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
2018-07-25 09:50:55	ga_s2am_ard_3-2-1_55KDS_2018-07-25_final.stac-item
2018-07-25 09:50:55	ga_s2am_ard_3-2-1_55KES_2018-07-25_final.stac-item
2018-07-25 09:50:55	ga_s2am_ard_3-2-1_55KFS_2018-07-25_final.stac-item
2018-07-25 09:50:55	ga_s2am_ard_3-2-1_55KGS_2018-07-25_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_51KUS_2018-07-25_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_51KVS_2018-07-25_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_51KWS_2018-07-25_final.stac-item
2018-07-25 11:32:58	ga_s2am_ard_3-2-1_51KXS_2018-07-25_final.stac-item
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_53KKS_2018-07-26_final.stac-item
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52KEB_2018-07-26_final.stac-item
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52KFB_2018-07-26_final.stac-item
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52KGB_2018-07-26_final.stac-item
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52KHA_2018-07-26_final.stac-item
2018-07-26 10:57:17	ga_s2am_ard_3-2-1_52KHB_2018-07-26_final.stac-item
2018-07-29 11:13:14	ga_s2am_ard_3-2-1_52KBB_2018-07-29_final.stac-item
2018-07-29 11:13:14	ga_s2am_ard_3-2-1_52KDB_2018-07-29_final.stac-item
2018-07-29 11:13:14	ga_s2am_ard_3-2-1_52KEB_2018-07-29_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_53KKS_2018-08-02_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_53KLS_2018-08-02_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_53KMS_2018-08-02_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_52KGB_2018-08-02_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_52KHA_2018-08-02_final.stac-item
2018-08-02 10:47:25	ga_s2am_ard_3-2-1_52KHB_2018-08-02_final.stac-item
2018-08-04 09:50:54	ga_s2am_ard_3-2-1_55KDS_2018-08-04_final.stac-item
2018-08-04 09:50:54	ga_s2am_ard_3-2-1_55KES_2018-08-04_final.stac-item
2018-08-04 09:50:54	ga_s2am_ard_3-2-1_55KFS_2018-08-04_final.stac-item
2018-08-04 09:50:54	ga_s2am_ard_3-2-1_55KGS_2018-08-04_final.stac-item
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_53KKS_2018-08-05_final.stac-item
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52KEB_2018-08-05_final.stac-item
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52KFB_2018-08-05_final.stac-item
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52KGB_2018-08-05_final.stac-item
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52KHA_2018-08-05_final.stac-item
2018-08-05 10:57:16	ga_s2am_ard_3-2-1_52KHB_2018-08-05_final.stac-item
2019-03-28 10:12:54	ga_s2am_ard_3-2-1_54KYB_2019-03-28_final.stac-item
2019-03-28 10:12:57	ga_s2am_ard_3-2-1_54KXB_2019-03-28_final.stac-item
2019-03-28 10:13:03	ga_s2am_ard_3-2-1_54KWB_2019-03-28_final.stac-item
2019-03-28 10:13:04	ga_s2am_ard_3-2-1_54KZA_2019-03-28_final.stac-item
2019-04-03 12:13:40	ga_s2am_ard_3-2-1_50KKB_2019-04-03_final.stac-item
2019-04-03 12:13:55	ga_s2am_ard_3-2-1_49KHR_2019-04-03_final.stac-item
2019-04-03 12:13:59	ga_s2am_ard_3-2-1_49KGR_2019-04-03_final.stac-item
2019-06-29 12:03:38	ga_s2am_ard_3-2-1_50KNB_2019-06-29_final.stac-item
2019-06-29 12:03:42	ga_s2am_ard_3-2-1_50KMB_2019-06-29_final.stac-item
2019-06-29 12:03:46	ga_s2am_ard_3-2-1_50KLB_2019-06-29_final.stac-item
2019-06-29 12:03:49	ga_s2am_ard_3-2-1_50KKB_2019-06-29_final.stac-item
2019-06-29 12:04:04	ga_s2am_ard_3-2-1_49KHR_2019-06-29_final.stac-item
2019-06-30 11:33:28	ga_s2am_ard_3-2-1_51KXS_2019-06-30_final.stac-item
2019-06-30 11:33:32	ga_s2am_ard_3-2-1_51KWS_2019-06-30_final.stac-item
2019-06-30 11:33:35	ga_s2am_ard_3-2-1_51KVS_2019-06-30_final.stac-item
2019-06-30 11:33:39	ga_s2am_ard_3-2-1_51KUS_2019-06-30_final.stac-item
