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
2019-08-08 11:13:36	ga_s2bm_ard_3-2-1_51KZS_2019-08-08_final.stac-item
2019-08-08 11:13:37	ga_s2bm_ard_3-2-1_52KDA_2019-08-08_final.stac-item
2019-08-08 11:13:39	ga_s2bm_ard_3-2-1_52KCA_2019-08-08_final.stac-item
2019-08-08 11:13:40	ga_s2bm_ard_3-2-1_52KBA_2019-08-08_final.stac-item
2019-08-08 11:13:41	ga_s2bm_ard_3-2-1_51KZR_2019-08-08_final.stac-item
2019-08-08 11:13:43	ga_s2bm_ard_3-2-1_52KEA_2019-08-08_final.stac-item
2019-08-08 11:13:44	ga_s2bm_ard_3-2-1_52KDA_2019-08-08_final.stac-item
2019-08-08 11:13:46	ga_s2bm_ard_3-2-1_52KCA_2019-08-08_final.stac-item
2019-08-08 11:13:47	ga_s2bm_ard_3-2-1_52KBA_2019-08-08_final.stac-item
2019-08-08 11:13:48	ga_s2bm_ard_3-2-1_51KZR_2019-08-08_final.stac-item
2019-08-08 11:13:51	ga_s2bm_ard_3-2-1_52KEV_2019-08-08_final.stac-item
2019-08-08 11:13:55	ga_s2bm_ard_3-2-1_52KDV_2019-08-08_final.stac-item
2019-08-08 11:13:58	ga_s2bm_ard_3-2-1_52KCV_2019-08-08_final.stac-item
2019-08-08 11:14:01	ga_s2bm_ard_3-2-1_51KZQ_2019-08-08_final.stac-item
2019-08-08 11:14:01	ga_s2bm_ard_3-2-1_52KBV_2019-08-08_final.stac-item
2019-08-08 11:14:04	ga_s2bm_ard_3-2-1_52KEU_2019-08-08_final.stac-item
2019-08-08 11:14:09	ga_s2bm_ard_3-2-1_52KDU_2019-08-08_final.stac-item
2019-08-08 11:14:13	ga_s2bm_ard_3-2-1_52KCU_2019-08-08_final.stac-item
2019-08-08 11:14:15	ga_s2bm_ard_3-2-1_52JET_2019-08-08_final.stac-item
2019-08-08 11:14:16	ga_s2bm_ard_3-2-1_51KZP_2019-08-08_final.stac-item
2019-08-08 11:14:16	ga_s2bm_ard_3-2-1_52KBU_2019-08-08_final.stac-item
2019-08-08 11:14:24	ga_s2bm_ard_3-2-1_52JDT_2019-08-08_final.stac-item
2019-08-08 11:14:28	ga_s2bm_ard_3-2-1_52JCT_2019-08-08_final.stac-item
2019-08-08 11:14:30	ga_s2bm_ard_3-2-1_51JZN_2019-08-08_final.stac-item
2019-08-08 11:14:31	ga_s2bm_ard_3-2-1_52JBT_2019-08-08_final.stac-item
2019-08-08 11:14:36	ga_s2bm_ard_3-2-1_51JYN_2019-08-08_final.stac-item
2019-08-08 11:14:38	ga_s2bm_ard_3-2-1_52JDS_2019-08-08_final.stac-item
2019-08-08 11:14:42	ga_s2bm_ard_3-2-1_52JCS_2019-08-08_final.stac-item
2019-08-08 11:14:45	ga_s2bm_ard_3-2-1_51JZM_2019-08-08_final.stac-item
2019-08-08 11:14:45	ga_s2bm_ard_3-2-1_52JBS_2019-08-08_final.stac-item
2019-08-08 11:14:48	ga_s2bm_ard_3-2-1_51JYM_2019-08-08_final.stac-item
2019-08-08 11:14:53	ga_s2bm_ard_3-2-1_52JDR_2019-08-08_final.stac-item
2019-08-08 11:14:57	ga_s2bm_ard_3-2-1_52JCR_2019-08-08_final.stac-item
