Search ga_s2bm_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
2019-10-03 11:36:52	ga_s2bm_ard_3-2-1_50HPJ_2019-10-03_final.stac-item
2019-10-03 11:37:07	ga_s2bm_ard_3-2-1_50HPH_2019-10-03_final.stac-item
2019-10-06 11:44:24	ga_s2bm_ard_3-2-1_50KPU_2019-10-06_final.stac-item
2019-10-06 11:44:39	ga_s2bm_ard_3-2-1_50JPT_2019-10-06_final.stac-item
2019-10-06 11:44:53	ga_s2bm_ard_3-2-1_50JPS_2019-10-06_final.stac-item
2019-10-06 11:45:08	ga_s2bm_ard_3-2-1_50JPR_2019-10-06_final.stac-item
2019-10-06 11:45:22	ga_s2bm_ard_3-2-1_50JPQ_2019-10-06_final.stac-item
2019-10-06 11:45:37	ga_s2bm_ard_3-2-1_50JPP_2019-10-06_final.stac-item
2019-10-06 11:45:51	ga_s2bm_ard_3-2-1_50JPN_2019-10-06_final.stac-item
2019-10-06 11:46:06	ga_s2bm_ard_3-2-1_50JPM_2019-10-06_final.stac-item
2019-10-06 11:46:20	ga_s2bm_ard_3-2-1_50JPL_2019-10-06_final.stac-item
2019-10-06 11:46:34	ga_s2bm_ard_3-2-1_50HPK_2019-10-06_final.stac-item
2019-10-06 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2019-10-06_final.stac-item
2019-10-06 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2019-10-06_final.stac-item
2019-10-16 11:44:29	ga_s2bm_ard_3-2-1_50KPU_2019-10-16_final.stac-item
2019-10-16 11:44:39	ga_s2bm_ard_3-2-1_50JPT_2019-10-16_final.stac-item
2019-10-16 11:44:54	ga_s2bm_ard_3-2-1_50JPS_2019-10-16_final.stac-item
2019-10-16 11:45:08	ga_s2bm_ard_3-2-1_50JPR_2019-10-16_final.stac-item
2019-10-16 11:45:22	ga_s2bm_ard_3-2-1_50JPQ_2019-10-16_final.stac-item
2019-10-16 11:45:37	ga_s2bm_ard_3-2-1_50JPP_2019-10-16_final.stac-item
2019-10-16 11:45:51	ga_s2bm_ard_3-2-1_50JPN_2019-10-16_final.stac-item
2019-10-16 11:46:06	ga_s2bm_ard_3-2-1_50JPM_2019-10-16_final.stac-item
2019-10-16 11:46:20	ga_s2bm_ard_3-2-1_50JPL_2019-10-16_final.stac-item
2019-10-16 11:46:35	ga_s2bm_ard_3-2-1_50HPK_2019-10-16_final.stac-item
2019-10-16 11:46:49	ga_s2bm_ard_3-2-1_50HPJ_2019-10-16_final.stac-item
2019-10-16 11:47:03	ga_s2bm_ard_3-2-1_50HPH_2019-10-16_final.stac-item
2019-10-19 11:53:22	ga_s2bm_ard_3-2-1_50KPC_2019-10-19_final.stac-item
2019-10-19 11:53:37	ga_s2bm_ard_3-2-1_50KPB_2019-10-19_final.stac-item
2019-10-19 11:53:51	ga_s2bm_ard_3-2-1_50KPA_2019-10-19_final.stac-item
2019-10-19 11:54:06	ga_s2bm_ard_3-2-1_50KPV_2019-10-19_final.stac-item
