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
2023-02-20 11:57:22	ga_s2bm_ard_3-2-1_49HFC_2023-02-20_nrt.stac-item
2023-02-20 11:57:22	ga_s2bm_ard_3-2-1_50HLG_2023-02-20_final
2023-02-20 11:57:24	ga_s2bm_ard_3-2-1_50HKG_2023-02-20_nrt.stac-item
2023-02-20 11:57:24	ga_s2bm_ard_3-2-1_49HGB_2023-02-20_nrt.stac-item
2023-02-20 11:57:27	ga_s2bm_ard_3-2-1_49HFB_2023-02-20_nrt.stac-item
2023-02-20 11:57:27	ga_s2bm_ard_3-2-1_50HMF_2023-02-20_nrt.stac-item
2023-02-20 11:57:29	ga_s2bm_ard_3-2-1_50HLF_2023-02-20_nrt.stac-item
2023-02-21 09:39:34	ga_s2bm_ard_3-2-1_56LPP_2023-02-21_nrt.stac-item
2023-02-21 09:39:38	ga_s2bm_ard_3-2-1_56LNP_2023-02-21_nrt.stac-item
2023-02-21 09:39:41	ga_s2bm_ard_3-2-1_56LMP_2023-02-21_nrt.stac-item
2023-02-21 09:39:48	ga_s2bm_ard_3-2-1_56LLP_2023-02-21_nrt.stac-item
2023-02-21 09:39:49	ga_s2bm_ard_3-2-1_56LPN_2023-02-21_nrt.stac-item
2023-02-21 09:39:53	ga_s2bm_ard_3-2-1_56LNN_2023-02-21_nrt.stac-item
2023-02-21 09:39:56	ga_s2bm_ard_3-2-1_56LMN_2023-02-21_nrt.stac-item
2023-02-21 09:39:59	ga_s2bm_ard_3-2-1_56LLN_2023-02-21_nrt.stac-item
2023-02-21 09:40:03	ga_s2bm_ard_3-2-1_56LPM_2023-02-21_nrt.stac-item
2023-02-21 09:40:05	ga_s2bm_ard_3-2-1_56LNM_2023-02-21_nrt.stac-item
2023-02-21 09:40:07	ga_s2bm_ard_3-2-1_56LMM_2023-02-21_nrt.stac-item
2023-02-21 09:40:08	ga_s2bm_ard_3-2-1_56LLM_2023-02-21_nrt.stac-item
2023-02-21 09:40:11	ga_s2bm_ard_3-2-1_56LPL_2023-02-21_nrt.stac-item
2023-02-21 09:41:13	ga_s2bm_ard_3-2-1_56LNH_2023-02-21_nrt.stac-item
2023-02-21 09:41:14	ga_s2bm_ard_3-2-1_56LMH_2023-02-21_nrt.stac-item
2023-02-21 09:41:16	ga_s2bm_ard_3-2-1_56LLH_2023-02-21_nrt.stac-item
2023-02-21 09:41:17	ga_s2bm_ard_3-2-1_56LKH_2023-02-21_nrt.stac-item
2023-02-21 09:41:20	ga_s2bm_ard_3-2-1_56KNG_2023-02-21_nrt.stac-item
2023-02-21 09:41:34	ga_s2bm_ard_3-2-1_56KNF_2023-02-21_nrt.stac-item
2023-02-21 09:41:41	ga_s2bm_ard_3-2-1_56KLF_2023-02-21_final
2023-02-21 09:41:44	ga_s2bm_ard_3-2-1_56KKF_2023-02-21_final
2023-02-21 09:41:45	ga_s2bm_ard_3-2-1_55KHA_2023-02-21_nrt.stac-item
2023-02-21 09:41:46	ga_s2bm_ard_3-2-1_56KNE_2023-02-21_nrt.stac-item
2023-02-21 09:41:55	ga_s2bm_ard_3-2-1_56KLE_2023-02-21_final
