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
2015-12-08 11:30:59	ga_s2am_ard_3-2-1_51KYT_2015-12-08_final.stac-item
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_50HNG_2016-01-07_final
2016-01-07 11:37:54	ga_s2am_ard_3-2-1_51KWB_2016-01-07_final.stac-item
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51KWB_2016-01-20_final.stac-item
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_51HVD_2016-02-06_final.stac-item
2016-06-05 11:32:15	ga_s2am_ard_3-2-1_51KYT_2016-06-05_final.stac-item
2016-08-10 11:48:22	ga_s2am_ard_3-2-1_50HMK_2016-08-10_final.stac-item
2016-11-21 12:02:48	ga_s2am_ard_3-2-1_50KKB_2016-11-21_final.stac-item
2016-12-06 11:13:53	ga_s2am_ard_3-2-1_51JZN_2016-12-06_final.stac-item
2017-02-26 11:52:43	ga_s2am_ard_3-2-1_50JNQ_2017-02-26_final.stac-item
2017-03-01 12:03:41	ga_s2am_ard_3-2-1_49KHQ_2017-03-01_final.stac-item
2017-03-24 12:13:37	ga_s2am_ard_3-2-1_50KKA_2017-03-24_final.stac-item
2017-03-25 11:38:25	ga_s2am_ard_3-2-1_51KUV_2017-03-25_final.stac-item
2017-04-07 11:49:43	ga_s2am_ard_3-2-1_50KNC_2017-04-07_final.stac-item
2017-04-21 11:28:37	ga_s2am_ard_3-2-1_51KXA_2017-04-21_final.stac-item
2017-04-28 11:20:48	ga_s2am_ard_3-2-1_51KXT_2017-04-28_final.stac-item
2017-06-07 11:19:47	ga_s2am_ard_3-2-1_51KXU_2017-06-07_final.stac-item
2017-11-06 12:02:48	ga_s2am_ard_3-2-1_50KNA_2017-11-06_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51KWB_2017-11-07_final.stac-item
2018-04-09 11:40:31	ga_s2am_ard_3-2-1_51KVT_2018-04-09_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51KYS_2018-09-10_final.stac-item
2019-01-13 12:14:08	ga_s2am_ard_3-2-1_49KGQ_2019-01-13_final.stac-item
2019-01-23 12:13:51	ga_s2am_ard_3-2-1_50KKA_2019-01-23_final.stac-item
2019-01-23 12:14:09	ga_s2am_ard_3-2-1_49KGQ_2019-01-23_final.stac-item
2019-01-23 12:14:23	ga_s2am_ard_3-2-1_49KGP_2019-01-23_final.stac-item
2019-01-31 11:32:08	ga_s2am_ard_3-2-1_51KXB_2019-01-31_final.stac-item
2019-02-03 11:42:57	ga_s2am_ard_3-2-1_51KUU_2019-02-03_final.stac-item
2019-02-07 11:22:57	ga_s2am_ard_3-2-1_51KXU_2019-02-07_final.stac-item
2019-04-21 11:33:55	ga_s2am_ard_3-2-1_51KXQ_2019-04-21_final.stac-item
2019-05-01 11:33:38	ga_s2am_ard_3-2-1_51KUS_2019-05-01_final.stac-item
2019-07-13 11:43:08	ga_s2am_ard_3-2-1_51KTU_2019-07-13_final.stac-item
2019-07-29 12:03:49	ga_s2am_ard_3-2-1_50KKB_2019-07-29_final.stac-item
2019-08-02 11:42:26	ga_s2am_ard_3-2-1_51KWA_2019-08-02_final.stac-item
2019-08-12 11:43:33	ga_s2am_ard_3-2-1_51KUS_2019-08-12_final.stac-item
2019-10-01 11:43:06	ga_s2am_ard_3-2-1_50KRD_2019-10-01_final.stac-item
2019-11-20 11:42:47	ga_s2am_ard_3-2-1_51KUV_2019-11-20_final.stac-item
2019-11-27 11:33:22	ga_s2am_ard_3-2-1_51KUT_2019-11-27_final.stac-item
2019-12-13 11:52:54	ga_s2am_ard_3-2-1_50KRD_2019-12-13_final.stac-item
2019-12-17 11:33:42	ga_s2am_ard_3-2-1_51KUR_2019-12-17_final.stac-item
2020-01-23 11:23:36	ga_s2am_ard_3-2-1_51KXR_2020-01-23_final.stac-item
2020-03-03 11:22:56	ga_s2am_ard_3-2-1_51KXU_2020-03-03_final.stac-item
2020-03-03 11:26:39	ga_s2am_ard_3-2-1_51HVD_2020-03-03_final.stac-item
2020-03-29 11:43:07	ga_s2am_ard_3-2-1_51KVT_2020-03-29_final.stac-item
2020-05-24 12:04:09	ga_s2am_ard_3-2-1_50KMV_2020-05-24_final.stac-item
2020-06-07 11:43:06	ga_s2am_ard_3-2-1_51KUU_2020-06-07_final.stac-item
2020-07-14 11:33:43	ga_s2am_ard_3-2-1_51KXR_2020-07-14_final.stac-item
2020-08-26 11:42:14	ga_s2am_ard_3-2-1_51KWB_2020-08-26_final.stac-item
2020-08-29 11:56:16	ga_s2am_ard_3-2-1_50JLM_2020-08-29_final.stac-item
2020-09-02 11:33:50	ga_s2am_ard_3-2-1_51KVR_2020-09-02_final.stac-item
