Search ga_s2bm_ard_3 on 11th December 2019

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
2019-12-11 10:20:12	ga_s2bm_ard_3-2-1_54LWN_2019-12-11_final.stac-item
2019-12-11 10:20:25	ga_s2bm_ard_3-2-1_54LWM_2019-12-11_final.stac-item
2019-12-11 10:20:37	ga_s2bm_ard_3-2-1_54LXL_2019-12-11_final.stac-item
2019-12-11 10:20:40	ga_s2bm_ard_3-2-1_54LWL_2019-12-11_final.stac-item
2019-12-11 10:20:51	ga_s2bm_ard_3-2-1_54LXK_2019-12-11_final.stac-item
2019-12-11 10:20:55	ga_s2bm_ard_3-2-1_54LWK_2019-12-11_final.stac-item
2019-12-11 10:21:06	ga_s2bm_ard_3-2-1_54LXJ_2019-12-11_final.stac-item
2019-12-11 10:21:09	ga_s2bm_ard_3-2-1_54LWJ_2019-12-11_final.stac-item
2019-12-11 10:21:20	ga_s2bm_ard_3-2-1_54LXH_2019-12-11_final.stac-item
2019-12-11 10:21:23	ga_s2bm_ard_3-2-1_54LWH_2019-12-11_final.stac-item
2019-12-11 10:21:27	ga_s2bm_ard_3-2-1_54LVH_2019-12-11_final.stac-item
2019-12-11 10:21:31	ga_s2bm_ard_3-2-1_54KYG_2019-12-11_final.stac-item
2019-12-11 10:21:35	ga_s2bm_ard_3-2-1_54KXG_2019-12-11_final.stac-item
2019-12-11 10:21:38	ga_s2bm_ard_3-2-1_54KWG_2019-12-11_final.stac-item
2019-12-11 10:21:41	ga_s2bm_ard_3-2-1_54KVG_2019-12-11_final.stac-item
2019-12-11 10:21:45	ga_s2bm_ard_3-2-1_54KYF_2019-12-11_final.stac-item
2019-12-11 10:21:49	ga_s2bm_ard_3-2-1_54KXF_2019-12-11_final.stac-item
2019-12-11 10:21:53	ga_s2bm_ard_3-2-1_54KWF_2019-12-11_final.stac-item
2019-12-11 10:21:56	ga_s2bm_ard_3-2-1_54KVF_2019-12-11_final.stac-item
2019-12-11 10:21:58	ga_s2bm_ard_3-2-1_54KYE_2019-12-11_final.stac-item
2019-12-11 10:22:04	ga_s2bm_ard_3-2-1_54KXE_2019-12-11_final.stac-item
2019-12-11 10:22:07	ga_s2bm_ard_3-2-1_54KWE_2019-12-11_final.stac-item
2019-12-11 10:22:08	ga_s2bm_ard_3-2-1_54KYD_2019-12-11_final.stac-item
2019-12-11 10:22:11	ga_s2bm_ard_3-2-1_54KVE_2019-12-11_final.stac-item
2019-12-11 10:22:18	ga_s2bm_ard_3-2-1_54KXD_2019-12-11_final.stac-item
2019-12-11 10:22:22	ga_s2bm_ard_3-2-1_54KWD_2019-12-11_final.stac-item
2019-12-11 10:22:25	ga_s2bm_ard_3-2-1_54KVD_2019-12-11_final.stac-item
2019-12-11 10:22:29	ga_s2bm_ard_3-2-1_54KUD_2019-12-11_final.stac-item
2019-12-11 10:22:33	ga_s2bm_ard_3-2-1_54KXC_2019-12-11_final.stac-item
2019-12-11 10:22:36	ga_s2bm_ard_3-2-1_54KWC_2019-12-11_final.stac-item
2019-12-11 10:22:39	ga_s2bm_ard_3-2-1_54KVC_2019-12-11_final.stac-item
2019-12-11 10:22:42	ga_s2bm_ard_3-2-1_54KUC_2019-12-11_final.stac-item
2019-12-11 10:22:47	ga_s2bm_ard_3-2-1_54KXB_2019-12-11_final.stac-item
