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
2019-07-02 09:48:07	ga_s2bm_ard_3-2-1_55GER_2019-07-02_final.stac-item
2019-07-02 09:48:10	ga_s2bm_ard_3-2-1_55GDR_2019-07-02_final.stac-item
2019-07-02 09:48:14	ga_s2bm_ard_3-2-1_55GCR_2019-07-02_final.stac-item
2019-07-02 09:48:17	ga_s2bm_ard_3-2-1_55GBR_2019-07-02_final.stac-item
2019-07-02 09:48:17	ga_s2bm_ard_3-2-1_54GYA_2019-07-02_final.stac-item
2019-07-02 09:48:28	ga_s2bm_ard_3-2-1_55GCQ_2019-07-02_final.stac-item
2019-07-12 09:48:07	ga_s2bm_ard_3-2-1_55GER_2019-07-12_final.stac-item
2019-07-12 09:48:11	ga_s2bm_ard_3-2-1_55GDR_2019-07-12_final.stac-item
2019-07-25 09:58:13	ga_s2bm_ard_3-2-1_55GBR_2019-07-25_final.stac-item
2019-07-25 09:58:14	ga_s2bm_ard_3-2-1_54GYA_2019-07-25_final.stac-item
2019-07-25 09:58:22	ga_s2bm_ard_3-2-1_55GCQ_2019-07-25_final.stac-item
2019-10-14 09:28:02	ga_s2bm_ard_3-2-1_55GFR_2019-10-13_final.stac-item
2019-10-14 09:28:17	ga_s2bm_ard_3-2-1_55GFQ_2019-10-13_final.stac-item
2019-10-17 09:37:59	ga_s2bm_ard_3-2-1_55GFR_2019-10-17_final.stac-item
2019-10-17 09:38:03	ga_s2bm_ard_3-2-1_55GER_2019-10-17_final.stac-item
2019-10-17 09:38:06	ga_s2bm_ard_3-2-1_55GDR_2019-10-17_final.stac-item
2019-10-17 09:38:13	ga_s2bm_ard_3-2-1_55GFQ_2019-10-17_final.stac-item
2019-10-20 09:47:59	ga_s2bm_ard_3-2-1_55GER_2019-10-20_final.stac-item
2019-10-20 09:48:03	ga_s2bm_ard_3-2-1_55GDR_2019-10-20_final.stac-item
2019-10-20 09:48:06	ga_s2bm_ard_3-2-1_55GCR_2019-10-20_final.stac-item
2019-10-20 09:48:10	ga_s2bm_ard_3-2-1_55GBR_2019-10-20_final.stac-item
2019-10-20 09:48:10	ga_s2bm_ard_3-2-1_54GYA_2019-10-20_final.stac-item
2019-10-20 09:48:21	ga_s2bm_ard_3-2-1_55GCQ_2019-10-20_final.stac-item
2019-10-24 09:28:02	ga_s2bm_ard_3-2-1_55GFR_2019-10-23_final.stac-item
2019-10-24 09:28:17	ga_s2bm_ard_3-2-1_55GFQ_2019-10-23_final.stac-item
2019-10-27 09:37:59	ga_s2bm_ard_3-2-1_55GFR_2019-10-27_final.stac-item
2019-10-27 09:38:03	ga_s2bm_ard_3-2-1_55GER_2019-10-27_final.stac-item
2019-10-27 09:38:06	ga_s2bm_ard_3-2-1_55GDR_2019-10-27_final.stac-item
2019-10-27 09:38:13	ga_s2bm_ard_3-2-1_55GFQ_2019-10-27_final.stac-item
2019-10-30 09:47:59	ga_s2bm_ard_3-2-1_55GER_2019-10-30_final.stac-item
2019-10-30 09:48:03	ga_s2bm_ard_3-2-1_55GDR_2019-10-30_final.stac-item
