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
2019-01-01 11:32:26	ga_s2am_ard_3-2-1_51KVA_2019-01-01_final.stac-item
2019-01-01 11:32:40	ga_s2am_ard_3-2-1_51KVV_2019-01-01_final.stac-item
2019-01-01 11:32:52	ga_s2am_ard_3-2-1_51KWU_2019-01-01_final.stac-item
2019-01-04 11:41:50	ga_s2am_ard_3-2-1_51LWC_2019-01-04_final.stac-item
2019-01-04 11:42:22	ga_s2am_ard_3-2-1_51KVA_2019-01-04_final.stac-item
2019-01-04 11:42:36	ga_s2am_ard_3-2-1_51KVV_2019-01-04_final.stac-item
2019-01-04 11:42:40	ga_s2am_ard_3-2-1_51KUV_2019-01-04_final.stac-item
2019-01-04 11:42:58	ga_s2am_ard_3-2-1_50KRD_2019-01-04_final.stac-item
2019-01-11 11:31:13	ga_s2am_ard_3-2-1_52LBK_2019-01-11_final.stac-item
2019-01-11 11:31:55	ga_s2am_ard_3-2-1_51LWC_2019-01-11_final.stac-item
2019-01-11 11:32:28	ga_s2am_ard_3-2-1_51KVA_2019-01-11_final.stac-item
2019-01-11 11:32:42	ga_s2am_ard_3-2-1_51KVV_2019-01-11_final.stac-item
2019-01-11 11:32:54	ga_s2am_ard_3-2-1_51KWU_2019-01-11_final.stac-item
2019-01-12 11:02:50	ga_s2am_ard_3-2-1_52KHC_2019-01-12_final.stac-item
2019-01-14 11:42:38	ga_s2am_ard_3-2-1_51KVV_2019-01-14_final.stac-item
2019-01-14 11:43:00	ga_s2am_ard_3-2-1_50KRD_2019-01-14_final.stac-item
2019-01-17 11:52:55	ga_s2am_ard_3-2-1_50KRD_2019-01-17_final.stac-item
2019-01-18 11:21:36	ga_s2am_ard_3-2-1_51LZD_2019-01-18_final.stac-item
2019-01-21 11:32:29	ga_s2am_ard_3-2-1_51KVA_2019-01-21_final.stac-item
2019-01-21 11:32:43	ga_s2am_ard_3-2-1_51KVV_2019-01-21_final.stac-item
2019-01-21 11:32:55	ga_s2am_ard_3-2-1_51KWU_2019-01-21_final.stac-item
2019-01-22 11:04:14	ga_s2am_ard_3-2-1_52JET_2019-01-22_final.stac-item
2019-01-24 11:41:52	ga_s2am_ard_3-2-1_51LWC_2019-01-24_final.stac-item
2019-01-24 11:42:24	ga_s2am_ard_3-2-1_51KVA_2019-01-24_final.stac-item
2019-01-24 11:42:39	ga_s2am_ard_3-2-1_51KVV_2019-01-24_final.stac-item
2019-01-24 11:42:42	ga_s2am_ard_3-2-1_51KUV_2019-01-24_final.stac-item
2019-01-24 11:43:01	ga_s2am_ard_3-2-1_50KRD_2019-01-24_final.stac-item
2019-01-25 11:11:30	ga_s2am_ard_3-2-1_52LEJ_2019-01-25_final.stac-item
2019-01-27 11:52:56	ga_s2am_ard_3-2-1_50KRD_2019-01-27_final.stac-item
2019-01-28 11:21:21	ga_s2am_ard_3-2-1_52LBK_2019-01-28_final.stac-item
2019-01-28 11:23:22	ga_s2am_ard_3-2-1_51KYS_2019-01-28_final.stac-item
2019-01-31 11:31:15	ga_s2am_ard_3-2-1_52LBK_2019-01-31_final.stac-item
2019-01-31 11:31:32	ga_s2am_ard_3-2-1_51LZD_2019-01-31_final.stac-item
