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
2019-03-03 10:16:07	ga_s2bm_ard_3-2-1_54HWJ_2019-03-03_final.stac-item
2019-03-03 10:16:11	ga_s2bm_ard_3-2-1_54HVJ_2019-03-03_final.stac-item
2019-03-03 10:16:14	ga_s2bm_ard_3-2-1_54HUJ_2019-03-03_final.stac-item
2019-03-03 10:16:19	ga_s2bm_ard_3-2-1_54HTJ_2019-03-03_final.stac-item
2019-03-04 09:46:03	ga_s2bm_ard_3-2-1_55HDD_2019-03-04_final.stac-item
2019-03-10 10:06:01	ga_s2bm_ard_3-2-1_55HBD_2019-03-10_final.stac-item
2019-03-10 10:06:03	ga_s2bm_ard_3-2-1_54HYJ_2019-03-10_final.stac-item
2019-03-10 10:06:07	ga_s2bm_ard_3-2-1_54HXJ_2019-03-10_final.stac-item
2019-03-10 10:06:11	ga_s2bm_ard_3-2-1_54HWJ_2019-03-10_final.stac-item
2019-03-10 10:06:16	ga_s2bm_ard_3-2-1_55HBC_2019-03-10_final.stac-item
2019-03-10 10:06:18	ga_s2bm_ard_3-2-1_54HYH_2019-03-10_final.stac-item
2019-03-10 10:06:22	ga_s2bm_ard_3-2-1_54HXH_2019-03-10_final.stac-item
2019-03-10 10:06:25	ga_s2bm_ard_3-2-1_54HWH_2019-03-10_final.stac-item
2019-04-27 09:26:01	ga_s2bm_ard_3-2-1_56HMJ_2019-04-26_final.stac-item
2019-04-27 09:26:04	ga_s2bm_ard_3-2-1_56HLJ_2019-04-26_final.stac-item
2019-04-27 09:26:12	ga_s2bm_ard_3-2-1_56HLJ_2019-04-26_final.stac-item
2019-05-03 09:46:02	ga_s2bm_ard_3-2-1_55HGD_2019-05-03_final.stac-item
2019-05-06 09:56:09	ga_s2bm_ard_3-2-1_55HDD_2019-05-06_final.stac-item
2019-05-06 09:56:13	ga_s2bm_ard_3-2-1_55HCD_2019-05-06_final.stac-item
2019-05-06 09:56:16	ga_s2bm_ard_3-2-1_55HBD_2019-05-06_final.stac-item
2019-05-06 09:56:18	ga_s2bm_ard_3-2-1_54HYJ_2019-05-06_final.stac-item
2019-05-06 09:56:24	ga_s2bm_ard_3-2-1_55HDC_2019-05-06_final.stac-item
2019-05-06 09:56:28	ga_s2bm_ard_3-2-1_55HCC_2019-05-06_final.stac-item
2019-05-06 09:56:31	ga_s2bm_ard_3-2-1_55HBC_2019-05-06_final.stac-item
2019-05-06 09:56:33	ga_s2bm_ard_3-2-1_54HYH_2019-05-06_final.stac-item
2019-05-06 11:36:51	ga_s2bm_ard_3-2-1_51HUD_2019-05-06_final.stac-item
2019-05-06 11:36:54	ga_s2bm_ard_3-2-1_51HTD_2019-05-06_final.stac-item
2019-05-06 11:36:56	ga_s2bm_ard_3-2-1_50HQJ_2019-05-06_final.stac-item
2019-05-06 11:37:00	ga_s2bm_ard_3-2-1_50HPJ_2019-05-06_final.stac-item
2019-05-06 11:37:05	ga_s2bm_ard_3-2-1_51HUC_2019-05-06_final.stac-item
2019-05-06 11:37:09	ga_s2bm_ard_3-2-1_51HTC_2019-05-06_final.stac-item
2019-05-06 11:37:11	ga_s2bm_ard_3-2-1_50HQH_2019-05-06_final.stac-item
