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
2023-08-09 10:10:04	ga_s2bm_ard_3-2-1_54LZP_2023-08-09_final
2023-08-09 10:10:16	ga_s2bm_ard_3-2-1_54LZN_2023-08-09_final
2023-08-09 10:11:10	ga_s2bm_ard_3-2-1_55LCD_2023-08-09_final
2023-08-09 10:11:24	ga_s2bm_ard_3-2-1_55LCC_2023-08-09_final
2023-08-09 10:11:29	ga_s2bm_ard_3-2-1_54LZH_2023-08-09_final
2023-08-09 10:11:32	ga_s2bm_ard_3-2-1_54LYH_2023-08-09_final
2023-08-09 10:11:54	ga_s2bm_ard_3-2-1_55KCA_2023-08-09_final
2023-08-09 10:12:12	ga_s2bm_ard_3-2-1_55KBV_2023-08-09_final
2023-08-09 10:12:22	ga_s2bm_ard_3-2-1_55KCU_2023-08-09_final
2023-08-09 10:12:45	ga_s2bm_ard_3-2-1_54KYC_2023-08-09_final
2023-08-09 10:12:48	ga_s2bm_ard_3-2-1_54KXC_2023-08-09_final
2023-08-09 10:12:55	ga_s2bm_ard_3-2-1_54KZB_2023-08-09_final
2023-08-09 10:12:59	ga_s2bm_ard_3-2-1_54KYB_2023-08-09_final
2023-08-09 10:13:03	ga_s2bm_ard_3-2-1_54KXB_2023-08-09_final
2023-08-09 10:13:10	ga_s2bm_ard_3-2-1_54KZA_2023-08-09_final
2023-08-09 10:13:14	ga_s2bm_ard_3-2-1_54KYA_2023-08-09_final
2023-08-09 10:13:24	ga_s2bm_ard_3-2-1_55KBQ_2023-08-09_final
2023-08-09 10:13:38	ga_s2bm_ard_3-2-1_55KBP_2023-08-09_final
2023-08-09 10:13:49	ga_s2bm_ard_3-2-1_55JBN_2023-08-09_final
2023-08-09 10:13:51	ga_s2bm_ard_3-2-1_54JZT_2023-08-09_final
2023-08-09 10:14:30	ga_s2bm_ard_3-2-1_54JXR_2023-08-09_final
2023-08-09 10:14:33	ga_s2bm_ard_3-2-1_54JWR_2023-08-09_final
2023-08-09 10:14:35	ga_s2bm_ard_3-2-1_54JVR_2023-08-09_final
2023-08-09 10:14:37	ga_s2bm_ard_3-2-1_54JYQ_2023-08-09_final
2023-08-09 10:14:39	ga_s2bm_ard_3-2-1_54JXQ_2023-08-09_final
2023-08-09 10:14:41	ga_s2bm_ard_3-2-1_54JWR_2023-08-09_final
2023-08-09 10:14:41	ga_s2bm_ard_3-2-1_54JWQ_2023-08-09_final
2023-08-09 10:14:42	ga_s2bm_ard_3-2-1_54JVR_2023-08-09_final
2023-08-09 10:14:42	ga_s2bm_ard_3-2-1_54JVQ_2023-08-09_final
2023-08-09 10:14:44	ga_s2bm_ard_3-2-1_54JYQ_2023-08-09_final
2023-08-09 10:14:46	ga_s2bm_ard_3-2-1_54JXQ_2023-08-09_final
2023-08-09 10:14:48	ga_s2bm_ard_3-2-1_54JWQ_2023-08-09_final
2023-08-09 10:14:51	ga_s2bm_ard_3-2-1_54JVQ_2023-08-09_final
2023-08-09 10:14:53	ga_s2bm_ard_3-2-1_54JYP_2023-08-09_final
2023-08-09 10:15:02	ga_s2bm_ard_3-2-1_54JWP_2023-08-09_final
2023-08-09 10:15:55	ga_s2bm_ard_3-2-1_54HXK_2023-08-09_final
2023-08-09 10:16:00	ga_s2bm_ard_3-2-1_54HWK_2023-08-09_final
2023-08-09 10:16:04	ga_s2bm_ard_3-2-1_54HVK_2023-08-09_final
2023-08-09 10:16:07	ga_s2bm_ard_3-2-1_54HUK_2023-08-09_final
2023-08-09 10:16:19	ga_s2bm_ard_3-2-1_54HVJ_2023-08-09_final
2023-08-09 10:16:57	ga_s2bm_ard_3-2-1_53HQB_2023-08-09_final
2023-08-09 10:17:09	ga_s2bm_ard_3-2-1_54HTF_2023-08-09_final
2023-08-09 10:17:20	ga_s2bm_ard_3-2-1_54HUE_2023-08-09_final
2023-08-09 10:17:23	ga_s2bm_ard_3-2-1_54HTE_2023-08-09_final
2023-08-09 10:17:31	ga_s2bm_ard_3-2-1_54HVD_2023-08-09_final
2023-08-09 10:17:35	ga_s2bm_ard_3-2-1_54HUD_2023-08-09_final
2023-08-09 10:17:42	ga_s2bm_ard_3-2-1_54HVC_2023-08-09_final
2023-08-09 11:51:19	ga_s2bm_ard_3-2-1_51LUF_2023-08-09_final
2023-08-09 11:52:43	ga_s2bm_ard_3-2-1_50KPF_2023-08-09_final
