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
2023-11-10 12:04:44	ga_s2bm_ard_3-2-1_49JHN_2023-11-10_final
2023-11-10 12:04:44	ga_s2bm_ard_3-2-1_50JKT_2023-11-10_final
2023-11-10 12:04:48	ga_s2bm_ard_3-2-1_49JGN_2023-11-10_final
2023-11-10 12:04:50	ga_s2bm_ard_3-2-1_50JMS_2023-11-10_final
2023-11-10 12:04:55	ga_s2bm_ard_3-2-1_50JLS_2023-11-10_final
2023-11-10 12:04:58	ga_s2bm_ard_3-2-1_49JHM_2023-11-10_final
2023-11-10 12:04:59	ga_s2bm_ard_3-2-1_50JKS_2023-11-10_final
2023-11-10 12:05:21	ga_s2bm_ard_3-2-1_49JFL_2023-11-10_nrt
2023-11-10 12:05:31	ga_s2bm_ard_3-2-1_49JGK_2023-11-10_final
2023-11-10 12:05:34	ga_s2bm_ard_3-2-1_49JFK_2023-11-10_nrt
2023-11-10 12:05:49	ga_s2bm_ard_3-2-1_49JFJ_2023-11-10_nrt
2023-11-10 12:06:04	ga_s2bm_ard_3-2-1_49JFH_2023-11-10_nrt
2023-11-10 12:06:14	ga_s2bm_ard_3-2-1_49JGG_2023-11-10_nrt
2023-11-10 12:06:16	ga_s2bm_ard_3-2-1_50JLL_2023-11-10_final
2023-11-10 12:06:18	ga_s2bm_ard_3-2-1_49JFG_2023-11-10_nrt
2023-11-10 12:06:23	ga_s2bm_ard_3-2-1_50JKL_2023-11-10_nrt
2023-11-10 12:06:25	ga_s2bm_ard_3-2-1_49JGF_2023-11-10_nrt
2023-11-10 12:06:26	ga_s2bm_ard_3-2-1_49JFF_2023-11-10_nrt
2023-11-11 09:49:38	ga_s2bm_ard_3-2-1_56LMP_2023-11-11_nrt
2023-11-11 09:49:42	ga_s2bm_ard_3-2-1_56LLP_2023-11-11_nrt
2023-11-11 09:49:45	ga_s2bm_ard_3-2-1_56LKP_2023-11-11_nrt
2023-11-11 09:49:47	ga_s2bm_ard_3-2-1_55LHJ_2023-11-11_nrt
2023-11-11 09:49:50	ga_s2bm_ard_3-2-1_56LMN_2023-11-11_nrt
2023-11-11 09:49:51	ga_s2bm_ard_3-2-1_55LGJ_2023-11-11_nrt
2023-11-11 09:49:56	ga_s2bm_ard_3-2-1_56LLN_2023-11-11_nrt
2023-11-11 09:49:59	ga_s2bm_ard_3-2-1_56LKN_2023-11-11_nrt
2023-11-11 09:50:00	ga_s2bm_ard_3-2-1_55LHH_2023-11-11_nrt
2023-11-11 09:50:00	ga_s2bm_ard_3-2-1_56LMM_2023-11-11_nrt
2023-11-11 09:50:01	ga_s2bm_ard_3-2-1_55LGH_2023-11-11_nrt
2023-11-11 09:50:04	ga_s2bm_ard_3-2-1_56LLM_2023-11-11_nrt
2023-11-11 09:50:06	ga_s2bm_ard_3-2-1_56LKM_2023-11-11_nrt
2023-11-11 09:50:06	ga_s2bm_ard_3-2-1_55LHG_2023-11-11_nrt
2023-11-11 09:51:01	ga_s2bm_ard_3-2-1_56LLJ_2023-11-11_nrt
2023-11-11 09:51:03	ga_s2bm_ard_3-2-1_56LKJ_2023-11-11_nrt
2023-11-11 09:51:03	ga_s2bm_ard_3-2-1_55LHD_2023-11-11_nrt
2023-11-11 09:51:05	ga_s2bm_ard_3-2-1_56LLH_2023-11-11_nrt
2023-11-11 09:51:05	ga_s2bm_ard_3-2-1_55LGD_2023-11-11_nrt
2023-11-11 09:51:07	ga_s2bm_ard_3-2-1_55LFD_2023-11-11_nrt
2023-11-11 09:51:12	ga_s2bm_ard_3-2-1_56LKH_2023-11-11_nrt
2023-11-11 09:57:08	ga_s2bm_ard_3-2-1_55HBV_2023-11-11_final
2023-11-11 09:57:09	ga_s2bm_ard_3-2-1_54HYE_2023-11-11_final
2023-11-11 09:57:10	ga_s2bm_ard_3-2-1_55HDU_2023-11-11_final
2023-11-11 09:57:13	ga_s2bm_ard_3-2-1_54HXE_2023-11-11_final
2023-11-11 09:57:19	ga_s2bm_ard_3-2-1_55HCU_2023-11-11_final
2023-11-11 09:57:23	ga_s2bm_ard_3-2-1_55HBU_2023-11-11_final
2023-11-11 09:57:24	ga_s2bm_ard_3-2-1_54HYD_2023-11-11_final
2023-11-11 09:57:28	ga_s2bm_ard_3-2-1_54HXD_2023-11-11_final
2023-11-11 09:57:34	ga_s2bm_ard_3-2-1_55HCT_2023-11-11_final
2023-11-11 09:57:37	ga_s2bm_ard_3-2-1_55HBT_2023-11-11_final
2023-11-11 09:57:38	ga_s2bm_ard_3-2-1_54HYC_2023-11-11_final
