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

First 100 results (query limit)

Time (local)	Label
2022-12-22 10:09:48	ga_s2bm_ard_3-2-1_55LDJ_2022-12-22_nrt.stac-item
2022-12-22 10:09:51	ga_s2bm_ard_3-2-1_55LCJ_2022-12-22_nrt.stac-item
2022-12-22 10:09:54	ga_s2bm_ard_3-2-1_55LBJ_2022-12-22_nrt.stac-item
2022-12-22 10:10:02	ga_s2bm_ard_3-2-1_55LDH_2022-12-22_nrt.stac-item
2022-12-22 10:10:06	ga_s2bm_ard_3-2-1_55LCH_2022-12-22_nrt.stac-item
2022-12-22 10:10:09	ga_s2bm_ard_3-2-1_55LBH_2022-12-22_nrt.stac-item
2022-12-22 10:10:20	ga_s2bm_ard_3-2-1_55LCG_2022-12-22_nrt.stac-item
2022-12-22 10:10:23	ga_s2bm_ard_3-2-1_55LBG_2022-12-22_nrt.stac-item
2022-12-22 10:10:31	ga_s2bm_ard_3-2-1_55LDF_2022-12-22_nrt.stac-item
2022-12-22 10:10:35	ga_s2bm_ard_3-2-1_55LCF_2022-12-22_nrt.stac-item
2022-12-22 10:10:38	ga_s2bm_ard_3-2-1_55LBF_2022-12-22_nrt.stac-item
2022-12-22 10:10:46	ga_s2bm_ard_3-2-1_55LDE_2022-12-22_nrt.stac-item
2022-12-22 10:11:00	ga_s2bm_ard_3-2-1_55LDD_2022-12-22_nrt.stac-item
2022-12-22 10:11:12	ga_s2bm_ard_3-2-1_55LDC_2022-12-22_nrt.stac-item
2022-12-22 10:17:32	ga_s2bm_ard_3-2-1_54HTD_2022-12-22_nrt.stac-item
2022-12-22 10:17:33	ga_s2bm_ard_3-2-1_53HQU_2022-12-22_nrt.stac-item
2022-12-22 11:50:29	ga_s2bm_ard_3-2-1_51LUJ_2022-12-22_nrt.stac-item
2022-12-22 11:50:32	ga_s2bm_ard_3-2-1_51LTJ_2022-12-22_nrt.stac-item
2022-12-22 11:50:34	ga_s2bm_ard_3-2-1_50LRP_2022-12-22_nrt.stac-item
2022-12-22 11:50:37	ga_s2bm_ard_3-2-1_50LQP_2022-12-22_nrt.stac-item
2022-12-22 11:50:43	ga_s2bm_ard_3-2-1_51LUH_2022-12-22_nrt.stac-item
2022-12-22 11:50:47	ga_s2bm_ard_3-2-1_51LTH_2022-12-22_nrt.stac-item
2022-12-22 11:50:48	ga_s2bm_ard_3-2-1_50LRN_2022-12-22_nrt.stac-item
2022-12-22 11:50:52	ga_s2bm_ard_3-2-1_50LQN_2022-12-22_nrt.stac-item
2022-12-22 11:50:58	ga_s2bm_ard_3-2-1_51LUG_2022-12-22_nrt.stac-item
2022-12-22 11:51:01	ga_s2bm_ard_3-2-1_51LTG_2022-12-22_nrt.stac-item
2022-12-22 11:51:03	ga_s2bm_ard_3-2-1_50LRM_2022-12-22_nrt.stac-item
2022-12-22 11:51:06	ga_s2bm_ard_3-2-1_50LQM_2022-12-22_nrt.stac-item
2022-12-22 11:51:16	ga_s2bm_ard_3-2-1_51LTF_2022-12-22_nrt.stac-item
2022-12-22 11:51:17	ga_s2bm_ard_3-2-1_50LRL_2022-12-22_nrt.stac-item
2022-12-22 11:51:21	ga_s2bm_ard_3-2-1_50LQL_2022-12-22_nrt.stac-item
2022-12-22 11:51:25	ga_s2bm_ard_3-2-1_50LPL_2022-12-22_nrt.stac-item
2022-12-22 11:51:30	ga_s2bm_ard_3-2-1_51LTE_2022-12-22_nrt.stac-item
