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
2019-04-28 10:35:22	ga_s2bm_ard_3-2-1_53JMJ_2019-04-28_final.stac-item
2019-04-28 10:35:34	ga_s2bm_ard_3-2-1_53JMH_2019-04-28_final.stac-item
2019-04-28 10:35:45	ga_s2bm_ard_3-2-1_53JNG_2019-04-28_final.stac-item
2019-04-28 10:35:48	ga_s2bm_ard_3-2-1_53JMG_2019-04-28_final.stac-item
2019-04-28 10:35:59	ga_s2bm_ard_3-2-1_53JNF_2019-04-28_final.stac-item
2019-04-28 10:36:03	ga_s2bm_ard_3-2-1_53JMF_2019-04-28_final.stac-item
2019-04-28 10:36:14	ga_s2bm_ard_3-2-1_53HNE_2019-04-28_final.stac-item
2019-04-28 10:36:17	ga_s2bm_ard_3-2-1_53HME_2019-04-28_final.stac-item
2019-04-28 10:36:28	ga_s2bm_ard_3-2-1_53HND_2019-04-28_final.stac-item
2019-04-28 10:36:32	ga_s2bm_ard_3-2-1_53HMD_2019-04-28_final.stac-item
2019-04-28 10:36:43	ga_s2bm_ard_3-2-1_53HNC_2019-04-28_final.stac-item
2019-04-28 10:36:57	ga_s2bm_ard_3-2-1_53HNB_2019-04-28_final.stac-item
2019-05-01 10:42:51	ga_s2bm_ard_3-2-1_53KMU_2019-05-01_final.stac-item
2019-05-01 10:43:04	ga_s2bm_ard_3-2-1_53KMT_2019-05-01_final.stac-item
2019-05-01 10:43:19	ga_s2bm_ard_3-2-1_53KMS_2019-05-01_final.stac-item
2019-05-11 10:42:52	ga_s2bm_ard_3-2-1_53KMU_2019-05-11_final.stac-item
2019-05-11 10:43:05	ga_s2bm_ard_3-2-1_53KMT_2019-05-11_final.stac-item
2019-05-11 10:43:20	ga_s2bm_ard_3-2-1_53KMS_2019-05-11_final.stac-item
2019-05-11 10:43:34	ga_s2bm_ard_3-2-1_53KMR_2019-05-11_final.stac-item
2019-05-11 10:43:49	ga_s2bm_ard_3-2-1_53KMQ_2019-05-11_final.stac-item
2019-05-11 10:44:03	ga_s2bm_ard_3-2-1_53KMP_2019-05-11_final.stac-item
2019-05-11 10:44:18	ga_s2bm_ard_3-2-1_53JMN_2019-05-11_final.stac-item
2019-05-11 10:44:33	ga_s2bm_ard_3-2-1_53JMM_2019-05-11_final.stac-item
2019-05-11 10:44:47	ga_s2bm_ard_3-2-1_53JML_2019-05-11_final.stac-item
2019-05-11 10:45:02	ga_s2bm_ard_3-2-1_53JMK_2019-05-11_final.stac-item
2019-05-11 10:45:16	ga_s2bm_ard_3-2-1_53JMJ_2019-05-11_final.stac-item
2019-05-11 10:45:31	ga_s2bm_ard_3-2-1_53JMH_2019-05-11_final.stac-item
2019-05-11 10:45:40	ga_s2bm_ard_3-2-1_53JNG_2019-05-11_final.stac-item
2019-05-11 10:45:45	ga_s2bm_ard_3-2-1_53JMG_2019-05-11_final.stac-item
2019-05-11 10:45:50	ga_s2bm_ard_3-2-1_53JNF_2019-05-11_final.stac-item
2019-05-11 10:46:00	ga_s2bm_ard_3-2-1_53JMF_2019-05-11_final.stac-item
2019-08-06 10:36:58	ga_s2bm_ard_3-2-1_53HNB_2019-08-06_final.stac-item
