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
2019-02-17 10:33:38	ga_s2bm_ard_3-2-1_53KPQ_2019-02-17_final.stac-item
2019-02-17 10:33:45	ga_s2bm_ard_3-2-1_54KTU_2019-02-17_final.stac-item
2019-02-17 10:33:52	ga_s2bm_ard_3-2-1_54JUT_2019-02-17_final.stac-item
2019-02-17 10:33:52	ga_s2bm_ard_3-2-1_53KPP_2019-02-17_final.stac-item
2019-02-17 10:33:59	ga_s2bm_ard_3-2-1_53JRN_2019-02-17_final.stac-item
2019-02-17 10:33:59	ga_s2bm_ard_3-2-1_54JTT_2019-02-17_final.stac-item
2019-02-17 10:34:03	ga_s2bm_ard_3-2-1_53JQN_2019-02-17_final.stac-item
2019-02-17 10:34:07	ga_s2bm_ard_3-2-1_53JPN_2019-02-17_final.stac-item
2019-02-17 12:13:39	ga_s2bm_ard_3-2-1_50KKB_2019-02-17_final.stac-item
2019-02-17 12:13:54	ga_s2bm_ard_3-2-1_50KKA_2019-02-17_final.stac-item
2019-02-17 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2019-02-17_final.stac-item
2019-02-17 12:13:58	ga_s2bm_ard_3-2-1_49KGR_2019-02-17_final.stac-item
2019-02-17 12:14:07	ga_s2bm_ard_3-2-1_50KKV_2019-02-17_final.stac-item
2019-02-17 12:14:08	ga_s2bm_ard_3-2-1_49KHQ_2019-02-17_final.stac-item
2019-02-17 12:14:12	ga_s2bm_ard_3-2-1_49KGQ_2019-02-17_final.stac-item
2019-02-17 12:14:18	ga_s2bm_ard_3-2-1_50KKU_2019-02-17_final.stac-item
2019-02-17 12:14:21	ga_s2bm_ard_3-2-1_49KHP_2019-02-17_final.stac-item
2019-02-17 12:14:27	ga_s2bm_ard_3-2-1_49KGP_2019-02-17_final.stac-item
2019-02-17 12:14:31	ga_s2bm_ard_3-2-1_49JHN_2019-02-17_final.stac-item
2019-02-17 12:14:41	ga_s2bm_ard_3-2-1_49JGN_2019-02-17_final.stac-item
2019-02-17 12:14:45	ga_s2bm_ard_3-2-1_49JFN_2019-02-17_final.stac-item
2019-02-17 12:14:56	ga_s2bm_ard_3-2-1_49JGM_2019-02-17_final.stac-item
2019-02-17 12:14:59	ga_s2bm_ard_3-2-1_49JFM_2019-02-17_final.stac-item
2019-02-17 12:15:10	ga_s2bm_ard_3-2-1_49JGL_2019-02-17_final.stac-item
2019-02-17 12:15:19	ga_s2bm_ard_3-2-1_49JGK_2019-02-17_final.stac-item
2019-02-18 10:01:11	ga_s2bm_ard_3-2-1_55LCD_2019-02-18_final.stac-item
2019-02-18 10:01:13	ga_s2bm_ard_3-2-1_55LFC_2019-02-18_final.stac-item
2019-02-18 10:01:17	ga_s2bm_ard_3-2-1_55LEC_2019-02-18_final.stac-item
2019-02-18 10:01:24	ga_s2bm_ard_3-2-1_55LCC_2019-02-18_final.stac-item
2019-02-18 10:01:28	ga_s2bm_ard_3-2-1_55KFB_2019-02-18_final.stac-item
2019-02-18 10:01:32	ga_s2bm_ard_3-2-1_55KEB_2019-02-18_final.stac-item
2019-02-18 10:01:35	ga_s2bm_ard_3-2-1_55KDB_2019-02-18_final.stac-item
2019-02-18 10:01:38	ga_s2bm_ard_3-2-1_55KCB_2019-02-18_final.stac-item
