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
2019-05-09 10:51:35	ga_s2am_ard_3-2-1_53LPC_2019-05-09_final
2019-05-09 10:51:40	ga_s2am_ard_3-2-1_53LNC_2019-05-09_final.stac-item
2019-05-09 10:51:44	ga_s2am_ard_3-2-1_53LMC_2019-05-09_final.stac-item
2019-05-09 10:51:47	ga_s2am_ard_3-2-1_53LLC_2019-05-09_final.stac-item
2019-07-20 09:51:21	ga_s2am_ard_3-2-1_55LGC_2019-07-20_final.stac-item
2019-07-20 09:51:24	ga_s2am_ard_3-2-1_55LFC_2019-07-20_final.stac-item
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 11:02:02	ga_s2am_ard_3-2-1_52KHG_2019-07-21_final.stac-item
2019-07-24 11:11:45	ga_s2am_ard_3-2-1_52LGH_2019-07-24_final.stac-item
2019-07-24 11:11:50	ga_s2am_ard_3-2-1_52LFH_2019-07-24_final.stac-item
2019-07-24 11:11:53	ga_s2am_ard_3-2-1_52LEH_2019-07-24_final.stac-item
2019-07-24 11:11:57	ga_s2am_ard_3-2-1_52LDH_2019-07-24_final.stac-item
2019-07-25 10:41:39	ga_s2am_ard_3-2-1_53LQC_2019-07-25_final
2019-07-25 10:41:43	ga_s2am_ard_3-2-1_53LPC_2019-07-25_final
2019-07-25 10:41:46	ga_s2am_ard_3-2-1_53LNC_2019-07-25_final.stac-item
2019-07-30 09:51:20	ga_s2am_ard_3-2-1_55LGC_2019-07-30_final.stac-item
2019-07-30 09:51:23	ga_s2am_ard_3-2-1_55LFC_2019-07-30_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 11:02:02	ga_s2am_ard_3-2-1_52KHG_2019-07-31_final.stac-item
2019-08-02 10:01:18	ga_s2am_ard_3-2-1_55LFC_2019-08-02_final.stac-item
2019-08-02 10:01:22	ga_s2am_ard_3-2-1_55LEC_2019-08-02_final.stac-item
2019-08-02 10:01:29	ga_s2am_ard_3-2-1_55LCC_2019-08-02_final.stac-item
2019-08-04 10:41:46	ga_s2am_ard_3-2-1_53LNC_2019-08-04_final.stac-item
2019-08-05 10:11:23	ga_s2am_ard_3-2-1_55LCC_2019-08-05_final.stac-item
2019-08-05 10:11:27	ga_s2am_ard_3-2-1_55LBC_2019-08-05_final.stac-item
2019-08-05 10:11:28	ga_s2am_ard_3-2-1_54LZH_2019-08-05_final.stac-item
2019-08-05 10:11:31	ga_s2am_ard_3-2-1_54LYH_2019-08-05_final.stac-item
2019-08-05 10:11:42	ga_s2am_ard_3-2-1_54KZG_2019-08-05_final.stac-item
2019-08-09 09:51:19	ga_s2am_ard_3-2-1_55LGC_2019-08-09_final.stac-item
2019-08-09 09:51:22	ga_s2am_ard_3-2-1_55LFC_2019-08-09_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 11:02:01	ga_s2am_ard_3-2-1_52KHG_2019-08-10_final.stac-item
2019-08-12 10:01:17	ga_s2am_ard_3-2-1_55LFC_2019-08-12_final.stac-item
2019-08-12 10:01:21	ga_s2am_ard_3-2-1_55LEC_2019-08-12_final.stac-item
2019-08-12 10:01:28	ga_s2am_ard_3-2-1_55LCC_2019-08-12_final.stac-item
2019-08-14 10:41:38	ga_s2am_ard_3-2-1_53LQC_2019-08-14_final
2019-08-14 10:41:41	ga_s2am_ard_3-2-1_53LPC_2019-08-14_final
2019-08-14 10:41:45	ga_s2am_ard_3-2-1_53LNC_2019-08-14_final.stac-item
2019-10-31 11:42:02	ga_s2am_ard_3-2-1_51LWC_2019-10-31_final.stac-item
2019-10-31 11:42:04	ga_s2am_ard_3-2-1_51LVC_2019-10-31_final.stac-item
2019-11-20 11:41:56	ga_s2am_ard_3-2-1_51LWC_2019-11-20_final.stac-item
2019-11-20 11:42:00	ga_s2am_ard_3-2-1_51LVC_2019-11-20_final.stac-item
2020-09-20 10:51:36	ga_s2am_ard_3-2-1_53LPC_2020-09-20_final
2020-09-20 10:51:41	ga_s2am_ard_3-2-1_53LNC_2020-09-20_final.stac-item
2020-09-20 10:51:45	ga_s2am_ard_3-2-1_53LMC_2020-09-20_final.stac-item
