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
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54GYV_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54GYA_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYB_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYC_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYD_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYE_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYF_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYG_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYH_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYJ_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_54HYK_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55GBR_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBA_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBB_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBC_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBD_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBE_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBS_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBT_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBU_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55HBV_2015-12-28_final.stac-item
2015-12-28 09:58:43	ga_s2am_ard_3-2-1_55GBQ_2015-12-28_final
2016-02-02 10:10:45	ga_s2am_ard_3-2-1_54LZJ_2016-02-02_final.stac-item
2016-02-02 10:10:45	ga_s2am_ard_3-2-1_54LZK_2016-02-02_final.stac-item
2016-02-02 10:10:56	ga_s2am_ard_3-2-1_54KYG_2016-02-02_final.stac-item
2016-02-02 10:10:56	ga_s2am_ard_3-2-1_54KZG_2016-02-02_final.stac-item
2016-02-02 10:10:56	ga_s2am_ard_3-2-1_54LZH_2016-02-02_final.stac-item
2016-02-02 10:10:56	ga_s2am_ard_3-2-1_54LZJ_2016-02-02_final.stac-item
2019-03-29 09:48:08	ga_s2am_ard_3-2-1_55GBR_2019-03-29_final.stac-item
2019-03-29 09:48:08	ga_s2am_ard_3-2-1_54GYA_2019-03-29_final.stac-item
2019-10-11 10:03:34	ga_s2am_ard_3-2-1_54KYV_2019-10-11_final.stac-item
2019-10-11 10:03:45	ga_s2am_ard_3-2-1_54KYU_2019-10-11_final.stac-item
2019-10-14 10:10:43	ga_s2am_ard_3-2-1_54LZL_2019-10-14_final.stac-item
2019-10-14 10:11:45	ga_s2am_ard_3-2-1_54KYG_2019-10-14_final.stac-item
2019-10-14 10:11:59	ga_s2am_ard_3-2-1_54KYF_2019-10-14_final.stac-item
2019-10-14 10:12:13	ga_s2am_ard_3-2-1_54KYE_2019-10-14_final.stac-item
2019-10-14 10:12:28	ga_s2am_ard_3-2-1_54KYD_2019-10-14_final.stac-item
2019-10-14 10:12:43	ga_s2am_ard_3-2-1_54KYC_2019-10-14_final.stac-item
2019-10-14 10:12:57	ga_s2am_ard_3-2-1_54KYB_2019-10-14_final.stac-item
2019-10-14 10:13:08	ga_s2am_ard_3-2-1_54KZA_2019-10-14_final.stac-item
2019-10-14 10:13:11	ga_s2am_ard_3-2-1_54KYA_2019-10-14_final.stac-item
2019-10-14 10:13:26	ga_s2am_ard_3-2-1_54KYV_2019-10-14_final.stac-item
2019-10-14 10:13:40	ga_s2am_ard_3-2-1_54KYU_2019-10-14_final.stac-item
2019-10-14 10:13:55	ga_s2am_ard_3-2-1_54JYT_2019-10-14_final.stac-item
2019-10-14 10:14:09	ga_s2am_ard_3-2-1_54JYS_2019-10-14_final.stac-item
2019-10-24 10:10:44	ga_s2am_ard_3-2-1_54LZL_2019-10-24_final.stac-item
2019-10-24 10:10:58	ga_s2am_ard_3-2-1_54LZK_2019-10-24_final.stac-item
2019-10-24 10:11:12	ga_s2am_ard_3-2-1_54LZJ_2019-10-24_final.stac-item
2019-10-24 10:11:27	ga_s2am_ard_3-2-1_54LZH_2019-10-24_final.stac-item
