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
2023-09-15 10:01:38	ga_s2bm_ard_3-2-1_55KDB_2023-09-15_final
2023-09-15 10:01:41	ga_s2bm_ard_3-2-1_55KCB_2023-09-15_final
2023-09-15 10:01:45	ga_s2bm_ard_3-2-1_55KFA_2023-09-15_final
2023-09-15 10:01:49	ga_s2bm_ard_3-2-1_55KEA_2023-09-15_nrt
2023-09-15 10:01:53	ga_s2bm_ard_3-2-1_55KDA_2023-09-15_final
2023-09-15 10:01:56	ga_s2bm_ard_3-2-1_55KCA_2023-09-15_final
2023-09-15 10:01:58	ga_s2bm_ard_3-2-1_55KFV_2023-09-15_nrt
2023-09-15 10:02:04	ga_s2bm_ard_3-2-1_55KEV_2023-09-15_final
2023-09-15 10:02:07	ga_s2bm_ard_3-2-1_55KDV_2023-09-15_final
2023-09-15 10:02:11	ga_s2bm_ard_3-2-1_55KCV_2023-09-15_final
2023-09-15 10:02:17	ga_s2bm_ard_3-2-1_55KBV_2023-09-15_final
2023-09-15 10:02:18	ga_s2bm_ard_3-2-1_55KEU_2023-09-15_final
2023-09-15 10:02:22	ga_s2bm_ard_3-2-1_55KDU_2023-09-15_final
2023-09-15 10:02:25	ga_s2bm_ard_3-2-1_55KCU_2023-09-15_final
2023-09-15 10:02:29	ga_s2bm_ard_3-2-1_55KBU_2023-09-15_final
2023-09-15 10:02:33	ga_s2bm_ard_3-2-1_55KET_2023-09-15_final
2023-09-15 10:02:36	ga_s2bm_ard_3-2-1_55KDT_2023-09-15_final
2023-09-15 10:02:37	ga_s2bm_ard_3-2-1_55KCT_2023-09-15_final
2023-09-15 10:02:39	ga_s2bm_ard_3-2-1_55KBT_2023-09-15_final
2023-09-15 10:02:40	ga_s2bm_ard_3-2-1_54KZC_2023-09-15_final
2023-09-15 10:02:41	ga_s2bm_ard_3-2-1_55KET_2023-09-15_final
2023-09-15 10:02:41	ga_s2bm_ard_3-2-1_55KES_2023-09-15_final
2023-09-15 10:02:42	ga_s2bm_ard_3-2-1_55KDS_2023-09-15_final
2023-09-15 10:02:42	ga_s2bm_ard_3-2-1_55KDT_2023-09-15_final
2023-09-15 10:02:44	ga_s2bm_ard_3-2-1_55KCT_2023-09-15_final
2023-09-15 10:02:45	ga_s2bm_ard_3-2-1_55KBT_2023-09-15_final
2023-09-15 10:02:46	ga_s2bm_ard_3-2-1_54KZC_2023-09-15_final
2023-09-15 10:02:48	ga_s2bm_ard_3-2-1_55KES_2023-09-15_final
2023-09-15 10:02:51	ga_s2bm_ard_3-2-1_55KDS_2023-09-15_final
2023-09-15 10:02:54	ga_s2bm_ard_3-2-1_55KCS_2023-09-15_final
2023-09-15 10:02:57	ga_s2bm_ard_3-2-1_55KBS_2023-09-15_final
2023-09-15 10:02:57	ga_s2bm_ard_3-2-1_54KZB_2023-09-15_final
2023-09-15 10:03:01	ga_s2bm_ard_3-2-1_55KER_2023-09-15_final
2023-09-15 10:03:05	ga_s2bm_ard_3-2-1_55KDR_2023-09-15_final
2023-09-15 10:03:09	ga_s2bm_ard_3-2-1_55KCR_2023-09-15_final
2023-09-15 10:03:12	ga_s2bm_ard_3-2-1_55KEQ_2023-09-15_final
2023-09-15 10:03:12	ga_s2bm_ard_3-2-1_55KBR_2023-09-15_final
2023-09-15 10:03:12	ga_s2bm_ard_3-2-1_54KZA_2023-09-15_final
2023-09-15 10:03:20	ga_s2bm_ard_3-2-1_55KDQ_2023-09-15_final
2023-09-15 10:03:23	ga_s2bm_ard_3-2-1_55KCQ_2023-09-15_final
2023-09-15 10:03:26	ga_s2bm_ard_3-2-1_55KBQ_2023-09-15_final
2023-09-15 10:03:27	ga_s2bm_ard_3-2-1_54KZV_2023-09-15_final
2023-09-15 10:03:34	ga_s2bm_ard_3-2-1_55KDP_2023-09-15_final
2023-09-15 10:03:35	ga_s2bm_ard_3-2-1_54KYV_2023-09-15_final
2023-09-15 10:03:38	ga_s2bm_ard_3-2-1_55KCP_2023-09-15_final
2023-09-15 10:05:19	ga_s2bm_ard_3-2-1_55JCG_2023-09-15_final
2023-09-15 10:05:23	ga_s2bm_ard_3-2-1_55JBG_2023-09-15_final
2023-09-15 10:05:26	ga_s2bm_ard_3-2-1_54JYM_2023-09-15_final
2023-09-15 10:05:29	ga_s2bm_ard_3-2-1_54JXM_2023-09-15_final
2023-09-15 10:05:32	ga_s2bm_ard_3-2-1_55JCF_2023-09-15_final
