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
2022-04-09 12:04:28	ga_s2bm_ard_3-2-1_49KGP_2022-04-09_final.stac-item
2022-04-09 12:04:32	ga_s2bm_ard_3-2-1_50JMT_2022-04-09_final.stac-item
2022-04-09 12:04:35	ga_s2bm_ard_3-2-1_50JLT_2022-04-09_final.stac-item
2022-04-09 12:04:36	ga_s2bm_ard_3-2-1_49JHN_2022-04-09_final.stac-item
2022-04-09 12:04:36	ga_s2bm_ard_3-2-1_50JKT_2022-04-09_final.stac-item
2022-04-09 12:04:38	ga_s2bm_ard_3-2-1_49JGN_2022-04-09_final.stac-item
2022-04-09 12:04:39	ga_s2bm_ard_3-2-1_50JMT_2022-04-09_final.stac-item
2022-04-09 12:04:40	ga_s2bm_ard_3-2-1_50JMS_2022-04-09_final.stac-item
2022-04-09 12:04:40	ga_s2bm_ard_3-2-1_50JLS_2022-04-09_final.stac-item
2022-04-09 12:04:41	ga_s2bm_ard_3-2-1_50JLT_2022-04-09_final.stac-item
2022-04-09 12:04:43	ga_s2bm_ard_3-2-1_50JKT_2022-04-09_final.stac-item
2022-04-09 12:04:43	ga_s2bm_ard_3-2-1_49JHN_2022-04-09_final.stac-item
2022-04-09 12:04:45	ga_s2bm_ard_3-2-1_49JGN_2022-04-09_final.stac-item
2022-04-09 12:04:45	ga_s2bm_ard_3-2-1_50JMS_2022-04-09_final.stac-item
2022-04-09 12:04:50	ga_s2bm_ard_3-2-1_50JLS_2022-04-09_final.stac-item
2022-04-09 12:04:53	ga_s2bm_ard_3-2-1_49JHM_2022-04-09_final.stac-item
2022-04-09 12:04:54	ga_s2bm_ard_3-2-1_50JKS_2022-04-09_final.stac-item
2022-04-09 12:04:55	ga_s2bm_ard_3-2-1_50JMR_2022-04-09_final.stac-item
2022-04-09 12:04:57	ga_s2bm_ard_3-2-1_49JGM_2022-04-09_final.stac-item
2022-04-09 12:05:05	ga_s2bm_ard_3-2-1_50JLR_2022-04-09_final.stac-item
2022-04-09 12:05:09	ga_s2bm_ard_3-2-1_50JKR_2022-04-09_final.stac-item
2022-04-09 12:05:12	ga_s2bm_ard_3-2-1_49JGL_2022-04-09_final.stac-item
2022-04-09 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2022-04-09_final.stac-item
2022-04-09 12:05:23	ga_s2bm_ard_3-2-1_50JKQ_2022-04-09_final.stac-item
2022-04-09 12:05:26	ga_s2bm_ard_3-2-1_49JGK_2022-04-09_final.stac-item
2022-04-09 12:05:34	ga_s2bm_ard_3-2-1_50JLP_2022-04-09_final.stac-item
2022-04-09 12:05:38	ga_s2bm_ard_3-2-1_50JKP_2022-04-09_final.stac-item
2022-04-09 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2022-04-09_final.stac-item
2022-04-09 12:05:48	ga_s2bm_ard_3-2-1_50JLN_2022-04-09_final.stac-item
2022-04-09 12:05:52	ga_s2bm_ard_3-2-1_50JKN_2022-04-09_final.stac-item
2022-04-09 12:06:01	ga_s2bm_ard_3-2-1_50JLM_2022-04-09_final.stac-item
2022-04-09 12:06:07	ga_s2bm_ard_3-2-1_50JKM_2022-04-09_final.stac-item
2022-04-09 12:06:11	ga_s2bm_ard_3-2-1_50JLL_2022-04-09_final.stac-item