2020-09-22 11:33:50	ga_s2am_ard_3-2-1_51KVR_2020-09-22_final.stac-item
2020-10-02 11:34:08	ga_s2am_ard_3-2-1_51KUQ_2020-10-02_final.stac-item
2020-11-10 12:05:01	ga_s2am_ard_3-2-1_50JKS_2020-11-10_final.stac-item
2020-12-24 11:42:56	ga_s2am_ard_3-2-1_51KVU_2020-12-24_final.stac-item
2021-02-19 11:32:14	ga_s2am_ard_3-2-1_51KWB_2021-02-19_final.stac-item
2021-04-30 11:33:36	ga_s2am_ard_3-2-1_51KXR_2021-04-30_final.stac-item
2021-05-17 11:23:28	ga_s2am_ard_3-2-1_51KXS_2021-05-17_final.stac-item
2021-06-02 11:43:19	ga_s2am_ard_3-2-1_51KTT_2021-06-02_final.stac-item
2021-10-10 11:47:12	ga_s2am_ard_3-2-1_50HNH_2021-10-10_final.stac-item
2021-11-22 11:52:34	ga_s2am_ard_3-2-1_50KQF_2021-11-22_final
2021-11-22 11:56:40	ga_s2am_ard_3-2-1_50HLK_2021-11-22_final.stac-item
2021-11-26 11:33:13	ga_s2am_ard_3-2-1_51KWT_2021-11-26_final.stac-item
2021-12-16 11:33:48	ga_s2am_ard_3-2-1_51KUR_2021-12-16_final.stac-item
2022-01-21 11:55:59	ga_s2am_ard_3-2-1_50JKN_2022-01-21_final.stac-item
2022-02-14 11:34:37	ga_s2am_ard_3-2-1_50JRT_2022-02-14_final.stac-item
2022-03-02 11:56:14	ga_s2am_ard_3-2-1_50JLM_2022-03-02_final.stac-item
2022-03-22 11:56:11	ga_s2am_ard_3-2-1_50JMM_2022-03-22_final.stac-item
2022-03-26 11:35:50	ga_s2am_ard_3-2-1_51JTH_2022-03-26_final.stac-item
2022-04-01 11:56:32	ga_s2am_ard_3-2-1_50HNK_2022-04-01_final.stac-item
2022-04-22 11:26:45	ga_s2am_ard_3-2-1_51HWD_2022-04-22_final.stac-item
2022-05-05 11:32:51	ga_s2am_ard_3-2-1_51KVV_2022-05-05_final.stac-item
2022-05-15 11:33:32	ga_s2am_ard_3-2-1_51KWS_2022-05-15_final.stac-item
2022-08-03 11:33:41	ga_s2am_ard_3-2-1_51KVS_2022-08-03_final.stac-item
2022-08-13 11:33:21	ga_s2am_ard_3-2-1_51KXT_2022-08-13_final.stac-item
2022-10-11 12:05:43	ga_s2am_ard_3-2-1_50JLP_2022-10-11_final.stac-item
2022-10-25 11:43:27	ga_s2am_ard_3-2-1_51KVS_2022-10-25_final.stac-item
2022-11-10 12:05:33	ga_s2am_ard_3-2-1_49JGK_2022-11-10_final.stac-item
2022-12-11 11:33:13	ga_s2am_ard_3-2-1_51KWT_2022-12-11_final.stac-item
2022-12-28 11:27:06	ga_s2am_ard_3-2-1_51HTC_2022-12-28_final.stac-item
2023-01-10 11:36:50	ga_s2am_ard_3-2-1_50HPJ_2023-01-10_final.stac-item
2023-01-27 11:23:59	ga_s2am_ard_3-2-1_51KWQ_2023-01-27_final.stac-item
2023-02-09 11:33:33	ga_s2am_ard_3-2-1_51KUS_2023-02-09_final.stac-item
2023-02-12 11:43:17	ga_s2am_ard_3-2-1_50KRC_2023-02-12_final
2023-02-22 11:45:33	ga_s2am_ard_3-2-1_50JPP_2023-02-22_nrt.stac-item
2023-02-22 11:45:33	ga_s2am_ard_3-2-1_50JPP_2023-02-22_final
2023-03-01 11:36:44	ga_s2am_ard_3-2-1_51HTD_2023-03-01_final
2023-04-10 11:33:16	ga_s2am_ard_3-2-1_51KVT_2023-04-10_final
2023-05-10 11:33:23	ga_s2am_ard_3-2-1_51KXS_2023-05-10_final
2023-05-16 11:56:15	ga_s2am_ard_3-2-1_50JKM_2023-05-16_final
2023-07-29 11:33:03	ga_s2am_ard_3-2-1_51KWU_2023-07-29_final
2023-07-29 11:34:16	ga_s2am_ard_3-2-1_51KWP_2023-07-29_final
2023-10-03 11:54:53	ga_s2am_ard_3-2-1_50JNS_2023-10-03_final
2023-10-27 11:33:01	ga_s2am_ard_3-2-1_51KVU_2023-10-27_final
2023-11-16 11:32:57	ga_s2am_ard_3-2-1_51KWU_2023-11-16_final
2023-11-23 11:23:06	ga_s2am_ard_3-2-1_51KYT_2023-11-23_final
2023-11-29 11:46:54	ga_s2am_ard_3-2-1_50HPH_2023-11-29_final
2023-12-29 11:42:06	ga_s2am_ard_3-2-1_51KWB_2023-12-29_final
2024-01-29 11:14:04	ga_s2am_ard_3-2-1_51KZP_2024-01-29_final
2024-02-21 11:23:11	ga_s2am_ard_3-2-1_51KXT_2024-02-21_final
2024-03-27 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2024-03-27_final
2024-04-11 11:23:01	ga_s2am_ard_3-2-1_51KXU_2024-04-11_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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