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
2016-05-03 11:23:12	ga_s2am_ard_3-2-1_51HUD_2016-05-03_final.stac-item
2016-09-05 12:14:41	ga_s2am_ard_3-2-1_49JGM_2016-09-05_final.stac-item
2016-09-20 11:22:33	ga_s2am_ard_3-2-1_51JWL_2016-09-20_final.stac-item
2016-10-10 11:22:34	ga_s2am_ard_3-2-1_51JXK_2016-10-10_final.stac-item
2016-11-02 11:26:18	ga_s2am_ard_3-2-1_51KXB_2016-11-02_final.stac-item
2016-12-09 11:21:01	ga_s2am_ard_3-2-1_51KXR_2016-12-09_final.stac-item
2017-01-30 12:02:43	ga_s2am_ard_3-2-1_50KKA_2017-01-30_final.stac-item
2017-12-30 11:37:45	ga_s2am_ard_3-2-1_51LUE_2017-12-30_final.stac-item
2018-02-02 11:18:14	ga_s2am_ard_3-2-1_51LZE_2018-02-02_final.stac-item
2018-03-24 11:24:03	ga_s2am_ard_3-2-1_51JXK_2018-03-24_final.stac-item
2018-04-19 11:40:43	ga_s2am_ard_3-2-1_51KUV_2018-04-19_final.stac-item
2018-05-09 11:34:47	ga_s2am_ard_3-2-1_51KVV_2018-05-09_final.stac-item
2018-06-15 11:26:20	ga_s2am_ard_3-2-1_51KWA_2018-06-15_final.stac-item
2018-06-25 11:32:58	ga_s2am_ard_3-2-1_51KXQ_2018-06-25_final.stac-item
2018-07-22 11:17:00	ga_s2am_ard_3-2-1_51KYA_2018-07-22_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JGL_2018-07-24_final.stac-item
2018-07-27 12:13:22	ga_s2am_ard_3-2-1_49KHR_2018-07-27_final.stac-item
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_50JQP_2018-08-17_final.stac-item
2018-08-17 11:40:30	ga_s2am_ard_3-2-1_51LWC_2018-08-17_final.stac-item
2018-08-24 11:33:07	ga_s2am_ard_3-2-1_51KWS_2018-08-24_final.stac-item
2018-10-26 11:41:08	ga_s2am_ard_3-2-1_51KVB_2018-10-26_final.stac-item
2018-11-02 11:27:40	ga_s2am_ard_3-2-1_51KVB_2018-11-02_final.stac-item
2018-12-19 11:23:53	ga_s2am_ard_3-2-1_51KWQ_2018-12-19_final.stac-item
2018-12-22 11:34:06	ga_s2am_ard_3-2-1_51KVP_2018-12-22_final.stac-item
2019-01-14 11:46:33	ga_s2am_ard_3-2-1_50HNK_2019-01-14_final.stac-item
2019-02-20 11:33:11	ga_s2am_ard_3-2-1_51KVT_2019-02-20_final.stac-item
2019-03-02 11:34:38	ga_s2am_ard_3-2-1_51JVM_2019-03-02_final.stac-item
2019-03-12 11:33:34	ga_s2am_ard_3-2-1_51KXR_2019-03-12_final.stac-item
2019-04-14 11:47:12	ga_s2am_ard_3-2-1_50HMH_2019-04-14_final.stac-item
2019-06-10 11:37:00	ga_s2am_ard_3-2-1_51HUC_2019-06-10_final.stac-item
2019-06-13 11:43:00	ga_s2am_ard_3-2-1_51KVU_2019-06-13_final.stac-item
2019-07-06 11:57:11	ga_s2am_ard_3-2-1_50HMH_2019-07-06_final.stac-item