2022-04-10 09:51:37	ga_s2bm_ard_3-2-1_56KKF_2022-04-10_final.stac-item
2022-04-10 09:55:08	ga_s2bm_ard_3-2-1_55JBH_2022-04-10_final.stac-item
2022-04-10 09:55:21	ga_s2bm_ard_3-2-1_55JBG_2022-04-10_final.stac-item
2022-04-10 09:55:36	ga_s2bm_ard_3-2-1_55JBF_2022-04-10_final.stac-item
2022-04-10 09:55:39	ga_s2bm_ard_3-2-1_55HEE_2022-04-10_final.stac-item
2022-04-10 09:55:44	ga_s2bm_ard_3-2-1_55HDE_2022-04-10_final.stac-item
2022-04-10 09:55:47	ga_s2bm_ard_3-2-1_55HCE_2022-04-10_final.stac-item
2022-04-10 09:55:50	ga_s2bm_ard_3-2-1_55HBE_2022-04-10_final.stac-item
2022-04-10 09:55:51	ga_s2bm_ard_3-2-1_55HED_2022-04-10_final.stac-item
2022-04-10 09:55:54	ga_s2bm_ard_3-2-1_54HYK_2022-04-10_final.stac-item
2022-04-10 11:31:15	ga_s2bm_ard_3-2-1_52LBK_2022-04-10_final.stac-item
2022-04-10 11:31:17	ga_s2bm_ard_3-2-1_51LZE_2022-04-10_final.stac-item
2022-04-10 11:31:21	ga_s2bm_ard_3-2-1_51LYE_2022-04-10_final.stac-item
2022-04-10 11:31:26	ga_s2bm_ard_3-2-1_52LBJ_2022-04-10_final.stac-item
2022-04-10 11:31:27	ga_s2bm_ard_3-2-1_51LWE_2022-04-10_final.stac-item
2022-04-10 11:31:32	ga_s2bm_ard_3-2-1_51LZD_2022-04-10_final.stac-item
2022-04-10 11:31:36	ga_s2bm_ard_3-2-1_51LYD_2022-04-10_final.stac-item
2022-04-10 11:31:39	ga_s2bm_ard_3-2-1_51LXD_2022-04-10_final.stac-item
2022-04-10 11:31:45	ga_s2bm_ard_3-2-1_51LZC_2022-04-10_final.stac-item
2022-04-10 11:31:50	ga_s2bm_ard_3-2-1_51LYC_2022-04-10_final.stac-item
2022-04-10 11:31:53	ga_s2bm_ard_3-2-1_51LXC_2022-04-10_final.stac-item
2022-04-10 11:31:56	ga_s2bm_ard_3-2-1_51KZB_2022-04-10_final.stac-item
2022-04-10 11:31:57	ga_s2bm_ard_3-2-1_51LWC_2022-04-10_final.stac-item
2022-04-10 11:32:01	ga_s2bm_ard_3-2-1_51KYB_2022-04-10_final.stac-item
2022-04-10 11:32:03	ga_s2bm_ard_3-2-1_51KXB_2022-04-10_final.stac-item
2022-04-10 11:32:05	ga_s2bm_ard_3-2-1_51KWB_2022-04-10_final.stac-item
2022-04-10 11:32:05	ga_s2bm_ard_3-2-1_51LWC_2022-04-10_final.stac-item
2022-04-10 11:32:08	ga_s2bm_ard_3-2-1_51KYB_2022-04-10_final.stac-item
2022-04-10 11:32:10	ga_s2bm_ard_3-2-1_51KXB_2022-04-10_final.stac-item
2022-04-10 11:32:12	ga_s2bm_ard_3-2-1_51KWB_2022-04-10_final.stac-item
2022-04-10 11:32:16	ga_s2bm_ard_3-2-1_51KVB_2022-04-10_final.stac-item
2022-04-10 11:32:19	ga_s2bm_ard_3-2-1_51KYA_2022-04-10_final.stac-item
2022-04-10 11:32:22	ga_s2bm_ard_3-2-1_51KXA_2022-04-10_final.stac-item
2022-04-10 11:32:26	ga_s2bm_ard_3-2-1_51KWA_2022-04-10_final.stac-item
