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
2022-11-25 10:19:37	ga_s2bm_ard_3-2-1_54LZQ_2022-11-25_final.stac-item
2022-11-25 10:19:58	ga_s2bm_ard_3-2-1_54LXP_2022-11-25_final.stac-item
2022-11-25 10:20:09	ga_s2bm_ard_3-2-1_54LYN_2022-11-25_final.stac-item
2022-11-25 10:20:13	ga_s2bm_ard_3-2-1_54LXN_2022-11-25_final.stac-item
2022-11-25 10:20:20	ga_s2bm_ard_3-2-1_54LZM_2022-11-25_final.stac-item
2022-11-25 10:20:27	ga_s2bm_ard_3-2-1_54LXM_2022-11-25_final.stac-item
2022-11-25 10:20:35	ga_s2bm_ard_3-2-1_54LZL_2022-11-25_final.stac-item
2022-11-25 10:20:53	ga_s2bm_ard_3-2-1_54LYK_2022-11-25_final.stac-item
2022-11-25 10:20:56	ga_s2bm_ard_3-2-1_54LXK_2022-11-25_final.stac-item
2022-11-25 10:21:07	ga_s2bm_ard_3-2-1_54LYJ_2022-11-25_final.stac-item
2022-11-25 10:21:29	ga_s2bm_ard_3-2-1_54LWH_2022-11-25_final.stac-item
2022-11-25 10:21:54	ga_s2bm_ard_3-2-1_54KXF_2022-11-25_final.stac-item
2022-11-25 10:21:58	ga_s2bm_ard_3-2-1_54KWF_2022-11-25_final.stac-item
2022-11-25 10:22:01	ga_s2bm_ard_3-2-1_54KVF_2022-11-25_final.stac-item
2022-11-25 10:22:13	ga_s2bm_ard_3-2-1_54KYD_2022-11-25_final.stac-item
2022-11-25 10:22:16	ga_s2bm_ard_3-2-1_54KVE_2022-11-25_final.stac-item
2022-11-25 10:22:27	ga_s2bm_ard_3-2-1_54KWD_2022-11-25_final.stac-item
2022-11-25 10:22:30	ga_s2bm_ard_3-2-1_54KVD_2022-11-25_final.stac-item
2022-11-25 10:22:38	ga_s2bm_ard_3-2-1_54KXC_2022-11-25_final.stac-item
2022-11-25 10:22:41	ga_s2bm_ard_3-2-1_54KWC_2022-11-25_final.stac-item
2022-11-25 10:23:02	ga_s2bm_ard_3-2-1_54KUB_2022-11-25_final.stac-item
2022-11-25 10:23:14	ga_s2bm_ard_3-2-1_54KVA_2022-11-25_final.stac-item
2022-11-25 10:23:17	ga_s2bm_ard_3-2-1_54KUA_2022-11-25_final.stac-item
2022-11-25 10:23:24	ga_s2bm_ard_3-2-1_54KWV_2022-11-25_final.stac-item
2022-11-25 10:23:39	ga_s2bm_ard_3-2-1_53KRQ_2022-11-25_final.stac-item
2022-11-25 10:23:46	ga_s2bm_ard_3-2-1_54KUU_2022-11-25_final.stac-item
2022-11-25 10:23:54	ga_s2bm_ard_3-2-1_54JWT_2022-11-25_final.stac-item
2022-11-25 10:24:01	ga_s2bm_ard_3-2-1_54JUT_2022-11-25_final.stac-item
2022-11-25 10:24:18	ga_s2bm_ard_3-2-1_54JTS_2022-11-25_final.stac-item
2022-11-25 10:24:26	ga_s2bm_ard_3-2-1_54JVR_2022-11-25_final.stac-item
2022-11-25 10:24:30	ga_s2bm_ard_3-2-1_54JUR_2022-11-25_final.stac-item
2022-11-25 10:24:33	ga_s2bm_ard_3-2-1_54JTR_2022-11-25_final.stac-item
2022-11-25 10:24:44	ga_s2bm_ard_3-2-1_54JUQ_2022-11-25_final.stac-item
