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
2023-01-16 11:01:25	ga_s2bm_ard_3-2-1_52LHJ_2023-01-16_final.stac-item
2023-01-16 11:02:29	ga_s2bm_ard_3-2-1_52KFE_2023-01-16_final.stac-item
2023-01-16 11:02:35	ga_s2bm_ard_3-2-1_52KFD_2023-01-16_final.stac-item
2023-01-16 11:02:49	ga_s2bm_ard_3-2-1_52KED_2023-01-16_final.stac-item
2023-01-16 11:03:02	ga_s2bm_ard_3-2-1_52KEC_2023-01-16_final.stac-item
2023-01-16 11:03:16	ga_s2bm_ard_3-2-1_52KEB_2023-01-16_final.stac-item
2023-01-16 11:03:38	ga_s2bm_ard_3-2-1_52KGV_2023-01-16_final.stac-item
2023-01-16 11:04:07	ga_s2bm_ard_3-2-1_52JGT_2023-01-16_final.stac-item
2023-01-16 11:04:11	ga_s2bm_ard_3-2-1_52JFT_2023-01-16_final.stac-item
2023-01-16 11:04:15	ga_s2bm_ard_3-2-1_52JET_2023-01-16_final.stac-item
2023-01-16 11:04:25	ga_s2bm_ard_3-2-1_52JFS_2023-01-16_final.stac-item
2023-01-16 11:04:29	ga_s2bm_ard_3-2-1_52JES_2023-01-16_final.stac-item
2023-01-16 11:05:31	ga_s2bm_ard_3-2-1_52JDN_2023-01-16_final.stac-item
2023-01-16 11:05:49	ga_s2bm_ard_3-2-1_52JDM_2023-01-16_final.stac-item
2023-01-17 10:35:35	ga_s2bm_ard_3-2-1_53JNG_2023-01-17_final.stac-item
2023-01-17 10:36:07	ga_s2bm_ard_3-2-1_53HME_2023-01-17_final.stac-item
2023-01-17 10:36:18	ga_s2bm_ard_3-2-1_53HND_2023-01-17_final.stac-item
2023-01-17 10:36:56	ga_s2bm_ard_3-2-1_53HPA_2023-01-17_final.stac-item
2023-01-17 12:13:36	ga_s2bm_ard_3-2-1_50KKB_2023-01-17_final.stac-item
2023-01-17 12:13:51	ga_s2bm_ard_3-2-1_49KHR_2023-01-17_final.stac-item
2023-01-17 12:14:28	ga_s2bm_ard_3-2-1_49JHN_2023-01-17_final.stac-item
2023-01-17 12:14:42	ga_s2bm_ard_3-2-1_49JFN_2023-01-17_final.stac-item
2023-01-17 12:14:57	ga_s2bm_ard_3-2-1_49JFM_2023-01-17_final.stac-item
2023-01-17 12:15:07	ga_s2bm_ard_3-2-1_49JGL_2023-01-17_final.stac-item
2023-01-17 12:15:17	ga_s2bm_ard_3-2-1_49JGK_2023-01-17_final.stac-item
2023-01-18 11:41:15	ga_s2bm_ard_3-2-1_51LUF_2023-01-18_final.stac-item
2023-01-18 11:41:56	ga_s2bm_ard_3-2-1_51LVC_2023-01-18_final.stac-item
2023-01-18 11:42:25	ga_s2bm_ard_3-2-1_51KVA_2023-01-18_final.stac-item
2023-01-18 11:42:57	ga_s2bm_ard_3-2-1_51KUU_2023-01-18_final.stac-item
2023-01-18 11:43:15	ga_s2bm_ard_3-2-1_51KTT_2023-01-18_final.stac-item
2023-01-18 11:43:16	ga_s2bm_ard_3-2-1_50KRC_2023-01-18_final.stac-item
2023-01-18 11:43:19	ga_s2bm_ard_3-2-1_50KQC_2023-01-18_final.stac-item
2023-01-18 11:43:33	ga_s2bm_ard_3-2-1_50KQB_2023-01-18_final.stac-item
