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
2019-07-21 11:01:43	ga_s2am_ard_3-2-1_53LLC_2019-07-21_final.stac-item
2019-07-21 11:01:47	ga_s2am_ard_3-2-1_53LKC_2019-07-21_final.stac-item
2019-07-21 11:01:48	ga_s2am_ard_3-2-1_52LHH_2019-07-21_final.stac-item
2019-07-21 11:01:51	ga_s2am_ard_3-2-1_52LGH_2019-07-21_final.stac-item
2019-07-21 11:01:55	ga_s2am_ard_3-2-1_52LFH_2019-07-21_final.stac-item
2019-07-21 11:01:57	ga_s2am_ard_3-2-1_53KLB_2019-07-21_final.stac-item
2019-07-21 11:02:01	ga_s2am_ard_3-2-1_53KKB_2019-07-21_final.stac-item
2019-07-21 11:02:02	ga_s2am_ard_3-2-1_52KHG_2019-07-21_final.stac-item
2019-07-21 11:02:06	ga_s2am_ard_3-2-1_52KGG_2019-07-21_final.stac-item
2019-07-21 11:02:09	ga_s2am_ard_3-2-1_52KFG_2019-07-21_final.stac-item
2019-07-27 11:21:52	ga_s2am_ard_3-2-1_52LDH_2019-07-27_final.stac-item
2019-07-27 11:21:55	ga_s2am_ard_3-2-1_52LCH_2019-07-27_final.stac-item
2019-07-27 11:21:58	ga_s2am_ard_3-2-1_52LBH_2019-07-27_final.stac-item
2019-07-27 11:21:59	ga_s2am_ard_3-2-1_51LZC_2019-07-27_final.stac-item
2019-07-27 11:22:04	ga_s2am_ard_3-2-1_51LYC_2019-07-27_final.stac-item
2019-07-27 11:22:09	ga_s2am_ard_3-2-1_52KCG_2019-07-27_final.stac-item
2019-07-27 11:22:11	ga_s2am_ard_3-2-1_52KBG_2019-07-27_final.stac-item
2019-07-27 11:22:11	ga_s2am_ard_3-2-1_51KZB_2019-07-27_final.stac-item
2019-07-27 11:22:13	ga_s2am_ard_3-2-1_51KYB_2019-07-27_final.stac-item
2019-07-31 11:01:43	ga_s2am_ard_3-2-1_53LLC_2019-07-31_final.stac-item
2019-07-31 11:01:46	ga_s2am_ard_3-2-1_53LKC_2019-07-31_final.stac-item
2019-07-31 11:01:47	ga_s2am_ard_3-2-1_52LHH_2019-07-31_final.stac-item
2019-07-31 11:01:51	ga_s2am_ard_3-2-1_52LGH_2019-07-31_final.stac-item
2019-07-31 11:01:55	ga_s2am_ard_3-2-1_52LFH_2019-07-31_final.stac-item
2019-07-31 11:01:56	ga_s2am_ard_3-2-1_53KLB_2019-07-31_final.stac-item
2019-07-31 11:02:00	ga_s2am_ard_3-2-1_53KKB_2019-07-31_final.stac-item
2019-07-31 11:02:02	ga_s2am_ard_3-2-1_52KHG_2019-07-31_final.stac-item
2019-07-31 11:02:05	ga_s2am_ard_3-2-1_52KGG_2019-07-31_final.stac-item
2019-07-31 11:02:08	ga_s2am_ard_3-2-1_52KFG_2019-07-31_final.stac-item
2019-08-10 11:01:42	ga_s2am_ard_3-2-1_53LLC_2019-08-10_final.stac-item
2019-08-10 11:01:45	ga_s2am_ard_3-2-1_53LKC_2019-08-10_final.stac-item
2019-08-10 11:01:47	ga_s2am_ard_3-2-1_52LHH_2019-08-10_final.stac-item
2019-08-10 11:01:50	ga_s2am_ard_3-2-1_52LGH_2019-08-10_final.stac-item
2019-08-10 11:01:54	ga_s2am_ard_3-2-1_52LFH_2019-08-10_final.stac-item
2019-08-10 11:01:55	ga_s2am_ard_3-2-1_53KLB_2019-08-10_final.stac-item
2019-08-10 11:02:00	ga_s2am_ard_3-2-1_53KKB_2019-08-10_final.stac-item
2019-08-10 11:02:01	ga_s2am_ard_3-2-1_52KHG_2019-08-10_final.stac-item
2019-08-10 11:02:04	ga_s2am_ard_3-2-1_52KGG_2019-08-10_final.stac-item
2019-08-10 11:02:07	ga_s2am_ard_3-2-1_52KFG_2019-08-10_final.stac-item
2019-08-12 11:41:59	ga_s2am_ard_3-2-1_51LWC_2019-08-12_final.stac-item
2019-08-12 11:42:02	ga_s2am_ard_3-2-1_51LVC_2019-08-12_final.stac-item
2023-12-09 10:01:08	ga_s2am_ard_3-2-1_55LFC_2023-12-09_final
2023-12-09 10:01:12	ga_s2am_ard_3-2-1_55LEC_2023-12-09_final
2023-12-09 10:01:15	ga_s2am_ard_3-2-1_55LDC_2023-12-09_final
2023-12-09 10:01:19	ga_s2am_ard_3-2-1_55LCC_2023-12-09_final
2023-12-11 10:41:24	ga_s2am_ard_3-2-1_54LTH_2023-12-11_final
2023-12-11 10:41:26	ga_s2am_ard_3-2-1_53LRC_2023-12-11_final
