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
2022-01-15 10:44:38	ga_s2bm_ard_3-2-1_53JLL_2022-01-15_final.stac-item
2022-01-15 10:44:52	ga_s2bm_ard_3-2-1_53JLK_2022-01-15_final.stac-item
2022-01-15 10:45:07	ga_s2bm_ard_3-2-1_53JLJ_2022-01-15_final.stac-item
2022-01-15 10:45:18	ga_s2bm_ard_3-2-1_53JLH_2022-01-15_final.stac-item
2022-01-15 10:45:25	ga_s2bm_ard_3-2-1_53JLH_2022-01-15_final.stac-item
2022-01-15 10:45:36	ga_s2bm_ard_3-2-1_53JLG_2022-01-15_final.stac-item
2022-02-10 11:00:08	ga_s2bm_ard_3-2-1_53LKJ_2022-02-10_final
2022-02-10 11:00:23	ga_s2bm_ard_3-2-1_53LKH_2022-02-10_final.stac-item
2022-02-10 11:00:37	ga_s2bm_ard_3-2-1_53LKG_2022-02-10_final.stac-item
2022-02-10 11:00:52	ga_s2bm_ard_3-2-1_53LKF_2022-02-10_final.stac-item
2022-02-10 11:01:07	ga_s2bm_ard_3-2-1_53LKE_2022-02-10_final.stac-item
2022-02-10 11:01:21	ga_s2bm_ard_3-2-1_53LKD_2022-02-10_final.stac-item
2022-02-10 11:01:36	ga_s2bm_ard_3-2-1_53LKC_2022-02-10_final.stac-item
2022-02-10 11:01:50	ga_s2bm_ard_3-2-1_53KKB_2022-02-10_final.stac-item
2022-02-10 11:01:58	ga_s2bm_ard_3-2-1_53KLA_2022-02-10_final.stac-item
2022-02-10 11:02:04	ga_s2bm_ard_3-2-1_53KKA_2022-02-10_final.stac-item
2022-02-17 10:51:55	ga_s2bm_ard_3-2-1_53KKB_2022-02-17_final.stac-item
2022-02-17 10:52:05	ga_s2bm_ard_3-2-1_53KLA_2022-02-17_final.stac-item
2022-02-17 10:52:08	ga_s2bm_ard_3-2-1_53KKA_2022-02-17_final.stac-item
2022-02-17 10:52:14	ga_s2bm_ard_3-2-1_53KLV_2022-02-17_final.stac-item
2022-02-17 10:52:15	ga_s2bm_ard_3-2-1_53KKA_2022-02-17_final.stac-item
2022-02-17 10:52:16	ga_s2bm_ard_3-2-1_53KKV_2022-02-17_final.stac-item
2022-02-17 10:52:21	ga_s2bm_ard_3-2-1_53KLV_2022-02-17_final.stac-item
2022-02-17 10:52:23	ga_s2bm_ard_3-2-1_53KKV_2022-02-17_final.stac-item
2022-02-17 10:52:35	ga_s2bm_ard_3-2-1_53KLU_2022-02-17_final.stac-item
2022-02-17 10:52:38	ga_s2bm_ard_3-2-1_53KKU_2022-02-17_final.stac-item
2022-02-17 10:52:49	ga_s2bm_ard_3-2-1_53KLT_2022-02-17_final.stac-item
2022-02-17 10:52:52	ga_s2bm_ard_3-2-1_53KKT_2022-02-17_final.stac-item
2022-02-17 10:53:04	ga_s2bm_ard_3-2-1_53KLS_2022-02-17_final.stac-item
2022-02-17 10:53:07	ga_s2bm_ard_3-2-1_53KKS_2022-02-17_final.stac-item
2022-02-17 10:53:18	ga_s2bm_ard_3-2-1_53KLR_2022-02-17_final.stac-item
2022-02-17 10:53:21	ga_s2bm_ard_3-2-1_53KKR_2022-02-17_final.stac-item
2022-02-17 10:53:33	ga_s2bm_ard_3-2-1_53KLQ_2022-02-17_final.stac-item
