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
2019-09-19 10:16:45	ga_s2bm_ard_3-2-1_54HUG_2019-09-19_final.stac-item
2019-09-19 10:16:48	ga_s2bm_ard_3-2-1_54HTG_2019-09-19_final.stac-item
2019-09-19 10:16:51	ga_s2bm_ard_3-2-1_53HQB_2019-09-19_final.stac-item
2019-09-19 10:16:51	ga_s2bm_ard_3-2-1_54HWF_2019-09-19_final.stac-item
2019-09-19 10:16:56	ga_s2bm_ard_3-2-1_54HVF_2019-09-19_final.stac-item
2019-09-19 10:16:59	ga_s2bm_ard_3-2-1_54HUF_2019-09-19_final.stac-item
2019-09-19 10:17:02	ga_s2bm_ard_3-2-1_54HTF_2019-09-19_final.stac-item
2019-09-19 10:17:03	ga_s2bm_ard_3-2-1_54HWE_2019-09-19_final.stac-item
2019-09-19 10:17:04	ga_s2bm_ard_3-2-1_53HQA_2019-09-19_final.stac-item
2019-09-19 10:17:10	ga_s2bm_ard_3-2-1_54HVE_2019-09-19_final.stac-item
2019-09-19 10:17:25	ga_s2bm_ard_3-2-1_54HVD_2019-09-19_final.stac-item
2019-09-19 11:51:12	ga_s2bm_ard_3-2-1_51LUF_2019-09-19_final.stac-item
2019-09-19 11:51:25	ga_s2bm_ard_3-2-1_51LUE_2019-09-19_final.stac-item
2019-09-19 11:51:32	ga_s2bm_ard_3-2-1_51LUE_2019-09-19_final.stac-item
2019-09-19 11:52:53	ga_s2bm_ard_3-2-1_51KTU_2019-09-19_final.stac-item
2019-09-19 11:52:58	ga_s2bm_ard_3-2-1_50KRD_2019-09-19_final.stac-item
2019-09-19 11:53:10	ga_s2bm_ard_3-2-1_50KRC_2019-09-19_final.stac-item
2019-09-19 11:53:16	ga_s2bm_ard_3-2-1_50KQC_2019-09-19_final.stac-item
2019-09-19 11:53:20	ga_s2bm_ard_3-2-1_50KPC_2019-09-19_final.stac-item
2019-09-19 11:53:23	ga_s2bm_ard_3-2-1_50KNC_2019-09-19_final.stac-item
2019-09-19 11:53:30	ga_s2bm_ard_3-2-1_50KMC_2019-09-19_final.stac-item
2019-09-19 11:53:31	ga_s2bm_ard_3-2-1_50KQB_2019-09-19_final.stac-item
2019-09-19 11:53:35	ga_s2bm_ard_3-2-1_50KPB_2019-09-19_final.stac-item
2019-09-19 11:53:38	ga_s2bm_ard_3-2-1_50KNB_2019-09-19_final.stac-item
2019-09-19 11:53:42	ga_s2bm_ard_3-2-1_50KMB_2019-09-19_final.stac-item
2019-09-19 11:53:45	ga_s2bm_ard_3-2-1_50KQA_2019-09-19_final.stac-item
2019-09-19 11:53:49	ga_s2bm_ard_3-2-1_50KPA_2019-09-19_final.stac-item
2019-09-19 11:53:52	ga_s2bm_ard_3-2-1_50KNA_2019-09-19_final.stac-item
2019-09-19 11:53:55	ga_s2bm_ard_3-2-1_50KMA_2019-09-19_final.stac-item
2019-09-19 11:54:00	ga_s2bm_ard_3-2-1_50KQV_2019-09-19_final.stac-item
2019-09-19 11:54:04	ga_s2bm_ard_3-2-1_50KPV_2019-09-19_final.stac-item
2019-09-19 11:54:07	ga_s2bm_ard_3-2-1_50KNV_2019-09-19_final.stac-item
2019-09-19 11:54:10	ga_s2bm_ard_3-2-1_50KMV_2019-09-19_final.stac-item
