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
2015-12-11 09:59:08	ga_s2am_ard_3-2-1_54JZT_2015-12-11_final.stac-item
2015-12-11 09:59:08	ga_s2am_ard_3-2-1_54KYU_2015-12-11_final.stac-item
2015-12-11 09:59:08	ga_s2am_ard_3-2-1_54KZU_2015-12-11_final.stac-item
2015-12-11 09:59:08	ga_s2am_ard_3-2-1_55KBP_2015-12-11_final.stac-item
2015-12-28 09:55:35	ga_s2am_ard_3-2-1_55KDP_2015-12-28_final.stac-item
2015-12-28 09:55:35	ga_s2am_ard_3-2-1_55KEP_2015-12-28_final.stac-item
2015-12-28 09:55:35	ga_s2am_ard_3-2-1_55KFP_2015-12-28_final.stac-item
2015-12-28 09:55:35	ga_s2am_ard_3-2-1_55KGP_2015-12-28_final.stac-item
2015-12-29 11:06:56	ga_s2am_ard_3-2-1_52KDU_2015-12-29_final.stac-item
2015-12-29 11:06:56	ga_s2am_ard_3-2-1_52KEU_2015-12-29_final.stac-item
2015-12-29 11:06:56	ga_s2am_ard_3-2-1_52KFU_2015-12-29_final.stac-item
2015-12-29 11:06:56	ga_s2am_ard_3-2-1_52KGU_2015-12-29_final.stac-item
2016-01-15 10:56:39	ga_s2am_ard_3-2-1_52JHT_2016-01-15_final.stac-item
2016-01-15 10:56:39	ga_s2am_ard_3-2-1_53KKP_2016-01-15_final.stac-item
2016-01-15 10:56:39	ga_s2am_ard_3-2-1_53KLP_2016-01-15_final.stac-item
2016-01-15 10:56:39	ga_s2am_ard_3-2-1_53KMP_2016-01-15_final.stac-item
2016-01-15 10:56:39	ga_s2am_ard_3-2-1_52KGU_2016-01-15_final.stac-item
2016-01-15 10:56:39	ga_s2am_ard_3-2-1_52KHU_2016-01-15_final.stac-item
2016-01-17 09:53:34	ga_s2am_ard_3-2-1_55KEP_2016-01-17_final.stac-item
2016-01-17 09:53:34	ga_s2am_ard_3-2-1_55KFP_2016-01-17_final.stac-item
2016-01-17 09:53:34	ga_s2am_ard_3-2-1_55KGP_2016-01-17_final.stac-item
2016-01-18 11:02:07	ga_s2am_ard_3-2-1_52KDU_2016-01-18_final.stac-item
2016-01-18 11:02:07	ga_s2am_ard_3-2-1_52KEU_2016-01-18_final.stac-item
2016-01-18 11:02:07	ga_s2am_ard_3-2-1_52KFU_2016-01-18_final.stac-item
2016-01-18 11:02:07	ga_s2am_ard_3-2-1_52KGU_2016-01-18_final.stac-item
2016-01-21 09:33:46	ga_s2am_ard_3-2-1_56KMU_2016-01-21_final.stac-item
2016-01-21 09:33:46	ga_s2am_ard_3-2-1_56KLU_2016-01-21_final.stac-item
2016-01-21 11:14:09	ga_s2am_ard_3-2-1_51KZP_2016-01-21_final.stac-item
2016-01-21 11:14:09	ga_s2am_ard_3-2-1_52KBU_2016-01-21_final.stac-item
2016-01-21 11:14:09	ga_s2am_ard_3-2-1_52KCU_2016-01-21_final.stac-item
2016-01-21 11:14:09	ga_s2am_ard_3-2-1_52KDU_2016-01-21_final.stac-item
2016-01-21 11:14:09	ga_s2am_ard_3-2-1_52KEU_2016-01-21_final.stac-item
2016-01-22 10:44:08	ga_s2am_ard_3-2-1_53KLP_2016-01-22_final.stac-item
2016-01-22 10:44:08	ga_s2am_ard_3-2-1_53KMP_2016-01-22_final.stac-item
2016-01-22 10:44:08	ga_s2am_ard_3-2-1_53KNP_2016-01-22_final.stac-item
2016-01-22 10:44:08	ga_s2am_ard_3-2-1_53KPP_2016-01-22_final.stac-item
2016-02-01 10:39:39	ga_s2am_ard_3-2-1_53KLP_2016-02-01_final.stac-item
2016-02-01 10:39:39	ga_s2am_ard_3-2-1_53KMP_2016-02-01_final.stac-item
2016-02-01 10:39:39	ga_s2am_ard_3-2-1_53KNP_2016-02-01_final.stac-item
2016-02-01 10:39:39	ga_s2am_ard_3-2-1_53KPP_2016-02-01_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KUP_2018-10-23_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KVP_2018-10-23_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KWP_2018-10-23_final.stac-item
2018-10-23 11:33:19	ga_s2am_ard_3-2-1_51KXP_2018-10-23_final.stac-item
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_54KTU_2018-10-25_final.stac-item
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_54KUU_2018-10-25_final.stac-item
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_53JRN_2018-10-25_final.stac-item
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_53KPP_2018-10-25_final.stac-item
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_53KQP_2018-10-25_final.stac-item
2018-10-25 10:27:05	ga_s2am_ard_3-2-1_53KRP_2018-10-25_final.stac-item
