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

88 results

Time (local)	Label
2022-12-28 10:29:39	ga_s2bm_ard_3-2-1_54LXQ_2022-12-28_final.stac-item
2022-12-28 10:30:11	ga_s2bm_ard_3-2-1_54LWN_2022-12-28_final.stac-item
2022-12-28 10:30:17	ga_s2bm_ard_3-2-1_54LXM_2022-12-28_final.stac-item
2022-12-28 10:30:25	ga_s2bm_ard_3-2-1_54LWM_2022-12-28_final.stac-item
2022-12-28 10:30:55	ga_s2bm_ard_3-2-1_54LWK_2022-12-28_final.stac-item
2022-12-28 10:31:09	ga_s2bm_ard_3-2-1_54LWJ_2022-12-28_final.stac-item
2022-12-28 10:31:21	ga_s2bm_ard_3-2-1_54LWH_2022-12-28_final.stac-item
2022-12-28 10:31:27	ga_s2bm_ard_3-2-1_54LVH_2022-12-28_final.stac-item
2022-12-28 10:31:30	ga_s2bm_ard_3-2-1_54LUH_2022-12-28_final.stac-item
2022-12-28 10:31:31	ga_s2bm_ard_3-2-1_54KWG_2022-12-28_final.stac-item
2022-12-28 10:31:41	ga_s2bm_ard_3-2-1_54KVG_2022-12-28_final.stac-item
2022-12-28 10:31:48	ga_s2bm_ard_3-2-1_54KTG_2022-12-28_final.stac-item
2022-12-28 10:31:56	ga_s2bm_ard_3-2-1_54KVF_2022-12-28_final.stac-item
2022-12-28 10:32:14	ga_s2bm_ard_3-2-1_54KUE_2022-12-28_final.stac-item
2022-12-28 10:32:17	ga_s2bm_ard_3-2-1_54KTE_2022-12-28_final.stac-item
2022-12-28 10:32:18	ga_s2bm_ard_3-2-1_53KRV_2022-12-28_final.stac-item
2022-12-28 10:32:32	ga_s2bm_ard_3-2-1_54KTD_2022-12-28_final.stac-item
2022-12-28 10:32:36	ga_s2bm_ard_3-2-1_53KQU_2022-12-28_final.stac-item
2022-12-28 10:32:46	ga_s2bm_ard_3-2-1_54KTC_2022-12-28_final.stac-item
2022-12-28 10:32:47	ga_s2bm_ard_3-2-1_53KRT_2022-12-28_final.stac-item
2022-12-28 10:32:51	ga_s2bm_ard_3-2-1_53KQT_2022-12-28_final.stac-item
2022-12-28 10:32:57	ga_s2bm_ard_3-2-1_54KUB_2022-12-28_final.stac-item
2022-12-28 10:33:01	ga_s2bm_ard_3-2-1_54KTB_2022-12-28_final.stac-item
2022-12-28 10:33:01	ga_s2bm_ard_3-2-1_53KRS_2022-12-28_final.stac-item
2022-12-28 10:33:12	ga_s2bm_ard_3-2-1_54KUA_2022-12-28_final.stac-item
2022-12-28 10:33:16	ga_s2bm_ard_3-2-1_53KRR_2022-12-28_final.stac-item
2022-12-28 10:33:27	ga_s2bm_ard_3-2-1_54KUV_2022-12-28_final.stac-item
2022-12-28 10:33:45	ga_s2bm_ard_3-2-1_54KTU_2022-12-28_final.stac-item
2022-12-28 10:33:59	ga_s2bm_ard_3-2-1_54JTT_2022-12-28_final.stac-item
2022-12-28 10:34:02	ga_s2bm_ard_3-2-1_53JQN_2022-12-28_final.stac-item
2022-12-28 10:34:10	ga_s2bm_ard_3-2-1_53JPN_2022-12-28_final.stac-item
2022-12-28 10:34:24	ga_s2bm_ard_3-2-1_53JNM_2022-12-28_final.stac-item
2022-12-28 10:34:28	ga_s2bm_ard_3-2-1_54JTR_2022-12-28_final.stac-item
2022-12-28 10:34:35	ga_s2bm_ard_3-2-1_53JPL_2022-12-28_final.stac-item
2022-12-28 10:35:00	ga_s2bm_ard_3-2-1_53JQJ_2022-12-28_final.stac-item
2022-12-28 10:35:04	ga_s2bm_ard_3-2-1_53JPJ_2022-12-28_final.stac-item
2022-12-28 10:35:08	ga_s2bm_ard_3-2-1_53JNJ_2022-12-28_final.stac-item
2022-12-28 10:35:35	ga_s2bm_ard_3-2-1_53JMG_2022-12-28_final.stac-item
2022-12-28 10:35:37	ga_s2bm_ard_3-2-1_53JQG_2022-12-28_final.stac-item
2022-12-28 10:35:39	ga_s2bm_ard_3-2-1_53JPG_2022-12-28_final.stac-item
2022-12-28 10:35:39	ga_s2bm_ard_3-2-1_53JPF_2022-12-28_final.stac-item
2022-12-28 10:35:42	ga_s2bm_ard_3-2-1_53JMG_2022-12-28_final.stac-item
2022-12-28 10:35:44	ga_s2bm_ard_3-2-1_53JQF_2022-12-28_final.stac-item
