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
2015-10-21 12:14:27	ga_s2am_ard_3-2-1_49KGP_2015-10-21_final.stac-item
2015-11-27 12:03:46	ga_s2am_ard_3-2-1_49KHR_2015-11-27_final.stac-item
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_49JGM_2015-11-27_final.stac-item
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_50JLT_2015-11-27_final.stac-item
2015-11-27 12:04:40	ga_s2am_ard_3-2-1_49JGN_2015-11-27_final.stac-item
2015-11-30 12:04:46	ga_s2am_ard_3-2-1_49KGP_2015-11-30_final.stac-item
2015-11-30 12:14:12	ga_s2am_ard_3-2-1_49KGQ_2015-11-30_final.stac-item
2015-12-07 12:04:41	ga_s2am_ard_3-2-1_50JLQ_2015-12-07_final.stac-item
2022-08-19 11:55:37	ga_s2am_ard_3-2-1_50JMQ_2022-08-19_final.stac-item
2022-08-22 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-08-22_final.stac-item
2022-08-29 11:55:40	ga_s2am_ard_3-2-1_50JLQ_2022-08-29_final.stac-item
2022-09-01 12:04:11	ga_s2am_ard_3-2-1_49KHR_2022-09-01_final.stac-item
2022-09-01 12:04:30	ga_s2am_ard_3-2-1_49KGQ_2022-09-01_final.stac-item
2022-09-01 12:05:01	ga_s2am_ard_3-2-1_50JMS_2022-09-01_final.stac-item
2022-09-01 12:05:35	ga_s2am_ard_3-2-1_50JLQ_2022-09-01_final.stac-item
2022-09-04 12:14:06	ga_s2am_ard_3-2-1_49KHR_2022-09-04_final.stac-item
2022-09-04 12:14:25	ga_s2am_ard_3-2-1_49KGQ_2022-09-04_final.stac-item
2022-09-04 12:14:39	ga_s2am_ard_3-2-1_49KGP_2022-09-04_final.stac-item
2022-09-04 12:14:57	ga_s2am_ard_3-2-1_49JFN_2022-09-04_final.stac-item
2022-09-08 11:55:06	ga_s2am_ard_3-2-1_50JMS_2022-09-08_final.stac-item
2022-09-08 11:55:39	ga_s2am_ard_3-2-1_50JLQ_2022-09-08_final.stac-item
2022-09-11 12:04:57	ga_s2am_ard_3-2-1_49JGN_2022-09-11_final.stac-item
2022-09-11 12:05:33	ga_s2am_ard_3-2-1_50JLQ_2022-09-11_final.stac-item
2022-09-14 12:14:08	ga_s2am_ard_3-2-1_49KGR_2022-09-14_final.stac-item
2022-09-14 12:14:23	ga_s2am_ard_3-2-1_49KGQ_2022-09-14_final.stac-item
2022-09-14 12:14:37	ga_s2am_ard_3-2-1_49KGP_2022-09-14_final.stac-item
2022-09-14 12:14:51	ga_s2am_ard_3-2-1_49JGN_2022-09-14_final.stac-item
2022-09-18 11:55:03	ga_s2am_ard_3-2-1_50JMS_2022-09-18_final.stac-item
2022-09-18 11:55:33	ga_s2am_ard_3-2-1_50JMQ_2022-09-18_final.stac-item
2022-09-18 11:55:36	ga_s2am_ard_3-2-1_50JLQ_2022-09-18_final.stac-item
2022-09-21 12:04:07	ga_s2am_ard_3-2-1_49KHR_2022-09-21_final.stac-item
2022-09-21 12:04:42	ga_s2am_ard_3-2-1_49KGP_2022-09-21_final.stac-item
2022-09-21 12:04:53	ga_s2am_ard_3-2-1_49JGN_2022-09-21_final.stac-item
