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
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56HLJ_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56HLK_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56HMJ_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56HMK_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JLL_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JLM_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JLN_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JLP_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JLQ_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JLR_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JLS_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JLT_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JML_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JMM_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56JMN_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56KLA_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56KLB_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56KLU_2018-09-02_final.stac-item
2018-09-02 09:32:31	ga_s2bm_ard_3-2-1_56KLV_2018-09-02_final.stac-item
2018-09-09 09:24:12	ga_s2bm_ard_3-2-1_56HLJ_2018-09-08_final.stac-item
2018-09-09 09:24:12	ga_s2bm_ard_3-2-1_56HLK_2018-09-08_final.stac-item
2018-09-09 09:24:12	ga_s2bm_ard_3-2-1_56HMJ_2018-09-08_final.stac-item
2018-09-09 09:24:12	ga_s2bm_ard_3-2-1_56HMK_2018-09-08_final.stac-item
2018-09-09 09:24:12	ga_s2bm_ard_3-2-1_56JLL_2018-09-08_final.stac-item
2018-09-09 09:24:12	ga_s2bm_ard_3-2-1_56JML_2018-09-08_final.stac-item
2018-10-02 09:32:35	ga_s2bm_ard_3-2-1_56JLR_2018-10-02_final.stac-item
2018-10-02 09:32:35	ga_s2bm_ard_3-2-1_56JLS_2018-10-02_final.stac-item
2018-10-02 09:32:35	ga_s2bm_ard_3-2-1_56JLT_2018-10-02_final.stac-item
2018-10-02 09:32:35	ga_s2bm_ard_3-2-1_56KLA_2018-10-02_final.stac-item
2018-10-02 09:32:35	ga_s2bm_ard_3-2-1_56KLB_2018-10-02_final.stac-item
2018-10-02 09:32:35	ga_s2bm_ard_3-2-1_56KLU_2018-10-02_final.stac-item
2018-10-02 09:32:35	ga_s2bm_ard_3-2-1_56KLV_2018-10-02_final.stac-item
2018-10-02 09:34:02	ga_s2bm_ard_3-2-1_56JLQ_2018-10-02_final.stac-item
2018-10-02 09:34:02	ga_s2bm_ard_3-2-1_56JLR_2018-10-02_final.stac-item
2018-10-05 09:41:04	ga_s2bm_ard_3-2-1_56KLA_2018-10-05_final.stac-item
2018-10-05 09:41:04	ga_s2bm_ard_3-2-1_56KLB_2018-10-05_final.stac-item
2018-10-05 09:41:04	ga_s2bm_ard_3-2-1_56KLD_2018-10-05_final.stac-item
2018-10-05 09:41:04	ga_s2bm_ard_3-2-1_56KLE_2018-10-05_final.stac-item
2018-10-05 09:41:04	ga_s2bm_ard_3-2-1_56KLF_2018-10-05_final.stac-item
2018-10-05 09:41:04	ga_s2bm_ard_3-2-1_56KLV_2018-10-05_final.stac-item
2018-10-09 09:22:40	ga_s2bm_ard_3-2-1_56HLJ_2018-10-08_final.stac-item
2018-10-09 09:22:40	ga_s2bm_ard_3-2-1_56HLK_2018-10-08_final.stac-item
2018-10-09 09:22:40	ga_s2bm_ard_3-2-1_56HMJ_2018-10-08_final.stac-item
2018-10-09 09:22:40	ga_s2bm_ard_3-2-1_56HMK_2018-10-08_final.stac-item
2018-10-09 09:22:40	ga_s2bm_ard_3-2-1_56JLL_2018-10-08_final.stac-item
2018-10-09 09:22:40	ga_s2bm_ard_3-2-1_56JML_2018-10-08_final.stac-item
2019-07-02 09:41:50	ga_s2bm_ard_3-2-1_56KLF_2019-07-02_final.stac-item
2019-07-02 09:42:05	ga_s2bm_ard_3-2-1_56KLE_2019-07-02_final.stac-item
