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
2017-10-05 12:13:06	ga_s2bm_ard_3-2-1_49KGR_2017-10-05_final.stac-item
2017-10-05 12:13:06	ga_s2bm_ard_3-2-1_49KHR_2017-10-05_final.stac-item
2017-10-05 12:13:06	ga_s2bm_ard_3-2-1_50KKA_2017-10-05_final.stac-item
2017-10-05 12:13:06	ga_s2bm_ard_3-2-1_50KKB_2017-10-05_final.stac-item
2017-10-05 12:13:31	ga_s2bm_ard_3-2-1_49KGR_2017-10-05_final.stac-item
2017-10-14 11:01:57	ga_s2bm_ard_3-2-1_52KEB_2017-10-14_final.stac-item
2017-10-14 11:01:57	ga_s2bm_ard_3-2-1_53KKR_2017-10-14_final.stac-item
2018-01-21 09:51:48	ga_s2bm_ard_3-2-1_55KDS_2018-01-21_final.stac-item
2018-01-21 09:51:48	ga_s2bm_ard_3-2-1_55KES_2018-01-21_final.stac-item
2018-01-21 09:51:48	ga_s2bm_ard_3-2-1_55KFR_2018-01-21_final.stac-item
2018-01-21 09:51:48	ga_s2bm_ard_3-2-1_55KFS_2018-01-21_final.stac-item
2018-01-21 09:51:48	ga_s2bm_ard_3-2-1_55KGR_2018-01-21_final.stac-item
2018-01-21 09:51:48	ga_s2bm_ard_3-2-1_55KGS_2018-01-21_final.stac-item
2018-01-24 10:01:34	ga_s2bm_ard_3-2-1_55KBR_2018-01-24_final.stac-item
2018-01-24 10:01:34	ga_s2bm_ard_3-2-1_55KBS_2018-01-24_final.stac-item
2018-01-24 10:01:34	ga_s2bm_ard_3-2-1_55KCS_2018-01-24_final.stac-item
2018-01-24 10:01:34	ga_s2bm_ard_3-2-1_54KZA_2018-01-24_final.stac-item
2018-01-24 10:01:34	ga_s2bm_ard_3-2-1_54KZB_2018-01-24_final.stac-item
2018-01-24 10:01:34	ga_s2bm_ard_3-2-1_55KDS_2018-01-24_final.stac-item
2018-01-24 10:01:34	ga_s2bm_ard_3-2-1_55KES_2018-01-24_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_54KWB_2018-02-06_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_54KXA_2018-02-06_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_54KXB_2018-02-06_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_55KBR_2018-02-06_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_55KBS_2018-02-06_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_54KYA_2018-02-06_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_54KYB_2018-02-06_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_54KZA_2018-02-06_final.stac-item
2018-02-06 10:11:24	ga_s2bm_ard_3-2-1_54KZB_2018-02-06_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_49KHR_2018-10-07_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_50KKA_2018-10-07_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_50KKB_2018-10-07_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_50KLB_2018-10-07_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_50KMB_2018-10-07_final.stac-item
2018-10-07 12:02:45	ga_s2bm_ard_3-2-1_50KNB_2018-10-07_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KMB_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KNB_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KPA_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KPB_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KQA_2018-10-14_final.stac-item
2018-10-14 11:52:46	ga_s2bm_ard_3-2-1_50KQB_2018-10-14_final.stac-item
2018-10-15 09:41:05	ga_s2bm_ard_3-2-1_56KKA_2018-10-15_final.stac-item
2018-10-15 09:41:05	ga_s2bm_ard_3-2-1_56KKB_2018-10-15_final.stac-item
2018-10-15 09:41:05	ga_s2bm_ard_3-2-1_56KLB_2018-10-15_final.stac-item
2018-10-15 09:41:05	ga_s2bm_ard_3-2-1_55KGR_2018-10-15_final.stac-item
2018-10-15 09:41:05	ga_s2bm_ard_3-2-1_55KGS_2018-10-15_final.stac-item
2018-10-15 09:41:05	ga_s2bm_ard_3-2-1_55KHR_2018-10-15_final.stac-item
2018-10-15 09:41:05	ga_s2bm_ard_3-2-1_55KHS_2018-10-15_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_49KHR_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50KKA_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50KKB_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50KLB_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50KMB_2018-10-17_final.stac-item
