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
2019-07-20 10:41:54	ga_s2bm_ard_3-2-1_53KRB_2019-07-20_final
2019-07-20 10:41:57	ga_s2bm_ard_3-2-1_53KQB_2019-07-20_final
2019-07-20 10:42:01	ga_s2bm_ard_3-2-1_53KPB_2019-07-20_final.stac-item
2019-07-20 10:42:03	ga_s2bm_ard_3-2-1_54KTF_2019-07-20_final.stac-item
2019-07-20 10:42:04	ga_s2bm_ard_3-2-1_53KNB_2019-07-20_final.stac-item
2019-07-20 10:42:07	ga_s2bm_ard_3-2-1_53KRA_2019-07-20_final.stac-item
2019-07-20 10:42:09	ga_s2bm_ard_3-2-1_53KQA_2019-07-20_final.stac-item
2019-07-20 10:42:10	ga_s2bm_ard_3-2-1_53KPA_2019-07-20_final.stac-item
2019-07-20 10:42:11	ga_s2bm_ard_3-2-1_53KNB_2019-07-20_final.stac-item
2019-07-20 10:42:12	ga_s2bm_ard_3-2-1_53KNA_2019-07-20_final.stac-item
2019-07-20 10:42:13	ga_s2bm_ard_3-2-1_53KRA_2019-07-20_final.stac-item
2019-07-20 10:42:15	ga_s2bm_ard_3-2-1_53KQA_2019-07-20_final.stac-item
2019-07-20 10:42:17	ga_s2bm_ard_3-2-1_53KPA_2019-07-20_final.stac-item
2019-07-20 10:42:19	ga_s2bm_ard_3-2-1_53KNA_2019-07-20_final.stac-item
2019-07-20 10:42:21	ga_s2bm_ard_3-2-1_53KRV_2019-07-20_final.stac-item
2019-07-20 10:42:26	ga_s2bm_ard_3-2-1_53KQV_2019-07-20_final.stac-item
2019-07-20 10:42:30	ga_s2bm_ard_3-2-1_53KPV_2019-07-20_final.stac-item
2019-07-20 10:42:31	ga_s2bm_ard_3-2-1_53KRU_2019-07-20_final.stac-item
2019-07-20 10:42:33	ga_s2bm_ard_3-2-1_53KNV_2019-07-20_final.stac-item
2019-07-20 10:42:41	ga_s2bm_ard_3-2-1_53KQU_2019-07-20_final.stac-item
2019-07-20 10:42:45	ga_s2bm_ard_3-2-1_53KPU_2019-07-20_final.stac-item
2019-07-20 10:42:48	ga_s2bm_ard_3-2-1_53KNU_2019-07-20_final.stac-item
2019-07-20 10:42:52	ga_s2bm_ard_3-2-1_53KMU_2019-07-20_final.stac-item
2019-07-20 10:42:55	ga_s2bm_ard_3-2-1_53KQT_2019-07-20_final.stac-item
2019-07-20 10:42:59	ga_s2bm_ard_3-2-1_53KPT_2019-07-20_final.stac-item
2019-07-20 10:43:02	ga_s2bm_ard_3-2-1_53KNT_2019-07-20_final.stac-item
2019-07-20 10:43:05	ga_s2bm_ard_3-2-1_53KMT_2019-07-20_final.stac-item
2019-07-20 10:43:10	ga_s2bm_ard_3-2-1_53KQS_2019-07-20_final.stac-item
2019-07-20 10:43:13	ga_s2bm_ard_3-2-1_53KPS_2019-07-20_final.stac-item
2019-07-20 10:43:17	ga_s2bm_ard_3-2-1_53KNS_2019-07-20_final.stac-item
2019-07-20 10:43:20	ga_s2bm_ard_3-2-1_53KMS_2019-07-20_final.stac-item
2019-07-20 10:43:23	ga_s2bm_ard_3-2-1_53KQR_2019-07-20_final.stac-item
2019-07-20 10:43:28	ga_s2bm_ard_3-2-1_53KPR_2019-07-20_final.stac-item
