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
2019-11-03 11:04:25	ga_s2bm_ard_3-2-1_52JGS_2019-11-03_final.stac-item
2019-11-03 11:04:29	ga_s2bm_ard_3-2-1_52JFS_2019-11-03_final.stac-item
2019-11-03 11:04:33	ga_s2bm_ard_3-2-1_52JES_2019-11-03_final.stac-item
2019-11-03 11:04:36	ga_s2bm_ard_3-2-1_52JGR_2019-11-03_final.stac-item
2019-11-03 11:04:36	ga_s2bm_ard_3-2-1_52JDS_2019-11-03_final.stac-item
2019-11-03 11:04:43	ga_s2bm_ard_3-2-1_52JFR_2019-11-03_final.stac-item
2019-11-03 11:04:47	ga_s2bm_ard_3-2-1_52JER_2019-11-03_final.stac-item
2019-11-03 11:04:51	ga_s2bm_ard_3-2-1_52JDR_2019-11-03_final.stac-item
2019-11-03 11:04:56	ga_s2bm_ard_3-2-1_52JCR_2019-11-03_final.stac-item
2019-11-03 11:04:58	ga_s2bm_ard_3-2-1_52JFQ_2019-11-03_final.stac-item
2019-11-03 11:05:02	ga_s2bm_ard_3-2-1_52JEQ_2019-11-03_final.stac-item
2019-11-03 11:05:05	ga_s2bm_ard_3-2-1_52JDQ_2019-11-03_final.stac-item
2019-11-03 11:05:09	ga_s2bm_ard_3-2-1_52JCQ_2019-11-03_final.stac-item
2019-11-03 11:05:13	ga_s2bm_ard_3-2-1_52JFP_2019-11-03_final.stac-item
2019-11-03 11:05:16	ga_s2bm_ard_3-2-1_52JEP_2019-11-03_final.stac-item
2019-11-03 11:05:20	ga_s2bm_ard_3-2-1_52JDP_2019-11-03_final.stac-item
2019-11-03 11:05:23	ga_s2bm_ard_3-2-1_52JCP_2019-11-03_final.stac-item
2019-11-03 11:05:27	ga_s2bm_ard_3-2-1_52JFN_2019-11-03_final.stac-item
2019-11-03 11:05:31	ga_s2bm_ard_3-2-1_52JEN_2019-11-03_final.stac-item
2019-11-03 11:05:34	ga_s2bm_ard_3-2-1_52JDN_2019-11-03_final.stac-item
2019-11-03 11:05:38	ga_s2bm_ard_3-2-1_52JCN_2019-11-03_final.stac-item
2019-11-03 11:05:39	ga_s2bm_ard_3-2-1_52JFM_2019-11-03_final.stac-item
2019-11-03 11:05:45	ga_s2bm_ard_3-2-1_52JEM_2019-11-03_final.stac-item
2019-11-03 11:05:49	ga_s2bm_ard_3-2-1_52JDM_2019-11-03_final.stac-item
2019-11-03 11:05:52	ga_s2bm_ard_3-2-1_52JCM_2019-11-03_final.stac-item
2019-11-03 11:05:59	ga_s2bm_ard_3-2-1_52JBM_2019-11-03_final.stac-item
2019-11-03 11:06:00	ga_s2bm_ard_3-2-1_52JEL_2019-11-03_final.stac-item
2019-11-03 11:06:03	ga_s2bm_ard_3-2-1_52JDL_2019-11-03_final.stac-item
2019-11-03 11:06:07	ga_s2bm_ard_3-2-1_52JCL_2019-11-03_final.stac-item
2019-11-03 11:06:10	ga_s2bm_ard_3-2-1_52JBL_2019-11-03_final.stac-item
2019-11-03 11:06:24	ga_s2bm_ard_3-2-1_52HBK_2019-11-03_final.stac-item
2019-11-03 11:06:37	ga_s2bm_ard_3-2-1_51HYD_2019-11-03_final.stac-item
2019-11-04 10:29:40	ga_s2bm_ard_3-2-1_54LXQ_2019-11-04_final.stac-item
