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
2022-04-01 11:55:00	ga_s2am_ard_3-2-1_50JLS_2022-04-01_final.stac-item
2022-04-01 11:55:18	ga_s2am_ard_3-2-1_50JPQ_2022-04-01_final.stac-item
2022-04-01 11:55:37	ga_s2am_ard_3-2-1_50JNP_2022-04-01_final.stac-item
2022-04-01 11:55:44	ga_s2am_ard_3-2-1_50JLP_2022-04-01_final.stac-item
2022-04-01 11:55:49	ga_s2am_ard_3-2-1_50JMN_2022-04-01_final.stac-item
2022-04-01 11:55:51	ga_s2am_ard_3-2-1_50JLP_2022-04-01_final.stac-item
2022-04-01 11:55:56	ga_s2am_ard_3-2-1_50JMN_2022-04-01_final.stac-item
2022-04-04 12:04:15	ga_s2am_ard_3-2-1_49KHQ_2022-04-04_final.stac-item
2022-04-04 12:04:20	ga_s2am_ard_3-2-1_49KGQ_2022-04-04_final.stac-item
2022-04-04 12:04:44	ga_s2am_ard_3-2-1_49JHN_2022-04-04_final.stac-item
2022-04-04 12:04:44	ga_s2am_ard_3-2-1_50JKT_2022-04-04_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 12:05:39	ga_s2am_ard_3-2-1_50JLP_2022-04-04_final.stac-item
2022-04-07 12:14:09	ga_s2am_ard_3-2-1_49KHQ_2022-04-07_final.stac-item
2022-04-07 12:14:13	ga_s2am_ard_3-2-1_49KGQ_2022-04-07_final.stac-item
2022-04-07 12:14:46	ga_s2am_ard_3-2-1_49JFN_2022-04-07_final.stac-item
2022-04-08 11:45:22	ga_s2am_ard_3-2-1_50JPQ_2022-04-08_final.stac-item
2022-04-08 11:45:40	ga_s2am_ard_3-2-1_50JNP_2022-04-08_final.stac-item
2022-04-08 11:45:51	ga_s2am_ard_3-2-1_50JPN_2022-04-08_final.stac-item
2022-04-11 11:55:00	ga_s2am_ard_3-2-1_50JLS_2022-04-11_final.stac-item
2022-04-11 11:55:17	ga_s2am_ard_3-2-1_50JPQ_2022-04-11_final.stac-item
2022-04-11 11:55:37	ga_s2am_ard_3-2-1_50JNP_2022-04-11_final.stac-item
2022-04-11 11:55:44	ga_s2am_ard_3-2-1_50JLP_2022-04-11_final.stac-item
2022-04-11 11:55:55	ga_s2am_ard_3-2-1_50JMN_2022-04-11_final.stac-item
2022-04-14 12:04:21	ga_s2am_ard_3-2-1_49KGQ_2022-04-14_final.stac-item
2022-04-14 12:04:34	ga_s2am_ard_3-2-1_49KGP_2022-04-14_final.stac-item
2022-04-14 12:04:45	ga_s2am_ard_3-2-1_49JHN_2022-04-14_final.stac-item
2022-04-14 12:04:45	ga_s2am_ard_3-2-1_50JKT_2022-04-14_final.stac-item
2022-04-14 12:04:56	ga_s2am_ard_3-2-1_50JLS_2022-04-14_final.stac-item
2022-04-14 12:05:40	ga_s2am_ard_3-2-1_50JLP_2022-04-14_final.stac-item
2022-04-17 12:14:12	ga_s2am_ard_3-2-1_49KHQ_2022-04-17_final.stac-item
2022-04-17 12:14:16	ga_s2am_ard_3-2-1_49KGQ_2022-04-17_final.stac-item
2022-04-17 12:14:30	ga_s2am_ard_3-2-1_49KGP_2022-04-17_final.stac-item
2022-04-17 12:14:34	ga_s2am_ard_3-2-1_49JHN_2022-04-17_final.stac-item
