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
2019-03-25 11:47:13	ga_s2am_ard_3-2-1_50HLH_2019-03-25_final.stac-item
2019-03-31 12:04:25	ga_s2am_ard_3-2-1_50KLU_2019-03-31_final.stac-item
2019-03-31 12:04:39	ga_s2am_ard_3-2-1_50JLT_2019-03-31_final.stac-item
2019-03-31 12:04:54	ga_s2am_ard_3-2-1_50JLS_2019-03-31_final.stac-item
2019-03-31 12:05:05	ga_s2am_ard_3-2-1_50JLR_2019-03-31_final.stac-item
2019-04-17 11:54:47	ga_s2am_ard_3-2-1_50JLT_2019-04-17_final.stac-item
2019-04-17 11:55:00	ga_s2am_ard_3-2-1_50JLS_2019-04-17_final.stac-item
2019-04-17 11:55:15	ga_s2am_ard_3-2-1_50JLR_2019-04-17_final.stac-item
2019-04-17 11:55:30	ga_s2am_ard_3-2-1_50JLQ_2019-04-17_final.stac-item
2019-04-17 11:55:44	ga_s2am_ard_3-2-1_50JLP_2019-04-17_final.stac-item
2019-04-17 11:55:59	ga_s2am_ard_3-2-1_50JLN_2019-04-17_final.stac-item
2019-04-17 11:56:14	ga_s2am_ard_3-2-1_50JLM_2019-04-17_final.stac-item
2019-04-27 11:54:48	ga_s2am_ard_3-2-1_50JLT_2019-04-27_final.stac-item
2019-04-27 11:55:01	ga_s2am_ard_3-2-1_50JLS_2019-04-27_final.stac-item
2019-04-27 11:55:16	ga_s2am_ard_3-2-1_50JLR_2019-04-27_final.stac-item
2019-04-27 11:55:31	ga_s2am_ard_3-2-1_50JLQ_2019-04-27_final.stac-item
2019-04-27 11:55:45	ga_s2am_ard_3-2-1_50JLP_2019-04-27_final.stac-item
2019-04-27 11:56:00	ga_s2am_ard_3-2-1_50JLN_2019-04-27_final.stac-item
2019-04-27 11:56:14	ga_s2am_ard_3-2-1_50JLM_2019-04-27_final.stac-item
2019-07-19 12:04:59	ga_s2am_ard_3-2-1_50JLS_2019-07-19_final.stac-item
2019-07-19 12:05:13	ga_s2am_ard_3-2-1_50JLR_2019-07-19_final.stac-item
2019-07-23 11:47:15	ga_s2am_ard_3-2-1_50HMH_2019-07-23_final.stac-item
2019-07-23 11:47:19	ga_s2am_ard_3-2-1_50HLH_2019-07-23_final.stac-item
2019-07-29 12:04:58	ga_s2am_ard_3-2-1_50JLS_2019-07-29_final.stac-item
2019-07-29 12:05:13	ga_s2am_ard_3-2-1_50JLR_2019-07-29_final.stac-item
2019-08-02 11:47:00	ga_s2am_ard_3-2-1_50HMJ_2019-08-02_final.stac-item
2019-08-02 11:47:14	ga_s2am_ard_3-2-1_50HMH_2019-08-02_final.stac-item
2019-08-02 11:47:19	ga_s2am_ard_3-2-1_50HLH_2019-08-02_final.stac-item
2019-08-05 11:54:49	ga_s2am_ard_3-2-1_50JLT_2019-08-05_final.stac-item
2019-08-05 11:55:02	ga_s2am_ard_3-2-1_50JLS_2019-08-05_final.stac-item
2019-08-05 11:55:17	ga_s2am_ard_3-2-1_50JLR_2019-08-05_final.stac-item
2019-08-05 11:55:32	ga_s2am_ard_3-2-1_50JLQ_2019-08-05_final.stac-item
2019-08-05 11:55:46	ga_s2am_ard_3-2-1_50JLP_2019-08-05_final.stac-item
2019-08-05 11:56:01	ga_s2am_ard_3-2-1_50JLN_2019-08-05_final.stac-item
