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
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_52KBC_2017-01-25_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_52KCC_2017-01-25_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_52KDC_2017-01-25_final.stac-item
2017-01-25 11:08:57	ga_s2am_ard_3-2-1_52KEC_2017-01-25_final.stac-item
2017-01-26 10:42:01	ga_s2am_ard_3-2-1_53KMT_2017-01-26_final.stac-item
2017-01-26 10:42:01	ga_s2am_ard_3-2-1_53KNT_2017-01-26_final.stac-item
2017-01-26 10:42:01	ga_s2am_ard_3-2-1_53KPT_2017-01-26_final.stac-item
2017-01-26 10:42:01	ga_s2am_ard_3-2-1_53KQT_2017-01-26_final.stac-item
2017-01-27 10:07:55	ga_s2am_ard_3-2-1_54KXC_2017-01-27_final.stac-item
2017-01-27 10:07:55	ga_s2am_ard_3-2-1_54KYC_2017-01-27_final.stac-item
2017-01-27 10:07:55	ga_s2am_ard_3-2-1_54KZB_2017-01-27_final.stac-item
2017-01-27 10:07:55	ga_s2am_ard_3-2-1_54KZC_2017-01-27_final.stac-item
2017-01-27 10:07:55	ga_s2am_ard_3-2-1_55KBT_2017-01-27_final.stac-item
2017-01-29 10:52:10	ga_s2am_ard_3-2-1_53KKT_2017-01-29_final.stac-item
2017-01-29 10:52:10	ga_s2am_ard_3-2-1_53KLT_2017-01-29_final.stac-item
2017-01-29 10:52:10	ga_s2am_ard_3-2-1_53KMT_2017-01-29_final.stac-item
2017-01-29 10:52:10	ga_s2am_ard_3-2-1_52KHB_2017-01-29_final.stac-item
2017-01-29 10:52:10	ga_s2am_ard_3-2-1_52KHC_2017-01-29_final.stac-item
2017-02-05 10:42:31	ga_s2am_ard_3-2-1_53KMT_2017-02-05_final.stac-item
2017-02-05 10:42:31	ga_s2am_ard_3-2-1_53KNT_2017-02-05_final.stac-item
2017-02-05 10:42:31	ga_s2am_ard_3-2-1_53KPT_2017-02-05_final.stac-item
2017-02-05 10:42:31	ga_s2am_ard_3-2-1_53KQT_2017-02-05_final.stac-item
2017-02-06 10:07:38	ga_s2am_ard_3-2-1_54KXC_2017-02-06_final.stac-item
2017-02-06 10:07:38	ga_s2am_ard_3-2-1_54KYC_2017-02-06_final.stac-item
2017-02-06 10:07:38	ga_s2am_ard_3-2-1_54KZB_2017-02-06_final.stac-item
2017-02-06 10:07:38	ga_s2am_ard_3-2-1_54KZC_2017-02-06_final.stac-item
2017-02-06 10:07:38	ga_s2am_ard_3-2-1_55KBT_2017-02-06_final.stac-item
2017-02-10 11:32:51	ga_s2am_ard_3-2-1_51KXT_2017-02-10_final.stac-item
2017-02-15 10:37:21	ga_s2am_ard_3-2-1_53KMT_2017-02-15_final.stac-item
2017-02-15 10:37:21	ga_s2am_ard_3-2-1_53KNT_2017-02-15_final.stac-item
2017-02-15 10:37:21	ga_s2am_ard_3-2-1_53KPT_2017-02-15_final.stac-item
2017-02-15 10:37:21	ga_s2am_ard_3-2-1_53KQT_2017-02-15_final.stac-item
2017-02-16 10:07:16	ga_s2am_ard_3-2-1_54KXC_2017-02-16_final.stac-item
2017-02-16 10:07:16	ga_s2am_ard_3-2-1_54KYC_2017-02-16_final.stac-item
2017-02-16 10:07:16	ga_s2am_ard_3-2-1_54KZB_2017-02-16_final.stac-item
2017-02-16 10:07:16	ga_s2am_ard_3-2-1_54KZC_2017-02-16_final.stac-item
2017-02-16 10:07:16	ga_s2am_ard_3-2-1_55KBT_2017-02-16_final.stac-item
2017-02-17 09:42:07	ga_s2am_ard_3-2-1_55KGT_2017-02-17_final.stac-item
2017-02-17 09:42:07	ga_s2am_ard_3-2-1_55KHS_2017-02-17_final.stac-item
2017-02-21 11:00:21	ga_s2am_ard_3-2-1_53KKT_2017-02-21_final.stac-item
2017-02-21 11:00:21	ga_s2am_ard_3-2-1_52KEC_2017-02-21_final.stac-item
2017-02-21 11:00:21	ga_s2am_ard_3-2-1_52KFC_2017-02-21_final.stac-item
2017-02-21 11:00:21	ga_s2am_ard_3-2-1_52KGC_2017-02-21_final.stac-item
2017-02-21 11:00:21	ga_s2am_ard_3-2-1_52KHC_2017-02-21_final.stac-item
2017-03-25 11:38:25	ga_s2am_ard_3-2-1_50KQC_2017-03-25_final.stac-item
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55KET_2018-10-23_final.stac-item
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55KFT_2018-10-23_final.stac-item