2023-11-11 09:57:42	ga_s2bm_ard_3-2-1_54HXC_2023-11-11_final
2023-11-11 09:57:47	ga_s2bm_ard_3-2-1_54HWC_2023-11-11_final
2023-11-11 09:57:48	ga_s2bm_ard_3-2-1_55HCS_2023-11-11_final
2023-11-11 09:57:52	ga_s2bm_ard_3-2-1_55HBS_2023-11-11_final
2023-11-11 09:57:52	ga_s2bm_ard_3-2-1_54HYB_2023-11-11_final
2023-11-11 09:57:56	ga_s2bm_ard_3-2-1_54HXB_2023-11-11_nrt
2023-11-11 09:58:00	ga_s2bm_ard_3-2-1_54HWB_2023-11-11_nrt
2023-11-11 09:58:02	ga_s2bm_ard_3-2-1_55GCR_2023-11-11_final
2023-11-11 09:58:06	ga_s2bm_ard_3-2-1_55GBR_2023-11-11_final
2023-11-11 09:58:07	ga_s2bm_ard_3-2-1_54GYA_2023-11-11_final
2023-11-11 09:58:11	ga_s2bm_ard_3-2-1_54GXA_2023-11-11_nrt
2023-11-11 09:58:15	ga_s2bm_ard_3-2-1_54GWA_2023-11-11_nrt
2023-11-11 09:58:15	ga_s2bm_ard_3-2-1_55GCQ_2023-11-11_final
2023-11-11 09:58:21	ga_s2bm_ard_3-2-1_55GBQ_2023-11-11_final
2023-11-11 09:58:21	ga_s2bm_ard_3-2-1_54GYV_2023-11-11_final
2023-11-11 09:58:25	ga_s2bm_ard_3-2-1_55GCP_2023-11-11_final
2023-11-11 09:58:25	ga_s2bm_ard_3-2-1_54GXV_2023-11-11_nrt
2023-11-11 09:58:28	ga_s2bm_ard_3-2-1_54GWV_2023-11-11_nrt
2023-11-11 09:58:30	ga_s2bm_ard_3-2-1_54GYU_2023-11-11_nrt
2023-11-11 09:58:30	ga_s2bm_ard_3-2-1_55GBP_2023-11-11_nrt
2023-11-11 09:58:32	ga_s2bm_ard_3-2-1_54GXU_2023-11-11_nrt
2023-11-11 09:58:33	ga_s2bm_ard_3-2-1_54GVV_2023-11-11_nrt
2023-11-11 11:30:15	ga_s2bm_ard_3-2-1_52LCP_2023-11-11_nrt
2023-11-11 11:30:22	ga_s2bm_ard_3-2-1_52LBP_2023-11-11_nrt
2023-11-11 11:30:24	ga_s2bm_ard_3-2-1_51LZJ_2023-11-11_nrt
2023-11-11 11:30:28	ga_s2bm_ard_3-2-1_51LYJ_2023-11-11_nrt
2023-11-11 11:30:31	ga_s2bm_ard_3-2-1_51LXJ_2023-11-11_nrt
2023-11-11 11:30:37	ga_s2bm_ard_3-2-1_52LBN_2023-11-11_nrt
2023-11-11 11:30:39	ga_s2bm_ard_3-2-1_51LZH_2023-11-11_nrt
2023-11-11 11:30:42	ga_s2bm_ard_3-2-1_51LYH_2023-11-11_nrt
2023-11-11 11:30:44	ga_s2bm_ard_3-2-1_51LXH_2023-11-11_nrt
2023-11-11 11:30:47	ga_s2bm_ard_3-2-1_52LBM_2023-11-11_nrt
2023-11-11 11:30:48	ga_s2bm_ard_3-2-1_51LZG_2023-11-11_nrt
2023-11-11 11:30:49	ga_s2bm_ard_3-2-1_51LYH_2023-11-11_nrt
2023-11-11 11:30:49	ga_s2bm_ard_3-2-1_51LYG_2023-11-11_nrt
2023-11-11 11:30:50	ga_s2bm_ard_3-2-1_51LXH_2023-11-11_nrt
2023-11-11 11:30:53	ga_s2bm_ard_3-2-1_52LBM_2023-11-11_nrt
2023-11-11 11:30:54	ga_s2bm_ard_3-2-1_51LZG_2023-11-11_nrt
2023-11-11 11:30:57	ga_s2bm_ard_3-2-1_51LYG_2023-11-11_nrt
2023-11-11 11:31:00	ga_s2bm_ard_3-2-1_51LXG_2023-11-11_nrt
2023-11-11 11:31:06	ga_s2bm_ard_3-2-1_52LBL_2023-11-11_nrt
2023-11-11 11:31:07	ga_s2bm_ard_3-2-1_51LZF_2023-11-11_nrt
2023-11-11 11:31:11	ga_s2bm_ard_3-2-1_51LYF_2023-11-11_nrt
2023-11-11 11:31:15	ga_s2bm_ard_3-2-1_51LXF_2023-11-11_nrt
2023-11-11 11:31:19	ga_s2bm_ard_3-2-1_51LWF_2023-11-11_nrt
2023-11-11 11:31:19	ga_s2bm_ard_3-2-1_52LBK_2023-11-11_final
2023-11-11 11:31:22	ga_s2bm_ard_3-2-1_51LZE_2023-11-11_final
2023-11-11 11:31:26	ga_s2bm_ard_3-2-1_51LYE_2023-11-11_final
2023-11-11 11:31:29	ga_s2bm_ard_3-2-1_51LXE_2023-11-11_nrt
2023-11-11 11:31:30	ga_s2bm_ard_3-2-1_52LBJ_2023-11-11_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