2019-09-19 11:54:12	ga_s2bm_ard_3-2-1_50KQU_2019-09-19_final.stac-item
2019-09-19 11:54:18	ga_s2bm_ard_3-2-1_50KPU_2019-09-19_final.stac-item
2019-09-19 11:54:22	ga_s2bm_ard_3-2-1_50KNU_2019-09-19_final.stac-item
2019-09-19 11:54:22	ga_s2bm_ard_3-2-1_50JQT_2019-09-19_final.stac-item
2019-09-19 11:54:25	ga_s2bm_ard_3-2-1_50KMU_2019-09-19_final.stac-item
2019-09-19 11:54:32	ga_s2bm_ard_3-2-1_50JPT_2019-09-19_final.stac-item
2019-09-19 11:54:33	ga_s2bm_ard_3-2-1_50KLU_2019-09-19_final.stac-item
2019-09-19 11:54:36	ga_s2bm_ard_3-2-1_50JNT_2019-09-19_final.stac-item
2019-09-19 11:54:39	ga_s2bm_ard_3-2-1_50JMT_2019-09-19_final.stac-item
2019-09-19 11:54:43	ga_s2bm_ard_3-2-1_50JLT_2019-09-19_final.stac-item
2019-09-19 11:54:47	ga_s2bm_ard_3-2-1_50JPS_2019-09-19_final.stac-item
2019-09-19 11:54:51	ga_s2bm_ard_3-2-1_50JNS_2019-09-19_final.stac-item
2019-09-19 11:54:54	ga_s2bm_ard_3-2-1_50JMS_2019-09-19_final.stac-item
2019-09-19 11:54:57	ga_s2bm_ard_3-2-1_50JLS_2019-09-19_final.stac-item
2019-09-19 11:55:01	ga_s2bm_ard_3-2-1_50JPR_2019-09-19_final.stac-item
2019-09-19 11:55:05	ga_s2bm_ard_3-2-1_50JNR_2019-09-19_final.stac-item
2019-09-19 11:55:09	ga_s2bm_ard_3-2-1_50JMR_2019-09-19_final.stac-item
2019-09-19 11:55:12	ga_s2bm_ard_3-2-1_50JLR_2019-09-19_final.stac-item
2019-09-19 11:55:15	ga_s2bm_ard_3-2-1_50JPQ_2019-09-19_final.stac-item
2019-09-19 11:55:19	ga_s2bm_ard_3-2-1_50JNQ_2019-09-19_final.stac-item
2019-09-19 11:55:23	ga_s2bm_ard_3-2-1_50JMQ_2019-09-19_final.stac-item
2019-09-19 11:55:25	ga_s2bm_ard_3-2-1_50JPP_2019-09-19_final.stac-item
2019-09-19 11:55:26	ga_s2bm_ard_3-2-1_50JLQ_2019-09-19_final.stac-item
2019-09-19 11:55:34	ga_s2bm_ard_3-2-1_50JNP_2019-09-19_final.stac-item
2019-09-19 11:55:38	ga_s2bm_ard_3-2-1_50JMP_2019-09-19_final.stac-item
2019-09-19 11:55:41	ga_s2bm_ard_3-2-1_50JLP_2019-09-19_final.stac-item
2019-09-19 11:55:45	ga_s2bm_ard_3-2-1_50JKP_2019-09-19_final.stac-item
2019-09-19 11:55:48	ga_s2bm_ard_3-2-1_50JNN_2019-09-19_final.stac-item
2019-09-19 11:55:52	ga_s2bm_ard_3-2-1_50JMN_2019-09-19_final.stac-item
2019-09-19 11:55:55	ga_s2bm_ard_3-2-1_50JLN_2019-09-19_final.stac-item
2019-09-19 11:55:58	ga_s2bm_ard_3-2-1_50JKN_2019-09-19_final.stac-item
2019-09-19 11:56:03	ga_s2bm_ard_3-2-1_50JNM_2019-09-19_final.stac-item
2019-09-19 11:56:07	ga_s2bm_ard_3-2-1_50JMM_2019-09-19_final.stac-item
2019-09-19 11:56:10	ga_s2bm_ard_3-2-1_50JLM_2019-09-19_final.stac-item