2019-08-08 11:15:00	ga_s2bm_ard_3-2-1_52JBR_2019-08-08_final.stac-item
2019-08-08 11:15:03	ga_s2bm_ard_3-2-1_51JYL_2019-08-08_final.stac-item
2019-08-08 11:15:07	ga_s2bm_ard_3-2-1_52JDQ_2019-08-08_final.stac-item
2019-08-08 11:15:11	ga_s2bm_ard_3-2-1_52JCQ_2019-08-08_final.stac-item
2019-08-08 11:15:14	ga_s2bm_ard_3-2-1_52JBQ_2019-08-08_final.stac-item
2019-08-08 11:15:17	ga_s2bm_ard_3-2-1_51JYK_2019-08-08_final.stac-item
2019-08-08 11:15:19	ga_s2bm_ard_3-2-1_52JDP_2019-08-08_final.stac-item
2019-08-08 11:15:25	ga_s2bm_ard_3-2-1_52JCP_2019-08-08_final.stac-item
2019-08-08 11:15:29	ga_s2bm_ard_3-2-1_52JBP_2019-08-08_final.stac-item
2019-08-08 11:15:32	ga_s2bm_ard_3-2-1_51JYJ_2019-08-08_final.stac-item
2019-08-08 11:15:37	ga_s2bm_ard_3-2-1_51JXJ_2019-08-08_final.stac-item
2019-08-08 11:15:40	ga_s2bm_ard_3-2-1_52JCN_2019-08-08_final.stac-item
2019-08-08 11:15:44	ga_s2bm_ard_3-2-1_52JBN_2019-08-08_final.stac-item
2019-08-08 11:15:46	ga_s2bm_ard_3-2-1_51JYH_2019-08-08_final.stac-item
2019-08-08 11:15:50	ga_s2bm_ard_3-2-1_51JXH_2019-08-08_final.stac-item
2019-08-08 11:15:55	ga_s2bm_ard_3-2-1_52JCM_2019-08-08_final.stac-item
2019-08-08 11:15:58	ga_s2bm_ard_3-2-1_52JBM_2019-08-08_final.stac-item
2019-08-08 11:16:01	ga_s2bm_ard_3-2-1_51JYG_2019-08-08_final.stac-item
2019-08-08 11:16:04	ga_s2bm_ard_3-2-1_51JXG_2019-08-08_final.stac-item
2019-08-08 11:16:09	ga_s2bm_ard_3-2-1_52JCL_2019-08-08_final.stac-item
2019-08-08 11:16:13	ga_s2bm_ard_3-2-1_52JBL_2019-08-08_final.stac-item
2019-08-08 11:16:15	ga_s2bm_ard_3-2-1_51JYF_2019-08-08_final.stac-item
2019-08-08 11:16:19	ga_s2bm_ard_3-2-1_51JXF_2019-08-08_final.stac-item
2019-08-08 11:16:27	ga_s2bm_ard_3-2-1_51JWF_2019-08-08_final.stac-item
2019-08-08 11:16:27	ga_s2bm_ard_3-2-1_52HBK_2019-08-08_final.stac-item
2019-08-08 11:16:30	ga_s2bm_ard_3-2-1_51HYE_2019-08-08_final.stac-item
2019-08-08 11:16:33	ga_s2bm_ard_3-2-1_51HXE_2019-08-08_final.stac-item
2019-08-08 11:16:38	ga_s2bm_ard_3-2-1_51HWE_2019-08-08_final.stac-item
2019-08-08 11:16:44	ga_s2bm_ard_3-2-1_51HYD_2019-08-08_final.stac-item
2019-08-08 11:16:48	ga_s2bm_ard_3-2-1_51HXD_2019-08-08_final.stac-item
2019-08-08 11:16:51	ga_s2bm_ard_3-2-1_51HWD_2019-08-08_final.stac-item
2019-08-09 10:41:30	ga_s2bm_ard_3-2-1_53LPD_2019-08-09_final
2019-08-09 10:41:42	ga_s2bm_ard_3-2-1_53LQC_2019-08-09_final
2019-08-09 10:41:45	ga_s2bm_ard_3-2-1_53LPC_2019-08-09_final
2019-08-09 10:41:52	ga_s2bm_ard_3-2-1_53KRB_2019-08-09_final
