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
2020-04-20 10:45:42	ga_s2am_ard_3-2-1_53JNF_2020-04-20_final.stac-item
2020-04-27 10:35:54	ga_s2am_ard_3-2-1_53JNF_2020-04-27_final.stac-item
2020-05-07 10:35:56	ga_s2am_ard_3-2-1_53JNF_2020-05-07_final.stac-item
2020-05-10 10:45:46	ga_s2am_ard_3-2-1_53JNF_2020-05-10_final.stac-item
2020-05-27 10:35:58	ga_s2am_ard_3-2-1_53JNF_2020-05-27_final.stac-item
2020-05-30 10:45:48	ga_s2am_ard_3-2-1_53JNF_2020-05-30_final.stac-item
2020-06-29 10:45:47	ga_s2am_ard_3-2-1_53JNF_2020-06-29_final.stac-item
2020-07-06 10:35:57	ga_s2am_ard_3-2-1_53JNF_2020-07-06_final.stac-item
2020-07-16 10:35:57	ga_s2am_ard_3-2-1_53JNF_2020-07-16_final.stac-item
2020-07-26 10:35:58	ga_s2am_ard_3-2-1_53JNF_2020-07-26_final.stac-item
2020-08-08 10:45:48	ga_s2am_ard_3-2-1_53JNF_2020-08-08_final.stac-item
2020-08-18 10:45:47	ga_s2am_ard_3-2-1_53JNF_2020-08-18_final.stac-item
2020-08-28 10:45:47	ga_s2am_ard_3-2-1_53JNF_2020-08-28_final.stac-item
2020-09-04 10:35:57	ga_s2am_ard_3-2-1_53JNF_2020-09-04_final.stac-item
2020-09-14 10:35:56	ga_s2am_ard_3-2-1_53JNF_2020-09-14_final.stac-item
2020-09-17 10:45:46	ga_s2am_ard_3-2-1_53JNF_2020-09-17_final.stac-item
2020-10-07 10:45:47	ga_s2am_ard_3-2-1_53JNF_2020-10-07_final.stac-item
2020-10-14 10:35:58	ga_s2am_ard_3-2-1_53JNF_2020-10-14_final.stac-item
2020-10-27 10:45:47	ga_s2am_ard_3-2-1_53JNF_2020-10-27_final.stac-item
2020-11-13 10:35:56	ga_s2am_ard_3-2-1_53JNF_2020-11-13_final.stac-item
2020-11-23 10:35:54	ga_s2am_ard_3-2-1_53JNF_2020-11-23_final.stac-item
2020-12-03 10:35:51	ga_s2am_ard_3-2-1_53JNF_2020-12-03_final.stac-item
2020-12-13 10:35:49	ga_s2am_ard_3-2-1_53JNF_2020-12-13_final.stac-item
2020-12-26 10:45:41	ga_s2am_ard_3-2-1_53JNF_2020-12-26_final.stac-item
2021-02-04 10:45:41	ga_s2am_ard_3-2-1_53JNF_2021-02-04_final.stac-item
2021-06-24 10:45:43	ga_s2am_ard_3-2-1_53JNF_2021-06-24_final.stac-item
2021-07-24 10:45:45	ga_s2am_ard_3-2-1_53JNF_2021-07-24_final.stac-item
2021-10-12 10:45:47	ga_s2am_ard_3-2-1_53JNF_2021-10-12_final.stac-item
2022-02-09 10:45:41	ga_s2am_ard_3-2-1_53JNF_2022-02-09_final.stac-item
2022-03-08 10:35:56	ga_s2am_ard_3-2-1_53JNF_2022-03-08_final.stac-item
2022-03-21 10:45:45	ga_s2am_ard_3-2-1_53JNF_2022-03-21_final.stac-item
2022-03-28 10:35:55	ga_s2am_ard_3-2-1_53JNF_2022-03-28_final.stac-item
2022-03-31 10:45:44	ga_s2am_ard_3-2-1_53JNF_2022-03-31_final.stac-item
