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The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

71 results

Time (local)	Label
2023-01-18 09:59:41	ga_s2bm_ard_3-2-1_55LGJ_2023-01-18_nrt.stac-item
2023-01-18 09:59:55	ga_s2bm_ard_3-2-1_55LGH_2023-01-18_nrt.stac-item
2023-01-18 10:00:02	ga_s2bm_ard_3-2-1_55LEH_2023-01-18_nrt.stac-item
2023-01-18 10:00:13	ga_s2bm_ard_3-2-1_55LFG_2023-01-18_nrt.stac-item
2023-01-18 10:00:46	ga_s2bm_ard_3-2-1_55LEE_2023-01-18_nrt.stac-item
2023-01-18 10:00:57	ga_s2bm_ard_3-2-1_55LFD_2023-01-18_nrt.stac-item
2023-01-18 10:01:00	ga_s2bm_ard_3-2-1_55LED_2023-01-18_nrt.stac-item
2023-01-18 10:01:04	ga_s2bm_ard_3-2-1_55LDD_2023-01-18_nrt.stac-item
2023-01-18 10:01:18	ga_s2bm_ard_3-2-1_55LDC_2023-01-18_nrt.stac-item
2023-01-18 11:40:22	ga_s2bm_ard_3-2-1_51LXJ_2023-01-18_nrt.stac-item
2023-01-18 11:40:25	ga_s2bm_ard_3-2-1_51LWJ_2023-01-18_nrt.stac-item
2023-01-18 11:40:29	ga_s2bm_ard_3-2-1_51LVJ_2023-01-18_nrt.stac-item
2023-01-18 11:40:32	ga_s2bm_ard_3-2-1_51LUJ_2023-01-18_nrt.stac-item
2023-01-18 11:40:36	ga_s2bm_ard_3-2-1_51LXH_2023-01-18_nrt.stac-item
2023-01-18 11:40:40	ga_s2bm_ard_3-2-1_51LWH_2023-01-18_nrt.stac-item
2023-01-18 11:40:43	ga_s2bm_ard_3-2-1_51LVH_2023-01-18_nrt.stac-item
2023-01-18 11:40:46	ga_s2bm_ard_3-2-1_51LUH_2023-01-18_nrt.stac-item
2023-01-18 11:40:51	ga_s2bm_ard_3-2-1_51LXG_2023-01-18_nrt.stac-item
2023-01-18 11:41:01	ga_s2bm_ard_3-2-1_51LUG_2023-01-18_nrt.stac-item
2023-01-18 11:41:04	ga_s2bm_ard_3-2-1_51LXF_2023-01-18_nrt.stac-item
2023-01-18 11:41:09	ga_s2bm_ard_3-2-1_51LWF_2023-01-18_nrt.stac-item
2023-01-18 11:41:15	ga_s2bm_ard_3-2-1_51LXE_2023-01-18_nrt.stac-item
2023-01-18 11:41:35	ga_s2bm_ard_3-2-1_51LTE_2023-01-18_nrt.stac-item
2023-01-18 11:41:38	ga_s2bm_ard_3-2-1_51LWD_2023-01-18_nrt.stac-item
2023-01-18 11:41:41	ga_s2bm_ard_3-2-1_51LVD_2023-01-18_nrt.stac-item
2023-01-18 11:41:48	ga_s2bm_ard_3-2-1_51LTD_2023-01-18_nrt.stac-item
2023-01-18 11:42:02	ga_s2bm_ard_3-2-1_51LTC_2023-01-18_nrt.stac-item
2023-01-18 11:42:05	ga_s2bm_ard_3-2-1_50LRH_2023-01-18_nrt.stac-item
2023-01-18 11:42:17	ga_s2bm_ard_3-2-1_51KTB_2023-01-18_nrt.stac-item
2023-01-18 11:42:18	ga_s2bm_ard_3-2-1_50KRG_2023-01-18_nrt.stac-item
2023-01-18 11:42:31	ga_s2bm_ard_3-2-1_51KTA_2023-01-18_nrt.stac-item
2023-01-18 11:42:32	ga_s2bm_ard_3-2-1_50KRF_2023-01-18_nrt.stac-item
2023-01-18 11:42:46	ga_s2bm_ard_3-2-1_51KTV_2023-01-18_nrt.stac-item
2023-01-18 11:42:47	ga_s2bm_ard_3-2-1_50KRE_2023-01-18_nrt.stac-item
2023-01-18 11:47:27	ga_s2bm_ard_3-2-1_50HPF_2023-01-18_nrt.stac-item
