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
2017-09-27 11:12:00	ga_s2bm_ard_3-2-1_52KCU_2017-09-27_final.stac-item
2017-12-15 11:37:37	ga_s2bm_ard_3-2-1_50JPR_2017-12-15_final.stac-item
2018-01-11 11:27:21	ga_s2bm_ard_3-2-1_51LYC_2018-01-11_final.stac-item
2018-01-21 11:30:33	ga_s2bm_ard_3-2-1_51JTH_2018-01-21_final.stac-item
2018-02-13 11:37:45	ga_s2bm_ard_3-2-1_51LWC_2018-02-13_final.stac-item
2018-05-11 11:26:19	ga_s2bm_ard_3-2-1_51KXV_2018-05-11_final.stac-item
2018-06-06 11:51:08	ga_s2bm_ard_3-2-1_50JNT_2018-06-06_final.stac-item
2018-06-21 11:03:15	ga_s2bm_ard_3-2-1_52JCN_2018-06-21_final.stac-item
2018-08-23 11:12:48	ga_s2bm_ard_3-2-1_51JYG_2018-08-23_final.stac-item
2018-09-01 11:35:18	ga_s2bm_ard_3-2-1_50JML_2018-09-01_final.stac-item
2018-10-08 11:30:50	ga_s2bm_ard_3-2-1_51KXR_2018-10-08_final.stac-item
2018-10-22 11:07:23	ga_s2bm_ard_3-2-1_52LDH_2018-10-22_final.stac-item
2019-01-20 11:11:27	ga_s2bm_ard_3-2-1_52LGJ_2019-01-20_final.stac-item
2019-02-09 11:13:40	ga_s2bm_ard_3-2-1_51KZR_2019-02-09_final.stac-item
2019-03-01 11:16:39	ga_s2bm_ard_3-2-1_51HXD_2019-03-01_final.stac-item
2019-03-21 11:13:14	ga_s2bm_ard_3-2-1_52KBC_2019-03-21_final.stac-item
2019-03-21 11:15:38	ga_s2bm_ard_3-2-1_51JYH_2019-03-21_final.stac-item
2019-04-03 11:23:41	ga_s2bm_ard_3-2-1_51KYR_2019-04-03_final.stac-item
2019-06-17 12:14:10	ga_s2bm_ard_3-2-1_49KHR_2019-06-17_final.stac-item
2019-06-21 11:53:47	ga_s2bm_ard_3-2-1_50KNB_2019-06-21_final.stac-item
2019-07-17 12:15:28	ga_s2bm_ard_3-2-1_49JGK_2019-07-17_final.stac-item
2019-08-03 12:06:17	ga_s2bm_ard_3-2-1_50JKM_2019-08-03_final.stac-item
2019-08-24 11:33:00	ga_s2bm_ard_3-2-1_51KXU_2019-08-24_final.stac-item
2019-09-23 11:31:29	ga_s2bm_ard_3-2-1_52LBJ_2019-09-23_final.stac-item
2020-02-04 11:11:27	ga_s2bm_ard_3-2-1_52LEJ_2020-02-04_final.stac-item
2020-03-07 11:56:20	ga_s2bm_ard_3-2-1_50JML_2020-03-07_final.stac-item
2020-03-25 11:13:38	ga_s2bm_ard_3-2-1_51KZR_2020-03-25_final.stac-item
2020-04-07 11:26:41	ga_s2bm_ard_3-2-1_51HVD_2020-04-07_final.stac-item
2020-04-11 11:03:01	ga_s2bm_ard_3-2-1_52KEC_2020-04-11_final.stac-item
2020-04-13 11:47:06	ga_s2bm_ard_3-2-1_50HMH_2020-04-13_final.stac-item
2020-05-11 11:04:49	ga_s2bm_ard_3-2-1_52JDR_2020-05-11_final.stac-item
2020-05-30 11:33:46	ga_s2bm_ard_3-2-1_51KVR_2020-05-30_final.stac-item