2022-09-24 12:14:48	ga_s2am_ard_3-2-1_49JGN_2022-09-24_final.stac-item
2022-09-25 11:45:28	ga_s2am_ard_3-2-1_50JPQ_2022-09-25_final.stac-item
2022-10-01 12:04:06	ga_s2am_ard_3-2-1_49KHR_2022-10-01_final.stac-item
2022-10-01 12:04:36	ga_s2am_ard_3-2-1_49KGP_2022-10-01_final.stac-item
2022-10-01 12:04:40	ga_s2am_ard_3-2-1_50JLT_2022-10-01_final.stac-item
2022-10-01 12:04:42	ga_s2am_ard_3-2-1_49KGP_2022-10-01_final.stac-item
2022-10-01 12:04:53	ga_s2am_ard_3-2-1_49JGN_2022-10-01_final.stac-item
2022-10-01 12:04:56	ga_s2am_ard_3-2-1_50JMS_2022-10-01_final.stac-item
2022-10-01 12:05:04	ga_s2am_ard_3-2-1_49JHM_2022-10-01_final.stac-item
2022-10-01 12:05:08	ga_s2am_ard_3-2-1_49JGM_2022-10-01_final.stac-item
2022-10-01 12:05:36	ga_s2am_ard_3-2-1_49JGK_2022-10-01_final.stac-item
2022-10-01 12:05:51	ga_s2am_ard_3-2-1_49JGJ_2022-10-01_final.stac-item
2022-10-02 11:36:34	ga_s2am_ard_3-2-1_50JPL_2022-10-02_final.stac-item
2022-10-02 11:37:14	ga_s2am_ard_3-2-1_50HPH_2022-10-02_final.stac-item
2022-10-04 12:14:02	ga_s2am_ard_3-2-1_49KHR_2022-10-04_final.stac-item
2022-10-04 12:14:28	ga_s2am_ard_3-2-1_49KHP_2022-10-04_final.stac-item
2022-10-04 12:14:34	ga_s2am_ard_3-2-1_49KGP_2022-10-04_final.stac-item
2022-10-04 12:15:03	ga_s2am_ard_3-2-1_49JGM_2022-10-04_final.stac-item
2022-10-05 11:46:26	ga_s2am_ard_3-2-1_50JPL_2022-10-05_final.stac-item
2022-10-05 11:46:48	ga_s2am_ard_3-2-1_50HMK_2022-10-05_final.stac-item
2022-10-05 11:47:00	ga_s2am_ard_3-2-1_50HQH_2022-10-05_final.stac-item
2022-10-05 11:47:09	ga_s2am_ard_3-2-1_50HPH_2022-10-05_final.stac-item
2022-10-08 11:55:01	ga_s2am_ard_3-2-1_50JMS_2022-10-08_final.stac-item
2022-10-08 11:55:30	ga_s2am_ard_3-2-1_50JMQ_2022-10-08_final.stac-item
2022-10-08 11:55:34	ga_s2am_ard_3-2-1_50JLQ_2022-10-08_final.stac-item
2022-10-08 11:56:11	ga_s2am_ard_3-2-1_50JNM_2022-10-08_final.stac-item
2022-10-08 11:56:17	ga_s2am_ard_3-2-1_50JLM_2022-10-08_final.stac-item
2022-10-08 11:57:01	ga_s2am_ard_3-2-1_50HLJ_2022-10-08_final.stac-item
2022-10-11 12:04:05	ga_s2am_ard_3-2-1_49KHR_2022-10-11_final.stac-item
2022-10-11 12:04:34	ga_s2am_ard_3-2-1_49KGP_2022-10-11_final.stac-item
2022-10-11 12:04:38	ga_s2am_ard_3-2-1_50JLT_2022-10-11_final.stac-item
2022-10-11 12:04:39	ga_s2am_ard_3-2-1_49KHP_2022-10-11_final.stac-item
2022-10-11 12:04:51	ga_s2am_ard_3-2-1_49JGN_2022-10-11_final.stac-item
2022-10-11 12:05:02	ga_s2am_ard_3-2-1_49JHM_2022-10-11_final.stac-item
