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
2019-07-26 11:04:59	ga_s2bm_ard_3-2-1_52JDR_2019-07-26_final.stac-item
2019-07-26 11:05:04	ga_s2bm_ard_3-2-1_52JCR_2019-07-26_final.stac-item
2019-07-26 11:05:13	ga_s2bm_ard_3-2-1_52JDQ_2019-07-26_final.stac-item
2019-07-26 11:05:16	ga_s2bm_ard_3-2-1_52JCQ_2019-07-26_final.stac-item
2019-07-26 11:05:28	ga_s2bm_ard_3-2-1_52JDP_2019-07-26_final.stac-item
2019-07-26 11:05:31	ga_s2bm_ard_3-2-1_52JCP_2019-07-26_final.stac-item
2019-07-26 11:05:42	ga_s2bm_ard_3-2-1_52JDN_2019-07-26_final.stac-item
2019-07-29 11:13:27	ga_s2bm_ard_3-2-1_52KDB_2019-07-29_final.stac-item
2019-07-29 11:13:30	ga_s2bm_ard_3-2-1_52KCB_2019-07-29_final.stac-item
2019-07-29 11:13:41	ga_s2bm_ard_3-2-1_52KDA_2019-07-29_final.stac-item
2019-07-29 11:13:45	ga_s2bm_ard_3-2-1_52KCA_2019-07-29_final.stac-item
2019-07-29 11:13:56	ga_s2bm_ard_3-2-1_52KDV_2019-07-29_final.stac-item
2019-07-29 11:13:59	ga_s2bm_ard_3-2-1_52KCV_2019-07-29_final.stac-item
2019-07-29 11:14:10	ga_s2bm_ard_3-2-1_52KDU_2019-07-29_final.stac-item
2019-07-29 11:14:14	ga_s2bm_ard_3-2-1_52KCU_2019-07-29_final.stac-item
2019-07-29 11:14:25	ga_s2bm_ard_3-2-1_52JDT_2019-07-29_final.stac-item
2019-07-29 11:14:28	ga_s2bm_ard_3-2-1_52JCT_2019-07-29_final.stac-item
2019-07-29 11:14:36	ga_s2bm_ard_3-2-1_52JDS_2019-07-29_final.stac-item
2019-07-29 11:14:38	ga_s2bm_ard_3-2-1_52JCS_2019-07-29_final.stac-item
2019-07-29 11:14:43	ga_s2bm_ard_3-2-1_52JDS_2019-07-29_final.stac-item
2019-07-29 11:14:44	ga_s2bm_ard_3-2-1_52JCS_2019-07-29_final.stac-item
2019-07-29 11:14:54	ga_s2bm_ard_3-2-1_52JDR_2019-07-29_final.stac-item
2019-07-29 11:14:58	ga_s2bm_ard_3-2-1_52JCR_2019-07-29_final.stac-item
2019-07-29 11:15:08	ga_s2bm_ard_3-2-1_52JDQ_2019-07-29_final.stac-item
2019-07-29 11:15:12	ga_s2bm_ard_3-2-1_52JCQ_2019-07-29_final.stac-item
2019-07-29 11:15:20	ga_s2bm_ard_3-2-1_52JDP_2019-07-29_final.stac-item
2019-07-29 11:15:26	ga_s2bm_ard_3-2-1_52JCP_2019-07-29_final.stac-item
2019-08-01 11:21:43	ga_s2bm_ard_3-2-1_52LCJ_2019-08-01_final.stac-item
2019-08-01 11:21:58	ga_s2bm_ard_3-2-1_52LCH_2019-08-01_final.stac-item
2019-08-01 11:22:08	ga_s2bm_ard_3-2-1_52KDG_2019-08-01_final.stac-item
2019-08-01 11:22:12	ga_s2bm_ard_3-2-1_52KCG_2019-08-01_final.stac-item
2019-08-01 11:22:20	ga_s2bm_ard_3-2-1_52KDF_2019-08-01_final.stac-item
2020-04-21 11:05:43	ga_s2bm_ard_3-2-1_52JDM_2020-04-21_final.stac-item
2020-04-21 11:05:47	ga_s2bm_ard_3-2-1_52JCM_2020-04-21_final.stac-item
2020-04-21 11:05:58	ga_s2bm_ard_3-2-1_52JDL_2020-04-21_final.stac-item
2023-05-12 11:22:15	ga_s2bm_ard_3-2-1_52KDF_2023-05-12_final
2023-05-12 11:22:21	ga_s2bm_ard_3-2-1_52KCF_2023-05-12_final
2023-05-16 11:06:34	ga_s2bm_ard_3-2-1_52HDJ_2023-05-16_nrt
2023-08-24 11:04:54	ga_s2bm_ard_3-2-1_52JDR_2023-08-24_final
2023-08-24 11:05:00	ga_s2bm_ard_3-2-1_52JCR_2023-08-24_final
2023-08-24 11:05:09	ga_s2bm_ard_3-2-1_52JDQ_2023-08-24_final
2023-08-24 11:05:11	ga_s2bm_ard_3-2-1_52JCQ_2023-08-24_final
2023-08-24 11:05:16	ga_s2bm_ard_3-2-1_52JDQ_2023-08-24_final
2023-08-24 11:05:16	ga_s2bm_ard_3-2-1_52JDP_2023-08-24_final
2023-08-24 11:05:16	ga_s2bm_ard_3-2-1_52JCP_2023-08-24_final
2023-08-24 11:05:17	ga_s2bm_ard_3-2-1_52JCQ_2023-08-24_final
2023-08-24 11:05:24	ga_s2bm_ard_3-2-1_52JDP_2023-08-24_final