2020-07-01 12:14:00	ga_s2bm_ard_3-2-1_49KGR_2020-07-01_final.stac-item
2020-07-19 11:34:16	ga_s2bm_ard_3-2-1_51KVP_2020-07-19_final.stac-item
2020-08-27 12:04:45	ga_s2bm_ard_3-2-1_49JHN_2020-08-27_final.stac-item
2020-09-10 11:46:15	ga_s2bm_ard_3-2-1_50JMM_2020-09-10_final.stac-item
2020-10-05 10:56:04	ga_s2bm_ard_3-2-1_52JFL_2020-10-05_final.stac-item
2020-10-29 12:14:16	ga_s2bm_ard_3-2-1_49KGQ_2020-10-29_final.stac-item
2020-10-30 11:43:28	ga_s2bm_ard_3-2-1_51KVS_2020-10-30_final.stac-item
2021-01-12 11:25:20	ga_s2bm_ard_3-2-1_51JYJ_2021-01-12_final.stac-item
2021-01-22 11:21:47	ga_s2bm_ard_3-2-1_52LDH_2021-01-22_final.stac-item
2021-01-29 11:10:57	ga_s2bm_ard_3-2-1_52LGL_2021-01-29_final.stac-item
2021-03-16 11:32:54	ga_s2bm_ard_3-2-1_51KXU_2021-03-16_final.stac-item
2021-03-20 11:12:52	ga_s2bm_ard_3-2-1_52KCD_2021-03-20_final.stac-item
2021-04-01 11:57:07	ga_s2bm_ard_3-2-1_50HLH_2021-04-01_final.stac-item
2021-04-13 10:53:17	ga_s2bm_ard_3-2-1_52KGB_2021-04-13_final.stac-item
2021-05-02 11:23:31	ga_s2bm_ard_3-2-1_52KBA_2021-05-02_final.stac-item
2021-05-05 11:36:35	ga_s2bm_ard_3-2-1_50HPK_2021-05-05_final.stac-item
2021-05-06 11:03:17	ga_s2bm_ard_3-2-1_52KEB_2021-05-06_final.stac-item
2021-06-30 11:56:15	ga_s2bm_ard_3-2-1_50JKM_2021-06-30_final.stac-item
2021-07-28 11:10:39	ga_s2bm_ard_3-2-1_52LHM_2021-07-28_final.stac-item
2021-09-02 11:34:22	ga_s2bm_ard_3-2-1_51JWN_2021-09-02_final.stac-item
2021-10-20 10:56:05	ga_s2bm_ard_3-2-1_52JEL_2021-10-20_final.stac-item
2022-01-14 11:11:44	ga_s2bm_ard_3-2-1_52LEH_2022-01-14_final.stac-item
2022-01-18 10:55:23	ga_s2bm_ard_3-2-1_52JGN_2022-01-18_final.stac-item
2022-03-02 11:05:55	ga_s2bm_ard_3-2-1_52JBM_2022-03-02_final.stac-item
2022-04-01 11:04:13	ga_s2bm_ard_3-2-1_52JGT_2022-04-01_final.stac-item
2022-04-03 11:43:33	ga_s2bm_ard_3-2-1_51KVR_2022-04-03_final.stac-item
2022-05-01 11:03:54	ga_s2bm_ard_3-2-1_52KFU_2022-05-01_final.stac-item
2022-05-31 11:04:03	ga_s2bm_ard_3-2-1_52KEU_2022-05-31_final.stac-item
2022-06-27 10:52:36	ga_s2bm_ard_3-2-1_52KHE_2022-06-27_final.stac-item
2022-07-28 12:04:53	ga_s2bm_ard_3-2-1_50JMS_2022-07-28_final.stac-item
2022-08-20 12:15:01	ga_s2bm_ard_3-2-1_49JFM_2022-08-20_final.stac-item
2022-09-04 11:24:31	ga_s2bm_ard_3-2-1_51JWN_2022-09-04_final.stac-item
2022-09-10 11:45:16	ga_s2bm_ard_3-2-1_51JTK_2022-09-10_final.stac-item