2023-01-18 11:43:44	ga_s2bm_ard_3-2-1_50KRA_2023-01-18_final.stac-item
2023-01-18 11:43:48	ga_s2bm_ard_3-2-1_50KQA_2023-01-18_final.stac-item
2023-01-18 11:43:59	ga_s2bm_ard_3-2-1_50KRV_2023-01-18_final.stac-item
2023-01-18 11:44:03	ga_s2bm_ard_3-2-1_50KQV_2023-01-18_final.stac-item
2023-01-18 11:44:42	ga_s2bm_ard_3-2-1_51JTM_2023-01-18_final.stac-item
2023-01-18 11:44:46	ga_s2bm_ard_3-2-1_50JQS_2023-01-18_final.stac-item
2023-01-18 11:44:50	ga_s2bm_ard_3-2-1_50JPS_2023-01-18_final.stac-item
2023-01-18 11:44:57	ga_s2bm_ard_3-2-1_51JTL_2023-01-18_final.stac-item
2023-01-18 11:45:04	ga_s2bm_ard_3-2-1_50JPR_2023-01-18_final.stac-item
2023-01-18 11:45:09	ga_s2bm_ard_3-2-1_50JNR_2023-01-18_final.stac-item
2023-01-18 11:45:15	ga_s2bm_ard_3-2-1_50JQQ_2023-01-18_final.stac-item
2023-01-18 11:45:29	ga_s2bm_ard_3-2-1_50JQP_2023-01-18_final.stac-item
2023-01-18 11:45:44	ga_s2bm_ard_3-2-1_50JQN_2023-01-18_final.stac-item
2023-01-18 11:45:51	ga_s2bm_ard_3-2-1_50JNN_2023-01-18_final.stac-item
2023-01-18 11:46:05	ga_s2bm_ard_3-2-1_51JTF_2023-01-18_final.stac-item
2023-01-18 11:46:05	ga_s2bm_ard_3-2-1_50JNM_2023-01-18_final.stac-item
2023-01-18 11:46:10	ga_s2bm_ard_3-2-1_50JMM_2023-01-18_final.stac-item
2023-01-18 11:46:16	ga_s2bm_ard_3-2-1_50JPL_2023-01-18_final.stac-item
2023-01-18 11:46:23	ga_s2bm_ard_3-2-1_50JML_2023-01-18_final.stac-item
2023-01-18 11:46:27	ga_s2bm_ard_3-2-1_50HQK_2023-01-18_final.stac-item
2023-01-18 11:46:31	ga_s2bm_ard_3-2-1_50HPK_2023-01-18_final.stac-item
2023-01-18 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2023-01-18_final.stac-item
2023-01-18 11:46:38	ga_s2bm_ard_3-2-1_50HMK_2023-01-18_final.stac-item
2023-01-18 11:46:45	ga_s2bm_ard_3-2-1_50HPJ_2023-01-18_final.stac-item
2023-01-18 11:46:49	ga_s2bm_ard_3-2-1_50HNJ_2023-01-18_final.stac-item
2023-01-18 11:46:51	ga_s2bm_ard_3-2-1_50HQH_2023-01-18_final.stac-item
2023-01-18 11:47:04	ga_s2bm_ard_3-2-1_50HNH_2023-01-18_final.stac-item
2023-01-19 11:11:13	ga_s2bm_ard_3-2-1_52LFK_2023-01-19_final.stac-item
2023-01-19 11:11:31	ga_s2bm_ard_3-2-1_52LEJ_2023-01-19_final.stac-item
2023-01-19 11:11:46	ga_s2bm_ard_3-2-1_52LEH_2023-01-19_final.stac-item
2023-01-19 11:12:18	ga_s2bm_ard_3-2-1_52KDF_2023-01-19_final.stac-item
2023-01-19 11:12:26	ga_s2bm_ard_3-2-1_52KFE_2023-01-19_final.stac-item
2023-01-19 11:12:33	ga_s2bm_ard_3-2-1_52KDE_2023-01-19_final.stac-item
2023-01-19 11:12:35	ga_s2bm_ard_3-2-1_52KCE_2023-01-19_final.stac-item
