Search ga_s2am_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
2023-01-28 10:50:39	ga_s2am_ard_3-2-1_53LMG_2023-01-28_final.stac-item
2023-01-28 10:50:54	ga_s2am_ard_3-2-1_53LMF_2023-01-28_final.stac-item
2023-01-28 10:51:20	ga_s2am_ard_3-2-1_53LND_2023-01-28_final.stac-item
2023-01-28 10:51:34	ga_s2am_ard_3-2-1_53LNC_2023-01-28_final.stac-item
2023-01-28 10:51:41	ga_s2am_ard_3-2-1_53LLC_2023-01-28_final.stac-item
2023-01-28 10:51:55	ga_s2am_ard_3-2-1_53KLB_2023-01-28_final.stac-item
2023-01-28 10:52:03	ga_s2am_ard_3-2-1_53KNA_2023-01-28_final.stac-item
2023-01-28 10:52:10	ga_s2am_ard_3-2-1_53KLA_2023-01-28_final.stac-item
2023-01-28 10:52:17	ga_s2am_ard_3-2-1_52KHF_2023-01-28_final.stac-item
2023-01-28 10:52:24	ga_s2am_ard_3-2-1_53KLV_2023-01-28_final.stac-item
2023-01-28 10:52:31	ga_s2am_ard_3-2-1_53KNU_2023-01-28_final.stac-item
2023-01-28 10:52:50	ga_s2am_ard_3-2-1_53KMT_2023-01-28_final.stac-item
2023-01-28 10:52:57	ga_s2am_ard_3-2-1_53KKT_2023-01-28_final.stac-item
2023-01-28 10:52:57	ga_s2am_ard_3-2-1_52KHC_2023-01-28_final.stac-item
2023-01-28 10:53:08	ga_s2am_ard_3-2-1_53KLS_2023-01-28_final.stac-item
2023-01-28 10:53:15	ga_s2am_ard_3-2-1_53KMR_2023-01-28_final.stac-item
2023-01-28 10:53:19	ga_s2am_ard_3-2-1_52KHA_2023-01-28_final.stac-item
2023-01-28 10:53:20	ga_s2am_ard_3-2-1_52KGB_2023-01-28_final.stac-item
2023-01-28 10:53:22	ga_s2am_ard_3-2-1_53KMR_2023-01-28_final.stac-item
2023-01-28 10:53:24	ga_s2am_ard_3-2-1_53KLR_2023-01-28_final.stac-item
2023-01-28 10:53:26	ga_s2am_ard_3-2-1_53KKR_2023-01-28_final.stac-item
2023-01-28 10:53:30	ga_s2am_ard_3-2-1_52KGA_2023-01-28_final.stac-item
2023-01-28 10:53:40	ga_s2am_ard_3-2-1_53KKQ_2023-01-28_final.stac-item
2023-01-28 10:53:55	ga_s2am_ard_3-2-1_53KKP_2023-01-28_final.stac-item
2023-01-28 10:54:06	ga_s2am_ard_3-2-1_53JLN_2023-01-28_final.stac-item
2023-01-28 10:54:19	ga_s2am_ard_3-2-1_52JFT_2023-01-28_final.stac-item
2023-01-28 10:54:20	ga_s2am_ard_3-2-1_53JLM_2023-01-28_final.stac-item
2023-01-28 10:54:24	ga_s2am_ard_3-2-1_52JHS_2023-01-28_final.stac-item
2023-01-28 10:54:24	ga_s2am_ard_3-2-1_53JKM_2023-01-28_final.stac-item
2023-01-28 10:54:27	ga_s2am_ard_3-2-1_52JGS_2023-01-28_final.stac-item
2023-01-28 10:54:39	ga_s2am_ard_3-2-1_53JKL_2023-01-28_final.stac-item
2023-01-28 10:54:53	ga_s2am_ard_3-2-1_53JKK_2023-01-28_final.stac-item
2023-01-28 10:55:00	ga_s2am_ard_3-2-1_52JFQ_2023-01-28_final.stac-item