2023-09-15 10:05:36	ga_s2bm_ard_3-2-1_54JWM_2023-09-15_final
2023-09-15 10:05:37	ga_s2bm_ard_3-2-1_55JBF_2023-09-15_final
2023-09-15 10:05:40	ga_s2bm_ard_3-2-1_54JYL_2023-09-15_final
2023-09-15 10:05:44	ga_s2bm_ard_3-2-1_54JXL_2023-09-15_final
2023-09-15 10:05:48	ga_s2bm_ard_3-2-1_54JWL_2023-09-15_final
2023-09-15 10:05:52	ga_s2bm_ard_3-2-1_55HBE_2023-09-15_final
2023-09-15 10:05:55	ga_s2bm_ard_3-2-1_54HYK_2023-09-15_final
2023-09-15 10:05:58	ga_s2bm_ard_3-2-1_54HXK_2023-09-15_final
2023-09-15 10:06:02	ga_s2bm_ard_3-2-1_54HWK_2023-09-15_final
2023-09-15 10:06:07	ga_s2bm_ard_3-2-1_55HBD_2023-09-15_final
2023-09-15 10:06:13	ga_s2bm_ard_3-2-1_54HXJ_2023-09-15_final
2023-09-15 10:06:17	ga_s2bm_ard_3-2-1_54HWJ_2023-09-15_final
2023-09-15 10:06:21	ga_s2bm_ard_3-2-1_55HBC_2023-09-15_final
2023-09-15 10:06:23	ga_s2bm_ard_3-2-1_54HYH_2023-09-15_final
2023-09-15 10:06:27	ga_s2bm_ard_3-2-1_54HXH_2023-09-15_final
2023-09-15 10:06:31	ga_s2bm_ard_3-2-1_54HWH_2023-09-15_final
2023-09-15 10:06:35	ga_s2bm_ard_3-2-1_55HBB_2023-09-15_final
2023-09-15 10:06:42	ga_s2bm_ard_3-2-1_54HXG_2023-09-15_final
2023-09-15 10:06:45	ga_s2bm_ard_3-2-1_54HWG_2023-09-15_final
2023-09-15 11:41:03	ga_s2bm_ard_3-2-1_51LVG_2023-09-15_final
2023-09-15 11:41:06	ga_s2bm_ard_3-2-1_51LUG_2023-09-15_nrt
2023-09-15 11:41:10	ga_s2bm_ard_3-2-1_51LXF_2023-09-15_nrt
2023-09-15 11:41:14	ga_s2bm_ard_3-2-1_51LWF_2023-09-15_nrt
2023-09-15 11:41:18	ga_s2bm_ard_3-2-1_51LVF_2023-09-15_final
2023-09-15 11:41:20	ga_s2bm_ard_3-2-1_51LXE_2023-09-15_nrt
2023-09-15 11:41:21	ga_s2bm_ard_3-2-1_51LUF_2023-09-15_final
2023-09-15 11:41:29	ga_s2bm_ard_3-2-1_51LWE_2023-09-15_final
2023-09-15 11:41:33	ga_s2bm_ard_3-2-1_51LVE_2023-09-15_final
2023-09-15 11:41:36	ga_s2bm_ard_3-2-1_51LUE_2023-09-15_final
2023-09-15 11:41:40	ga_s2bm_ard_3-2-1_51LTE_2023-09-15_nrt
2023-09-15 11:41:43	ga_s2bm_ard_3-2-1_51LWD_2023-09-15_nrt
2023-09-15 11:41:47	ga_s2bm_ard_3-2-1_51LVD_2023-09-15_nrt
2023-09-15 11:41:50	ga_s2bm_ard_3-2-1_51LUD_2023-09-15_final
2023-09-15 11:41:53	ga_s2bm_ard_3-2-1_51LTD_2023-09-15_nrt
2023-09-15 11:41:58	ga_s2bm_ard_3-2-1_51LWC_2023-09-15_final
2023-09-15 11:42:01	ga_s2bm_ard_3-2-1_51LVC_2023-09-15_final
2023-09-15 11:42:05	ga_s2bm_ard_3-2-1_51LUC_2023-09-15_final
2023-09-15 11:42:08	ga_s2bm_ard_3-2-1_51LTC_2023-09-15_nrt
2023-09-15 11:42:10	ga_s2bm_ard_3-2-1_50LRH_2023-09-15_nrt
2023-09-15 11:42:12	ga_s2bm_ard_3-2-1_51KWB_2023-09-15_final
2023-09-15 11:42:16	ga_s2bm_ard_3-2-1_51KVB_2023-09-15_final
2023-09-15 11:42:19	ga_s2bm_ard_3-2-1_51KUB_2023-09-15_final
2023-09-15 11:42:22	ga_s2bm_ard_3-2-1_51KTB_2023-09-15_nrt
2023-09-15 11:42:23	ga_s2bm_ard_3-2-1_50KRG_2023-09-15_nrt
2023-09-15 11:42:24	ga_s2bm_ard_3-2-1_51KWA_2023-09-15_final
2023-09-15 11:42:30	ga_s2bm_ard_3-2-1_51KVA_2023-09-15_final
2023-09-15 11:42:34	ga_s2bm_ard_3-2-1_51KUA_2023-09-15_final
2023-09-15 11:42:37	ga_s2bm_ard_3-2-1_51KTA_2023-09-15_nrt
2023-09-15 11:42:38	ga_s2bm_ard_3-2-1_50KRF_2023-09-15_nrt
2023-09-15 11:42:45	ga_s2bm_ard_3-2-1_51KVV_2023-09-15_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