2022-11-25 10:24:55	ga_s2bm_ard_3-2-1_54JVP_2022-11-25_final.stac-item
2022-11-25 10:24:59	ga_s2bm_ard_3-2-1_54JUP_2022-11-25_final.stac-item
2022-11-25 10:25:02	ga_s2bm_ard_3-2-1_54JTP_2022-11-25_final.stac-item
2022-11-25 10:25:10	ga_s2bm_ard_3-2-1_54JVN_2022-11-25_final.stac-item
2022-11-25 10:25:17	ga_s2bm_ard_3-2-1_54JTN_2022-11-25_final.stac-item
2022-11-25 10:25:19	ga_s2bm_ard_3-2-1_53JQH_2022-11-25_final.stac-item
2022-11-25 10:25:28	ga_s2bm_ard_3-2-1_54JUM_2022-11-25_final.stac-item
2022-11-25 10:25:31	ga_s2bm_ard_3-2-1_54JTM_2022-11-25_final.stac-item
2022-11-25 10:25:46	ga_s2bm_ard_3-2-1_54JTL_2022-11-25_final.stac-item
2022-11-25 10:25:57	ga_s2bm_ard_3-2-1_54HUK_2022-11-25_final.stac-item
2022-11-25 10:25:59	ga_s2bm_ard_3-2-1_54HTK_2022-11-25_final.stac-item
2022-11-25 10:26:00	ga_s2bm_ard_3-2-1_53HQE_2022-11-25_final.stac-item
2022-11-25 10:26:02	ga_s2bm_ard_3-2-1_53HPE_2022-11-25_final.stac-item
2022-11-25 10:26:04	ga_s2bm_ard_3-2-1_54HUK_2022-11-25_final.stac-item
2022-11-25 10:26:06	ga_s2bm_ard_3-2-1_54HTK_2022-11-25_final.stac-item
2022-11-25 10:26:09	ga_s2bm_ard_3-2-1_53HPE_2022-11-25_final.stac-item
2022-11-25 10:26:12	ga_s2bm_ard_3-2-1_54HUJ_2022-11-25_final.stac-item
2022-11-25 10:26:15	ga_s2bm_ard_3-2-1_54HTJ_2022-11-25_final.stac-item
2022-11-25 10:26:17	ga_s2bm_ard_3-2-1_53HQD_2022-11-25_final.stac-item
2022-11-25 10:26:21	ga_s2bm_ard_3-2-1_53HPD_2022-11-25_final.stac-item
2022-11-25 10:26:58	ga_s2bm_ard_3-2-1_54HTF_2022-11-25_final.stac-item
2022-11-25 10:27:00	ga_s2bm_ard_3-2-1_53HQA_2022-11-25_final.stac-item
2022-11-25 12:03:23	ga_s2bm_ard_3-2-1_50KMC_2022-11-25_final.stac-item
2022-11-25 12:03:37	ga_s2bm_ard_3-2-1_50KMB_2022-11-25_final.stac-item
2022-11-25 12:03:40	ga_s2bm_ard_3-2-1_50KLB_2022-11-25_final.stac-item
2022-11-25 12:03:55	ga_s2bm_ard_3-2-1_50KLA_2022-11-25_final.stac-item
2022-11-25 12:03:58	ga_s2bm_ard_3-2-1_50KKA_2022-11-25_final.stac-item
2022-11-25 12:03:58	ga_s2bm_ard_3-2-1_49KHR_2022-11-25_final.stac-item
2022-11-25 12:04:06	ga_s2bm_ard_3-2-1_50KMV_2022-11-25_final.stac-item
2022-11-25 12:04:09	ga_s2bm_ard_3-2-1_50KLV_2022-11-25_final.stac-item
2022-11-25 12:04:13	ga_s2bm_ard_3-2-1_49KHQ_2022-11-25_final.stac-item
2022-11-25 12:04:17	ga_s2bm_ard_3-2-1_49KGQ_2022-11-25_final.stac-item
2022-11-25 12:04:24	ga_s2bm_ard_3-2-1_50KLU_2022-11-25_final.stac-item
