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
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HNH_2016-02-19_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HNJ_2016-02-19_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50JNN_2016-02-19_final.stac-item
2016-02-19 11:45:19	ga_s2am_ard_3-2-1_50HNG_2016-02-19_final
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNL_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNM_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNN_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNP_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNQ_2016-03-03_final.stac-item
2016-03-03 11:49:03	ga_s2am_ard_3-2-1_50JNR_2016-03-03_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JNL_2016-04-02_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JNM_2016-04-02_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JNN_2016-04-02_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JNP_2016-04-02_final.stac-item
2016-04-02 11:49:05	ga_s2am_ard_3-2-1_50JNQ_2016-04-02_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNL_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNM_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNN_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNP_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNQ_2016-05-22_final.stac-item
2016-05-22 11:48:35	ga_s2am_ard_3-2-1_50JNR_2016-05-22_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50KNB_2018-07-04_final.stac-item
2018-07-04 12:02:50	ga_s2am_ard_3-2-1_50KNC_2018-07-04_final.stac-item
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50JNN_2018-07-08_final.stac-item
2018-07-08 11:40:21	ga_s2am_ard_3-2-1_50JNP_2018-07-08_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50HNH_2018-07-18_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50HNJ_2018-07-18_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50HNK_2018-07-18_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50JNL_2018-07-18_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50JNM_2018-07-18_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50JNN_2018-07-18_final.stac-item
2018-07-18 11:42:49	ga_s2am_ard_3-2-1_50JNP_2018-07-18_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNL_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNM_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNN_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNP_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNQ_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNR_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNS_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50JNT_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50KNA_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50KNB_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50KNC_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50KNU_2018-07-21_final.stac-item
2018-07-21 11:51:59	ga_s2am_ard_3-2-1_50KNV_2018-07-21_final.stac-item
2019-07-26 11:53:44	ga_s2am_ard_3-2-1_50KNB_2019-07-26_final.stac-item
2019-07-26 11:53:58	ga_s2am_ard_3-2-1_50KNA_2019-07-26_final.stac-item
2019-07-26 11:54:42	ga_s2am_ard_3-2-1_50JNT_2019-07-26_final.stac-item
2019-07-26 11:54:56	ga_s2am_ard_3-2-1_50JNS_2019-07-26_final.stac-item
2019-07-26 11:55:11	ga_s2am_ard_3-2-1_50JNR_2019-07-26_final.stac-item
2019-07-26 11:55:25	ga_s2am_ard_3-2-1_50JNQ_2019-07-26_final.stac-item
2019-07-26 11:55:40	ga_s2am_ard_3-2-1_50JNP_2019-07-26_final.stac-item
