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
2019-01-10 11:10:24	ga_s2bm_ard_3-2-1_52LHN_2019-01-10_final.stac-item
2019-01-10 11:10:36	ga_s2bm_ard_3-2-1_52LHM_2019-01-10_final.stac-item
2019-01-11 10:45:43	ga_s2bm_ard_3-2-1_53JKG_2019-01-11_final.stac-item
2019-01-11 10:45:46	ga_s2bm_ard_3-2-1_52JGM_2019-01-11_final.stac-item
2019-01-11 10:45:57	ga_s2bm_ard_3-2-1_53JKF_2019-01-11_final.stac-item
2019-01-11 10:45:59	ga_s2bm_ard_3-2-1_52JGL_2019-01-11_final.stac-item
2019-01-14 10:55:53	ga_s2bm_ard_3-2-1_53JKF_2019-01-14_final.stac-item
2019-01-14 10:55:56	ga_s2bm_ard_3-2-1_52JGL_2019-01-14_final.stac-item
2019-01-17 11:00:30	ga_s2bm_ard_3-2-1_52LHN_2019-01-17_final.stac-item
2019-01-17 11:00:44	ga_s2bm_ard_3-2-1_52LHM_2019-01-17_final.stac-item
2019-01-17 11:00:59	ga_s2bm_ard_3-2-1_52LHL_2019-01-17_final.stac-item
2019-01-17 11:01:13	ga_s2bm_ard_3-2-1_52LHK_2019-01-17_final.stac-item
2019-01-17 11:01:28	ga_s2bm_ard_3-2-1_52LHJ_2019-01-17_final.stac-item
2019-01-17 11:01:42	ga_s2bm_ard_3-2-1_52LHH_2019-01-17_final.stac-item
2019-01-17 11:01:46	ga_s2bm_ard_3-2-1_52LGH_2019-01-17_final.stac-item
2019-01-17 11:01:57	ga_s2bm_ard_3-2-1_52KHG_2019-01-17_final.stac-item
2019-01-17 11:02:00	ga_s2bm_ard_3-2-1_52KGG_2019-01-17_final.stac-item
2019-01-17 11:02:11	ga_s2bm_ard_3-2-1_52KHF_2019-01-17_final.stac-item
2019-01-17 11:02:15	ga_s2bm_ard_3-2-1_52KGF_2019-01-17_final.stac-item
2019-01-17 11:02:25	ga_s2bm_ard_3-2-1_52KHE_2019-01-17_final.stac-item
2019-01-17 11:02:29	ga_s2bm_ard_3-2-1_52KGE_2019-01-17_final.stac-item
2019-01-17 11:02:40	ga_s2bm_ard_3-2-1_52KHD_2019-01-17_final.stac-item
2019-01-17 11:02:44	ga_s2bm_ard_3-2-1_52KGD_2019-01-17_final.stac-item
2019-01-17 11:02:54	ga_s2bm_ard_3-2-1_52KHC_2019-01-17_final.stac-item
2019-01-17 11:02:58	ga_s2bm_ard_3-2-1_52KGC_2019-01-17_final.stac-item
2019-01-17 11:03:09	ga_s2bm_ard_3-2-1_52KHB_2019-01-17_final.stac-item
2019-01-17 11:03:13	ga_s2bm_ard_3-2-1_52KGB_2019-01-17_final.stac-item
2019-01-17 11:03:27	ga_s2bm_ard_3-2-1_52KGA_2019-01-17_final.stac-item
2019-01-17 11:03:41	ga_s2bm_ard_3-2-1_52KGV_2019-01-17_final.stac-item
2019-01-24 10:53:14	ga_s2bm_ard_3-2-1_52KHB_2019-01-24_final.stac-item