2020-09-20 10:51:48	ga_s2am_ard_3-2-1_53LLC_2020-09-20_final.stac-item
2020-09-22 09:51:17	ga_s2am_ard_3-2-1_55LHC_2020-09-22_final
2020-09-22 09:51:20	ga_s2am_ard_3-2-1_55LGC_2020-09-22_final.stac-item
2020-09-22 09:51:24	ga_s2am_ard_3-2-1_55LFC_2020-09-22_final.stac-item
2020-09-22 09:51:31	ga_s2am_ard_3-2-1_55KHB_2020-09-22_final
2020-09-25 11:42:01	ga_s2am_ard_3-2-1_51LWC_2020-09-25_final.stac-item
2020-09-25 11:42:04	ga_s2am_ard_3-2-1_51LVC_2020-09-25_final.stac-item
2020-09-25 11:42:07	ga_s2am_ard_3-2-1_51LUC_2020-09-25_final
2020-09-29 09:41:38	ga_s2am_ard_3-2-1_55KHB_2020-09-29_final
2020-09-29 11:21:52	ga_s2am_ard_3-2-1_52LDH_2020-09-29_final.stac-item
2020-09-29 11:21:56	ga_s2am_ard_3-2-1_52LCH_2020-09-29_final.stac-item
2020-09-29 11:21:59	ga_s2am_ard_3-2-1_52LBH_2020-09-29_final.stac-item
2020-09-29 11:22:00	ga_s2am_ard_3-2-1_51LZC_2020-09-29_final.stac-item
2020-09-29 11:22:04	ga_s2am_ard_3-2-1_51LYC_2020-09-29_final.stac-item
2020-09-29 11:22:14	ga_s2am_ard_3-2-1_51KZB_2020-09-29_final.stac-item
2020-10-02 09:51:18	ga_s2am_ard_3-2-1_55LHC_2020-10-02_final
2020-10-02 09:51:21	ga_s2am_ard_3-2-1_55LGC_2020-10-02_final.stac-item
2020-10-02 09:51:24	ga_s2am_ard_3-2-1_55LFC_2020-10-02_final.stac-item
2020-10-02 09:51:32	ga_s2am_ard_3-2-1_55KHB_2020-10-02_final
2020-10-05 11:42:01	ga_s2am_ard_3-2-1_51LWC_2020-10-05_final.stac-item
2020-10-05 11:42:04	ga_s2am_ard_3-2-1_51LVC_2020-10-05_final.stac-item
2020-10-05 11:42:08	ga_s2am_ard_3-2-1_51LUC_2020-10-05_final
2020-10-10 10:51:37	ga_s2am_ard_3-2-1_53LPC_2020-10-10_final
2020-10-10 10:51:42	ga_s2am_ard_3-2-1_53LNC_2020-10-10_final.stac-item
2020-10-10 10:51:46	ga_s2am_ard_3-2-1_53LMC_2020-10-10_final.stac-item
2020-10-10 10:51:49	ga_s2am_ard_3-2-1_53LLC_2020-10-10_final.stac-item
2022-03-13 11:21:51	ga_s2am_ard_3-2-1_52LDH_2022-03-13_final.stac-item
2022-03-13 11:21:54	ga_s2am_ard_3-2-1_52LCH_2022-03-13_final.stac-item
2022-03-13 11:21:57	ga_s2am_ard_3-2-1_52LBH_2022-03-13_final.stac-item
2022-03-13 11:21:58	ga_s2am_ard_3-2-1_51LZC_2022-03-13_final.stac-item
2022-03-13 11:22:03	ga_s2am_ard_3-2-1_51LYC_2022-03-13_final.stac-item
2022-03-13 11:22:13	ga_s2am_ard_3-2-1_51KZB_2022-03-13_final.stac-item
2022-03-14 10:51:35	ga_s2am_ard_3-2-1_53LPC_2022-03-14_final.stac-item
2022-03-14 10:51:40	ga_s2am_ard_3-2-1_53LNC_2022-03-14_final.stac-item
2022-03-14 10:51:44	ga_s2am_ard_3-2-1_53LMC_2022-03-14_final.stac-item
2022-03-14 10:51:47	ga_s2am_ard_3-2-1_53LLC_2022-03-14_final.stac-item
2022-03-25 10:21:25	ga_s2am_ard_3-2-1_54LYH_2022-03-25_final.stac-item
2022-03-25 10:21:29	ga_s2am_ard_3-2-1_54LXH_2022-03-25_final.stac-item
2022-03-25 10:21:32	ga_s2am_ard_3-2-1_54LWH_2022-03-25_final.stac-item
2022-03-25 10:21:35	ga_s2am_ard_3-2-1_54LVH_2022-03-25_final.stac-item
2022-04-04 10:21:24	ga_s2am_ard_3-2-1_54LYH_2022-04-04_final.stac-item
2022-04-04 10:21:28	ga_s2am_ard_3-2-1_54LXH_2022-04-04_final.stac-item
2022-04-04 10:21:31	ga_s2am_ard_3-2-1_54LWH_2022-04-04_final.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

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