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
2016-01-20 11:47:47	ga_s2am_ard_3-2-1_51KUQ_2016-01-20_final.stac-item
2016-03-07 11:32:50	ga_s2am_ard_3-2-1_51HVE_2016-03-07_final
2016-04-29 11:42:00	ga_s2am_ard_3-2-1_51KUR_2016-04-29_final.stac-item
2016-05-08 12:13:49	ga_s2am_ard_3-2-1_49KHQ_2016-05-08_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51JTG_2016-05-09_final.stac-item
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51JTL_2016-05-09_final.stac-item
2016-05-15 12:02:55	ga_s2am_ard_3-2-1_50KNB_2016-05-15_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNN_2016-05-22_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_51JTL_2016-05-29_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_51KUP_2016-05-29_final.stac-item
2016-11-12 11:26:19	ga_s2am_ard_3-2-1_51KVT_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51KVR_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51KVS_2016-11-12_final.stac-item
2016-11-12 11:33:14	ga_s2am_ard_3-2-1_51KXQ_2016-11-12_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51KUT_2016-11-22_final.stac-item
2016-11-22 11:27:24	ga_s2am_ard_3-2-1_51KWT_2016-11-22_final.stac-item
2016-12-15 11:38:49	ga_s2am_ard_3-2-1_51KVS_2016-12-15_final.stac-item
2016-12-22 11:29:07	ga_s2am_ard_3-2-1_51KUP_2016-12-22_final.stac-item
2016-12-25 11:36:56	ga_s2am_ard_3-2-1_51KUU_2016-12-25_final.stac-item
2016-12-31 12:02:43	ga_s2am_ard_3-2-1_49KHS_2016-12-31_final
2017-01-01 11:30:38	ga_s2am_ard_3-2-1_51KWU_2017-01-01_final.stac-item
2017-01-14 11:34:53	ga_s2am_ard_3-2-1_51KVT_2017-01-14_final.stac-item
2017-11-07 11:31:46	ga_s2am_ard_3-2-1_51KXQ_2017-11-07_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_51KVS_2017-11-20_final.stac-item
2018-02-08 11:40:45	ga_s2am_ard_3-2-1_51KUT_2018-02-08_final.stac-item
2018-02-15 11:30:37	ga_s2am_ard_3-2-1_51KVT_2018-02-15_final.stac-item
2018-10-30 11:16:56	ga_s2am_ard_3-2-1_51KWQ_2018-10-30_final.stac-item
2018-12-02 11:33:04	ga_s2am_ard_3-2-1_51KWT_2018-12-02_final.stac-item
2018-12-12 11:33:04	ga_s2am_ard_3-2-1_51KWT_2018-12-12_final.stac-item
2018-12-25 11:43:51	ga_s2am_ard_3-2-1_51KUQ_2018-12-25_final.stac-item
2018-12-29 11:23:50	ga_s2am_ard_3-2-1_51KXQ_2018-12-29_final.stac-item
2019-01-01 11:33:21	ga_s2am_ard_3-2-1_51KWS_2019-01-01_final.stac-item
2019-01-11 11:33:52	ga_s2am_ard_3-2-1_51KWQ_2019-01-11_final.stac-item
2019-01-11 11:34:13	ga_s2am_ard_3-2-1_51KUP_2019-01-11_final.stac-item
2019-01-21 11:33:59	ga_s2am_ard_3-2-1_51KUQ_2019-01-21_final.stac-item
2019-11-10 11:43:27	ga_s2am_ard_3-2-1_51KVS_2019-11-10_final.stac-item
2019-11-11 11:14:31	ga_s2am_ard_3-2-1_51JYN_2019-11-11_final.stac-item
2019-11-17 11:33:36	ga_s2am_ard_3-2-1_51KUS_2019-11-17_final.stac-item
2019-11-17 11:33:47	ga_s2am_ard_3-2-1_51KVR_2019-11-17_final.stac-item
2019-11-17 11:33:58	ga_s2am_ard_3-2-1_51KWQ_2019-11-17_final.stac-item
2019-11-27 11:32:46	ga_s2am_ard_3-2-1_51KVV_2019-11-27_final.stac-item
2019-12-07 11:33:54	ga_s2am_ard_3-2-1_51KWQ_2019-12-07_final.stac-item
2019-12-17 11:34:08	ga_s2am_ard_3-2-1_51KVP_2019-12-17_final.stac-item
2019-12-27 11:33:54	ga_s2am_ard_3-2-1_51KVQ_2019-12-27_final.stac-item
2020-01-16 11:34:31	ga_s2am_ard_3-2-1_50JRT_2020-01-16_final.stac-item
2020-01-19 11:43:23	ga_s2am_ard_3-2-1_51KUS_2020-01-19_final.stac-item
2020-02-15 11:33:16	ga_s2am_ard_3-2-1_51KUT_2020-02-15_final.stac-item
2020-02-15 11:33:27	ga_s2am_ard_3-2-1_51KUS_2020-02-15_final.stac-item
2020-02-15 11:33:35	ga_s2am_ard_3-2-1_51KWR_2020-02-15_final.stac-item