2019-08-09 11:33:56	ga_s2am_ard_3-2-1_51KXQ_2019-08-09_final.stac-item
2019-10-22 11:13:34	ga_s2am_ard_3-2-1_51KZS_2019-10-22_final.stac-item
2019-12-13 11:53:17	ga_s2am_ard_3-2-1_50KPC_2019-12-13_final.stac-item
2019-12-17 11:33:39	ga_s2am_ard_3-2-1_51KVR_2019-12-17_final.stac-item
2019-12-23 11:57:03	ga_s2am_ard_3-2-1_50HLH_2019-12-23_final.stac-item
2020-01-09 11:45:41	ga_s2am_ard_3-2-1_50JQN_2020-01-09_final.stac-item
2020-01-15 12:04:04	ga_s2am_ard_3-2-1_50KLV_2020-01-15_final.stac-item
2020-04-18 11:43:36	ga_s2am_ard_3-2-1_51KVR_2020-04-18_final.stac-item
2020-05-08 11:41:02	ga_s2am_ard_3-2-1_51LWG_2020-05-08_final
2020-05-31 11:56:32	ga_s2am_ard_3-2-1_50JLL_2020-05-31_final.stac-item
2020-06-14 11:34:55	ga_s2am_ard_3-2-1_51JVM_2020-06-14_final.stac-item
2020-07-23 12:05:43	ga_s2am_ard_3-2-1_50JLP_2020-07-23_final.stac-item
2020-10-09 11:23:49	ga_s2am_ard_3-2-1_51KXR_2020-10-09_final.stac-item
2020-11-20 12:03:29	ga_s2am_ard_3-2-1_50KLC_2020-11-20_final.stac-item
2020-11-28 11:26:59	ga_s2am_ard_3-2-1_51HVC_2020-11-28_final.stac-item
2021-01-20 11:36:39	ga_s2am_ard_3-2-1_50HPK_2021-01-20_final.stac-item
2021-02-02 11:46:12	ga_s2am_ard_3-2-1_50JMM_2021-02-02_final.stac-item
2021-03-04 11:43:43	ga_s2am_ard_3-2-1_51KUR_2021-03-04_final.stac-item
2021-03-11 11:31:59	ga_s2am_ard_3-2-1_51KZB_2021-03-11_final.stac-item
2021-04-04 11:15:09	ga_s2am_ard_3-2-1_52JDP_2021-04-04_final.stac-item
2021-04-07 11:26:34	ga_s2am_ard_3-2-1_51HWD_2021-04-07_final.stac-item
2021-04-10 11:33:51	ga_s2am_ard_3-2-1_51KWQ_2021-04-10_final.stac-item
2021-05-10 11:34:10	ga_s2am_ard_3-2-1_51KWP_2021-05-10_final.stac-item
2021-07-03 11:13:56	ga_s2am_ard_3-2-1_51KZQ_2021-07-03_final.stac-item
2021-07-19 11:35:15	ga_s2am_ard_3-2-1_51JVK_2021-07-19_final.stac-item
2021-08-17 12:06:07	ga_s2am_ard_3-2-1_50JLM_2021-08-17_final.stac-item
2021-09-10 11:42:09	ga_s2am_ard_3-2-1_51KWB_2021-09-10_final.stac-item
2021-09-10 11:42:42	ga_s2am_ard_3-2-1_51KVV_2021-09-10_final.stac-item
2021-09-24 11:22:45	ga_s2am_ard_3-2-1_51KYV_2021-09-24_final.stac-item
2021-10-06 12:04:30	ga_s2am_ard_3-2-1_50KLU_2021-10-06_final.stac-item
2021-10-07 11:36:51	ga_s2am_ard_3-2-1_51HTD_2021-10-07_final.stac-item
2021-12-02 11:57:05	ga_s2am_ard_3-2-1_50HMH_2021-12-02_final.stac-item
2022-01-08 11:43:30	ga_s2am_ard_3-2-1_51KUS_2022-01-08_final.stac-item
2022-02-11 11:23:42	ga_s2am_ard_3-2-1_51KXR_2022-02-11_final.stac-item