2019-02-18 10:01:42	ga_s2bm_ard_3-2-1_55KFA_2019-02-18_final.stac-item
2019-02-18 10:01:50	ga_s2bm_ard_3-2-1_55KDA_2019-02-18_final.stac-item
2019-02-18 10:01:53	ga_s2bm_ard_3-2-1_55KCA_2019-02-18_final.stac-item
2019-02-18 10:02:00	ga_s2bm_ard_3-2-1_55KEV_2019-02-18_final.stac-item
2019-02-18 10:02:04	ga_s2bm_ard_3-2-1_55KDV_2019-02-18_final.stac-item
2019-02-18 10:02:05	ga_s2bm_ard_3-2-1_55KFU_2019-02-18_final.stac-item
2019-02-18 10:02:07	ga_s2bm_ard_3-2-1_55KCV_2019-02-18_final.stac-item
2019-02-18 10:02:15	ga_s2bm_ard_3-2-1_55KBV_2019-02-18_final.stac-item
2019-02-18 10:02:15	ga_s2bm_ard_3-2-1_55KEU_2019-02-18_final.stac-item
2019-02-18 10:02:19	ga_s2bm_ard_3-2-1_55KDU_2019-02-18_final.stac-item
2019-02-18 10:02:22	ga_s2bm_ard_3-2-1_55KCU_2019-02-18_final.stac-item
2019-02-18 10:02:26	ga_s2bm_ard_3-2-1_55KBU_2019-02-18_final.stac-item
2019-02-18 10:02:30	ga_s2bm_ard_3-2-1_55KET_2019-02-18_final.stac-item
2019-02-18 10:02:33	ga_s2bm_ard_3-2-1_55KDT_2019-02-18_final.stac-item
2019-02-18 10:02:35	ga_s2bm_ard_3-2-1_55KCT_2019-02-18_final.stac-item
2019-02-18 10:02:37	ga_s2bm_ard_3-2-1_55KBT_2019-02-18_final.stac-item
2019-02-18 10:02:38	ga_s2bm_ard_3-2-1_54KZC_2019-02-18_final.stac-item
2019-02-18 10:02:39	ga_s2bm_ard_3-2-1_55KES_2019-02-18_final.stac-item
2019-02-18 10:02:41	ga_s2bm_ard_3-2-1_55KDT_2019-02-18_final.stac-item
2019-02-18 10:02:41	ga_s2bm_ard_3-2-1_55KDS_2019-02-18_final.stac-item
2019-02-18 10:02:42	ga_s2bm_ard_3-2-1_55KCS_2019-02-18_final.stac-item
2019-02-18 10:02:42	ga_s2bm_ard_3-2-1_55KCT_2019-02-18_final.stac-item
2019-02-18 10:02:43	ga_s2bm_ard_3-2-1_55KBT_2019-02-18_final.stac-item
2019-02-18 10:02:44	ga_s2bm_ard_3-2-1_54KZC_2019-02-18_final.stac-item
2019-02-18 10:02:46	ga_s2bm_ard_3-2-1_55KES_2019-02-18_final.stac-item
2019-02-18 10:02:48	ga_s2bm_ard_3-2-1_55KDS_2019-02-18_final.stac-item
2019-02-18 10:02:51	ga_s2bm_ard_3-2-1_55KCS_2019-02-18_final.stac-item
2019-02-18 10:02:54	ga_s2bm_ard_3-2-1_55KBS_2019-02-18_final.stac-item
2019-02-18 10:02:54	ga_s2bm_ard_3-2-1_54KZB_2019-02-18_final.stac-item
2019-02-18 10:02:58	ga_s2bm_ard_3-2-1_55KER_2019-02-18_final.stac-item
2019-02-18 10:03:02	ga_s2bm_ard_3-2-1_55KDR_2019-02-18_final.stac-item
2019-02-18 10:03:05	ga_s2bm_ard_3-2-1_55KCR_2019-02-18_final.stac-item
2019-02-18 10:03:09	ga_s2bm_ard_3-2-1_55KEQ_2019-02-18_final.stac-item
2019-02-18 10:03:09	ga_s2bm_ard_3-2-1_55KBR_2019-02-18_final.stac-item