2022-08-20 10:36:12	ga_s2bm_ard_3-2-1_53HME_2022-08-20_final.stac-item
2022-08-20 10:36:23	ga_s2bm_ard_3-2-1_53HND_2022-08-20_final.stac-item
2022-08-20 10:36:26	ga_s2bm_ard_3-2-1_53HMD_2022-08-20_final.stac-item
2022-08-20 10:36:37	ga_s2bm_ard_3-2-1_53HNC_2022-08-20_final.stac-item
2022-08-20 10:36:52	ga_s2bm_ard_3-2-1_53HNB_2022-08-20_final.stac-item
2022-08-23 10:42:44	ga_s2bm_ard_3-2-1_53KMU_2022-08-23_final.stac-item
2022-08-23 10:42:53	ga_s2bm_ard_3-2-1_53KMT_2022-08-23_final.stac-item
2022-08-23 10:42:59	ga_s2bm_ard_3-2-1_53KMT_2022-08-23_final.stac-item
2022-08-23 10:43:12	ga_s2bm_ard_3-2-1_53KMS_2022-08-23_final.stac-item
2022-12-18 10:35:13	ga_s2bm_ard_3-2-1_53JMJ_2022-12-18_final.stac-item
2022-12-18 10:35:25	ga_s2bm_ard_3-2-1_53JMH_2022-12-18_final.stac-item
2022-12-18 10:35:34	ga_s2bm_ard_3-2-1_53JMG_2022-12-18_final.stac-item
2022-12-18 10:35:40	ga_s2bm_ard_3-2-1_53JNG_2022-12-18_final.stac-item
2022-12-18 10:35:41	ga_s2bm_ard_3-2-1_53JMG_2022-12-18_final.stac-item
2022-12-18 10:35:51	ga_s2bm_ard_3-2-1_53JNF_2022-12-18_final.stac-item
2022-12-18 10:35:54	ga_s2bm_ard_3-2-1_53JMF_2022-12-18_final.stac-item
2022-12-18 10:36:05	ga_s2bm_ard_3-2-1_53HNE_2022-12-18_final.stac-item
2022-12-18 10:36:09	ga_s2bm_ard_3-2-1_53HME_2022-12-18_final.stac-item
2022-12-21 10:43:10	ga_s2bm_ard_3-2-1_53KMS_2022-12-21_final.stac-item
2022-12-21 10:43:25	ga_s2bm_ard_3-2-1_53KMR_2022-12-21_final.stac-item
2022-12-21 10:43:40	ga_s2bm_ard_3-2-1_53KMQ_2022-12-21_final.stac-item
2022-12-21 10:43:51	ga_s2bm_ard_3-2-1_53KMP_2022-12-21_final.stac-item
2022-12-21 10:43:57	ga_s2bm_ard_3-2-1_53KMP_2022-12-21_final.stac-item
2022-12-21 10:44:09	ga_s2bm_ard_3-2-1_53JMN_2022-12-21_final.stac-item
2022-12-21 10:44:23	ga_s2bm_ard_3-2-1_53JMM_2022-12-21_final.stac-item
2022-12-21 10:44:38	ga_s2bm_ard_3-2-1_53JML_2022-12-21_final.stac-item
2022-12-21 10:44:52	ga_s2bm_ard_3-2-1_53JMK_2022-12-21_final.stac-item
2022-12-21 10:45:07	ga_s2bm_ard_3-2-1_53JMJ_2022-12-21_final.stac-item
2023-02-09 10:42:42	ga_s2bm_ard_3-2-1_53KMU_2023-02-09_final.stac-item
2023-02-09 10:42:55	ga_s2bm_ard_3-2-1_53KMT_2023-02-09_final.stac-item
2023-02-09 10:43:08	ga_s2bm_ard_3-2-1_53KMS_2023-02-09_final.stac-item
2023-02-09 10:43:15	ga_s2bm_ard_3-2-1_53KMS_2023-02-09_final.stac-item
2023-02-09 10:43:24	ga_s2bm_ard_3-2-1_53KMR_2023-02-09_final.stac-item
