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
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_53HMD_2018-10-20_final.stac-item
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_53HME_2018-10-20_final.stac-item
2018-10-20 10:31:25	ga_s2bm_ard_3-2-1_53JMF_2018-10-20_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KMP_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KMQ_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KMR_2018-10-26_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53HMD_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53HME_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53JMF_2018-10-30_final.stac-item
2018-11-15 10:50:39	ga_s2bm_ard_3-2-1_53LMG_2018-11-15_final.stac-item
2018-11-15 10:50:53	ga_s2bm_ard_3-2-1_53LMF_2018-11-15_final.stac-item
2018-11-15 10:51:08	ga_s2bm_ard_3-2-1_53LME_2018-11-15_final.stac-item
2018-11-15 10:51:23	ga_s2bm_ard_3-2-1_53LMD_2018-11-15_final.stac-item
2018-11-15 10:51:37	ga_s2bm_ard_3-2-1_53LMC_2018-11-15_final.stac-item
2018-11-15 10:51:52	ga_s2bm_ard_3-2-1_53KMB_2018-11-15_final.stac-item
2018-11-15 10:52:06	ga_s2bm_ard_3-2-1_53KMA_2018-11-15_final.stac-item
2018-11-15 10:52:21	ga_s2bm_ard_3-2-1_53KMV_2018-11-15_final.stac-item
2018-11-15 10:52:35	ga_s2bm_ard_3-2-1_53KMU_2018-11-15_final.stac-item
2018-11-15 10:52:49	ga_s2bm_ard_3-2-1_53KMT_2018-11-15_final.stac-item
2018-11-15 10:53:04	ga_s2bm_ard_3-2-1_53KMS_2018-11-15_final.stac-item
2018-11-15 10:53:19	ga_s2bm_ard_3-2-1_53KMR_2018-11-15_final.stac-item
2018-11-15 10:53:33	ga_s2bm_ard_3-2-1_53KMQ_2018-11-15_final.stac-item
2018-11-15 10:53:46	ga_s2bm_ard_3-2-1_53KMP_2018-11-15_final.stac-item
2018-11-19 10:35:53	ga_s2bm_ard_3-2-1_53JMF_2018-11-19_final.stac-item
2018-11-19 10:36:07	ga_s2bm_ard_3-2-1_53HME_2018-11-19_final.stac-item
2018-11-19 10:36:22	ga_s2bm_ard_3-2-1_53HMD_2018-11-19_final.stac-item
2019-03-02 10:46:04	ga_s2bm_ard_3-2-1_53HME_2019-03-02_final.stac-item
2019-03-02 10:46:19	ga_s2bm_ard_3-2-1_53HMD_2019-03-02_final.stac-item
2019-03-12 10:46:03	ga_s2bm_ard_3-2-1_53HME_2019-03-12_final.stac-item
2019-03-12 10:46:18	ga_s2bm_ard_3-2-1_53HMD_2019-03-12_final.stac-item
2019-09-25 10:35:55	ga_s2bm_ard_3-2-1_53JMF_2019-09-25_final.stac-item
2019-09-25 10:36:10	ga_s2bm_ard_3-2-1_53HME_2019-09-25_final.stac-item
2019-09-25 10:36:24	ga_s2bm_ard_3-2-1_53HMD_2019-09-25_final.stac-item
2019-09-28 10:44:54	ga_s2bm_ard_3-2-1_53JMK_2019-09-28_final.stac-item
2019-09-28 10:45:08	ga_s2bm_ard_3-2-1_53JMJ_2019-09-28_final.stac-item
2019-09-28 10:45:23	ga_s2bm_ard_3-2-1_53JMH_2019-09-28_final.stac-item
2019-09-28 10:45:37	ga_s2bm_ard_3-2-1_53JMG_2019-09-28_final.stac-item
2019-09-28 10:45:51	ga_s2bm_ard_3-2-1_53JMF_2019-09-28_final.stac-item
2019-09-28 10:46:06	ga_s2bm_ard_3-2-1_53HME_2019-09-28_final.stac-item
2019-10-01 10:50:42	ga_s2bm_ard_3-2-1_53LMG_2019-10-01_final.stac-item
2019-10-01 10:50:56	ga_s2bm_ard_3-2-1_53LMF_2019-10-01_final.stac-item
2019-10-01 10:51:11	ga_s2bm_ard_3-2-1_53LME_2019-10-01_final.stac-item
2019-10-01 10:51:26	ga_s2bm_ard_3-2-1_53LMD_2019-10-01_final.stac-item
2019-10-01 10:51:40	ga_s2bm_ard_3-2-1_53LMC_2019-10-01_final.stac-item
2019-10-01 10:51:55	ga_s2bm_ard_3-2-1_53KMB_2019-10-01_final.stac-item
2019-10-01 10:52:09	ga_s2bm_ard_3-2-1_53KMA_2019-10-01_final.stac-item
2019-10-01 10:52:24	ga_s2bm_ard_3-2-1_53KMV_2019-10-01_final.stac-item
2019-10-01 10:52:38	ga_s2bm_ard_3-2-1_53KMU_2019-10-01_final.stac-item
2019-10-01 10:52:53	ga_s2bm_ard_3-2-1_53KMT_2019-10-01_final.stac-item
2019-10-01 10:53:07	ga_s2bm_ard_3-2-1_53KMS_2019-10-01_final.stac-item
