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
2017-12-05 11:40:37	ga_s2bm_ard_3-2-1_50JQS_2017-12-05_final.stac-item
2018-01-01 11:30:30	ga_s2bm_ard_3-2-1_51KVB_2018-01-01_final.stac-item
2018-01-14 11:46:06	ga_s2bm_ard_3-2-1_50HLH_2018-01-14_final.stac-item
2018-01-21 11:30:33	ga_s2bm_ard_3-2-1_51KVU_2018-01-21_final.stac-item
2018-02-03 11:40:42	ga_s2bm_ard_3-2-1_51KUV_2018-02-03_final.stac-item
2018-03-02 11:33:20	ga_s2bm_ard_3-2-1_50HQH_2018-03-02_final.stac-item
2018-03-05 11:42:06	ga_s2bm_ard_3-2-1_51KTU_2018-03-05_final.stac-item
2018-03-11 12:02:40	ga_s2bm_ard_3-2-1_50JKP_2018-03-11_final.stac-item
2018-03-12 11:29:59	ga_s2bm_ard_3-2-1_51KWT_2018-03-12_final.stac-item
2018-03-15 11:39:58	ga_s2bm_ard_3-2-1_51KVS_2018-03-15_final.stac-item
2018-03-15 11:39:58	ga_s2bm_ard_3-2-1_51KVU_2018-03-15_final.stac-item
2018-03-29 11:23:39	ga_s2bm_ard_3-2-1_51JVF_2018-03-29_final.stac-item
2018-04-01 11:30:00	ga_s2bm_ard_3-2-1_50JQP_2018-04-01_final.stac-item
2018-04-04 11:45:38	ga_s2bm_ard_3-2-1_50HNJ_2018-04-04_final.stac-item
2018-04-04 11:45:38	ga_s2bm_ard_3-2-1_50JNP_2018-04-04_final.stac-item
2018-04-04 11:45:38	ga_s2bm_ard_3-2-1_50JPN_2018-04-04_final.stac-item
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JKN_2018-04-07_final.stac-item
2018-04-07 11:53:07	ga_s2bm_ard_3-2-1_50JKP_2018-04-07_final.stac-item
2018-04-08 11:24:02	ga_s2bm_ard_3-2-1_51HUE_2018-04-08_final.stac-item
2018-04-11 11:30:56	ga_s2bm_ard_3-2-1_50HPK_2018-04-11_final.stac-item
2018-04-24 11:41:02	ga_s2bm_ard_3-2-1_50JPP_2018-04-24_final.stac-item
2018-04-24 11:41:02	ga_s2bm_ard_3-2-1_50KPU_2018-04-24_final.stac-item
2018-05-21 11:31:10	ga_s2bm_ard_3-2-1_51KWU_2018-05-21_final.stac-item
2018-06-13 11:37:58	ga_s2bm_ard_3-2-1_51KVS_2018-06-13_final.stac-item
2018-07-30 11:31:34	ga_s2bm_ard_3-2-1_51KWS_2018-07-30_final.stac-item
2018-08-09 11:30:50	ga_s2bm_ard_3-2-1_51KUT_2018-08-09_final.stac-item
2018-09-18 11:30:06	ga_s2bm_ard_3-2-1_51KWA_2018-09-18_final.stac-item
2018-10-01 11:38:19	ga_s2bm_ard_3-2-1_50KRD_2018-10-01_final.stac-item
2018-10-08 11:30:50	ga_s2bm_ard_3-2-1_51KWU_2018-10-08_final.stac-item
2018-10-28 11:31:46	ga_s2bm_ard_3-2-1_51KVS_2018-10-28_final.stac-item
2018-11-30 11:43:10	ga_s2bm_ard_3-2-1_51KUT_2018-11-30_final.stac-item
2018-12-20 11:43:10	ga_s2bm_ard_3-2-1_51KUT_2018-12-20_final.stac-item