2022-11-25 12:04:30	ga_s2bm_ard_3-2-1_49KGP_2022-11-25_final.stac-item
2022-11-25 12:04:35	ga_s2bm_ard_3-2-1_50JMT_2022-11-25_final.stac-item
2022-11-25 12:04:39	ga_s2bm_ard_3-2-1_50JLT_2022-11-25_final.stac-item
2022-11-25 12:04:56	ga_s2bm_ard_3-2-1_50JKS_2022-11-25_final.stac-item
2022-11-25 12:05:11	ga_s2bm_ard_3-2-1_50JKR_2022-11-25_final.stac-item
2022-11-25 12:05:14	ga_s2bm_ard_3-2-1_49JGL_2022-11-25_final.stac-item
2022-11-25 12:05:29	ga_s2bm_ard_3-2-1_49JGK_2022-11-25_final.stac-item
2022-11-25 12:05:51	ga_s2bm_ard_3-2-1_50JLN_2022-11-25_final.stac-item
2022-11-25 12:06:03	ga_s2bm_ard_3-2-1_50JLM_2022-11-25_final.stac-item
2022-11-25 12:06:09	ga_s2bm_ard_3-2-1_50JKM_2022-11-25_final.stac-item
2022-12-26 11:30:35	ga_s2bm_ard_3-2-1_52LBN_2022-12-26_nrt.stac-item
2022-12-26 11:30:40	ga_s2bm_ard_3-2-1_51LYH_2022-12-26_nrt.stac-item
2022-12-26 11:37:25	ga_s2bm_ard_3-2-1_51HUA_2022-12-26_nrt.stac-item
2022-12-26 11:37:28	ga_s2bm_ard_3-2-1_50HQF_2022-12-26_nrt.stac-item
2022-12-26 11:37:30	ga_s2bm_ard_3-2-1_50HPF_2022-12-26_nrt.stac-item
2022-12-27 09:26:48	ga_s2bm_ard_3-2-1_56HNE_2022-12-26_nrt.stac-item
2022-12-27 09:26:58	ga_s2bm_ard_3-2-1_56HKE_2022-12-26_nrt.stac-item
2022-12-27 09:27:02	ga_s2bm_ard_3-2-1_56HND_2022-12-26_nrt.stac-item
2022-12-27 09:27:13	ga_s2bm_ard_3-2-1_56HKD_2022-12-26_nrt.stac-item
2022-12-27 09:27:14	ga_s2bm_ard_3-2-1_56HNC_2022-12-26_nrt.stac-item
2022-12-27 09:27:27	ga_s2bm_ard_3-2-1_56HKC_2022-12-26_nrt.stac-item
2022-12-27 09:27:28	ga_s2bm_ard_3-2-1_55HGT_2022-12-26_nrt.stac-item
2022-12-27 09:27:42	ga_s2bm_ard_3-2-1_56HKB_2022-12-26_nrt.stac-item
2022-12-27 09:27:42	ga_s2bm_ard_3-2-1_55HGS_2022-12-26_nrt.stac-item
2022-12-27 09:27:50	ga_s2bm_ard_3-2-1_56GMA_2022-12-26_nrt.stac-item
2022-12-27 09:28:04	ga_s2bm_ard_3-2-1_56GMV_2022-12-26_nrt.stac-item
2022-12-27 09:28:08	ga_s2bm_ard_3-2-1_56GLV_2022-12-26_nrt.stac-item
2022-12-27 09:28:17	ga_s2bm_ard_3-2-1_56GMU_2022-12-26_nrt.stac-item
2022-12-27 09:28:22	ga_s2bm_ard_3-2-1_56GLU_2022-12-26_nrt.stac-item
2022-12-27 09:28:28	ga_s2bm_ard_3-2-1_56GMT_2022-12-26_nrt.stac-item
2022-12-27 09:28:58	ga_s2bm_ard_3-2-1_55GFM_2022-12-26_nrt.stac-item
2022-12-27 11:06:13	ga_s2bm_ard_3-2-1_52HEK_2022-12-27_nrt.stac-item
2022-12-27 11:06:28	ga_s2bm_ard_3-2-1_52HEJ_2022-12-27_nrt.stac-item
2022-12-27 11:06:30	ga_s2bm_ard_3-2-1_52HDJ_2022-12-27_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years