH_2024-01-01_final
2024-01-08 11:42:56	ga_s2am_ard_3-2-1_51KUU_2024-01-08_final
2024-01-11 11:56:02	ga_s2am_ard_3-2-1_50JMM_2024-01-11_final
2024-01-18 11:42:51	ga_s2am_ard_3-2-1_51KUU_2024-01-18_final
2024-02-27 11:42:59	ga_s2am_ard_3-2-1_51KUU_2024-02-27_final
2024-03-11 11:53:21	ga_s2am_ard_3-2-1_50KPC_2024-03-11_final
2024-04-03 12:03:56	ga_s2am_ard_3-2-1_50KKA_2024-04-03_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