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
2023-09-24 10:32:00	ga_s2bm_ard_3-2-1_54KVF_2023-09-24_final
2023-09-24 10:32:04	ga_s2bm_ard_3-2-1_54KUF_2023-09-24_final
2023-09-24 10:32:07	ga_s2bm_ard_3-2-1_54KTF_2023-09-24_final
2023-09-24 10:32:08	ga_s2bm_ard_3-2-1_53KRA_2023-09-24_final
2023-09-24 10:32:14	ga_s2bm_ard_3-2-1_53KQA_2023-09-24_final
2023-09-24 10:32:18	ga_s2bm_ard_3-2-1_54KUE_2023-09-24_final
2023-09-24 10:32:22	ga_s2bm_ard_3-2-1_54KTE_2023-09-24_final
2023-09-24 10:32:22	ga_s2bm_ard_3-2-1_53KRV_2023-09-24_final
2023-09-24 10:32:26	ga_s2bm_ard_3-2-1_53KQV_2023-09-24_final
2023-09-25 10:01:46	ga_s2bm_ard_3-2-1_55KFA_2023-09-25_final
2023-09-25 10:01:50	ga_s2bm_ard_3-2-1_55KEA_2023-09-25_nrt
2023-09-25 10:01:53	ga_s2bm_ard_3-2-1_55KDA_2023-09-25_final
2023-09-25 10:01:56	ga_s2bm_ard_3-2-1_55KCA_2023-09-25_final
2023-09-29 11:22:21	ga_s2bm_ard_3-2-1_52KCF_2023-09-29_final
2023-09-29 11:22:25	ga_s2bm_ard_3-2-1_52KBF_2023-09-29_final
2023-09-29 11:22:26	ga_s2bm_ard_3-2-1_51KZA_2023-09-29_final
2023-09-29 11:22:29	ga_s2bm_ard_3-2-1_51KYA_2023-09-29_final
2023-09-29 11:22:36	ga_s2bm_ard_3-2-1_52KCE_2023-09-29_final
2023-09-29 11:22:40	ga_s2bm_ard_3-2-1_52KBE_2023-09-29_final
2023-09-29 11:22:40	ga_s2bm_ard_3-2-1_51KZV_2023-09-29_final
2023-09-29 11:22:44	ga_s2bm_ard_3-2-1_51KYV_2023-09-29_final
2023-10-02 09:51:41	ga_s2bm_ard_3-2-1_56KKF_2023-10-02_final
2023-10-02 09:51:42	ga_s2bm_ard_3-2-1_55KHA_2023-10-02_interim.stac-item
2023-10-02 09:51:46	ga_s2bm_ard_3-2-1_55KGA_2023-10-02_nrt
2023-10-02 09:51:49	ga_s2bm_ard_3-2-1_55KFA_2023-10-02_final
2023-10-02 09:51:55	ga_s2bm_ard_3-2-1_55KEA_2023-10-02_interim.stac-item
2023-10-02 09:51:56	ga_s2bm_ard_3-2-1_56KKE_2023-10-02_nrt
2023-10-02 09:51:57	ga_s2bm_ard_3-2-1_55KHV_2023-10-02_nrt
2023-10-02 09:52:00	ga_s2bm_ard_3-2-1_55KGV_2023-10-02_interim.stac-item
2023-10-02 09:52:04	ga_s2bm_ard_3-2-1_55KFV_2023-10-02_nrt
2023-10-02 11:32:23	ga_s2bm_ard_3-2-1_51KYA_2023-10-02_final
2023-10-02 11:32:27	ga_s2bm_ard_3-2-1_51KXA_2023-10-02_final
2023-10-02 11:32:30	ga_s2bm_ard_3-2-1_51KWA_2023-10-02_final
2023-10-02 11:32:34	ga_s2bm_ard_3-2-1_51KVA_2023-10-02_final
2023-10-02 11:32:38	ga_s2bm_ard_3-2-1_51KYV_2023-10-02_final
2023-10-02 11:32:42	ga_s2bm_ard_3-2-1_51KXV_2023-10-02_final
2023-10-03 11:02:11	ga_s2bm_ard_3-2-1_53KKA_2023-10-03_final
2023-10-03 11:02:13	ga_s2bm_ard_3-2-1_52KHF_2023-10-03_final
2023-10-03 11:02:16	ga_s2bm_ard_3-2-1_52KGF_2023-10-03_final
2023-10-03 11:02:19	ga_s2bm_ard_3-2-1_52KFF_2023-10-03_final
2023-10-03 11:02:26	ga_s2bm_ard_3-2-1_53KKV_2023-10-03_final
2023-10-03 11:02:27	ga_s2bm_ard_3-2-1_52KHE_2023-10-03_final
2023-10-03 11:02:30	ga_s2bm_ard_3-2-1_52KGE_2023-10-03_final
2023-10-03 11:02:33	ga_s2bm_ard_3-2-1_52KFE_2023-10-03_final
2023-10-04 10:31:57	ga_s2bm_ard_3-2-1_54KVF_2023-10-04_final
2023-10-04 10:32:04	ga_s2bm_ard_3-2-1_54KTF_2023-10-04_final
2023-10-04 10:32:05	ga_s2bm_ard_3-2-1_53KRA_2023-10-04_final
2023-10-04 10:32:11	ga_s2bm_ard_3-2-1_53KQA_2023-10-04_final
2023-10-04 10:32:19	ga_s2bm_ard_3-2-1_54KTE_2023-10-04_final
2023-10-04 10:32:19	ga_s2bm_ard_3-2-1_53KRV_2023-10-04_final