2022-04-07 10:35:53	ga_s2am_ard_3-2-1_53JNF_2022-04-07_final.stac-item
2022-04-10 10:45:43	ga_s2am_ard_3-2-1_53JNF_2022-04-10_final.stac-item
2022-04-17 10:35:56	ga_s2am_ard_3-2-1_53JNF_2022-04-17_final.stac-item
2022-04-20 10:45:46	ga_s2am_ard_3-2-1_53JNF_2022-04-20_final.stac-item
2022-04-27 10:35:57	ga_s2am_ard_3-2-1_53JNF_2022-04-27_final.stac-item
2022-04-30 10:45:47	ga_s2am_ard_3-2-1_53JNF_2022-04-30_final.stac-item
2022-05-07 10:35:57	ga_s2am_ard_3-2-1_53JNF_2022-05-07_final.stac-item
2022-05-10 10:45:46	ga_s2am_ard_3-2-1_53JNF_2022-05-10_final.stac-item
2022-05-17 10:35:57	ga_s2am_ard_3-2-1_53JNF_2022-05-17_final.stac-item
2022-05-20 10:45:48	ga_s2am_ard_3-2-1_53JNF_2022-05-20_final.stac-item
2022-05-27 10:36:00	ga_s2am_ard_3-2-1_53JNF_2022-05-27_final.stac-item
2022-05-30 10:45:49	ga_s2am_ard_3-2-1_53JNF_2022-05-30_final.stac-item
2022-06-06 10:36:00	ga_s2am_ard_3-2-1_53JNF_2022-06-06_final.stac-item
2022-06-09 10:45:50	ga_s2am_ard_3-2-1_53JNF_2022-06-09_final.stac-item
2022-06-16 10:36:03	ga_s2am_ard_3-2-1_53JNF_2022-06-16_final.stac-item
2022-06-19 10:45:53	ga_s2am_ard_3-2-1_53JNF_2022-06-19_final.stac-item
2022-06-26 10:36:05	ga_s2am_ard_3-2-1_53JNF_2022-06-26_final.stac-item
2022-06-29 10:45:54	ga_s2am_ard_3-2-1_53JNF_2022-06-29_final.stac-item
2022-07-06 10:36:05	ga_s2am_ard_3-2-1_53JNF_2022-07-06_final.stac-item
2022-07-09 10:45:54	ga_s2am_ard_3-2-1_53JNF_2022-07-09_final.stac-item
2022-07-16 10:36:04	ga_s2am_ard_3-2-1_53JNF_2022-07-16_final.stac-item
2022-07-19 10:45:53	ga_s2am_ard_3-2-1_53JNF_2022-07-19_final.stac-item
2022-07-26 10:36:02	ga_s2am_ard_3-2-1_53JNF_2022-07-26_final.stac-item
2022-07-29 10:45:51	ga_s2am_ard_3-2-1_53JNF_2022-07-29_final.stac-item
2022-08-05 10:36:03	ga_s2am_ard_3-2-1_53JNF_2022-08-05_final.stac-item
2022-08-05 10:36:11	ga_s2am_ard_3-2-1_53JNF_2022-08-05_final.stac-item
2022-08-08 10:45:53	ga_s2am_ard_3-2-1_53JNF_2022-08-08_final.stac-item
2022-08-15 10:36:05	ga_s2am_ard_3-2-1_53JNF_2022-08-15_final.stac-item
2022-08-18 10:45:54	ga_s2am_ard_3-2-1_53JNF_2022-08-18_final.stac-item
2022-08-25 10:36:05	ga_s2am_ard_3-2-1_53JNF_2022-08-25_final.stac-item
2022-09-04 10:36:04	ga_s2am_ard_3-2-1_53JNF_2022-09-04_final.stac-item
2022-09-07 10:45:53	ga_s2am_ard_3-2-1_53JNF_2022-09-07_final.stac-item
2022-09-14 10:36:02	ga_s2am_ard_3-2-1_53JNF_2022-09-14_final.stac-item