2018-10-23 09:50:51	ga_s2am_ard_3-2-1_55KGT_2018-10-23_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_54KZB_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_54KZC_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55KBT_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55KCT_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55KDT_2018-10-26_final.stac-item
2018-10-26 09:57:04	ga_s2am_ard_3-2-1_55KET_2018-10-26_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54KXC_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54KYC_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54KZB_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_54KZC_2018-10-29_final.stac-item
2018-10-29 10:07:01	ga_s2am_ard_3-2-1_55KBT_2018-10-29_final.stac-item
2018-11-05 09:57:03	ga_s2am_ard_3-2-1_54KZB_2018-11-05_final.stac-item
2018-11-05 09:57:03	ga_s2am_ard_3-2-1_54KZC_2018-11-05_final.stac-item
2018-11-05 09:57:03	ga_s2am_ard_3-2-1_55KBT_2018-11-05_final.stac-item
2018-11-05 09:57:03	ga_s2am_ard_3-2-1_55KCT_2018-11-05_final.stac-item
2018-11-05 09:57:03	ga_s2am_ard_3-2-1_55KDT_2018-11-05_final.stac-item
2018-11-05 09:57:03	ga_s2am_ard_3-2-1_55KET_2018-11-05_final.stac-item
2018-11-14 10:32:57	ga_s2am_ard_3-2-1_53KRS_2018-11-14_final.stac-item
2018-11-15 10:02:24	ga_s2am_ard_3-2-1_55KET_2018-11-15_final.stac-item
2018-11-15 10:02:28	ga_s2am_ard_3-2-1_55KDT_2018-11-15_final.stac-item
2018-11-15 10:02:31	ga_s2am_ard_3-2-1_55KCT_2018-11-15_final.stac-item
2018-11-15 10:02:34	ga_s2am_ard_3-2-1_55KBT_2018-11-15_final.stac-item
2018-11-15 10:02:36	ga_s2am_ard_3-2-1_54KZC_2018-11-15_final.stac-item
2018-11-15 10:02:49	ga_s2am_ard_3-2-1_54KZB_2018-11-15_final.stac-item
2018-11-16 11:12:55	ga_s2am_ard_3-2-1_52KEC_2018-11-16_final.stac-item
2018-11-16 11:12:58	ga_s2am_ard_3-2-1_52KDC_2018-11-16_final.stac-item
2018-11-16 11:13:02	ga_s2am_ard_3-2-1_52KCC_2018-11-16_final.stac-item
2018-11-16 11:13:08	ga_s2am_ard_3-2-1_52KBC_2018-11-16_final.stac-item
2019-01-07 11:53:16	ga_s2am_ard_3-2-1_50KPC_2019-01-07_final.stac-item
2019-01-07 11:53:19	ga_s2am_ard_3-2-1_50KNC_2019-01-07_final.stac-item
2019-01-07 11:53:26	ga_s2am_ard_3-2-1_50KMC_2019-01-07_final.stac-item
2019-01-10 12:03:15	ga_s2am_ard_3-2-1_50KNC_2019-01-10_final.stac-item
2019-01-10 12:03:19	ga_s2am_ard_3-2-1_50KMC_2019-01-10_final.stac-item
2019-01-10 12:03:22	ga_s2am_ard_3-2-1_50KLC_2019-01-10_final.stac-item
2019-01-20 12:03:16	ga_s2am_ard_3-2-1_50KNC_2019-01-20_final.stac-item
2019-01-20 12:03:20	ga_s2am_ard_3-2-1_50KMC_2019-01-20_final.stac-item
2019-01-20 12:03:23	ga_s2am_ard_3-2-1_50KLC_2019-01-20_final.stac-item
2019-03-19 09:42:32	ga_s2am_ard_3-2-1_55KHS_2019-03-19_final.stac-item
2019-03-19 09:42:34	ga_s2am_ard_3-2-1_55KGT_2019-03-19_final.stac-item
2019-03-19 09:42:40	ga_s2am_ard_3-2-1_55KHS_2019-03-19_final.stac-item
2019-03-24 10:32:42	ga_s2am_ard_3-2-1_54KUC_2019-03-24_final.stac-item
2019-03-24 10:32:46	ga_s2am_ard_3-2-1_54KTC_2019-03-24_final.stac-item
2019-03-24 10:32:46	ga_s2am_ard_3-2-1_53KRT_2019-03-24_final.stac-item
2019-03-24 10:32:50	ga_s2am_ard_3-2-1_53KQT_2019-03-24_final.stac-item
2019-03-24 10:33:01	ga_s2am_ard_3-2-1_53KRS_2019-03-24_final.stac-item
2019-03-29 09:42:33	ga_s2am_ard_3-2-1_55KGT_2019-03-29_final.stac-item
2019-03-29 09:42:43	ga_s2am_ard_3-2-1_55KHS_2019-03-29_final.stac-item
2019-03-29 11:23:02	ga_s2am_ard_3-2-1_52KCC_2019-03-29_final.stac-item
2019-03-29 11:23:06	ga_s2am_ard_3-2-1_52KBC_2019-03-29_final.stac-item
2019-03-29 11:23:06	ga_s2am_ard_3-2-1_51KZT_2019-03-29_final.stac-item
2019-03-29 11:23:10	ga_s2am_ard_3-2-1_51KYT_2019-03-29_final.stac-item
2019-03-29 11:23:13	ga_s2am_ard_3-2-1_51KXT_2019-03-29_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

All years