2019-02-18 10:03:09	ga_s2bm_ard_3-2-1_54KZA_2019-02-18_final.stac-item
2019-02-18 10:03:16	ga_s2bm_ard_3-2-1_55KDQ_2019-02-18_final.stac-item
2019-02-18 10:03:20	ga_s2bm_ard_3-2-1_55KCQ_2019-02-18_final.stac-item
2019-02-18 10:03:23	ga_s2bm_ard_3-2-1_55KBQ_2019-02-18_final.stac-item
2019-02-18 10:03:23	ga_s2bm_ard_3-2-1_54KZV_2019-02-18_final.stac-item
2019-02-18 10:03:31	ga_s2bm_ard_3-2-1_55KDP_2019-02-18_final.stac-item
2019-02-18 10:03:35	ga_s2bm_ard_3-2-1_55KCP_2019-02-18_final.stac-item
2019-02-18 10:03:38	ga_s2bm_ard_3-2-1_55KBP_2019-02-18_final.stac-item
2019-02-18 10:03:38	ga_s2bm_ard_3-2-1_54KZU_2019-02-18_final.stac-item
2019-02-18 10:03:42	ga_s2bm_ard_3-2-1_54KYU_2019-02-18_final.stac-item
2019-02-18 10:03:46	ga_s2bm_ard_3-2-1_55JDN_2019-02-18_final.stac-item
2019-02-18 10:03:49	ga_s2bm_ard_3-2-1_55JCN_2019-02-18_final.stac-item
2019-02-18 10:03:52	ga_s2bm_ard_3-2-1_54JZT_2019-02-18_final.stac-item
2019-02-18 10:03:52	ga_s2bm_ard_3-2-1_55JBN_2019-02-18_final.stac-item
2019-02-18 10:03:56	ga_s2bm_ard_3-2-1_54JYT_2019-02-18_final.stac-item
2019-02-18 10:04:00	ga_s2bm_ard_3-2-1_55JDM_2019-02-18_final.stac-item
2019-02-18 10:04:04	ga_s2bm_ard_3-2-1_55JCM_2019-02-18_final.stac-item
2019-02-18 10:04:07	ga_s2bm_ard_3-2-1_54JZS_2019-02-18_final.stac-item
2019-02-18 10:04:07	ga_s2bm_ard_3-2-1_55JBM_2019-02-18_final.stac-item
2019-02-18 10:04:10	ga_s2bm_ard_3-2-1_54JYS_2019-02-18_final.stac-item
2019-02-18 10:04:13	ga_s2bm_ard_3-2-1_55JDL_2019-02-18_final.stac-item
2019-02-18 10:04:18	ga_s2bm_ard_3-2-1_55JCL_2019-02-18_final.stac-item
2019-02-18 10:04:22	ga_s2bm_ard_3-2-1_55JBL_2019-02-18_final.stac-item
2019-02-18 10:04:23	ga_s2bm_ard_3-2-1_55JDK_2019-02-18_final.stac-item
2019-02-18 10:04:25	ga_s2bm_ard_3-2-1_54JYR_2019-02-18_final.stac-item
2019-02-18 10:04:32	ga_s2bm_ard_3-2-1_54JXR_2019-02-18_final.stac-item
2019-02-18 10:04:33	ga_s2bm_ard_3-2-1_55JCK_2019-02-18_final.stac-item
2019-02-18 10:04:36	ga_s2bm_ard_3-2-1_55JBK_2019-02-18_final.stac-item
2019-02-18 10:07:15	ga_s2bm_ard_3-2-1_54HVE_2019-02-18_final.stac-item
2019-02-18 10:07:21	ga_s2bm_ard_3-2-1_54HXD_2019-02-18_final.stac-item
2019-02-18 10:07:26	ga_s2bm_ard_3-2-1_54HWD_2019-02-18_final.stac-item
2019-02-18 10:07:29	ga_s2bm_ard_3-2-1_54HVD_2019-02-18_final.stac-item
2019-02-18 10:07:36	ga_s2bm_ard_3-2-1_54HXC_2019-02-18_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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