2019-08-05 11:56:15	ga_s2am_ard_3-2-1_50JLM_2019-08-05_final.stac-item
2019-08-05 11:56:30	ga_s2am_ard_3-2-1_50JLL_2019-08-05_final.stac-item
2019-08-05 11:56:44	ga_s2am_ard_3-2-1_50HLK_2019-08-05_final.stac-item
2019-08-05 11:56:55	ga_s2am_ard_3-2-1_50HMJ_2019-08-05_final.stac-item
2019-08-05 11:56:59	ga_s2am_ard_3-2-1_50HLJ_2019-08-05_final.stac-item
2019-08-08 12:03:31	ga_s2am_ard_3-2-1_50KLC_2019-08-08_final.stac-item
2019-08-08 12:03:45	ga_s2am_ard_3-2-1_50KLB_2019-08-08_final.stac-item
2019-08-08 12:04:00	ga_s2am_ard_3-2-1_50KLA_2019-08-08_final.stac-item
2019-08-08 12:04:07	ga_s2am_ard_3-2-1_50KLA_2019-08-08_final.stac-item
2019-08-08 12:04:09	ga_s2am_ard_3-2-1_50KLV_2019-08-08_final.stac-item
2019-08-08 12:04:14	ga_s2am_ard_3-2-1_50KLV_2019-08-08_final.stac-item
2019-08-08 12:04:29	ga_s2am_ard_3-2-1_50KLU_2019-08-08_final.stac-item
2019-08-08 12:04:43	ga_s2am_ard_3-2-1_50JLT_2019-08-08_final.stac-item
2019-08-08 12:04:58	ga_s2am_ard_3-2-1_50JLS_2019-08-08_final.stac-item
2019-08-08 12:05:12	ga_s2am_ard_3-2-1_50JLR_2019-08-08_final.stac-item
2019-08-12 11:47:13	ga_s2am_ard_3-2-1_50HMH_2019-08-12_final.stac-item
2019-08-12 11:47:18	ga_s2am_ard_3-2-1_50HLH_2019-08-12_final.stac-item
2019-12-23 11:54:39	ga_s2am_ard_3-2-1_50JLT_2019-12-23_final.stac-item
2019-12-23 11:54:52	ga_s2am_ard_3-2-1_50JLS_2019-12-23_final.stac-item
2019-12-23 11:55:07	ga_s2am_ard_3-2-1_50JLR_2019-12-23_final.stac-item
2019-12-23 11:55:22	ga_s2am_ard_3-2-1_50JLQ_2019-12-23_final.stac-item
2019-12-23 11:55:36	ga_s2am_ard_3-2-1_50JLP_2019-12-23_final.stac-item
2019-12-26 12:03:21	ga_s2am_ard_3-2-1_50KLC_2019-12-26_final.stac-item
2019-12-26 12:03:35	ga_s2am_ard_3-2-1_50KLB_2019-12-26_final.stac-item
2019-12-26 12:03:50	ga_s2am_ard_3-2-1_50KLA_2019-12-26_final.stac-item
2019-12-26 12:04:05	ga_s2am_ard_3-2-1_50KLV_2019-12-26_final.stac-item
2019-12-26 12:04:19	ga_s2am_ard_3-2-1_50KLU_2019-12-26_final.stac-item
2019-12-26 12:04:34	ga_s2am_ard_3-2-1_50JLT_2019-12-26_final.stac-item
2019-12-26 12:04:48	ga_s2am_ard_3-2-1_50JLS_2019-12-26_final.stac-item
2019-12-26 12:05:03	ga_s2am_ard_3-2-1_50JLR_2019-12-26_final.stac-item
2020-01-02 11:54:39	ga_s2am_ard_3-2-1_50JLT_2020-01-02_final.stac-item
2020-01-02 11:54:52	ga_s2am_ard_3-2-1_50JLS_2020-01-02_final.stac-item
2020-01-02 11:55:07	ga_s2am_ard_3-2-1_50JLR_2020-01-02_final.stac-item
2020-01-02 11:55:22	ga_s2am_ard_3-2-1_50JLQ_2020-01-02_final.stac-item
