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
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_53KKT_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_53KKU_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KEC_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KED_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KFC_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KFD_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KGC_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KGD_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KHC_2018-02-26_final.stac-item
2018-02-26 10:57:12	ga_s2am_ard_3-2-1_52KHD_2018-02-26_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KKT_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KKU_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KLT_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KLU_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KMT_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KMU_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_53KNU_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_52KHC_2018-03-15_final.stac-item
2018-03-15 10:47:20	ga_s2am_ard_3-2-1_52KHD_2018-03-15_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_53KKT_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_53KKU_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52KEC_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52KED_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52KFC_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52KFD_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52KGC_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52KGD_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52KHC_2018-03-18_final.stac-item
2018-03-18 10:57:12	ga_s2am_ard_3-2-1_52KHD_2018-03-18_final.stac-item
2019-03-27 10:42:31	ga_s2am_ard_3-2-1_53KQU_2019-03-27_final.stac-item
2019-03-27 10:42:35	ga_s2am_ard_3-2-1_53KPU_2019-03-27_final.stac-item
2019-03-27 10:42:38	ga_s2am_ard_3-2-1_53KNU_2019-03-27_final.stac-item
2019-03-27 10:42:42	ga_s2am_ard_3-2-1_53KMU_2019-03-27_final.stac-item
2019-03-27 10:42:46	ga_s2am_ard_3-2-1_53KQT_2019-03-27_final.stac-item
2019-03-27 10:42:49	ga_s2am_ard_3-2-1_53KPT_2019-03-27_final.stac-item
2019-03-27 10:42:53	ga_s2am_ard_3-2-1_53KNT_2019-03-27_final.stac-item
2019-03-28 10:12:16	ga_s2am_ard_3-2-1_55KCU_2019-03-28_final.stac-item
2019-03-28 10:12:20	ga_s2am_ard_3-2-1_55KBU_2019-03-28_final.stac-item
2019-03-28 10:12:21	ga_s2am_ard_3-2-1_54KZD_2019-03-28_final.stac-item
2019-03-28 10:12:25	ga_s2am_ard_3-2-1_54KYD_2019-03-28_final.stac-item
2019-03-28 10:12:27	ga_s2am_ard_3-2-1_55KCT_2019-03-28_final.stac-item
2019-03-28 10:12:28	ga_s2am_ard_3-2-1_54KXD_2019-03-28_final.stac-item
2019-03-28 10:12:34	ga_s2am_ard_3-2-1_55KBT_2019-03-28_final.stac-item
2019-03-28 10:12:35	ga_s2am_ard_3-2-1_54KZC_2019-03-28_final.stac-item
2019-03-28 10:12:39	ga_s2am_ard_3-2-1_54KYC_2019-03-28_final.stac-item
2019-03-28 10:12:43	ga_s2am_ard_3-2-1_54KXC_2019-03-28_final.stac-item
2019-04-02 11:02:40	ga_s2am_ard_3-2-1_53KKU_2019-04-02_final.stac-item
2019-04-02 11:02:41	ga_s2am_ard_3-2-1_52KHD_2019-04-02_final.stac-item
2019-04-02 11:02:45	ga_s2am_ard_3-2-1_52KGD_2019-04-02_final.stac-item
2019-04-02 11:02:48	ga_s2am_ard_3-2-1_52KFD_2019-04-02_final.stac-item
2019-04-02 11:02:52	ga_s2am_ard_3-2-1_52KED_2019-04-02_final.stac-item
2019-04-02 11:02:55	ga_s2am_ard_3-2-1_53KKT_2019-04-02_final.stac-item
