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
2023-09-03 09:24:28	ga_s2bm_ard_3-2-1_56JNQ_2023-09-02_final
2023-09-03 09:24:33	ga_s2bm_ard_3-2-1_56JMQ_2023-09-02_final
2023-09-03 09:24:43	ga_s2bm_ard_3-2-1_56JNP_2023-09-02_final
2023-09-03 09:24:46	ga_s2bm_ard_3-2-1_56JMP_2023-09-02_final
2023-09-03 09:24:57	ga_s2bm_ard_3-2-1_56JNN_2023-09-02_final
2023-09-03 09:25:01	ga_s2bm_ard_3-2-1_56JMN_2023-09-02_final
2023-09-03 09:25:12	ga_s2bm_ard_3-2-1_56JNM_2023-09-02_final
2023-09-03 09:25:15	ga_s2bm_ard_3-2-1_56JMM_2023-09-02_final
2023-09-03 09:25:26	ga_s2bm_ard_3-2-1_56JNL_2023-09-02_final
2023-09-03 09:25:28	ga_s2bm_ard_3-2-1_56JML_2023-09-02_final
2023-09-03 09:25:33	ga_s2bm_ard_3-2-1_56JNL_2023-09-02_final
2023-09-03 09:25:35	ga_s2bm_ard_3-2-1_56JML_2023-09-02_final
2023-09-03 09:25:41	ga_s2bm_ard_3-2-1_56HNK_2023-09-02_nrt
2023-09-03 09:25:44	ga_s2bm_ard_3-2-1_56HMK_2023-09-02_final
2023-09-06 09:32:34	ga_s2bm_ard_3-2-1_56KMC_2023-09-06_nrt
2023-09-06 09:32:45	ga_s2bm_ard_3-2-1_56KMB_2023-09-06_final
2023-09-06 09:33:00	ga_s2bm_ard_3-2-1_56KMA_2023-09-06_final
2023-09-06 09:33:14	ga_s2bm_ard_3-2-1_56KMV_2023-09-06_nrt
2023-09-06 09:33:29	ga_s2bm_ard_3-2-1_56KMU_2023-09-06_final
2023-09-06 09:33:40	ga_s2bm_ard_3-2-1_56JNT_2023-09-06_final
2023-09-06 09:33:44	ga_s2bm_ard_3-2-1_56JMT_2023-09-06_final
2023-09-06 09:33:54	ga_s2bm_ard_3-2-1_56JNS_2023-09-06_final
2023-09-06 09:33:58	ga_s2bm_ard_3-2-1_56JMS_2023-09-06_final
2023-09-16 09:34:54	ga_s2bm_ard_3-2-1_56JMN_2023-09-16_final
2023-09-19 09:41:19	ga_s2bm_ard_3-2-1_56LMH_2023-09-19_nrt
2023-09-19 09:41:27	ga_s2bm_ard_3-2-1_56KMG_2023-09-19_final
2023-09-19 09:41:42	ga_s2bm_ard_3-2-1_56KMF_2023-09-19_final
2023-09-19 09:41:56	ga_s2bm_ard_3-2-1_56KME_2023-09-19_final
2023-10-13 09:24:26	ga_s2bm_ard_3-2-1_56JNQ_2023-10-12_final
2023-10-13 09:24:30	ga_s2bm_ard_3-2-1_56JMQ_2023-10-12_final
2023-10-13 09:24:40	ga_s2bm_ard_3-2-1_56JNP_2023-10-12_final
2023-10-13 09:24:43	ga_s2bm_ard_3-2-1_56JMP_2023-10-12_final
2023-10-13 09:24:55	ga_s2bm_ard_3-2-1_56JNN_2023-10-12_final
2023-10-13 09:24:58	ga_s2bm_ard_3-2-1_56JMN_2023-10-12_final
2023-10-13 09:25:09	ga_s2bm_ard_3-2-1_56JNM_2023-10-12_final
2023-10-13 09:25:13	ga_s2bm_ard_3-2-1_56JMM_2023-10-12_final
2023-10-13 09:25:24	ga_s2bm_ard_3-2-1_56JNL_2023-10-12_final
2023-10-13 09:25:27	ga_s2bm_ard_3-2-1_56JML_2023-10-12_final
2023-10-13 09:25:38	ga_s2bm_ard_3-2-1_56HNK_2023-10-12_nrt
2023-10-13 09:25:42	ga_s2bm_ard_3-2-1_56HMK_2023-10-12_final
2023-10-13 09:25:53	ga_s2bm_ard_3-2-1_56HNJ_2023-10-12_nrt
2023-10-13 09:25:56	ga_s2bm_ard_3-2-1_56HMJ_2023-10-12_final
2023-10-13 09:26:07	ga_s2bm_ard_3-2-1_56HNH_2023-10-12_nrt
2023-10-13 09:26:11	ga_s2bm_ard_3-2-1_56HMH_2023-10-12_nrt
2023-10-13 09:26:21	ga_s2bm_ard_3-2-1_56HNG_2023-10-12_nrt
2023-10-13 09:26:25	ga_s2bm_ard_3-2-1_56HMG_2023-10-12_nrt
2023-10-13 09:26:36	ga_s2bm_ard_3-2-1_56HNF_2023-10-12_nrt
2023-10-13 09:26:40	ga_s2bm_ard_3-2-1_56HMF_2023-10-12_nrt
2023-10-13 09:26:51	ga_s2bm_ard_3-2-1_56HNE_2023-10-12_nrt
2023-10-13 09:26:54	ga_s2bm_ard_3-2-1_56HME_2023-10-12_nrt
