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
2018-10-23 10:41:55	ga_s2bm_ard_3-2-1_53JMF_2018-10-23_final.stac-item
2018-10-23 10:41:55	ga_s2bm_ard_3-2-1_53JMG_2018-10-23_final.stac-item
2018-10-23 10:41:55	ga_s2bm_ard_3-2-1_53JMH_2018-10-23_final.stac-item
2018-10-23 10:41:55	ga_s2bm_ard_3-2-1_53JMJ_2018-10-23_final.stac-item
2018-10-23 10:41:55	ga_s2bm_ard_3-2-1_53JMK_2018-10-23_final.stac-item
2018-10-23 10:41:55	ga_s2bm_ard_3-2-1_53JML_2018-10-23_final.stac-item
2018-10-23 10:41:55	ga_s2bm_ard_3-2-1_53JMM_2018-10-23_final.stac-item
2018-10-26 10:47:22	ga_s2bm_ard_3-2-1_53LMG_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KMA_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KMB_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KMT_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KMU_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KMV_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KNA_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KNB_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KNT_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KNU_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53KNV_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53LMC_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53LMD_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53LME_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53LMF_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53LMG_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53LNC_2018-10-26_final.stac-item
2018-10-26 10:50:30	ga_s2bm_ard_3-2-1_53LND_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_53HNB_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53HNC_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53HND_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53HNE_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
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53JMG_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53JMH_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53JMJ_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53JNF_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53JNG_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53JNH_2018-10-30_final.stac-item
2018-10-30 10:32:44	ga_s2bm_ard_3-2-1_53JNJ_2018-10-30_final.stac-item
2019-05-08 10:35:17	ga_s2bm_ard_3-2-1_53JNJ_2019-05-08_final.stac-item
2019-05-08 10:35:23	ga_s2bm_ard_3-2-1_53JMJ_2019-05-08_final.stac-item
2020-02-15 10:43:18	ga_s2bm_ard_3-2-1_53KNR_2020-02-15_final.stac-item
2020-02-15 10:43:22	ga_s2bm_ard_3-2-1_53KMR_2020-02-15_final.stac-item
2020-02-15 10:43:33	ga_s2bm_ard_3-2-1_53KNQ_2020-02-15_final.stac-item
2020-02-15 10:43:36	ga_s2bm_ard_3-2-1_53KMQ_2020-02-15_final.stac-item
2020-02-15 10:43:47	ga_s2bm_ard_3-2-1_53KNP_2020-02-15_final.stac-item
2020-02-15 10:43:51	ga_s2bm_ard_3-2-1_53KMP_2020-02-15_final.stac-item
2020-02-15 10:44:02	ga_s2bm_ard_3-2-1_53JNN_2020-02-15_final.stac-item
2020-02-15 10:44:05	ga_s2bm_ard_3-2-1_53JMN_2020-02-15_final.stac-item
2020-02-15 10:44:16	ga_s2bm_ard_3-2-1_53JNM_2020-02-15_final.stac-item
2020-02-15 10:44:20	ga_s2bm_ard_3-2-1_53JMM_2020-02-15_final.stac-item
2020-02-15 10:44:31	ga_s2bm_ard_3-2-1_53JNL_2020-02-15_final.stac-item
2020-02-15 10:44:34	ga_s2bm_ard_3-2-1_53JML_2020-02-15_final.stac-item
2020-02-15 10:44:45	ga_s2bm_ard_3-2-1_53JNK_2020-02-15_final.stac-item
