Search ga_s2bm_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

81 results

Time (local)	Label
2023-04-01 11:50:33	ga_s2bm_ard_3-2-1_51LUJ_2023-04-01_nrt.stac-item
2023-04-01 11:50:36	ga_s2bm_ard_3-2-1_51LTJ_2023-04-01_nrt.stac-item
2023-04-01 11:50:38	ga_s2bm_ard_3-2-1_50LRP_2023-04-01_nrt.stac-item
2023-04-01 11:50:47	ga_s2bm_ard_3-2-1_51LUH_2023-04-01_nrt.stac-item
2023-04-01 11:50:53	ga_s2bm_ard_3-2-1_50LRN_2023-04-01_nrt.stac-item
2023-04-01 11:50:56	ga_s2bm_ard_3-2-1_50LQN_2023-04-01_nrt.stac-item
2023-04-01 11:51:06	ga_s2bm_ard_3-2-1_51LTG_2023-04-01_nrt.stac-item
2023-04-01 11:51:20	ga_s2bm_ard_3-2-1_51LTF_2023-04-01_nrt.stac-item
2023-04-01 11:51:22	ga_s2bm_ard_3-2-1_50LRL_2023-04-01_nrt.stac-item
2023-04-01 11:51:25	ga_s2bm_ard_3-2-1_50LQL_2023-04-01_nrt.stac-item
2023-04-01 11:51:36	ga_s2bm_ard_3-2-1_50LRK_2023-04-01_nrt.stac-item
2023-04-01 11:51:43	ga_s2bm_ard_3-2-1_50LPK_2023-04-01_nrt.stac-item
2023-04-01 11:51:49	ga_s2bm_ard_3-2-1_51LTD_2023-04-01_nrt.stac-item
2023-04-01 11:51:51	ga_s2bm_ard_3-2-1_50LRJ_2023-04-01_nrt.stac-item
2023-04-01 11:51:54	ga_s2bm_ard_3-2-1_50LQJ_2023-04-01_nrt.stac-item
2023-04-01 11:51:57	ga_s2bm_ard_3-2-1_50LPJ_2023-04-01_nrt.stac-item
2023-04-01 11:52:03	ga_s2bm_ard_3-2-1_51LTC_2023-04-01_nrt.stac-item
2023-04-01 11:52:05	ga_s2bm_ard_3-2-1_50LRH_2023-04-01_nrt.stac-item
2023-04-01 11:52:08	ga_s2bm_ard_3-2-1_50LQH_2023-04-01_nrt.stac-item
2023-04-01 11:52:12	ga_s2bm_ard_3-2-1_50LPH_2023-04-01_nrt.stac-item
2023-04-01 11:52:18	ga_s2bm_ard_3-2-1_51KTB_2023-04-01_nrt.stac-item
2023-04-01 11:52:19	ga_s2bm_ard_3-2-1_50KRG_2023-04-01_nrt.stac-item
2023-04-01 11:52:26	ga_s2bm_ard_3-2-1_50KPG_2023-04-01_nrt.stac-item
2023-04-01 11:52:32	ga_s2bm_ard_3-2-1_50KNG_2023-04-01_nrt.stac-item
2023-04-01 11:52:33	ga_s2bm_ard_3-2-1_51KTA_2023-04-01_nrt.stac-item
2023-04-01 11:52:34	ga_s2bm_ard_3-2-1_50KRF_2023-04-01_nrt.stac-item
2023-04-01 11:52:44	ga_s2bm_ard_3-2-1_50KNF_2023-04-01_nrt.stac-item
2023-04-01 11:52:46	ga_s2bm_ard_3-2-1_51KTV_2023-04-01_nrt.stac-item
2023-04-01 11:52:55	ga_s2bm_ard_3-2-1_50KPE_2023-04-01_nrt.stac-item
2023-04-01 11:53:13	ga_s2bm_ard_3-2-1_50KND_2023-04-01_nrt.stac-item
2023-04-01 11:56:49	ga_s2bm_ard_3-2-1_49HGE_2023-04-01_nrt.stac-item
2023-04-01 11:57:01	ga_s2bm_ard_3-2-1_50HKJ_2023-04-01_nrt.stac-item
2023-04-01 11:57:03	ga_s2bm_ard_3-2-1_49HGD_2023-04-01_nrt.stac-item
2023-04-01 11:57:18	ga_s2bm_ard_3-2-1_49HGC_2023-04-01_nrt.stac-item
2023-04-01 11:57:28	ga_s2bm_ard_3-2-1_50HKG_2023-04-01_nrt.stac-item
2023-04-01 11:57:29	ga_s2bm_ard_3-2-1_49HGB_2023-04-01_nrt.stac-item
2023-04-01 11:57:31	ga_s2bm_ard_3-2-1_49HFB_2023-04-01_nrt.stac-item
2023-04-01 11:57:33	ga_s2bm_ard_3-2-1_50HLF_2023-04-01_nrt.stac-item
2023-04-02 09:39:38	ga_s2bm_ard_3-2-1_56LPP_2023-04-02_nrt.stac-item
2023-04-02 09:39:42	ga_s2bm_ard_3-2-1_56LNP_2023-04-02_nrt.stac-item
2023-04-02 09:39:45	ga_s2bm_ard_3-2-1_56LMP_2023-04-02_nrt.stac-item