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KGP_2018-10-25_final.stac-item
2018-10-25 12:13:18	ga_s2am_ard_3-2-1_49KHP_2018-10-25_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_54JZT_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_54KYU_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_54KZU_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55KBP_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55KCP_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55KDP_2018-10-26_final.stac-item
2018-10-27 09:32:37	ga_s2am_ard_3-2-1_56KMU_2018-10-27_final.stac-item
2018-10-27 09:32:37	ga_s2am_ard_3-2-1_56KLU_2018-10-27_final.stac-item
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_56KKU_2018-10-30_final.stac-item
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_56KLU_2018-10-30_final.stac-item
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_55JHN_2018-10-30_final.stac-item
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_55KFP_2018-10-30_final.stac-item
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_55KGP_2018-10-30_final.stac-item
2018-10-30 09:41:05	ga_s2am_ard_3-2-1_55KHP_2018-10-30_final.stac-item
2018-11-11 12:04:16	ga_s2am_ard_3-2-1_50KMU_2018-11-11_final.stac-item
2018-11-11 12:04:20	ga_s2am_ard_3-2-1_50KLU_2018-11-11_final.stac-item
2018-11-11 12:04:23	ga_s2am_ard_3-2-1_49KHP_2018-11-11_final.stac-item
2018-11-11 12:04:23	ga_s2am_ard_3-2-1_50KKU_2018-11-11_final.stac-item
2018-11-11 12:04:26	ga_s2am_ard_3-2-1_49KGP_2018-11-11_final.stac-item
2018-11-11 12:04:37	ga_s2am_ard_3-2-1_49JHN_2018-11-11_final.stac-item
2018-11-12 09:53:20	ga_s2am_ard_3-2-1_55KGP_2018-11-12_final.stac-item
2018-11-12 09:53:24	ga_s2am_ard_3-2-1_55KFP_2018-11-12_final.stac-item
2018-11-12 09:53:28	ga_s2am_ard_3-2-1_55KEP_2018-11-12_final.stac-item
2018-11-12 09:53:31	ga_s2am_ard_3-2-1_55KDP_2018-11-12_final.stac-item
2019-10-12 11:14:00	ga_s2am_ard_3-2-1_52KEU_2019-10-12_final.stac-item
2019-10-12 11:14:05	ga_s2am_ard_3-2-1_52KDU_2019-10-12_final.stac-item
2019-10-12 11:14:08	ga_s2am_ard_3-2-1_52KCU_2019-10-12_final.stac-item
2019-10-12 11:14:12	ga_s2am_ard_3-2-1_51KZP_2019-10-12_final.stac-item
2019-10-12 11:14:12	ga_s2am_ard_3-2-1_52KBU_2019-10-12_final.stac-item
2019-10-12 11:14:26	ga_s2am_ard_3-2-1_51JZN_2019-10-12_final.stac-item
2019-10-16 10:53:52	ga_s2am_ard_3-2-1_53KMP_2019-10-16_final.stac-item
2019-10-16 10:53:57	ga_s2am_ard_3-2-1_53KLP_2019-10-16_final.stac-item
2019-10-16 10:54:00	ga_s2am_ard_3-2-1_53KKP_2019-10-16_final.stac-item
2019-10-16 10:54:00	ga_s2am_ard_3-2-1_52KHU_2019-10-16_final.stac-item
2019-10-16 10:54:04	ga_s2am_ard_3-2-1_52KGU_2019-10-16_final.stac-item
2019-10-16 10:54:15	ga_s2am_ard_3-2-1_52JHT_2019-10-16_final.stac-item
2019-10-22 11:14:27	ga_s2am_ard_3-2-1_51JZN_2019-10-22_final.stac-item
2019-10-25 09:43:26	ga_s2am_ard_3-2-1_56KLU_2019-10-25_final.stac-item
2019-10-25 09:43:30	ga_s2am_ard_3-2-1_56KKU_2019-10-25_final.stac-item
2019-10-25 09:43:30	ga_s2am_ard_3-2-1_55KHP_2019-10-25_final.stac-item
2019-10-25 09:43:33	ga_s2am_ard_3-2-1_55KGP_2019-10-25_final.stac-item
2019-10-25 09:43:38	ga_s2am_ard_3-2-1_55KFP_2019-10-25_final.stac-item
2019-10-25 09:43:44	ga_s2am_ard_3-2-1_55JHN_2019-10-25_final.stac-item
2019-10-27 10:23:43	ga_s2am_ard_3-2-1_54KWU_2019-10-27_final.stac-item
2019-10-27 10:23:47	ga_s2am_ard_3-2-1_54KVU_2019-10-27_final.stac-item
2019-10-27 10:23:50	ga_s2am_ard_3-2-1_54KUU_2019-10-27_final.stac-item
2019-10-27 10:23:53	ga_s2am_ard_3-2-1_54KTU_2019-10-27_final.stac-item
2019-10-27 10:23:54	ga_s2am_ard_3-2-1_53KRP_2019-10-27_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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