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
2018-12-23 11:03:48	ga_s2am_ard_3-2-1_52KGU_2018-12-23_final.stac-item
2018-12-23 11:03:52	ga_s2am_ard_3-2-1_52KFU_2018-12-23_final.stac-item
2018-12-23 11:03:55	ga_s2am_ard_3-2-1_52KEU_2018-12-23_final.stac-item
2018-12-23 11:03:59	ga_s2am_ard_3-2-1_52KDU_2018-12-23_final.stac-item
2018-12-29 09:43:16	ga_s2am_ard_3-2-1_56KLU_2018-12-29_final.stac-item
2018-12-29 09:43:20	ga_s2am_ard_3-2-1_56KKU_2018-12-29_final.stac-item
2018-12-29 09:43:20	ga_s2am_ard_3-2-1_55KHP_2018-12-29_final.stac-item
2018-12-29 09:43:23	ga_s2am_ard_3-2-1_55KGP_2018-12-29_final.stac-item
2018-12-29 09:43:28	ga_s2am_ard_3-2-1_55KFP_2018-12-29_final.stac-item
2018-12-29 09:43:34	ga_s2am_ard_3-2-1_55JHN_2018-12-29_final.stac-item
2018-12-29 09:43:38	ga_s2am_ard_3-2-1_55JGN_2018-12-29_final.stac-item
2019-04-14 11:44:15	ga_s2am_ard_3-2-1_51KUP_2019-04-14_final.stac-item
2019-04-14 11:44:18	ga_s2am_ard_3-2-1_50KRU_2019-04-14_final.stac-item
2019-04-14 11:44:18	ga_s2am_ard_3-2-1_51KTP_2019-04-14_final.stac-item
2019-04-14 11:44:22	ga_s2am_ard_3-2-1_50KQU_2019-04-14_final.stac-item
2019-04-14 11:44:25	ga_s2am_ard_3-2-1_50KPU_2019-04-14_final.stac-item
2019-04-14 11:44:33	ga_s2am_ard_3-2-1_50JRT_2019-04-14_final.stac-item
2019-04-14 11:44:37	ga_s2am_ard_3-2-1_50JQT_2019-04-14_final.stac-item
2019-04-17 11:54:16	ga_s2am_ard_3-2-1_50KQU_2019-04-17_final.stac-item
2019-04-17 11:54:21	ga_s2am_ard_3-2-1_50KPU_2019-04-17_final.stac-item
2019-04-17 11:54:25	ga_s2am_ard_3-2-1_50KNU_2019-04-17_final.stac-item
2019-04-17 11:54:28	ga_s2am_ard_3-2-1_50KMU_2019-04-17_final.stac-item
2019-04-17 11:54:36	ga_s2am_ard_3-2-1_50KLU_2019-04-17_final.stac-item
2019-04-20 12:04:24	ga_s2am_ard_3-2-1_50KMU_2019-04-20_final.stac-item
2019-04-20 12:04:28	ga_s2am_ard_3-2-1_50KLU_2019-04-20_final.stac-item
2019-04-20 12:04:31	ga_s2am_ard_3-2-1_49KHP_2019-04-20_final.stac-item
2019-04-20 12:04:31	ga_s2am_ard_3-2-1_50KKU_2019-04-20_final.stac-item
2019-04-20 12:04:34	ga_s2am_ard_3-2-1_49KGP_2019-04-20_final.stac-item
2019-04-20 12:04:45	ga_s2am_ard_3-2-1_49JHN_2019-04-20_final.stac-item
2019-04-20 12:04:49	ga_s2am_ard_3-2-1_49JGN_2019-04-20_final.stac-item
2019-04-24 11:44:16	ga_s2am_ard_3-2-1_51KUP_2019-04-24_final.stac-item
2019-04-24 11:44:19	ga_s2am_ard_3-2-1_50KRU_2019-04-24_final.stac-item
2019-04-24 11:44:19	ga_s2am_ard_3-2-1_51KTP_2019-04-24_final.stac-item