2019-12-11 10:22:51	ga_s2bm_ard_3-2-1_54KWB_2019-12-11_final.stac-item
2019-12-11 10:22:54	ga_s2bm_ard_3-2-1_54KVB_2019-12-11_final.stac-item
2019-12-11 10:22:57	ga_s2bm_ard_3-2-1_54KUB_2019-12-11_final.stac-item
2019-12-11 10:23:01	ga_s2bm_ard_3-2-1_54KXA_2019-12-11_final.stac-item
2019-12-11 10:23:05	ga_s2bm_ard_3-2-1_54KWA_2019-12-11_final.stac-item
2019-12-11 10:23:09	ga_s2bm_ard_3-2-1_54KVA_2019-12-11_final.stac-item
2019-12-11 10:23:12	ga_s2bm_ard_3-2-1_54KXV_2019-12-11_final.stac-item
2019-12-11 10:23:12	ga_s2bm_ard_3-2-1_54KUA_2019-12-11_final.stac-item
2019-12-11 10:23:19	ga_s2bm_ard_3-2-1_54KWV_2019-12-11_final.stac-item
2019-12-11 10:23:23	ga_s2bm_ard_3-2-1_54KVV_2019-12-11_final.stac-item
2019-12-11 10:23:26	ga_s2bm_ard_3-2-1_54KUV_2019-12-11_final.stac-item
2019-12-11 10:23:31	ga_s2bm_ard_3-2-1_54KTV_2019-12-11_final.stac-item
2019-12-11 10:23:34	ga_s2bm_ard_3-2-1_54KWU_2019-12-11_final.stac-item
2019-12-11 10:23:38	ga_s2bm_ard_3-2-1_54KVU_2019-12-11_final.stac-item
2019-12-11 10:23:41	ga_s2bm_ard_3-2-1_54KUU_2019-12-11_final.stac-item
2019-12-11 10:23:44	ga_s2bm_ard_3-2-1_54KTU_2019-12-11_final.stac-item
2019-12-11 10:23:45	ga_s2bm_ard_3-2-1_53KRP_2019-12-11_final.stac-item
2019-12-11 10:23:49	ga_s2bm_ard_3-2-1_54JWT_2019-12-11_final.stac-item
2019-12-11 10:23:52	ga_s2bm_ard_3-2-1_54JVT_2019-12-11_final.stac-item
2019-12-11 10:23:56	ga_s2bm_ard_3-2-1_54JUT_2019-12-11_final.stac-item
2019-12-11 10:23:58	ga_s2bm_ard_3-2-1_53JRN_2019-12-11_final.stac-item
2019-12-11 10:23:58	ga_s2bm_ard_3-2-1_54JTT_2019-12-11_final.stac-item
2019-12-11 10:24:03	ga_s2bm_ard_3-2-1_54JWS_2019-12-11_final.stac-item
2019-12-11 10:26:45	ga_s2bm_ard_3-2-1_54HUF_2019-12-11_final.stac-item
2019-12-11 10:26:48	ga_s2bm_ard_3-2-1_53HNB_2019-12-11_final.stac-item
2019-12-11 10:26:53	ga_s2bm_ard_3-2-1_54HTF_2019-12-11_final.stac-item
2019-12-11 10:26:55	ga_s2bm_ard_3-2-1_53HQA_2019-12-11_final.stac-item
2019-12-11 10:26:59	ga_s2bm_ard_3-2-1_53HPA_2019-12-11_final.stac-item
2019-12-11 12:03:14	ga_s2bm_ard_3-2-1_50KNC_2019-12-11_final.stac-item
2019-12-11 12:03:17	ga_s2bm_ard_3-2-1_50KMC_2019-12-11_final.stac-item
2019-12-11 12:03:21	ga_s2bm_ard_3-2-1_50KLC_2019-12-11_final.stac-item
2019-12-11 12:03:27	ga_s2bm_ard_3-2-1_50KNB_2019-12-11_final.stac-item
2019-12-11 12:03:32	ga_s2bm_ard_3-2-1_50KMB_2019-12-11_final.stac-item
2019-12-11 12:03:35	ga_s2bm_ard_3-2-1_50KLB_2019-12-11_final.stac-item
