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
2023-02-03 10:25:31	ga_s2bm_ard_3-2-1_53JQG_2023-02-03_final.stac-item
2023-02-03 10:25:37	ga_s2bm_ard_3-2-1_53JPG_2023-02-03_final.stac-item
2023-02-03 10:25:46	ga_s2bm_ard_3-2-1_53JQF_2023-02-03_final.stac-item
2023-02-03 10:26:58	ga_s2bm_ard_3-2-1_53HQA_2023-02-03_final.stac-item
2023-02-03 10:27:02	ga_s2bm_ard_3-2-1_53HPA_2023-02-03_final.stac-item
2023-02-03 12:03:41	ga_s2bm_ard_3-2-1_50KKB_2023-02-03_final.stac-item
2023-02-03 12:04:03	ga_s2bm_ard_3-2-1_50KMV_2023-02-03_final.stac-item
2023-02-03 12:04:07	ga_s2bm_ard_3-2-1_50KLV_2023-02-03_final.stac-item
2023-02-03 12:04:10	ga_s2bm_ard_3-2-1_49KHQ_2023-02-03_final.stac-item
2023-02-03 12:04:18	ga_s2bm_ard_3-2-1_50KMU_2023-02-03_final.stac-item
2023-02-03 12:04:21	ga_s2bm_ard_3-2-1_50KLU_2023-02-03_final.stac-item
2023-02-03 12:04:25	ga_s2bm_ard_3-2-1_49KHP_2023-02-03_final.stac-item
2023-02-03 12:04:39	ga_s2bm_ard_3-2-1_49JHN_2023-02-03_final.stac-item
2023-02-03 12:04:39	ga_s2bm_ard_3-2-1_50JKT_2023-02-03_final.stac-item
2023-02-03 12:04:43	ga_s2bm_ard_3-2-1_49JGN_2023-02-03_final.stac-item
2023-02-03 12:04:45	ga_s2bm_ard_3-2-1_50JMS_2023-02-03_final.stac-item
2023-02-03 12:04:49	ga_s2bm_ard_3-2-1_50JLS_2023-02-03_final.stac-item
2023-02-03 12:04:50	ga_s2bm_ard_3-2-1_49JHM_2023-02-03_final.stac-item
2023-02-03 12:04:50	ga_s2bm_ard_3-2-1_50JKS_2023-02-03_final.stac-item
2023-02-03 12:04:52	ga_s2bm_ard_3-2-1_49JGM_2023-02-03_final.stac-item
2023-02-03 12:04:53	ga_s2bm_ard_3-2-1_50JMS_2023-02-03_final.stac-item
2023-02-03 12:04:54	ga_s2bm_ard_3-2-1_50JMR_2023-02-03_final.stac-item
2023-02-03 12:04:54	ga_s2bm_ard_3-2-1_50JLR_2023-02-03_final.stac-item
2023-02-03 12:04:56	ga_s2bm_ard_3-2-1_50JLS_2023-02-03_final.stac-item
2023-02-03 12:04:56	ga_s2bm_ard_3-2-1_50JMR_2023-02-03_final.stac-item
2023-02-03 12:04:57	ga_s2bm_ard_3-2-1_49JHM_2023-02-03_final.stac-item
2023-02-03 12:04:57	ga_s2bm_ard_3-2-1_50JKS_2023-02-03_final.stac-item
2023-02-03 12:04:59	ga_s2bm_ard_3-2-1_49JGM_2023-02-03_final.stac-item
2023-02-03 12:05:05	ga_s2bm_ard_3-2-1_50JLR_2023-02-03_final.stac-item
2023-02-03 12:05:08	ga_s2bm_ard_3-2-1_50JKR_2023-02-03_final.stac-item
2023-02-03 12:05:20	ga_s2bm_ard_3-2-1_50JLQ_2023-02-03_final.stac-item
2023-02-03 12:05:34	ga_s2bm_ard_3-2-1_50JLP_2023-02-03_final.stac-item
2023-02-03 12:05:41	ga_s2bm_ard_3-2-1_49JGJ_2023-02-03_final.stac-item
