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

96 results

Time (local)	Label
2022-10-20 11:40:42	ga_s2bm_ard_3-2-1_51LWH_2022-10-20_interim.stac-item
2022-10-20 11:41:00	ga_s2bm_ard_3-2-1_51LVG_2022-10-20_final.stac-item
2022-10-20 11:41:14	ga_s2bm_ard_3-2-1_51LVF_2022-10-20_final.stac-item
2022-10-20 11:41:18	ga_s2bm_ard_3-2-1_51LUF_2022-10-20_final.stac-item
2022-10-20 11:41:25	ga_s2bm_ard_3-2-1_51LWE_2022-10-20_final.stac-item
2022-10-20 11:41:29	ga_s2bm_ard_3-2-1_51LVE_2022-10-20_final.stac-item
2022-10-20 11:41:32	ga_s2bm_ard_3-2-1_51LUE_2022-10-20_final.stac-item
2022-10-20 11:41:55	ga_s2bm_ard_3-2-1_51LWC_2022-10-20_final.stac-item
2022-10-20 11:41:58	ga_s2bm_ard_3-2-1_51LVC_2022-10-20_final.stac-item
2022-10-20 11:42:04	ga_s2bm_ard_3-2-1_51LTC_2022-10-20_interim.stac-item
2022-10-20 11:42:09	ga_s2bm_ard_3-2-1_51KWB_2022-10-20_final.stac-item
2022-10-20 11:42:13	ga_s2bm_ard_3-2-1_51KVB_2022-10-20_final.stac-item
2022-10-20 11:42:21	ga_s2bm_ard_3-2-1_51KWA_2022-10-20_final.stac-item
2022-10-20 11:42:27	ga_s2bm_ard_3-2-1_51KVA_2022-10-20_final.stac-item
2022-10-20 11:42:30	ga_s2bm_ard_3-2-1_51KUA_2022-10-20_final.stac-item
2022-10-20 11:42:41	ga_s2bm_ard_3-2-1_51KVV_2022-10-20_final.stac-item
2022-10-20 11:42:45	ga_s2bm_ard_3-2-1_51KUV_2022-10-20_final.stac-item
2022-10-20 11:42:56	ga_s2bm_ard_3-2-1_51KVU_2022-10-20_final.stac-item
2022-10-20 11:42:59	ga_s2bm_ard_3-2-1_51KUU_2022-10-20_final.stac-item
2022-10-20 11:43:03	ga_s2bm_ard_3-2-1_51KTU_2022-10-20_final.stac-item
2022-10-20 11:43:03	ga_s2bm_ard_3-2-1_50KRD_2022-10-20_final.stac-item
2022-10-20 11:43:11	ga_s2bm_ard_3-2-1_51KVT_2022-10-20_final.stac-item
2022-10-20 11:43:14	ga_s2bm_ard_3-2-1_51KUT_2022-10-20_final.stac-item
2022-10-20 11:43:17	ga_s2bm_ard_3-2-1_51KTT_2022-10-20_final.stac-item
2022-10-20 11:43:18	ga_s2bm_ard_3-2-1_50KRC_2022-10-20_final.stac-item
2022-10-20 11:43:21	ga_s2bm_ard_3-2-1_50KQC_2022-10-20_final.stac-item
2022-10-20 11:43:24	ga_s2bm_ard_3-2-1_51KVS_2022-10-20_final.stac-item
2022-10-20 11:43:28	ga_s2bm_ard_3-2-1_51KUS_2022-10-20_final.stac-item
2022-10-20 11:43:32	ga_s2bm_ard_3-2-1_51KTS_2022-10-20_final.stac-item
2022-10-20 11:43:32	ga_s2bm_ard_3-2-1_50KRB_2022-10-20_final.stac-item
2022-10-20 11:43:35	ga_s2bm_ard_3-2-1_51KVR_2022-10-20_final.stac-item
2022-10-20 11:43:36	ga_s2bm_ard_3-2-1_50KQB_2022-10-20_final.stac-item