2023-02-09 10:43:39	ga_s2bm_ard_3-2-1_53KMQ_2023-02-09_final.stac-item
2023-02-09 10:43:53	ga_s2bm_ard_3-2-1_53KMP_2023-02-09_final.stac-item
2023-02-12 10:50:11	ga_s2bm_ard_3-2-1_53LMJ_2023-02-12_nrt.stac-item
2023-02-12 10:50:40	ga_s2bm_ard_3-2-1_53LMG_2023-02-12_final
2023-02-12 10:50:55	ga_s2bm_ard_3-2-1_53LMF_2023-02-12_nrt.stac-item
2023-02-12 10:50:55	ga_s2bm_ard_3-2-1_53LMF_2023-02-12_final
2023-02-12 10:51:09	ga_s2bm_ard_3-2-1_53LME_2023-02-12_final
2023-02-12 10:51:24	ga_s2bm_ard_3-2-1_53LMD_2023-02-12_final
2023-02-12 10:51:38	ga_s2bm_ard_3-2-1_53LMC_2023-02-12_nrt.stac-item
2023-02-12 10:51:38	ga_s2bm_ard_3-2-1_53LMC_2023-02-12_final
2023-02-12 10:51:51	ga_s2bm_ard_3-2-1_53KMB_2023-02-12_final
2023-02-12 10:51:58	ga_s2bm_ard_3-2-1_53KMB_2023-02-12_final
2023-02-12 10:52:07	ga_s2bm_ard_3-2-1_53KMA_2023-02-12_final
2023-02-12 10:52:22	ga_s2bm_ard_3-2-1_53KMV_2023-02-12_final
2023-02-12 10:52:36	ga_s2bm_ard_3-2-1_53KMU_2023-02-12_final
2023-02-12 10:52:51	ga_s2bm_ard_3-2-1_53KMT_2023-02-12_final
2023-02-16 10:36:34	ga_s2bm_ard_3-2-1_53HNC_2023-02-16_final
2023-02-16 10:36:37	ga_s2bm_ard_3-2-1_53HMC_2023-02-16_final
2023-02-16 10:36:48	ga_s2bm_ard_3-2-1_53HNB_2023-02-16_final
2023-02-16 10:37:01	ga_s2bm_ard_3-2-1_53HNA_2023-02-16_nrt.stac-item
2023-02-16 10:37:03	ga_s2bm_ard_3-2-1_53HMA_2023-02-16_nrt.stac-item
2023-02-19 10:44:08	ga_s2bm_ard_3-2-1_53JMN_2023-02-19_nrt.stac-item
2023-02-19 10:44:08	ga_s2bm_ard_3-2-1_53JMN_2023-02-19_final
2023-02-19 10:44:23	ga_s2bm_ard_3-2-1_53JMM_2023-02-19_final
2023-02-19 10:44:38	ga_s2bm_ard_3-2-1_53JML_2023-02-19_final
2023-02-19 10:44:52	ga_s2bm_ard_3-2-1_53JMK_2023-02-19_final
2023-02-19 10:45:07	ga_s2bm_ard_3-2-1_53JMJ_2023-02-19_final
2023-02-19 10:45:21	ga_s2bm_ard_3-2-1_53JMH_2023-02-19_final
2023-02-19 10:45:30	ga_s2bm_ard_3-2-1_53JNG_2023-02-19_final
2023-02-19 10:45:36	ga_s2bm_ard_3-2-1_53JMG_2023-02-19_final
2023-02-19 10:45:40	ga_s2bm_ard_3-2-1_53JNF_2023-02-19_final
2023-02-19 10:45:50	ga_s2bm_ard_3-2-1_53JMF_2023-02-19_final
2023-02-22 10:50:12	ga_s2bm_ard_3-2-1_53LMJ_2023-02-22_nrt.stac-item
2023-02-22 10:50:41	ga_s2bm_ard_3-2-1_53LMG_2023-02-22_final
2023-02-22 10:50:56	ga_s2bm_ard_3-2-1_53LMF_2023-02-22_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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