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
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53HLD_2017-08-09_final.stac-item
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53HLE_2017-08-09_final.stac-item
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53JLF_2017-08-09_final.stac-item
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53JLG_2017-08-09_final.stac-item
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53JLH_2017-08-09_final.stac-item
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53JLJ_2017-08-09_final.stac-item
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53JLK_2017-08-09_final.stac-item
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53JLL_2017-08-09_final.stac-item
2017-08-09 10:43:05	ga_s2bm_ard_3-2-1_53JLM_2017-08-09_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53JKN_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53JLN_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KKP_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KKQ_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KKR_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KKS_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KKT_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KKU_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KKV_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KLP_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KLQ_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KLR_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KLS_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KLT_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KLU_2017-08-12_final.stac-item
2017-08-12 10:52:15	ga_s2bm_ard_3-2-1_53KLV_2017-08-12_final.stac-item
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53HLD_2018-02-15_final.stac-item
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53HLE_2018-02-15_final.stac-item
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53JLF_2018-02-15_final.stac-item
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53JLG_2018-02-15_final.stac-item
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53JLH_2018-02-15_final.stac-item
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53JLJ_2018-02-15_final.stac-item
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53JLK_2018-02-15_final.stac-item
2018-02-15 10:37:20	ga_s2bm_ard_3-2-1_53JLL_2018-02-15_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KKA_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KKB_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KKR_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KKS_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KKT_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KKU_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KKV_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KLA_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KLB_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KLR_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KLS_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KLT_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KLU_2018-02-18_final.stac-item
2018-02-18 10:47:17	ga_s2bm_ard_3-2-1_53KLV_2018-02-18_final.stac-item
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53JLH_2018-06-05_final.stac-item
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53JLJ_2018-06-05_final.stac-item
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53JLK_2018-06-05_final.stac-item
2018-06-05 10:37:24	ga_s2bm_ard_3-2-1_53JLL_2018-06-05_final.stac-item
2018-06-05 10:45:09	ga_s2bm_ard_3-2-1_53HLD_2018-06-05_final.stac-item
2018-06-05 10:45:09	ga_s2bm_ard_3-2-1_53HLE_2018-06-05_final.stac-item
2018-06-05 10:45:09	ga_s2bm_ard_3-2-1_53JLF_2018-06-05_final.stac-item
2018-06-05 10:45:09	ga_s2bm_ard_3-2-1_53JLG_2018-06-05_final.stac-item
2018-06-05 10:45:09	ga_s2bm_ard_3-2-1_53JLH_2018-06-05_final.stac-item
2018-06-05 10:45:09	ga_s2bm_ard_3-2-1_53JLJ_2018-06-05_final.stac-item
2018-06-08 10:54:57	ga_s2bm_ard_3-2-1_53JLJ_2018-06-08_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53KKA_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53KKB_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53KLA_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53KLB_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53LKC_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53LKD_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53LKE_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53LKF_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53LKG_2018-06-11_final.stac-item
2018-06-11 10:58:30	ga_s2bm_ard_3-2-1_53LKH_2018-06-11_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53JKN_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53JLJ_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53JLK_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53JLL_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53JLM_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53JLN_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKA_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKB_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKP_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKQ_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKR_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKS_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKT_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKU_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KKV_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLA_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLB_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLP_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLQ_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLR_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLS_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLT_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLU_2018-06-18_final.stac-item
2018-06-18 10:47:23	ga_s2bm_ard_3-2-1_53KLV_2018-06-18_final.stac-item
2018-06-18 10:54:54	ga_s2bm_ard_3-2-1_53JLJ_2018-06-18_final.stac-item
2018-06-18 10:54:54	ga_s2bm_ard_3-2-1_53JLK_2018-06-18_final.stac-item
2018-06-21 10:59:06	ga_s2bm_ard_3-2-1_53KKA_2018-06-21_final.stac-item
2019-08-22 10:54:13	ga_s2bm_ard_3-2-1_53JLN_2019-08-22_final.stac-item
2019-08-22 10:54:17	ga_s2bm_ard_3-2-1_53JKN_2019-08-22_final.stac-item
2019-08-22 10:54:28	ga_s2bm_ard_3-2-1_53JLM_2019-08-22_final.stac-item
2019-08-22 10:54:43	ga_s2bm_ard_3-2-1_53JLL_2019-08-22_final.stac-item
2019-08-22 10:54:57	ga_s2bm_ard_3-2-1_53JLK_2019-08-22_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

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