2022-10-20 11:43:43	ga_s2bm_ard_3-2-1_51KUR_2022-10-20_final.stac-item
2022-10-20 11:43:46	ga_s2bm_ard_3-2-1_51KTR_2022-10-20_final.stac-item
2022-10-20 11:43:47	ga_s2bm_ard_3-2-1_50KRA_2022-10-20_final.stac-item
2022-10-20 11:43:50	ga_s2bm_ard_3-2-1_50KQA_2022-10-20_final.stac-item
2022-10-20 11:43:57	ga_s2bm_ard_3-2-1_51KUQ_2022-10-20_final.stac-item
2022-10-20 11:44:01	ga_s2bm_ard_3-2-1_51KTQ_2022-10-20_final.stac-item
2022-10-20 11:44:01	ga_s2bm_ard_3-2-1_50KRV_2022-10-20_final.stac-item
2022-10-20 11:44:05	ga_s2bm_ard_3-2-1_50KQV_2022-10-20_final.stac-item
2022-10-20 11:44:09	ga_s2bm_ard_3-2-1_50KPV_2022-10-20_final.stac-item
2022-10-20 11:44:12	ga_s2bm_ard_3-2-1_51KUP_2022-10-20_final.stac-item
2022-10-20 11:44:15	ga_s2bm_ard_3-2-1_50KRU_2022-10-20_final.stac-item
2022-10-20 11:44:16	ga_s2bm_ard_3-2-1_51KTP_2022-10-20_final.stac-item
2022-10-20 11:44:19	ga_s2bm_ard_3-2-1_50KQU_2022-10-20_final.stac-item
2022-10-20 11:44:22	ga_s2bm_ard_3-2-1_50KPU_2022-10-20_final.stac-item
2022-10-20 11:44:27	ga_s2bm_ard_3-2-1_51JUN_2022-10-20_final.stac-item
2022-10-20 11:44:30	ga_s2bm_ard_3-2-1_50JRT_2022-10-20_final.stac-item
2022-10-20 11:44:30	ga_s2bm_ard_3-2-1_51JTN_2022-10-20_final.stac-item
2022-10-20 11:44:34	ga_s2bm_ard_3-2-1_50JQT_2022-10-20_final.stac-item
2022-10-20 11:44:37	ga_s2bm_ard_3-2-1_50JPT_2022-10-20_final.stac-item
2022-10-20 11:44:40	ga_s2bm_ard_3-2-1_51JUM_2022-10-20_final.stac-item
2022-10-20 11:44:44	ga_s2bm_ard_3-2-1_50JRS_2022-10-20_final.stac-item
2022-10-20 11:44:45	ga_s2bm_ard_3-2-1_51JTM_2022-10-20_final.stac-item
2022-10-20 11:44:48	ga_s2bm_ard_3-2-1_50JQS_2022-10-20_final.stac-item
2022-10-20 11:44:50	ga_s2bm_ard_3-2-1_51JUL_2022-10-20_final.stac-item
2022-10-20 11:44:52	ga_s2bm_ard_3-2-1_50JPS_2022-10-20_final.stac-item
2022-10-20 11:44:59	ga_s2bm_ard_3-2-1_51JTL_2022-10-20_final.stac-item
2022-10-20 11:45:03	ga_s2bm_ard_3-2-1_50JQR_2022-10-20_final.stac-item
2022-10-20 11:45:06	ga_s2bm_ard_3-2-1_50JPR_2022-10-20_final.stac-item
2022-10-20 11:45:11	ga_s2bm_ard_3-2-1_50JNR_2022-10-20_final.stac-item
2022-10-20 11:45:14	ga_s2bm_ard_3-2-1_51JTK_2022-10-20_final.stac-item
2022-10-20 11:45:17	ga_s2bm_ard_3-2-1_50JQQ_2022-10-20_final.stac-item
2022-10-20 11:45:21	ga_s2bm_ard_3-2-1_50JPQ_2022-10-20_final.stac-item