2022-02-17 10:53:36	ga_s2bm_ard_3-2-1_53KKQ_2022-02-17_final.stac-item
2022-02-20 11:00:08	ga_s2bm_ard_3-2-1_53LKJ_2022-02-20_final
2022-02-20 11:00:23	ga_s2bm_ard_3-2-1_53LKH_2022-02-20_final.stac-item
2022-02-20 11:00:37	ga_s2bm_ard_3-2-1_53LKG_2022-02-20_final.stac-item
2022-02-20 11:00:52	ga_s2bm_ard_3-2-1_53LKF_2022-02-20_final.stac-item
2022-02-20 11:01:01	ga_s2bm_ard_3-2-1_53LKE_2022-02-20_final.stac-item
2022-02-20 11:01:08	ga_s2bm_ard_3-2-1_53LKE_2022-02-20_final.stac-item
2022-02-20 11:01:21	ga_s2bm_ard_3-2-1_53LKD_2022-02-20_final.stac-item
2022-02-20 11:01:36	ga_s2bm_ard_3-2-1_53LKC_2022-02-20_final.stac-item
2022-02-20 11:01:50	ga_s2bm_ard_3-2-1_53KKB_2022-02-20_final.stac-item
2022-02-20 11:02:04	ga_s2bm_ard_3-2-1_53KKA_2022-02-20_final.stac-item
2022-02-24 10:44:37	ga_s2bm_ard_3-2-1_53JLL_2022-02-24_final.stac-item
2022-02-24 10:44:50	ga_s2bm_ard_3-2-1_53JLK_2022-02-24_final.stac-item
2022-02-24 10:44:56	ga_s2bm_ard_3-2-1_53JLK_2022-02-24_final.stac-item
2022-02-24 10:45:06	ga_s2bm_ard_3-2-1_53JLJ_2022-02-24_final.stac-item
2022-02-24 10:45:21	ga_s2bm_ard_3-2-1_53JLH_2022-02-24_final.stac-item
2022-02-24 10:45:36	ga_s2bm_ard_3-2-1_53JLG_2022-02-24_final.stac-item
2022-02-24 10:45:50	ga_s2bm_ard_3-2-1_53JLF_2022-02-24_final.stac-item
2022-03-12 11:00:27	ga_s2bm_ard_3-2-1_53LKH_2022-03-12_final.stac-item
2022-03-12 11:00:41	ga_s2bm_ard_3-2-1_53LKG_2022-03-12_final.stac-item
2022-03-12 11:00:56	ga_s2bm_ard_3-2-1_53LKF_2022-03-12_final.stac-item
2022-03-12 11:01:03	ga_s2bm_ard_3-2-1_53LKF_2022-03-12_final.stac-item
2022-03-12 11:01:03	ga_s2bm_ard_3-2-1_53LKE_2022-03-12_final.stac-item
2022-03-12 11:01:10	ga_s2bm_ard_3-2-1_53LKE_2022-03-12_final.stac-item
2022-03-12 11:01:25	ga_s2bm_ard_3-2-1_53LKD_2022-03-12_final.stac-item
2022-03-12 11:01:39	ga_s2bm_ard_3-2-1_53LKC_2022-03-12_final.stac-item
2022-03-12 11:01:54	ga_s2bm_ard_3-2-1_53KKB_2022-03-12_final.stac-item
2022-03-12 11:02:08	ga_s2bm_ard_3-2-1_53KKA_2022-03-12_final.stac-item
2022-03-16 10:44:40	ga_s2bm_ard_3-2-1_53JLL_2022-03-16_final.stac-item
2022-03-16 10:44:53	ga_s2bm_ard_3-2-1_53JLK_2022-03-16_final.stac-item
2022-03-16 10:44:59	ga_s2bm_ard_3-2-1_53JLK_2022-03-16_final.stac-item
2022-03-16 10:45:09	ga_s2bm_ard_3-2-1_53JLJ_2022-03-16_final.stac-item
2022-03-16 10:45:24	ga_s2bm_ard_3-2-1_53JLH_2022-03-16_final.stac-item
2022-03-16 10:45:38	ga_s2bm_ard_3-2-1_53JLG_2022-03-16_final.stac-item