2023-08-24 11:05:27	ga_s2bm_ard_3-2-1_52JCP_2023-08-24_final
2023-08-24 11:05:38	ga_s2bm_ard_3-2-1_52JDN_2023-08-24_final
2023-08-24 11:05:41	ga_s2bm_ard_3-2-1_52JCN_2023-08-24_final
2023-08-24 11:05:53	ga_s2bm_ard_3-2-1_52JDM_2023-08-24_final
2023-08-24 11:06:07	ga_s2bm_ard_3-2-1_52JDL_2023-08-24_final
2023-08-24 11:06:22	ga_s2bm_ard_3-2-1_52HDK_2023-08-24_final
2023-08-24 11:06:34	ga_s2bm_ard_3-2-1_52HDJ_2023-08-24_nrt
2023-08-27 11:12:10	ga_s2bm_ard_3-2-1_52KDG_2023-08-27_final
2023-08-27 11:12:15	ga_s2bm_ard_3-2-1_52KCG_2023-08-27_final
2023-08-27 11:12:25	ga_s2bm_ard_3-2-1_52KDF_2023-08-27_final
2023-08-27 11:12:28	ga_s2bm_ard_3-2-1_52KCF_2023-08-27_final
2023-08-27 11:12:39	ga_s2bm_ard_3-2-1_52KDE_2023-08-27_final
2023-08-27 11:12:42	ga_s2bm_ard_3-2-1_52KCE_2023-08-27_final
2023-08-27 11:12:54	ga_s2bm_ard_3-2-1_52KDD_2023-08-27_final
2023-08-27 11:12:57	ga_s2bm_ard_3-2-1_52KCD_2023-08-27_final
2023-08-27 11:13:09	ga_s2bm_ard_3-2-1_52KDC_2023-08-27_final
2023-08-27 11:13:12	ga_s2bm_ard_3-2-1_52KCC_2023-08-27_final
2023-08-27 11:13:22	ga_s2bm_ard_3-2-1_52KDB_2023-08-27_final
2023-08-27 11:13:23	ga_s2bm_ard_3-2-1_52KCB_2023-08-27_final
2023-08-27 11:13:28	ga_s2bm_ard_3-2-1_52KDB_2023-08-27_final
2023-08-27 11:13:30	ga_s2bm_ard_3-2-1_52KCB_2023-08-27_final
2023-08-27 11:13:38	ga_s2bm_ard_3-2-1_52KDA_2023-08-27_final
2023-08-27 11:13:41	ga_s2bm_ard_3-2-1_52KCA_2023-08-27_final
2023-08-27 11:13:52	ga_s2bm_ard_3-2-1_52KDV_2023-08-27_final
2023-08-27 11:13:56	ga_s2bm_ard_3-2-1_52KCV_2023-08-27_final
2023-08-27 11:14:07	ga_s2bm_ard_3-2-1_52KDU_2023-08-27_final
2023-08-27 11:14:10	ga_s2bm_ard_3-2-1_52KCU_2023-08-27_final
2023-08-27 11:14:21	ga_s2bm_ard_3-2-1_52JDT_2023-08-27_final
2023-08-27 11:14:25	ga_s2bm_ard_3-2-1_52JCT_2023-08-27_final
2023-08-27 11:14:36	ga_s2bm_ard_3-2-1_52JDS_2023-08-27_final
2023-08-27 11:14:39	ga_s2bm_ard_3-2-1_52JCS_2023-08-27_final
2023-08-27 11:14:50	ga_s2bm_ard_3-2-1_52JDR_2023-08-27_final
2023-08-27 11:14:54	ga_s2bm_ard_3-2-1_52JCR_2023-08-27_final
2023-08-27 11:15:04	ga_s2bm_ard_3-2-1_52JDQ_2023-08-27_final
2023-08-27 11:15:08	ga_s2bm_ard_3-2-1_52JCQ_2023-08-27_final
2023-08-27 11:15:16	ga_s2bm_ard_3-2-1_52JDP_2023-08-27_final
2023-08-27 11:15:23	ga_s2bm_ard_3-2-1_52JCP_2023-08-27_final
2023-08-30 11:22:17	ga_s2bm_ard_3-2-1_52KDF_2023-08-30_final
2023-08-30 11:22:23	ga_s2bm_ard_3-2-1_52KCF_2023-08-30_final
2023-09-03 11:04:55	ga_s2bm_ard_3-2-1_52JDR_2023-09-03_final
2023-09-03 11:05:00	ga_s2bm_ard_3-2-1_52JCR_2023-09-03_final
2023-09-03 11:05:09	ga_s2bm_ard_3-2-1_52JDQ_2023-09-03_final
2023-09-03 11:05:12	ga_s2bm_ard_3-2-1_52JCQ_2023-09-03_final
2023-09-03 11:05:16	ga_s2bm_ard_3-2-1_52JDQ_2023-09-03_final
2023-09-03 11:05:17	ga_s2bm_ard_3-2-1_52JCQ_2023-09-03_final
2023-09-03 11:05:24	ga_s2bm_ard_3-2-1_52JDP_2023-09-03_final
2023-09-03 11:05:27	ga_s2bm_ard_3-2-1_52JCP_2023-09-03_final
2023-09-03 11:05:39	ga_s2bm_ard_3-2-1_52JDN_2023-09-03_final
2023-09-03 11:05:42	ga_s2bm_ard_3-2-1_52JCN_2023-09-03_final
2023-09-03 11:05:53	ga_s2bm_ard_3-2-1_52JDM_2023-09-03_final
2023-09-03 11:05:57	ga_s2bm_ard_3-2-1_52JCM_2023-09-03_final
2023-09-03 11:06:08	ga_s2bm_ard_3-2-1_52JDL_2023-09-03_final
2023-09-03 11:06:22	ga_s2bm_ard_3-2-1_52HDK_2023-09-03_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

All years