2019-10-19 11:54:20	ga_s2bm_ard_3-2-1_50KPU_2019-10-19_final.stac-item
2019-10-19 11:54:34	ga_s2bm_ard_3-2-1_50JPT_2019-10-19_final.stac-item
2019-10-19 11:54:49	ga_s2bm_ard_3-2-1_50JPS_2019-10-19_final.stac-item
2019-10-29 11:53:22	ga_s2bm_ard_3-2-1_50KPC_2019-10-29_final.stac-item
2019-10-29 11:53:36	ga_s2bm_ard_3-2-1_50KPB_2019-10-29_final.stac-item
2019-10-29 11:53:51	ga_s2bm_ard_3-2-1_50KPA_2019-10-29_final.stac-item
2019-10-29 11:54:05	ga_s2bm_ard_3-2-1_50KPV_2019-10-29_final.stac-item
2019-10-29 11:54:20	ga_s2bm_ard_3-2-1_50KPU_2019-10-29_final.stac-item
2019-10-29 11:54:34	ga_s2bm_ard_3-2-1_50JPT_2019-10-29_final.stac-item
2019-10-29 11:54:49	ga_s2bm_ard_3-2-1_50JPS_2019-10-29_final.stac-item
2023-12-11 11:36:49	ga_s2bm_ard_3-2-1_50HPJ_2023-12-11_final
2023-12-11 11:37:03	ga_s2bm_ard_3-2-1_50HPH_2023-12-11_final
2023-12-11 11:37:18	ga_s2bm_ard_3-2-1_50HPG_2023-12-11_final
2023-12-11 11:37:27	ga_s2bm_ard_3-2-1_50HPF_2023-12-11_nrt
2023-12-14 11:46:32	ga_s2bm_ard_3-2-1_50HPK_2023-12-14_final
2023-12-14 11:46:46	ga_s2bm_ard_3-2-1_50HPJ_2023-12-14_final
2023-12-14 11:47:00	ga_s2bm_ard_3-2-1_50HPH_2023-12-14_final
2023-12-14 11:47:15	ga_s2bm_ard_3-2-1_50HPG_2023-12-14_final
2023-12-14 11:47:28	ga_s2bm_ard_3-2-1_50HPF_2023-12-14_nrt
2023-12-17 11:51:26	ga_s2bm_ard_3-2-1_50LPL_2023-12-17_nrt
2023-12-17 11:51:39	ga_s2bm_ard_3-2-1_50LPK_2023-12-17_nrt
2023-12-17 11:51:53	ga_s2bm_ard_3-2-1_50LPJ_2023-12-17_nrt
2023-12-17 11:52:08	ga_s2bm_ard_3-2-1_50LPH_2023-12-17_nrt
2023-12-17 11:52:20	ga_s2bm_ard_3-2-1_50KPG_2023-12-17_nrt
2023-12-17 11:52:26	ga_s2bm_ard_3-2-1_50KPG_2023-12-17_nrt
2023-12-17 11:52:37	ga_s2bm_ard_3-2-1_50KPF_2023-12-17_final
2023-12-20 12:00:37	ga_s2bm_ard_3-2-1_50LPP_2023-12-20_nrt
2023-12-20 12:00:52	ga_s2bm_ard_3-2-1_50LPN_2023-12-20_nrt
2023-12-20 12:01:06	ga_s2bm_ard_3-2-1_50LPM_2023-12-20_nrt
2023-12-20 12:01:21	ga_s2bm_ard_3-2-1_50LPL_2023-12-20_nrt
2023-12-20 12:01:33	ga_s2bm_ard_3-2-1_50LPK_2023-12-20_nrt
2023-12-24 11:44:24	ga_s2bm_ard_3-2-1_50KPU_2023-12-24_final
2023-12-24 11:44:39	ga_s2bm_ard_3-2-1_50JPT_2023-12-24_final
2023-12-24 11:44:54	ga_s2bm_ard_3-2-1_50JPS_2023-12-24_final
2023-12-24 11:45:08	ga_s2bm_ard_3-2-1_50JPR_2023-12-24_final