2019-01-31 11:32:29	ga_s2am_ard_3-2-1_51KVA_2019-01-31_final.stac-item
2019-01-31 11:32:43	ga_s2am_ard_3-2-1_51KVV_2019-01-31_final.stac-item
2019-01-31 11:32:55	ga_s2am_ard_3-2-1_51KWU_2019-01-31_final.stac-item
2019-02-02 12:13:36	ga_s2am_ard_3-2-1_50KKB_2019-02-02_final.stac-item
2019-02-02 12:13:51	ga_s2am_ard_3-2-1_49KHR_2019-02-02_final.stac-item
2019-02-02 12:13:55	ga_s2am_ard_3-2-1_49KGR_2019-02-02_final.stac-item
2019-02-02 12:14:04	ga_s2am_ard_3-2-1_50KKV_2019-02-02_final.stac-item
2019-02-02 12:14:06	ga_s2am_ard_3-2-1_49KHQ_2019-02-02_final.stac-item
2019-02-02 12:14:28	ga_s2am_ard_3-2-1_49JHN_2019-02-02_final.stac-item
2019-02-09 12:03:56	ga_s2am_ard_3-2-1_50KKA_2019-02-09_final.stac-item
2019-02-09 12:03:56	ga_s2am_ard_3-2-1_49KHR_2019-02-09_final.stac-item
2019-02-09 12:04:10	ga_s2am_ard_3-2-1_50KKV_2019-02-09_final.stac-item
2019-02-09 12:04:25	ga_s2am_ard_3-2-1_49KHP_2019-02-09_final.stac-item
2019-02-12 12:13:36	ga_s2am_ard_3-2-1_50KKB_2019-02-12_final.stac-item
2019-02-12 12:13:51	ga_s2am_ard_3-2-1_50KKA_2019-02-12_final.stac-item
2019-02-12 12:13:51	ga_s2am_ard_3-2-1_49KHR_2019-02-12_final.stac-item
2019-02-12 12:14:04	ga_s2am_ard_3-2-1_50KKV_2019-02-12_final.stac-item
2019-02-12 12:14:05	ga_s2am_ard_3-2-1_49KHQ_2019-02-12_final.stac-item
2019-02-12 12:14:18	ga_s2am_ard_3-2-1_49KHP_2019-02-12_final.stac-item
2019-02-19 12:03:40	ga_s2am_ard_3-2-1_50KKB_2019-02-19_final.stac-item
2019-02-19 12:04:10	ga_s2am_ard_3-2-1_49KHQ_2019-02-19_final.stac-item
2019-02-19 12:04:24	ga_s2am_ard_3-2-1_49KHP_2019-02-19_final.stac-item
2019-02-19 12:04:39	ga_s2am_ard_3-2-1_49JHN_2019-02-19_final.stac-item
2019-02-22 12:13:35	ga_s2am_ard_3-2-1_50KKB_2019-02-22_final.stac-item
2019-02-22 12:13:50	ga_s2am_ard_3-2-1_49KHR_2019-02-22_final.stac-item
2019-02-22 12:13:54	ga_s2am_ard_3-2-1_49KGR_2019-02-22_final.stac-item
2019-02-22 12:14:03	ga_s2am_ard_3-2-1_50KKV_2019-02-22_final.stac-item
2019-02-22 12:14:17	ga_s2am_ard_3-2-1_49KHP_2019-02-22_final.stac-item
2019-02-22 12:14:27	ga_s2am_ard_3-2-1_49JHN_2019-02-22_final.stac-item
2019-03-01 12:05:21	ga_s2am_ard_3-2-1_50JKQ_2019-03-01_final.stac-item
2019-03-02 11:36:00	ga_s2am_ard_3-2-1_50JQM_2019-03-02_final.stac-item
2019-03-02 11:36:33	ga_s2am_ard_3-2-1_50HPK_2019-03-02_final.stac-item
2019-03-04 12:15:05	ga_s2am_ard_3-2-1_49JGL_2019-03-04_final.stac-item
2019-03-05 11:46:50	ga_s2am_ard_3-2-1_50HMJ_2019-03-05_final.stac-item