2022-12-22 11:51:32	ga_s2bm_ard_3-2-1_50LRK_2022-12-22_nrt.stac-item
2022-12-22 11:51:35	ga_s2bm_ard_3-2-1_50LQK_2022-12-22_nrt.stac-item
2022-12-22 11:51:38	ga_s2bm_ard_3-2-1_50LPK_2022-12-22_nrt.stac-item
2022-12-22 11:51:45	ga_s2bm_ard_3-2-1_51LTD_2022-12-22_nrt.stac-item
2022-12-22 11:51:46	ga_s2bm_ard_3-2-1_50LRJ_2022-12-22_nrt.stac-item
2022-12-22 11:51:50	ga_s2bm_ard_3-2-1_50LQJ_2022-12-22_nrt.stac-item
2022-12-22 11:51:53	ga_s2bm_ard_3-2-1_50LPJ_2022-12-22_nrt.stac-item
2022-12-22 11:51:59	ga_s2bm_ard_3-2-1_51LTC_2022-12-22_nrt.stac-item
2022-12-22 11:52:01	ga_s2bm_ard_3-2-1_50LRH_2022-12-22_nrt.stac-item
2022-12-22 11:52:04	ga_s2bm_ard_3-2-1_50LQH_2022-12-22_nrt.stac-item
2022-12-22 11:52:08	ga_s2bm_ard_3-2-1_50LPH_2022-12-22_nrt.stac-item
2022-12-22 11:52:14	ga_s2bm_ard_3-2-1_51KTB_2022-12-22_nrt.stac-item
2022-12-22 11:52:15	ga_s2bm_ard_3-2-1_50KRG_2022-12-22_nrt.stac-item
2022-12-22 11:52:22	ga_s2bm_ard_3-2-1_50KPG_2022-12-22_nrt.stac-item
2022-12-22 11:52:28	ga_s2bm_ard_3-2-1_50KNG_2022-12-22_nrt.stac-item
2022-12-22 11:52:28	ga_s2bm_ard_3-2-1_51KTA_2022-12-22_nrt.stac-item
2022-12-22 11:52:29	ga_s2bm_ard_3-2-1_50KRF_2022-12-22_nrt.stac-item
2022-12-22 11:52:40	ga_s2bm_ard_3-2-1_50KNF_2022-12-22_nrt.stac-item
2022-12-22 11:52:44	ga_s2bm_ard_3-2-1_50KRE_2022-12-22_nrt.stac-item
2022-12-22 11:52:51	ga_s2bm_ard_3-2-1_50KPE_2022-12-22_nrt.stac-item
2022-12-22 11:52:54	ga_s2bm_ard_3-2-1_50KNE_2022-12-22_nrt.stac-item
2022-12-22 11:53:09	ga_s2bm_ard_3-2-1_50KND_2022-12-22_nrt.stac-item
2022-12-22 11:56:28	ga_s2bm_ard_3-2-1_50JKL_2022-12-22_nrt.stac-item
2022-12-22 11:56:42	ga_s2bm_ard_3-2-1_50HKK_2022-12-22_nrt.stac-item
2022-12-22 11:56:44	ga_s2bm_ard_3-2-1_49HGE_2022-12-22_nrt.stac-item
2022-12-22 11:56:57	ga_s2bm_ard_3-2-1_50HKJ_2022-12-22_nrt.stac-item
2022-12-22 11:56:59	ga_s2bm_ard_3-2-1_49HGD_2022-12-22_nrt.stac-item
2022-12-22 11:57:12	ga_s2bm_ard_3-2-1_50HKH_2022-12-22_nrt.stac-item
2022-12-22 11:57:14	ga_s2bm_ard_3-2-1_49HGC_2022-12-22_nrt.stac-item
2022-12-22 11:57:21	ga_s2bm_ard_3-2-1_49HFC_2022-12-22_nrt.stac-item
2022-12-22 11:57:24	ga_s2bm_ard_3-2-1_50HKG_2022-12-22_nrt.stac-item
2022-12-22 11:57:24	ga_s2bm_ard_3-2-1_49HGB_2022-12-22_nrt.stac-item
2022-12-22 11:57:27	ga_s2bm_ard_3-2-1_49HFB_2022-12-22_nrt.stac-item
2022-12-22 11:57:27	ga_s2bm_ard_3-2-1_50HMF_2022-12-22_nrt.stac-item
