Search ga_s2bm_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

69 results

Time (local)	Label
2023-05-11 11:53:56	ga_s2bm_ard_3-2-1_50KQA_2023-05-11_final.stac-item
2023-05-11 11:53:57	ga_s2bm_ard_3-2-1_50KPA_2023-05-11_final.stac-item
2023-05-11 11:53:59	ga_s2bm_ard_3-2-1_50KNA_2023-05-11_final.stac-item
2023-05-11 11:54:00	ga_s2bm_ard_3-2-1_50KMA_2023-05-11_final.stac-item
2023-05-11 11:54:03	ga_s2bm_ard_3-2-1_50KQV_2023-05-11_final.stac-item
2023-05-11 11:54:07	ga_s2bm_ard_3-2-1_50KPV_2023-05-11_final.stac-item
2023-05-11 11:54:10	ga_s2bm_ard_3-2-1_50KNV_2023-05-11_final.stac-item
2023-05-11 11:54:14	ga_s2bm_ard_3-2-1_50KMV_2023-05-11_final.stac-item
2023-05-11 11:54:16	ga_s2bm_ard_3-2-1_50KQU_2023-05-11_final.stac-item
2023-05-11 11:54:21	ga_s2bm_ard_3-2-1_50KPU_2023-05-11_final.stac-item
2023-05-11 11:54:25	ga_s2bm_ard_3-2-1_50KNU_2023-05-11_final.stac-item
2023-05-11 11:54:25	ga_s2bm_ard_3-2-1_50JQT_2023-05-11_final.stac-item
2023-05-11 11:54:28	ga_s2bm_ard_3-2-1_50KMU_2023-05-11_final.stac-item
2023-05-11 11:54:36	ga_s2bm_ard_3-2-1_50KLU_2023-05-11_final.stac-item
2023-05-11 11:54:36	ga_s2bm_ard_3-2-1_50JPT_2023-05-11_final.stac-item
2023-05-11 11:54:40	ga_s2bm_ard_3-2-1_50JNT_2023-05-11_final.stac-item
2023-05-11 11:54:43	ga_s2bm_ard_3-2-1_50JMT_2023-05-11_final.stac-item
2023-05-11 11:54:47	ga_s2bm_ard_3-2-1_50JLT_2023-05-11_final.stac-item
2023-05-11 11:54:50	ga_s2bm_ard_3-2-1_50JPS_2023-05-11_final.stac-item
2023-05-11 11:54:54	ga_s2bm_ard_3-2-1_50JNS_2023-05-11_final.stac-item
2023-05-11 11:54:57	ga_s2bm_ard_3-2-1_50JMS_2023-05-11_final.stac-item
2023-05-11 11:55:00	ga_s2bm_ard_3-2-1_50JLS_2023-05-11_final.stac-item
2023-05-11 11:55:05	ga_s2bm_ard_3-2-1_50JPR_2023-05-11_final.stac-item
2023-05-11 11:55:08	ga_s2bm_ard_3-2-1_50JNR_2023-05-11_final.stac-item
2023-05-11 11:55:12	ga_s2bm_ard_3-2-1_50JMR_2023-05-11_final.stac-item
2023-05-11 11:55:15	ga_s2bm_ard_3-2-1_50JLR_2023-05-11_final.stac-item
2023-05-11 11:55:18	ga_s2bm_ard_3-2-1_50JPQ_2023-05-11_final.stac-item
2023-05-11 11:55:23	ga_s2bm_ard_3-2-1_50JNQ_2023-05-11_final.stac-item
2023-05-11 11:55:26	ga_s2bm_ard_3-2-1_50JMQ_2023-05-11_final.stac-item
2023-05-11 11:55:28	ga_s2bm_ard_3-2-1_50JPP_2023-05-11_final.stac-item
2023-05-11 11:55:30	ga_s2bm_ard_3-2-1_50JLQ_2023-05-11_final.stac-item
2023-05-11 11:55:37	ga_s2bm_ard_3-2-1_50JNP_2023-05-11_final.stac-item
2023-05-11 11:55:41	ga_s2bm_ard_3-2-1_50JMP_2023-05-11_final.stac-item
2023-05-11 11:55:44	ga_s2bm_ard_3-2-1_50JLP_2023-05-11_final.stac-item