2022-04-10 11:32:29	ga_s2bm_ard_3-2-1_51KVA_2022-04-10_final.stac-item
2022-04-10 11:32:33	ga_s2bm_ard_3-2-1_51KYV_2022-04-10_final.stac-item
2022-04-10 11:32:37	ga_s2bm_ard_3-2-1_51KXV_2022-04-10_final.stac-item
2022-04-10 11:32:40	ga_s2bm_ard_3-2-1_51KWV_2022-04-10_final.stac-item
2022-04-10 11:32:43	ga_s2bm_ard_3-2-1_51KVV_2022-04-10_final.stac-item
2022-04-10 11:32:47	ga_s2bm_ard_3-2-1_51KYU_2022-04-10_final.stac-item
2022-04-10 11:32:51	ga_s2bm_ard_3-2-1_51KXU_2022-04-10_final.stac-item
2022-04-10 11:32:55	ga_s2bm_ard_3-2-1_51KWU_2022-04-10_final.stac-item
2022-04-10 11:32:58	ga_s2bm_ard_3-2-1_51KVU_2022-04-10_final.stac-item
2022-04-10 11:32:59	ga_s2bm_ard_3-2-1_51KYT_2022-04-10_final.stac-item
2022-04-10 11:33:06	ga_s2bm_ard_3-2-1_51KXT_2022-04-10_final.stac-item
2022-04-10 11:33:09	ga_s2bm_ard_3-2-1_51KWT_2022-04-10_final.stac-item
2022-04-10 11:33:13	ga_s2bm_ard_3-2-1_51KVT_2022-04-10_final.stac-item
2022-04-10 11:33:19	ga_s2bm_ard_3-2-1_51KUT_2022-04-10_final.stac-item
2022-04-10 11:33:20	ga_s2bm_ard_3-2-1_51KXS_2022-04-10_final.stac-item
2022-04-10 11:33:24	ga_s2bm_ard_3-2-1_51KWS_2022-04-10_final.stac-item
2022-04-10 11:33:27	ga_s2bm_ard_3-2-1_51KVS_2022-04-10_final.stac-item
2022-04-10 11:33:31	ga_s2bm_ard_3-2-1_51KUS_2022-04-10_final.stac-item
2022-04-10 11:33:35	ga_s2bm_ard_3-2-1_51KXR_2022-04-10_final.stac-item
2022-04-10 11:33:38	ga_s2bm_ard_3-2-1_51KWR_2022-04-10_final.stac-item
2022-04-10 11:33:42	ga_s2bm_ard_3-2-1_51KVR_2022-04-10_final.stac-item
2022-04-10 11:33:45	ga_s2bm_ard_3-2-1_51KUR_2022-04-10_final.stac-item
2022-04-10 11:33:49	ga_s2bm_ard_3-2-1_51KXQ_2022-04-10_final.stac-item
2022-04-10 11:33:53	ga_s2bm_ard_3-2-1_51KWQ_2022-04-10_final.stac-item
2022-04-10 11:33:56	ga_s2bm_ard_3-2-1_51KVQ_2022-04-10_final.stac-item
2022-04-10 11:34:00	ga_s2bm_ard_3-2-1_51KUQ_2022-04-10_final.stac-item
2022-04-10 11:34:02	ga_s2bm_ard_3-2-1_51KXP_2022-04-10_final.stac-item
2022-04-10 11:34:07	ga_s2bm_ard_3-2-1_51KWP_2022-04-10_final.stac-item
2022-04-10 11:34:11	ga_s2bm_ard_3-2-1_51KVP_2022-04-10_final.stac-item
2022-04-10 11:34:12	ga_s2bm_ard_3-2-1_51JXN_2022-04-10_final.stac-item
2022-04-10 11:36:59	ga_s2bm_ard_3-2-1_50HQH_2022-04-10_final.stac-item
2022-04-10 11:37:03	ga_s2bm_ard_3-2-1_50HPH_2022-04-10_final.stac-item
2022-04-10 11:37:09	ga_s2bm_ard_3-2-1_51HUB_2022-04-10_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

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