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
2021-08-03 11:36:59	ga_s2bm_ard_3-2-1_51HUC_2021-08-03_final.stac-item
2021-08-03 11:37:14	ga_s2bm_ard_3-2-1_51HUB_2021-08-03_final
2021-08-13 11:36:43	ga_s2bm_ard_3-2-1_51HUD_2021-08-13_final.stac-item
2021-08-13 11:36:58	ga_s2bm_ard_3-2-1_51HUC_2021-08-13_final.stac-item
2021-08-13 11:37:13	ga_s2bm_ard_3-2-1_51HUB_2021-08-13_final
2021-08-23 11:36:56	ga_s2bm_ard_3-2-1_51HUC_2021-08-23_final.stac-item
2021-08-23 11:37:11	ga_s2bm_ard_3-2-1_51HUB_2021-08-23_final
2022-09-07 11:35:03	ga_s2bm_ard_3-2-1_51JUL_2022-09-07_final.stac-item
2022-09-07 11:35:06	ga_s2bm_ard_3-2-1_51JTL_2022-09-07_final.stac-item
2022-09-07 11:35:17	ga_s2bm_ard_3-2-1_51JUK_2022-09-07_final.stac-item
2022-09-07 11:35:21	ga_s2bm_ard_3-2-1_51JTK_2022-09-07_final.stac-item
2022-09-07 11:35:32	ga_s2bm_ard_3-2-1_51JUJ_2022-09-07_final.stac-item
2022-09-07 11:35:47	ga_s2bm_ard_3-2-1_51JUH_2022-09-07_final.stac-item
2022-09-07 11:36:01	ga_s2bm_ard_3-2-1_51JUG_2022-09-07_final.stac-item
2022-09-07 11:36:16	ga_s2bm_ard_3-2-1_51JUF_2022-09-07_final.stac-item
2022-09-07 11:36:30	ga_s2bm_ard_3-2-1_51HUE_2022-09-07_final.stac-item
2022-09-07 11:36:45	ga_s2bm_ard_3-2-1_51HUD_2022-09-07_final.stac-item
2022-09-07 11:36:59	ga_s2bm_ard_3-2-1_51HUC_2022-09-07_final.stac-item
2022-09-10 11:44:53	ga_s2bm_ard_3-2-1_51JUL_2022-09-10_final.stac-item
2022-09-10 11:45:02	ga_s2bm_ard_3-2-1_51JTL_2022-09-10_final.stac-item
2022-12-09 11:44:41	ga_s2bm_ard_3-2-1_51JTM_2022-12-09_final.stac-item
2022-12-09 11:44:56	ga_s2bm_ard_3-2-1_51JTL_2022-12-09_final.stac-item
2022-12-12 11:50:30	ga_s2bm_ard_3-2-1_51LTJ_2022-12-12_nrt.stac-item
2022-12-12 11:50:45	ga_s2bm_ard_3-2-1_51LTH_2022-12-12_nrt.stac-item
2022-12-12 11:50:59	ga_s2bm_ard_3-2-1_51LTG_2022-12-12_nrt.stac-item
2022-12-12 11:51:14	ga_s2bm_ard_3-2-1_51LTF_2022-12-12_nrt.stac-item
2022-12-12 11:51:28	ga_s2bm_ard_3-2-1_51LTE_2022-12-12_nrt.stac-item
2022-12-12 11:51:43	ga_s2bm_ard_3-2-1_51LTD_2022-12-12_nrt.stac-item
2022-12-12 11:51:57	ga_s2bm_ard_3-2-1_51LTC_2022-12-12_nrt.stac-item
2022-12-19 11:42:47	ga_s2bm_ard_3-2-1_51KTV_2022-12-19_nrt.stac-item
2022-12-19 11:43:02	ga_s2bm_ard_3-2-1_51KTU_2022-12-19_final.stac-item
2022-12-19 11:43:17	ga_s2bm_ard_3-2-1_51KTT_2022-12-19_final.stac-item