2019-04-24 11:44:23	ga_s2am_ard_3-2-1_50KQU_2019-04-24_final.stac-item
2019-04-24 11:44:26	ga_s2am_ard_3-2-1_50KPU_2019-04-24_final.stac-item
2019-04-24 11:44:34	ga_s2am_ard_3-2-1_50JRT_2019-04-24_final.stac-item
2019-04-24 11:44:38	ga_s2am_ard_3-2-1_50JQT_2019-04-24_final.stac-item
2019-04-27 11:54:17	ga_s2am_ard_3-2-1_50KQU_2019-04-27_final.stac-item
2019-04-27 11:54:22	ga_s2am_ard_3-2-1_50KPU_2019-04-27_final.stac-item
2019-04-27 11:54:26	ga_s2am_ard_3-2-1_50KNU_2019-04-27_final.stac-item
2019-04-27 11:54:29	ga_s2am_ard_3-2-1_50KMU_2019-04-27_final.stac-item
2019-04-27 11:54:37	ga_s2am_ard_3-2-1_50KLU_2019-04-27_final.stac-item
2019-04-30 10:23:43	ga_s2am_ard_3-2-1_54KWU_2019-04-30_final.stac-item
2019-04-30 10:23:47	ga_s2am_ard_3-2-1_54KVU_2019-04-30_final.stac-item
2019-04-30 10:23:50	ga_s2am_ard_3-2-1_54KUU_2019-04-30_final.stac-item
2019-04-30 10:23:53	ga_s2am_ard_3-2-1_54KTU_2019-04-30_final.stac-item
2019-04-30 10:23:54	ga_s2am_ard_3-2-1_53KRP_2019-04-30_final.stac-item
2019-04-30 10:24:08	ga_s2am_ard_3-2-1_53JRN_2019-04-30_final.stac-item
2019-04-30 12:04:25	ga_s2am_ard_3-2-1_50KMU_2019-04-30_final.stac-item
2019-04-30 12:04:28	ga_s2am_ard_3-2-1_50KLU_2019-04-30_final.stac-item
2019-04-30 12:04:31	ga_s2am_ard_3-2-1_49KHP_2019-04-30_final.stac-item
2019-04-30 12:04:31	ga_s2am_ard_3-2-1_50KKU_2019-04-30_final.stac-item
2019-04-30 12:04:35	ga_s2am_ard_3-2-1_49KGP_2019-04-30_final.stac-item
2019-04-30 12:04:46	ga_s2am_ard_3-2-1_49JHN_2019-04-30_final.stac-item
2019-04-30 12:04:49	ga_s2am_ard_3-2-1_49JGN_2019-04-30_final.stac-item
2019-05-01 11:34:09	ga_s2am_ard_3-2-1_51KXP_2019-05-01_final.stac-item
2019-05-01 11:34:14	ga_s2am_ard_3-2-1_51KWP_2019-05-01_final.stac-item
2019-05-01 11:34:18	ga_s2am_ard_3-2-1_51KVP_2019-05-01_final.stac-item
2019-05-01 11:34:21	ga_s2am_ard_3-2-1_51KUP_2019-05-01_final.stac-item
2019-05-04 11:44:17	ga_s2am_ard_3-2-1_51KUP_2019-05-04_final.stac-item
2019-05-04 11:44:20	ga_s2am_ard_3-2-1_50KRU_2019-05-04_final.stac-item
2019-05-04 11:44:20	ga_s2am_ard_3-2-1_51KTP_2019-05-04_final.stac-item
2019-05-04 11:44:23	ga_s2am_ard_3-2-1_50KQU_2019-05-04_final.stac-item
2019-05-04 11:44:27	ga_s2am_ard_3-2-1_50KPU_2019-05-04_final.stac-item
2019-05-04 11:44:34	ga_s2am_ard_3-2-1_50JRT_2019-05-04_final.stac-item
2019-05-04 11:44:38	ga_s2am_ard_3-2-1_50JQT_2019-05-04_final.stac-item
2020-09-10 10:53:53	ga_s2am_ard_3-2-1_53KMP_2020-09-10_final.stac-item