2023-08-09 11:52:59	ga_s2bm_ard_3-2-1_51KTU_2023-08-09_final
2023-08-09 11:53:08	ga_s2bm_ard_3-2-1_50KQD_2023-08-09_final
2023-08-09 11:53:12	ga_s2bm_ard_3-2-1_50KPD_2023-08-09_final
2023-08-09 11:53:16	ga_s2bm_ard_3-2-1_50KRC_2023-08-09_final
2023-08-09 11:53:23	ga_s2bm_ard_3-2-1_50KQC_2023-08-09_final
2023-08-09 11:53:26	ga_s2bm_ard_3-2-1_50KPC_2023-08-09_final
2023-08-09 11:53:30	ga_s2bm_ard_3-2-1_50KNC_2023-08-09_final
2023-08-09 11:53:36	ga_s2bm_ard_3-2-1_50KMC_2023-08-09_final
2023-08-09 11:53:37	ga_s2bm_ard_3-2-1_50KQB_2023-08-09_final
2023-08-09 11:53:41	ga_s2bm_ard_3-2-1_50KNB_2023-08-09_final
2023-08-09 11:53:44	ga_s2bm_ard_3-2-1_50KMB_2023-08-09_final
2023-08-09 11:53:45	ga_s2bm_ard_3-2-1_50KQA_2023-08-09_final
2023-08-19 11:50:35	ga_s2bm_ard_3-2-1_51LUJ_2023-08-19_nrt
2023-08-19 11:50:38	ga_s2bm_ard_3-2-1_51LTJ_2023-08-19_nrt
2023-08-19 11:50:49	ga_s2bm_ard_3-2-1_51LUH_2023-08-19_nrt
2023-08-19 11:50:53	ga_s2bm_ard_3-2-1_51LTH_2023-08-19_nrt
2023-08-19 11:51:04	ga_s2bm_ard_3-2-1_51LUG_2023-08-19_nrt
2023-08-19 11:51:07	ga_s2bm_ard_3-2-1_51LTG_2023-08-19_nrt
2023-08-19 11:51:12	ga_s2bm_ard_3-2-1_50LQM_2023-08-19_nrt
2023-08-19 11:51:22	ga_s2bm_ard_3-2-1_51LTF_2023-08-19_nrt
2023-08-19 11:51:27	ga_s2bm_ard_3-2-1_50LQL_2023-08-19_nrt
2023-08-19 11:51:31	ga_s2bm_ard_3-2-1_50LPL_2023-08-19_nrt
2023-08-19 11:51:36	ga_s2bm_ard_3-2-1_51LTE_2023-08-19_nrt
2023-08-19 11:51:41	ga_s2bm_ard_3-2-1_50LQK_2023-08-19_nrt
2023-08-19 11:51:44	ga_s2bm_ard_3-2-1_50LPK_2023-08-19_nrt
2023-08-19 11:51:51	ga_s2bm_ard_3-2-1_51LTD_2023-08-19_nrt
2023-08-19 11:51:56	ga_s2bm_ard_3-2-1_50LQJ_2023-08-19_nrt
2023-08-19 11:51:59	ga_s2bm_ard_3-2-1_50LPJ_2023-08-19_nrt
2023-08-19 11:52:05	ga_s2bm_ard_3-2-1_51LTC_2023-08-19_nrt
2023-08-19 11:52:10	ga_s2bm_ard_3-2-1_50LQH_2023-08-19_nrt
2023-08-19 11:52:14	ga_s2bm_ard_3-2-1_50LPH_2023-08-19_nrt
2023-08-19 11:52:20	ga_s2bm_ard_3-2-1_51KTB_2023-08-19_nrt
2023-08-19 11:52:28	ga_s2bm_ard_3-2-1_50KPG_2023-08-19_nrt
2023-08-19 11:52:34	ga_s2bm_ard_3-2-1_50KNG_2023-08-19_nrt
2023-08-19 11:52:35	ga_s2bm_ard_3-2-1_51KTA_2023-08-19_nrt
2023-08-19 11:52:46	ga_s2bm_ard_3-2-1_50KNF_2023-08-19_nrt
2023-08-19 11:52:57	ga_s2bm_ard_3-2-1_50KPE_2023-08-19_nrt
2023-08-19 11:53:00	ga_s2bm_ard_3-2-1_50KNE_2023-08-19_nrt
2023-08-19 11:53:15	ga_s2bm_ard_3-2-1_50KND_2023-08-19_nrt
2023-08-19 11:56:50	ga_s2bm_ard_3-2-1_49HGE_2023-08-19_nrt
2023-08-19 11:57:05	ga_s2bm_ard_3-2-1_49HGD_2023-08-19_nrt
2023-08-19 11:57:13	ga_s2bm_ard_3-2-1_49HGC_2023-08-19_nrt
2023-08-19 11:57:21	ga_s2bm_ard_3-2-1_49HGC_2023-08-19_nrt
2023-08-19 11:57:28	ga_s2bm_ard_3-2-1_49HFC_2023-08-19_nrt
2023-08-19 11:57:30	ga_s2bm_ard_3-2-1_49HGB_2023-08-19_nrt
2023-08-19 11:57:32	ga_s2bm_ard_3-2-1_49HFB_2023-08-19_nrt
2023-08-19 11:57:32	ga_s2bm_ard_3-2-1_50HMF_2023-08-19_nrt
2023-08-20 09:41:26	ga_s2bm_ard_3-2-1_56KNG_2023-08-20_nrt
2023-08-20 09:41:39	ga_s2bm_ard_3-2-1_56KNF_2023-08-20_nrt
2023-08-20 09:41:51	ga_s2bm_ard_3-2-1_56KNE_2023-08-20_nrt
2023-08-20 09:48:57	ga_s2bm_ard_3-2-1_54GYT_2023-08-20_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