2022-12-28 10:36:02	ga_s2bm_ard_3-2-1_53HPE_2022-12-28_final.stac-item
2022-12-28 10:36:06	ga_s2bm_ard_3-2-1_53HNE_2022-12-28_final.stac-item
2022-12-28 10:36:09	ga_s2bm_ard_3-2-1_53HME_2022-12-28_final.stac-item
2022-12-28 10:36:20	ga_s2bm_ard_3-2-1_53HND_2022-12-28_final.stac-item
2022-12-28 10:36:31	ga_s2bm_ard_3-2-1_53HPC_2022-12-28_final.stac-item
2022-12-28 10:36:35	ga_s2bm_ard_3-2-1_53HNC_2022-12-28_final.stac-item
2022-12-28 10:36:45	ga_s2bm_ard_3-2-1_53HPB_2022-12-28_final.stac-item
2022-12-28 10:36:58	ga_s2bm_ard_3-2-1_53HPA_2022-12-28_final.stac-item
2022-12-28 12:13:39	ga_s2bm_ard_3-2-1_50KKB_2022-12-28_final.stac-item
2022-12-28 12:13:53	ga_s2bm_ard_3-2-1_50KKA_2022-12-28_final.stac-item
2022-12-28 12:13:54	ga_s2bm_ard_3-2-1_49KHR_2022-12-28_final.stac-item
2022-12-28 12:14:07	ga_s2bm_ard_3-2-1_50KKV_2022-12-28_final.stac-item
2022-12-28 12:14:26	ga_s2bm_ard_3-2-1_49KGP_2022-12-28_final.stac-item
2022-12-28 12:14:30	ga_s2bm_ard_3-2-1_49JHN_2022-12-28_final.stac-item
2022-12-28 12:14:40	ga_s2bm_ard_3-2-1_49JGN_2022-12-28_final.stac-item
2022-12-28 12:14:55	ga_s2bm_ard_3-2-1_49JGM_2022-12-28_final.stac-item
2022-12-28 12:15:10	ga_s2bm_ard_3-2-1_49JGL_2022-12-28_final.stac-item
2022-12-28 12:15:19	ga_s2bm_ard_3-2-1_49JGK_2022-12-28_final.stac-item
2023-01-09 09:33:18	ga_s2bm_ard_3-2-1_56KNU_2023-01-09_nrt.stac-item
2023-01-09 11:10:11	ga_s2bm_ard_3-2-1_52LGP_2023-01-09_nrt.stac-item
2023-01-09 11:10:32	ga_s2bm_ard_3-2-1_52LEN_2023-01-09_nrt.stac-item
2023-01-09 11:10:47	ga_s2bm_ard_3-2-1_52LEM_2023-01-09_nrt.stac-item
2023-01-09 11:16:48	ga_s2bm_ard_3-2-1_51HYC_2023-01-09_nrt.stac-item
2023-01-09 11:17:00	ga_s2bm_ard_3-2-1_51HYB_2023-01-09_nrt.stac-item
2023-01-10 10:39:55	ga_s2bm_ard_3-2-1_54LUP_2023-01-10_nrt.stac-item
2023-01-10 10:39:59	ga_s2bm_ard_3-2-1_54LTP_2023-01-10_nrt.stac-item
2023-01-10 10:40:00	ga_s2bm_ard_3-2-1_53LRJ_2023-01-10_nrt.stac-item
2023-01-10 10:40:04	ga_s2bm_ard_3-2-1_53LQJ_2023-01-10_nrt.stac-item
2023-01-10 10:40:10	ga_s2bm_ard_3-2-1_54LUN_2023-01-10_nrt.stac-item
2023-01-10 10:40:18	ga_s2bm_ard_3-2-1_53LQH_2023-01-10_nrt.stac-item
2023-01-10 10:40:24	ga_s2bm_ard_3-2-1_54LUM_2023-01-10_nrt.stac-item
2023-01-10 10:40:28	ga_s2bm_ard_3-2-1_54LTM_2023-01-10_nrt.stac-item
2023-01-10 10:40:29	ga_s2bm_ard_3-2-1_53LRG_2023-01-10_nrt.stac-item
2023-01-10 10:40:36	ga_s2bm_ard_3-2-1_54LUL_2023-01-10_nrt.stac-item
2023-01-10 10:40:42	ga_s2bm_ard_3-2-1_54LTL_2023-01-10_nrt.stac-item
2023-01-10 10:40:44	ga_s2bm_ard_3-2-1_53LRF_2023-01-10_nrt.stac-item
2023-01-10 10:40:57	ga_s2bm_ard_3-2-1_54LTK_2023-01-10_nrt.stac-item
2023-01-10 10:40:58	ga_s2bm_ard_3-2-1_53LRE_2023-01-10_nrt.stac-item
2023-01-10 10:41:13	ga_s2bm_ard_3-2-1_53LRD_2023-01-10_nrt.stac-item
2023-01-10 10:46:23	ga_s2bm_ard_3-2-1_53HKD_2023-01-10_nrt.stac-item
2023-01-10 10:46:24	ga_s2bm_ard_3-2-1_52HGJ_2023-01-10_nrt.stac-item
2023-01-10 10:46:29	ga_s2bm_ard_3-2-1_53HLC_2023-01-10_nrt.stac-item
2023-01-10 10:46:30	ga_s2bm_ard_3-2-1_52HFJ_2023-01-10_nrt.stac-item
2023-01-10 10:46:30	ga_s2bm_ard_3-2-1_53HKC_2023-01-10_nrt.stac-item
2023-01-10 10:46:31	ga_s2bm_ard_3-2-1_52HGH_2023-01-10_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years