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
2019-05-31 10:41:54	ga_s2bm_ard_3-2-1_53KRB_2019-05-31_final
2019-05-31 10:42:06	ga_s2bm_ard_3-2-1_53KRA_2019-05-31_final.stac-item
2019-05-31 10:42:12	ga_s2bm_ard_3-2-1_53KRA_2019-05-31_final.stac-item
2019-05-31 10:42:21	ga_s2bm_ard_3-2-1_53KRV_2019-05-31_final.stac-item
2019-06-10 10:41:53	ga_s2bm_ard_3-2-1_53KRB_2019-06-10_final
2019-06-10 10:42:06	ga_s2bm_ard_3-2-1_53KRA_2019-06-10_final.stac-item
2019-06-10 10:42:12	ga_s2bm_ard_3-2-1_53KRA_2019-06-10_final.stac-item
2019-06-10 10:42:20	ga_s2bm_ard_3-2-1_53KRV_2019-06-10_final.stac-item
2023-05-20 10:40:09	ga_s2bm_ard_3-2-1_53LRJ_2023-05-20_nrt
2023-05-20 10:40:23	ga_s2bm_ard_3-2-1_53LRH_2023-05-20_nrt
2023-05-20 10:40:38	ga_s2bm_ard_3-2-1_53LRG_2023-05-20_nrt
2023-05-20 10:40:56	ga_s2bm_ard_3-2-1_53LRF_2023-05-20_nrt
2023-05-20 10:41:07	ga_s2bm_ard_3-2-1_53LRE_2023-05-20_nrt
2023-05-20 10:41:21	ga_s2bm_ard_3-2-1_53LRD_2023-05-20_nrt
2023-05-20 10:41:50	ga_s2bm_ard_3-2-1_53KRB_2023-05-20_final
2023-05-20 10:42:04	ga_s2bm_ard_3-2-1_53KRA_2023-05-20_final
2023-05-20 10:42:17	ga_s2bm_ard_3-2-1_53KRV_2023-05-20_final
2023-05-21 10:17:37	ga_s2bm_ard_3-2-1_54HTD_2023-05-21_nrt
2023-05-21 10:17:44	ga_s2bm_ard_3-2-1_54HTC_2023-05-21_nrt
2023-05-21 10:17:45	ga_s2bm_ard_3-2-1_53HQT_2023-05-21_nrt
2023-05-24 10:24:44	ga_s2bm_ard_3-2-1_53JQL_2023-05-24_final
2023-05-24 10:24:53	ga_s2bm_ard_3-2-1_54JTQ_2023-05-24_final
2023-05-24 10:24:56	ga_s2bm_ard_3-2-1_53JQK_2023-05-24_final
2023-05-24 10:25:08	ga_s2bm_ard_3-2-1_54JTP_2023-05-24_final
2023-05-24 10:25:10	ga_s2bm_ard_3-2-1_53JQJ_2023-05-24_final
2023-05-24 10:25:22	ga_s2bm_ard_3-2-1_54JTN_2023-05-24_final
2023-05-24 10:25:25	ga_s2bm_ard_3-2-1_53JQH_2023-05-24_final
2023-05-24 10:25:37	ga_s2bm_ard_3-2-1_54JTM_2023-05-24_final
2023-05-24 10:25:39	ga_s2bm_ard_3-2-1_53JQG_2023-05-24_final
2023-05-24 10:25:51	ga_s2bm_ard_3-2-1_54JTL_2023-05-24_final
2023-05-24 10:25:54	ga_s2bm_ard_3-2-1_53JQF_2023-05-24_final
2023-05-24 10:26:06	ga_s2bm_ard_3-2-1_54HTK_2023-05-24_final
2023-05-24 10:26:08	ga_s2bm_ard_3-2-1_53HQE_2023-05-24_final
2023-05-24 10:26:21	ga_s2bm_ard_3-2-1_54HTJ_2023-05-24_final
2023-05-24 10:26:23	ga_s2bm_ard_3-2-1_53HQD_2023-05-24_final
2023-05-24 10:26:35	ga_s2bm_ard_3-2-1_54HTH_2023-05-24_final
2023-05-24 10:26:37	ga_s2bm_ard_3-2-1_53HQC_2023-05-24_final
2023-05-24 10:26:50	ga_s2bm_ard_3-2-1_54HTG_2023-05-24_final
2023-05-24 10:26:51	ga_s2bm_ard_3-2-1_53HQB_2023-05-24_final
2023-05-24 10:27:04	ga_s2bm_ard_3-2-1_54HTF_2023-05-24_final
2023-05-24 10:27:06	ga_s2bm_ard_3-2-1_53HQA_2023-05-24_final
2023-05-24 10:27:16	ga_s2bm_ard_3-2-1_54HTE_2023-05-24_final
2023-05-24 10:27:17	ga_s2bm_ard_3-2-1_53HQV_2023-05-24_final
2023-06-06 10:31:54	ga_s2bm_ard_3-2-1_53KRB_2023-06-06_final
2023-06-06 10:32:09	ga_s2bm_ard_3-2-1_53KRA_2023-06-06_final
2023-06-06 10:32:23	ga_s2bm_ard_3-2-1_53KRV_2023-06-06_final
2023-06-06 10:32:38	ga_s2bm_ard_3-2-1_53KRU_2023-06-06_final
2023-06-06 10:35:06	ga_s2bm_ard_3-2-1_53JQJ_2023-06-06_final
2023-06-06 10:35:13	ga_s2bm_ard_3-2-1_54JTN_2023-06-06_final
2023-06-06 10:35:20	ga_s2bm_ard_3-2-1_53JQH_2023-06-06_final
