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
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JKP_2016-04-02_final.stac-item
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_50HMK_2016-04-29_final.stac-item
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51HVC_2016-05-03_final.stac-item
2016-08-20 11:56:10	ga_s2am_ard_3-2-1_50JLM_2016-08-20_final.stac-item
2016-09-06 11:40:12	ga_s2am_ard_3-2-1_51KVB_2016-09-06_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51KUV_2016-12-15_final.stac-item
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_51KVS_2017-01-01_final.stac-item
2017-06-13 11:40:49	ga_s2am_ard_3-2-1_51KUT_2017-06-13_final.stac-item
2017-07-03 11:37:51	ga_s2am_ard_3-2-1_51KUV_2017-07-03_final.stac-item
2017-08-19 11:30:19	ga_s2am_ard_3-2-1_51JVH_2017-08-19_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_50JQL_2017-09-28_final.stac-item
2017-10-17 12:02:48	ga_s2am_ard_3-2-1_50JLN_2017-10-17_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51KUS_2018-01-06_final.stac-item
2018-04-23 11:17:01	ga_s2am_ard_3-2-1_51JZM_2018-04-23_final.stac-item
2018-07-05 11:35:08	ga_s2am_ard_3-2-1_50HQH_2018-07-05_final.stac-item
2018-07-28 11:45:46	ga_s2am_ard_3-2-1_50HNH_2018-07-28_final.stac-item
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_51KVS_2018-08-17_final.stac-item
2018-08-23 12:02:48	ga_s2am_ard_3-2-1_50KMC_2018-08-23_final.stac-item
2018-10-13 11:32:54	ga_s2am_ard_3-2-1_51HTC_2018-10-13_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51HVE_2018-10-23_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_51KVT_2018-10-26_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KVT_2018-11-02_final.stac-item
2018-11-25 11:42:34	ga_s2am_ard_3-2-1_51KVV_2018-11-25_final.stac-item
2018-12-15 11:42:52	ga_s2am_ard_3-2-1_51KUU_2018-12-15_final.stac-item
2018-12-25 11:42:38	ga_s2am_ard_3-2-1_51KUV_2018-12-25_final.stac-item
2019-01-03 12:14:50	ga_s2am_ard_3-2-1_49JGM_2019-01-03_final.stac-item
2019-01-31 11:32:11	ga_s2am_ard_3-2-1_51KWB_2019-01-31_final.stac-item
2019-05-01 11:33:09	ga_s2am_ard_3-2-1_51KVU_2019-05-01_final.stac-item
2019-05-04 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2019-05-04_final.stac-item
2019-07-23 11:44:03	ga_s2am_ard_3-2-1_51KUQ_2019-07-23_final.stac-item
2019-09-01 11:43:30	ga_s2am_ard_3-2-1_51KUS_2019-09-01_final.stac-item
2019-10-31 11:46:51	ga_s2am_ard_3-2-1_50HPJ_2019-10-31_final.stac-item
2019-11-20 11:43:12	ga_s2am_ard_3-2-1_51KVT_2019-11-20_final.stac-item
2019-11-30 11:43:10	ga_s2am_ard_3-2-1_51KVT_2019-11-30_final.stac-item
2019-12-17 11:36:21	ga_s2am_ard_3-2-1_50JPL_2019-12-17_final.stac-item
2020-01-03 11:26:56	ga_s2am_ard_3-2-1_51HUC_2020-01-03_final.stac-item
2020-02-22 11:24:58	ga_s2am_ard_3-2-1_51JVL_2020-02-22_final.stac-item
2020-03-02 11:52:15	ga_s2am_ard_3-2-1_50KQG_2020-03-02_final
2020-03-09 11:43:07	ga_s2am_ard_3-2-1_51KVT_2020-03-09_final.stac-item
2020-05-08 11:43:01	ga_s2am_ard_3-2-1_51KVU_2020-05-08_final.stac-item
2020-06-14 11:36:32	ga_s2am_ard_3-2-1_50JPL_2020-06-14_final.stac-item
2020-06-17 11:43:09	ga_s2am_ard_3-2-1_51KTU_2020-06-17_final.stac-item
2020-08-10 11:26:38	ga_s2am_ard_3-2-1_51HUE_2020-08-10_final.stac-item
2020-09-02 11:35:53	ga_s2am_ard_3-2-1_51JTH_2020-09-02_final.stac-item
2020-09-02 11:36:47	ga_s2am_ard_3-2-1_51HUD_2020-09-02_final.stac-item
2020-10-15 11:42:51	ga_s2am_ard_3-2-1_51KUV_2020-10-15_final.stac-item
2020-10-22 11:32:25	ga_s2am_ard_3-2-1_51KVB_2020-10-22_final.stac-item
2021-02-09 11:32:28	ga_s2am_ard_3-2-1_51KWA_2021-02-09_final.stac-item