2022-12-22 11:57:29	ga_s2bm_ard_3-2-1_50HLF_2022-12-22_nrt.stac-item
2022-12-23 09:39:38	ga_s2bm_ard_3-2-1_56LNP_2022-12-23_nrt.stac-item
2022-12-23 09:39:41	ga_s2bm_ard_3-2-1_56LMP_2022-12-23_nrt.stac-item
2022-12-23 09:39:48	ga_s2bm_ard_3-2-1_56LLP_2022-12-23_nrt.stac-item
2022-12-23 09:39:52	ga_s2bm_ard_3-2-1_56LNN_2022-12-23_nrt.stac-item
2022-12-23 09:39:55	ga_s2bm_ard_3-2-1_56LMN_2022-12-23_nrt.stac-item
2022-12-23 09:39:59	ga_s2bm_ard_3-2-1_56LLN_2022-12-23_nrt.stac-item
2022-12-23 09:40:03	ga_s2bm_ard_3-2-1_56LPM_2022-12-23_nrt.stac-item
2022-12-23 09:40:05	ga_s2bm_ard_3-2-1_56LNM_2022-12-23_nrt.stac-item
2022-12-23 09:40:07	ga_s2bm_ard_3-2-1_56LMM_2022-12-23_nrt.stac-item
2022-12-23 09:40:08	ga_s2bm_ard_3-2-1_56LLM_2022-12-23_nrt.stac-item
2022-12-23 09:40:11	ga_s2bm_ard_3-2-1_56LPL_2022-12-23_nrt.stac-item
2022-12-23 09:40:12	ga_s2bm_ard_3-2-1_56LNL_2022-12-23_nrt.stac-item
2022-12-23 09:41:13	ga_s2bm_ard_3-2-1_56LNH_2022-12-23_nrt.stac-item
2022-12-23 09:41:14	ga_s2bm_ard_3-2-1_56LMH_2022-12-23_nrt.stac-item
2022-12-23 09:41:16	ga_s2bm_ard_3-2-1_56LLH_2022-12-23_nrt.stac-item
2022-12-23 09:41:17	ga_s2bm_ard_3-2-1_56LKH_2022-12-23_nrt.stac-item
2022-12-23 09:41:44	ga_s2bm_ard_3-2-1_55KHA_2022-12-23_nrt.stac-item
2022-12-23 09:41:59	ga_s2bm_ard_3-2-1_55KHV_2022-12-23_nrt.stac-item
2022-12-23 09:42:14	ga_s2bm_ard_3-2-1_55KHU_2022-12-23_nrt.stac-item
2022-12-23 09:42:28	ga_s2bm_ard_3-2-1_55KHT_2022-12-23_nrt.stac-item
2022-12-23 09:43:00	ga_s2bm_ard_3-2-1_56KMV_2022-12-23_nrt.stac-item
2022-12-23 11:20:15	ga_s2bm_ard_3-2-1_52LEP_2022-12-23_nrt.stac-item
2022-12-23 11:20:22	ga_s2bm_ard_3-2-1_52LCP_2022-12-23_nrt.stac-item
2022-12-23 11:20:30	ga_s2bm_ard_3-2-1_52LEN_2022-12-23_nrt.stac-item
2022-12-23 11:20:37	ga_s2bm_ard_3-2-1_52LCN_2022-12-23_nrt.stac-item
2022-12-23 11:20:44	ga_s2bm_ard_3-2-1_52LEM_2022-12-23_nrt.stac-item
2022-12-23 11:20:51	ga_s2bm_ard_3-2-1_52LCM_2022-12-23_nrt.stac-item
2022-12-23 11:20:54	ga_s2bm_ard_3-2-1_52LBM_2022-12-23_nrt.stac-item
2022-12-23 11:20:56	ga_s2bm_ard_3-2-1_51LZG_2022-12-23_nrt.stac-item
2022-12-23 11:21:06	ga_s2bm_ard_3-2-1_52LCL_2022-12-23_nrt.stac-item
2022-12-23 11:21:09	ga_s2bm_ard_3-2-1_52LBL_2022-12-23_nrt.stac-item
2022-12-23 11:21:10	ga_s2bm_ard_3-2-1_51LZF_2022-12-23_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

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