2019-01-24 10:53:20	ga_s2bm_ard_3-2-1_52KGB_2019-01-24_final.stac-item
2019-01-24 10:53:32	ga_s2bm_ard_3-2-1_52KGA_2019-01-24_final.stac-item
2019-01-24 10:53:46	ga_s2bm_ard_3-2-1_52KGV_2019-01-24_final.stac-item
2019-01-24 10:54:01	ga_s2bm_ard_3-2-1_52KGU_2019-01-24_final.stac-item
2019-01-24 10:54:15	ga_s2bm_ard_3-2-1_52JGT_2019-01-24_final.stac-item
2019-01-24 10:54:28	ga_s2bm_ard_3-2-1_52JGS_2019-01-24_final.stac-item
2019-01-24 10:54:34	ga_s2bm_ard_3-2-1_52JGS_2019-01-24_final.stac-item
2019-01-24 10:54:44	ga_s2bm_ard_3-2-1_52JGR_2019-01-24_final.stac-item
2019-01-24 10:54:59	ga_s2bm_ard_3-2-1_52JGQ_2019-01-24_final.stac-item
2019-01-24 10:55:13	ga_s2bm_ard_3-2-1_52JGP_2019-01-24_final.stac-item
2019-01-24 10:55:24	ga_s2bm_ard_3-2-1_53JKH_2019-01-24_final.stac-item
2019-01-24 10:55:28	ga_s2bm_ard_3-2-1_52JGN_2019-01-24_final.stac-item
2019-01-24 10:55:39	ga_s2bm_ard_3-2-1_53JKG_2019-01-24_final.stac-item
2023-05-26 11:02:46	ga_s2bm_ard_3-2-1_52KHD_2023-05-26_final
2023-05-26 11:02:49	ga_s2bm_ard_3-2-1_52KGD_2023-05-26_final
2023-05-26 11:02:59	ga_s2bm_ard_3-2-1_52KHC_2023-05-26_final
2023-05-26 11:03:03	ga_s2bm_ard_3-2-1_52KGC_2023-05-26_final
2023-05-26 11:03:14	ga_s2bm_ard_3-2-1_52KHB_2023-05-26_final
2023-05-26 11:03:32	ga_s2bm_ard_3-2-1_52KGA_2023-05-26_final
2023-05-26 11:03:46	ga_s2bm_ard_3-2-1_52KGV_2023-05-26_final
2023-05-29 11:10:29	ga_s2bm_ard_3-2-1_52LHN_2023-05-29_final
2023-05-29 11:10:41	ga_s2bm_ard_3-2-1_52LHM_2023-05-29_final
2023-05-30 10:46:30	ga_s2bm_ard_3-2-1_53HKD_2023-05-30_nrt
2023-05-30 10:46:31	ga_s2bm_ard_3-2-1_52HGJ_2023-05-30_nrt
2023-06-02 10:53:24	ga_s2bm_ard_3-2-1_52KGB_2023-06-02_final
2023-06-02 10:53:35	ga_s2bm_ard_3-2-1_52KGA_2023-06-02_final
2023-06-02 10:53:41	ga_s2bm_ard_3-2-1_52KGA_2023-06-02_final
2023-06-02 10:53:41	ga_s2bm_ard_3-2-1_52KGV_2023-06-02_final
2023-06-02 10:53:50	ga_s2bm_ard_3-2-1_52KGV_2023-06-02_final
2023-06-02 10:54:05	ga_s2bm_ard_3-2-1_52KGU_2023-06-02_final
2023-06-02 10:54:19	ga_s2bm_ard_3-2-1_52JGT_2023-06-02_final
2023-06-02 10:54:33	ga_s2bm_ard_3-2-1_52JGS_2023-06-02_final
2023-06-02 10:54:48	ga_s2bm_ard_3-2-1_52JGR_2023-06-02_final
2023-06-02 10:55:02	ga_s2bm_ard_3-2-1_52JGQ_2023-06-02_final
2023-06-02 10:55:17	ga_s2bm_ard_3-2-1_52JGP_2023-06-02_final