2019-04-02 11:02:55	ga_s2am_ard_3-2-1_52KHC_2019-04-02_final.stac-item
2019-04-02 11:02:59	ga_s2am_ard_3-2-1_52KGC_2019-04-02_final.stac-item
2019-04-02 11:03:02	ga_s2am_ard_3-2-1_52KFC_2019-04-02_final.stac-item
2019-04-02 11:03:05	ga_s2am_ard_3-2-1_52KEC_2019-04-02_final.stac-item
2019-04-03 10:32:26	ga_s2am_ard_3-2-1_54KVD_2019-04-03_final.stac-item
2019-04-03 10:32:30	ga_s2am_ard_3-2-1_54KUD_2019-04-03_final.stac-item
2019-04-03 10:32:33	ga_s2am_ard_3-2-1_54KTD_2019-04-03_final.stac-item
2019-04-03 10:32:34	ga_s2am_ard_3-2-1_53KRU_2019-04-03_final.stac-item
2019-04-03 10:32:37	ga_s2am_ard_3-2-1_53KQU_2019-04-03_final.stac-item
2019-04-03 10:32:37	ga_s2am_ard_3-2-1_54KVC_2019-04-03_final.stac-item
2019-04-03 10:32:44	ga_s2am_ard_3-2-1_54KUC_2019-04-03_final.stac-item
2019-04-03 10:32:48	ga_s2am_ard_3-2-1_54KTC_2019-04-03_final.stac-item
2019-04-03 10:32:48	ga_s2am_ard_3-2-1_53KRT_2019-04-03_final.stac-item
2019-04-03 10:32:52	ga_s2am_ard_3-2-1_53KQT_2019-04-03_final.stac-item
2019-04-07 10:12:18	ga_s2am_ard_3-2-1_55KCU_2019-04-07_final.stac-item
2019-04-07 10:12:22	ga_s2am_ard_3-2-1_55KBU_2019-04-07_final.stac-item
2019-04-07 10:12:23	ga_s2am_ard_3-2-1_54KZD_2019-04-07_final.stac-item
2019-04-07 10:12:26	ga_s2am_ard_3-2-1_54KYD_2019-04-07_final.stac-item
2019-04-07 10:12:29	ga_s2am_ard_3-2-1_55KCT_2019-04-07_final.stac-item
2019-04-07 10:12:29	ga_s2am_ard_3-2-1_54KXD_2019-04-07_final.stac-item
2019-04-07 10:12:36	ga_s2am_ard_3-2-1_55KBT_2019-04-07_final.stac-item
2019-04-07 10:12:37	ga_s2am_ard_3-2-1_54KZC_2019-04-07_final.stac-item
2019-04-07 10:12:41	ga_s2am_ard_3-2-1_54KYC_2019-04-07_final.stac-item
2019-04-07 10:12:44	ga_s2am_ard_3-2-1_54KXC_2019-04-07_final.stac-item
2019-06-30 11:32:55	ga_s2am_ard_3-2-1_51KYU_2019-06-30_final.stac-item
2019-06-30 11:32:59	ga_s2am_ard_3-2-1_51KXU_2019-06-30_final.stac-item
2019-06-30 11:33:02	ga_s2am_ard_3-2-1_51KWU_2019-06-30_final.stac-item
2019-06-30 11:33:05	ga_s2am_ard_3-2-1_51KYT_2019-06-30_final.stac-item
2019-06-30 11:33:07	ga_s2am_ard_3-2-1_51KXU_2019-06-30_final.stac-item
2019-06-30 11:33:07	ga_s2am_ard_3-2-1_51KXT_2019-06-30_final.stac-item
2019-06-30 11:33:08	ga_s2am_ard_3-2-1_51KWT_2019-06-30_final.stac-item
2019-06-30 11:33:08	ga_s2am_ard_3-2-1_51KWU_2019-06-30_final.stac-item
2019-06-30 11:33:10	ga_s2am_ard_3-2-1_51KVU_2019-06-30_final.stac-item
2019-06-30 11:33:14	ga_s2am_ard_3-2-1_51KXT_2019-06-30_final.stac-item
2019-06-30 11:33:17	ga_s2am_ard_3-2-1_51KWT_2019-06-30_final.stac-item
2019-07-10 11:32:56	ga_s2am_ard_3-2-1_51KYU_2019-07-10_final.stac-item
2019-07-10 11:33:00	ga_s2am_ard_3-2-1_51KXU_2019-07-10_final.stac-item
2019-07-10 11:33:02	ga_s2am_ard_3-2-1_51KWU_2019-07-10_final.stac-item
2019-07-10 11:33:06	ga_s2am_ard_3-2-1_51KYT_2019-07-10_final.stac-item
2019-07-10 11:33:08	ga_s2am_ard_3-2-1_51KXT_2019-07-10_final.stac-item
2019-07-10 11:33:08	ga_s2am_ard_3-2-1_51KXU_2019-07-10_final.stac-item
2019-07-10 11:33:09	ga_s2am_ard_3-2-1_51KWT_2019-07-10_final.stac-item
2019-07-10 11:33:09	ga_s2am_ard_3-2-1_51KWU_2019-07-10_final.stac-item
2019-07-10 11:33:11	ga_s2am_ard_3-2-1_51KVU_2019-07-10_final.stac-item
2019-07-10 11:33:14	ga_s2am_ard_3-2-1_51KXT_2019-07-10_final.stac-item
2019-07-10 11:33:18	ga_s2am_ard_3-2-1_51KWT_2019-07-10_final.stac-item
2019-07-16 11:53:04	ga_s2am_ard_3-2-1_50KRD_2019-07-16_final.stac-item
2019-07-16 11:53:16	ga_s2am_ard_3-2-1_50KRC_2019-07-16_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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