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
2017-07-09 11:12:47	ga_s2bm_ard_3-2-1_52KEA_2017-07-09_final.stac-item
2017-07-31 11:49:45	ga_s2bm_ard_3-2-1_50KRC_2017-07-31_final.stac-item
2018-01-12 11:02:50	ga_s2bm_ard_3-2-1_52JBM_2018-01-12_final.stac-item
2018-01-15 11:07:04	ga_s2bm_ard_3-2-1_52LEH_2018-01-15_final.stac-item
2018-01-31 11:27:22	ga_s2bm_ard_3-2-1_51JVH_2018-01-31_final.stac-item
2018-03-10 10:47:15	ga_s2bm_ard_3-2-1_53JLH_2018-03-10_final.stac-item
2018-05-19 10:47:23	ga_s2bm_ard_3-2-1_53KLU_2018-05-19_final.stac-item
2018-05-30 12:02:46	ga_s2bm_ard_3-2-1_50JKS_2018-05-30_final.stac-item
2018-06-07 11:19:54	ga_s2bm_ard_3-2-1_51JZN_2018-06-07_final.stac-item
2018-07-22 10:31:03	ga_s2bm_ard_3-2-1_53JMF_2018-07-22_final.stac-item
2018-07-26 11:52:57	ga_s2bm_ard_3-2-1_50HLH_2018-07-26_final.stac-item
2018-08-04 10:40:09	ga_s2bm_ard_3-2-1_53HMD_2018-08-04_final.stac-item
2018-08-08 12:04:30	ga_s2bm_ard_3-2-1_50JKN_2018-08-08_final.stac-item
2018-09-21 11:40:23	ga_s2bm_ard_3-2-1_51KVT_2018-09-21_final.stac-item
2018-10-02 11:07:11	ga_s2bm_ard_3-2-1_52LGN_2018-10-02_final.stac-item
2018-11-11 11:14:53	ga_s2bm_ard_3-2-1_51JYL_2018-11-11_final.stac-item
2019-01-08 10:36:57	ga_s2bm_ard_3-2-1_53HPA_2019-01-08_final.stac-item
2019-04-17 11:06:29	ga_s2bm_ard_3-2-1_52HBK_2019-04-17_final.stac-item
2019-06-05 11:33:10	ga_s2bm_ard_3-2-1_51KYT_2019-06-05_final.stac-item
2019-10-06 11:46:41	ga_s2bm_ard_3-2-1_50HMK_2019-10-06_final.stac-item
2019-10-09 11:56:56	ga_s2bm_ard_3-2-1_50HLJ_2019-10-09_final.stac-item
2019-11-01 12:05:38	ga_s2bm_ard_3-2-1_50JLP_2019-11-01_final.stac-item
2019-12-01 10:26:50	ga_s2bm_ard_3-2-1_53HPB_2019-12-01_final.stac-item
2020-01-04 11:44:26	ga_s2bm_ard_3-2-1_50JRT_2020-01-04_final.stac-item
2020-01-26 10:46:17	ga_s2bm_ard_3-2-1_53HLD_2020-01-26_final.stac-item
2020-03-02 11:06:01	ga_s2bm_ard_3-2-1_52JDL_2020-03-02_final.stac-item
2020-04-16 10:16:48	ga_s2bm_ard_3-2-1_53HQB_2020-04-16_final.stac-item
2020-04-19 10:26:27	ga_s2bm_ard_3-2-1_53HQC_2020-04-19_final.stac-item
2020-05-20 11:33:30	ga_s2bm_ard_3-2-1_51KVS_2020-05-20_final.stac-item
2020-06-13 11:14:34	ga_s2bm_ard_3-2-1_52JDS_2020-06-13_final.stac-item
2020-07-02 11:43:53	ga_s2bm_ard_3-2-1_50KQA_2020-07-02_final.stac-item
2020-08-02 11:15:32	ga_s2bm_ard_3-2-1_51JXJ_2020-08-02_final.stac-item
