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
2019-04-15 12:06:09	ga_s2bm_ard_3-2-1_50JLM_2019-04-15_final.stac-item
2019-05-02 11:54:34	ga_s2bm_ard_3-2-1_50KMU_2019-05-02_final.stac-item
2019-05-02 11:54:41	ga_s2bm_ard_3-2-1_50KLU_2019-05-02_final.stac-item
2019-05-02 11:54:41	ga_s2bm_ard_3-2-1_50JPT_2019-05-02_final.stac-item
2019-05-02 11:54:45	ga_s2bm_ard_3-2-1_50JNT_2019-05-02_final.stac-item
2019-05-02 11:54:53	ga_s2bm_ard_3-2-1_50JPS_2019-05-02_final.stac-item
2019-05-02 11:54:57	ga_s2bm_ard_3-2-1_50JMS_2019-05-02_final.stac-item
2019-05-02 11:55:00	ga_s2bm_ard_3-2-1_50JPS_2019-05-02_final.stac-item
2019-05-02 11:55:03	ga_s2bm_ard_3-2-1_50JMS_2019-05-02_final.stac-item
2019-05-02 11:55:35	ga_s2bm_ard_3-2-1_50JLQ_2019-05-02_final.stac-item
2019-05-02 11:55:49	ga_s2bm_ard_3-2-1_50JLP_2019-05-02_final.stac-item
2019-05-02 11:55:54	ga_s2bm_ard_3-2-1_50JKP_2019-05-02_final.stac-item
2019-05-02 11:55:57	ga_s2bm_ard_3-2-1_50JNN_2019-05-02_final.stac-item
2019-05-02 11:56:01	ga_s2bm_ard_3-2-1_50JMN_2019-05-02_final.stac-item
2019-05-02 11:56:07	ga_s2bm_ard_3-2-1_50JKN_2019-05-02_final.stac-item
2019-05-05 12:04:18	ga_s2bm_ard_3-2-1_50KLV_2019-05-05_final.stac-item
2019-05-05 12:04:29	ga_s2bm_ard_3-2-1_50KMU_2019-05-05_final.stac-item
2019-05-05 12:04:33	ga_s2bm_ard_3-2-1_50KLU_2019-05-05_final.stac-item
2019-05-05 12:04:56	ga_s2bm_ard_3-2-1_50JMS_2019-05-05_final.stac-item
2019-05-05 12:05:05	ga_s2bm_ard_3-2-1_49JHM_2019-05-05_final.stac-item
2019-05-05 12:05:05	ga_s2bm_ard_3-2-1_50JKS_2019-05-05_final.stac-item
2019-05-05 12:05:09	ga_s2bm_ard_3-2-1_49JGM_2019-05-05_final.stac-item
2019-05-05 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-05-05_final.stac-item
2019-05-05 12:05:31	ga_s2bm_ard_3-2-1_50JLQ_2019-05-05_final.stac-item
2019-05-05 12:05:34	ga_s2bm_ard_3-2-1_50JKQ_2019-05-05_final.stac-item
2019-05-05 12:05:46	ga_s2bm_ard_3-2-1_50JLP_2019-05-05_final.stac-item
2019-05-05 12:05:49	ga_s2bm_ard_3-2-1_50JKP_2019-05-05_final.stac-item
2019-05-05 12:06:03	ga_s2bm_ard_3-2-1_50JKN_2019-05-05_final.stac-item
2019-05-08 12:15:04	ga_s2bm_ard_3-2-1_49JGM_2019-05-08_final.stac-item
2019-05-09 11:44:46	ga_s2bm_ard_3-2-1_50JPT_2019-05-09_final.stac-item
2019-05-09 11:44:57	ga_s2bm_ard_3-2-1_50JQS_2019-05-09_final.stac-item
2019-05-09 11:45:01	ga_s2bm_ard_3-2-1_50JPS_2019-05-09_final.stac-item
2019-05-09 11:45:12	ga_s2bm_ard_3-2-1_50JQR_2019-05-09_final.stac-item