2019-07-20 10:43:31	ga_s2bm_ard_3-2-1_53KNR_2019-07-20_final.stac-item
2019-07-20 10:43:34	ga_s2bm_ard_3-2-1_53KQQ_2019-07-20_final.stac-item
2019-07-20 10:43:35	ga_s2bm_ard_3-2-1_53KMR_2019-07-20_final.stac-item
2019-07-20 10:43:42	ga_s2bm_ard_3-2-1_53KPQ_2019-07-20_final.stac-item
2019-07-20 10:43:46	ga_s2bm_ard_3-2-1_53KNQ_2019-07-20_final.stac-item
2019-07-20 10:43:49	ga_s2bm_ard_3-2-1_53KMQ_2019-07-20_final.stac-item
2019-07-20 10:43:54	ga_s2bm_ard_3-2-1_53KLQ_2019-07-20_final.stac-item
2019-07-20 10:43:57	ga_s2bm_ard_3-2-1_53KPP_2019-07-20_final.stac-item
2019-07-20 10:44:00	ga_s2bm_ard_3-2-1_53KNP_2019-07-20_final.stac-item
2019-07-20 10:44:04	ga_s2bm_ard_3-2-1_53KMP_2019-07-20_final.stac-item
2019-07-20 10:44:07	ga_s2bm_ard_3-2-1_53KLP_2019-07-20_final.stac-item
2019-07-20 10:44:11	ga_s2bm_ard_3-2-1_53JPN_2019-07-20_final.stac-item
2019-07-20 10:44:15	ga_s2bm_ard_3-2-1_53JNN_2019-07-20_final.stac-item
2019-07-20 10:44:18	ga_s2bm_ard_3-2-1_53JMN_2019-07-20_final.stac-item
2019-07-20 10:44:21	ga_s2bm_ard_3-2-1_53JLN_2019-07-20_final.stac-item
2019-07-20 10:44:25	ga_s2bm_ard_3-2-1_53JPM_2019-07-20_final.stac-item
2019-07-20 10:44:29	ga_s2bm_ard_3-2-1_53JNM_2019-07-20_final.stac-item
2019-07-20 10:44:33	ga_s2bm_ard_3-2-1_53JMM_2019-07-20_final.stac-item
2019-07-20 10:44:36	ga_s2bm_ard_3-2-1_53JLM_2019-07-20_final.stac-item
2019-07-20 10:44:37	ga_s2bm_ard_3-2-1_53JPL_2019-07-20_final.stac-item
2019-07-20 10:44:44	ga_s2bm_ard_3-2-1_53JNL_2019-07-20_final.stac-item
2019-07-20 10:44:47	ga_s2bm_ard_3-2-1_53JML_2019-07-20_final.stac-item
2019-07-20 10:44:51	ga_s2bm_ard_3-2-1_53JLL_2019-07-20_final.stac-item
2019-07-20 10:44:56	ga_s2bm_ard_3-2-1_53JKL_2019-07-20_final.stac-item
2019-07-20 10:44:58	ga_s2bm_ard_3-2-1_53JNK_2019-07-20_final.stac-item
2019-07-20 10:45:02	ga_s2bm_ard_3-2-1_53JMK_2019-07-20_final.stac-item
2019-07-20 10:45:05	ga_s2bm_ard_3-2-1_53JLK_2019-07-20_final.stac-item
2019-07-20 10:45:09	ga_s2bm_ard_3-2-1_53JKK_2019-07-20_final.stac-item
2019-07-20 10:45:13	ga_s2bm_ard_3-2-1_53JNJ_2019-07-20_final.stac-item
2019-07-20 10:45:16	ga_s2bm_ard_3-2-1_53JMJ_2019-07-20_final.stac-item
2019-07-20 10:45:20	ga_s2bm_ard_3-2-1_53JLJ_2019-07-20_final.stac-item
2019-07-20 10:45:23	ga_s2bm_ard_3-2-1_53JKJ_2019-07-20_final.stac-item
2019-07-20 10:45:27	ga_s2bm_ard_3-2-1_53JNH_2019-07-20_final.stac-item
2019-07-20 10:45:31	ga_s2bm_ard_3-2-1_53JMH_2019-07-20_final.stac-item
