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
2015-12-27 12:04:06	ga_s2am_ard_3-2-1_50KLV_2015-12-27_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JLT_2016-05-22_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_50JNR_2016-05-29_final.stac-item
2016-10-07 11:12:10	ga_s2am_ard_3-2-1_51KZS_2016-10-07_final.stac-item
2016-10-12 12:03:43	ga_s2am_ard_3-2-1_50KLA_2016-10-12_final.stac-item
2016-11-14 12:13:24	ga_s2am_ard_3-2-1_50KKB_2016-11-14_final.stac-item
2016-11-15 11:44:31	ga_s2am_ard_3-2-1_50HLG_2016-11-15_final
2016-11-18 11:54:00	ga_s2am_ard_3-2-1_50HLG_2016-11-18_final
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_49JGJ_2017-03-31_final.stac-item
2017-04-11 11:36:02	ga_s2am_ard_3-2-1_51JUG_2017-04-11_final.stac-item
2017-07-03 11:43:16	ga_s2am_ard_3-2-1_50JNL_2017-07-03_final.stac-item
2017-07-17 11:20:58	ga_s2am_ard_3-2-1_51HVD_2017-07-17_final.stac-item
2017-09-28 11:30:00	ga_s2am_ard_3-2-1_51KVT_2017-09-28_final.stac-item
2017-10-07 12:03:46	ga_s2am_ard_3-2-1_50JKR_2017-10-07_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51KWQ_2017-11-07_final.stac-item
2017-12-03 11:53:28	ga_s2am_ard_3-2-1_50JLN_2017-12-03_final.stac-item
2017-12-26 12:03:42	ga_s2am_ard_3-2-1_50KLV_2017-12-26_final.stac-item
2017-12-26 12:04:36	ga_s2am_ard_3-2-1_49JHM_2017-12-26_final.stac-item
2017-12-26 12:04:47	ga_s2am_ard_3-2-1_50JKS_2017-12-26_final.stac-item
2018-02-22 11:20:58	ga_s2am_ard_3-2-1_51JWL_2018-02-22_final.stac-item
2018-03-17 11:33:01	ga_s2am_ard_3-2-1_51KWT_2018-03-17_final.stac-item
2018-03-30 11:39:33	ga_s2am_ard_3-2-1_51LUE_2018-03-30_final.stac-item
2018-04-06 11:31:45	ga_s2am_ard_3-2-1_51KVR_2018-04-06_final.stac-item
2018-04-29 11:40:08	ga_s2am_ard_3-2-1_51LWC_2018-04-29_final.stac-item
2018-05-06 11:32:02	ga_s2am_ard_3-2-1_51KWT_2018-05-06_final.stac-item
2018-06-15 11:32:57	ga_s2am_ard_3-2-1_51KWT_2018-06-15_final.stac-item
2018-08-06 12:13:21	ga_s2am_ard_3-2-1_50KKB_2018-08-06_final.stac-item
2018-08-24 11:26:19	ga_s2am_ard_3-2-1_51KXT_2018-08-24_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JNR_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JPS_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50JPT_2018-08-27_final.stac-item
2018-08-27 11:40:29	ga_s2am_ard_3-2-1_50KPU_2018-08-27_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_51KZQ_2018-08-28_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_50JPL_2018-09-03_final.stac-item
2018-09-30 11:16:55	ga_s2am_ard_3-2-1_51KYU_2018-09-30_final.stac-item
2018-10-05 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-10-05_final.stac-item
2018-10-15 12:13:18	ga_s2am_ard_3-2-1_50KKB_2018-10-15_final.stac-item
2018-10-16 11:40:28	ga_s2am_ard_3-2-1_51KTU_2018-10-16_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KUR_2018-10-23_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_50JNN_2018-10-26_final.stac-item
2018-10-29 11:49:24	ga_s2am_ard_3-2-1_50KRD_2018-10-29_final.stac-item
2018-11-22 11:37:00	ga_s2am_ard_3-2-1_50HPH_2018-11-22_final.stac-item
2019-01-03 12:13:48	ga_s2am_ard_3-2-1_50KKA_2019-01-03_final.stac-item
2019-01-04 11:45:09	ga_s2am_ard_3-2-1_51JTK_2019-01-04_final.stac-item
2019-01-07 11:54:39	ga_s2am_ard_3-2-1_50JLT_2019-01-07_final.stac-item
2019-01-24 11:43:32	ga_s2am_ard_3-2-1_51KVR_2019-01-24_final.stac-item
2019-03-25 11:42:59	ga_s2am_ard_3-2-1_51KUU_2019-03-25_final.stac-item
2019-05-11 11:32:44	ga_s2am_ard_3-2-1_51KXV_2019-05-11_final.stac-item
2019-06-13 11:43:18	ga_s2am_ard_3-2-1_51KUT_2019-06-13_final.stac-item