2023-06-09 10:41:35	ga_s2bm_ard_3-2-1_53LRC_2023-06-09_nrt
2023-06-09 10:41:50	ga_s2bm_ard_3-2-1_53KRB_2023-06-09_final
2023-06-09 10:42:04	ga_s2bm_ard_3-2-1_53KRA_2023-06-09_final
2023-06-09 10:42:17	ga_s2bm_ard_3-2-1_53KRV_2023-06-09_final
2023-06-13 10:24:45	ga_s2bm_ard_3-2-1_53JQL_2023-06-13_final
2023-06-13 10:24:53	ga_s2bm_ard_3-2-1_54JTQ_2023-06-13_final
2023-06-13 10:24:56	ga_s2bm_ard_3-2-1_53JQK_2023-06-13_final
2023-06-13 10:25:08	ga_s2bm_ard_3-2-1_54JTP_2023-06-13_final
2023-06-13 10:25:10	ga_s2bm_ard_3-2-1_53JQJ_2023-06-13_final
2023-06-13 10:25:22	ga_s2bm_ard_3-2-1_54JTN_2023-06-13_final
2023-06-13 10:25:25	ga_s2bm_ard_3-2-1_53JQH_2023-06-13_final
2023-06-13 10:25:37	ga_s2bm_ard_3-2-1_54JTM_2023-06-13_final
2023-06-13 10:25:40	ga_s2bm_ard_3-2-1_53JQG_2023-06-13_final
2023-06-13 10:25:52	ga_s2bm_ard_3-2-1_54JTL_2023-06-13_final
2023-06-13 10:25:54	ga_s2bm_ard_3-2-1_53JQF_2023-06-13_final
2023-06-16 10:31:55	ga_s2bm_ard_3-2-1_53KRB_2023-06-16_final
2023-06-16 10:32:09	ga_s2bm_ard_3-2-1_53KRA_2023-06-16_final
2023-06-16 10:32:24	ga_s2bm_ard_3-2-1_53KRV_2023-06-16_final
2023-06-16 10:32:38	ga_s2bm_ard_3-2-1_53KRU_2023-06-16_final
2023-06-16 10:32:47	ga_s2bm_ard_3-2-1_53KRT_2023-06-16_final
2023-06-16 10:32:54	ga_s2bm_ard_3-2-1_53KRT_2023-06-16_final
2023-06-16 10:32:56	ga_s2bm_ard_3-2-1_53KQT_2023-06-16_final
2023-06-16 10:33:07	ga_s2bm_ard_3-2-1_53KRS_2023-06-16_final
2023-06-16 10:33:11	ga_s2bm_ard_3-2-1_53KQS_2023-06-16_final
2023-06-16 10:33:22	ga_s2bm_ard_3-2-1_53KRR_2023-06-16_final
2023-06-16 10:33:25	ga_s2bm_ard_3-2-1_53KQR_2023-06-16_final
2023-06-16 10:33:36	ga_s2bm_ard_3-2-1_53KRQ_2023-06-16_final
2023-06-16 10:33:40	ga_s2bm_ard_3-2-1_53KQQ_2023-06-16_final
2023-06-16 10:33:50	ga_s2bm_ard_3-2-1_53KRP_2023-06-16_final
2023-06-16 10:33:54	ga_s2bm_ard_3-2-1_53KQP_2023-06-16_final
2023-06-16 10:34:04	ga_s2bm_ard_3-2-1_53JRN_2023-06-16_final
2023-06-16 10:34:09	ga_s2bm_ard_3-2-1_53JQN_2023-06-16_final
2023-06-16 10:34:23	ga_s2bm_ard_3-2-1_53JQM_2023-06-16_final
2023-06-16 10:34:37	ga_s2bm_ard_3-2-1_53JQL_2023-06-16_final
2023-06-16 10:34:49	ga_s2bm_ard_3-2-1_54JTQ_2023-06-16_final
2023-06-16 10:34:52	ga_s2bm_ard_3-2-1_53JQK_2023-06-16_final
2023-06-16 10:35:02	ga_s2bm_ard_3-2-1_54JTP_2023-06-16_final
2023-06-16 10:35:06	ga_s2bm_ard_3-2-1_53JQJ_2023-06-16_final
2023-06-16 10:35:13	ga_s2bm_ard_3-2-1_54JTN_2023-06-16_final
2023-06-16 10:35:20	ga_s2bm_ard_3-2-1_53JQH_2023-06-16_final
2023-06-30 10:17:09	ga_s2bm_ard_3-2-1_54HTF_2023-06-30_final
2023-06-30 10:17:10	ga_s2bm_ard_3-2-1_53HQA_2023-06-30_final
2023-06-30 10:17:23	ga_s2bm_ard_3-2-1_54HTE_2023-06-30_final
2023-06-30 10:17:24	ga_s2bm_ard_3-2-1_53HQV_2023-06-30_final
2023-06-30 10:17:37	ga_s2bm_ard_3-2-1_54HTD_2023-06-30_nrt
2023-06-30 10:17:38	ga_s2bm_ard_3-2-1_53HQU_2023-06-30_nrt
2023-06-30 10:17:45	ga_s2bm_ard_3-2-1_54HTC_2023-06-30_nrt
2023-06-30 10:17:45	ga_s2bm_ard_3-2-1_53HQT_2023-06-30_nrt
2023-07-03 10:24:45	ga_s2bm_ard_3-2-1_53JQL_2023-07-03_final
2023-07-03 10:24:53	ga_s2bm_ard_3-2-1_54JTQ_2023-07-03_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