2019-11-04 10:29:54	ga_s2bm_ard_3-2-1_54LXP_2019-11-04_final.stac-item
2019-11-04 10:30:08	ga_s2bm_ard_3-2-1_54LXN_2019-11-04_final.stac-item
2019-11-04 10:30:12	ga_s2bm_ard_3-2-1_54LWN_2019-11-04_final.stac-item
2019-11-04 10:30:18	ga_s2bm_ard_3-2-1_54LXM_2019-11-04_final.stac-item
2019-11-04 10:30:26	ga_s2bm_ard_3-2-1_54LWM_2019-11-04_final.stac-item
2019-11-04 10:30:41	ga_s2bm_ard_3-2-1_54LWL_2019-11-04_final.stac-item
2019-11-04 10:30:56	ga_s2bm_ard_3-2-1_54LWK_2019-11-04_final.stac-item
2019-11-04 10:31:10	ga_s2bm_ard_3-2-1_54LWJ_2019-11-04_final.stac-item
2019-11-04 10:31:23	ga_s2bm_ard_3-2-1_54LWH_2019-11-04_final.stac-item
2019-11-04 10:31:28	ga_s2bm_ard_3-2-1_54LVH_2019-11-04_final.stac-item
2019-11-04 10:31:31	ga_s2bm_ard_3-2-1_54LUH_2019-11-04_final.stac-item
2019-11-04 10:31:32	ga_s2bm_ard_3-2-1_54KWG_2019-11-04_final.stac-item
2019-11-04 10:31:42	ga_s2bm_ard_3-2-1_54KVG_2019-11-04_final.stac-item
2019-11-04 10:31:46	ga_s2bm_ard_3-2-1_54KUG_2019-11-04_final.stac-item
2019-11-04 10:31:49	ga_s2bm_ard_3-2-1_54KTG_2019-11-04_final.stac-item
2019-11-04 10:31:50	ga_s2bm_ard_3-2-1_53KRB_2019-11-04_final
2019-11-04 10:31:57	ga_s2bm_ard_3-2-1_54KVF_2019-11-04_final.stac-item
2019-11-04 10:32:00	ga_s2bm_ard_3-2-1_54KUF_2019-11-04_final.stac-item
2019-11-04 10:32:04	ga_s2bm_ard_3-2-1_54KTF_2019-11-04_final.stac-item
2019-11-04 10:32:05	ga_s2bm_ard_3-2-1_53KRA_2019-11-04_final.stac-item
2019-11-04 10:32:11	ga_s2bm_ard_3-2-1_53KQA_2019-11-04_final.stac-item
2019-11-04 10:32:12	ga_s2bm_ard_3-2-1_54KVE_2019-11-04_final.stac-item
2019-11-04 10:32:15	ga_s2bm_ard_3-2-1_54KUE_2019-11-04_final.stac-item
2019-11-04 10:32:18	ga_s2bm_ard_3-2-1_54KTE_2019-11-04_final.stac-item
2019-11-04 10:32:19	ga_s2bm_ard_3-2-1_53KRV_2019-11-04_final.stac-item
2019-11-04 10:32:23	ga_s2bm_ard_3-2-1_53KQV_2019-11-04_final.stac-item
2019-11-04 10:32:25	ga_s2bm_ard_3-2-1_54KVD_2019-11-04_final.stac-item
2019-11-04 10:32:30	ga_s2bm_ard_3-2-1_54KUD_2019-11-04_final.stac-item
2019-11-04 10:32:33	ga_s2bm_ard_3-2-1_54KTD_2019-11-04_final.stac-item
2019-11-04 10:32:34	ga_s2bm_ard_3-2-1_53KRU_2019-11-04_final.stac-item
2019-11-04 10:32:37	ga_s2bm_ard_3-2-1_53KQU_2019-11-04_final.stac-item
2019-11-04 10:32:37	ga_s2bm_ard_3-2-1_54KVC_2019-11-04_final.stac-item
2019-11-04 10:32:44	ga_s2bm_ard_3-2-1_54KUC_2019-11-04_final.stac-item
2019-11-04 10:32:47	ga_s2bm_ard_3-2-1_54KTC_2019-11-04_final.stac-item