2023-01-19 11:12:40	ga_s2bm_ard_3-2-1_52KFD_2023-01-19_final.stac-item
2023-01-19 11:12:44	ga_s2bm_ard_3-2-1_52KED_2023-01-19_final.stac-item
2023-01-19 11:12:50	ga_s2bm_ard_3-2-1_52KCD_2023-01-19_final.stac-item
2023-01-19 11:13:13	ga_s2bm_ard_3-2-1_52KEB_2023-01-19_final.stac-item
2023-01-19 11:14:06	ga_s2bm_ard_3-2-1_52KBU_2023-01-19_final.stac-item
2023-01-19 11:14:21	ga_s2bm_ard_3-2-1_52JBT_2023-01-19_final.stac-item
2023-01-19 11:14:36	ga_s2bm_ard_3-2-1_52JBS_2023-01-19_final.stac-item
2023-01-19 11:14:53	ga_s2bm_ard_3-2-1_51JYL_2023-01-19_final.stac-item
2023-01-19 11:15:08	ga_s2bm_ard_3-2-1_51JYK_2023-01-19_final.stac-item
2023-01-19 11:15:40	ga_s2bm_ard_3-2-1_51JXH_2023-01-19_final.stac-item
2023-01-19 11:15:55	ga_s2bm_ard_3-2-1_51JXG_2023-01-19_final.stac-item
2023-01-19 11:16:20	ga_s2bm_ard_3-2-1_51HYE_2023-01-19_final.stac-item
2023-01-19 11:16:28	ga_s2bm_ard_3-2-1_51HWE_2023-01-19_final.stac-item
2023-01-20 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2023-01-20_final.stac-item
2023-01-20 10:44:59	ga_s2bm_ard_3-2-1_53JKK_2023-01-20_final.stac-item
2023-01-20 10:46:03	ga_s2bm_ard_3-2-1_53HME_2023-01-20_final.stac-item
2023-02-03 12:00:37	ga_s2bm_ard_3-2-1_50LNP_2023-02-03_nrt.stac-item
2023-02-03 12:00:59	ga_s2bm_ard_3-2-1_50LQM_2023-02-03_nrt.stac-item
2023-02-03 12:01:09	ga_s2bm_ard_3-2-1_50LMM_2023-02-03_nrt.stac-item
2023-02-03 12:01:20	ga_s2bm_ard_3-2-1_50LNL_2023-02-03_nrt.stac-item
2023-02-03 12:01:24	ga_s2bm_ard_3-2-1_50LML_2023-02-03_nrt.stac-item
2023-02-03 12:01:24	ga_s2bm_ard_3-2-1_50LQK_2023-02-03_nrt.stac-item
2023-02-03 12:01:31	ga_s2bm_ard_3-2-1_50LPK_2023-02-03_nrt.stac-item
2023-02-03 12:01:35	ga_s2bm_ard_3-2-1_50LMK_2023-02-03_nrt.stac-item
2023-02-03 12:01:38	ga_s2bm_ard_3-2-1_50LPJ_2023-02-03_nrt.stac-item
2023-02-03 12:02:53	ga_s2bm_ard_3-2-1_50KNE_2023-02-03_nrt.stac-item
2023-02-03 12:03:05	ga_s2bm_ard_3-2-1_50KMD_2023-02-03_nrt.stac-item
2023-02-03 12:03:11	ga_s2bm_ard_3-2-1_50KKD_2023-02-03_nrt.stac-item
2023-02-03 12:03:27	ga_s2bm_ard_3-2-1_49KHT_2023-02-03_nrt.stac-item
2023-02-03 12:05:16	ga_s2bm_ard_3-2-1_49JFL_2023-02-03_nrt.stac-item
2023-02-03 12:05:29	ga_s2bm_ard_3-2-1_49JFK_2023-02-03_nrt.stac-item
2023-02-03 12:05:44	ga_s2bm_ard_3-2-1_49JFJ_2023-02-03_nrt.stac-item
2023-02-03 12:06:19	ga_s2bm_ard_3-2-1_50JKL_2023-02-03_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

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