2019-10-30 09:48:06	ga_s2bm_ard_3-2-1_55GCR_2019-10-30_final.stac-item
2019-10-30 09:48:09	ga_s2bm_ard_3-2-1_55GBR_2019-10-30_final.stac-item
2019-10-30 09:48:09	ga_s2bm_ard_3-2-1_54GYA_2019-10-30_final.stac-item
2019-10-30 09:48:20	ga_s2bm_ard_3-2-1_55GCQ_2019-10-30_final.stac-item
2019-11-02 09:58:01	ga_s2bm_ard_3-2-1_55GCR_2019-11-02_final.stac-item
2019-11-02 09:58:05	ga_s2bm_ard_3-2-1_55GBR_2019-11-02_final.stac-item
2019-11-02 09:58:06	ga_s2bm_ard_3-2-1_54GYA_2019-11-02_final.stac-item
2019-11-02 09:58:14	ga_s2bm_ard_3-2-1_55GCQ_2019-11-02_final.stac-item
2019-11-03 09:28:02	ga_s2bm_ard_3-2-1_55GFR_2019-11-02_final.stac-item
2019-11-03 09:28:16	ga_s2bm_ard_3-2-1_55GFQ_2019-11-02_final.stac-item
2019-11-12 09:58:00	ga_s2bm_ard_3-2-1_55GCR_2019-11-12_final.stac-item
2019-11-12 09:58:04	ga_s2bm_ard_3-2-1_55GBR_2019-11-12_final.stac-item
2019-11-12 09:58:04	ga_s2bm_ard_3-2-1_54GYA_2019-11-12_final.stac-item
2019-11-12 09:58:13	ga_s2bm_ard_3-2-1_55GCQ_2019-11-12_final.stac-item
2019-11-22 09:57:58	ga_s2bm_ard_3-2-1_55GCR_2019-11-22_final.stac-item
2019-11-22 09:58:02	ga_s2bm_ard_3-2-1_55GBR_2019-11-22_final.stac-item
2019-11-22 09:58:02	ga_s2bm_ard_3-2-1_54GYA_2019-11-22_final.stac-item
2019-11-22 09:58:11	ga_s2bm_ard_3-2-1_55GCQ_2019-11-22_final.stac-item
2019-11-23 09:27:58	ga_s2bm_ard_3-2-1_55GFR_2019-11-22_final.stac-item
2019-11-23 09:28:13	ga_s2bm_ard_3-2-1_55GFQ_2019-11-22_final.stac-item
2019-12-02 09:57:56	ga_s2bm_ard_3-2-1_55GCR_2019-12-02_final.stac-item
2023-09-02 09:58:06	ga_s2bm_ard_3-2-1_55GCR_2023-09-02_final
2023-09-02 09:58:10	ga_s2bm_ard_3-2-1_55GBR_2023-09-02_final
2023-09-02 09:58:10	ga_s2bm_ard_3-2-1_54GYA_2023-09-02_final
2023-09-02 09:58:14	ga_s2bm_ard_3-2-1_54GXA_2023-09-02_nrt
2023-09-02 09:58:18	ga_s2bm_ard_3-2-1_54GWA_2023-09-02_nrt
2023-09-02 09:58:18	ga_s2bm_ard_3-2-1_55GCQ_2023-09-02_final
2023-09-02 09:58:24	ga_s2bm_ard_3-2-1_55GBQ_2023-09-02_final
2023-09-02 09:58:24	ga_s2bm_ard_3-2-1_54GYV_2023-09-02_final
2023-09-02 09:58:28	ga_s2bm_ard_3-2-1_54GXV_2023-09-02_nrt
2023-09-03 09:27:55	ga_s2bm_ard_3-2-1_56GMA_2023-09-02_nrt
2023-09-03 09:27:59	ga_s2bm_ard_3-2-1_56GLA_2023-09-02_nrt
2023-09-03 09:28:02	ga_s2bm_ard_3-2-1_56GKA_2023-09-02_nrt
