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
2023-04-21 11:01:59	ga_s2am_ard_3-2-1_52KGG_2023-04-21_final
2023-04-21 11:03:47	ga_s2am_ard_3-2-1_52KEV_2023-04-21_final
2023-04-21 11:04:49	ga_s2am_ard_3-2-1_52JDR_2023-04-21_final
2023-04-21 11:06:02	ga_s2am_ard_3-2-1_52JDL_2023-04-21_final
2023-04-22 10:30:11	ga_s2am_ard_3-2-1_54LWN_2023-04-22_final
2023-04-22 10:31:12	ga_s2am_ard_3-2-1_54LVJ_2023-04-22_final
2023-04-22 10:31:48	ga_s2am_ard_3-2-1_54KTG_2023-04-22_final
2023-04-22 10:31:55	ga_s2am_ard_3-2-1_53KRB_2023-04-22_final
2023-04-22 10:33:33	ga_s2am_ard_3-2-1_53KQQ_2023-04-22_final
2023-04-22 10:36:09	ga_s2am_ard_3-2-1_53HME_2023-04-22_final
2023-04-22 10:36:27	ga_s2am_ard_3-2-1_53HLD_2023-04-22_final
2023-04-22 12:13:53	ga_s2am_ard_3-2-1_49KHR_2023-04-22_final
2023-04-22 12:14:44	ga_s2am_ard_3-2-1_49JFN_2023-04-22_final
2023-04-23 10:01:31	ga_s2am_ard_3-2-1_55KEB_2023-04-23_final
2023-04-23 10:01:37	ga_s2am_ard_3-2-1_55KCB_2023-04-23_final
2023-04-23 10:01:49	ga_s2am_ard_3-2-1_55KDA_2023-04-23_final
2023-04-23 10:02:07	ga_s2am_ard_3-2-1_55KCV_2023-04-23_final
2023-04-23 10:02:53	ga_s2am_ard_3-2-1_55KBS_2023-04-23_final
2023-04-23 10:03:02	ga_s2am_ard_3-2-1_55KDR_2023-04-23_final
2023-04-23 10:03:08	ga_s2am_ard_3-2-1_55KEQ_2023-04-23_final
2023-04-23 10:03:08	ga_s2am_ard_3-2-1_55KBR_2023-04-23_final
2023-04-23 10:03:26	ga_s2am_ard_3-2-1_55KCP_2023-04-23_final
2023-04-23 10:03:31	ga_s2am_ard_3-2-1_54KYV_2023-04-23_final
2023-04-23 10:03:34	ga_s2am_ard_3-2-1_55KCP_2023-04-23_final
2023-04-23 10:03:37	ga_s2am_ard_3-2-1_55KBP_2023-04-23_final
2023-04-23 10:03:37	ga_s2am_ard_3-2-1_54KZU_2023-04-23_final
2023-04-23 10:03:42	ga_s2am_ard_3-2-1_54KYU_2023-04-23_final
2023-04-23 10:03:45	ga_s2am_ard_3-2-1_55JDN_2023-04-23_final
2023-04-23 10:03:52	ga_s2am_ard_3-2-1_54JZT_2023-04-23_final
2023-04-23 10:04:12	ga_s2am_ard_3-2-1_55JDL_2023-04-23_final
2023-04-23 10:04:24	ga_s2am_ard_3-2-1_54JYR_2023-04-23_final
2023-04-23 10:04:32	ga_s2am_ard_3-2-1_55JCK_2023-04-23_final
2023-04-23 10:04:57	ga_s2am_ard_3-2-1_54JXP_2023-04-23_final
2023-04-23 10:05:02	ga_s2am_ard_3-2-1_55JCH_2023-04-23_final
2023-04-23 10:05:15	ga_s2am_ard_3-2-1_55JCG_2023-04-23_final
2023-04-23 10:05:19	ga_s2am_ard_3-2-1_55JBG_2023-04-23_final
2023-04-23 10:05:22	ga_s2am_ard_3-2-1_54JYM_2023-04-23_final
2023-04-23 10:05:34	ga_s2am_ard_3-2-1_55JBF_2023-04-23_final
2023-04-23 10:05:36	ga_s2am_ard_3-2-1_54JYL_2023-04-23_final