2022-10-11 12:05:06	ga_s2am_ard_3-2-1_49JGM_2022-10-11_final.stac-item
2022-10-11 12:05:17	ga_s2am_ard_3-2-1_50JKR_2022-10-11_final.stac-item
2022-10-11 12:05:28	ga_s2am_ard_3-2-1_50JLQ_2022-10-11_final.stac-item
2022-10-11 12:05:35	ga_s2am_ard_3-2-1_49JGK_2022-10-11_final.stac-item
2022-10-11 12:05:49	ga_s2am_ard_3-2-1_49JGJ_2022-10-11_final.stac-item
2022-10-12 11:37:12	ga_s2am_ard_3-2-1_50HPH_2022-10-12_final.stac-item
2022-10-14 12:14:03	ga_s2am_ard_3-2-1_49KGR_2022-10-14_final.stac-item
2022-10-14 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-10-14_final.stac-item
2022-10-14 12:14:19	ga_s2am_ard_3-2-1_49KGQ_2022-10-14_final.stac-item
2022-10-14 12:14:26	ga_s2am_ard_3-2-1_49KHP_2022-10-14_final.stac-item
2022-10-14 12:15:04	ga_s2am_ard_3-2-1_49JFM_2022-10-14_final.stac-item
2022-10-14 12:15:24	ga_s2am_ard_3-2-1_49JGK_2022-10-14_final.stac-item
2022-10-15 11:46:45	ga_s2am_ard_3-2-1_50HMK_2022-10-15_final.stac-item
2022-10-15 11:47:06	ga_s2am_ard_3-2-1_50HPH_2022-10-15_final.stac-item
2022-10-18 11:54:47	ga_s2am_ard_3-2-1_50JLT_2022-10-18_final.stac-item
2022-10-18 11:55:41	ga_s2am_ard_3-2-1_50JMP_2022-10-18_final.stac-item
2022-10-21 12:04:01	ga_s2am_ard_3-2-1_49KHR_2022-10-21_final.stac-item
2022-10-21 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2022-10-21_final.stac-item
2022-10-21 12:04:29	ga_s2am_ard_3-2-1_49KHP_2022-10-21_final.stac-item
2022-10-21 12:04:41	ga_s2am_ard_3-2-1_50JLT_2022-10-21_final.stac-item
2022-10-21 12:04:50	ga_s2am_ard_3-2-1_50JMS_2022-10-21_final.stac-item
2022-10-21 12:04:55	ga_s2am_ard_3-2-1_49JHM_2022-10-21_final.stac-item
2022-10-21 12:05:02	ga_s2am_ard_3-2-1_49JHM_2022-10-21_final.stac-item
2022-10-21 12:05:04	ga_s2am_ard_3-2-1_49JGM_2022-10-21_final.stac-item
2022-10-21 12:05:45	ga_s2am_ard_3-2-1_49JGJ_2022-10-21_final.stac-item
2022-10-22 11:37:05	ga_s2am_ard_3-2-1_50HQH_2022-10-22_final.stac-item
2022-10-24 12:13:57	ga_s2am_ard_3-2-1_49KHR_2022-10-24_final.stac-item
2022-10-24 12:14:15	ga_s2am_ard_3-2-1_49KGQ_2022-10-24_final.stac-item
2022-10-24 12:14:29	ga_s2am_ard_3-2-1_49KGP_2022-10-24_final.stac-item
2022-10-24 12:14:44	ga_s2am_ard_3-2-1_49JGN_2022-10-24_final.stac-item
2022-10-24 12:15:02	ga_s2am_ard_3-2-1_49JFM_2022-10-24_final.stac-item
2022-10-25 11:46:22	ga_s2am_ard_3-2-1_50JPL_2022-10-25_final.stac-item
2022-10-25 11:47:05	ga_s2am_ard_3-2-1_50HPH_2022-10-25_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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