2023-01-28 10:55:03	ga_s2am_ard_3-2-1_53JLJ_2023-01-28_final.stac-item
2023-01-28 10:55:11	ga_s2am_ard_3-2-1_52JGP_2023-01-28_final.stac-item
2023-01-28 10:55:14	ga_s2am_ard_3-2-1_52JFP_2023-01-28_final.stac-item
2023-01-28 10:55:22	ga_s2am_ard_3-2-1_53JKH_2023-01-28_final.stac-item
2023-01-28 10:55:25	ga_s2am_ard_3-2-1_52JGN_2023-01-28_final.stac-item
2023-01-28 10:55:37	ga_s2am_ard_3-2-1_53JKG_2023-01-28_final.stac-item
2023-01-28 10:55:40	ga_s2am_ard_3-2-1_52JGM_2023-01-28_final.stac-item
2023-01-28 10:55:43	ga_s2am_ard_3-2-1_52JFM_2023-01-28_final.stac-item
2023-01-28 10:55:54	ga_s2am_ard_3-2-1_52JFL_2023-01-28_final.stac-item
2023-01-28 10:56:01	ga_s2am_ard_3-2-1_52JFL_2023-01-28_final.stac-item
2023-01-29 10:22:33	ga_s2am_ard_3-2-1_54KUD_2023-01-29_final.stac-item
2023-01-29 10:22:54	ga_s2am_ard_3-2-1_54KWB_2023-01-29_final.stac-item
2023-01-29 10:23:04	ga_s2am_ard_3-2-1_54KXA_2023-01-29_final.stac-item
2023-01-29 10:23:12	ga_s2am_ard_3-2-1_54KVA_2023-01-29_final.stac-item
2023-01-29 10:23:15	ga_s2am_ard_3-2-1_54KXV_2023-01-29_final.stac-item
2023-01-29 10:23:48	ga_s2am_ard_3-2-1_53KRP_2023-01-29_final.stac-item
2023-01-29 10:24:02	ga_s2am_ard_3-2-1_53JRN_2023-01-29_final.stac-item
2023-01-29 10:24:43	ga_s2am_ard_3-2-1_54JUQ_2023-01-29_final.stac-item
2023-01-29 10:24:46	ga_s2am_ard_3-2-1_54JTQ_2023-01-29_final.stac-item
2023-01-29 10:25:01	ga_s2am_ard_3-2-1_54JTP_2023-01-29_final.stac-item
2023-01-29 10:25:03	ga_s2am_ard_3-2-1_53JQJ_2023-01-29_final.stac-item
2023-01-29 10:25:09	ga_s2am_ard_3-2-1_54JTP_2023-01-29_final.stac-item
2023-01-29 10:25:38	ga_s2am_ard_3-2-1_53JPG_2023-01-29_final.stac-item
2023-01-29 10:26:38	ga_s2am_ard_3-2-1_54HUG_2023-01-29_final.stac-item
2023-01-29 10:26:49	ga_s2am_ard_3-2-1_54HUF_2023-01-29_final.stac-item
2023-01-29 12:04:16	ga_s2am_ard_3-2-1_49KGQ_2023-01-29_final.stac-item
2023-01-29 12:04:19	ga_s2am_ard_3-2-1_50KMU_2023-01-29_final.stac-item
2023-01-29 12:04:23	ga_s2am_ard_3-2-1_50KLU_2023-01-29_final.stac-item
2023-01-29 12:04:29	ga_s2am_ard_3-2-1_49KGP_2023-01-29_final.stac-item
2023-01-29 12:04:33	ga_s2am_ard_3-2-1_50JMT_2023-01-29_final.stac-item
2023-01-29 12:04:52	ga_s2am_ard_3-2-1_50JLS_2023-01-29_final.stac-item
2023-01-29 12:04:55	ga_s2am_ard_3-2-1_49JHM_2023-01-29_final.stac-item
2023-01-29 12:04:56	ga_s2am_ard_3-2-1_50JMR_2023-01-29_final.stac-item
2023-01-29 12:05:35	ga_s2am_ard_3-2-1_50JLP_2023-01-29_final.stac-item
2023-01-29 12:06:08	ga_s2am_ard_3-2-1_50JKM_2023-01-29_final.stac-item