2019-11-04 10:32:48	ga_s2bm_ard_3-2-1_53KRT_2019-11-04_final.stac-item
2019-11-04 10:32:52	ga_s2bm_ard_3-2-1_53KQT_2019-11-04_final.stac-item
2019-11-04 10:32:58	ga_s2bm_ard_3-2-1_54KUB_2019-11-04_final.stac-item
2019-11-04 10:33:02	ga_s2bm_ard_3-2-1_54KTB_2019-11-04_final.stac-item
2019-11-04 10:33:02	ga_s2bm_ard_3-2-1_53KRS_2019-11-04_final.stac-item
2019-11-04 10:33:06	ga_s2bm_ard_3-2-1_53KQS_2019-11-04_final.stac-item
2019-11-04 10:33:12	ga_s2bm_ard_3-2-1_53KPS_2019-11-04_final.stac-item
2019-11-04 10:33:13	ga_s2bm_ard_3-2-1_54KUA_2019-11-04_final.stac-item
2019-11-04 10:33:16	ga_s2bm_ard_3-2-1_54KTA_2019-11-04_final.stac-item
2019-11-04 10:33:16	ga_s2bm_ard_3-2-1_53KRR_2019-11-04_final.stac-item
2019-11-04 10:33:18	ga_s2bm_ard_3-2-1_53KQR_2019-11-04_final.stac-item
2019-11-04 10:33:20	ga_s2bm_ard_3-2-1_53KPR_2019-11-04_final.stac-item
2019-11-04 10:33:21	ga_s2bm_ard_3-2-1_54KUA_2019-11-04_final.stac-item
2019-11-04 10:33:21	ga_s2bm_ard_3-2-1_54KUV_2019-11-04_final.stac-item
2019-11-04 10:33:22	ga_s2bm_ard_3-2-1_53KRQ_2019-11-04_final.stac-item
2019-11-04 10:33:22	ga_s2bm_ard_3-2-1_54KTV_2019-11-04_final.stac-item
2019-11-04 10:33:22	ga_s2bm_ard_3-2-1_53KRR_2019-11-04_final.stac-item
2019-11-04 10:33:22	ga_s2bm_ard_3-2-1_54KTA_2019-11-04_final.stac-item
2019-11-04 10:33:24	ga_s2bm_ard_3-2-1_53KQR_2019-11-04_final.stac-item
2019-11-04 10:33:26	ga_s2bm_ard_3-2-1_53KPR_2019-11-04_final.stac-item
2019-11-04 10:33:28	ga_s2bm_ard_3-2-1_54KUV_2019-11-04_final.stac-item
2019-11-04 10:33:31	ga_s2bm_ard_3-2-1_54KTV_2019-11-04_final.stac-item
2019-11-04 10:33:31	ga_s2bm_ard_3-2-1_53KRQ_2019-11-04_final.stac-item
2019-11-04 10:33:35	ga_s2bm_ard_3-2-1_53KQQ_2019-11-04_final.stac-item
2019-11-04 10:33:38	ga_s2bm_ard_3-2-1_53KPQ_2019-11-04_final.stac-item
2019-11-04 10:33:41	ga_s2bm_ard_3-2-1_54KUU_2019-11-04_final.stac-item
2019-11-04 10:33:46	ga_s2bm_ard_3-2-1_54KTU_2019-11-04_final.stac-item
2019-11-04 10:33:46	ga_s2bm_ard_3-2-1_53KRP_2019-11-04_final.stac-item
2019-11-04 10:33:49	ga_s2bm_ard_3-2-1_53KQP_2019-11-04_final.stac-item
2019-11-04 10:36:17	ga_s2bm_ard_3-2-1_53HLE_2019-11-04_final.stac-item
2019-11-04 10:36:29	ga_s2bm_ard_3-2-1_53HLD_2019-11-04_final.stac-item
2019-11-04 10:36:46	ga_s2bm_ard_3-2-1_53HPB_2019-11-04_final.stac-item
2019-11-04 10:36:50	ga_s2bm_ard_3-2-1_53HNB_2019-11-04_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