2022-09-17 10:45:51	ga_s2am_ard_3-2-1_53JNF_2022-09-17_final.stac-item
2022-09-24 10:35:59	ga_s2am_ard_3-2-1_53JNF_2022-09-24_final.stac-item
2022-09-27 10:45:49	ga_s2am_ard_3-2-1_53JNF_2022-09-27_final.stac-item
2022-10-04 10:35:59	ga_s2am_ard_3-2-1_53JNF_2022-10-04_final.stac-item
2022-10-07 10:45:48	ga_s2am_ard_3-2-1_53JNF_2022-10-07_final.stac-item
2022-10-14 10:35:57	ga_s2am_ard_3-2-1_53JNF_2022-10-14_final.stac-item
2022-10-17 10:45:45	ga_s2am_ard_3-2-1_53JNF_2022-10-17_final.stac-item
2022-10-24 10:35:55	ga_s2am_ard_3-2-1_53JNF_2022-10-24_final.stac-item
2022-10-27 10:45:45	ga_s2am_ard_3-2-1_53JNF_2022-10-27_final.stac-item
2022-11-03 10:35:56	ga_s2am_ard_3-2-1_53JNF_2022-11-03_final.stac-item
2022-11-06 10:45:46	ga_s2am_ard_3-2-1_53JNF_2022-11-06_final.stac-item
2022-11-13 10:35:55	ga_s2am_ard_3-2-1_53JNF_2022-11-13_final.stac-item
2022-11-16 10:45:44	ga_s2am_ard_3-2-1_53JNF_2022-11-16_final.stac-item
2022-11-23 10:35:52	ga_s2am_ard_3-2-1_53JNF_2022-11-23_final.stac-item
2022-11-26 10:45:41	ga_s2am_ard_3-2-1_53JNF_2022-11-26_final.stac-item
2022-12-03 10:35:52	ga_s2am_ard_3-2-1_53JNF_2022-12-03_final.stac-item
2022-12-06 10:45:42	ga_s2am_ard_3-2-1_53JNF_2022-12-06_final.stac-item
2022-12-13 10:35:52	ga_s2am_ard_3-2-1_53JNF_2022-12-13_final.stac-item
2022-12-16 10:45:41	ga_s2am_ard_3-2-1_53JNF_2022-12-16_final.stac-item
2022-12-23 10:35:50	ga_s2am_ard_3-2-1_53JNF_2022-12-23_final.stac-item
2022-12-26 10:45:40	ga_s2am_ard_3-2-1_53JNF_2022-12-26_final.stac-item
2023-01-02 10:35:51	ga_s2am_ard_3-2-1_53JNF_2023-01-02_final.stac-item
2023-01-05 10:45:41	ga_s2am_ard_3-2-1_53JNF_2023-01-05_final.stac-item
2023-01-12 10:35:50	ga_s2am_ard_3-2-1_53JNF_2023-01-12_final.stac-item
2023-01-15 10:45:39	ga_s2am_ard_3-2-1_53JNF_2023-01-15_final.stac-item
2023-01-22 10:35:48	ga_s2am_ard_3-2-1_53JNF_2023-01-22_final.stac-item
2023-01-25 10:45:39	ga_s2am_ard_3-2-1_53JNF_2023-01-25_final.stac-item
2023-02-01 10:35:51	ga_s2am_ard_3-2-1_53JNF_2023-02-01_final.stac-item
2023-02-04 10:45:40	ga_s2am_ard_3-2-1_53JNF_2023-02-04_final.stac-item
2023-02-11 10:35:51	ga_s2am_ard_3-2-1_53JNF_2023-02-11_final
2023-02-21 10:35:50	ga_s2am_ard_3-2-1_53JNF_2023-02-21_final
2023-08-03 10:45:47	ga_s2am_ard_3-2-1_53JNF_2023-08-03_final
2023-08-13 10:45:47	ga_s2am_ard_3-2-1_53JNF_2023-08-13_final
2023-08-20 10:35:58	ga_s2am_ard_3-2-1_53JNF_2023-08-20_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

All years