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
2016-05-09 11:40:18	ga_s2am_ard_3-2-1_51KUR_2016-05-09_final.stac-item
2016-05-16 11:32:16	ga_s2am_ard_3-2-1_51KVQ_2016-05-16_final.stac-item
2016-11-05 11:39:53	ga_s2am_ard_3-2-1_51KTT_2016-11-05_final.stac-item
2017-02-13 11:37:46	ga_s2am_ard_3-2-1_50KRC_2017-02-13_final.stac-item
2017-05-31 11:28:39	ga_s2am_ard_3-2-1_51KWB_2017-05-31_final.stac-item
2017-05-31 11:35:01	ga_s2am_ard_3-2-1_51HTC_2017-05-31_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_51KUU_2017-11-20_final.stac-item
2017-11-20 11:41:28	ga_s2am_ard_3-2-1_51KVA_2017-11-20_final.stac-item
2017-11-26 12:02:45	ga_s2am_ard_3-2-1_50KNC_2017-11-26_final.stac-item
2018-01-06 11:32:02	ga_s2am_ard_3-2-1_51KUT_2018-01-06_final.stac-item
2018-02-15 11:30:37	ga_s2am_ard_3-2-1_51KWA_2018-02-15_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_51KWU_2018-05-26_final.stac-item
2018-06-25 11:32:58	ga_s2am_ard_3-2-1_51KWU_2018-06-25_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_49KGP_2018-07-14_final.stac-item
2018-07-15 11:32:59	ga_s2am_ard_3-2-1_50HQH_2018-07-15_final.stac-item
2018-11-22 11:32:07	ga_s2am_ard_3-2-1_51KWB_2018-11-22_final.stac-item
2018-11-25 11:42:38	ga_s2am_ard_3-2-1_51KUV_2018-11-25_final.stac-item
2018-12-02 11:34:02	ga_s2am_ard_3-2-1_51KWP_2018-12-02_final.stac-item
2019-01-01 11:33:36	ga_s2am_ard_3-2-1_51KWR_2019-01-01_final.stac-item
2019-01-04 11:42:40	ga_s2am_ard_3-2-1_51KUV_2019-01-04_final.stac-item
2019-02-03 11:43:12	ga_s2am_ard_3-2-1_51KUT_2019-02-03_final.stac-item
2019-02-16 11:56:37	ga_s2am_ard_3-2-1_50HLK_2019-02-16_final.stac-item
2019-03-22 11:33:40	ga_s2am_ard_3-2-1_51KWR_2019-03-22_final.stac-item
2019-05-14 11:42:13	ga_s2am_ard_3-2-1_51KWB_2019-05-14_final.stac-item
2019-05-21 11:34:03	ga_s2am_ard_3-2-1_51KVQ_2019-05-21_final.stac-item
2019-06-13 11:43:21	ga_s2am_ard_3-2-1_51KTT_2019-06-13_final.stac-item
2019-06-17 11:25:13	ga_s2am_ard_3-2-1_51JXK_2019-06-17_final.stac-item
2019-10-08 11:33:59	ga_s2am_ard_3-2-1_51KWQ_2019-10-08_final.stac-item
2019-10-21 11:43:18	ga_s2am_ard_3-2-1_51KUT_2019-10-21_final.stac-item
2019-11-20 11:43:12	ga_s2am_ard_3-2-1_51KVT_2019-11-20_final.stac-item
2019-12-06 12:03:57	ga_s2am_ard_3-2-1_49KHR_2019-12-06_final.stac-item
2019-12-14 11:24:32	ga_s2am_ard_3-2-1_51JYM_2019-12-14_final.stac-item
2020-01-09 11:42:08	ga_s2am_ard_3-2-1_51KVB_2020-01-09_final.stac-item
2020-03-18 12:14:38	ga_s2am_ard_3-2-1_49JGN_2020-03-18_final.stac-item
2020-03-23 11:26:58	ga_s2am_ard_3-2-1_51HUC_2020-03-23_final.stac-item
2020-05-12 11:24:19	ga_s2am_ard_3-2-1_51KWP_2020-05-12_final.stac-item
2020-05-18 11:42:22	ga_s2am_ard_3-2-1_51KUB_2020-05-18_final
2020-06-30 11:52:25	ga_s2am_ard_3-2-1_50KQG_2020-06-30_final
2020-06-30 11:56:04	ga_s2am_ard_3-2-1_50JKN_2020-06-30_final.stac-item
2020-07-04 11:33:10	ga_s2am_ard_3-2-1_51KVU_2020-07-04_final.stac-item
2020-07-14 11:34:07	ga_s2am_ard_3-2-1_51KUQ_2020-07-14_final.stac-item
2020-08-09 11:53:27	ga_s2am_ard_3-2-1_50KPC_2020-08-09_final.stac-item
2020-11-08 11:24:02	ga_s2am_ard_3-2-1_51KXQ_2020-11-08_final.stac-item
2020-11-14 11:45:43	ga_s2am_ard_3-2-1_50JNP_2020-11-14_final.stac-item
2020-11-15 11:16:47	ga_s2am_ard_3-2-1_51HWD_2020-11-15_final.stac-item
2020-12-04 11:44:18	ga_s2am_ard_3-2-1_50KQU_2020-12-04_final.stac-item
2021-02-08 12:03:22	ga_s2am_ard_3-2-1_50KMC_2021-02-08_final.stac-item
2021-03-24 11:43:23	ga_s2am_ard_3-2-1_51KVS_2021-03-24_final.stac-item
