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
2023-06-25 11:00:35	ga_s2bm_ard_3-2-1_52LHN_2023-06-25_final
2023-06-25 11:00:41	ga_s2bm_ard_3-2-1_52LGN_2023-06-25_final
2023-06-25 11:00:53	ga_s2bm_ard_3-2-1_52LGM_2023-06-25_final
2023-06-25 11:01:17	ga_s2bm_ard_3-2-1_53LKE_2023-06-25_final
2023-06-25 11:01:31	ga_s2bm_ard_3-2-1_53LKD_2023-06-25_final
2023-06-25 11:01:46	ga_s2bm_ard_3-2-1_53LKC_2023-06-25_final
2023-06-25 11:02:01	ga_s2bm_ard_3-2-1_52KHG_2023-06-25_final
2023-06-25 11:02:08	ga_s2bm_ard_3-2-1_52KFG_2023-06-25_final
2023-06-25 11:02:16	ga_s2bm_ard_3-2-1_52KHF_2023-06-25_final
2023-06-25 11:02:19	ga_s2bm_ard_3-2-1_52KGF_2023-06-25_final
2023-06-25 11:02:23	ga_s2bm_ard_3-2-1_52KFF_2023-06-25_final
2023-06-25 11:02:41	ga_s2bm_ard_3-2-1_52KGE_2023-06-25_final
2023-06-25 11:03:14	ga_s2bm_ard_3-2-1_52KHB_2023-06-25_final
2023-06-25 11:03:23	ga_s2bm_ard_3-2-1_53KKR_2023-06-25_final
2023-06-25 11:03:53	ga_s2bm_ard_3-2-1_52KEV_2023-06-25_final
2023-06-25 11:03:58	ga_s2bm_ard_3-2-1_52KDV_2023-06-25_final
2023-06-25 11:04:08	ga_s2bm_ard_3-2-1_52KEU_2023-06-25_final
2023-06-25 11:04:15	ga_s2bm_ard_3-2-1_52JGT_2023-06-25_final
2023-06-25 11:04:51	ga_s2bm_ard_3-2-1_52JER_2023-06-25_final
2023-06-25 11:04:55	ga_s2bm_ard_3-2-1_52JDR_2023-06-25_final
2023-06-25 11:05:06	ga_s2bm_ard_3-2-1_52JEQ_2023-06-25_final
2023-06-25 11:05:09	ga_s2bm_ard_3-2-1_52JDQ_2023-06-25_final
2023-06-25 11:05:17	ga_s2bm_ard_3-2-1_52JFP_2023-06-25_final
2023-06-25 11:05:20	ga_s2bm_ard_3-2-1_52JEP_2023-06-25_final
2023-06-25 11:05:31	ga_s2bm_ard_3-2-1_52JFN_2023-06-25_final
2023-06-25 11:05:42	ga_s2bm_ard_3-2-1_52JCN_2023-06-25_final
2023-06-26 10:32:09	ga_s2bm_ard_3-2-1_53KRA_2023-06-26_final
2023-06-26 10:32:15	ga_s2bm_ard_3-2-1_53KQA_2023-06-26_final
2023-06-26 10:32:52	ga_s2bm_ard_3-2-1_53KRT_2023-06-26_final
2023-06-26 10:33:50	ga_s2bm_ard_3-2-1_54KTU_2023-06-26_final
2023-06-26 10:34:12	ga_s2bm_ard_3-2-1_53JPN_2023-06-26_final
2023-06-26 10:34:59	ga_s2bm_ard_3-2-1_53JNK_2023-06-26_final
2023-06-26 10:35:13	ga_s2bm_ard_3-2-1_53JNJ_2023-06-26_final
2023-06-26 10:36:11	ga_s2bm_ard_3-2-1_53HNE_2023-06-26_final
2023-06-26 10:36:26	ga_s2bm_ard_3-2-1_53HND_2023-06-26_final
2023-06-26 10:36:44	ga_s2bm_ard_3-2-1_53HMC_2023-06-26_final
2023-06-26 10:36:58	ga_s2bm_ard_3-2-1_53HMB_2023-06-26_final
2023-06-26 10:37:03	ga_s2bm_ard_3-2-1_53HPA_2023-06-26_final
2023-06-26 12:13:44	ga_s2bm_ard_3-2-1_50KKB_2023-06-26_final
2023-06-26 12:14:03	ga_s2bm_ard_3-2-1_49KGR_2023-06-26_final
2023-06-26 12:14:25	ga_s2bm_ard_3-2-1_49KHP_2023-06-26_final
2023-06-26 12:14:31	ga_s2bm_ard_3-2-1_49KGP_2023-06-26_final
2023-06-26 12:14:50	ga_s2bm_ard_3-2-1_49JFN_2023-06-26_final
2023-06-26 12:15:15	ga_s2bm_ard_3-2-1_49JGL_2023-06-26_final
2023-06-26 12:15:23	ga_s2bm_ard_3-2-1_49JGK_2023-06-26_final
2023-06-27 10:04:01	ga_s2bm_ard_3-2-1_54JYT_2023-06-27_final
2023-06-27 10:04:12	ga_s2bm_ard_3-2-1_54JZS_2023-06-27_final
2023-06-27 10:05:34	ga_s2bm_ard_3-2-1_54JYL_2023-06-27_final
2023-06-27 10:05:42	ga_s2bm_ard_3-2-1_54JYL_2023-06-27_final
2023-06-27 10:06:11	ga_s2bm_ard_3-2-1_54HYJ_2023-06-27_final