2019-05-06 11:37:15	ga_s2bm_ard_3-2-1_50HPH_2019-05-06_final.stac-item
2019-05-07 09:26:01	ga_s2bm_ard_3-2-1_56HMJ_2019-05-06_final.stac-item
2019-05-07 09:26:08	ga_s2bm_ard_3-2-1_56HMJ_2019-05-06_final.stac-item
2019-05-07 09:26:09	ga_s2bm_ard_3-2-1_56HLJ_2019-05-06_final.stac-item
2019-05-10 09:35:56	ga_s2bm_ard_3-2-1_56HMJ_2019-05-10_final.stac-item
2019-05-10 09:36:02	ga_s2bm_ard_3-2-1_56HLJ_2019-05-10_final.stac-item
2019-05-10 09:36:05	ga_s2bm_ard_3-2-1_56HKJ_2019-05-10_final.stac-item
2019-05-10 09:36:07	ga_s2bm_ard_3-2-1_55HGD_2019-05-10_final.stac-item
2019-05-10 09:36:11	ga_s2bm_ard_3-2-1_55HFD_2019-05-10_final.stac-item
2019-05-10 09:36:20	ga_s2bm_ard_3-2-1_56HKH_2019-05-10_final.stac-item
2019-05-10 09:36:21	ga_s2bm_ard_3-2-1_55HGC_2019-05-10_final.stac-item
2019-05-10 09:36:25	ga_s2bm_ard_3-2-1_55HFC_2019-05-10_final.stac-item
2019-05-11 10:46:29	ga_s2bm_ard_3-2-1_53HMD_2019-05-11_final.stac-item
2019-05-11 10:46:32	ga_s2bm_ard_3-2-1_53HLD_2019-05-11_final.stac-item
2019-05-22 10:16:36	ga_s2bm_ard_3-2-1_54HVH_2019-05-22_final.stac-item
2019-05-22 10:16:40	ga_s2bm_ard_3-2-1_54HUH_2019-05-22_final.stac-item
2019-05-22 10:16:43	ga_s2bm_ard_3-2-1_54HTH_2019-05-22_final.stac-item
2019-07-10 10:46:29	ga_s2bm_ard_3-2-1_53HMD_2019-07-10_final.stac-item
2019-07-10 10:46:33	ga_s2bm_ard_3-2-1_53HLD_2019-07-10_final.stac-item
2019-07-11 10:16:18	ga_s2bm_ard_3-2-1_54HWJ_2019-07-11_final.stac-item
2019-07-11 10:16:22	ga_s2bm_ard_3-2-1_54HVJ_2019-07-11_final.stac-item
2019-07-11 10:16:25	ga_s2bm_ard_3-2-1_54HUJ_2019-07-11_final.stac-item
2019-07-11 10:16:29	ga_s2bm_ard_3-2-1_54HTJ_2019-07-11_final.stac-item
2019-07-15 09:56:10	ga_s2bm_ard_3-2-1_55HDD_2019-07-15_final.stac-item
2019-07-15 09:56:14	ga_s2bm_ard_3-2-1_55HCD_2019-07-15_final.stac-item
2019-07-15 09:56:17	ga_s2bm_ard_3-2-1_55HBD_2019-07-15_final.stac-item
2019-07-15 09:56:19	ga_s2bm_ard_3-2-1_54HYJ_2019-07-15_final.stac-item
2019-07-15 09:56:25	ga_s2bm_ard_3-2-1_55HDC_2019-07-15_final.stac-item
2019-07-15 09:56:28	ga_s2bm_ard_3-2-1_55HCC_2019-07-15_final.stac-item
2019-07-15 09:56:31	ga_s2bm_ard_3-2-1_55HBC_2019-07-15_final.stac-item
2019-07-15 09:56:33	ga_s2bm_ard_3-2-1_54HYH_2019-07-15_final.stac-item
2019-07-17 10:36:26	ga_s2bm_ard_3-2-1_53HPD_2019-07-17_final.stac-item