2020-01-02 11:55:36	ga_s2am_ard_3-2-1_50JLP_2020-01-02_final.stac-item
2020-01-02 11:55:51	ga_s2am_ard_3-2-1_50JLN_2020-01-02_final.stac-item
2020-01-02 11:56:05	ga_s2am_ard_3-2-1_50JLM_2020-01-02_final.stac-item
2020-01-02 11:56:20	ga_s2am_ard_3-2-1_50JLL_2020-01-02_final.stac-item
2020-09-25 11:47:19	ga_s2am_ard_3-2-1_50HLH_2020-09-25_final.stac-item
2020-09-28 11:56:31	ga_s2am_ard_3-2-1_50JLL_2020-09-28_final.stac-item
2020-09-28 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-09-28_final.stac-item
2020-09-28 11:56:56	ga_s2am_ard_3-2-1_50HMJ_2020-09-28_final.stac-item
2020-09-28 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-09-28_final.stac-item
2020-09-28 11:57:11	ga_s2am_ard_3-2-1_50HMH_2020-09-28_final.stac-item
2020-09-28 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-09-28_final.stac-item
2020-10-05 11:47:01	ga_s2am_ard_3-2-1_50HMJ_2020-10-05_final.stac-item
2020-10-05 11:47:16	ga_s2am_ard_3-2-1_50HMH_2020-10-05_final.stac-item
2020-10-05 11:47:20	ga_s2am_ard_3-2-1_50HLH_2020-10-05_final.stac-item
2020-10-08 11:54:50	ga_s2am_ard_3-2-1_50JLT_2020-10-08_final.stac-item
2020-10-08 11:55:04	ga_s2am_ard_3-2-1_50JLS_2020-10-08_final.stac-item
2020-10-08 11:55:18	ga_s2am_ard_3-2-1_50JLR_2020-10-08_final.stac-item
2020-10-08 11:55:33	ga_s2am_ard_3-2-1_50JLQ_2020-10-08_final.stac-item
2020-10-08 11:55:48	ga_s2am_ard_3-2-1_50JLP_2020-10-08_final.stac-item
2020-10-08 11:56:02	ga_s2am_ard_3-2-1_50JLN_2020-10-08_final.stac-item
2020-10-08 11:56:17	ga_s2am_ard_3-2-1_50JLM_2020-10-08_final.stac-item
2020-10-08 11:56:31	ga_s2am_ard_3-2-1_50JLL_2020-10-08_final.stac-item
2020-10-08 11:56:46	ga_s2am_ard_3-2-1_50HLK_2020-10-08_final.stac-item
2020-10-08 11:56:57	ga_s2am_ard_3-2-1_50HMJ_2020-10-08_final.stac-item
2020-10-08 11:57:00	ga_s2am_ard_3-2-1_50HLJ_2020-10-08_final.stac-item
2020-10-08 11:57:12	ga_s2am_ard_3-2-1_50HMH_2020-10-08_final.stac-item
2020-10-08 11:57:15	ga_s2am_ard_3-2-1_50HLH_2020-10-08_final.stac-item
2020-10-11 12:04:45	ga_s2am_ard_3-2-1_50JLT_2020-10-11_final.stac-item
2020-10-11 12:04:59	ga_s2am_ard_3-2-1_50JLS_2020-10-11_final.stac-item
2020-10-11 12:05:14	ga_s2am_ard_3-2-1_50JLR_2020-10-11_final.stac-item
2022-04-04 12:04:55	ga_s2am_ard_3-2-1_50JLS_2022-04-04_final.stac-item
2022-04-04 12:05:05	ga_s2am_ard_3-2-1_50JLR_2022-04-04_final.stac-item

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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