2022-03-16 10:45:53	ga_s2bm_ard_3-2-1_53JLF_2022-03-16_final.stac-item
2022-03-16 10:46:07	ga_s2bm_ard_3-2-1_53HLE_2022-03-16_final.stac-item
2022-03-16 10:46:22	ga_s2bm_ard_3-2-1_53HLD_2022-03-16_final.stac-item
2022-03-26 10:44:39	ga_s2bm_ard_3-2-1_53JLL_2022-03-26_final.stac-item
2022-03-26 10:44:52	ga_s2bm_ard_3-2-1_53JLK_2022-03-26_final.stac-item
2022-03-26 10:44:59	ga_s2bm_ard_3-2-1_53JLK_2022-03-26_final.stac-item
2022-03-26 10:45:08	ga_s2bm_ard_3-2-1_53JLJ_2022-03-26_final.stac-item
2022-03-26 10:45:23	ga_s2bm_ard_3-2-1_53JLH_2022-03-26_final.stac-item
2022-03-26 10:45:38	ga_s2bm_ard_3-2-1_53JLG_2022-03-26_final.stac-item
2022-03-26 10:45:52	ga_s2bm_ard_3-2-1_53JLF_2022-03-26_final.stac-item
2022-03-26 10:46:07	ga_s2bm_ard_3-2-1_53HLE_2022-03-26_final.stac-item
2022-03-26 10:46:21	ga_s2bm_ard_3-2-1_53HLD_2022-03-26_final.stac-item
2022-05-21 11:00:14	ga_s2bm_ard_3-2-1_53LKJ_2022-05-21_final
2022-05-21 11:00:29	ga_s2bm_ard_3-2-1_53LKH_2022-05-21_final.stac-item
2022-05-21 11:00:43	ga_s2bm_ard_3-2-1_53LKG_2022-05-21_final.stac-item
2022-05-21 11:00:58	ga_s2bm_ard_3-2-1_53LKF_2022-05-21_final.stac-item
2022-05-21 11:01:05	ga_s2bm_ard_3-2-1_53LKF_2022-05-21_final.stac-item
2022-05-21 11:01:05	ga_s2bm_ard_3-2-1_53LKE_2022-05-21_final.stac-item
2022-05-21 11:01:12	ga_s2bm_ard_3-2-1_53LKE_2022-05-21_final.stac-item
2022-05-21 11:01:27	ga_s2bm_ard_3-2-1_53LKD_2022-05-21_final.stac-item
2022-05-21 11:01:41	ga_s2bm_ard_3-2-1_53LKC_2022-05-21_final.stac-item
2022-05-21 11:01:56	ga_s2bm_ard_3-2-1_53KKB_2022-05-21_final.stac-item
2022-05-21 11:02:10	ga_s2bm_ard_3-2-1_53KKA_2022-05-21_final.stac-item
2022-05-28 10:53:43	ga_s2bm_ard_3-2-1_53KKQ_2022-05-28_final.stac-item
2022-05-28 10:53:54	ga_s2bm_ard_3-2-1_53KLP_2022-05-28_final.stac-item
2022-05-28 10:53:57	ga_s2bm_ard_3-2-1_53KKP_2022-05-28_final.stac-item
2022-05-28 10:54:08	ga_s2bm_ard_3-2-1_53JLN_2022-05-28_final.stac-item
2022-05-28 10:54:12	ga_s2bm_ard_3-2-1_53JKN_2022-05-28_final.stac-item
2022-05-28 10:54:23	ga_s2bm_ard_3-2-1_53JLM_2022-05-28_final.stac-item
2022-05-28 10:54:38	ga_s2bm_ard_3-2-1_53JLL_2022-05-28_final.stac-item
2022-05-28 10:54:52	ga_s2bm_ard_3-2-1_53JLK_2022-05-28_final.stac-item
2022-05-28 10:55:00	ga_s2bm_ard_3-2-1_53JLK_2022-05-28_final.stac-item
2022-05-28 10:55:00	ga_s2bm_ard_3-2-1_53JLJ_2022-05-28_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