2023-04-02 09:39:52	ga_s2bm_ard_3-2-1_56LLP_2023-04-02_nrt.stac-item
2023-04-02 09:39:53	ga_s2bm_ard_3-2-1_56LPN_2023-04-02_nrt.stac-item
2023-04-02 09:39:57	ga_s2bm_ard_3-2-1_56LNN_2023-04-02_nrt.stac-item
2023-04-02 09:40:00	ga_s2bm_ard_3-2-1_56LMN_2023-04-02_nrt.stac-item
2023-04-02 09:40:03	ga_s2bm_ard_3-2-1_56LLN_2023-04-02_nrt.stac-item
2023-04-02 09:40:07	ga_s2bm_ard_3-2-1_56LPM_2023-04-02_nrt.stac-item
2023-04-02 09:40:09	ga_s2bm_ard_3-2-1_56LNM_2023-04-02_nrt.stac-item
2023-04-02 09:40:11	ga_s2bm_ard_3-2-1_56LMM_2023-04-02_nrt.stac-item
2023-04-02 09:40:12	ga_s2bm_ard_3-2-1_56LLM_2023-04-02_nrt.stac-item
2023-04-02 09:40:15	ga_s2bm_ard_3-2-1_56LPL_2023-04-02_nrt.stac-item
2023-04-02 09:40:17	ga_s2bm_ard_3-2-1_56LNL_2023-04-02_nrt.stac-item
2023-04-02 09:41:17	ga_s2bm_ard_3-2-1_56LNH_2023-04-02_nrt.stac-item
2023-04-02 09:41:18	ga_s2bm_ard_3-2-1_56LMH_2023-04-02_nrt.stac-item
2023-04-02 09:41:20	ga_s2bm_ard_3-2-1_56LLH_2023-04-02_nrt.stac-item
2023-04-02 09:41:21	ga_s2bm_ard_3-2-1_56LKH_2023-04-02_nrt.stac-item
2023-04-02 09:41:24	ga_s2bm_ard_3-2-1_56KNG_2023-04-02_nrt.stac-item
2023-04-02 09:41:37	ga_s2bm_ard_3-2-1_56KNF_2023-04-02_nrt.stac-item
2023-04-02 09:41:48	ga_s2bm_ard_3-2-1_55KHA_2023-04-02_nrt.stac-item
2023-04-02 09:41:50	ga_s2bm_ard_3-2-1_56KNE_2023-04-02_nrt.stac-item
2023-04-02 09:42:03	ga_s2bm_ard_3-2-1_56KKE_2023-04-02_nrt.stac-item
2023-04-02 09:42:03	ga_s2bm_ard_3-2-1_55KHV_2023-04-02_nrt.stac-item
2023-04-02 09:42:17	ga_s2bm_ard_3-2-1_56KKD_2023-04-02_nrt.stac-item
2023-04-02 09:42:18	ga_s2bm_ard_3-2-1_55KHU_2023-04-02_nrt.stac-item
2023-04-02 09:42:25	ga_s2bm_ard_3-2-1_56KMC_2023-04-02_nrt.stac-item
2023-04-02 09:42:28	ga_s2bm_ard_3-2-1_56KLC_2023-04-02_nrt.stac-item
2023-04-02 09:42:31	ga_s2bm_ard_3-2-1_56KKC_2023-04-02_nrt.stac-item
2023-04-02 09:42:32	ga_s2bm_ard_3-2-1_55KHT_2023-04-02_nrt.stac-item
2023-04-02 09:43:04	ga_s2bm_ard_3-2-1_56KMV_2023-04-02_nrt.stac-item
2023-04-02 09:48:41	ga_s2bm_ard_3-2-1_54GYU_2023-04-02_nrt.stac-item
2023-04-02 09:48:41	ga_s2bm_ard_3-2-1_55GBP_2023-04-02_nrt.stac-item
2023-04-02 09:48:46	ga_s2bm_ard_3-2-1_54GXU_2023-04-02_nrt.stac-item
2023-04-02 09:48:55	ga_s2bm_ard_3-2-1_54GYT_2023-04-02_nrt.stac-item
2023-04-02 09:48:59	ga_s2bm_ard_3-2-1_54GXT_2023-04-02_nrt.stac-item
2023-04-02 09:49:05	ga_s2bm_ard_3-2-1_54GYS_2023-04-02_nrt.stac-item
2023-04-02 09:49:07	ga_s2bm_ard_3-2-1_54GXS_2023-04-02_nrt.stac-item
2023-04-02 11:20:26	ga_s2bm_ard_3-2-1_52LCP_2023-04-02_nrt.stac-item
2023-04-02 11:20:29	ga_s2bm_ard_3-2-1_52LBP_2023-04-02_nrt.stac-item
2023-04-02 11:20:41	ga_s2bm_ard_3-2-1_52LCN_2023-04-02_nrt.stac-item
2023-04-02 11:20:58	ga_s2bm_ard_3-2-1_52LBM_2023-04-02_nrt.stac-item
2023-04-02 11:27:18	ga_s2bm_ard_3-2-1_51HWA_2023-04-02_nrt.stac-item

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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years