2023-02-21 09:41:59	ga_s2bm_ard_3-2-1_56KKE_2023-02-21_nrt.stac-item
2023-02-21 09:41:59	ga_s2bm_ard_3-2-1_55KHV_2023-02-21_nrt.stac-item
2023-02-21 09:47:32	ga_s2bm_ard_3-2-1_55HDT_2023-02-21_final
2023-02-21 09:47:36	ga_s2bm_ard_3-2-1_55HCT_2023-02-21_final
2023-02-21 09:47:57	ga_s2bm_ard_3-2-1_55GER_2023-02-21_final
2023-02-21 09:48:01	ga_s2bm_ard_3-2-1_55GDR_2023-02-21_final
2023-02-21 09:48:05	ga_s2bm_ard_3-2-1_55GCR_2023-02-21_final
2023-02-21 09:48:08	ga_s2bm_ard_3-2-1_54GYA_2023-02-21_final
2023-02-21 09:48:11	ga_s2bm_ard_3-2-1_55GEQ_2023-02-21_final
2023-02-21 09:48:19	ga_s2bm_ard_3-2-1_55GCQ_2023-02-21_final
2023-02-21 09:48:45	ga_s2bm_ard_3-2-1_55GDN_2023-02-21_final
2023-02-21 09:48:48	ga_s2bm_ard_3-2-1_55GCN_2023-02-21_final
2023-02-21 11:21:24	ga_s2bm_ard_3-2-1_52LBK_2023-02-21_final
2023-02-21 11:21:35	ga_s2bm_ard_3-2-1_52LCJ_2023-02-21_final
2023-02-21 11:21:39	ga_s2bm_ard_3-2-1_51LZD_2023-02-21_final
2023-02-21 11:21:46	ga_s2bm_ard_3-2-1_52LDH_2023-02-21_final
2023-02-21 11:21:50	ga_s2bm_ard_3-2-1_52LCH_2023-02-21_final
2023-02-21 11:21:53	ga_s2bm_ard_3-2-1_52LBH_2023-02-21_final
2023-02-21 11:21:54	ga_s2bm_ard_3-2-1_51LZC_2023-02-21_nrt.stac-item
2023-02-21 11:21:54	ga_s2bm_ard_3-2-1_51LZC_2023-02-21_final
2023-02-21 11:21:58	ga_s2bm_ard_3-2-1_51LYC_2023-02-21_final
2023-02-21 11:22:00	ga_s2bm_ard_3-2-1_52KDG_2023-02-21_nrt.stac-item
2023-02-21 11:22:00	ga_s2bm_ard_3-2-1_52KDG_2023-02-21_final
2023-02-21 11:22:04	ga_s2bm_ard_3-2-1_52KCG_2023-02-21_final
2023-02-21 11:22:07	ga_s2bm_ard_3-2-1_52KBG_2023-02-21_final
2023-02-21 11:22:08	ga_s2bm_ard_3-2-1_51KZB_2023-02-21_final
2023-02-21 11:22:11	ga_s2bm_ard_3-2-1_51KYB_2023-02-21_final
2023-02-21 11:22:12	ga_s2bm_ard_3-2-1_52KDF_2023-02-21_final
2023-02-21 11:22:18	ga_s2bm_ard_3-2-1_52KCF_2023-02-21_final
2023-02-21 11:22:22	ga_s2bm_ard_3-2-1_52KBF_2023-02-21_final
2023-02-21 11:22:23	ga_s2bm_ard_3-2-1_51KZA_2023-02-21_final
2023-02-21 11:22:26	ga_s2bm_ard_3-2-1_51KYA_2023-02-21_nrt.stac-item
2023-02-21 11:22:26	ga_s2bm_ard_3-2-1_51KYA_2023-02-21_final
2023-02-21 11:22:33	ga_s2bm_ard_3-2-1_52KCE_2023-02-21_final
2023-02-21 11:22:36	ga_s2bm_ard_3-2-1_52KBE_2023-02-21_final