2023-09-03 09:28:02	ga_s2bm_ard_3-2-1_55GGR_2023-09-02_nrt
2023-09-03 09:28:06	ga_s2bm_ard_3-2-1_55GFR_2023-09-02_final
2023-09-03 09:28:13	ga_s2bm_ard_3-2-1_56GLV_2023-09-02_nrt
2023-09-03 09:28:17	ga_s2bm_ard_3-2-1_56GKV_2023-09-02_nrt
2023-09-03 09:28:17	ga_s2bm_ard_3-2-1_55GGQ_2023-09-02_nrt
2023-09-03 09:28:21	ga_s2bm_ard_3-2-1_55GFQ_2023-09-02_final
2023-09-16 09:37:57	ga_s2bm_ard_3-2-1_56GKA_2023-09-16_nrt
2023-09-16 09:37:57	ga_s2bm_ard_3-2-1_55GGR_2023-09-16_nrt
2023-09-16 09:38:01	ga_s2bm_ard_3-2-1_55GFR_2023-09-16_final
2023-09-16 09:38:05	ga_s2bm_ard_3-2-1_55GER_2023-09-16_final
2023-09-16 09:38:08	ga_s2bm_ard_3-2-1_55GDR_2023-09-16_final
2023-09-16 09:38:10	ga_s2bm_ard_3-2-1_56GKV_2023-09-16_nrt
2023-09-16 09:38:11	ga_s2bm_ard_3-2-1_55GGQ_2023-09-16_nrt
2023-09-16 09:38:15	ga_s2bm_ard_3-2-1_55GFQ_2023-09-16_final
2023-09-19 09:48:02	ga_s2bm_ard_3-2-1_55GER_2023-09-19_final
2023-09-19 09:48:05	ga_s2bm_ard_3-2-1_55GDR_2023-09-19_final
2023-09-19 09:48:09	ga_s2bm_ard_3-2-1_55GCR_2023-09-19_final
2023-09-19 09:48:12	ga_s2bm_ard_3-2-1_55GBR_2023-09-19_final
2023-09-19 09:48:12	ga_s2bm_ard_3-2-1_54GYA_2023-09-19_final
2023-09-19 09:48:23	ga_s2bm_ard_3-2-1_55GCQ_2023-09-19_final
2023-09-19 09:48:27	ga_s2bm_ard_3-2-1_55GBQ_2023-09-19_final
2023-09-19 09:48:27	ga_s2bm_ard_3-2-1_54GYV_2023-09-19_final
2023-10-13 09:27:52	ga_s2bm_ard_3-2-1_56GMA_2023-10-12_nrt
2023-10-13 09:27:56	ga_s2bm_ard_3-2-1_56GLA_2023-10-12_nrt
2023-10-13 09:27:59	ga_s2bm_ard_3-2-1_56GKA_2023-10-12_nrt
2023-10-13 09:28:00	ga_s2bm_ard_3-2-1_55GGR_2023-10-12_nrt
2023-10-13 09:28:03	ga_s2bm_ard_3-2-1_55GFR_2023-10-12_final
2023-10-13 09:28:11	ga_s2bm_ard_3-2-1_56GLV_2023-10-12_nrt
2023-10-13 09:28:14	ga_s2bm_ard_3-2-1_56GKV_2023-10-12_nrt
2023-10-13 09:28:14	ga_s2bm_ard_3-2-1_55GGQ_2023-10-12_nrt
2023-10-13 09:28:18	ga_s2bm_ard_3-2-1_55GFQ_2023-10-12_final
2023-10-16 09:37:56	ga_s2bm_ard_3-2-1_56GKA_2023-10-16_nrt
2023-10-16 09:37:56	ga_s2bm_ard_3-2-1_55GGR_2023-10-16_nrt
2023-10-16 09:38:00	ga_s2bm_ard_3-2-1_55GFR_2023-10-16_final
2023-10-16 09:38:04	ga_s2bm_ard_3-2-1_55GER_2023-10-16_final
2023-10-16 09:38:07	ga_s2bm_ard_3-2-1_55GDR_2023-10-16_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