2022-12-19 11:43:28	ga_s2bm_ard_3-2-1_51KUS_2022-12-19_final.stac-item
2022-12-19 11:43:31	ga_s2bm_ard_3-2-1_51KTS_2022-12-19_final.stac-item
2022-12-19 11:43:42	ga_s2bm_ard_3-2-1_51KUR_2022-12-19_final.stac-item
2022-12-19 11:43:46	ga_s2bm_ard_3-2-1_51KTR_2022-12-19_final.stac-item
2022-12-19 11:43:57	ga_s2bm_ard_3-2-1_51KUQ_2022-12-19_final.stac-item
2022-12-19 11:44:00	ga_s2bm_ard_3-2-1_51KTQ_2022-12-19_final.stac-item
2022-12-19 11:44:12	ga_s2bm_ard_3-2-1_51KUP_2022-12-19_final.stac-item
2022-12-19 11:44:15	ga_s2bm_ard_3-2-1_51KTP_2022-12-19_final.stac-item
2022-12-19 11:44:26	ga_s2bm_ard_3-2-1_51JUN_2022-12-19_final.stac-item
2022-12-19 11:44:29	ga_s2bm_ard_3-2-1_50JRT_2022-12-19_final.stac-item
2022-12-19 11:44:30	ga_s2bm_ard_3-2-1_51JTN_2022-12-19_final.stac-item
2022-12-19 11:44:39	ga_s2bm_ard_3-2-1_51JUM_2022-12-19_final.stac-item
2022-12-19 11:44:44	ga_s2bm_ard_3-2-1_50JRS_2022-12-19_final.stac-item
2022-12-19 11:44:44	ga_s2bm_ard_3-2-1_51JTM_2022-12-19_final.stac-item
2022-12-19 11:44:50	ga_s2bm_ard_3-2-1_51JUL_2022-12-19_final.stac-item
2022-12-19 11:44:58	ga_s2bm_ard_3-2-1_51JTL_2022-12-19_final.stac-item
2023-01-25 11:34:30	ga_s2bm_ard_3-2-1_51JUN_2023-01-25_final.stac-item
2023-01-25 11:34:34	ga_s2bm_ard_3-2-1_51JTN_2023-01-25_final.stac-item
2023-01-25 11:34:35	ga_s2bm_ard_3-2-1_50JRT_2023-01-25_final.stac-item
2023-01-25 11:34:44	ga_s2bm_ard_3-2-1_51JUM_2023-01-25_final.stac-item
2023-01-25 11:34:47	ga_s2bm_ard_3-2-1_50JRS_2023-01-25_final.stac-item
2023-01-25 11:34:47	ga_s2bm_ard_3-2-1_51JTM_2023-01-25_final.stac-item
2023-01-25 11:34:59	ga_s2bm_ard_3-2-1_51JUL_2023-01-25_final.stac-item
2023-01-25 11:35:02	ga_s2bm_ard_3-2-1_51JTL_2023-01-25_final.stac-item
2023-01-25 11:35:14	ga_s2bm_ard_3-2-1_51JUK_2023-01-25_final.stac-item
2023-01-25 11:35:17	ga_s2bm_ard_3-2-1_51JTK_2023-01-25_final.stac-item
2023-01-25 11:35:28	ga_s2bm_ard_3-2-1_51JUJ_2023-01-25_final.stac-item
2023-01-25 11:35:43	ga_s2bm_ard_3-2-1_51JUH_2023-01-25_final.stac-item
2023-01-25 11:35:57	ga_s2bm_ard_3-2-1_51JUG_2023-01-25_final.stac-item
2023-01-25 11:36:12	ga_s2bm_ard_3-2-1_51JUF_2023-01-25_final.stac-item
2023-01-25 11:36:26	ga_s2bm_ard_3-2-1_51HUE_2023-01-25_final.stac-item
2023-01-25 11:36:41	ga_s2bm_ard_3-2-1_51HUD_2023-01-25_final.stac-item