2023-12-24 11:45:22	ga_s2bm_ard_3-2-1_50JPQ_2023-12-24_final
2023-12-24 11:45:37	ga_s2bm_ard_3-2-1_50JPP_2023-12-24_final
2023-12-24 11:45:51	ga_s2bm_ard_3-2-1_50JPN_2023-12-24_final
2023-12-24 11:46:06	ga_s2bm_ard_3-2-1_50JPM_2023-12-24_final
2023-12-24 11:46:20	ga_s2bm_ard_3-2-1_50JPL_2023-12-24_final
2023-12-30 12:00:38	ga_s2bm_ard_3-2-1_50LPP_2023-12-30_nrt
2023-12-30 12:00:52	ga_s2bm_ard_3-2-1_50LPN_2023-12-30_nrt
2023-12-30 12:01:07	ga_s2bm_ard_3-2-1_50LPM_2023-12-30_nrt
2023-12-30 12:01:21	ga_s2bm_ard_3-2-1_50LPL_2023-12-30_nrt
2023-12-30 12:01:34	ga_s2bm_ard_3-2-1_50LPK_2023-12-30_nrt
2023-12-31 11:37:22	ga_s2bm_ard_3-2-1_50HPG_2023-12-31_final
2023-12-31 11:37:31	ga_s2bm_ard_3-2-1_50HPF_2023-12-31_nrt
2024-01-06 11:51:27	ga_s2bm_ard_3-2-1_50LPL_2024-01-06_nrt
2024-01-06 11:51:39	ga_s2bm_ard_3-2-1_50LPK_2024-01-06_nrt
2024-01-09 12:00:36	ga_s2bm_ard_3-2-1_50LPP_2024-01-09_nrt
2024-01-09 12:00:50	ga_s2bm_ard_3-2-1_50LPN_2024-01-09_nrt
2024-01-09 12:01:01	ga_s2bm_ard_3-2-1_50LPM_2024-01-09_nrt
2024-01-09 12:01:08	ga_s2bm_ard_3-2-1_50LPM_2024-01-09_nrt
2024-01-09 12:01:19	ga_s2bm_ard_3-2-1_50LPL_2024-01-09_nrt
2024-01-10 11:36:50	ga_s2bm_ard_3-2-1_50HPJ_2024-01-10_final
2024-01-13 11:45:48	ga_s2bm_ard_3-2-1_50JPN_2024-01-13_final
2024-01-13 11:46:03	ga_s2bm_ard_3-2-1_50JPM_2024-01-13_final
2024-01-13 11:46:17	ga_s2bm_ard_3-2-1_50JPL_2024-01-13_final
2024-01-13 11:46:32	ga_s2bm_ard_3-2-1_50HPK_2024-01-13_final
2024-01-13 11:46:46	ga_s2bm_ard_3-2-1_50HPJ_2024-01-13_final
2024-01-13 11:47:00	ga_s2bm_ard_3-2-1_50HPH_2024-01-13_final
2024-01-13 11:47:15	ga_s2bm_ard_3-2-1_50HPG_2024-01-13_final
2024-01-13 11:47:28	ga_s2bm_ard_3-2-1_50HPF_2024-01-13_nrt
2024-01-16 11:53:20	ga_s2bm_ard_3-2-1_50KPC_2024-01-16_final
2024-01-16 11:53:34	ga_s2bm_ard_3-2-1_50KPB_2024-01-16_final
2024-01-16 11:53:49	ga_s2bm_ard_3-2-1_50KPA_2024-01-16_final
2024-01-16 11:54:03	ga_s2bm_ard_3-2-1_50KPV_2024-01-16_final
2024-01-16 11:54:18	ga_s2bm_ard_3-2-1_50KPU_2024-01-16_final
2024-01-16 11:54:32	ga_s2bm_ard_3-2-1_50JPT_2024-01-16_final
2024-01-19 12:01:24	ga_s2bm_ard_3-2-1_50LPL_2024-01-19_nrt

Return to ga_s2bm_ard_3 whole collection overview

ga_s2bm_ard_3: Geoscience Australia Sentinel 2B MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years