2023-12-11 10:41:29	ga_s2am_ard_3-2-1_53LQC_2023-12-11_final
2023-12-11 10:41:33	ga_s2am_ard_3-2-1_53LPC_2023-12-11_final
2023-12-11 10:41:36	ga_s2am_ard_3-2-1_53LNC_2023-12-11_final
2023-12-11 10:41:38	ga_s2am_ard_3-2-1_54KTG_2023-12-11_final
2023-12-11 10:41:40	ga_s2am_ard_3-2-1_53KRB_2023-12-11_final
2023-12-11 10:41:44	ga_s2am_ard_3-2-1_53KQB_2023-12-11_final
2023-12-11 10:41:47	ga_s2am_ard_3-2-1_53KPB_2023-12-11_final
2023-12-12 10:11:14	ga_s2am_ard_3-2-1_55LCC_2023-12-12_final
2023-12-12 10:11:18	ga_s2am_ard_3-2-1_55LBC_2023-12-12_final
2023-12-12 10:11:19	ga_s2am_ard_3-2-1_54LZH_2023-12-12_final
2023-12-12 10:11:22	ga_s2am_ard_3-2-1_54LYH_2023-12-12_final
2023-12-12 10:11:29	ga_s2am_ard_3-2-1_55KCB_2023-12-12_final
2023-12-12 10:11:32	ga_s2am_ard_3-2-1_55KBB_2023-12-12_final
2023-12-12 10:11:33	ga_s2am_ard_3-2-1_54KZG_2023-12-12_final
2023-12-12 10:11:37	ga_s2am_ard_3-2-1_54KYG_2023-12-12_final
2023-12-13 11:21:54	ga_s2am_ard_3-2-1_51LYC_2023-12-13_final
2023-12-13 11:22:00	ga_s2am_ard_3-2-1_52KCG_2023-12-13_final
2023-12-13 11:22:03	ga_s2am_ard_3-2-1_52KBG_2023-12-13_final
2023-12-13 11:22:04	ga_s2am_ard_3-2-1_51KZB_2023-12-13_final
2023-12-13 11:22:07	ga_s2am_ard_3-2-1_51KYB_2023-12-13_final
2023-12-23 09:41:11	ga_s2am_ard_3-2-1_56LNH_2023-12-23_nrt
2023-12-23 09:41:12	ga_s2am_ard_3-2-1_56LMH_2023-12-23_nrt
2023-12-23 09:41:13	ga_s2am_ard_3-2-1_56LLH_2023-12-23_nrt
2023-12-23 09:41:15	ga_s2am_ard_3-2-1_56LKH_2023-12-23_final
2023-12-30 11:11:37	ga_s2am_ard_3-2-1_52LGH_2023-12-30_final
2023-12-30 11:11:42	ga_s2am_ard_3-2-1_52LFH_2023-12-30_final
2023-12-30 11:11:45	ga_s2am_ard_3-2-1_52LEH_2023-12-30_final
2023-12-30 11:11:47	ga_s2am_ard_3-2-1_52KGG_2023-12-30_final
2023-12-30 11:11:49	ga_s2am_ard_3-2-1_52LDH_2023-12-30_final
2023-12-30 11:11:56	ga_s2am_ard_3-2-1_52KFG_2023-12-30_final
2023-12-31 10:41:26	ga_s2am_ard_3-2-1_54LTH_2023-12-31_final
2023-12-31 10:41:28	ga_s2am_ard_3-2-1_53LRC_2023-12-31_final
2023-12-31 10:41:31	ga_s2am_ard_3-2-1_53LQC_2023-12-31_final
2023-12-31 10:41:35	ga_s2am_ard_3-2-1_53LPC_2023-12-31_final
2023-12-31 10:41:38	ga_s2am_ard_3-2-1_53LNC_2023-12-31_final
2023-12-31 10:41:40	ga_s2am_ard_3-2-1_54KTG_2023-12-31_final
2023-12-31 10:41:42	ga_s2am_ard_3-2-1_53KRB_2023-12-31_final
2024-02-17 10:01:12	ga_s2am_ard_3-2-1_55LFC_2024-02-17_final
2024-02-17 10:01:15	ga_s2am_ard_3-2-1_55LEC_2024-02-17_final
2024-02-17 10:01:22	ga_s2am_ard_3-2-1_55LCC_2024-02-17_final
2024-02-20 10:11:17	ga_s2am_ard_3-2-1_55LCC_2024-02-20_final
2024-02-20 10:11:21	ga_s2am_ard_3-2-1_55LBC_2024-02-20_final
2024-02-20 10:11:22	ga_s2am_ard_3-2-1_54LZH_2024-02-20_final
2024-02-20 10:11:25	ga_s2am_ard_3-2-1_54LYH_2024-02-20_final
2024-02-20 10:11:32	ga_s2am_ard_3-2-1_55KCB_2024-02-20_final
2024-02-20 10:11:35	ga_s2am_ard_3-2-1_55KBB_2024-02-20_final
2024-02-20 10:11:36	ga_s2am_ard_3-2-1_54KZG_2024-02-20_final
2024-02-20 10:11:40	ga_s2am_ard_3-2-1_54KYG_2024-02-20_final
2024-02-28 11:11:39	ga_s2am_ard_3-2-1_52LGH_2024-02-28_final
2024-02-28 11:11:44	ga_s2am_ard_3-2-1_52LFH_2024-02-28_final
2024-02-28 11:11:48	ga_s2am_ard_3-2-1_52LEH_2024-02-28_final
2024-02-28 11:11:50	ga_s2am_ard_3-2-1_52KGG_2024-02-28_final
2024-02-28 11:11:51	ga_s2am_ard_3-2-1_52LDH_2024-02-28_final

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