2020-02-15 10:44:49	ga_s2bm_ard_3-2-1_53JMK_2020-02-15_final.stac-item
2020-02-15 10:45:00	ga_s2bm_ard_3-2-1_53JNJ_2020-02-15_final.stac-item
2020-02-15 10:45:03	ga_s2bm_ard_3-2-1_53JMJ_2020-02-15_final.stac-item
2020-02-15 10:45:14	ga_s2bm_ard_3-2-1_53JNH_2020-02-15_final.stac-item
2020-02-15 10:45:18	ga_s2bm_ard_3-2-1_53JMH_2020-02-15_final.stac-item
2020-02-15 10:45:27	ga_s2bm_ard_3-2-1_53JNG_2020-02-15_final.stac-item
2020-02-15 10:45:32	ga_s2bm_ard_3-2-1_53JMG_2020-02-15_final.stac-item
2020-02-15 10:45:37	ga_s2bm_ard_3-2-1_53JNF_2020-02-15_final.stac-item
2020-02-15 10:45:47	ga_s2bm_ard_3-2-1_53JMF_2020-02-15_final.stac-item
2020-02-18 10:50:23	ga_s2bm_ard_3-2-1_53LMH_2020-02-18_final
2020-02-18 10:50:38	ga_s2bm_ard_3-2-1_53LMG_2020-02-18_final.stac-item
2020-02-18 10:50:52	ga_s2bm_ard_3-2-1_53LMF_2020-02-18_final.stac-item
2020-02-18 10:51:07	ga_s2bm_ard_3-2-1_53LME_2020-02-18_final.stac-item
2020-02-18 10:51:18	ga_s2bm_ard_3-2-1_53LND_2020-02-18_final.stac-item
2020-02-18 10:51:21	ga_s2bm_ard_3-2-1_53LMD_2020-02-18_final.stac-item
2020-02-18 10:51:32	ga_s2bm_ard_3-2-1_53LNC_2020-02-18_final.stac-item
2020-02-18 10:51:36	ga_s2bm_ard_3-2-1_53LMC_2020-02-18_final.stac-item
2020-02-18 10:51:47	ga_s2bm_ard_3-2-1_53KNB_2020-02-18_final.stac-item
2020-02-18 10:51:50	ga_s2bm_ard_3-2-1_53KMB_2020-02-18_final.stac-item
2020-02-18 10:52:01	ga_s2bm_ard_3-2-1_53KNA_2020-02-18_final.stac-item
2020-02-18 10:52:03	ga_s2bm_ard_3-2-1_53KMA_2020-02-18_final.stac-item
2020-02-18 10:52:08	ga_s2bm_ard_3-2-1_53KNA_2020-02-18_final.stac-item
2020-02-18 10:52:10	ga_s2bm_ard_3-2-1_53KMA_2020-02-18_final.stac-item
2020-02-18 10:52:16	ga_s2bm_ard_3-2-1_53KNV_2020-02-18_final.stac-item
2020-02-18 10:52:19	ga_s2bm_ard_3-2-1_53KMV_2020-02-18_final.stac-item
2020-02-18 10:52:30	ga_s2bm_ard_3-2-1_53KNU_2020-02-18_final.stac-item
2020-02-18 10:52:34	ga_s2bm_ard_3-2-1_53KMU_2020-02-18_final.stac-item
2020-02-18 10:52:41	ga_s2bm_ard_3-2-1_53KNT_2020-02-18_final.stac-item
2020-02-18 10:52:48	ga_s2bm_ard_3-2-1_53KMT_2020-02-18_final.stac-item
2020-03-16 10:45:17	ga_s2bm_ard_3-2-1_53JNH_2020-03-16_final.stac-item
2020-03-16 10:45:20	ga_s2bm_ard_3-2-1_53JMH_2020-03-16_final.stac-item
2020-03-16 10:45:30	ga_s2bm_ard_3-2-1_53JNG_2020-03-16_final.stac-item
2020-03-16 10:45:35	ga_s2bm_ard_3-2-1_53JMG_2020-03-16_final.stac-item
2020-03-16 10:45:40	ga_s2bm_ard_3-2-1_53JNF_2020-03-16_final.stac-item
2020-03-16 10:45:49	ga_s2bm_ard_3-2-1_53JMF_2020-03-16_final.stac-item
2020-03-23 10:35:07	ga_s2bm_ard_3-2-1_53JNJ_2020-03-23_final.stac-item
2020-03-23 10:35:13	ga_s2bm_ard_3-2-1_53JMJ_2020-03-23_final.stac-item
2020-03-23 10:35:21	ga_s2bm_ard_3-2-1_53JNH_2020-03-23_final.stac-item
2020-03-23 10:35:25	ga_s2bm_ard_3-2-1_53JMH_2020-03-23_final.stac-item
2020-03-23 10:35:36	ga_s2bm_ard_3-2-1_53JNG_2020-03-23_final.stac-item
2020-03-23 10:35:39	ga_s2bm_ard_3-2-1_53JMG_2020-03-23_final.stac-item
2020-03-23 10:35:50	ga_s2bm_ard_3-2-1_53JNF_2020-03-23_final.stac-item
2020-03-23 10:35:54	ga_s2bm_ard_3-2-1_53JMF_2020-03-23_final.stac-item
2020-03-23 10:36:05	ga_s2bm_ard_3-2-1_53HNE_2020-03-23_final.stac-item
2020-03-23 10:36:08	ga_s2bm_ard_3-2-1_53HME_2020-03-23_final.stac-item
2020-03-23 10:36:19	ga_s2bm_ard_3-2-1_53HND_2020-03-23_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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