2022-10-20 11:45:24	ga_s2bm_ard_3-2-1_50JNQ_2022-10-20_final.stac-item
2022-10-20 11:45:28	ga_s2bm_ard_3-2-1_51JTJ_2022-10-20_final.stac-item
2022-10-20 11:45:31	ga_s2bm_ard_3-2-1_50JQP_2022-10-20_final.stac-item
2022-10-20 11:45:35	ga_s2bm_ard_3-2-1_50JPP_2022-10-20_final.stac-item
2022-10-20 11:45:39	ga_s2bm_ard_3-2-1_50JNP_2022-10-20_final.stac-item
2022-10-20 11:45:43	ga_s2bm_ard_3-2-1_51JTH_2022-10-20_final.stac-item
2022-10-20 11:45:46	ga_s2bm_ard_3-2-1_50JQN_2022-10-20_final.stac-item
2022-10-20 11:45:50	ga_s2bm_ard_3-2-1_50JPN_2022-10-20_final.stac-item
2022-10-20 11:45:53	ga_s2bm_ard_3-2-1_50JNN_2022-10-20_final.stac-item
2022-10-20 11:45:56	ga_s2bm_ard_3-2-1_51JTG_2022-10-20_final.stac-item
2022-10-20 11:46:00	ga_s2bm_ard_3-2-1_50JQM_2022-10-20_final.stac-item
2022-10-20 11:46:04	ga_s2bm_ard_3-2-1_50JPM_2022-10-20_final.stac-item
2022-10-20 11:46:07	ga_s2bm_ard_3-2-1_51JTF_2022-10-20_final.stac-item
2022-10-20 11:46:08	ga_s2bm_ard_3-2-1_50JNM_2022-10-20_final.stac-item
2022-10-20 11:46:12	ga_s2bm_ard_3-2-1_50JMM_2022-10-20_final.stac-item
2022-10-20 11:46:15	ga_s2bm_ard_3-2-1_50JQL_2022-10-20_final.stac-item
2022-10-20 11:46:18	ga_s2bm_ard_3-2-1_50JPL_2022-10-20_final.stac-item
2022-10-20 11:46:22	ga_s2bm_ard_3-2-1_50JNL_2022-10-20_final.stac-item
2022-10-20 11:46:25	ga_s2bm_ard_3-2-1_50JML_2022-10-20_final.stac-item
2022-10-20 11:46:29	ga_s2bm_ard_3-2-1_50HQK_2022-10-20_final.stac-item
2022-10-20 11:46:33	ga_s2bm_ard_3-2-1_50HPK_2022-10-20_final.stac-item
2022-10-20 11:46:37	ga_s2bm_ard_3-2-1_50HNK_2022-10-20_final.stac-item
2022-10-20 11:46:40	ga_s2bm_ard_3-2-1_50HMK_2022-10-20_final.stac-item
2022-10-20 11:46:42	ga_s2bm_ard_3-2-1_50HQJ_2022-10-20_final.stac-item
2022-10-20 11:46:47	ga_s2bm_ard_3-2-1_50HPJ_2022-10-20_final.stac-item
2022-10-20 11:46:51	ga_s2bm_ard_3-2-1_50HNJ_2022-10-20_final.stac-item
2022-10-20 11:46:53	ga_s2bm_ard_3-2-1_50HQH_2022-10-20_final.stac-item
2022-10-20 11:46:55	ga_s2bm_ard_3-2-1_50HMJ_2022-10-20_final.stac-item
2022-10-20 11:47:02	ga_s2bm_ard_3-2-1_50HPH_2022-10-20_final.stac-item
2022-10-20 11:47:06	ga_s2bm_ard_3-2-1_50HNH_2022-10-20_final.stac-item
2022-10-20 11:47:09	ga_s2bm_ard_3-2-1_50HMH_2022-10-20_final.stac-item
2022-10-20 11:47:14	ga_s2bm_ard_3-2-1_50HLH_2022-10-20_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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