2023-01-25 11:36:55	ga_s2bm_ard_3-2-1_51HUC_2023-01-25_final.stac-item
2023-01-25 11:37:24	ga_s2bm_ard_3-2-1_51HUA_2023-01-25_nrt.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 11:35:16	ga_s2bm_ard_3-2-1_51JTK_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 11:35:42	ga_s2bm_ard_3-2-1_51JUH_2023-02-04_final.stac-item
2023-02-04 11:35:56	ga_s2bm_ard_3-2-1_51JUG_2023-02-04_final.stac-item
2023-02-04 11:36:11	ga_s2bm_ard_3-2-1_51JUF_2023-02-04_final.stac-item
2023-02-04 11:36:25	ga_s2bm_ard_3-2-1_51HUE_2023-02-04_final.stac-item
2023-02-04 11:36:40	ga_s2bm_ard_3-2-1_51HUD_2023-02-04_final.stac-item
2023-02-04 11:36:54	ga_s2bm_ard_3-2-1_51HUC_2023-02-04_final.stac-item
2023-02-04 11:37:23	ga_s2bm_ard_3-2-1_51HUA_2023-02-04_nrt.stac-item
2023-02-07 11:41:35	ga_s2bm_ard_3-2-1_51LTE_2023-02-07_nrt.stac-item
2023-02-07 11:41:48	ga_s2bm_ard_3-2-1_51LTD_2023-02-07_nrt.stac-item
2023-02-07 11:42:03	ga_s2bm_ard_3-2-1_51LTC_2023-02-07_nrt.stac-item
2023-02-07 11:42:18	ga_s2bm_ard_3-2-1_51KTB_2023-02-07_nrt.stac-item
2023-02-07 11:42:32	ga_s2bm_ard_3-2-1_51KTA_2023-02-07_nrt.stac-item
2023-02-07 11:42:47	ga_s2bm_ard_3-2-1_51KTV_2023-02-07_nrt.stac-item
2023-02-07 11:43:01	ga_s2bm_ard_3-2-1_51KTU_2023-02-07_final
2023-02-07 11:43:16	ga_s2bm_ard_3-2-1_51KTT_2023-02-07_final
2023-02-07 11:43:27	ga_s2bm_ard_3-2-1_51KUS_2023-02-07_final
2023-02-07 11:43:30	ga_s2bm_ard_3-2-1_51KTS_2023-02-07_final
2023-02-07 11:43:41	ga_s2bm_ard_3-2-1_51KUR_2023-02-07_final
2023-02-07 11:43:45	ga_s2bm_ard_3-2-1_51KTR_2023-02-07_final
2023-02-07 11:43:56	ga_s2bm_ard_3-2-1_51KUQ_2023-02-07_final
2023-02-07 11:44:00	ga_s2bm_ard_3-2-1_51KTQ_2023-02-07_final
2023-02-07 11:44:11	ga_s2bm_ard_3-2-1_51KUP_2023-02-07_final
2023-02-07 11:44:14	ga_s2bm_ard_3-2-1_51KTP_2023-02-07_final
2023-02-07 11:44:25	ga_s2bm_ard_3-2-1_51JUN_2023-02-07_final
2023-02-07 11:44:29	ga_s2bm_ard_3-2-1_50JRT_2023-02-07_final
2023-02-07 11:44:29	ga_s2bm_ard_3-2-1_51JTN_2023-02-07_final
2023-02-07 11:44:39	ga_s2bm_ard_3-2-1_51JUM_2023-02-07_final
2023-02-07 11:44:43	ga_s2bm_ard_3-2-1_50JRS_2023-02-07_final
2023-02-07 11:44:43	ga_s2bm_ard_3-2-1_51JTM_2023-02-07_final
2023-02-07 11:44:49	ga_s2bm_ard_3-2-1_51JUL_2023-02-07_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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