2023-05-11 11:55:49	ga_s2bm_ard_3-2-1_50JKP_2023-05-11_final.stac-item
2023-05-11 11:55:52	ga_s2bm_ard_3-2-1_50JNN_2023-05-11_final.stac-item
2023-05-11 11:55:55	ga_s2bm_ard_3-2-1_50JMN_2023-05-11_final.stac-item
2023-05-11 11:55:59	ga_s2bm_ard_3-2-1_50JLN_2023-05-11_final.stac-item
2023-05-11 11:56:02	ga_s2bm_ard_3-2-1_50JKN_2023-05-11_final.stac-item
2023-05-11 11:56:07	ga_s2bm_ard_3-2-1_50JNM_2023-05-11_final.stac-item
2023-05-11 11:56:10	ga_s2bm_ard_3-2-1_50JMM_2023-05-11_final.stac-item
2023-05-11 11:56:13	ga_s2bm_ard_3-2-1_50JLM_2023-05-11_final.stac-item
2023-05-11 11:56:16	ga_s2bm_ard_3-2-1_50JKM_2023-05-11_final.stac-item
2023-05-11 11:56:20	ga_s2bm_ard_3-2-1_50JNL_2023-05-11_final.stac-item
2023-05-11 11:56:24	ga_s2bm_ard_3-2-1_50JML_2023-05-11_final.stac-item
2023-05-11 11:56:28	ga_s2bm_ard_3-2-1_50JLL_2023-05-11_final.stac-item
2023-05-11 11:56:31	ga_s2bm_ard_3-2-1_50JKL_2023-05-11_nrt.stac-item
2023-05-11 11:56:32	ga_s2bm_ard_3-2-1_50HNK_2023-05-11_final.stac-item
2023-05-11 11:56:35	ga_s2bm_ard_3-2-1_49JGF_2023-05-11_nrt.stac-item
2023-05-11 11:56:39	ga_s2bm_ard_3-2-1_50HMK_2023-05-11_final.stac-item
2023-05-11 11:56:43	ga_s2bm_ard_3-2-1_50HLK_2023-05-11_final.stac-item
2023-05-11 11:56:46	ga_s2bm_ard_3-2-1_50HKK_2023-05-11_nrt.stac-item
2023-05-11 11:56:48	ga_s2bm_ard_3-2-1_49HGE_2023-05-11_nrt.stac-item
2023-05-11 11:56:53	ga_s2bm_ard_3-2-1_50HMJ_2023-05-11_final.stac-item
2023-05-11 11:56:57	ga_s2bm_ard_3-2-1_50HLJ_2023-05-11_final.stac-item
2023-05-11 11:57:00	ga_s2bm_ard_3-2-1_50HKJ_2023-05-11_nrt.stac-item
2023-05-11 11:57:02	ga_s2bm_ard_3-2-1_49HGD_2023-05-11_nrt.stac-item
2023-05-11 11:57:08	ga_s2bm_ard_3-2-1_50HMH_2023-05-11_final.stac-item
2023-05-11 11:57:12	ga_s2bm_ard_3-2-1_50HLH_2023-05-11_final.stac-item
2023-05-11 11:57:15	ga_s2bm_ard_3-2-1_50HKH_2023-05-11_nrt.stac-item
2023-05-11 11:57:17	ga_s2bm_ard_3-2-1_49HGC_2023-05-11_nrt.stac-item
2023-05-11 11:57:23	ga_s2bm_ard_3-2-1_50HMG_2023-05-11_final.stac-item
2023-05-11 11:57:25	ga_s2bm_ard_3-2-1_49HFC_2023-05-11_nrt.stac-item
2023-05-11 11:57:26	ga_s2bm_ard_3-2-1_50HLG_2023-05-11_final.stac-item
2023-05-11 11:57:27	ga_s2bm_ard_3-2-1_50HKG_2023-05-11_nrt.stac-item
2023-05-11 11:57:28	ga_s2bm_ard_3-2-1_49HGB_2023-05-11_nrt.stac-item
2023-05-11 11:57:30	ga_s2bm_ard_3-2-1_49HFB_2023-05-11_nrt.stac-item
2023-05-11 11:57:31	ga_s2bm_ard_3-2-1_50HMF_2023-05-11_nrt.stac-item
2023-05-11 11:57:32	ga_s2bm_ard_3-2-1_50HLF_2023-05-11_nrt.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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years