2019-12-11 12:03:38	ga_s2bm_ard_3-2-1_50KKB_2019-12-11_final.stac-item
2019-12-11 12:03:39	ga_s2bm_ard_3-2-1_50KNA_2019-12-11_final.stac-item
2019-12-11 12:03:46	ga_s2bm_ard_3-2-1_50KMA_2019-12-11_final.stac-item
2019-12-11 12:03:50	ga_s2bm_ard_3-2-1_50KLA_2019-12-11_final.stac-item
2019-12-11 12:03:53	ga_s2bm_ard_3-2-1_50KKA_2019-12-11_final.stac-item
2019-12-11 12:03:53	ga_s2bm_ard_3-2-1_49KHR_2019-12-11_final.stac-item
2019-12-11 12:04:01	ga_s2bm_ard_3-2-1_50KMV_2019-12-11_final.stac-item
2019-12-11 12:04:04	ga_s2bm_ard_3-2-1_50KLV_2019-12-11_final.stac-item
2019-12-11 12:04:07	ga_s2bm_ard_3-2-1_50KKV_2019-12-11_final.stac-item
2019-12-11 12:04:08	ga_s2bm_ard_3-2-1_49KHQ_2019-12-11_final.stac-item
2019-12-11 12:04:12	ga_s2bm_ard_3-2-1_49KGQ_2019-12-11_final.stac-item
2019-12-11 12:04:16	ga_s2bm_ard_3-2-1_50KMU_2019-12-11_final.stac-item
2019-12-11 12:04:19	ga_s2bm_ard_3-2-1_50KLU_2019-12-11_final.stac-item
2019-12-11 12:04:22	ga_s2bm_ard_3-2-1_49KHP_2019-12-11_final.stac-item
2019-12-11 12:04:22	ga_s2bm_ard_3-2-1_50KKU_2019-12-11_final.stac-item
2019-12-11 12:04:25	ga_s2bm_ard_3-2-1_49KGP_2019-12-11_final.stac-item
2019-12-11 12:04:30	ga_s2bm_ard_3-2-1_50JMT_2019-12-11_final.stac-item
2019-12-11 12:04:34	ga_s2bm_ard_3-2-1_50JLT_2019-12-11_final.stac-item
2019-12-11 12:04:37	ga_s2bm_ard_3-2-1_49JHN_2019-12-11_final.stac-item
2019-12-11 12:04:37	ga_s2bm_ard_3-2-1_50JKT_2019-12-11_final.stac-item
2019-12-11 12:04:40	ga_s2bm_ard_3-2-1_49JGN_2019-12-11_final.stac-item
2019-12-11 12:04:43	ga_s2bm_ard_3-2-1_50JMS_2019-12-11_final.stac-item
2019-12-11 12:04:48	ga_s2bm_ard_3-2-1_50JLS_2019-12-11_final.stac-item
2019-12-11 12:04:51	ga_s2bm_ard_3-2-1_49JHM_2019-12-11_final.stac-item
2019-12-11 12:04:51	ga_s2bm_ard_3-2-1_50JKS_2019-12-11_final.stac-item
2019-12-11 12:04:53	ga_s2bm_ard_3-2-1_50JMR_2019-12-11_final.stac-item
2019-12-11 12:04:55	ga_s2bm_ard_3-2-1_49JGM_2019-12-11_final.stac-item
2019-12-11 12:05:02	ga_s2bm_ard_3-2-1_50JLR_2019-12-11_final.stac-item
2019-12-11 12:05:06	ga_s2bm_ard_3-2-1_50JKR_2019-12-11_final.stac-item
2019-12-11 12:05:09	ga_s2bm_ard_3-2-1_49JGL_2019-12-11_final.stac-item
2019-12-11 12:05:17	ga_s2bm_ard_3-2-1_50JLQ_2019-12-11_final.stac-item
2019-12-11 12:05:20	ga_s2bm_ard_3-2-1_50JKQ_2019-12-11_final.stac-item
2019-12-11 12:05:23	ga_s2bm_ard_3-2-1_49JGK_2019-12-11_final.stac-item

Return to ga_s2bm_ard_3 on 11th December 2019 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

2019

December

11th