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
2017-11-17 10:37:14	ga_s2bm_ard_3-2-1_53KMT_2017-11-17_final.stac-item
2017-11-17 10:37:14	ga_s2bm_ard_3-2-1_53KNT_2017-11-17_final.stac-item
2017-11-17 10:37:14	ga_s2bm_ard_3-2-1_53KPT_2017-11-17_final.stac-item
2017-11-17 10:37:14	ga_s2bm_ard_3-2-1_53KQT_2017-11-17_final.stac-item
2017-11-18 10:06:52	ga_s2bm_ard_3-2-1_54KXC_2017-11-18_final.stac-item
2017-11-18 10:06:52	ga_s2bm_ard_3-2-1_55KBT_2017-11-18_final.stac-item
2017-11-18 10:06:52	ga_s2bm_ard_3-2-1_54KYC_2017-11-18_final.stac-item
2017-11-18 10:06:52	ga_s2bm_ard_3-2-1_54KZB_2017-11-18_final.stac-item
2017-11-18 10:06:52	ga_s2bm_ard_3-2-1_54KZC_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KMC_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KNC_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KPC_2017-11-18_final.stac-item
2017-11-18 11:49:07	ga_s2bm_ard_3-2-1_50KQC_2017-11-18_final.stac-item
2017-11-21 10:16:54	ga_s2bm_ard_3-2-1_54KUC_2017-11-21_final.stac-item
2017-11-21 10:16:54	ga_s2bm_ard_3-2-1_54KVC_2017-11-21_final.stac-item
2017-11-21 10:16:54	ga_s2bm_ard_3-2-1_54KWC_2017-11-21_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55KET_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55KFT_2017-11-22_final.stac-item
2017-11-22 09:51:43	ga_s2bm_ard_3-2-1_55KGT_2017-11-22_final.stac-item
2017-11-28 10:06:53	ga_s2bm_ard_3-2-1_54KXC_2017-11-28_final.stac-item
2017-11-28 10:06:53	ga_s2bm_ard_3-2-1_55KBT_2017-11-28_final.stac-item
2017-11-28 10:06:53	ga_s2bm_ard_3-2-1_54KYC_2017-11-28_final.stac-item
2017-11-28 10:06:53	ga_s2bm_ard_3-2-1_54KZB_2017-11-28_final.stac-item
2017-11-28 10:06:53	ga_s2bm_ard_3-2-1_54KZC_2017-11-28_final.stac-item
2017-11-30 10:47:13	ga_s2bm_ard_3-2-1_53KKT_2017-11-30_final.stac-item
2017-11-30 10:47:13	ga_s2bm_ard_3-2-1_53KLT_2017-11-30_final.stac-item
2017-11-30 10:47:13	ga_s2bm_ard_3-2-1_53KMT_2017-11-30_final.stac-item
2017-11-30 10:47:13	ga_s2bm_ard_3-2-1_52KHB_2017-11-30_final.stac-item
2017-11-30 10:47:13	ga_s2bm_ard_3-2-1_52KHC_2017-11-30_final.stac-item
2017-12-02 09:50:43	ga_s2bm_ard_3-2-1_55KET_2017-12-02_final.stac-item
2017-12-02 09:50:43	ga_s2bm_ard_3-2-1_55KFT_2017-12-02_final.stac-item
2017-12-02 09:50:43	ga_s2bm_ard_3-2-1_55KGT_2017-12-02_final.stac-item
2017-12-12 09:51:43	ga_s2bm_ard_3-2-1_55KET_2017-12-12_final.stac-item
2017-12-12 09:51:43	ga_s2bm_ard_3-2-1_55KFT_2017-12-12_final.stac-item
2017-12-12 09:51:43	ga_s2bm_ard_3-2-1_55KGT_2017-12-12_final.stac-item
2017-12-15 10:01:29	ga_s2bm_ard_3-2-1_55KBT_2017-12-15_final.stac-item
2017-12-15 10:01:29	ga_s2bm_ard_3-2-1_55KCT_2017-12-15_final.stac-item
2017-12-15 10:01:29	ga_s2bm_ard_3-2-1_54KZB_2017-12-15_final.stac-item
2017-12-15 10:01:29	ga_s2bm_ard_3-2-1_54KZC_2017-12-15_final.stac-item
2017-12-15 10:01:29	ga_s2bm_ard_3-2-1_55KDT_2017-12-15_final.stac-item
2017-12-15 10:01:29	ga_s2bm_ard_3-2-1_55KET_2017-12-15_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_54KXC_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_55KBT_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_54KYC_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_54KZB_2017-12-18_final.stac-item
2017-12-18 10:06:52	ga_s2bm_ard_3-2-1_54KZC_2017-12-18_final.stac-item
2017-12-22 09:50:42	ga_s2bm_ard_3-2-1_55KET_2017-12-22_final.stac-item
2017-12-22 09:50:42	ga_s2bm_ard_3-2-1_55KFT_2017-12-22_final.stac-item
2017-12-22 09:50:42	ga_s2bm_ard_3-2-1_55KGT_2017-12-22_final.stac-item
2018-11-28 11:02:50	ga_s2bm_ard_3-2-1_53KKT_2018-11-28_final.stac-item
2018-11-28 11:02:51	ga_s2bm_ard_3-2-1_52KHC_2018-11-28_final.stac-item