2022-04-17 12:14:49	ga_s2am_ard_3-2-1_49JFN_2022-04-17_final.stac-item
2022-04-18 11:45:25	ga_s2am_ard_3-2-1_50JPQ_2022-04-18_final.stac-item
2022-04-18 11:45:43	ga_s2am_ard_3-2-1_50JNP_2022-04-18_final.stac-item
2022-04-18 11:45:54	ga_s2am_ard_3-2-1_50JPN_2022-04-18_final.stac-item
2022-04-21 11:55:02	ga_s2am_ard_3-2-1_50JLS_2022-04-21_final.stac-item
2022-04-21 11:55:20	ga_s2am_ard_3-2-1_50JPQ_2022-04-21_final.stac-item
2022-04-21 11:55:39	ga_s2am_ard_3-2-1_50JNP_2022-04-21_final.stac-item
2022-04-21 11:55:46	ga_s2am_ard_3-2-1_50JLP_2022-04-21_final.stac-item
2022-04-21 11:55:57	ga_s2am_ard_3-2-1_50JMN_2022-04-21_final.stac-item
2022-04-24 12:04:18	ga_s2am_ard_3-2-1_49KHQ_2022-04-24_final.stac-item
2022-04-24 12:04:23	ga_s2am_ard_3-2-1_49KGQ_2022-04-24_final.stac-item
2022-04-24 12:04:36	ga_s2am_ard_3-2-1_49KGP_2022-04-24_final.stac-item
2022-04-24 12:04:47	ga_s2am_ard_3-2-1_49JHN_2022-04-24_final.stac-item
2022-04-24 12:04:47	ga_s2am_ard_3-2-1_50JKT_2022-04-24_final.stac-item
2022-04-24 12:04:58	ga_s2am_ard_3-2-1_50JLS_2022-04-24_final.stac-item
2022-04-24 12:05:42	ga_s2am_ard_3-2-1_50JLP_2022-04-24_final.stac-item
2022-04-27 12:14:18	ga_s2am_ard_3-2-1_49KGQ_2022-04-27_final.stac-item
2022-04-27 12:14:32	ga_s2am_ard_3-2-1_49KGP_2022-04-27_final.stac-item
2022-04-27 12:14:50	ga_s2am_ard_3-2-1_49JFN_2022-04-27_final.stac-item
2022-04-28 11:45:26	ga_s2am_ard_3-2-1_50JPQ_2022-04-28_final.stac-item
2022-04-28 11:45:44	ga_s2am_ard_3-2-1_50JNP_2022-04-28_final.stac-item
2022-04-28 11:45:55	ga_s2am_ard_3-2-1_50JPN_2022-04-28_final.stac-item
2022-05-01 11:56:13	ga_s2am_ard_3-2-1_50JMM_2022-05-01_final.stac-item
2022-05-01 11:56:23	ga_s2am_ard_3-2-1_50JNL_2022-05-01_final.stac-item
2022-05-01 11:56:31	ga_s2am_ard_3-2-1_50JLL_2022-05-01_final.stac-item
2022-05-01 11:56:35	ga_s2am_ard_3-2-1_50HNK_2022-05-01_final.stac-item
2022-05-01 11:56:45	ga_s2am_ard_3-2-1_50HLK_2022-05-01_final.stac-item
2022-05-05 11:36:36	ga_s2am_ard_3-2-1_50HPK_2022-05-05_final.stac-item
2022-05-05 11:36:43	ga_s2am_ard_3-2-1_50HPK_2022-05-05_final.stac-item
2022-05-08 11:46:17	ga_s2am_ard_3-2-1_50JMM_2022-05-08_final.stac-item
2022-05-08 11:46:27	ga_s2am_ard_3-2-1_50JNL_2022-05-08_final.stac-item
2022-05-08 11:46:38	ga_s2am_ard_3-2-1_50HPK_2022-05-08_final.stac-item
2022-05-08 11:46:42	ga_s2am_ard_3-2-1_50HNK_2022-05-08_final.stac-item