2019-07-26 11:55:54	ga_s2am_ard_3-2-1_50JNN_2019-07-26_final.stac-item
2019-07-29 12:03:24	ga_s2am_ard_3-2-1_50KNC_2019-07-29_final.stac-item
2019-07-29 12:03:38	ga_s2am_ard_3-2-1_50KNB_2019-07-29_final.stac-item
2019-08-15 11:53:28	ga_s2am_ard_3-2-1_50KNC_2019-08-15_final.stac-item
2019-08-15 11:53:42	ga_s2am_ard_3-2-1_50KNB_2019-08-15_final.stac-item
2019-08-15 11:53:57	ga_s2am_ard_3-2-1_50KNA_2019-08-15_final.stac-item
2019-08-15 11:54:11	ga_s2am_ard_3-2-1_50KNV_2019-08-15_final.stac-item
2019-08-15 11:54:26	ga_s2am_ard_3-2-1_50KNU_2019-08-15_final.stac-item
2019-08-15 11:54:40	ga_s2am_ard_3-2-1_50JNT_2019-08-15_final.stac-item
2019-08-15 11:54:55	ga_s2am_ard_3-2-1_50JNS_2019-08-15_final.stac-item
2019-08-15 11:55:09	ga_s2am_ard_3-2-1_50JNR_2019-08-15_final.stac-item
2019-08-15 11:55:24	ga_s2am_ard_3-2-1_50JNQ_2019-08-15_final.stac-item
2019-08-15 11:55:38	ga_s2am_ard_3-2-1_50JNP_2019-08-15_final.stac-item
2022-11-04 11:45:43	ga_s2am_ard_3-2-1_50JNP_2022-11-04_final.stac-item
2022-11-04 11:45:58	ga_s2am_ard_3-2-1_50JNN_2022-11-04_final.stac-item
2022-11-04 11:46:12	ga_s2am_ard_3-2-1_50JNM_2022-11-04_final.stac-item
2022-11-04 11:46:27	ga_s2am_ard_3-2-1_50JNL_2022-11-04_final.stac-item
2022-11-04 11:46:41	ga_s2am_ard_3-2-1_50HNK_2022-11-04_final.stac-item
2022-11-04 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2022-11-04_final.stac-item
2022-11-04 11:47:10	ga_s2am_ard_3-2-1_50HNH_2022-11-04_final.stac-item
2022-11-07 11:56:08	ga_s2am_ard_3-2-1_50JNM_2022-11-07_final.stac-item
2022-11-07 11:56:22	ga_s2am_ard_3-2-1_50JNL_2022-11-07_final.stac-item
2022-11-10 12:03:23	ga_s2am_ard_3-2-1_50KNC_2022-11-10_final.stac-item
2022-11-10 12:03:37	ga_s2am_ard_3-2-1_50KNB_2022-11-10_final.stac-item
2022-11-14 11:45:42	ga_s2am_ard_3-2-1_50JNP_2022-11-14_final.stac-item
2022-11-14 11:45:57	ga_s2am_ard_3-2-1_50JNN_2022-11-14_final.stac-item
2022-11-14 11:46:11	ga_s2am_ard_3-2-1_50JNM_2022-11-14_final.stac-item
2022-11-14 11:46:25	ga_s2am_ard_3-2-1_50JNL_2022-11-14_final.stac-item
2022-11-14 11:46:40	ga_s2am_ard_3-2-1_50HNK_2022-11-14_final.stac-item
2022-11-14 11:46:55	ga_s2am_ard_3-2-1_50HNJ_2022-11-14_final.stac-item
2022-11-14 11:47:09	ga_s2am_ard_3-2-1_50HNH_2022-11-14_final.stac-item
2022-11-17 11:53:18	ga_s2am_ard_3-2-1_50KNC_2022-11-17_final.stac-item
2022-11-17 11:53:26	ga_s2am_ard_3-2-1_50KNC_2022-11-17_final.stac-item
2022-11-17 11:53:41	ga_s2am_ard_3-2-1_50KNB_2022-11-17_final.stac-item
2022-12-24 11:45:37	ga_s2am_ard_3-2-1_50JNP_2022-12-24_final.stac-item
2022-12-24 11:45:52	ga_s2am_ard_3-2-1_50JNN_2022-12-24_final.stac-item
2022-12-24 11:46:06	ga_s2am_ard_3-2-1_50JNM_2022-12-24_final.stac-item
2022-12-24 11:46:21	ga_s2am_ard_3-2-1_50JNL_2022-12-24_final.stac-item
2022-12-24 11:46:35	ga_s2am_ard_3-2-1_50HNK_2022-12-24_final.stac-item
2022-12-24 11:46:50	ga_s2am_ard_3-2-1_50HNJ_2022-12-24_final.stac-item
2022-12-24 11:47:04	ga_s2am_ard_3-2-1_50HNH_2022-12-24_final.stac-item
2022-12-27 11:53:08	ga_s2am_ard_3-2-1_50KND_2022-12-27_nrt.stac-item
2022-12-27 11:53:23	ga_s2am_ard_3-2-1_50KNC_2022-12-27_final.stac-item
2022-12-27 11:53:37	ga_s2am_ard_3-2-1_50KNB_2022-12-27_final.stac-item
2022-12-27 11:53:52	ga_s2am_ard_3-2-1_50KNA_2022-12-27_final.stac-item
2022-12-27 11:54:06	ga_s2am_ard_3-2-1_50KNV_2022-12-27_final.stac-item
2022-12-27 11:56:16	ga_s2am_ard_3-2-1_50JNL_2022-12-27_final.stac-item
2022-12-30 12:03:19	ga_s2am_ard_3-2-1_50KNC_2022-12-30_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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