2018-11-28 11:02:54	ga_s2bm_ard_3-2-1_52KGC_2018-11-28_final.stac-item
2018-11-28 11:02:58	ga_s2bm_ard_3-2-1_52KFC_2018-11-28_final.stac-item
2018-11-28 11:03:01	ga_s2bm_ard_3-2-1_52KEC_2018-11-28_final.stac-item
2018-11-29 10:32:39	ga_s2bm_ard_3-2-1_54KUC_2018-11-29_final.stac-item
2018-11-29 10:32:43	ga_s2bm_ard_3-2-1_54KTC_2018-11-29_final.stac-item
2018-11-29 10:32:44	ga_s2bm_ard_3-2-1_53KRT_2018-11-29_final.stac-item
2018-11-29 10:32:47	ga_s2bm_ard_3-2-1_53KQT_2018-11-29_final.stac-item
2018-11-29 10:32:58	ga_s2bm_ard_3-2-1_53KRS_2018-11-29_final.stac-item
2018-12-05 10:52:47	ga_s2bm_ard_3-2-1_53KMT_2018-12-05_final.stac-item
2018-12-05 10:52:51	ga_s2bm_ard_3-2-1_53KLT_2018-12-05_final.stac-item
2018-12-05 10:52:54	ga_s2bm_ard_3-2-1_53KKT_2018-12-05_final.stac-item
2018-12-05 10:52:54	ga_s2bm_ard_3-2-1_52KHC_2018-12-05_final.stac-item
2018-12-05 10:53:09	ga_s2bm_ard_3-2-1_52KHB_2018-12-05_final.stac-item
2018-12-06 12:03:14	ga_s2bm_ard_3-2-1_50KNC_2018-12-06_final.stac-item
2018-12-06 12:03:17	ga_s2bm_ard_3-2-1_50KMC_2018-12-06_final.stac-item
2018-12-06 12:03:22	ga_s2bm_ard_3-2-1_50KNC_2018-12-06_final.stac-item
2018-12-06 12:03:23	ga_s2bm_ard_3-2-1_50KMC_2018-12-06_final.stac-item
2018-12-06 12:03:25	ga_s2bm_ard_3-2-1_50KLC_2018-12-06_final.stac-item
2018-12-07 11:33:03	ga_s2bm_ard_3-2-1_51KXT_2018-12-07_final.stac-item
2018-12-07 11:33:07	ga_s2bm_ard_3-2-1_51KWT_2018-12-07_final.stac-item
2018-12-07 11:33:10	ga_s2bm_ard_3-2-1_51KVT_2018-12-07_final.stac-item
2018-12-07 11:33:17	ga_s2bm_ard_3-2-1_51KUT_2018-12-07_final.stac-item
2018-12-09 10:32:38	ga_s2bm_ard_3-2-1_54KUC_2018-12-09_final.stac-item
2018-12-09 10:32:41	ga_s2bm_ard_3-2-1_54KTC_2018-12-09_final.stac-item
2018-12-09 10:32:42	ga_s2bm_ard_3-2-1_53KRT_2018-12-09_final.stac-item
2018-12-09 10:32:45	ga_s2bm_ard_3-2-1_53KQT_2018-12-09_final.stac-item
2018-12-09 10:32:56	ga_s2bm_ard_3-2-1_53KRS_2018-12-09_final.stac-item
2018-12-10 10:02:24	ga_s2bm_ard_3-2-1_55KET_2018-12-10_final.stac-item
2018-12-10 10:02:27	ga_s2bm_ard_3-2-1_55KDT_2018-12-10_final.stac-item
2018-12-10 10:02:31	ga_s2bm_ard_3-2-1_55KCT_2018-12-10_final.stac-item
2018-12-10 10:02:33	ga_s2bm_ard_3-2-1_55KBT_2018-12-10_final.stac-item
2018-12-10 10:02:35	ga_s2bm_ard_3-2-1_54KZC_2018-12-10_final.stac-item
2018-12-10 10:02:48	ga_s2bm_ard_3-2-1_54KZB_2018-12-10_final.stac-item
2018-12-10 11:43:05	ga_s2bm_ard_3-2-1_51KVT_2018-12-10_final.stac-item
2018-12-10 11:43:09	ga_s2bm_ard_3-2-1_51KUT_2018-12-10_final.stac-item
2018-12-10 11:43:12	ga_s2bm_ard_3-2-1_51KTT_2018-12-10_final.stac-item
2018-12-10 11:43:12	ga_s2bm_ard_3-2-1_50KRC_2018-12-10_final.stac-item
2018-12-11 11:12:54	ga_s2bm_ard_3-2-1_52KEC_2018-12-11_final.stac-item
2018-12-11 11:12:58	ga_s2bm_ard_3-2-1_52KDC_2018-12-11_final.stac-item
2018-12-11 11:13:01	ga_s2bm_ard_3-2-1_52KCC_2018-12-11_final.stac-item
2018-12-11 11:13:07	ga_s2bm_ard_3-2-1_52KBC_2018-12-11_final.stac-item
2019-06-02 09:42:41	ga_s2bm_ard_3-2-1_55KGT_2019-06-02_final.stac-item
2019-06-02 09:42:51	ga_s2bm_ard_3-2-1_55KHS_2019-06-02_final.stac-item
2019-06-16 11:03:02	ga_s2bm_ard_3-2-1_53KKT_2019-06-16_final.stac-item
2019-06-16 11:03:02	ga_s2bm_ard_3-2-1_52KHC_2019-06-16_final.stac-item
2019-06-16 11:03:06	ga_s2bm_ard_3-2-1_52KGC_2019-06-16_final.stac-item
2019-06-16 11:03:09	ga_s2bm_ard_3-2-1_52KFC_2019-06-16_final.stac-item
2019-06-16 11:03:12	ga_s2bm_ard_3-2-1_52KEC_2019-06-16_final.stac-item
2019-06-22 09:42:41	ga_s2bm_ard_3-2-1_55KGT_2019-06-22_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

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