2019-09-19 11:56:13	ga_s2bm_ard_3-2-1_50JKM_2019-09-19_final.stac-item
2019-09-19 11:56:17	ga_s2bm_ard_3-2-1_50JNL_2019-09-19_final.stac-item
2019-09-19 11:56:21	ga_s2bm_ard_3-2-1_50JML_2019-09-19_final.stac-item
2019-09-19 11:56:25	ga_s2bm_ard_3-2-1_50JLL_2019-09-19_final.stac-item
2019-09-19 11:56:29	ga_s2bm_ard_3-2-1_50HNK_2019-09-19_final.stac-item
2019-09-19 11:56:35	ga_s2bm_ard_3-2-1_50HMK_2019-09-19_final.stac-item
2019-09-19 11:56:39	ga_s2bm_ard_3-2-1_50HLK_2019-09-19_final.stac-item
2019-09-19 11:56:50	ga_s2bm_ard_3-2-1_50HMJ_2019-09-19_final.stac-item
2019-09-19 11:56:54	ga_s2bm_ard_3-2-1_50HLJ_2019-09-19_final.stac-item
2019-09-19 11:57:05	ga_s2bm_ard_3-2-1_50HMH_2019-09-19_final.stac-item
2019-09-19 11:57:08	ga_s2bm_ard_3-2-1_50HLH_2019-09-19_final.stac-item
2019-09-20 09:46:40	ga_s2bm_ard_3-2-1_55HCB_2019-09-20_final.stac-item
2019-09-20 09:46:51	ga_s2bm_ard_3-2-1_55HCA_2019-09-20_final.stac-item
2019-09-20 09:47:21	ga_s2bm_ard_3-2-1_55HCU_2019-09-20_final.stac-item
2019-09-20 09:47:29	ga_s2bm_ard_3-2-1_55HBU_2019-09-20_final.stac-item
2019-09-20 09:47:35	ga_s2bm_ard_3-2-1_55HCT_2019-09-20_final.stac-item
2019-09-20 09:47:39	ga_s2bm_ard_3-2-1_55HBT_2019-09-20_final.stac-item
2019-09-20 09:47:44	ga_s2bm_ard_3-2-1_54HYC_2019-09-20_final.stac-item
2019-09-20 09:47:50	ga_s2bm_ard_3-2-1_55HCS_2019-09-20_final.stac-item
2019-09-20 09:47:53	ga_s2bm_ard_3-2-1_55HBS_2019-09-20_final.stac-item
2019-09-20 09:47:54	ga_s2bm_ard_3-2-1_54HYB_2019-09-20_final.stac-item
2019-09-20 09:47:57	ga_s2bm_ard_3-2-1_55GER_2019-09-20_final.stac-item
2019-09-20 09:48:01	ga_s2bm_ard_3-2-1_55GDR_2019-09-20_final.stac-item
2019-09-20 09:48:04	ga_s2bm_ard_3-2-1_55GCR_2019-09-20_final.stac-item
2019-09-20 09:48:08	ga_s2bm_ard_3-2-1_55GBR_2019-09-20_final.stac-item
2019-09-20 09:48:08	ga_s2bm_ard_3-2-1_54GYA_2019-09-20_final.stac-item
2019-09-20 09:48:11	ga_s2bm_ard_3-2-1_55GEQ_2019-09-20_final.stac-item
2019-09-20 09:48:15	ga_s2bm_ard_3-2-1_55GDQ_2019-09-20_final.stac-item
2019-09-20 09:48:19	ga_s2bm_ard_3-2-1_55GCQ_2019-09-20_final.stac-item
2019-09-20 09:48:21	ga_s2bm_ard_3-2-1_55GEP_2019-09-20_final.stac-item
2019-09-20 09:48:30	ga_s2bm_ard_3-2-1_55GDP_2019-09-20_final.stac-item
2019-09-20 09:48:34	ga_s2bm_ard_3-2-1_55GCP_2019-09-20_final.stac-item
2019-09-20 09:48:44	ga_s2bm_ard_3-2-1_55GDN_2019-09-20_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