2022-05-08 11:46:56	ga_s2am_ard_3-2-1_50HNJ_2022-05-08_final.stac-item
2022-05-08 11:47:11	ga_s2am_ard_3-2-1_50HNH_2022-05-08_final.stac-item
2022-05-11 11:56:11	ga_s2am_ard_3-2-1_50JMM_2022-05-11_final.stac-item
2022-05-11 11:56:22	ga_s2am_ard_3-2-1_50JNL_2022-05-11_final.stac-item
2022-05-11 11:56:29	ga_s2am_ard_3-2-1_50JLL_2022-05-11_final.stac-item
2022-05-11 11:56:34	ga_s2am_ard_3-2-1_50HNK_2022-05-11_final.stac-item
2022-05-11 11:56:44	ga_s2am_ard_3-2-1_50HLK_2022-05-11_final.stac-item
2022-05-15 11:36:09	ga_s2am_ard_3-2-1_50JQM_2022-05-15_final.stac-item
2022-05-15 11:36:42	ga_s2am_ard_3-2-1_50HPK_2022-05-15_final.stac-item
2022-05-18 11:46:10	ga_s2am_ard_3-2-1_50JPM_2022-05-18_final.stac-item
2022-05-18 11:46:18	ga_s2am_ard_3-2-1_50JMM_2022-05-18_final.stac-item
2022-05-18 11:46:28	ga_s2am_ard_3-2-1_50JNL_2022-05-18_final.stac-item
2022-05-18 11:46:39	ga_s2am_ard_3-2-1_50HPK_2022-05-18_final.stac-item
2022-05-18 11:46:43	ga_s2am_ard_3-2-1_50HNK_2022-05-18_final.stac-item
2022-05-18 11:46:57	ga_s2am_ard_3-2-1_50HNJ_2022-05-18_final.stac-item
2022-05-18 11:47:12	ga_s2am_ard_3-2-1_50HNH_2022-05-18_final.stac-item
2022-05-21 11:56:14	ga_s2am_ard_3-2-1_50JMM_2022-05-21_final.stac-item
2022-05-21 11:56:24	ga_s2am_ard_3-2-1_50JNL_2022-05-21_final.stac-item
2022-05-21 11:56:32	ga_s2am_ard_3-2-1_50JLL_2022-05-21_final.stac-item
2022-05-21 11:56:36	ga_s2am_ard_3-2-1_50HNK_2022-05-21_final.stac-item
2022-05-21 11:56:46	ga_s2am_ard_3-2-1_50HLK_2022-05-21_final.stac-item
2022-05-25 11:36:45	ga_s2am_ard_3-2-1_50HPK_2022-05-25_final.stac-item
2022-05-28 11:46:12	ga_s2am_ard_3-2-1_50JPM_2022-05-28_final.stac-item
2022-05-28 11:46:20	ga_s2am_ard_3-2-1_50JMM_2022-05-28_final.stac-item
2022-05-28 11:46:30	ga_s2am_ard_3-2-1_50JNL_2022-05-28_final.stac-item
2022-05-28 11:46:41	ga_s2am_ard_3-2-1_50HPK_2022-05-28_final.stac-item
2022-05-28 11:46:45	ga_s2am_ard_3-2-1_50HNK_2022-05-28_final.stac-item
2022-05-28 11:46:59	ga_s2am_ard_3-2-1_50HNJ_2022-05-28_final.stac-item
2022-05-28 11:47:14	ga_s2am_ard_3-2-1_50HNH_2022-05-28_final.stac-item
2022-05-31 11:56:15	ga_s2am_ard_3-2-1_50JMM_2022-05-31_final.stac-item
2022-05-31 11:56:26	ga_s2am_ard_3-2-1_50JNL_2022-05-31_final.stac-item
2022-05-31 11:56:33	ga_s2am_ard_3-2-1_50JLL_2022-05-31_final.stac-item
2022-05-31 11:56:37	ga_s2am_ard_3-2-1_50HNK_2022-05-31_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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