2020-09-06 10:24:07	ga_s2bm_ard_3-2-1_53JRN_2020-09-06_final.stac-item
2020-10-05 10:55:57	ga_s2bm_ard_3-2-1_53JKF_2020-10-05_final.stac-item
2020-10-12 10:45:08	ga_s2bm_ard_3-2-1_53JNJ_2020-10-12_final.stac-item
2020-11-06 11:34:16	ga_s2bm_ard_3-2-1_51KVP_2020-11-06_final.stac-item
2020-11-30 11:14:46	ga_s2bm_ard_3-2-1_52JDR_2020-11-30_final.stac-item
2020-12-06 11:31:41	ga_s2bm_ard_3-2-1_51LXD_2020-12-06_final.stac-item
2020-12-06 11:32:18	ga_s2bm_ard_3-2-1_51KVB_2020-12-06_final.stac-item
2020-12-13 11:23:17	ga_s2bm_ard_3-2-1_52KBB_2020-12-13_final.stac-item
2021-01-05 11:31:58	ga_s2bm_ard_3-2-1_51KZB_2021-01-05_final.stac-item
2021-01-08 11:43:50	ga_s2bm_ard_3-2-1_50KQA_2021-01-08_final.stac-item
2021-04-08 11:46:35	ga_s2bm_ard_3-2-1_50HNK_2021-04-08_final.stac-item
2021-05-19 11:14:23	ga_s2bm_ard_3-2-1_52JBT_2021-05-19_final.stac-item
2021-07-13 12:04:23	ga_s2bm_ard_3-2-1_49KHP_2021-07-13_final.stac-item
2021-07-30 11:55:08	ga_s2bm_ard_3-2-1_50JNR_2021-07-30_final.stac-item
2021-08-10 11:25:17	ga_s2bm_ard_3-2-1_51JVK_2021-08-10_final.stac-item
2021-08-25 10:36:57	ga_s2bm_ard_3-2-1_53HPA_2021-08-25_final.stac-item
2021-09-22 11:33:36	ga_s2bm_ard_3-2-1_51KXR_2021-09-22_final.stac-item
2021-10-02 11:34:25	ga_s2bm_ard_3-2-1_51JWN_2021-10-02_final.stac-item
2021-10-21 12:05:18	ga_s2bm_ard_3-2-1_49JGL_2021-10-21_final.stac-item
2022-01-15 10:45:43	ga_s2bm_ard_3-2-1_52JGM_2022-01-15_final.stac-item
2022-02-23 11:10:32	ga_s2bm_ard_3-2-1_52LHM_2022-02-23_final.stac-item
2022-02-28 10:25:02	ga_s2bm_ard_3-2-1_53JQJ_2022-02-28_final.stac-item
2022-03-01 11:32:55	ga_s2bm_ard_3-2-1_51KWU_2022-03-01_final.stac-item
2022-03-08 11:23:37	ga_s2bm_ard_3-2-1_51KYR_2022-03-08_final.stac-item
2022-04-28 10:53:39	ga_s2bm_ard_3-2-1_52KGV_2022-04-28_final.stac-item
2022-05-04 11:13:39	ga_s2bm_ard_3-2-1_52KEV_2022-05-04_final.stac-item
2022-05-23 11:44:45	ga_s2bm_ard_3-2-1_50JRS_2022-05-23_final.stac-item
2022-05-30 11:34:29	ga_s2bm_ard_3-2-1_51JVN_2022-05-30_final.stac-item
2022-06-06 11:25:29	ga_s2bm_ard_3-2-1_51JWJ_2022-06-06_final.stac-item
2022-06-08 12:04:01	ga_s2bm_ard_3-2-1_49KHR_2022-06-08_final.stac-item
2022-06-30 11:05:28	ga_s2bm_ard_3-2-1_52JCP_2022-06-30_final.stac-item
2022-07-19 11:36:33	ga_s2bm_ard_3-2-1_51HUE_2022-07-19_final.stac-item