2023-02-08 12:02:55	ga_s2am_ard_3-2-1_50KNE_2023-02-08_nrt.stac-item
2023-02-08 12:02:58	ga_s2am_ard_3-2-1_50KLE_2023-02-08_nrt.stac-item
2023-02-08 12:03:04	ga_s2am_ard_3-2-1_50KND_2023-02-08_nrt.stac-item
2023-02-08 12:03:11	ga_s2am_ard_3-2-1_50KLD_2023-02-08_nrt.stac-item
2023-02-08 12:03:16	ga_s2am_ard_3-2-1_49KHU_2023-02-08_nrt.stac-item
2023-02-08 12:03:29	ga_s2am_ard_3-2-1_49KHT_2023-02-08_nrt.stac-item
2023-02-08 12:05:31	ga_s2am_ard_3-2-1_49JFK_2023-02-08_nrt.stac-item
2023-02-08 12:05:46	ga_s2am_ard_3-2-1_49JFJ_2023-02-08_nrt.stac-item
2023-02-08 12:06:01	ga_s2am_ard_3-2-1_49JFH_2023-02-08_nrt.stac-item
2023-02-08 12:06:11	ga_s2am_ard_3-2-1_49JGG_2023-02-08_nrt.stac-item
2023-02-08 12:06:14	ga_s2am_ard_3-2-1_49JFG_2023-02-08_nrt.stac-item
2023-02-08 12:06:20	ga_s2am_ard_3-2-1_49JFF_2023-02-08_nrt.stac-item
2023-02-08 12:06:20	ga_s2am_ard_3-2-1_49JFG_2023-02-08_nrt.stac-item
2023-02-08 12:06:24	ga_s2am_ard_3-2-1_49JFF_2023-02-08_nrt.stac-item
2023-02-09 09:49:35	ga_s2am_ard_3-2-1_56LMP_2023-02-09_nrt.stac-item
2023-02-09 09:49:39	ga_s2am_ard_3-2-1_56LLP_2023-02-09_nrt.stac-item
2023-02-09 09:49:48	ga_s2am_ard_3-2-1_56LMN_2023-02-09_nrt.stac-item
2023-02-09 09:49:48	ga_s2am_ard_3-2-1_55LGJ_2023-02-09_nrt.stac-item
2023-02-09 09:49:53	ga_s2am_ard_3-2-1_56LLN_2023-02-09_nrt.stac-item
2023-02-09 09:49:58	ga_s2am_ard_3-2-1_56LMM_2023-02-09_nrt.stac-item
2023-02-09 09:50:00	ga_s2am_ard_3-2-1_55LGH_2023-02-09_nrt.stac-item
2023-02-09 09:50:03	ga_s2am_ard_3-2-1_56LLM_2023-02-09_nrt.stac-item
2023-02-09 09:51:02	ga_s2am_ard_3-2-1_55LGD_2023-02-09_nrt.stac-item
2023-02-09 09:51:58	ga_s2am_ard_3-2-1_55KGV_2023-02-09_nrt.stac-item
2023-02-09 09:52:07	ga_s2am_ard_3-2-1_56KKD_2023-02-09_nrt.stac-item
2023-02-09 09:57:54	ga_s2am_ard_3-2-1_54HXB_2023-02-09_nrt.stac-item
2023-02-09 09:58:08	ga_s2am_ard_3-2-1_54GXA_2023-02-09_nrt.stac-item
2023-02-09 09:58:12	ga_s2am_ard_3-2-1_54GWA_2023-02-09_nrt.stac-item
2023-02-09 09:58:22	ga_s2am_ard_3-2-1_54GXV_2023-02-09_nrt.stac-item
2023-02-09 09:58:25	ga_s2am_ard_3-2-1_54GWV_2023-02-09_nrt.stac-item
2023-02-09 09:58:30	ga_s2am_ard_3-2-1_54GXU_2023-02-09_nrt.stac-item
2023-02-09 09:58:30	ga_s2am_ard_3-2-1_54GVV_2023-02-09_nrt.stac-item

Return to ga_s2am_ard_3 whole collection overview

ga_s2am_ard_3: Geoscience Australia Sentinel 2A MSI Analysis Ready Data Collection 3

Baseline satellite data

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years