2019-08-09 10:41:56	ga_s2bm_ard_3-2-1_53KQB_2019-08-09_final
2019-08-09 10:44:17	ga_s2bm_ard_3-2-1_53JMN_2019-08-09_final.stac-item
2019-08-09 10:44:20	ga_s2bm_ard_3-2-1_53JLN_2019-08-09_final.stac-item
2019-08-09 10:44:31	ga_s2bm_ard_3-2-1_53JMM_2019-08-09_final.stac-item
2019-08-09 10:44:35	ga_s2bm_ard_3-2-1_53JLM_2019-08-09_final.stac-item
2019-08-09 10:44:46	ga_s2bm_ard_3-2-1_53JML_2019-08-09_final.stac-item
2019-08-09 10:44:49	ga_s2bm_ard_3-2-1_53JLL_2019-08-09_final.stac-item
2019-08-09 10:44:55	ga_s2bm_ard_3-2-1_53JKL_2019-08-09_final.stac-item
2019-08-09 10:45:00	ga_s2bm_ard_3-2-1_53JMK_2019-08-09_final.stac-item
2019-08-09 10:45:04	ga_s2bm_ard_3-2-1_53JLK_2019-08-09_final.stac-item
2019-08-09 10:45:07	ga_s2bm_ard_3-2-1_53JKK_2019-08-09_final.stac-item
2019-08-09 10:45:11	ga_s2bm_ard_3-2-1_53JNJ_2019-08-09_final.stac-item
2019-08-09 10:45:15	ga_s2bm_ard_3-2-1_53JMJ_2019-08-09_final.stac-item
2019-08-09 10:45:18	ga_s2bm_ard_3-2-1_53JLJ_2019-08-09_final.stac-item
2019-08-09 10:45:21	ga_s2bm_ard_3-2-1_53JKJ_2019-08-09_final.stac-item
2019-08-09 10:45:26	ga_s2bm_ard_3-2-1_53JNH_2019-08-09_final.stac-item
2019-08-09 10:45:30	ga_s2bm_ard_3-2-1_53JMH_2019-08-09_final.stac-item
2019-08-09 10:45:33	ga_s2bm_ard_3-2-1_53JLH_2019-08-09_final.stac-item
2019-08-09 10:45:36	ga_s2bm_ard_3-2-1_53JKH_2019-08-09_final.stac-item
2019-08-09 10:45:39	ga_s2bm_ard_3-2-1_53JNG_2019-08-09_final.stac-item
2019-08-09 10:45:44	ga_s2bm_ard_3-2-1_53JMG_2019-08-09_final.stac-item
2019-08-09 10:45:47	ga_s2bm_ard_3-2-1_53JLG_2019-08-09_final.stac-item
2019-08-09 10:45:49	ga_s2bm_ard_3-2-1_53JNF_2019-08-09_final.stac-item
2019-08-09 10:45:51	ga_s2bm_ard_3-2-1_53JKG_2019-08-09_final.stac-item
2019-08-09 10:45:54	ga_s2bm_ard_3-2-1_52JGM_2019-08-09_final.stac-item
2019-08-09 10:45:58	ga_s2bm_ard_3-2-1_53JMF_2019-08-09_final.stac-item
2019-08-09 10:46:02	ga_s2bm_ard_3-2-1_53JLF_2019-08-09_final.stac-item
2019-08-09 10:46:05	ga_s2bm_ard_3-2-1_53JKF_2019-08-09_final.stac-item
2019-08-09 10:46:07	ga_s2bm_ard_3-2-1_52JGL_2019-08-09_final.stac-item
2019-08-09 10:46:13	ga_s2bm_ard_3-2-1_53HME_2019-08-09_final.stac-item
2019-08-09 10:46:16	ga_s2bm_ard_3-2-1_53HLE_2019-08-09_final.stac-item
2019-08-09 10:46:28	ga_s2bm_ard_3-2-1_53HMD_2019-08-09_final.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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

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