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
2016-02-06 11:34:36	ga_s2am_ard_3-2-1_50HQH_2016-02-06_final.stac-item
2016-05-28 12:13:49	ga_s2am_ard_3-2-1_50KKA_2016-05-28_final.stac-item
2016-05-29 11:40:18	ga_s2am_ard_3-2-1_51KVS_2016-05-29_final.stac-item
2016-05-30 11:11:45	ga_s2am_ard_3-2-1_51JYL_2016-05-30_final.stac-item
2016-07-21 11:48:33	ga_s2am_ard_3-2-1_50JLR_2016-07-21_final.stac-item
2016-09-13 11:32:07	ga_s2am_ard_3-2-1_51KWB_2016-09-13_final.stac-item
2017-01-31 11:26:14	ga_s2am_ard_3-2-1_51KVU_2017-01-31_final.stac-item
2017-03-05 11:37:45	ga_s2am_ard_3-2-1_51KUV_2017-03-05_final.stac-item
2017-03-31 12:02:45	ga_s2am_ard_3-2-1_50KLB_2017-03-31_final.stac-item
2017-04-20 12:02:50	ga_s2am_ard_3-2-1_49KGQ_2017-04-20_final.stac-item
2017-10-30 12:13:43	ga_s2am_ard_3-2-1_50KKA_2017-10-30_final.stac-item
2017-12-17 11:26:50	ga_s2am_ard_3-2-1_51KXB_2017-12-17_final.stac-item
2018-02-18 11:45:05	ga_s2am_ard_3-2-1_50HPH_2018-02-18_final.stac-item
2018-05-26 11:31:39	ga_s2am_ard_3-2-1_51JTK_2018-05-26_final.stac-item
2018-06-22 11:20:28	ga_s2am_ard_3-2-1_51KXU_2018-06-22_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50KKU_2018-07-04_final.stac-item
2018-08-07 11:40:42	ga_s2am_ard_3-2-1_51KVA_2018-08-07_final.stac-item
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_51KVA_2018-08-17_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50HLJ_2018-09-09_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_51KTU_2018-10-26_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_51KVB_2018-10-26_final.stac-item
2018-11-09 11:23:38	ga_s2am_ard_3-2-1_51KXR_2018-11-09_final.stac-item
2018-11-22 11:36:50	ga_s2am_ard_3-2-1_51HUC_2018-11-22_final.stac-item
2018-12-15 11:42:55	ga_s2am_ard_3-2-1_51KTU_2018-12-15_final.stac-item
2018-12-15 11:46:14	ga_s2am_ard_3-2-1_50JNL_2018-12-15_final.stac-item
2019-03-19 11:24:09	ga_s2am_ard_3-2-1_51KXP_2019-03-19_final.stac-item
2019-03-31 12:03:44	ga_s2am_ard_3-2-1_50KKB_2019-03-31_final.stac-item
2019-04-08 11:25:54	ga_s2am_ard_3-2-1_51JXG_2019-04-08_final.stac-item
2019-06-27 11:26:45	ga_s2am_ard_3-2-1_51HWD_2019-06-27_final.stac-item
2019-07-07 11:25:43	ga_s2am_ard_3-2-1_51JXH_2019-07-07_final.stac-item
2019-08-29 11:32:16	ga_s2am_ard_3-2-1_51KWB_2019-08-29_final.stac-item
2019-11-10 11:43:08	ga_s2am_ard_3-2-1_51KUU_2019-11-10_final.stac-item
2019-11-27 11:34:37	ga_s2am_ard_3-2-1_50JRT_2019-11-27_final.stac-item
2019-12-04 11:23:12	ga_s2am_ard_3-2-1_51KXT_2019-12-04_final.stac-item
2019-12-07 11:32:44	ga_s2am_ard_3-2-1_51KVV_2019-12-07_final.stac-item
2019-12-11 11:16:04	ga_s2am_ard_3-2-1_51JYF_2019-12-11_final.stac-item
2019-12-20 11:44:28	ga_s2am_ard_3-2-1_50JQT_2019-12-20_final.stac-item
2020-02-01 11:53:17	ga_s2am_ard_3-2-1_50KNC_2020-02-01_final.stac-item
2020-02-11 11:53:10	ga_s2am_ard_3-2-1_50KQC_2020-02-11_final.stac-item
2020-02-28 11:42:37	ga_s2am_ard_3-2-1_51KVV_2020-02-28_final.stac-item
2020-03-19 11:41:29	ga_s2am_ard_3-2-1_51LUE_2020-03-19_final.stac-item
2020-03-26 11:32:55	ga_s2am_ard_3-2-1_51KVU_2020-03-26_final.stac-item
2020-04-01 11:56:51	ga_s2am_ard_3-2-1_50HLJ_2020-04-01_final.stac-item
2020-04-04 12:04:03	ga_s2am_ard_3-2-1_50KKV_2020-04-04_final.stac-item
2020-04-18 11:46:19	ga_s2am_ard_3-2-1_50JPL_2020-04-18_final.stac-item
2020-04-25 11:35:00	ga_s2am_ard_3-2-1_51JVL_2020-04-25_final.stac-item
2020-05-04 12:05:01	ga_s2am_ard_3-2-1_50JKS_2020-05-04_final.stac-item
2020-05-15 11:34:19	ga_s2am_ard_3-2-1_51KVP_2020-05-15_final.stac-item
2020-06-01 11:22:59	ga_s2am_ard_3-2-1_51KZU_2020-06-01_final.stac-item
