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
2023-09-27 10:41:55	ga_s2bm_ard_3-2-1_53KPB_2023-09-27_final
2023-09-27 10:41:57	ga_s2bm_ard_3-2-1_54KTF_2023-09-27_final
2023-09-27 10:41:58	ga_s2bm_ard_3-2-1_53KNB_2023-09-27_final
2023-09-27 10:42:02	ga_s2bm_ard_3-2-1_53KRA_2023-09-27_final
2023-09-27 10:42:06	ga_s2bm_ard_3-2-1_53KQA_2023-09-27_final
2023-09-27 10:42:10	ga_s2bm_ard_3-2-1_53KPA_2023-09-27_final
2023-09-27 10:42:13	ga_s2bm_ard_3-2-1_53KNA_2023-09-27_final
2023-09-27 10:42:15	ga_s2bm_ard_3-2-1_53KRV_2023-09-27_final
2023-09-27 10:42:21	ga_s2bm_ard_3-2-1_53KQV_2023-09-27_final
2023-09-27 10:42:24	ga_s2bm_ard_3-2-1_53KPV_2023-09-27_final
2023-09-27 10:42:25	ga_s2bm_ard_3-2-1_53KRU_2023-09-27_final
2023-09-27 10:42:28	ga_s2bm_ard_3-2-1_53KNV_2023-09-27_final
2023-09-27 10:42:35	ga_s2bm_ard_3-2-1_53KQU_2023-09-27_final
2023-09-27 10:42:39	ga_s2bm_ard_3-2-1_53KPU_2023-09-27_final
2023-09-27 10:42:42	ga_s2bm_ard_3-2-1_53KNU_2023-09-27_final
2023-09-27 10:42:46	ga_s2bm_ard_3-2-1_53KMU_2023-09-27_final
2023-09-27 10:42:50	ga_s2bm_ard_3-2-1_53KQT_2023-09-27_final
2023-09-27 10:42:52	ga_s2bm_ard_3-2-1_53KPT_2023-09-27_final
2023-09-27 10:42:54	ga_s2bm_ard_3-2-1_53KNT_2023-09-27_final
2023-09-27 10:42:56	ga_s2bm_ard_3-2-1_53KMT_2023-09-27_final
2023-09-27 10:42:58	ga_s2bm_ard_3-2-1_53KQT_2023-09-27_final
2023-09-27 10:45:43	ga_s2bm_ard_3-2-1_53JLG_2023-09-27_final
2023-09-27 10:45:45	ga_s2bm_ard_3-2-1_53JNF_2023-09-27_final
2023-09-27 10:45:47	ga_s2bm_ard_3-2-1_53JKG_2023-09-27_final
2023-09-27 10:45:50	ga_s2bm_ard_3-2-1_52JGM_2023-09-27_final
2023-09-27 10:45:54	ga_s2bm_ard_3-2-1_53JMF_2023-09-27_final
2023-09-27 10:45:58	ga_s2bm_ard_3-2-1_53JLF_2023-09-27_final
2023-09-27 10:46:01	ga_s2bm_ard_3-2-1_53JKF_2023-09-27_final
2023-09-27 10:46:03	ga_s2bm_ard_3-2-1_52JGL_2023-09-27_final
2023-09-27 10:46:09	ga_s2bm_ard_3-2-1_53HME_2023-09-27_final
2023-09-27 10:46:12	ga_s2bm_ard_3-2-1_53HLE_2023-09-27_final
2023-09-27 10:46:16	ga_s2bm_ard_3-2-1_53HKE_2023-09-27_final
2023-09-27 10:46:18	ga_s2bm_ard_3-2-1_52HGK_2023-09-27_final
2023-09-27 10:46:24	ga_s2bm_ard_3-2-1_53HMD_2023-09-27_final
2023-09-27 10:46:27	ga_s2bm_ard_3-2-1_53HLD_2023-09-27_final
2023-09-27 10:46:29	ga_s2bm_ard_3-2-1_53HKD_2023-09-27_nrt
2023-09-27 10:46:30	ga_s2bm_ard_3-2-1_52HGJ_2023-09-27_nrt
2023-09-27 10:46:33	ga_s2bm_ard_3-2-1_53HMC_2023-09-27_final
2023-09-27 10:46:35	ga_s2bm_ard_3-2-1_52HFJ_2023-09-27_nrt
2023-09-27 10:46:37	ga_s2bm_ard_3-2-1_53HKC_2023-09-27_nrt
2023-09-27 14:13:39	ga_s2bm_ard_3-2-1_43FDB_2023-09-27_final
2023-09-27 14:13:42	ga_s2bm_ard_3-2-1_43FCB_2023-09-27_final
2023-09-28 08:34:23	ga_s2bm_ard_3-2-1_59JKH_2023-09-27_final
2023-09-28 08:34:25	ga_s2bm_ard_3-2-1_58JGN_2023-09-27_final
2023-09-28 08:41:43	ga_s2bm_ard_3-2-1_57FVV_2023-09-27_final
2023-09-28 10:09:48	ga_s2bm_ard_3-2-1_55LEJ_2023-09-28_nrt
2023-09-28 10:09:52	ga_s2bm_ard_3-2-1_55LDJ_2023-09-28_nrt
2023-09-28 10:09:55	ga_s2bm_ard_3-2-1_55LCJ_2023-09-28_nrt
2023-09-28 10:09:58	ga_s2bm_ard_3-2-1_55LBJ_2023-09-28_nrt
2023-09-28 10:10:01	ga_s2bm_ard_3-2-1_54LZP_2023-09-28_final