2019-07-07 11:24:03	ga_s2am_ard_3-2-1_51KWQ_2019-07-07_final.stac-item
2019-10-15 11:23:16	ga_s2am_ard_3-2-1_51KXT_2019-10-15_final.stac-item
2019-11-17 11:33:32	ga_s2am_ard_3-2-1_51KVS_2019-11-17_final.stac-item
2020-03-09 11:43:25	ga_s2am_ard_3-2-1_51KUS_2020-03-09_final.stac-item
2020-03-16 11:36:54	ga_s2am_ard_3-2-1_51HUC_2020-03-16_final.stac-item
2020-04-01 11:52:15	ga_s2am_ard_3-2-1_50KQG_2020-04-01_final
2020-04-05 11:35:30	ga_s2am_ard_3-2-1_51JTJ_2020-04-05_final.stac-item
2020-04-05 11:35:41	ga_s2am_ard_3-2-1_51JUH_2020-04-05_final.stac-item
2020-04-08 11:40:55	ga_s2am_ard_3-2-1_51LWG_2020-04-08_final
2020-04-08 11:43:12	ga_s2am_ard_3-2-1_51KUT_2020-04-08_final.stac-item
2020-04-12 11:23:48	ga_s2am_ard_3-2-1_51KZQ_2020-04-12_final.stac-item
2020-04-22 11:23:15	ga_s2am_ard_3-2-1_51KXT_2020-04-22_final.stac-item
2020-04-27 12:13:56	ga_s2am_ard_3-2-1_50KKA_2020-04-27_final.stac-item
2020-05-08 11:46:17	ga_s2am_ard_3-2-1_50JMM_2020-05-08_final.stac-item
2020-06-14 11:33:08	ga_s2am_ard_3-2-1_51KVU_2020-06-14_final.stac-item
2020-06-24 11:33:18	ga_s2am_ard_3-2-1_51KWT_2020-06-24_final.stac-item
2020-06-28 11:13:45	ga_s2am_ard_3-2-1_51KZR_2020-06-28_final.stac-item
2020-08-09 11:55:01	ga_s2am_ard_3-2-1_50JMS_2020-08-09_final.stac-item
2020-12-14 11:42:14	ga_s2am_ard_3-2-1_51KUB_2020-12-14_final
2020-12-30 12:04:31	ga_s2am_ard_3-2-1_49KGP_2020-12-30_final.stac-item
2021-03-01 11:34:54	ga_s2am_ard_3-2-1_51JWL_2021-03-01_final.stac-item
2021-03-05 11:13:28	ga_s2am_ard_3-2-1_51KZS_2021-03-05_final.stac-item
2021-03-31 11:33:31	ga_s2am_ard_3-2-1_51KUS_2021-03-31_final.stac-item
2021-04-29 12:03:38	ga_s2am_ard_3-2-1_50KLB_2021-04-29_final.stac-item
2021-05-02 12:14:57	ga_s2am_ard_3-2-1_49JFM_2021-05-02_final.stac-item
2021-05-20 11:33:09	ga_s2am_ard_3-2-1_51KXT_2021-05-20_final.stac-item
2021-05-27 11:25:14	ga_s2am_ard_3-2-1_51JWK_2021-05-27_final.stac-item
2021-05-27 11:25:57	ga_s2am_ard_3-2-1_51JWG_2021-05-27_final.stac-item
2021-07-02 11:42:59	ga_s2am_ard_3-2-1_51KVU_2021-07-02_final.stac-item
2021-07-05 11:53:05	ga_s2am_ard_3-2-1_50KQD_2021-07-05_final
2021-07-05 11:56:06	ga_s2am_ard_3-2-1_50JNM_2021-07-05_final.stac-item
2021-08-02 11:13:57	ga_s2am_ard_3-2-1_51KZQ_2021-08-02_final.stac-item
2021-09-07 11:33:57	ga_s2am_ard_3-2-1_51KWQ_2021-09-07_final.stac-item
2021-12-05 12:03:58	ga_s2am_ard_3-2-1_49KHR_2021-12-05_final.stac-item
2022-04-07 12:15:11	ga_s2am_ard_3-2-1_49JGL_2022-04-07_final.stac-item
2022-05-21 11:52:26	ga_s2am_ard_3-2-1_50KQG_2022-05-21_final
2022-05-24 12:04:41	ga_s2am_ard_3-2-1_50JKT_2022-05-24_final.stac-item
2022-08-19 11:53:11	ga_s2am_ard_3-2-1_50KRD_2022-08-19_final.stac-item
2022-09-02 11:33:57	ga_s2am_ard_3-2-1_51KVR_2022-09-02_final.stac-item
2022-09-19 11:23:29	ga_s2am_ard_3-2-1_51KZS_2022-09-19_final.stac-item
2022-09-22 11:36:33	ga_s2am_ard_3-2-1_50JPL_2022-09-22_final.stac-item
2022-10-22 11:35:14	ga_s2am_ard_3-2-1_51JVK_2022-10-22_final.stac-item
2022-11-01 11:32:50	ga_s2am_ard_3-2-1_51KVV_2022-11-01_final.stac-item
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
2023-04-13 11:44:50	ga_s2am_ard_3-2-1_50JQS_2023-04-13_final
2023-05-06 11:57:20	ga_s2am_ard_3-2-1_50HMG_2023-05-06_final
2023-05-14 11:16:59	ga_s2am_ard_3-2-1_51HWC_2023-05-14_final
2023-05-17 11:23:44	ga_s2am_ard_3-2-1_51KXR_2023-05-17_final
2023-09-30 11:47:29	ga_s2am_ard_3-2-1_50HLG_2023-09-30_final
2024-01-05 11:35:15	ga_s2am_ard_3-2-1_51JWJ_2024-01-05_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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