2023-02-21 11:22:37	ga_s2bm_ard_3-2-1_51KZV_2023-02-21_final
2023-02-21 11:22:41	ga_s2bm_ard_3-2-1_51KYV_2023-02-21_final
2023-02-21 11:22:47	ga_s2bm_ard_3-2-1_52KCD_2023-02-21_final
2023-02-21 11:22:49	ga_s2bm_ard_3-2-1_52KBD_2023-02-21_nrt.stac-item
2023-02-21 11:22:49	ga_s2bm_ard_3-2-1_52KBD_2023-02-21_final
2023-02-21 11:22:49	ga_s2bm_ard_3-2-1_51KZU_2023-02-21_final
2023-02-21 11:22:51	ga_s2bm_ard_3-2-1_51KYU_2023-02-21_final
2023-02-21 11:22:53	ga_s2bm_ard_3-2-1_51KXU_2023-02-21_final
2023-02-21 11:22:54	ga_s2bm_ard_3-2-1_52KCC_2023-02-21_final
2023-02-21 11:22:54	ga_s2bm_ard_3-2-1_52KCD_2023-02-21_final
2023-02-21 11:22:56	ga_s2bm_ard_3-2-1_52KBD_2023-02-21_final
2023-02-21 11:22:56	ga_s2bm_ard_3-2-1_51KZU_2023-02-21_final
2023-02-21 11:22:58	ga_s2bm_ard_3-2-1_51KYU_2023-02-21_final
2023-02-21 11:23:01	ga_s2bm_ard_3-2-1_51KXU_2023-02-21_final
2023-02-21 11:23:02	ga_s2bm_ard_3-2-1_52KCC_2023-02-21_final
2023-02-21 11:23:06	ga_s2bm_ard_3-2-1_52KBC_2023-02-21_final
2023-02-21 11:23:06	ga_s2bm_ard_3-2-1_51KZT_2023-02-21_final
2023-02-21 11:23:10	ga_s2bm_ard_3-2-1_51KYT_2023-02-21_final
2023-02-21 11:23:13	ga_s2bm_ard_3-2-1_51KXT_2023-02-21_final
2023-02-21 11:23:16	ga_s2bm_ard_3-2-1_52KCB_2023-02-21_final
2023-02-21 11:23:20	ga_s2bm_ard_3-2-1_52KBB_2023-02-21_nrt.stac-item
2023-02-21 11:23:20	ga_s2bm_ard_3-2-1_52KBB_2023-02-21_final
2023-02-21 11:23:21	ga_s2bm_ard_3-2-1_51KZS_2023-02-21_final
2023-02-21 11:23:24	ga_s2bm_ard_3-2-1_51KYS_2023-02-21_final
2023-02-21 11:23:27	ga_s2bm_ard_3-2-1_52KCA_2023-02-21_final
2023-02-21 11:23:27	ga_s2bm_ard_3-2-1_51KXS_2023-02-21_final
2023-02-21 11:23:34	ga_s2bm_ard_3-2-1_52KBA_2023-02-21_final
2023-02-21 11:23:35	ga_s2bm_ard_3-2-1_51KZR_2023-02-21_final
2023-02-21 11:23:39	ga_s2bm_ard_3-2-1_51KYR_2023-02-21_final
2023-02-21 11:23:42	ga_s2bm_ard_3-2-1_51KXR_2023-02-21_final
2023-02-21 11:23:49	ga_s2bm_ard_3-2-1_52KBV_2023-02-21_final
2023-02-21 11:23:49	ga_s2bm_ard_3-2-1_51KZQ_2023-02-21_final
2023-02-21 11:23:53	ga_s2bm_ard_3-2-1_51KYQ_2023-02-21_final
2023-02-21 11:23:57	ga_s2bm_ard_3-2-1_51KXQ_2023-02-21_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