2021-02-12 11:42:26	ga_s2am_ard_3-2-1_51KVA_2021-02-12_final.stac-item
2021-02-15 11:55:58	ga_s2am_ard_3-2-1_50JKN_2021-02-15_final.stac-item
2021-02-19 11:32:14	ga_s2am_ard_3-2-1_51KWB_2021-02-19_final.stac-item
2021-03-01 11:36:02	ga_s2am_ard_3-2-1_51JTG_2021-03-01_final.stac-item
2021-04-06 11:52:30	ga_s2am_ard_3-2-1_50KQF_2021-04-06_final
2021-04-13 11:46:28	ga_s2am_ard_3-2-1_50HPK_2021-04-13_final.stac-item
2021-06-22 11:43:59	ga_s2am_ard_3-2-1_51KUQ_2021-06-22_final.stac-item
2021-08-10 12:14:44	ga_s2am_ard_3-2-1_49JGN_2021-08-10_final.stac-item
2021-09-27 11:32:50	ga_s2am_ard_3-2-1_51KVV_2021-09-27_final.stac-item
2021-10-07 11:37:23	ga_s2am_ard_3-2-1_50HQG_2021-10-07_final
2021-10-17 11:33:21	ga_s2am_ard_3-2-1_51KVT_2021-10-17_final.stac-item
2021-10-26 12:03:49	ga_s2am_ard_3-2-1_50KKB_2021-10-26_final.stac-item
2022-01-08 11:43:23	ga_s2am_ard_3-2-1_50KQC_2022-01-08_final.stac-item
2022-01-18 11:43:12	ga_s2am_ard_3-2-1_51KVT_2022-01-18_final.stac-item
2022-04-22 11:24:06	ga_s2am_ard_3-2-1_51KWQ_2022-04-22_final.stac-item
2022-04-25 11:34:15	ga_s2am_ard_3-2-1_51KWP_2022-04-25_final.stac-item
2022-05-08 11:43:22	ga_s2am_ard_3-2-1_51KTT_2022-05-08_final.stac-item
2022-05-12 11:25:13	ga_s2am_ard_3-2-1_51JXK_2022-05-12_final.stac-item
2022-06-24 11:34:12	ga_s2am_ard_3-2-1_51KVQ_2022-06-24_final.stac-item
2022-08-02 12:04:09	ga_s2am_ard_3-2-1_50KKA_2022-08-02_final.stac-item
2022-08-13 11:33:46	ga_s2am_ard_3-2-1_51KUS_2022-08-13_final.stac-item
2022-11-05 11:14:33	ga_s2am_ard_3-2-1_51JYN_2022-11-05_final.stac-item
2022-11-24 11:43:28	ga_s2am_ard_3-2-1_51KUS_2022-11-24_final.stac-item
2022-12-04 11:42:42	ga_s2am_ard_3-2-1_51KVV_2022-12-04_final.stac-item
2022-12-11 11:33:48	ga_s2am_ard_3-2-1_51KUR_2022-12-11_final.stac-item
2023-01-13 11:42:40	ga_s2am_ard_3-2-1_51KVV_2023-01-13_final.stac-item
2023-01-19 12:05:24	ga_s2am_ard_3-2-1_49JGK_2023-01-19_final.stac-item
2023-01-20 11:37:16	ga_s2am_ard_3-2-1_50HPG_2023-01-20_final
2023-01-23 11:43:14	ga_s2am_ard_3-2-1_51KTT_2023-01-23_final.stac-item
2023-02-08 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-02-08_final
2023-02-18 12:04:57	ga_s2am_ard_3-2-1_49JGM_2023-02-18_final
2023-03-11 11:32:24	ga_s2am_ard_3-2-1_51KWA_2023-03-11_final
2023-04-20 11:32:13	ga_s2am_ard_3-2-1_51KWB_2023-04-20_final
2023-05-20 11:33:36	ga_s2am_ard_3-2-1_51KUS_2023-05-20_final
2023-06-09 11:34:03	ga_s2am_ard_3-2-1_51KVQ_2023-06-09_final
2023-06-12 11:42:50	ga_s2am_ard_3-2-1_51KUV_2023-06-12_final
2023-07-19 11:33:49	ga_s2am_ard_3-2-1_51KVR_2023-07-19_final
2023-07-29 11:37:12	ga_s2am_ard_3-2-1_50HPH_2023-07-29_final
2023-08-24 11:53:09	ga_s2am_ard_3-2-1_50KQD_2023-08-24_final
2023-09-07 11:32:25	ga_s2am_ard_3-2-1_51KVB_2023-09-07_final
2023-09-07 11:32:52	ga_s2am_ard_3-2-1_51KVV_2023-09-07_final
2023-09-23 11:53:12	ga_s2am_ard_3-2-1_50KRC_2023-09-23_final
2023-11-15 12:05:28	ga_s2am_ard_3-2-1_49JGK_2023-11-15_final
2023-12-16 11:32:43	ga_s2am_ard_3-2-1_51KVV_2023-12-16_final
2023-12-16 11:33:18	ga_s2am_ard_3-2-1_51KUT_2023-12-16_final
2023-12-16 11:37:13	ga_s2am_ard_3-2-1_50HQG_2023-12-16_final
2023-12-18 12:13:50	ga_s2am_ard_3-2-1_50KKA_2023-12-18_final
2024-01-02 11:24:12	ga_s2am_ard_3-2-1_51KWP_2024-01-02_final
2024-01-08 11:43:00	ga_s2am_ard_3-2-1_50KRD_2024-01-08_final
2024-01-25 11:33:54	ga_s2am_ard_3-2-1_51KVQ_2024-01-25_final
2024-02-24 11:33:54	ga_s2am_ard_3-2-1_51KWQ_2024-02-24_final
2024-04-17 11:42:34	ga_s2am_ard_3-2-1_51KVA_2024-04-17_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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