2019-07-17 10:36:30	ga_s2bm_ard_3-2-1_53HND_2019-07-17_final.stac-item
2019-07-17 10:36:33	ga_s2bm_ard_3-2-1_53HMD_2019-07-17_final.stac-item
2019-07-17 10:36:37	ga_s2bm_ard_3-2-1_53HLD_2019-07-17_final.stac-item
2019-07-17 10:36:41	ga_s2bm_ard_3-2-1_53HPC_2019-07-17_final.stac-item
2019-07-17 10:36:44	ga_s2bm_ard_3-2-1_53HNC_2019-07-17_final.stac-item
2023-04-20 10:46:22	ga_s2bm_ard_3-2-1_53HMD_2023-04-20_final
2023-04-20 10:46:26	ga_s2bm_ard_3-2-1_53HLD_2023-04-20_final
2023-04-20 10:46:29	ga_s2bm_ard_3-2-1_53HKD_2023-04-20_nrt
2023-04-20 10:46:30	ga_s2bm_ard_3-2-1_52HGJ_2023-04-20_nrt
2023-04-20 10:46:33	ga_s2bm_ard_3-2-1_53HMC_2023-04-20_final
2023-04-20 10:46:35	ga_s2bm_ard_3-2-1_53HLC_2023-04-20_nrt
2023-04-20 10:46:36	ga_s2bm_ard_3-2-1_53HKC_2023-04-20_nrt
2023-04-20 10:46:37	ga_s2bm_ard_3-2-1_52HGH_2023-04-20_nrt
2023-04-25 11:37:03	ga_s2bm_ard_3-2-1_51HTC_2023-04-25_final
2023-04-25 11:37:05	ga_s2bm_ard_3-2-1_50HQH_2023-04-25_final
2023-04-25 11:37:09	ga_s2bm_ard_3-2-1_50HPH_2023-04-25_final
2023-04-26 09:25:49	ga_s2bm_ard_3-2-1_56HPJ_2023-04-25_nrt
2023-04-26 09:25:52	ga_s2bm_ard_3-2-1_56HNJ_2023-04-25_nrt
2023-04-26 09:25:56	ga_s2bm_ard_3-2-1_56HMJ_2023-04-25_final
2023-04-26 09:25:59	ga_s2bm_ard_3-2-1_56HLJ_2023-04-25_final
2023-04-26 09:26:02	ga_s2bm_ard_3-2-1_56HPH_2023-04-25_nrt
2023-04-26 09:26:07	ga_s2bm_ard_3-2-1_56HNH_2023-04-25_nrt
2023-04-26 09:26:10	ga_s2bm_ard_3-2-1_56HMH_2023-04-25_nrt
2023-04-26 09:26:14	ga_s2bm_ard_3-2-1_56HLH_2023-04-25_final
2023-04-26 11:06:30	ga_s2bm_ard_3-2-1_52HEJ_2023-04-26_nrt
2023-04-26 11:06:33	ga_s2bm_ard_3-2-1_52HDJ_2023-04-26_nrt
2023-04-29 09:35:50	ga_s2bm_ard_3-2-1_56HMJ_2023-04-29_final
2023-04-29 09:35:55	ga_s2bm_ard_3-2-1_56HLJ_2023-04-29_final
2023-04-29 09:35:58	ga_s2bm_ard_3-2-1_56HKJ_2023-04-29_final
2023-04-29 09:36:00	ga_s2bm_ard_3-2-1_56HMH_2023-04-29_nrt
2023-05-01 10:16:11	ga_s2bm_ard_3-2-1_54HWJ_2023-05-01_final
2023-05-01 10:16:15	ga_s2bm_ard_3-2-1_54HVJ_2023-05-01_final
2023-05-01 10:16:19	ga_s2bm_ard_3-2-1_54HUJ_2023-05-01_final
2023-05-01 10:16:23	ga_s2bm_ard_3-2-1_54HTJ_2023-05-01_final
2023-05-01 10:16:30	ga_s2bm_ard_3-2-1_54HVH_2023-05-01_final
2023-05-01 10:16:33	ga_s2bm_ard_3-2-1_54HUH_2023-05-01_final

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