2022-09-03 11:55:40	ga_s2bm_ard_3-2-1_50JMP_2022-09-03_final.stac-item
2022-10-01 11:14:37	ga_s2bm_ard_3-2-1_51JZM_2022-10-01_final.stac-item
2022-10-31 11:16:18	ga_s2bm_ard_3-2-1_52HBK_2022-10-31_final.stac-item
2022-11-13 11:26:17	ga_s2bm_ard_3-2-1_51JUF_2022-11-13_final.stac-item
2022-12-15 12:05:13	ga_s2bm_ard_3-2-1_49JGL_2022-12-15_final.stac-item
2022-12-30 11:14:01	ga_s2bm_ard_3-2-1_52KDU_2022-12-30_final.stac-item
2023-01-02 11:23:38	ga_s2bm_ard_3-2-1_51KYR_2023-01-02_final.stac-item
2023-01-06 11:02:50	ga_s2bm_ard_3-2-1_52KED_2023-01-06_final.stac-item
2023-02-06 12:14:28	ga_s2bm_ard_3-2-1_49KFP_2023-02-06_nrt.stac-item
2023-02-22 10:53:14	ga_s2bm_ard_3-2-1_52KHB_2023-02-22_final
2023-02-25 11:03:10	ga_s2bm_ard_3-2-1_52KHB_2023-02-25_final
2023-03-04 10:51:59	ga_s2bm_ard_3-2-1_53KLB_2023-03-04_final
2023-03-07 11:02:37	ga_s2bm_ard_3-2-1_52KHD_2023-03-07_final
2023-03-29 11:44:38	ga_s2bm_ard_3-2-1_50JQT_2023-03-29_final
2023-04-10 10:44:37	ga_s2bm_ard_3-2-1_53JNL_2023-04-10_final
2023-04-12 11:22:13	ga_s2bm_ard_3-2-1_51KYB_2023-04-12_final
2023-04-13 10:54:12	ga_s2bm_ard_3-2-1_52JGT_2023-04-13_final
2023-05-16 11:06:03	ga_s2bm_ard_3-2-1_52JEL_2023-05-16_final
2023-05-17 10:36:55	ga_s2bm_ard_3-2-1_53HNB_2023-05-17_final
2023-05-22 11:25:11	ga_s2bm_ard_3-2-1_51JYK_2023-05-22_final
2023-05-27 12:14:35	ga_s2bm_ard_3-2-1_49KFP_2023-05-27_nrt
2023-06-30 11:57:17	ga_s2bm_ard_3-2-1_50HKH_2023-06-30_nrt
2023-07-23 12:04:05	ga_s2bm_ard_3-2-1_50KKA_2023-07-23_final
2023-10-22 11:36:35	ga_s2bm_ard_3-2-1_50HQK_2023-10-22_final
2023-10-24 12:14:15	ga_s2bm_ard_3-2-1_49KFQ_2023-10-24_nrt
2023-12-04 11:43:09	ga_s2bm_ard_3-2-1_51KVT_2023-12-04_final
2023-12-17 11:57:12	ga_s2bm_ard_3-2-1_50HKH_2023-12-17_nrt
2024-01-04 11:14:41	ga_s2bm_ard_3-2-1_51JYM_2024-01-04_final
2024-01-09 12:05:54	ga_s2bm_ard_3-2-1_50JKN_2024-01-09_final
2024-01-17 11:23:42	ga_s2bm_ard_3-2-1_51KXR_2024-01-17_final
2024-01-27 11:23:12	ga_s2bm_ard_3-2-1_51KZT_2024-01-27_final
2024-02-10 11:02:04	ga_s2bm_ard_3-2-1_52KFG_2024-02-10_final
2024-03-01 11:01:29	ga_s2bm_ard_3-2-1_52LGJ_2024-03-01_final
2024-03-04 11:10:34	ga_s2bm_ard_3-2-1_52LHM_2024-03-04_final
2024-03-12 10:36:25	ga_s2bm_ard_3-2-1_53HLD_2024-03-12_final
2024-03-13 11:41:56	ga_s2bm_ard_3-2-1_51LVC_2024-03-13_final

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