2019-05-09 11:45:26	ga_s2bm_ard_3-2-1_50JQQ_2019-05-09_final.stac-item
2019-05-09 11:46:02	ga_s2bm_ard_3-2-1_50JNN_2019-05-09_final.stac-item
2019-05-12 11:54:24	ga_s2bm_ard_3-2-1_50KMV_2019-05-12_final.stac-item
2019-05-12 11:54:34	ga_s2bm_ard_3-2-1_50KMU_2019-05-12_final.stac-item
2019-05-12 11:54:42	ga_s2bm_ard_3-2-1_50KLU_2019-05-12_final.stac-item
2019-05-12 11:54:42	ga_s2bm_ard_3-2-1_50JPT_2019-05-12_final.stac-item
2019-05-12 11:54:46	ga_s2bm_ard_3-2-1_50JNT_2019-05-12_final.stac-item
2019-05-12 11:54:56	ga_s2bm_ard_3-2-1_50JPS_2019-05-12_final.stac-item
2019-05-12 11:55:03	ga_s2bm_ard_3-2-1_50JMS_2019-05-12_final.stac-item
2019-05-12 11:55:36	ga_s2bm_ard_3-2-1_50JLQ_2019-05-12_final.stac-item
2019-05-12 11:55:50	ga_s2bm_ard_3-2-1_50JLP_2019-05-12_final.stac-item
2019-05-12 11:55:55	ga_s2bm_ard_3-2-1_50JKP_2019-05-12_final.stac-item
2019-05-12 11:55:58	ga_s2bm_ard_3-2-1_50JNN_2019-05-12_final.stac-item
2019-05-12 11:56:01	ga_s2bm_ard_3-2-1_50JMN_2019-05-12_final.stac-item
2019-05-12 11:56:08	ga_s2bm_ard_3-2-1_50JKN_2019-05-12_final.stac-item
2019-05-15 12:04:19	ga_s2bm_ard_3-2-1_50KLV_2019-05-15_final.stac-item
2019-05-15 12:04:30	ga_s2bm_ard_3-2-1_50KMU_2019-05-15_final.stac-item
2019-05-15 12:04:33	ga_s2bm_ard_3-2-1_50KLU_2019-05-15_final.stac-item
2019-05-15 12:04:57	ga_s2bm_ard_3-2-1_50JMS_2019-05-15_final.stac-item
2019-05-15 12:05:06	ga_s2bm_ard_3-2-1_50JKS_2019-05-15_final.stac-item
2019-05-15 12:05:20	ga_s2bm_ard_3-2-1_50JKR_2019-05-15_final.stac-item
2019-05-15 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2019-05-15_final.stac-item
2019-05-15 12:05:30	ga_s2bm_ard_3-2-1_50JKQ_2019-05-15_final.stac-item
2019-05-15 12:05:35	ga_s2bm_ard_3-2-1_50JLQ_2019-05-15_final.stac-item
2019-05-15 12:05:36	ga_s2bm_ard_3-2-1_50JKQ_2019-05-15_final.stac-item
2019-05-15 12:05:46	ga_s2bm_ard_3-2-1_50JLP_2019-05-15_final.stac-item
2019-05-15 12:05:52	ga_s2bm_ard_3-2-1_49JGJ_2019-05-15_final.stac-item
2019-05-18 12:15:05	ga_s2bm_ard_3-2-1_49JGM_2019-05-18_final.stac-item
2019-05-19 11:44:46	ga_s2bm_ard_3-2-1_50JPT_2019-05-19_final.stac-item
2019-05-19 11:44:57	ga_s2bm_ard_3-2-1_50JQS_2019-05-19_final.stac-item
2019-05-19 11:45:01	ga_s2bm_ard_3-2-1_50JPS_2019-05-19_final.stac-item
2019-05-19 11:45:12	ga_s2bm_ard_3-2-1_50JQR_2019-05-19_final.stac-item
2019-05-19 11:45:26	ga_s2bm_ard_3-2-1_50JQQ_2019-05-19_final.stac-item
2019-05-19 11:46:03	ga_s2bm_ard_3-2-1_50JNN_2019-05-19_final.stac-item
