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
2017-09-09 11:51:47	ga_s2bm_ard_3-2-1_50KLU_2017-09-09_final.stac-item
2017-09-09 11:51:47	ga_s2bm_ard_3-2-1_50KMU_2017-09-09_final.stac-item
2017-09-09 11:51:47	ga_s2bm_ard_3-2-1_50KNU_2017-09-09_final.stac-item
2017-09-09 11:51:47	ga_s2bm_ard_3-2-1_50KPU_2017-09-09_final.stac-item
2017-09-09 11:51:47	ga_s2bm_ard_3-2-1_50KQU_2017-09-09_final.stac-item
2017-09-10 09:41:02	ga_s2bm_ard_3-2-1_56KKU_2017-09-10_final.stac-item
2017-09-10 09:41:02	ga_s2bm_ard_3-2-1_56KLU_2017-09-10_final.stac-item
2017-09-10 09:41:02	ga_s2bm_ard_3-2-1_55JHN_2017-09-10_final.stac-item
2017-09-10 09:41:02	ga_s2bm_ard_3-2-1_55KFP_2017-09-10_final.stac-item
2017-09-10 09:41:02	ga_s2bm_ard_3-2-1_55KGP_2017-09-10_final.stac-item
2017-09-10 09:41:02	ga_s2bm_ard_3-2-1_55KHP_2017-09-10_final.stac-item
2017-09-10 11:21:50	ga_s2bm_ard_3-2-1_52KBU_2017-09-10_final.stac-item
2017-09-10 11:21:50	ga_s2bm_ard_3-2-1_51KWP_2017-09-10_final.stac-item
2017-09-10 11:21:50	ga_s2bm_ard_3-2-1_51KXP_2017-09-10_final.stac-item
2017-09-10 11:21:50	ga_s2bm_ard_3-2-1_51KYP_2017-09-10_final.stac-item
2017-09-10 11:21:50	ga_s2bm_ard_3-2-1_51KZP_2017-09-10_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50JRT_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_51KTP_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_51KUP_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50KPU_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50KQU_2017-09-16_final.stac-item
2017-09-16 11:40:38	ga_s2bm_ard_3-2-1_50KRU_2017-09-16_final.stac-item
2017-09-19 10:13:05	ga_s2bm_ard_3-2-1_54KWU_2017-09-19_final.stac-item
2017-09-19 10:13:05	ga_s2bm_ard_3-2-1_55KBP_2017-09-19_final.stac-item
2017-09-19 10:13:05	ga_s2bm_ard_3-2-1_54KXU_2017-09-19_final.stac-item
2017-09-19 10:13:05	ga_s2bm_ard_3-2-1_54KYU_2017-09-19_final.stac-item
2017-09-19 10:13:05	ga_s2bm_ard_3-2-1_54KZU_2017-09-19_final.stac-item
2017-09-20 09:37:19	ga_s2bm_ard_3-2-1_56KKU_2017-09-20_final.stac-item
2017-09-20 09:37:19	ga_s2bm_ard_3-2-1_56KLU_2017-09-20_final.stac-item
2017-09-20 09:37:19	ga_s2bm_ard_3-2-1_55JHN_2017-09-20_final.stac-item
2017-09-20 09:37:19	ga_s2bm_ard_3-2-1_55KFP_2017-09-20_final.stac-item
2017-09-20 09:37:19	ga_s2bm_ard_3-2-1_55KGP_2017-09-20_final.stac-item
2017-09-20 09:37:19	ga_s2bm_ard_3-2-1_55KHP_2017-09-20_final.stac-item
2017-09-21 10:52:04	ga_s2bm_ard_3-2-1_52JHT_2017-09-21_final.stac-item
2017-09-21 10:52:04	ga_s2bm_ard_3-2-1_53KKP_2017-09-21_final.stac-item
2017-09-21 10:52:04	ga_s2bm_ard_3-2-1_53KLP_2017-09-21_final.stac-item
2017-09-21 10:52:04	ga_s2bm_ard_3-2-1_53KMP_2017-09-21_final.stac-item
2017-09-21 10:52:04	ga_s2bm_ard_3-2-1_52KGU_2017-09-21_final.stac-item
2017-09-21 10:52:04	ga_s2bm_ard_3-2-1_52KHU_2017-09-21_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_49JHN_2017-09-22_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_49KGP_2017-09-22_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_49KHP_2017-09-22_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_50KKU_2017-09-22_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_50KLU_2017-09-22_final.stac-item
2017-09-22 12:02:37	ga_s2bm_ard_3-2-1_50KMU_2017-09-22_final.stac-item
2017-09-23 09:51:21	ga_s2bm_ard_3-2-1_55KFP_2017-09-23_final.stac-item
2017-09-23 09:51:21	ga_s2bm_ard_3-2-1_55KGP_2017-09-23_final.stac-item
2017-09-24 11:01:57	ga_s2bm_ard_3-2-1_52KDU_2017-09-24_final.stac-item