2021-05-04 11:15:55	ga_s2am_ard_3-2-1_51JXG_2021-05-04_final.stac-item
2021-06-09 11:37:07	ga_s2am_ard_3-2-1_50HPH_2021-06-09_final.stac-item
2021-06-18 12:04:28	ga_s2am_ard_3-2-1_50KKU_2021-06-18_final.stac-item
2021-09-17 11:32:48	ga_s2am_ard_3-2-1_51KVV_2021-09-17_final.stac-item
2021-10-07 11:33:27	ga_s2am_ard_3-2-1_51KUT_2021-10-07_final.stac-item
2021-10-27 11:34:05	ga_s2am_ard_3-2-1_51KVQ_2021-10-27_final.stac-item
2021-11-18 12:14:27	ga_s2am_ard_3-2-1_49KGP_2021-11-18_final.stac-item
2021-11-26 11:32:19	ga_s2am_ard_3-2-1_51KVB_2021-11-26_final.stac-item
2021-12-09 11:42:55	ga_s2am_ard_3-2-1_51KVU_2021-12-09_final.stac-item
2021-12-13 11:23:57	ga_s2am_ard_3-2-1_51KXQ_2021-12-13_final.stac-item
2022-01-08 11:43:05	ga_s2am_ard_3-2-1_51KTU_2022-01-08_final.stac-item
2022-01-18 11:42:57	ga_s2am_ard_3-2-1_51KVU_2022-01-18_final.stac-item
2022-03-19 11:42:46	ga_s2am_ard_3-2-1_51KVV_2022-03-19_final.stac-item
2022-04-04 12:04:33	ga_s2am_ard_3-2-1_49KGP_2022-04-04_final.stac-item
2022-04-11 11:53:12	ga_s2am_ard_3-2-1_50KRC_2022-04-11_final.stac-item
2022-06-11 11:23:52	ga_s2am_ard_3-2-1_51KXR_2022-06-11_final.stac-item
2022-07-01 11:26:31	ga_s2am_ard_3-2-1_51JUF_2022-07-01_final.stac-item
2022-07-04 11:32:42	ga_s2am_ard_3-2-1_51KWA_2022-07-04_final.stac-item
2022-07-24 11:32:54	ga_s2am_ard_3-2-1_51KWV_2022-07-24_final.stac-item
2022-08-26 11:43:09	ga_s2am_ard_3-2-1_51KVU_2022-08-26_final
2022-09-02 11:36:11	ga_s2am_ard_3-2-1_51JUG_2022-09-02_final.stac-item
2022-09-12 11:32:54	ga_s2am_ard_3-2-1_51KWV_2022-09-12_final.stac-item
2022-10-12 11:33:21	ga_s2am_ard_3-2-1_51KVT_2022-10-12_final.stac-item
2022-10-25 11:42:48	ga_s2am_ard_3-2-1_51KUV_2022-10-25_final.stac-item
2022-11-14 11:42:45	ga_s2am_ard_3-2-1_51KVV_2022-11-14_final.stac-item
2022-11-15 11:14:26	ga_s2am_ard_3-2-1_51JZN_2022-11-15_final.stac-item
2022-12-27 11:55:55	ga_s2am_ard_3-2-1_50JLN_2022-12-27_final.stac-item
2023-02-02 11:46:54	ga_s2am_ard_3-2-1_50HMJ_2023-02-02_final
2023-02-22 11:43:41	ga_s2am_ard_3-2-1_51KUR_2023-02-22_final
2023-03-01 11:36:40	ga_s2am_ard_3-2-1_51HUD_2023-03-01_final
2023-03-10 12:05:50	ga_s2am_ard_3-2-1_50JKN_2023-03-10_final
2023-04-10 11:32:32	ga_s2am_ard_3-2-1_51KVA_2023-04-10_final
2023-04-20 11:33:32	ga_s2am_ard_3-2-1_51KUS_2023-04-20_final
2023-04-30 11:33:34	ga_s2am_ard_3-2-1_51KUS_2023-04-30_final
2023-06-01 12:14:35	ga_s2am_ard_3-2-1_49KFP_2023-06-01_nrt
2023-06-12 11:42:13	ga_s2am_ard_3-2-1_51KWB_2023-06-12_final
2023-06-12 11:43:04	ga_s2am_ard_3-2-1_51KUU_2023-06-12_final
2023-07-12 11:43:23	ga_s2am_ard_3-2-1_51KTT_2023-07-12_final
2023-07-13 11:14:28	ga_s2am_ard_3-2-1_51JZN_2023-07-13_final
2023-08-04 11:53:26	ga_s2am_ard_3-2-1_50KPC_2023-08-04_final
2023-09-07 11:36:37	ga_s2am_ard_3-2-1_51HTE_2023-09-07_final
2023-09-30 11:43:27	ga_s2am_ard_3-2-1_51KVS_2023-09-30_final
2023-10-09 12:14:56	ga_s2am_ard_3-2-1_49JGM_2023-10-09_final
2023-10-24 11:27:02	ga_s2am_ard_3-2-1_51HUC_2023-10-24_final
2023-10-30 11:42:16	ga_s2am_ard_3-2-1_51KUB_2023-10-30_final
2023-11-13 11:23:56	ga_s2am_ard_3-2-1_51KXQ_2023-11-13_final
2023-11-16 11:33:55	ga_s2am_ard_3-2-1_51KWQ_2023-11-16_final
2024-01-01 11:52:21	ga_s2am_ard_3-2-1_50KQG_2024-01-01_final
2024-01-02 11:26:29	ga_s2am_ard_3-2-1_51HUE_2024-01-02_final
2024-01-28 11:42:58	ga_s2am_ard_3-2-1_51KTU_2024-01-28_final
2024-02-23 12:03:57	ga_s2am_ard_3-2-1_49KHR_2024-02-23_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