2023-01-18 11:47:29	ga_s2bm_ard_3-2-1_50HNF_2023-01-18_nrt.stac-item
2023-01-18 11:47:31	ga_s2bm_ard_3-2-1_50HMF_2023-01-18_nrt.stac-item
2023-01-18 11:47:32	ga_s2bm_ard_3-2-1_50HLF_2023-01-18_nrt.stac-item
2023-01-19 09:29:38	ga_s2bm_ard_3-2-1_56LPP_2023-01-18_nrt.stac-item
2023-01-19 09:29:52	ga_s2bm_ard_3-2-1_56LPN_2023-01-18_nrt.stac-item
2023-01-19 09:30:03	ga_s2bm_ard_3-2-1_56LPM_2023-01-19_nrt.stac-item
2023-01-19 09:31:23	ga_s2bm_ard_3-2-1_56KPG_2023-01-19_nrt.stac-item
2023-01-19 09:31:25	ga_s2bm_ard_3-2-1_56KNG_2023-01-19_nrt.stac-item
2023-01-19 09:31:30	ga_s2bm_ard_3-2-1_56KPF_2023-01-19_nrt.stac-item
2023-01-19 09:31:31	ga_s2bm_ard_3-2-1_56KNF_2023-01-19_nrt.stac-item
2023-01-19 09:32:26	ga_s2bm_ard_3-2-1_56KNC_2023-01-19_nrt.stac-item
2023-01-19 09:32:27	ga_s2bm_ard_3-2-1_56KMC_2023-01-19_nrt.stac-item
2023-01-19 09:32:46	ga_s2bm_ard_3-2-1_56KPA_2023-01-19_nrt.stac-item
2023-01-19 09:33:01	ga_s2bm_ard_3-2-1_56KPV_2023-01-19_nrt.stac-item
2023-01-19 09:33:07	ga_s2bm_ard_3-2-1_56KMV_2023-01-19_nrt.stac-item
2023-01-19 09:33:15	ga_s2bm_ard_3-2-1_56KPU_2023-01-19_nrt.stac-item
2023-01-19 09:33:28	ga_s2bm_ard_3-2-1_56JPT_2023-01-19_nrt.stac-item
2023-01-19 09:33:38	ga_s2bm_ard_3-2-1_56JPS_2023-01-19_nrt.stac-item
2023-01-19 09:35:56	ga_s2bm_ard_3-2-1_56HMH_2023-01-19_nrt.stac-item
2023-01-19 09:36:35	ga_s2bm_ard_3-2-1_56HLF_2023-01-19_nrt.stac-item
2023-01-19 09:36:49	ga_s2bm_ard_3-2-1_56HLE_2023-01-19_nrt.stac-item
2023-01-19 09:36:52	ga_s2bm_ard_3-2-1_56HKE_2023-01-19_nrt.stac-item
2023-01-19 09:37:01	ga_s2bm_ard_3-2-1_56HLD_2023-01-19_nrt.stac-item
2023-01-19 09:37:07	ga_s2bm_ard_3-2-1_56HKD_2023-01-19_nrt.stac-item
2023-01-19 09:37:11	ga_s2bm_ard_3-2-1_56HLC_2023-01-19_nrt.stac-item
2023-01-19 09:37:21	ga_s2bm_ard_3-2-1_56HKC_2023-01-19_nrt.stac-item
2023-01-19 09:37:22	ga_s2bm_ard_3-2-1_55HGT_2023-01-19_nrt.stac-item
2023-01-19 09:37:36	ga_s2bm_ard_3-2-1_56HKB_2023-01-19_nrt.stac-item
2023-01-19 09:37:37	ga_s2bm_ard_3-2-1_55HGS_2023-01-19_nrt.stac-item
2023-01-19 09:37:51	ga_s2bm_ard_3-2-1_56GKA_2023-01-19_nrt.stac-item
2023-01-19 09:37:51	ga_s2bm_ard_3-2-1_55GGR_2023-01-19_nrt.stac-item
2023-01-19 09:38:05	ga_s2bm_ard_3-2-1_56GKV_2023-01-19_nrt.stac-item
2023-01-19 09:38:05	ga_s2bm_ard_3-2-1_55GGQ_2023-01-19_nrt.stac-item
2023-01-19 09:38:17	ga_s2bm_ard_3-2-1_55GGP_2023-01-19_nrt.stac-item
2023-01-19 09:38:18	ga_s2bm_ard_3-2-1_56GKU_2023-01-19_nrt.stac-item
2023-01-19 09:38:53	ga_s2bm_ard_3-2-1_55GFM_2023-01-19_nrt.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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years