2023-10-04 10:32:23	ga_s2bm_ard_3-2-1_53KQV_2023-10-04_final
2023-10-05 10:01:43	ga_s2bm_ard_3-2-1_55KFA_2023-10-05_final
2023-10-05 10:01:47	ga_s2bm_ard_3-2-1_55KEA_2023-10-05_nrt
2023-10-05 10:01:50	ga_s2bm_ard_3-2-1_55KDA_2023-10-05_final
2023-10-05 10:01:53	ga_s2bm_ard_3-2-1_55KCA_2023-10-05_final
2023-10-09 11:22:20	ga_s2bm_ard_3-2-1_52KCF_2023-10-09_final
2023-10-09 11:22:24	ga_s2bm_ard_3-2-1_52KBF_2023-10-09_final
2023-10-09 11:22:25	ga_s2bm_ard_3-2-1_51KZA_2023-10-09_final
2023-10-09 11:22:28	ga_s2bm_ard_3-2-1_51KYA_2023-10-09_final
2023-10-09 11:22:35	ga_s2bm_ard_3-2-1_52KCE_2023-10-09_final
2023-10-09 11:22:38	ga_s2bm_ard_3-2-1_52KBE_2023-10-09_final
2023-10-09 11:22:39	ga_s2bm_ard_3-2-1_51KZV_2023-10-09_final
2023-10-09 11:22:42	ga_s2bm_ard_3-2-1_51KYV_2023-10-09_final
2023-10-10 10:52:07	ga_s2bm_ard_3-2-1_53KNA_2023-10-10_final
2023-10-10 10:52:10	ga_s2bm_ard_3-2-1_53KMA_2023-10-10_final
2023-10-10 10:52:13	ga_s2bm_ard_3-2-1_53KLA_2023-10-10_final
2023-10-10 10:52:16	ga_s2bm_ard_3-2-1_53KKA_2023-10-10_final
2023-10-10 10:52:21	ga_s2bm_ard_3-2-1_52KHF_2023-10-10_final
2023-10-10 10:52:28	ga_s2bm_ard_3-2-1_53KLV_2023-10-10_final
2023-10-10 10:52:31	ga_s2bm_ard_3-2-1_53KKV_2023-10-10_final
2023-10-10 10:52:32	ga_s2bm_ard_3-2-1_52KHE_2023-10-10_final
2023-10-11 10:21:53	ga_s2bm_ard_3-2-1_54KYF_2023-10-11_final
2023-10-11 10:21:57	ga_s2bm_ard_3-2-1_54KXF_2023-10-11_final
2023-10-11 10:22:00	ga_s2bm_ard_3-2-1_54KWF_2023-10-11_final
2023-10-11 10:22:03	ga_s2bm_ard_3-2-1_54KVF_2023-10-11_final
2023-10-11 10:22:05	ga_s2bm_ard_3-2-1_54KYE_2023-10-11_final
2023-10-11 10:22:11	ga_s2bm_ard_3-2-1_54KXE_2023-10-11_final
2023-10-12 09:51:42	ga_s2bm_ard_3-2-1_56KKF_2023-10-12_final
2023-10-12 09:51:42	ga_s2bm_ard_3-2-1_55KHA_2023-10-12_nrt
2023-10-12 09:51:46	ga_s2bm_ard_3-2-1_55KGA_2023-10-12_nrt
2023-10-12 09:51:50	ga_s2bm_ard_3-2-1_55KFA_2023-10-12_final
2023-10-12 09:51:55	ga_s2bm_ard_3-2-1_55KEA_2023-10-12_nrt
2023-10-12 09:51:56	ga_s2bm_ard_3-2-1_56KKE_2023-10-12_nrt
2023-10-12 09:51:57	ga_s2bm_ard_3-2-1_55KHV_2023-10-12_nrt
2023-10-12 09:52:01	ga_s2bm_ard_3-2-1_55KGV_2023-10-12_nrt
2023-10-12 09:52:04	ga_s2bm_ard_3-2-1_55KFV_2023-10-12_nrt
2023-10-12 11:32:24	ga_s2bm_ard_3-2-1_51KYA_2023-10-12_final
2023-12-29 10:52:07	ga_s2bm_ard_3-2-1_53KNA_2023-12-29_final
2023-12-29 10:52:10	ga_s2bm_ard_3-2-1_53KMA_2023-12-29_final
2023-12-29 10:52:13	ga_s2bm_ard_3-2-1_53KLA_2023-12-29_final
2023-12-29 10:52:16	ga_s2bm_ard_3-2-1_53KKA_2023-12-29_final
2023-12-29 10:52:21	ga_s2bm_ard_3-2-1_52KHF_2023-12-29_final
2023-12-29 10:52:28	ga_s2bm_ard_3-2-1_53KLV_2023-12-29_final
2023-12-29 10:52:31	ga_s2bm_ard_3-2-1_53KKV_2023-12-29_final
2023-12-29 10:52:32	ga_s2bm_ard_3-2-1_52KHE_2023-12-29_final
2023-12-30 10:21:52	ga_s2bm_ard_3-2-1_54KYF_2023-12-30_final
2023-12-30 10:21:56	ga_s2bm_ard_3-2-1_54KXF_2023-12-30_final
2023-12-30 10:22:00	ga_s2bm_ard_3-2-1_54KWF_2023-12-30_final
2023-12-30 10:22:03	ga_s2bm_ard_3-2-1_54KVF_2023-12-30_final
2023-12-30 10:22:05	ga_s2bm_ard_3-2-1_54KYE_2023-12-30_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