2022-02-11 11:24:07	ga_s2am_ard_3-2-1_51KYP_2022-02-11_final.stac-item
2022-02-11 11:25:12	ga_s2am_ard_3-2-1_51JWK_2022-02-11_final.stac-item
2022-02-17 11:43:05	ga_s2am_ard_3-2-1_50KRD_2022-02-17_final.stac-item
2022-02-27 11:43:07	ga_s2am_ard_3-2-1_50KRD_2022-02-27_final.stac-item
2022-03-23 11:22:30	ga_s2am_ard_3-2-1_51KYA_2022-03-23_final.stac-item
2022-03-28 12:13:57	ga_s2am_ard_3-2-1_50KKA_2022-03-28_final.stac-item
2022-05-04 12:03:49	ga_s2am_ard_3-2-1_50KKB_2022-05-04_final.stac-item
2022-05-12 11:22:59	ga_s2am_ard_3-2-1_51KYU_2022-05-12_final.stac-item
2022-05-15 11:34:07	ga_s2am_ard_3-2-1_51KUQ_2022-05-15_final.stac-item
2022-06-17 11:43:11	ga_s2am_ard_3-2-1_51KUU_2022-06-17_final.stac-item
2022-06-17 11:44:09	ga_s2am_ard_3-2-1_51KUQ_2022-06-17_final.stac-item
2022-06-24 11:33:03	ga_s2am_ard_3-2-1_51KYU_2022-06-24_final.stac-item
2022-07-30 11:52:29	ga_s2am_ard_3-2-1_50KQG_2022-07-30_final
2022-09-09 11:25:58	ga_s2am_ard_3-2-1_51JVH_2022-09-09_final.stac-item
2022-11-18 11:26:34	ga_s2am_ard_3-2-1_51HUE_2022-11-18_final.stac-item
2023-02-19 11:33:27	ga_s2am_ard_3-2-1_51KVS_2023-02-19_final
2023-03-27 11:56:02	ga_s2am_ard_3-2-1_50JNM_2023-03-27_final
2023-05-14 11:13:40	ga_s2am_ard_3-2-1_51KZR_2023-05-14_final
2023-05-30 11:34:14	ga_s2am_ard_3-2-1_51KWP_2023-05-30_final
2023-06-06 11:22:59	ga_s2am_ard_3-2-1_51KYU_2023-06-06_final
2023-06-19 11:32:51	ga_s2am_ard_3-2-1_51KVV_2023-06-19_final
2023-06-19 11:35:41	ga_s2am_ard_3-2-1_50JQP_2023-06-19_final
2023-08-08 11:33:46	ga_s2am_ard_3-2-1_51KWR_2023-08-08_final
2023-08-24 11:53:31	ga_s2am_ard_3-2-1_50KNC_2023-08-24_final
2023-09-07 11:31:47	ga_s2am_ard_3-2-1_51LXD_2023-09-07_final
2023-09-07 11:33:50	ga_s2am_ard_3-2-1_51KVR_2023-09-07_final
2023-09-17 11:34:14	ga_s2am_ard_3-2-1_51KWP_2023-09-17_final
2023-11-05 12:05:00	ga_s2am_ard_3-2-1_49JGM_2023-11-05_final
2023-12-23 11:24:01	ga_s2am_ard_3-2-1_51KZP_2023-12-23_final
2024-01-28 11:42:55	ga_s2am_ard_3-2-1_51KUU_2024-01-28_final
2024-02-07 11:43:14	ga_s2am_ard_3-2-1_51KTT_2024-02-07_final
2024-04-09 10:46:14	ga_s2am_ard_3-2-1_52HGK_2024-04-09_final
2024-05-04 11:36:46	ga_s2am_ard_3-2-1_51HUD_2024-05-04_final
2024-05-06 12:14:33	ga_s2am_ard_3-2-1_49KFP_2024-05-06_nrt

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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