2020-03-06 11:33:59	ga_s2am_ard_3-2-1_51KUQ_2020-03-06_final.stac-item
2020-06-13 12:05:50	ga_s2am_ard_3-2-1_49JGJ_2020-06-13_final.stac-item
2020-11-04 11:43:02	ga_s2am_ard_3-2-1_51KVU_2020-11-04_final.stac-item
2020-12-11 11:33:56	ga_s2am_ard_3-2-1_51KVQ_2020-12-11_final.stac-item
2020-12-28 11:23:57	ga_s2am_ard_3-2-1_51KXQ_2020-12-28_final.stac-item
2021-01-04 11:14:24	ga_s2am_ard_3-2-1_51JZN_2021-01-04_final.stac-item
2021-01-04 11:14:29	ga_s2am_ard_3-2-1_51JYN_2021-01-04_final.stac-item
2021-02-19 11:34:02	ga_s2am_ard_3-2-1_51KUQ_2021-02-19_final.stac-item
2021-11-16 11:33:57	ga_s2am_ard_3-2-1_51KWQ_2021-11-16_final.stac-item
2021-11-26 11:33:38	ga_s2am_ard_3-2-1_51KXR_2021-11-26_final.stac-item
2021-12-03 11:23:42	ga_s2am_ard_3-2-1_51KXR_2021-12-03_final.stac-item
2021-12-16 11:34:11	ga_s2am_ard_3-2-1_51KWP_2021-12-16_final.stac-item
2021-12-26 11:33:35	ga_s2am_ard_3-2-1_51KUS_2021-12-26_final.stac-item
2021-12-30 11:15:12	ga_s2am_ard_3-2-1_51JYK_2021-12-30_final.stac-item
2022-01-22 11:23:43	ga_s2am_ard_3-2-1_51KXR_2022-01-22_final.stac-item
2022-01-25 11:33:56	ga_s2am_ard_3-2-1_51KWQ_2022-01-25_final.stac-item
2022-02-04 11:33:30	ga_s2am_ard_3-2-1_51KVS_2022-02-04_final.stac-item
2022-02-04 11:33:41	ga_s2am_ard_3-2-1_51KWR_2022-02-04_final.stac-item
2022-02-04 11:33:45	ga_s2am_ard_3-2-1_51KVR_2022-02-04_final.stac-item
2022-02-14 11:33:42	ga_s2am_ard_3-2-1_51KWR_2022-02-14_final.stac-item
2022-02-21 11:24:04	ga_s2am_ard_3-2-1_51KWQ_2022-02-21_final.stac-item
2022-10-31 12:05:48	ga_s2am_ard_3-2-1_49JGJ_2022-10-31_final.stac-item
2022-12-04 11:43:15	ga_s2am_ard_3-2-1_51KUT_2022-12-04_final.stac-item
2022-12-04 11:44:13	ga_s2am_ard_3-2-1_51KUP_2022-12-04_final.stac-item
2022-12-11 11:33:22	ga_s2am_ard_3-2-1_51KUT_2022-12-11_final.stac-item
2022-12-24 11:43:23	ga_s2am_ard_3-2-1_51KVS_2022-12-24_final.stac-item
2022-12-24 11:43:56	ga_s2am_ard_3-2-1_51KUQ_2022-12-24_final.stac-item
2022-12-31 11:34:13	ga_s2am_ard_3-2-1_51KVP_2022-12-31_final.stac-item
2023-01-17 11:23:39	ga_s2am_ard_3-2-1_51KXR_2023-01-17_final.stac-item
2023-02-09 11:33:40	ga_s2am_ard_3-2-1_51KWR_2023-02-09_final.stac-item
2023-02-12 11:43:09	ga_s2am_ard_3-2-1_51KVT_2023-02-12_nrt.stac-item
2023-02-12 11:43:09	ga_s2am_ard_3-2-1_51KVT_2023-02-12_final
2023-02-16 11:23:59	ga_s2am_ard_3-2-1_51KWQ_2023-02-16_nrt.stac-item
2023-02-16 11:23:59	ga_s2am_ard_3-2-1_51KWQ_2023-02-16_final
2023-02-26 11:23:59	ga_s2am_ard_3-2-1_51KWQ_2023-02-26_final
2023-04-20 11:37:15	ga_s2am_ard_3-2-1_50HQG_2023-04-20_final
2023-10-10 11:42:16	ga_s2am_ard_3-2-1_51KUB_2023-10-10_final
2023-11-09 11:43:24	ga_s2am_ard_3-2-1_51KVS_2023-11-09_final
2023-11-09 11:44:12	ga_s2am_ard_3-2-1_51KUP_2023-11-09_final
2023-11-26 11:34:08	ga_s2am_ard_3-2-1_51KVP_2023-11-26_final
2023-12-09 11:43:19	ga_s2am_ard_3-2-1_51KVS_2023-12-09_final
2023-12-23 11:24:33	ga_s2am_ard_3-2-1_51JWN_2023-12-23_final
2023-12-26 11:32:55	ga_s2am_ard_3-2-1_51KWU_2023-12-26_final
2023-12-29 11:42:14	ga_s2am_ard_3-2-1_51KUB_2023-12-29_final
2024-01-05 11:34:07	ga_s2am_ard_3-2-1_51KWP_2024-01-05_final
2024-01-08 11:43:25	ga_s2am_ard_3-2-1_51KUS_2024-01-08_final
2024-01-25 11:33:24	ga_s2am_ard_3-2-1_51KVS_2024-01-25_final
2024-02-04 11:33:18	ga_s2am_ard_3-2-1_51KUT_2024-02-04_final
2024-02-07 11:44:09	ga_s2am_ard_3-2-1_51KUP_2024-02-07_final
2024-02-14 11:37:15	ga_s2am_ard_3-2-1_50HQG_2024-02-14_final
2024-02-24 11:33:40	ga_s2am_ard_3-2-1_51KWR_2024-02-24_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

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