2023-02-03 12:05:52	ga_s2bm_ard_3-2-1_50JKN_2023-02-03_final.stac-item
2023-02-03 12:06:11	ga_s2bm_ard_3-2-1_50JLL_2023-02-03_final.stac-item
2023-02-04 11:31:15	ga_s2bm_ard_3-2-1_52LBK_2023-02-04_final.stac-item
2023-02-04 11:31:39	ga_s2bm_ard_3-2-1_51LXD_2023-02-04_final.stac-item
2023-02-04 11:31:54	ga_s2bm_ard_3-2-1_51LXC_2023-02-04_final.stac-item
2023-02-04 11:31:57	ga_s2bm_ard_3-2-1_51KZB_2023-02-04_final.stac-item
2023-02-04 11:32:17	ga_s2bm_ard_3-2-1_51KVB_2023-02-04_final.stac-item
2023-02-04 11:32:44	ga_s2bm_ard_3-2-1_51KVV_2023-02-04_final.stac-item
2023-02-04 11:32:52	ga_s2bm_ard_3-2-1_51KXU_2023-02-04_final.stac-item
2023-02-04 11:32:55	ga_s2bm_ard_3-2-1_51KWU_2023-02-04_final.stac-item
2023-02-04 11:32:59	ga_s2bm_ard_3-2-1_51KVU_2023-02-04_final.stac-item
2023-02-04 11:33:06	ga_s2bm_ard_3-2-1_51KXT_2023-02-04_final.stac-item
2023-02-04 11:33:10	ga_s2bm_ard_3-2-1_51KWT_2023-02-04_final.stac-item
2023-02-04 11:33:24	ga_s2bm_ard_3-2-1_51KWS_2023-02-04_final.stac-item
2023-02-04 11:33:39	ga_s2bm_ard_3-2-1_51KWR_2023-02-04_final.stac-item
2023-02-04 11:33:45	ga_s2bm_ard_3-2-1_51KUR_2023-02-04_final.stac-item
2023-02-04 11:34:00	ga_s2bm_ard_3-2-1_51KUQ_2023-02-04_final.stac-item
2023-02-04 11:34:11	ga_s2bm_ard_3-2-1_51KVP_2023-02-04_final.stac-item
2023-02-04 11:34:22	ga_s2bm_ard_3-2-1_51JWN_2023-02-04_final.stac-item
2023-02-04 11:34:46	ga_s2bm_ard_3-2-1_51JTM_2023-02-04_final.stac-item
2023-02-04 11:34:58	ga_s2bm_ard_3-2-1_51JUL_2023-02-04_final.stac-item
2023-02-04 11:35:01	ga_s2bm_ard_3-2-1_51JTL_2023-02-04_final.stac-item
2023-02-04 11:35:13	ga_s2bm_ard_3-2-1_51JUK_2023-02-04_final.stac-item
2023-02-04 11:35:24	ga_s2bm_ard_3-2-1_51JVJ_2023-02-04_final.stac-item
2023-02-04 11:35:27	ga_s2bm_ard_3-2-1_51JUJ_2023-02-04_final.stac-item
2023-02-04 11:35:38	ga_s2bm_ard_3-2-1_51JVH_2023-02-04_final.stac-item
2023-02-04 11:36:14	ga_s2bm_ard_3-2-1_51JTF_2023-02-04_final.stac-item
2023-02-04 11:36:17	ga_s2bm_ard_3-2-1_50JQL_2023-02-04_final.stac-item
2023-02-04 11:36:24	ga_s2bm_ard_3-2-1_50JPL_2023-02-04_final.stac-item
2023-02-04 11:36:29	ga_s2bm_ard_3-2-1_51HTE_2023-02-04_final.stac-item
2023-02-04 11:36:31	ga_s2bm_ard_3-2-1_51HVD_2023-02-04_final.stac-item
2023-02-04 11:36:35	ga_s2bm_ard_3-2-1_50HPK_2023-02-04_final.stac-item
2023-02-04 11:36:43	ga_s2bm_ard_3-2-1_51HTD_2023-02-04_final.stac-item
2023-02-04 11:36:45	ga_s2bm_ard_3-2-1_50HQJ_2023-02-04_final.stac-item
