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
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53HPD_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53HPE_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53JPF_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53JPG_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53JPH_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53JPJ_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53JPK_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53JPL_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53JPM_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53JPN_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KPP_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KPQ_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KPR_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KPS_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KQQ_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KQR_2018-02-07_final.stac-item
2018-02-07 10:32:29	ga_s2am_ard_3-2-1_53KQS_2018-02-07_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53JPM_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53JPN_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53KPP_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53KPQ_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53KPR_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53KPS_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53KQQ_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53KQR_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53KQS_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53HPD_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53HPE_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53JPF_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53JPG_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53JPH_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53JPJ_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53JPK_2018-02-17_final.stac-item
2018-02-17 10:27:04	ga_s2am_ard_3-2-1_53JPL_2018-02-17_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KQB_2018-02-20_final
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53LPC_2018-02-20_final
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53LPD_2018-02-20_final
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53LQC_2018-02-20_final
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KPA_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KPB_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KPQ_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KPR_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KPS_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KPT_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KPU_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KPV_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KQA_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KQQ_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KQR_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KQS_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KQT_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KQU_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53KQV_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53LPE_2018-02-20_final.stac-item
2018-02-20 10:37:24	ga_s2am_ard_3-2-1_53LQD_2018-02-20_final.stac-item
2019-07-15 10:41:40	ga_s2am_ard_3-2-1_53LQC_2019-07-15_final
2019-07-15 10:41:43	ga_s2am_ard_3-2-1_53LPC_2019-07-15_final
2019-07-15 10:41:54	ga_s2am_ard_3-2-1_53KQB_2019-07-15_final
2019-07-15 10:41:57	ga_s2am_ard_3-2-1_53KPB_2019-07-15_final.stac-item
2019-07-15 10:42:08	ga_s2am_ard_3-2-1_53KQA_2019-07-15_final.stac-item
2019-07-15 10:42:12	ga_s2am_ard_3-2-1_53KPA_2019-07-15_final.stac-item
2019-07-15 10:42:23	ga_s2am_ard_3-2-1_53KQV_2019-07-15_final.stac-item
2019-07-15 10:42:26	ga_s2am_ard_3-2-1_53KPV_2019-07-15_final.stac-item
2019-07-15 10:42:37	ga_s2am_ard_3-2-1_53KQU_2019-07-15_final.stac-item
2019-07-15 10:42:41	ga_s2am_ard_3-2-1_53KPU_2019-07-15_final.stac-item
2019-07-15 10:42:52	ga_s2am_ard_3-2-1_53KQT_2019-07-15_final.stac-item
2019-07-15 10:42:55	ga_s2am_ard_3-2-1_53KPT_2019-07-15_final.stac-item
2019-07-15 10:43:06	ga_s2am_ard_3-2-1_53KQS_2019-07-15_final.stac-item
2019-07-15 10:43:10	ga_s2am_ard_3-2-1_53KPS_2019-07-15_final.stac-item
2019-07-15 10:43:20	ga_s2am_ard_3-2-1_53KQR_2019-07-15_final.stac-item
2019-07-15 10:43:24	ga_s2am_ard_3-2-1_53KPR_2019-07-15_final.stac-item
2019-07-15 10:43:30	ga_s2am_ard_3-2-1_53KQQ_2019-07-15_final.stac-item
2019-07-15 10:43:39	ga_s2am_ard_3-2-1_53KPQ_2019-07-15_final.stac-item
2023-09-09 10:34:56	ga_s2am_ard_3-2-1_53JPK_2023-09-09_final
2023-09-09 10:35:10	ga_s2am_ard_3-2-1_53JPJ_2023-09-09_final
2023-09-09 10:35:25	ga_s2am_ard_3-2-1_53JPH_2023-09-09_final
2023-09-09 10:35:39	ga_s2am_ard_3-2-1_53JPG_2023-09-09_final
2023-09-09 10:35:54	ga_s2am_ard_3-2-1_53JPF_2023-09-09_final
2023-09-09 10:36:08	ga_s2am_ard_3-2-1_53HPE_2023-09-09_final
2023-09-09 10:36:22	ga_s2am_ard_3-2-1_53HPD_2023-09-09_final
2023-09-12 10:43:06	ga_s2am_ard_3-2-1_53KQS_2023-09-12_final
2023-09-12 10:43:19	ga_s2am_ard_3-2-1_53KQR_2023-09-12_final
2023-09-12 10:43:24	ga_s2am_ard_3-2-1_53KPR_2023-09-12_final
2023-09-12 10:43:29	ga_s2am_ard_3-2-1_53KQQ_2023-09-12_final
2023-09-15 10:50:07	ga_s2am_ard_3-2-1_53LQJ_2023-09-15_final
2023-09-15 10:50:20	ga_s2am_ard_3-2-1_53LQH_2023-09-15_final
2023-09-15 10:50:31	ga_s2am_ard_3-2-1_53LQG_2023-09-15_final
2023-09-29 10:33:37	ga_s2am_ard_3-2-1_53KQQ_2023-09-29_final
2023-09-29 10:33:40	ga_s2am_ard_3-2-1_53KPQ_2023-09-29_final
2023-09-29 10:33:55	ga_s2am_ard_3-2-1_53KPP_2023-09-29_final
2023-09-29 10:34:09	ga_s2am_ard_3-2-1_53JPN_2023-09-29_final
2023-09-29 10:34:24	ga_s2am_ard_3-2-1_53JPM_2023-09-29_final
2023-09-29 10:34:38	ga_s2am_ard_3-2-1_53JPL_2023-09-29_final
2023-09-29 10:34:49	ga_s2am_ard_3-2-1_53JPK_2023-09-29_final
2023-09-29 10:34:55	ga_s2am_ard_3-2-1_53JPK_2023-09-29_final
2023-09-29 10:35:07	ga_s2am_ard_3-2-1_53JPJ_2023-09-29_final
2023-09-29 10:35:22	ga_s2am_ard_3-2-1_53JPH_2023-09-29_final
2023-09-29 10:35:36	ga_s2am_ard_3-2-1_53JPG_2023-09-29_final
2023-09-29 10:35:51	ga_s2am_ard_3-2-1_53JPF_2023-09-29_final
2023-09-29 10:36:05	ga_s2am_ard_3-2-1_53HPE_2023-09-29_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