2023-06-27 10:06:25	ga_s2bm_ard_3-2-1_54HYH_2023-06-27_final
2023-06-27 10:06:38	ga_s2bm_ard_3-2-1_54HVH_2023-06-27_final
2023-06-27 10:06:39	ga_s2bm_ard_3-2-1_54HYG_2023-06-27_final
2023-06-27 10:06:51	ga_s2bm_ard_3-2-1_54HVG_2023-06-27_final
2023-06-27 10:07:27	ga_s2bm_ard_3-2-1_54HXD_2023-06-27_final
2023-06-27 10:07:41	ga_s2bm_ard_3-2-1_54HXC_2023-06-27_final
2023-06-27 11:41:37	ga_s2bm_ard_3-2-1_51LUE_2023-06-27_final
2023-06-27 11:41:52	ga_s2bm_ard_3-2-1_51LUD_2023-06-27_final
2023-06-27 11:42:00	ga_s2bm_ard_3-2-1_51LWC_2023-06-27_final
2023-06-27 11:42:14	ga_s2bm_ard_3-2-1_51KWB_2023-06-27_final
2023-06-27 11:42:26	ga_s2bm_ard_3-2-1_51KWA_2023-06-27_final
2023-06-27 11:43:08	ga_s2bm_ard_3-2-1_51KTU_2023-06-27_final
2023-06-27 11:43:09	ga_s2bm_ard_3-2-1_50KRD_2023-06-27_final
2023-06-27 11:43:13	ga_s2bm_ard_3-2-1_50KQD_2023-06-27_final
2023-06-27 11:43:19	ga_s2bm_ard_3-2-1_51KUT_2023-06-27_final
2023-06-27 11:43:23	ga_s2bm_ard_3-2-1_51KTT_2023-06-27_final
2023-06-27 11:43:34	ga_s2bm_ard_3-2-1_51KUS_2023-06-27_final
2023-06-27 11:43:37	ga_s2bm_ard_3-2-1_51KTS_2023-06-27_final
2023-06-27 11:44:03	ga_s2bm_ard_3-2-1_51KUQ_2023-06-27_final
2023-06-27 11:44:10	ga_s2bm_ard_3-2-1_50KQV_2023-06-27_final
2023-06-27 11:44:21	ga_s2bm_ard_3-2-1_50KRU_2023-06-27_final
2023-06-27 11:44:24	ga_s2bm_ard_3-2-1_50KQU_2023-06-27_final
2023-06-27 11:44:32	ga_s2bm_ard_3-2-1_51JUN_2023-06-27_final
2023-06-27 11:44:35	ga_s2bm_ard_3-2-1_50JRT_2023-06-27_final
2023-06-27 11:44:35	ga_s2bm_ard_3-2-1_51JTN_2023-06-27_final
2023-06-27 11:44:42	ga_s2bm_ard_3-2-1_50JPT_2023-06-27_final
2023-06-27 11:44:45	ga_s2bm_ard_3-2-1_51JUM_2023-06-27_final
2023-06-27 11:44:53	ga_s2bm_ard_3-2-1_50JQS_2023-06-27_final
2023-06-27 11:45:11	ga_s2bm_ard_3-2-1_50JPR_2023-06-27_final
2023-06-27 11:45:16	ga_s2bm_ard_3-2-1_50JNR_2023-06-27_final
2023-06-27 11:45:19	ga_s2bm_ard_3-2-1_51JTK_2023-06-27_final
2023-06-27 11:45:26	ga_s2bm_ard_3-2-1_50JPQ_2023-06-27_final
2023-06-27 11:45:37	ga_s2bm_ard_3-2-1_50JQP_2023-06-27_final
2023-06-27 11:45:48	ga_s2bm_ard_3-2-1_51JTH_2023-06-27_final
2023-06-27 11:45:51	ga_s2bm_ard_3-2-1_50JQN_2023-06-27_final
2023-06-27 11:45:59	ga_s2bm_ard_3-2-1_50JNN_2023-06-27_final
2023-06-27 11:46:13	ga_s2bm_ard_3-2-1_50JNM_2023-06-27_final
2023-06-27 11:46:27	ga_s2bm_ard_3-2-1_50JNL_2023-06-27_final
2023-06-27 11:46:45	ga_s2bm_ard_3-2-1_50HMK_2023-06-27_final
2023-06-27 11:46:53	ga_s2bm_ard_3-2-1_50HPJ_2023-06-27_final
2023-06-27 11:47:00	ga_s2bm_ard_3-2-1_50HMJ_2023-06-27_final
2023-06-27 11:47:07	ga_s2bm_ard_3-2-1_50HPH_2023-06-27_final
2023-06-27 11:47:22	ga_s2bm_ard_3-2-1_50HPG_2023-06-27_final
2023-06-27 11:47:25	ga_s2bm_ard_3-2-1_50HNG_2023-06-27_final
2023-07-11 11:20:31	ga_s2bm_ard_3-2-1_52LBP_2023-07-11_nrt
2023-07-11 11:21:00	ga_s2bm_ard_3-2-1_52LBM_2023-07-11_nrt
2023-07-11 11:21:15	ga_s2bm_ard_3-2-1_52LBL_2023-07-11_nrt
2023-07-12 10:56:19	ga_s2bm_ard_3-2-1_52HFK_2023-07-12_nrt
2023-07-12 10:56:22	ga_s2bm_ard_3-2-1_52HEK_2023-07-12_nrt
2023-07-12 10:56:25	ga_s2bm_ard_3-2-1_52HGJ_2023-07-12_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