2023-02-04 11:36:49	ga_s2bm_ard_3-2-1_50HPJ_2023-02-04_final.stac-item
2023-02-04 11:37:04	ga_s2bm_ard_3-2-1_50HPH_2023-02-04_final.stac-item
2023-02-09 10:42:55	ga_s2bm_ard_3-2-1_53KMT_2023-02-09_final.stac-item
2023-02-09 10:43:57	ga_s2bm_ard_3-2-1_53KLP_2023-02-09_final.stac-item
2023-02-09 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2023-02-09_final.stac-item
2023-02-09 10:44:46	ga_s2bm_ard_3-2-1_53JKL_2023-02-09_final.stac-item
2023-02-09 10:44:48	ga_s2bm_ard_3-2-1_53JNK_2023-02-09_final.stac-item
2023-02-09 10:44:55	ga_s2bm_ard_3-2-1_53JLK_2023-02-09_final.stac-item
2023-02-09 10:45:03	ga_s2bm_ard_3-2-1_53JNJ_2023-02-09_final.stac-item
2023-02-09 10:45:06	ga_s2bm_ard_3-2-1_53JMJ_2023-02-09_final.stac-item
2023-02-09 10:45:21	ga_s2bm_ard_3-2-1_53JMH_2023-02-09_final.stac-item
2023-02-09 10:45:42	ga_s2bm_ard_3-2-1_53JKG_2023-02-09_final.stac-item
2023-02-09 10:46:08	ga_s2bm_ard_3-2-1_53HLE_2023-02-09_final.stac-item
2023-02-09 10:46:22	ga_s2bm_ard_3-2-1_53HLD_2023-02-09_final.stac-item
2023-02-20 11:50:29	ga_s2bm_ard_3-2-1_51LUJ_2023-02-20_nrt.stac-item
2023-02-20 11:50:43	ga_s2bm_ard_3-2-1_51LUH_2023-02-20_nrt.stac-item
2023-02-20 11:50:58	ga_s2bm_ard_3-2-1_51LUG_2023-02-20_nrt.stac-item
2023-02-20 11:51:38	ga_s2bm_ard_3-2-1_50LPK_2023-02-20_nrt.stac-item
2023-02-20 11:51:45	ga_s2bm_ard_3-2-1_51LTD_2023-02-20_nrt.stac-item
2023-02-20 11:51:53	ga_s2bm_ard_3-2-1_50LPJ_2023-02-20_nrt.stac-item
2023-02-20 11:51:59	ga_s2bm_ard_3-2-1_51LTC_2023-02-20_nrt.stac-item
2023-02-20 11:52:08	ga_s2bm_ard_3-2-1_50LPH_2023-02-20_nrt.stac-item
2023-02-20 11:52:14	ga_s2bm_ard_3-2-1_51KTB_2023-02-20_nrt.stac-item
2023-02-20 11:52:29	ga_s2bm_ard_3-2-1_51KTA_2023-02-20_nrt.stac-item
2023-02-20 11:56:32	ga_s2bm_ard_3-2-1_49JGF_2023-02-20_nrt.stac-item
2023-02-20 11:56:42	ga_s2bm_ard_3-2-1_50HKK_2023-02-20_nrt.stac-item
2023-02-20 11:56:57	ga_s2bm_ard_3-2-1_50HKJ_2023-02-20_nrt.stac-item
2023-02-20 11:56:59	ga_s2bm_ard_3-2-1_49HGD_2023-02-20_nrt.stac-item
2023-02-20 11:57:11	ga_s2bm_ard_3-2-1_50HKH_2023-02-20_nrt.stac-item
2023-02-20 11:57:22	ga_s2bm_ard_3-2-1_49HFC_2023-02-20_nrt.stac-item
2023-02-20 11:57:24	ga_s2bm_ard_3-2-1_50HKG_2023-02-20_nrt.stac-item
2023-02-20 11:57:24	ga_s2bm_ard_3-2-1_49HGB_2023-02-20_nrt.stac-item
2023-02-20 11:57:27	ga_s2bm_ard_3-2-1_49HFB_2023-02-20_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years