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
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49KGP_2018-07-04_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49KHR_2018-07-04_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50KKV_2018-07-04_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-07-04_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2018-07-07_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_50KKA_2018-07-07_final.stac-item
2018-07-07 12:13:22	ga_s2am_ard_3-2-1_49JHN_2018-07-07_final.stac-item
2018-07-13 10:47:26	ga_s2am_ard_3-2-1_52JFN_2018-07-13_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKA_2018-07-14_final.stac-item
2018-07-14 12:02:51	ga_s2am_ard_3-2-1_50KKV_2018-07-14_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49KGQ_2018-07-17_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_50KKA_2018-07-17_final.stac-item
2018-07-17 12:13:22	ga_s2am_ard_3-2-1_49JFN_2018-07-17_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49KGQ_2018-07-24_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49KHR_2018-07-24_final.stac-item
2018-07-24 12:02:50	ga_s2am_ard_3-2-1_49JHN_2018-07-24_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49KGQ_2018-07-27_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_50KKA_2018-07-27_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_50KKV_2018-07-27_final.stac-item
2018-07-27 12:13:47	ga_s2am_ard_3-2-1_49JFN_2018-07-27_final.stac-item
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_51JYJ_2018-08-01_final.stac-item
2018-08-01 11:23:55	ga_s2am_ard_3-2-1_51JYK_2018-08-01_final.stac-item
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52JDQ_2018-08-05_final.stac-item
2018-08-08 11:13:24	ga_s2am_ard_3-2-1_51JXJ_2018-08-08_final.stac-item
2018-08-11 11:19:45	ga_s2am_ard_3-2-1_51JYJ_2018-08-11_final.stac-item
2018-08-11 11:19:45	ga_s2am_ard_3-2-1_51JYK_2018-08-11_final.stac-item
2018-08-18 11:12:58	ga_s2am_ard_3-2-1_51JYJ_2018-08-18_final.stac-item
2018-08-18 11:12:58	ga_s2am_ard_3-2-1_51JYK_2018-08-18_final.stac-item
2018-08-18 11:12:58	ga_s2am_ard_3-2-1_52JDQ_2018-08-18_final.stac-item
2018-08-22 10:47:24	ga_s2am_ard_3-2-1_52JEN_2018-08-22_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_51JYJ_2018-08-28_final.stac-item
2018-08-28 11:10:58	ga_s2am_ard_3-2-1_52JCS_2018-08-28_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49KGQ_2018-09-02_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JLQ_2018-09-02_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50JMR_2018-09-02_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_50KKA_2018-09-02_final.stac-item
2018-09-02 12:02:47	ga_s2am_ard_3-2-1_49JHN_2018-09-02_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51JUJ_2018-09-03_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51JVH_2018-09-03_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51JVL_2018-09-03_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51JWK_2018-09-03_final.stac-item
2018-09-03 11:32:51	ga_s2am_ard_3-2-1_51JWL_2018-09-03_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KGQ_2018-09-05_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49KHR_2018-09-05_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_50KKV_2018-09-05_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JFN_2018-09-05_final.stac-item
2018-09-05 12:13:19	ga_s2am_ard_3-2-1_49JHN_2018-09-05_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JNP_2018-09-06_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JPR_2018-09-06_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JQQ_2018-09-06_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JQR_2018-09-06_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_50JQS_2018-09-06_final.stac-item
2018-09-06 11:40:28	ga_s2am_ard_3-2-1_51JTK_2018-09-06_final.stac-item
2018-09-07 11:13:22	ga_s2am_ard_3-2-1_51JXH_2018-09-07_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JLQ_2018-09-09_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JMR_2018-09-09_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JNP_2018-09-09_final.stac-item
2018-09-09 11:46:20	ga_s2am_ard_3-2-1_50JPR_2018-09-09_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51JVH_2018-09-10_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51JVL_2018-09-10_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51JWK_2018-09-10_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51JWL_2018-09-10_final.stac-item
2018-09-10 11:21:45	ga_s2am_ard_3-2-1_51JXJ_2018-09-10_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49KGQ_2018-09-12_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JLQ_2018-09-12_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50JMR_2018-09-12_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50KKA_2018-09-12_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_50KKV_2018-09-12_final.stac-item
2018-09-12 12:02:46	ga_s2am_ard_3-2-1_49JHN_2018-09-12_final.stac-item
2018-09-13 11:33:05	ga_s2am_ard_3-2-1_51JUK_2018-09-13_final.stac-item
2018-09-13 11:33:05	ga_s2am_ard_3-2-1_51JVM_2018-09-13_final.stac-item
2018-09-15 12:13:40	ga_s2am_ard_3-2-1_49KHR_2018-09-15_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JLQ_2018-09-19_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JMR_2018-09-19_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JNP_2018-09-19_final.stac-item
2018-09-19 11:52:05	ga_s2am_ard_3-2-1_50JPR_2018-09-19_final.stac-item
2018-09-20 11:24:00	ga_s2am_ard_3-2-1_51JXH_2018-09-20_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51JTK_2018-09-23_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51JUK_2018-09-23_final.stac-item
2018-09-23 11:33:04	ga_s2am_ard_3-2-1_51JVM_2018-09-23_final.stac-item
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KGQ_2018-09-25_final.stac-item
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KHR_2018-09-25_final.stac-item
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_50KKA_2018-09-25_final.stac-item
2018-09-25 12:13:17	ga_s2am_ard_3-2-1_49KHQ_2018-09-25_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KGP_2018-09-25_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49KGQ_2018-09-25_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_50KKA_2018-09-25_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_50KKV_2018-09-25_final.stac-item
2018-09-25 12:13:53	ga_s2am_ard_3-2-1_49JHN_2018-09-25_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JNP_2018-09-26_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JPR_2018-09-26_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JQQ_2018-09-26_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JQR_2018-09-26_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_50JQS_2018-09-26_final.stac-item
2018-09-26 11:42:55	ga_s2am_ard_3-2-1_51JTK_2018-09-26_final.stac-item
2018-09-27 11:12:40	ga_s2am_ard_3-2-1_51JXH_2018-09-27_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JLQ_2018-09-29_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JMR_2018-09-29_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JNP_2018-09-29_final.stac-item
2018-09-29 11:53:46	ga_s2am_ard_3-2-1_50JPR_2018-09-29_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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