2019-10-01 10:53:22	ga_s2bm_ard_3-2-1_53KMR_2019-10-01_final.stac-item
2019-10-01 10:53:36	ga_s2bm_ard_3-2-1_53KMQ_2019-10-01_final.stac-item
2019-10-01 10:53:50	ga_s2bm_ard_3-2-1_53KMP_2019-10-01_final.stac-item
2019-10-04 11:00:37	ga_s2bm_ard_3-2-1_53LMG_2019-10-04_final.stac-item
2019-10-05 10:35:56	ga_s2bm_ard_3-2-1_53JMF_2019-10-05_final.stac-item
2019-10-05 10:36:11	ga_s2bm_ard_3-2-1_53HME_2019-10-05_final.stac-item
2019-10-05 10:36:25	ga_s2bm_ard_3-2-1_53HMD_2019-10-05_final.stac-item
2019-10-11 10:50:43	ga_s2bm_ard_3-2-1_53LMG_2019-10-11_final.stac-item
2019-10-11 10:50:57	ga_s2bm_ard_3-2-1_53LMF_2019-10-11_final.stac-item
2019-10-11 10:51:12	ga_s2bm_ard_3-2-1_53LME_2019-10-11_final.stac-item
2019-10-11 10:51:26	ga_s2bm_ard_3-2-1_53LMD_2019-10-11_final.stac-item
2019-10-11 10:51:41	ga_s2bm_ard_3-2-1_53LMC_2019-10-11_final.stac-item
2019-10-11 10:51:48	ga_s2bm_ard_3-2-1_53LMC_2019-10-11_final.stac-item
2019-10-11 10:51:48	ga_s2bm_ard_3-2-1_53KMB_2019-10-11_final.stac-item
2019-10-11 10:51:55	ga_s2bm_ard_3-2-1_53KMB_2019-10-11_final.stac-item
2019-10-11 10:52:10	ga_s2bm_ard_3-2-1_53KMA_2019-10-11_final.stac-item
2019-10-11 10:52:24	ga_s2bm_ard_3-2-1_53KMV_2019-10-11_final.stac-item
2019-10-11 10:52:39	ga_s2bm_ard_3-2-1_53KMU_2019-10-11_final.stac-item
2019-10-11 10:52:53	ga_s2bm_ard_3-2-1_53KMT_2019-10-11_final.stac-item
2019-10-11 10:53:08	ga_s2bm_ard_3-2-1_53KMS_2019-10-11_final.stac-item
2019-10-11 10:53:23	ga_s2bm_ard_3-2-1_53KMR_2019-10-11_final.stac-item
2019-10-11 10:53:37	ga_s2bm_ard_3-2-1_53KMQ_2019-10-11_final.stac-item
2019-10-11 10:53:50	ga_s2bm_ard_3-2-1_53KMP_2019-10-11_final.stac-item
2019-12-14 10:35:50	ga_s2bm_ard_3-2-1_53JMF_2019-12-14_final.stac-item
2019-12-14 10:36:05	ga_s2bm_ard_3-2-1_53HME_2019-12-14_final.stac-item
2019-12-14 10:36:19	ga_s2bm_ard_3-2-1_53HMD_2019-12-14_final.stac-item
2019-12-30 10:53:17	ga_s2bm_ard_3-2-1_53KMR_2019-12-30_final.stac-item
2019-12-30 10:53:31	ga_s2bm_ard_3-2-1_53KMQ_2019-12-30_final.stac-item
2019-12-30 10:53:44	ga_s2bm_ard_3-2-1_53KMP_2019-12-30_final.stac-item
2020-01-03 10:35:51	ga_s2bm_ard_3-2-1_53JMF_2020-01-03_final.stac-item
2020-01-03 10:36:05	ga_s2bm_ard_3-2-1_53HME_2020-01-03_final.stac-item
2020-01-03 10:36:20	ga_s2bm_ard_3-2-1_53HMD_2020-01-03_final.stac-item
2020-01-03 10:36:49	ga_s2bm_ard_3-2-1_53HMB_2020-01-03_final
2020-01-06 10:43:21	ga_s2bm_ard_3-2-1_53KMR_2020-01-06_final.stac-item
2020-01-06 10:43:35	ga_s2bm_ard_3-2-1_53KMQ_2020-01-06_final.stac-item
2020-01-06 10:43:50	ga_s2bm_ard_3-2-1_53KMP_2020-01-06_final.stac-item
2020-01-06 10:44:05	ga_s2bm_ard_3-2-1_53JMN_2020-01-06_final.stac-item
2020-01-06 10:44:19	ga_s2bm_ard_3-2-1_53JMM_2020-01-06_final.stac-item
2020-01-06 10:44:34	ga_s2bm_ard_3-2-1_53JML_2020-01-06_final.stac-item
2020-01-06 10:44:48	ga_s2bm_ard_3-2-1_53JMK_2020-01-06_final.stac-item
2020-01-06 10:45:03	ga_s2bm_ard_3-2-1_53JMJ_2020-01-06_final.stac-item
2020-01-06 10:45:17	ga_s2bm_ard_3-2-1_53JMH_2020-01-06_final.stac-item
2020-01-06 10:45:31	ga_s2bm_ard_3-2-1_53JMG_2020-01-06_final.stac-item
2020-01-06 10:45:38	ga_s2bm_ard_3-2-1_53JMF_2020-01-06_final.stac-item
2020-01-06 10:45:38	ga_s2bm_ard_3-2-1_53JMG_2020-01-06_final.stac-item
2020-01-12 11:00:17	ga_s2bm_ard_3-2-1_53LMH_2020-01-12_final
2020-01-12 11:00:31	ga_s2bm_ard_3-2-1_53LMG_2020-01-12_final.stac-item
2020-01-13 10:35:50	ga_s2bm_ard_3-2-1_53JMF_2020-01-13_final.stac-item
2020-01-13 10:36:05	ga_s2bm_ard_3-2-1_53HME_2020-01-13_final.stac-item
2020-01-13 10:36:19	ga_s2bm_ard_3-2-1_53HMD_2020-01-13_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