2019-05-22 11:54:35	ga_s2bm_ard_3-2-1_50KMU_2019-05-22_final.stac-item
2019-05-22 11:54:41	ga_s2bm_ard_3-2-1_50JPT_2019-05-22_final.stac-item
2019-05-22 11:54:42	ga_s2bm_ard_3-2-1_50KLU_2019-05-22_final.stac-item
2019-05-22 11:54:44	ga_s2bm_ard_3-2-1_50JNT_2019-05-22_final.stac-item
2019-05-22 11:54:48	ga_s2bm_ard_3-2-1_50JPS_2019-05-22_final.stac-item
2019-05-22 11:54:48	ga_s2bm_ard_3-2-1_50JPT_2019-05-22_final.stac-item
2019-05-22 11:54:50	ga_s2bm_ard_3-2-1_50JNT_2019-05-22_final.stac-item
2019-05-22 11:54:56	ga_s2bm_ard_3-2-1_50JPS_2019-05-22_final.stac-item
2019-05-22 11:55:03	ga_s2bm_ard_3-2-1_50JMS_2019-05-22_final.stac-item
2019-05-22 11:55:36	ga_s2bm_ard_3-2-1_50JLQ_2019-05-22_final.stac-item
2019-05-22 11:55:50	ga_s2bm_ard_3-2-1_50JLP_2019-05-22_final.stac-item
2019-05-22 11:55:58	ga_s2bm_ard_3-2-1_50JNN_2019-05-22_final.stac-item
2019-05-22 11:56:02	ga_s2bm_ard_3-2-1_50JMN_2019-05-22_final.stac-item
2019-05-22 11:56:08	ga_s2bm_ard_3-2-1_50JKN_2019-05-22_final.stac-item
2019-05-25 12:04:19	ga_s2bm_ard_3-2-1_50KLV_2019-05-25_final.stac-item
2019-05-25 12:04:30	ga_s2bm_ard_3-2-1_50KMU_2019-05-25_final.stac-item
2019-05-25 12:04:33	ga_s2bm_ard_3-2-1_50KLU_2019-05-25_final.stac-item
2019-05-25 12:04:57	ga_s2bm_ard_3-2-1_50JMS_2019-05-25_final.stac-item
2019-05-25 12:05:05	ga_s2bm_ard_3-2-1_49JHM_2019-05-25_final.stac-item
2019-05-25 12:05:06	ga_s2bm_ard_3-2-1_50JKS_2019-05-25_final.stac-item
2019-05-25 12:05:09	ga_s2bm_ard_3-2-1_49JGM_2019-05-25_final.stac-item
2019-05-25 12:05:28	ga_s2bm_ard_3-2-1_50JLQ_2019-05-25_final.stac-item
2019-05-25 12:05:35	ga_s2bm_ard_3-2-1_50JLQ_2019-05-25_final.stac-item
2019-05-25 12:05:36	ga_s2bm_ard_3-2-1_50JKQ_2019-05-25_final.stac-item
2019-05-25 12:05:46	ga_s2bm_ard_3-2-1_50JLP_2019-05-25_final.stac-item
2019-05-25 12:05:49	ga_s2bm_ard_3-2-1_50JKP_2019-05-25_final.stac-item
2019-05-25 12:05:52	ga_s2bm_ard_3-2-1_49JGJ_2019-05-25_final.stac-item
2019-05-25 12:06:00	ga_s2bm_ard_3-2-1_50JLN_2019-05-25_final.stac-item
2019-05-29 11:44:46	ga_s2bm_ard_3-2-1_50JPT_2019-05-29_final.stac-item
2019-05-29 11:44:57	ga_s2bm_ard_3-2-1_50JQS_2019-05-29_final.stac-item
2019-05-29 11:45:01	ga_s2bm_ard_3-2-1_50JPS_2019-05-29_final.stac-item
2019-05-29 11:45:12	ga_s2bm_ard_3-2-1_50JQR_2019-05-29_final.stac-item
2019-05-29 11:45:26	ga_s2bm_ard_3-2-1_50JQQ_2019-05-29_final.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