2019-01-23 11:23:57	ga_s2bm_ard_3-2-1_51KXQ_2019-01-23_final.stac-item
2019-03-17 11:33:11	ga_s2bm_ard_3-2-1_51KWT_2019-03-17_final.stac-item
2019-03-17 11:33:20	ga_s2bm_ard_3-2-1_51KUT_2019-03-17_final.stac-item
2019-03-20 11:42:12	ga_s2bm_ard_3-2-1_51KVB_2019-03-20_final.stac-item
2019-05-16 11:33:36	ga_s2bm_ard_3-2-1_51KWS_2019-05-16_final.stac-item
2019-05-26 11:37:11	ga_s2bm_ard_3-2-1_50HQH_2019-05-26_final.stac-item
2019-10-26 11:43:16	ga_s2bm_ard_3-2-1_51KUT_2019-10-26_final.stac-item
2020-01-18 11:24:09	ga_s2bm_ard_3-2-1_51KWP_2020-01-18_final.stac-item
2020-06-12 11:43:05	ga_s2bm_ard_3-2-1_51KTU_2020-06-12_final.stac-item
2020-07-02 11:42:59	ga_s2bm_ard_3-2-1_51KVU_2020-07-02_final.stac-item
2020-07-16 11:23:58	ga_s2bm_ard_3-2-1_51KXQ_2020-07-16_final.stac-item
2020-08-18 11:33:31	ga_s2bm_ard_3-2-1_51KWS_2020-08-18_final.stac-item
2020-08-18 11:34:00	ga_s2bm_ard_3-2-1_51KWQ_2020-08-18_final.stac-item
2020-09-17 11:33:32	ga_s2bm_ard_3-2-1_51KVS_2020-09-17_final.stac-item
2020-09-26 12:05:58	ga_s2bm_ard_3-2-1_50JKN_2020-09-26_final.stac-item
2020-10-20 11:42:20	ga_s2bm_ard_3-2-1_51KUB_2020-10-20_final
2021-01-08 11:43:17	ga_s2bm_ard_3-2-1_50KRC_2021-01-08_final.stac-item
2021-02-17 11:43:09	ga_s2bm_ard_3-2-1_51KVT_2021-02-17_final.stac-item
2021-04-08 11:43:22	ga_s2bm_ard_3-2-1_51KVS_2021-04-08_final.stac-item
2021-05-12 11:26:34	ga_s2bm_ard_3-2-1_51HXD_2021-05-12_final.stac-item
2021-06-11 11:23:58	ga_s2bm_ard_3-2-1_51KXQ_2021-06-11_final.stac-item
2021-06-14 11:32:48	ga_s2bm_ard_3-2-1_51KVV_2021-06-14_final.stac-item
2021-06-14 11:33:35	ga_s2bm_ard_3-2-1_51KUS_2021-06-14_final.stac-item
2021-06-17 11:47:28	ga_s2bm_ard_3-2-1_50HLG_2021-06-17_final
2021-06-24 11:34:11	ga_s2bm_ard_3-2-1_51KWP_2021-06-24_final.stac-item
2021-07-04 11:33:35	ga_s2bm_ard_3-2-1_51KUS_2021-07-04_final.stac-item
2021-07-17 11:43:05	ga_s2bm_ard_3-2-1_51KTU_2021-07-17_final.stac-item
2021-07-24 11:37:19	ga_s2bm_ard_3-2-1_50HQG_2021-07-24_final
2021-07-30 11:57:25	ga_s2bm_ard_3-2-1_50HLG_2021-07-30_final
2021-08-13 11:37:21	ga_s2bm_ard_3-2-1_50HPG_2021-08-13_final
2021-08-20 11:23:56	ga_s2bm_ard_3-2-1_51KXQ_2021-08-20_final.stac-item
2021-08-23 11:33:15	ga_s2bm_ard_3-2-1_51KVT_2021-08-23_final.stac-item
2021-10-22 11:33:54	ga_s2bm_ard_3-2-1_51KXQ_2021-10-22_final.stac-item