2017-09-24 11:01:57	ga_s2bm_ard_3-2-1_52KEU_2017-09-24_final.stac-item
2017-09-24 11:01:57	ga_s2bm_ard_3-2-1_52KFU_2017-09-24_final.stac-item
2017-09-24 11:01:57	ga_s2bm_ard_3-2-1_52KGU_2017-09-24_final.stac-item
2017-09-29 11:51:40	ga_s2bm_ard_3-2-1_50KMU_2017-09-29_final.stac-item
2017-09-29 11:51:40	ga_s2bm_ard_3-2-1_50KNU_2017-09-29_final.stac-item
2017-09-29 11:51:40	ga_s2bm_ard_3-2-1_50KPU_2017-09-29_final.stac-item
2017-09-29 11:51:40	ga_s2bm_ard_3-2-1_50KQU_2017-09-29_final.stac-item
2017-09-30 09:40:53	ga_s2bm_ard_3-2-1_56KKU_2017-09-30_final.stac-item
2017-09-30 09:40:53	ga_s2bm_ard_3-2-1_56KLU_2017-09-30_final.stac-item
2017-09-30 09:40:53	ga_s2bm_ard_3-2-1_55JHN_2017-09-30_final.stac-item
2017-09-30 09:40:53	ga_s2bm_ard_3-2-1_55KFP_2017-09-30_final.stac-item
2017-09-30 09:40:53	ga_s2bm_ard_3-2-1_55KGP_2017-09-30_final.stac-item
2017-09-30 09:40:53	ga_s2bm_ard_3-2-1_55KHP_2017-09-30_final.stac-item
2017-10-04 11:02:43	ga_s2bm_ard_3-2-1_52KDU_2017-10-04_final.stac-item
2017-10-04 11:02:43	ga_s2bm_ard_3-2-1_52KEU_2017-10-04_final.stac-item
2017-10-04 11:02:43	ga_s2bm_ard_3-2-1_52KFU_2017-10-04_final.stac-item
2017-10-04 11:02:43	ga_s2bm_ard_3-2-1_52KGU_2017-10-04_final.stac-item
2017-10-15 10:31:57	ga_s2bm_ard_3-2-1_53KPP_2017-10-15_final.stac-item
2017-10-15 10:31:57	ga_s2bm_ard_3-2-1_54KTU_2017-10-15_final.stac-item
2017-10-15 10:31:57	ga_s2bm_ard_3-2-1_53KQP_2017-10-15_final.stac-item
2017-10-15 10:31:57	ga_s2bm_ard_3-2-1_54KUU_2017-10-15_final.stac-item
2017-10-15 10:31:57	ga_s2bm_ard_3-2-1_53KRP_2017-10-15_final.stac-item
2023-09-21 10:23:43	ga_s2bm_ard_3-2-1_54KWU_2023-09-21_final
2023-09-21 10:23:47	ga_s2bm_ard_3-2-1_54KVU_2023-09-21_final
2023-09-21 10:23:50	ga_s2bm_ard_3-2-1_54KUU_2023-09-21_final
2023-09-21 10:23:54	ga_s2bm_ard_3-2-1_53KRP_2023-09-21_final
2023-09-21 10:24:07	ga_s2bm_ard_3-2-1_53JRN_2023-09-21_final
2023-09-30 10:53:51	ga_s2bm_ard_3-2-1_53KMP_2023-09-30_final
2023-09-30 10:53:56	ga_s2bm_ard_3-2-1_53KLP_2023-09-30_final
2023-09-30 10:53:59	ga_s2bm_ard_3-2-1_53KKP_2023-09-30_final
2023-09-30 10:53:59	ga_s2bm_ard_3-2-1_52KHU_2023-09-30_final
2023-09-30 10:54:03	ga_s2bm_ard_3-2-1_52KGU_2023-09-30_final
2023-09-30 10:54:13	ga_s2bm_ard_3-2-1_52JHT_2023-09-30_final
2023-10-02 11:34:07	ga_s2bm_ard_3-2-1_51KXP_2023-10-02_final
2023-10-02 11:34:12	ga_s2bm_ard_3-2-1_51KWP_2023-10-02_final
2023-10-02 11:34:16	ga_s2bm_ard_3-2-1_51KVP_2023-10-02_final
2023-10-02 11:34:19	ga_s2bm_ard_3-2-1_51KUP_2023-10-02_final
2023-10-03 11:03:57	ga_s2bm_ard_3-2-1_52KGU_2023-10-03_final
2023-10-03 11:04:01	ga_s2bm_ard_3-2-1_52KFU_2023-10-03_final
2023-10-03 11:04:04	ga_s2bm_ard_3-2-1_52KEU_2023-10-03_final
2023-10-03 11:04:08	ga_s2bm_ard_3-2-1_52KDU_2023-10-03_final
2023-10-04 10:33:41	ga_s2bm_ard_3-2-1_54KUU_2023-10-04_final
2023-10-04 10:33:46	ga_s2bm_ard_3-2-1_54KTU_2023-10-04_final
2023-10-04 10:33:46	ga_s2bm_ard_3-2-1_53KRP_2023-10-04_final
2023-10-04 10:33:50	ga_s2bm_ard_3-2-1_53KQP_2023-10-04_final
2023-10-04 10:33:53	ga_s2bm_ard_3-2-1_53KPP_2023-10-04_final
2023-10-04 10:34:00	ga_s2bm_ard_3-2-1_53JRN_2023-10-04_final
2023-10-05 10:03:31	ga_s2bm_ard_3-2-1_55KDP_2023-10-05_final
2023-10-05 10:03:35	ga_s2bm_ard_3-2-1_55KCP_2023-10-05_final
2023-10-05 10:03:38	ga_s2bm_ard_3-2-1_55KBP_2023-10-05_final
2023-10-05 10:03:38	ga_s2bm_ard_3-2-1_54KZU_2023-10-05_final
2023-10-05 10:03:43	ga_s2bm_ard_3-2-1_54KYU_2023-10-05_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