2023-10-13 09:27:05	ga_s2bm_ard_3-2-1_56HND_2023-10-12_nrt
2023-10-13 09:27:09	ga_s2bm_ard_3-2-1_56HMD_2023-10-12_nrt
2023-10-13 09:27:17	ga_s2bm_ard_3-2-1_56HNC_2023-10-12_nrt
2023-10-13 09:27:23	ga_s2bm_ard_3-2-1_56HMC_2023-10-12_nrt
2023-10-23 09:25:37	ga_s2bm_ard_3-2-1_56HNK_2023-10-22_nrt
2023-10-23 09:25:41	ga_s2bm_ard_3-2-1_56HMK_2023-10-22_final
2023-10-23 09:25:52	ga_s2bm_ard_3-2-1_56HNJ_2023-10-22_nrt
2023-10-23 09:25:56	ga_s2bm_ard_3-2-1_56HMJ_2023-10-22_final
2023-10-23 09:26:06	ga_s2bm_ard_3-2-1_56HNH_2023-10-22_nrt
2023-10-23 09:26:10	ga_s2bm_ard_3-2-1_56HMH_2023-10-22_nrt
2023-10-23 09:26:21	ga_s2bm_ard_3-2-1_56HNG_2023-10-22_nrt
2023-10-23 09:26:25	ga_s2bm_ard_3-2-1_56HMG_2023-10-22_nrt
2023-10-23 09:26:35	ga_s2bm_ard_3-2-1_56HNF_2023-10-22_nrt
2023-10-23 09:26:39	ga_s2bm_ard_3-2-1_56HMF_2023-10-22_nrt
2023-10-23 09:26:50	ga_s2bm_ard_3-2-1_56HNE_2023-10-22_nrt
2023-10-23 09:26:54	ga_s2bm_ard_3-2-1_56HME_2023-10-22_nrt
2023-10-23 09:27:04	ga_s2bm_ard_3-2-1_56HND_2023-10-22_nrt
2023-10-23 09:27:08	ga_s2bm_ard_3-2-1_56HMD_2023-10-22_nrt
2023-10-23 09:27:16	ga_s2bm_ard_3-2-1_56HNC_2023-10-22_nrt
2023-10-23 09:27:22	ga_s2bm_ard_3-2-1_56HMC_2023-10-22_nrt
2023-12-02 09:24:21	ga_s2bm_ard_3-2-1_56JNQ_2023-12-01_final
2023-12-02 09:24:25	ga_s2bm_ard_3-2-1_56JMQ_2023-12-01_final
2023-12-02 09:24:35	ga_s2bm_ard_3-2-1_56JNP_2023-12-01_final
2023-12-02 09:24:38	ga_s2bm_ard_3-2-1_56JMP_2023-12-01_final
2023-12-02 09:24:50	ga_s2bm_ard_3-2-1_56JNN_2023-12-01_final
2023-12-02 09:24:53	ga_s2bm_ard_3-2-1_56JMN_2023-12-01_final
2023-12-02 09:25:04	ga_s2bm_ard_3-2-1_56JNM_2023-12-01_final
2023-12-02 09:25:08	ga_s2bm_ard_3-2-1_56JMM_2023-12-01_final
2023-12-02 09:25:19	ga_s2bm_ard_3-2-1_56JNL_2023-12-01_final
2023-12-02 09:25:22	ga_s2bm_ard_3-2-1_56JML_2023-12-01_final
2023-12-02 09:25:33	ga_s2bm_ard_3-2-1_56HNK_2023-12-01_nrt
2023-12-02 09:25:37	ga_s2bm_ard_3-2-1_56HMK_2023-12-01_final
2023-12-02 09:25:48	ga_s2bm_ard_3-2-1_56HNJ_2023-12-01_nrt
2023-12-02 09:25:51	ga_s2bm_ard_3-2-1_56HMJ_2023-12-01_final
2023-12-02 09:26:02	ga_s2bm_ard_3-2-1_56HNH_2023-12-01_nrt
2023-12-02 09:26:06	ga_s2bm_ard_3-2-1_56HMH_2023-12-01_nrt
2023-12-15 09:32:29	ga_s2bm_ard_3-2-1_56KMC_2023-12-15_nrt
2023-12-15 09:32:40	ga_s2bm_ard_3-2-1_56KMB_2023-12-15_final
2023-12-15 09:32:54	ga_s2bm_ard_3-2-1_56KMA_2023-12-15_final
2023-12-15 09:33:09	ga_s2bm_ard_3-2-1_56KMV_2023-12-15_nrt
2023-12-15 09:33:23	ga_s2bm_ard_3-2-1_56KMU_2023-12-15_final
2023-12-15 09:33:34	ga_s2bm_ard_3-2-1_56JNT_2023-12-15_final
2023-12-15 09:33:38	ga_s2bm_ard_3-2-1_56JMT_2023-12-15_final
2023-12-15 09:33:49	ga_s2bm_ard_3-2-1_56JNS_2023-12-15_final
2023-12-15 09:33:52	ga_s2bm_ard_3-2-1_56JMS_2023-12-15_final
2023-12-18 09:39:42	ga_s2bm_ard_3-2-1_56LMP_2023-12-18_nrt
2023-12-18 09:39:56	ga_s2bm_ard_3-2-1_56LMN_2023-12-18_nrt
2023-12-18 09:40:06	ga_s2bm_ard_3-2-1_56LMM_2023-12-18_nrt
2023-12-18 09:41:16	ga_s2bm_ard_3-2-1_56LMH_2023-12-18_nrt
2023-12-18 09:41:23	ga_s2bm_ard_3-2-1_56KMG_2023-12-18_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