2019-07-02 09:42:19	ga_s2bm_ard_3-2-1_56KLD_2019-07-02_final.stac-item
2019-07-02 09:42:48	ga_s2bm_ard_3-2-1_56KLB_2019-07-02_final.stac-item
2019-07-02 09:43:03	ga_s2bm_ard_3-2-1_56KLA_2019-07-02_final.stac-item
2019-07-02 09:43:17	ga_s2bm_ard_3-2-1_56KLV_2019-07-02_final.stac-item
2023-11-28 09:42:07	ga_s2bm_ard_3-2-1_56KLD_2023-11-28_final
2023-11-28 09:42:21	ga_s2bm_ard_3-2-1_56KLC_2023-11-28_nrt
2023-11-28 09:42:36	ga_s2bm_ard_3-2-1_56KLB_2023-11-28_final
2023-11-28 09:42:50	ga_s2bm_ard_3-2-1_56KLA_2023-11-28_final
2023-11-28 09:43:05	ga_s2bm_ard_3-2-1_56KLV_2023-11-28_final
2023-12-02 09:25:22	ga_s2bm_ard_3-2-1_56JML_2023-12-01_final
2023-12-02 09:25:27	ga_s2bm_ard_3-2-1_56JLL_2023-12-01_final
2023-12-02 09:25:37	ga_s2bm_ard_3-2-1_56HMK_2023-12-01_final
2023-12-02 09:25:40	ga_s2bm_ard_3-2-1_56HLK_2023-12-01_final
2023-12-02 09:25:51	ga_s2bm_ard_3-2-1_56HMJ_2023-12-01_final
2023-12-02 09:25:54	ga_s2bm_ard_3-2-1_56HLJ_2023-12-01_final
2023-12-02 09:26:06	ga_s2bm_ard_3-2-1_56HMH_2023-12-01_nrt
2023-12-28 09:40:01	ga_s2bm_ard_3-2-1_56LLN_2023-12-28_nrt
2023-12-28 09:40:09	ga_s2bm_ard_3-2-1_56LLM_2023-12-28_nrt
2023-12-28 09:41:18	ga_s2bm_ard_3-2-1_56LLH_2023-12-28_nrt
2023-12-28 09:41:28	ga_s2bm_ard_3-2-1_56KLG_2023-12-28_final
2023-12-28 09:41:43	ga_s2bm_ard_3-2-1_56KLF_2023-12-28_final
2023-12-28 09:41:57	ga_s2bm_ard_3-2-1_56KLE_2023-12-28_final
2023-12-28 09:42:12	ga_s2bm_ard_3-2-1_56KLD_2023-12-28_final
2023-12-28 09:42:26	ga_s2bm_ard_3-2-1_56KLC_2023-12-28_nrt
2023-12-28 09:42:41	ga_s2bm_ard_3-2-1_56KLB_2023-12-28_final
2023-12-28 09:42:55	ga_s2bm_ard_3-2-1_56KLA_2023-12-28_final
2023-12-28 09:43:10	ga_s2bm_ard_3-2-1_56KLV_2023-12-28_final
2023-12-31 09:49:41	ga_s2bm_ard_3-2-1_56LLP_2023-12-31_nrt
2024-01-01 09:26:09	ga_s2bm_ard_3-2-1_56HMH_2023-12-31_nrt
2024-01-01 09:26:24	ga_s2bm_ard_3-2-1_56HMG_2023-12-31_nrt
2024-01-01 09:26:39	ga_s2bm_ard_3-2-1_56HMF_2023-12-31_nrt
2024-01-01 09:26:42	ga_s2bm_ard_3-2-1_56HLF_2023-12-31_nrt
2024-01-01 09:26:53	ga_s2bm_ard_3-2-1_56HME_2023-12-31_nrt
2024-01-01 09:26:57	ga_s2bm_ard_3-2-1_56HLE_2023-12-31_nrt
2024-01-01 09:27:08	ga_s2bm_ard_3-2-1_56HMD_2023-12-31_nrt
2024-01-01 09:27:11	ga_s2bm_ard_3-2-1_56HLD_2023-12-31_nrt
2024-01-01 09:27:22	ga_s2bm_ard_3-2-1_56HMC_2023-12-31_nrt
2024-01-01 09:27:26	ga_s2bm_ard_3-2-1_56HLC_2023-12-31_nrt
2024-01-01 09:27:36	ga_s2bm_ard_3-2-1_56HMB_2023-12-31_nrt
2024-01-01 09:27:51	ga_s2bm_ard_3-2-1_56GMA_2023-12-31_nrt
2024-01-01 09:28:06	ga_s2bm_ard_3-2-1_56GMV_2023-12-31_nrt
2024-01-01 09:28:19	ga_s2bm_ard_3-2-1_56GMU_2023-12-31_nrt
2024-01-07 09:39:59	ga_s2bm_ard_3-2-1_56LLN_2024-01-07_nrt
2024-01-07 09:40:07	ga_s2bm_ard_3-2-1_56LLM_2024-01-07_nrt
2024-01-07 09:41:16	ga_s2bm_ard_3-2-1_56LLH_2024-01-07_nrt
2024-01-07 09:41:26	ga_s2bm_ard_3-2-1_56KLG_2024-01-07_final
2024-01-07 09:41:41	ga_s2bm_ard_3-2-1_56KLF_2024-01-07_final
2024-01-07 09:41:55	ga_s2bm_ard_3-2-1_56KLE_2024-01-07_final
2024-01-07 09:42:10	ga_s2bm_ard_3-2-1_56KLD_2024-01-07_final
2024-01-07 09:42:24	ga_s2bm_ard_3-2-1_56KLC_2024-01-07_nrt
2024-01-07 09:42:39	ga_s2bm_ard_3-2-1_56KLB_2024-01-07_final
2024-01-07 09:42:53	ga_s2bm_ard_3-2-1_56KLA_2024-01-07_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