2019-10-24 10:11:41	ga_s2am_ard_3-2-1_54KZG_2019-10-24_final.stac-item
2019-10-24 10:11:45	ga_s2am_ard_3-2-1_54KYG_2019-10-24_final.stac-item
2019-10-24 10:11:56	ga_s2am_ard_3-2-1_54KZF_2019-10-24_final.stac-item
2019-10-24 10:11:59	ga_s2am_ard_3-2-1_54KYF_2019-10-24_final.stac-item
2019-10-24 10:12:10	ga_s2am_ard_3-2-1_54KZE_2019-10-24_final.stac-item
2019-10-24 10:12:14	ga_s2am_ard_3-2-1_54KYE_2019-10-24_final.stac-item
2019-10-24 10:12:25	ga_s2am_ard_3-2-1_54KZD_2019-10-24_final.stac-item
2019-10-24 10:12:28	ga_s2am_ard_3-2-1_54KYD_2019-10-24_final.stac-item
2019-10-24 10:12:39	ga_s2am_ard_3-2-1_54KZC_2019-10-24_final.stac-item
2019-10-24 10:12:43	ga_s2am_ard_3-2-1_54KYC_2019-10-24_final.stac-item
2023-11-22 10:13:48	ga_s2am_ard_3-2-1_54JYT_2023-11-22_final
2023-11-22 10:13:59	ga_s2am_ard_3-2-1_54JYS_2023-11-22_final
2023-11-23 09:48:19	ga_s2am_ard_3-2-1_55GBQ_2023-11-23_final
2023-11-23 09:48:19	ga_s2am_ard_3-2-1_54GYV_2023-11-23_final
2023-11-23 09:48:33	ga_s2am_ard_3-2-1_54GYU_2023-11-23_nrt
2023-11-23 09:48:33	ga_s2am_ard_3-2-1_55GBP_2023-11-23_nrt
2023-11-23 09:48:47	ga_s2am_ard_3-2-1_54GYT_2023-11-23_nrt
2023-11-23 09:48:56	ga_s2am_ard_3-2-1_54GYS_2023-11-23_nrt
2023-11-26 09:56:02	ga_s2am_ard_3-2-1_55HBD_2023-11-26_final
2023-11-26 09:56:04	ga_s2am_ard_3-2-1_54HYJ_2023-11-26_final
2023-11-26 09:56:17	ga_s2am_ard_3-2-1_55HBC_2023-11-26_final
2023-11-26 09:56:19	ga_s2am_ard_3-2-1_54HYH_2023-11-26_final
2023-11-26 09:56:31	ga_s2am_ard_3-2-1_55HBB_2023-11-26_final
2023-11-26 09:56:33	ga_s2am_ard_3-2-1_54HYG_2023-11-26_final
2023-11-26 09:56:46	ga_s2am_ard_3-2-1_55HBA_2023-11-26_final
2023-11-26 09:56:48	ga_s2am_ard_3-2-1_54HYF_2023-11-26_final
2023-11-26 09:57:01	ga_s2am_ard_3-2-1_55HBV_2023-11-26_final
2023-11-26 09:57:02	ga_s2am_ard_3-2-1_54HYE_2023-11-26_final
2023-11-26 09:57:15	ga_s2am_ard_3-2-1_55HBU_2023-11-26_final
2023-11-26 09:57:16	ga_s2am_ard_3-2-1_54HYD_2023-11-26_final
2023-11-26 09:57:30	ga_s2am_ard_3-2-1_55HBT_2023-11-26_final
2023-11-26 09:57:31	ga_s2am_ard_3-2-1_54HYC_2023-11-26_final
2023-11-26 09:57:44	ga_s2am_ard_3-2-1_55HBS_2023-11-26_final
2023-11-26 09:57:45	ga_s2am_ard_3-2-1_54HYB_2023-11-26_final
2023-11-26 09:57:59	ga_s2am_ard_3-2-1_55GBR_2023-11-26_final
2023-11-26 09:57:59	ga_s2am_ard_3-2-1_54GYA_2023-11-26_final
2023-11-26 09:58:13	ga_s2am_ard_3-2-1_55GBQ_2023-11-26_final
2023-11-26 09:58:14	ga_s2am_ard_3-2-1_54GYV_2023-11-26_final
2023-11-26 09:58:23	ga_s2am_ard_3-2-1_54GYU_2023-11-26_nrt
2023-11-26 09:58:23	ga_s2am_ard_3-2-1_55GBP_2023-11-26_final
2023-11-29 10:04:46	ga_s2am_ard_3-2-1_54JYP_2023-11-29_final
2023-11-29 10:04:58	ga_s2am_ard_3-2-1_55JBH_2023-11-29_final
2023-11-29 10:05:01	ga_s2am_ard_3-2-1_54JYN_2023-11-29_final
2023-11-29 10:05:12	ga_s2am_ard_3-2-1_55JBG_2023-11-29_final
2023-11-29 10:05:15	ga_s2am_ard_3-2-1_54JYM_2023-11-29_final
2023-11-29 10:05:27	ga_s2am_ard_3-2-1_55JBF_2023-11-29_final
2023-11-29 10:05:30	ga_s2am_ard_3-2-1_54JYL_2023-11-29_final
2023-11-29 10:05:41	ga_s2am_ard_3-2-1_55HBE_2023-11-29_final
2023-11-29 10:05:44	ga_s2am_ard_3-2-1_54HYK_2023-11-29_final
2023-11-29 10:05:56	ga_s2am_ard_3-2-1_55HBD_2023-11-29_final
2023-11-29 10:05:58	ga_s2am_ard_3-2-1_54HYJ_2023-11-29_final

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