2023-06-05 11:00:20	ga_s2bm_ard_3-2-1_52LHP_2023-06-05_nrt
2023-06-05 11:00:35	ga_s2bm_ard_3-2-1_52LHN_2023-06-05_final
2023-06-05 11:00:49	ga_s2bm_ard_3-2-1_52LHM_2023-06-05_final
2023-06-05 11:01:04	ga_s2bm_ard_3-2-1_52LHL_2023-06-05_final
2023-06-05 11:01:18	ga_s2bm_ard_3-2-1_52LHK_2023-06-05_final
2023-06-05 11:01:33	ga_s2bm_ard_3-2-1_52LHJ_2023-06-05_final
2023-06-05 11:01:47	ga_s2bm_ard_3-2-1_52LHH_2023-06-05_final
2023-06-05 11:01:50	ga_s2bm_ard_3-2-1_52LGH_2023-06-05_final
2023-06-05 11:02:01	ga_s2bm_ard_3-2-1_52KHG_2023-06-05_final
2023-06-05 11:02:05	ga_s2bm_ard_3-2-1_52KGG_2023-06-05_final
2023-06-05 11:02:16	ga_s2bm_ard_3-2-1_52KHF_2023-06-05_final
2023-06-05 11:02:20	ga_s2bm_ard_3-2-1_52KGF_2023-06-05_final
2023-06-05 11:02:30	ga_s2bm_ard_3-2-1_52KHE_2023-06-05_final
2023-06-05 11:02:34	ga_s2bm_ard_3-2-1_52KGE_2023-06-05_final
2023-06-05 11:02:39	ga_s2bm_ard_3-2-1_52KHD_2023-06-05_final
2023-06-05 11:02:41	ga_s2bm_ard_3-2-1_52KGE_2023-06-05_final
2023-06-05 11:02:41	ga_s2bm_ard_3-2-1_52KGD_2023-06-05_final
2023-06-05 11:02:46	ga_s2bm_ard_3-2-1_52KHD_2023-06-05_final
2023-06-05 11:02:49	ga_s2bm_ard_3-2-1_52KGD_2023-06-05_final
2023-06-05 11:02:59	ga_s2bm_ard_3-2-1_52KHC_2023-06-05_final
2023-06-05 11:03:03	ga_s2bm_ard_3-2-1_52KGC_2023-06-05_final
2023-06-05 11:03:14	ga_s2bm_ard_3-2-1_52KHB_2023-06-05_final
2023-06-05 11:03:17	ga_s2bm_ard_3-2-1_52KGB_2023-06-05_final
2023-06-05 11:03:32	ga_s2bm_ard_3-2-1_52KGA_2023-06-05_final
2023-06-05 11:03:46	ga_s2bm_ard_3-2-1_52KGV_2023-06-05_final
2023-06-08 11:10:16	ga_s2bm_ard_3-2-1_52LHP_2023-06-08_nrt
2023-06-08 11:10:30	ga_s2bm_ard_3-2-1_52LHN_2023-06-08_final
2023-06-08 11:10:42	ga_s2bm_ard_3-2-1_52LHM_2023-06-08_final
2023-06-09 10:45:48	ga_s2bm_ard_3-2-1_53JKG_2023-06-09_final
2023-06-09 10:45:52	ga_s2bm_ard_3-2-1_52JGM_2023-06-09_final
2023-06-09 10:46:03	ga_s2bm_ard_3-2-1_53JKF_2023-06-09_final
2023-06-09 10:46:05	ga_s2bm_ard_3-2-1_52JGL_2023-06-09_final
2023-06-09 10:46:17	ga_s2bm_ard_3-2-1_53HKE_2023-06-09_final
2023-06-09 10:46:20	ga_s2bm_ard_3-2-1_52HGK_2023-06-09_final
2023-06-09 10:46:31	ga_s2bm_ard_3-2-1_53HKD_2023-06-09_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