2019-07-06 11:53:37	ga_s2am_ard_3-2-1_50KQB_2019-07-06_final.stac-item
2019-07-06 11:53:41	ga_s2am_ard_3-2-1_50KPB_2019-07-06_final.stac-item
2019-07-06 11:53:44	ga_s2am_ard_3-2-1_50KNB_2019-07-06_final.stac-item
2019-07-06 11:53:48	ga_s2am_ard_3-2-1_50KMB_2019-07-06_final.stac-item
2019-07-19 12:03:38	ga_s2am_ard_3-2-1_50KNB_2019-07-19_final.stac-item
2019-07-19 12:03:43	ga_s2am_ard_3-2-1_50KMB_2019-07-19_final.stac-item
2019-07-19 12:03:46	ga_s2am_ard_3-2-1_50KLB_2019-07-19_final.stac-item
2019-07-19 12:03:49	ga_s2am_ard_3-2-1_50KKB_2019-07-19_final.stac-item
2019-07-19 12:04:04	ga_s2am_ard_3-2-1_49KHR_2019-07-19_final.stac-item
2022-10-29 09:42:43	ga_s2am_ard_3-2-1_56KLB_2022-10-29_final.stac-item
2022-10-29 09:42:46	ga_s2am_ard_3-2-1_56KKB_2022-10-29_final.stac-item
2022-10-29 09:42:47	ga_s2am_ard_3-2-1_55KHS_2022-10-29_final.stac-item
2022-10-29 09:42:50	ga_s2am_ard_3-2-1_55KGS_2022-10-29_final.stac-item
2022-10-29 09:43:01	ga_s2am_ard_3-2-1_55KHR_2022-10-29_final.stac-item
2022-10-29 09:43:05	ga_s2am_ard_3-2-1_55KGR_2022-10-29_final.stac-item
2022-10-31 10:22:57	ga_s2am_ard_3-2-1_54KXB_2022-10-31_final.stac-item
2022-10-31 10:23:00	ga_s2am_ard_3-2-1_54KWB_2022-10-31_final.stac-item
2022-10-31 10:23:04	ga_s2am_ard_3-2-1_54KVB_2022-10-31_final.stac-item
2022-10-31 10:23:07	ga_s2am_ard_3-2-1_54KUB_2022-10-31_final.stac-item
2022-10-31 12:03:37	ga_s2am_ard_3-2-1_50KNB_2022-10-31_final.stac-item
2022-10-31 12:03:41	ga_s2am_ard_3-2-1_50KMB_2022-10-31_final.stac-item
2022-10-31 12:03:45	ga_s2am_ard_3-2-1_50KLB_2022-10-31_final.stac-item
2022-10-31 12:03:48	ga_s2am_ard_3-2-1_50KKB_2022-10-31_final.stac-item
2022-10-31 12:04:03	ga_s2am_ard_3-2-1_49KHR_2022-10-31_final.stac-item
2022-11-04 11:43:29	ga_s2am_ard_3-2-1_51KVS_2022-11-04_final.stac-item
2022-11-04 11:43:33	ga_s2am_ard_3-2-1_51KUS_2022-11-04_final.stac-item
2022-11-04 11:43:36	ga_s2am_ard_3-2-1_51KTS_2022-11-04_final.stac-item
2022-11-04 11:43:37	ga_s2am_ard_3-2-1_50KRB_2022-11-04_final.stac-item
2022-11-04 11:43:40	ga_s2am_ard_3-2-1_50KQB_2022-11-04_final.stac-item
2022-11-04 11:43:51	ga_s2am_ard_3-2-1_50KRA_2022-11-04_final.stac-item
2022-11-04 11:43:55	ga_s2am_ard_3-2-1_50KQA_2022-11-04_final.stac-item
2022-11-07 10:12:54	ga_s2am_ard_3-2-1_55KBS_2022-11-07_final.stac-item
2022-11-07 10:12:54	ga_s2am_ard_3-2-1_54KZB_2022-11-07_final.stac-item
2022-11-07 10:12:58	ga_s2am_ard_3-2-1_54KYB_2022-11-07_final.stac-item
2022-11-07 10:13:02	ga_s2am_ard_3-2-1_54KXB_2022-11-07_final.stac-item
2022-11-07 10:13:08	ga_s2am_ard_3-2-1_54KWB_2022-11-07_final.stac-item
2022-11-07 10:13:09	ga_s2am_ard_3-2-1_54KZA_2022-11-07_final.stac-item
2022-11-07 10:13:13	ga_s2am_ard_3-2-1_54KYA_2022-11-07_final.stac-item
2022-11-13 10:33:01	ga_s2am_ard_3-2-1_54KUB_2022-11-13_final.stac-item
2022-11-13 10:33:05	ga_s2am_ard_3-2-1_54KTB_2022-11-13_final.stac-item
2022-11-13 10:33:05	ga_s2am_ard_3-2-1_53KRS_2022-11-13_final.stac-item
2022-11-13 10:33:09	ga_s2am_ard_3-2-1_53KQS_2022-11-13_final.stac-item
2022-11-13 10:33:15	ga_s2am_ard_3-2-1_53KPS_2022-11-13_final.stac-item
2022-11-13 10:33:20	ga_s2am_ard_3-2-1_53KRR_2022-11-13_final.stac-item
2022-11-13 10:33:23	ga_s2am_ard_3-2-1_53KQR_2022-11-13_final.stac-item
2022-11-14 11:43:27	ga_s2am_ard_3-2-1_51KVS_2022-11-14_final.stac-item
2022-11-14 11:43:32	ga_s2am_ard_3-2-1_51KUS_2022-11-14_final.stac-item
2022-11-14 11:43:35	ga_s2am_ard_3-2-1_51KTS_2022-11-14_final.stac-item
2022-11-14 11:43:36	ga_s2am_ard_3-2-1_50KRB_2022-11-14_final.stac-item
2022-11-14 11:43:39	ga_s2am_ard_3-2-1_50KQB_2022-11-14_final.stac-item
2022-11-14 11:43:50	ga_s2am_ard_3-2-1_50KRA_2022-11-14_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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