2018-10-17 12:03:15	ga_s2bm_ard_3-2-1_50KNB_2018-10-17_final.stac-item
2019-08-02 10:53:15	ga_s2bm_ard_3-2-1_53KMS_2019-08-02_final.stac-item
2019-08-02 10:53:18	ga_s2bm_ard_3-2-1_53KLS_2019-08-02_final.stac-item
2019-08-02 10:53:21	ga_s2bm_ard_3-2-1_53KKS_2019-08-02_final.stac-item
2019-08-02 10:53:22	ga_s2bm_ard_3-2-1_52KHB_2019-08-02_final.stac-item
2019-08-02 10:53:28	ga_s2bm_ard_3-2-1_52KGB_2019-08-02_final.stac-item
2019-08-02 10:53:36	ga_s2bm_ard_3-2-1_53KKR_2019-08-02_final.stac-item
2019-08-03 10:23:01	ga_s2bm_ard_3-2-1_54KXB_2019-08-03_final.stac-item
2019-08-03 10:23:04	ga_s2bm_ard_3-2-1_54KWB_2019-08-03_final.stac-item
2019-08-03 10:23:07	ga_s2bm_ard_3-2-1_54KVB_2019-08-03_final.stac-item
2019-08-03 10:23:12	ga_s2bm_ard_3-2-1_54KWB_2019-08-03_final.stac-item
2019-08-03 10:23:14	ga_s2bm_ard_3-2-1_54KVB_2019-08-03_final.stac-item
2019-08-03 10:23:15	ga_s2bm_ard_3-2-1_54KUB_2019-08-03_final.stac-item
2019-08-10 10:12:57	ga_s2bm_ard_3-2-1_55KBS_2019-08-10_final.stac-item
2019-08-10 10:12:57	ga_s2bm_ard_3-2-1_54KZB_2019-08-10_final.stac-item
2019-08-10 10:13:01	ga_s2bm_ard_3-2-1_54KYB_2019-08-10_final.stac-item
2019-08-10 10:13:05	ga_s2bm_ard_3-2-1_54KXB_2019-08-10_final.stac-item
2019-08-10 10:13:11	ga_s2bm_ard_3-2-1_54KWB_2019-08-10_final.stac-item
2019-08-10 10:13:11	ga_s2bm_ard_3-2-1_55KBR_2019-08-10_final.stac-item
2019-08-10 10:13:12	ga_s2bm_ard_3-2-1_54KZA_2019-08-10_final.stac-item
2019-08-10 10:13:16	ga_s2bm_ard_3-2-1_54KYA_2019-08-10_final.stac-item
2019-08-10 10:13:19	ga_s2bm_ard_3-2-1_54KXA_2019-08-10_final.stac-item
2019-08-16 12:13:46	ga_s2bm_ard_3-2-1_50KKB_2019-08-16_final.stac-item
2019-08-16 12:14:00	ga_s2bm_ard_3-2-1_50KKA_2019-08-16_final.stac-item
2019-08-16 12:14:01	ga_s2bm_ard_3-2-1_49KHR_2019-08-16_final.stac-item
2019-08-16 12:14:04	ga_s2bm_ard_3-2-1_49KGR_2019-08-16_final.stac-item
2019-08-17 10:02:51	ga_s2bm_ard_3-2-1_55KES_2019-08-17_final.stac-item
2019-08-17 10:02:54	ga_s2bm_ard_3-2-1_55KDS_2019-08-17_final.stac-item
2019-08-17 10:02:58	ga_s2bm_ard_3-2-1_55KCS_2019-08-17_final.stac-item
2019-08-17 10:03:00	ga_s2bm_ard_3-2-1_55KBS_2019-08-17_final.stac-item
2019-08-17 10:03:01	ga_s2bm_ard_3-2-1_54KZB_2019-08-17_final.stac-item
2019-08-17 10:03:15	ga_s2bm_ard_3-2-1_55KBR_2019-08-17_final.stac-item
2019-08-17 10:03:15	ga_s2bm_ard_3-2-1_54KZA_2019-08-17_final.stac-item
2019-08-20 10:12:55	ga_s2bm_ard_3-2-1_55KBS_2019-08-20_final.stac-item
2019-08-20 10:12:56	ga_s2bm_ard_3-2-1_54KZB_2019-08-20_final.stac-item
2019-08-20 10:13:00	ga_s2bm_ard_3-2-1_54KYB_2019-08-20_final.stac-item
2019-08-20 10:13:03	ga_s2bm_ard_3-2-1_54KXB_2019-08-20_final.stac-item
2019-08-20 10:13:09	ga_s2bm_ard_3-2-1_54KWB_2019-08-20_final.stac-item
2019-08-20 10:13:10	ga_s2bm_ard_3-2-1_55KBR_2019-08-20_final.stac-item
2019-08-20 10:13:10	ga_s2bm_ard_3-2-1_54KZA_2019-08-20_final.stac-item
2019-08-20 10:13:14	ga_s2bm_ard_3-2-1_54KYA_2019-08-20_final.stac-item
2019-08-20 10:13:18	ga_s2bm_ard_3-2-1_54KXA_2019-08-20_final.stac-item
2020-05-26 11:53:33	ga_s2bm_ard_3-2-1_50KQB_2020-05-26_final.stac-item
2020-05-26 11:53:36	ga_s2bm_ard_3-2-1_50KPB_2020-05-26_final.stac-item
2020-05-26 11:53:40	ga_s2bm_ard_3-2-1_50KNB_2020-05-26_final.stac-item
2020-05-26 11:53:43	ga_s2bm_ard_3-2-1_50KMB_2020-05-26_final.stac-item
2020-05-26 11:53:47	ga_s2bm_ard_3-2-1_50KQA_2020-05-26_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

All years