2019-07-20 10:45:34	ga_s2bm_ard_3-2-1_53JLH_2019-07-20_final.stac-item
2019-07-20 10:45:38	ga_s2bm_ard_3-2-1_53JKH_2019-07-20_final.stac-item
2019-07-20 10:45:40	ga_s2bm_ard_3-2-1_53JNG_2019-07-20_final.stac-item
2019-07-20 10:45:45	ga_s2bm_ard_3-2-1_53JMG_2019-07-20_final.stac-item
2019-07-20 10:45:49	ga_s2bm_ard_3-2-1_53JLG_2019-07-20_final.stac-item
2019-07-20 10:45:50	ga_s2bm_ard_3-2-1_53JNF_2019-07-20_final.stac-item
2019-07-21 10:15:41	ga_s2bm_ard_3-2-1_54JUM_2019-07-21_final.stac-item
2019-07-21 10:15:56	ga_s2bm_ard_3-2-1_54JUL_2019-07-21_final.stac-item
2019-07-21 10:15:58	ga_s2bm_ard_3-2-1_54HXK_2019-07-21_final.stac-item
2019-07-21 10:16:04	ga_s2bm_ard_3-2-1_54HWK_2019-07-21_final.stac-item
2019-07-21 10:16:07	ga_s2bm_ard_3-2-1_54HVK_2019-07-21_final.stac-item
2019-07-21 10:16:09	ga_s2bm_ard_3-2-1_54HXJ_2019-07-21_final.stac-item
2019-07-21 10:16:11	ga_s2bm_ard_3-2-1_54HUK_2019-07-21_final.stac-item
2019-07-21 10:16:18	ga_s2bm_ard_3-2-1_54HWJ_2019-07-21_final.stac-item
2019-07-21 10:16:22	ga_s2bm_ard_3-2-1_54HVJ_2019-07-21_final.stac-item
2019-07-21 10:16:25	ga_s2bm_ard_3-2-1_54HUJ_2019-07-21_final.stac-item
2019-07-21 10:16:29	ga_s2bm_ard_3-2-1_54HTJ_2019-07-21_final.stac-item
2019-07-21 10:16:33	ga_s2bm_ard_3-2-1_54HWH_2019-07-21_final.stac-item
2019-07-21 10:16:36	ga_s2bm_ard_3-2-1_54HVH_2019-07-21_final.stac-item
2019-07-21 10:16:40	ga_s2bm_ard_3-2-1_54HUH_2019-07-21_final.stac-item
2019-07-21 10:16:43	ga_s2bm_ard_3-2-1_54HTH_2019-07-21_final.stac-item
2019-07-21 10:16:47	ga_s2bm_ard_3-2-1_54HWG_2019-07-21_final.stac-item
2019-07-21 10:16:51	ga_s2bm_ard_3-2-1_54HVG_2019-07-21_final.stac-item
2019-07-21 10:16:54	ga_s2bm_ard_3-2-1_54HUG_2019-07-21_final.stac-item
2019-07-21 10:16:57	ga_s2bm_ard_3-2-1_54HTG_2019-07-21_final.stac-item
2019-07-21 10:17:00	ga_s2bm_ard_3-2-1_53HQB_2019-07-21_final.stac-item
2019-07-21 10:17:01	ga_s2bm_ard_3-2-1_54HWF_2019-07-21_final.stac-item
2019-07-21 10:17:05	ga_s2bm_ard_3-2-1_54HVF_2019-07-21_final.stac-item
2019-07-21 10:17:09	ga_s2bm_ard_3-2-1_54HUF_2019-07-21_final.stac-item
2019-07-21 10:17:12	ga_s2bm_ard_3-2-1_54HWE_2019-07-21_final.stac-item
2019-07-21 10:17:12	ga_s2bm_ard_3-2-1_54HTF_2019-07-21_final.stac-item
2019-07-21 10:17:13	ga_s2bm_ard_3-2-1_53HQA_2019-07-21_final.stac-item
2019-07-21 10:17:20	ga_s2bm_ard_3-2-1_54HVE_2019-07-21_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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