2022-09-11 11:14:40	ga_s2bm_ard_3-2-1_52JBS_2022-09-11_final.stac-item
2022-11-13 11:26:58	ga_s2bm_ard_3-2-1_51HVC_2022-11-13_final.stac-item
2022-11-16 11:33:27	ga_s2bm_ard_3-2-1_51KWS_2022-11-16_final.stac-item
2022-12-07 11:04:44	ga_s2bm_ard_3-2-1_52JER_2022-12-07_final.stac-item
2022-12-16 11:36:41	ga_s2bm_ard_3-2-1_51HUD_2022-12-16_final.stac-item
2023-01-03 10:53:44	ga_s2bm_ard_3-2-1_52KGV_2023-01-03_final.stac-item
2023-01-29 11:10:55	ga_s2bm_ard_3-2-1_52LGL_2023-01-29_final.stac-item
2023-02-01 11:22:49	ga_s2bm_ard_3-2-1_51KZU_2023-02-01_final.stac-item
2023-02-21 11:23:06	ga_s2bm_ard_3-2-1_52KBC_2023-02-21_final
2023-03-26 11:34:42	ga_s2bm_ard_3-2-1_51JWM_2023-03-26_final
2023-04-03 10:54:51	ga_s2bm_ard_3-2-1_52JFR_2023-04-03_final
2023-04-06 11:06:27	ga_s2bm_ard_3-2-1_52HBK_2023-04-06_final
2023-04-18 11:43:23	ga_s2bm_ard_3-2-1_50KQC_2023-04-18_final
2023-04-24 12:05:53	ga_s2bm_ard_3-2-1_50JLN_2023-04-24_final
2023-05-15 11:33:06	ga_s2bm_ard_3-2-1_51KYT_2023-05-15_final
2023-06-21 11:24:48	ga_s2bm_ard_3-2-1_52JBR_2023-06-21_final
2023-06-27 11:46:05	ga_s2bm_ard_3-2-1_50JQM_2023-06-27_final
2023-07-02 10:53:37	ga_s2bm_ard_3-2-1_52KGA_2023-07-02_final
2023-07-05 11:03:54	ga_s2bm_ard_3-2-1_52KEV_2023-07-05_final
2023-07-31 11:23:06	ga_s2bm_ard_3-2-1_51KXU_2023-07-31_final
2023-08-13 11:35:50	ga_s2bm_ard_3-2-1_51JUH_2023-08-13_final
2023-08-14 11:04:41	ga_s2bm_ard_3-2-1_52JDS_2023-08-14_final
2023-08-16 11:45:17	ga_s2bm_ard_3-2-1_50JNR_2023-08-16_final
2023-08-16 11:47:01	ga_s2bm_ard_3-2-1_50HMJ_2023-08-16_final
2023-09-22 11:31:10	ga_s2bm_ard_3-2-1_51LZF_2023-09-22_nrt
2023-10-02 11:32:21	ga_s2bm_ard_3-2-1_51KVB_2023-10-02_final
2023-11-29 10:52:28	ga_s2bm_ard_3-2-1_52KHE_2023-11-29_final
2023-11-29 10:54:26	ga_s2bm_ard_3-2-1_52JGS_2023-11-29_final
2024-01-08 10:55:45	ga_s2bm_ard_3-2-1_52JFM_2024-01-08_final
2024-01-21 11:02:28	ga_s2bm_ard_3-2-1_52KHE_2024-01-21_final
2024-01-27 11:22:03	ga_s2bm_ard_3-2-1_52KCG_2024-01-27_final
2024-02-06 11:22:08	ga_s2bm_ard_3-2-1_51KZB_2024-02-06_final
2024-02-21 12:14:09	ga_s2bm_ard_3-2-1_49KFQ_2024-02-21_nrt
2024-03-08 10:54:06	ga_s2bm_ard_3-2-1_52JHT_2024-03-08_final
2024-03-14 11:11:13	ga_s2bm_ard_3-2-1_52LFK_2024-03-14_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

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