2020-09-10 10:53:57	ga_s2am_ard_3-2-1_53KLP_2020-09-10_final.stac-item
2020-09-10 10:54:01	ga_s2am_ard_3-2-1_53KKP_2020-09-10_final.stac-item
2020-09-10 10:54:01	ga_s2am_ard_3-2-1_52KHU_2020-09-10_final.stac-item
2020-09-10 10:54:05	ga_s2am_ard_3-2-1_52KGU_2020-09-10_final.stac-item
2020-09-10 10:54:15	ga_s2am_ard_3-2-1_52JHT_2020-09-10_final.stac-item
2020-09-10 10:54:19	ga_s2am_ard_3-2-1_52JGT_2020-09-10_final.stac-item
2020-09-12 09:53:40	ga_s2am_ard_3-2-1_55KDP_2020-09-12_final.stac-item
2022-05-29 09:33:32	ga_s2am_ard_3-2-1_56KMU_2022-05-29_final.stac-item
2022-05-29 09:33:35	ga_s2am_ard_3-2-1_56KLU_2022-05-29_final.stac-item
2022-05-30 10:43:56	ga_s2am_ard_3-2-1_53KPP_2022-05-30_final.stac-item
2022-05-30 10:43:59	ga_s2am_ard_3-2-1_53KNP_2022-05-30_final.stac-item
2022-05-30 10:44:03	ga_s2am_ard_3-2-1_53KMP_2022-05-30_final.stac-item
2022-05-30 10:44:06	ga_s2am_ard_3-2-1_53KLP_2022-05-30_final.stac-item
2022-06-02 10:54:09	ga_s2am_ard_3-2-1_52KGU_2022-06-02_final.stac-item
2022-06-02 10:54:19	ga_s2am_ard_3-2-1_52JHT_2022-06-02_final.stac-item
2022-06-02 10:54:23	ga_s2am_ard_3-2-1_52JGT_2022-06-02_final.stac-item
2022-06-05 11:04:05	ga_s2am_ard_3-2-1_52KGU_2022-06-05_final.stac-item
2022-06-05 11:04:08	ga_s2am_ard_3-2-1_52KFU_2022-06-05_final.stac-item
2022-06-05 11:04:11	ga_s2am_ard_3-2-1_52KEU_2022-06-05_final.stac-item
2022-06-05 11:04:14	ga_s2am_ard_3-2-1_52KDU_2022-06-05_final.stac-item
2022-06-11 09:43:32	ga_s2am_ard_3-2-1_56KLU_2022-06-11_final.stac-item
2022-06-11 09:43:36	ga_s2am_ard_3-2-1_56KKU_2022-06-11_final.stac-item
2022-06-11 09:43:36	ga_s2am_ard_3-2-1_55KHP_2022-06-11_final.stac-item
2022-06-11 09:43:40	ga_s2am_ard_3-2-1_55KGP_2022-06-11_final.stac-item
2022-06-11 09:43:44	ga_s2am_ard_3-2-1_55KFP_2022-06-11_final.stac-item
2022-06-11 09:43:50	ga_s2am_ard_3-2-1_55JHN_2022-06-11_final.stac-item
2022-06-11 09:43:54	ga_s2am_ard_3-2-1_55JGN_2022-06-11_final.stac-item
2022-06-12 10:53:59	ga_s2am_ard_3-2-1_53KMP_2022-06-12_final.stac-item
2022-06-12 10:54:04	ga_s2am_ard_3-2-1_53KLP_2022-06-12_final.stac-item
2022-06-12 10:54:07	ga_s2am_ard_3-2-1_53KKP_2022-06-12_final.stac-item
2022-06-12 10:54:07	ga_s2am_ard_3-2-1_52KHU_2022-06-12_final.stac-item
2022-06-12 10:54:11	ga_s2am_ard_3-2-1_52KGU_2022-06-12_final.stac-item
2022-06-12 10:54:21	ga_s2am_ard_3-2-1_52JHT_2022-06-12_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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