2019-03-05 11:46:57	ga_s2am_ard_3-2-1_50HPH_2019-03-05_final.stac-item
2019-03-05 11:47:01	ga_s2am_ard_3-2-1_50HNH_2019-03-05_final.stac-item
2019-03-06 11:10:56	ga_s2am_ard_3-2-1_52LFL_2019-03-06_final.stac-item
2019-03-08 11:55:41	ga_s2am_ard_3-2-1_50JKP_2019-03-08_final.stac-item
2019-03-08 11:56:05	ga_s2am_ard_3-2-1_50JLM_2019-03-08_final.stac-item
2019-03-08 11:56:12	ga_s2am_ard_3-2-1_50JNL_2019-03-08_final.stac-item
2019-03-08 11:57:00	ga_s2am_ard_3-2-1_50HMH_2019-03-08_final.stac-item
2019-03-12 11:36:01	ga_s2am_ard_3-2-1_50JQM_2019-03-12_final.stac-item
2019-03-12 11:36:29	ga_s2am_ard_3-2-1_50HQK_2019-03-12_final.stac-item
2019-03-12 11:36:33	ga_s2am_ard_3-2-1_50HPK_2019-03-12_final.stac-item
2019-03-13 11:01:24	ga_s2am_ard_3-2-1_52LHJ_2019-03-13_final.stac-item
2019-03-15 11:45:57	ga_s2am_ard_3-2-1_50JQM_2019-03-15_final.stac-item
2019-03-15 11:46:09	ga_s2am_ard_3-2-1_50JMM_2019-03-15_final.stac-item
2019-03-15 11:46:30	ga_s2am_ard_3-2-1_50HPK_2019-03-15_final.stac-item
2019-03-15 11:46:50	ga_s2am_ard_3-2-1_50HQH_2019-03-15_final.stac-item
2019-03-15 11:46:59	ga_s2am_ard_3-2-1_50HPH_2019-03-15_final.stac-item
2019-03-16 11:10:58	ga_s2am_ard_3-2-1_52LFL_2019-03-16_final.stac-item
2019-03-21 12:03:57	ga_s2am_ard_3-2-1_50KKA_2019-03-21_final.stac-item
2019-03-25 11:46:07	ga_s2am_ard_3-2-1_50JMM_2019-03-25_final.stac-item
2019-03-25 11:46:07	ga_s2am_ard_3-2-1_50JQM_2019-03-25_final.stac-item
2019-03-25 11:46:18	ga_s2am_ard_3-2-1_50JPL_2019-03-25_final.stac-item
2019-03-25 11:46:21	ga_s2am_ard_3-2-1_50JNL_2019-03-25_final.stac-item
2019-03-25 11:46:51	ga_s2am_ard_3-2-1_50HNJ_2019-03-25_final.stac-item
2019-03-26 11:16:43	ga_s2am_ard_3-2-1_51HWD_2019-03-26_final.stac-item
2019-03-28 11:56:22	ga_s2am_ard_3-2-1_50JML_2019-03-28_final.stac-item
2019-03-31 12:05:44	ga_s2am_ard_3-2-1_49JGJ_2019-03-31_final.stac-item
2019-04-07 11:55:05	ga_s2am_ard_3-2-1_50JMR_2019-04-07_final.stac-item
2019-04-07 11:55:06	ga_s2am_ard_3-2-1_50JLS_2019-04-07_final.stac-item
2019-04-10 12:05:39	ga_s2am_ard_3-2-1_50JLP_2019-04-10_final.stac-item
2019-04-20 12:04:57	ga_s2am_ard_3-2-1_50JLS_2019-04-20_final.stac-item
2019-04-21 11:34:40	ga_s2am_ard_3-2-1_50JRT_2019-04-21_final.stac-item
2019-04-24 11:44:54	ga_s2am_ard_3-2-1_51JUL_2019-04-24_final.stac-item
2019-04-27 11:54:51	ga_s2am_ard_3-2-1_50JPS_2019-04-27_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

All years