2023-09-28 10:10:01	ga_s2bm_ard_3-2-1_55LEH_2023-09-28_nrt
2023-09-28 10:10:06	ga_s2bm_ard_3-2-1_55LDH_2023-09-28_nrt
2023-09-28 10:10:09	ga_s2bm_ard_3-2-1_55LCH_2023-09-28_nrt
2023-09-28 10:10:11	ga_s2bm_ard_3-2-1_55LEG_2023-09-28_nrt
2023-09-28 10:10:13	ga_s2bm_ard_3-2-1_55LBH_2023-09-28_nrt
2023-09-28 10:10:14	ga_s2bm_ard_3-2-1_54LZN_2023-09-28_final
2023-09-28 10:10:20	ga_s2bm_ard_3-2-1_55LDG_2023-09-28_nrt
2023-09-28 10:10:24	ga_s2bm_ard_3-2-1_55LCG_2023-09-28_nrt
2023-09-28 10:10:27	ga_s2bm_ard_3-2-1_55LBG_2023-09-28_nrt
2023-09-28 10:10:28	ga_s2bm_ard_3-2-1_54LZM_2023-09-28_final
2023-09-28 10:10:35	ga_s2bm_ard_3-2-1_55LDF_2023-09-28_nrt
2023-09-28 10:10:38	ga_s2bm_ard_3-2-1_55LCF_2023-09-28_nrt
2023-09-28 10:10:42	ga_s2bm_ard_3-2-1_55LBF_2023-09-28_nrt
2023-09-28 10:10:43	ga_s2bm_ard_3-2-1_54LZL_2023-09-28_final
2023-09-28 10:10:50	ga_s2bm_ard_3-2-1_55LDE_2023-09-28_nrt
2023-09-28 10:10:53	ga_s2bm_ard_3-2-1_55LCE_2023-09-28_final
2023-09-28 10:10:56	ga_s2bm_ard_3-2-1_55LBE_2023-09-28_final
2023-09-28 10:10:58	ga_s2bm_ard_3-2-1_54LZK_2023-09-28_final
2023-09-28 10:11:03	ga_s2bm_ard_3-2-1_54LYK_2023-09-28_final
2023-09-28 10:11:04	ga_s2bm_ard_3-2-1_55LDD_2023-09-28_nrt
2023-09-28 10:11:08	ga_s2bm_ard_3-2-1_55LCD_2023-09-28_final
2023-09-28 10:11:11	ga_s2bm_ard_3-2-1_55LBD_2023-09-28_final
2023-09-28 10:11:12	ga_s2bm_ard_3-2-1_54LZJ_2023-09-28_final
2023-09-28 10:11:15	ga_s2bm_ard_3-2-1_54LYJ_2023-09-28_final
2023-09-28 10:11:16	ga_s2bm_ard_3-2-1_55LDC_2023-09-28_nrt
2023-09-28 10:11:22	ga_s2bm_ard_3-2-1_55LCC_2023-09-28_final
2023-09-28 10:11:25	ga_s2bm_ard_3-2-1_55LBC_2023-09-28_final
2023-09-28 10:11:27	ga_s2bm_ard_3-2-1_54LZH_2023-09-28_final
2023-09-28 10:11:30	ga_s2bm_ard_3-2-1_54LYH_2023-09-28_final
2023-09-28 10:11:36	ga_s2bm_ard_3-2-1_55KCB_2023-09-28_final
2023-09-28 10:11:40	ga_s2bm_ard_3-2-1_55KBB_2023-09-28_final
2023-09-28 10:11:41	ga_s2bm_ard_3-2-1_54KZG_2023-09-28_final
2023-09-28 10:11:44	ga_s2bm_ard_3-2-1_54KYG_2023-09-28_final
2023-09-28 10:11:54	ga_s2bm_ard_3-2-1_55KBA_2023-09-28_final
2023-09-28 10:11:56	ga_s2bm_ard_3-2-1_54KZF_2023-09-28_final
2023-09-28 10:12:05	ga_s2bm_ard_3-2-1_54KXF_2023-09-28_final
2023-09-28 10:12:09	ga_s2bm_ard_3-2-1_55KBV_2023-09-28_final
2023-09-28 10:12:13	ga_s2bm_ard_3-2-1_54KYE_2023-09-28_final
2023-09-28 10:12:19	ga_s2bm_ard_3-2-1_55KCU_2023-09-28_final
2023-09-28 10:12:23	ga_s2bm_ard_3-2-1_55KBU_2023-09-28_final
2023-09-28 10:12:24	ga_s2bm_ard_3-2-1_54KZD_2023-09-28_final
2023-09-28 10:12:28	ga_s2bm_ard_3-2-1_54KYD_2023-09-28_final
2023-09-28 10:12:38	ga_s2bm_ard_3-2-1_55KBT_2023-09-28_final
2023-09-28 10:12:42	ga_s2bm_ard_3-2-1_54KYC_2023-09-28_final
2023-09-28 10:12:46	ga_s2bm_ard_3-2-1_54KXC_2023-09-28_final
2023-09-28 10:12:52	ga_s2bm_ard_3-2-1_55KBS_2023-09-28_final
2023-09-28 10:12:57	ga_s2bm_ard_3-2-1_54KYB_2023-09-28_final
2023-09-28 10:12:59	ga_s2bm_ard_3-2-1_54KXB_2023-09-28_final
2023-09-28 10:13:02	ga_s2bm_ard_3-2-1_55KBR_2023-09-28_final
2023-09-28 10:13:04	ga_s2bm_ard_3-2-1_54KYB_2023-09-28_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