2021-12-21 11:36:41	ga_s2bm_ard_3-2-1_51HTD_2021-12-21_final.stac-item
2022-02-19 11:33:07	ga_s2bm_ard_3-2-1_51KWT_2022-02-19_final.stac-item
2022-03-04 11:43:00	ga_s2bm_ard_3-2-1_51KTU_2022-03-04_final.stac-item
2022-04-17 11:23:39	ga_s2bm_ard_3-2-1_51KXR_2022-04-17_final.stac-item
2022-05-07 11:23:39	ga_s2bm_ard_3-2-1_51KXR_2022-05-07_final.stac-item
2022-05-13 11:42:15	ga_s2bm_ard_3-2-1_51KUB_2022-05-13_final
2022-06-26 11:24:07	ga_s2bm_ard_3-2-1_51KWQ_2022-06-26_final.stac-item
2022-07-09 11:33:06	ga_s2bm_ard_3-2-1_51KVU_2022-07-09_final.stac-item
2022-07-09 11:34:04	ga_s2bm_ard_3-2-1_51KVQ_2022-07-09_final.stac-item
2022-07-29 11:33:47	ga_s2bm_ard_3-2-1_51KWR_2022-07-29_final.stac-item
2022-09-17 11:33:32	ga_s2bm_ard_3-2-1_51KVS_2022-09-17_final.stac-item
2022-09-27 11:33:02	ga_s2bm_ard_3-2-1_51KVU_2022-09-27_final.stac-item
2022-12-06 11:33:42	ga_s2bm_ard_3-2-1_51KVR_2022-12-06_final.stac-item
2023-03-15 12:03:49	ga_s2bm_ard_3-2-1_49KHS_2023-03-15_final
2023-04-01 11:56:14	ga_s2bm_ard_3-2-1_50JLM_2023-04-01_final
2023-04-25 11:33:32	ga_s2bm_ard_3-2-1_51KVS_2023-04-25_final
2023-05-12 11:24:00	ga_s2bm_ard_3-2-1_51KXQ_2023-05-12_final
2023-05-15 11:33:31	ga_s2bm_ard_3-2-1_51KWS_2023-05-15_final
2023-05-25 11:33:50	ga_s2bm_ard_3-2-1_51KVR_2023-05-25_final
2023-05-25 11:34:04	ga_s2bm_ard_3-2-1_51KVQ_2023-05-25_final
2023-06-24 11:33:26	ga_s2bm_ard_3-2-1_51KUT_2023-06-24_final
2023-08-12 12:03:50	ga_s2bm_ard_3-2-1_49KHS_2023-08-12_final
2023-08-13 11:32:25	ga_s2bm_ard_3-2-1_51KVB_2023-08-13_final
2023-08-16 11:42:51	ga_s2bm_ard_3-2-1_51KUV_2023-08-16_final
2023-09-02 11:33:32	ga_s2bm_ard_3-2-1_51KWS_2023-09-02_final
2023-10-05 11:43:25	ga_s2bm_ard_3-2-1_51KVS_2023-10-05_final
2023-12-04 11:43:04	ga_s2bm_ard_3-2-1_51KUU_2023-12-04_final
2023-12-27 11:52:20	ga_s2bm_ard_3-2-1_50KQG_2023-12-27_final
2024-01-03 11:43:25	ga_s2bm_ard_3-2-1_51KUS_2024-01-03_final
2024-01-20 11:33:52	ga_s2bm_ard_3-2-1_51KXQ_2024-01-20_final
2024-01-30 11:32:59	ga_s2bm_ard_3-2-1_51KVU_2024-01-30_final
2024-02-02 11:43:08	ga_s2bm_ard_3-2-1_51KVT_2024-02-02_final
2024-02-05 11:57:18	ga_s2bm_ard_3-2-1_50HMG_2024-02-05_final
2024-03-17 11:26:53	ga_s2bm_ard_3-2-1_51HWC_2024-03-17_final
2024-03-20 11:33:52	ga_s2bm_ard_3-2-1_51KXQ_2024-03-20_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