2020-06-30 11:56:13	ga_s2am_ard_3-2-1_50JMM_2020-06-30_final.stac-item
2020-09-29 11:25:48	ga_s2am_ard_3-2-1_51JWH_2020-09-29_final.stac-item
2020-11-28 11:21:55	ga_s2am_ard_3-2-1_51LZC_2020-11-28_final.stac-item
2020-12-01 11:32:19	ga_s2am_ard_3-2-1_51KVB_2020-12-01_final.stac-item
2020-12-10 12:05:34	ga_s2am_ard_3-2-1_50JLP_2020-12-10_final.stac-item
2020-12-14 11:42:39	ga_s2am_ard_3-2-1_51KVV_2020-12-14_final.stac-item
2020-12-24 11:43:17	ga_s2am_ard_3-2-1_50KRC_2020-12-24_final.stac-item
2021-03-11 11:36:37	ga_s2am_ard_3-2-1_50HPK_2021-03-11_final.stac-item
2021-04-10 11:37:08	ga_s2am_ard_3-2-1_50HPH_2021-04-10_final.stac-item
2021-06-19 11:34:06	ga_s2am_ard_3-2-1_51KXP_2021-06-19_final.stac-item
2021-07-22 11:42:31	ga_s2am_ard_3-2-1_51KVA_2021-07-22_final.stac-item
2021-07-28 12:04:35	ga_s2am_ard_3-2-1_49KGP_2021-07-28_final.stac-item
2021-08-18 11:35:47	ga_s2am_ard_3-2-1_51JUH_2021-08-18_final.stac-item
2021-08-24 11:53:13	ga_s2am_ard_3-2-1_50KRC_2021-08-24_final.stac-item
2021-10-26 12:04:36	ga_s2am_ard_3-2-1_49KGP_2021-10-26_final.stac-item
2021-11-23 11:23:35	ga_s2am_ard_3-2-1_51KZR_2021-11-23_final.stac-item
2021-12-10 11:14:07	ga_s2am_ard_3-2-1_51KZP_2021-12-10_final.stac-item
2021-12-30 11:14:39	ga_s2am_ard_3-2-1_51JZM_2021-12-30_final.stac-item
2022-01-18 11:41:19	ga_s2am_ard_3-2-1_51LUF_2022-01-18_final.stac-item
2022-01-28 11:43:22	ga_s2am_ard_3-2-1_50KQC_2022-01-28_final.stac-item
2022-04-08 11:40:58	ga_s2am_ard_3-2-1_51LWG_2022-04-08_final
2022-04-11 11:52:21	ga_s2am_ard_3-2-1_50KQG_2022-04-11_final
2022-05-07 12:13:44	ga_s2am_ard_3-2-1_50KKB_2022-05-07_final.stac-item
2022-06-14 11:32:57	ga_s2am_ard_3-2-1_51KVV_2022-06-14_final.stac-item
2022-06-23 12:06:04	ga_s2am_ard_3-2-1_50JLN_2022-06-23_final.stac-item
2022-07-14 11:32:59	ga_s2am_ard_3-2-1_51KVV_2022-07-14_final.stac-item
2022-08-19 11:56:49	ga_s2am_ard_3-2-1_50HMK_2022-08-19_final.stac-item
2022-10-29 11:26:26	ga_s2am_ard_3-2-1_51HXE_2022-10-29_final.stac-item
2022-11-30 12:04:39	ga_s2am_ard_3-2-1_50JLT_2022-11-30_final.stac-item
2023-01-16 11:54:15	ga_s2am_ard_3-2-1_50KPU_2023-01-16_final.stac-item
2023-01-27 11:24:20	ga_s2am_ard_3-2-1_51JYN_2023-01-27_final.stac-item
2023-02-02 11:43:10	ga_s2am_ard_3-2-1_51KVT_2023-02-02_final
2023-04-10 11:34:05	ga_s2am_ard_3-2-1_51KXP_2023-04-10_final
2023-04-20 11:35:14	ga_s2am_ard_3-2-1_51JUK_2023-04-20_final
2023-05-03 11:42:42	ga_s2am_ard_3-2-1_51KVV_2023-05-03_final
2023-05-09 12:06:04	ga_s2am_ard_3-2-1_50JLM_2023-05-09_final
2023-05-10 11:32:46	ga_s2am_ard_3-2-1_51KVV_2023-05-10_final
2023-06-05 11:56:00	ga_s2am_ard_3-2-1_50JLN_2023-06-05_final
2023-06-06 11:23:46	ga_s2am_ard_3-2-1_51KXR_2023-06-06_final
2023-06-12 11:46:38	ga_s2am_ard_3-2-1_50HPK_2023-06-12_final
2023-06-16 11:26:04	ga_s2am_ard_3-2-1_51JVG_2023-06-16_final
2023-09-04 11:24:24	ga_s2am_ard_3-2-1_51JZN_2023-09-04_final
2023-09-20 11:42:48	ga_s2am_ard_3-2-1_51KUV_2023-09-20_final
2023-10-03 11:57:08	ga_s2am_ard_3-2-1_50HMH_2023-10-03_final
2023-10-13 11:55:48	ga_s2am_ard_3-2-1_50JLN_2023-10-13_final
2023-11-06 11:32:50	ga_s2am_ard_3-2-1_51KYU_2023-11-06_final
2023-11-23 11:24:00	ga_s2am_ard_3-2-1_51KZP_2023-11-23_final
2024-01-11 11:55:59	ga_s2am_ard_3-2-1_50JNM_2024-01-11_final
2024-01-22 11:26:40	ga_s2am_ard_3-2-1_51HUD_2024-01-22_final
2024-02-24 11:34:12	ga_s2am_ard_3-2-1_51KVP_2024-02-24_final
2024-03-18 11:44:24	ga_s2am_ard_3-2-1_50KPU_2024-03-18_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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