2023-04-23 10:05:40	ga_s2am_ard_3-2-1_54JWL_2023-04-23_final
2023-04-23 10:05:43	ga_s2am_ard_3-2-1_54HYK_2023-04-23_final
2023-04-23 10:05:43	ga_s2am_ard_3-2-1_54JYL_2023-04-23_final
2023-04-23 10:05:46	ga_s2am_ard_3-2-1_54JWL_2023-04-23_final
2023-04-23 10:05:51	ga_s2am_ard_3-2-1_54HYK_2023-04-23_final
2023-04-23 10:06:13	ga_s2am_ard_3-2-1_54HWJ_2023-04-23_final
2023-04-23 10:06:18	ga_s2am_ard_3-2-1_55HBC_2023-04-23_final
2023-04-23 10:06:24	ga_s2am_ard_3-2-1_54HXH_2023-04-23_final
2023-04-23 10:06:32	ga_s2am_ard_3-2-1_55HBB_2023-04-23_final
2023-04-23 10:06:34	ga_s2am_ard_3-2-1_54HYG_2023-04-23_final
2023-04-23 10:06:38	ga_s2am_ard_3-2-1_54HXG_2023-04-23_final
2023-04-23 10:06:45	ga_s2am_ard_3-2-1_54HVG_2023-04-23_final
2023-04-23 10:06:56	ga_s2am_ard_3-2-1_54HWF_2023-04-23_final
2023-04-23 10:07:13	ga_s2am_ard_3-2-1_54HYD_2023-04-23_final
2023-04-23 10:07:21	ga_s2am_ard_3-2-1_54HXD_2023-04-23_final
2023-04-23 10:07:34	ga_s2am_ard_3-2-1_54HUD_2023-04-23_final
2023-04-23 11:40:56	ga_s2am_ard_3-2-1_51LWG_2023-04-23_final
2023-04-23 11:41:00	ga_s2am_ard_3-2-1_51LVG_2023-04-23_final
2023-04-23 11:41:14	ga_s2am_ard_3-2-1_51LVF_2023-04-23_final
2023-04-23 11:41:25	ga_s2am_ard_3-2-1_51LWE_2023-04-23_final
2023-04-23 11:41:29	ga_s2am_ard_3-2-1_51LVE_2023-04-23_final
2023-04-23 11:42:12	ga_s2am_ard_3-2-1_51KVB_2023-04-23_final
2023-04-23 11:42:16	ga_s2am_ard_3-2-1_51KUB_2023-04-23_final
2023-04-23 11:42:20	ga_s2am_ard_3-2-1_51KWA_2023-04-23_final
2023-04-23 11:42:30	ga_s2am_ard_3-2-1_51KUA_2023-04-23_final
2023-04-23 11:43:03	ga_s2am_ard_3-2-1_50KRD_2023-04-23_final
2023-04-23 11:43:10	ga_s2am_ard_3-2-1_51KVT_2023-04-23_final
2023-04-23 11:43:28	ga_s2am_ard_3-2-1_51KUS_2023-04-23_final
2023-04-23 11:43:31	ga_s2am_ard_3-2-1_51KTS_2023-04-23_final
2023-04-23 11:43:35	ga_s2am_ard_3-2-1_50KQB_2023-04-23_final
2023-04-23 11:43:46	ga_s2am_ard_3-2-1_51KTR_2023-04-23_final
2023-04-23 11:43:50	ga_s2am_ard_3-2-1_50KQA_2023-04-23_final
2023-04-23 11:44:01	ga_s2am_ard_3-2-1_51KTQ_2023-04-23_final
2023-04-23 11:44:15	ga_s2am_ard_3-2-1_50KRU_2023-04-23_final
2023-04-23 11:44:19	ga_s2am_ard_3-2-1_50KQU_2023-04-23_final
2023-04-23 11:44:26	ga_s2am_ard_3-2-1_51JUN_2023-04-23_final
2023-04-23 11:44:44	ga_s2am_ard_3-2-1_51JTM_2023-04-23_final
2023-04-23 11:44:52	ga_s2am_ard_3-2-1_50JPS_2023-04-23_final
2023-04-23 11:45:10	ga_s2am_ard_3-2-1_50JNR_2023-04-23_final
2023-04-23 11:45:28	ga_s2am_ard_3-2-1_51JTJ_2023-04-23_final
2023-04-23 11:45:31	ga_s2am_ard_3-2-1_50JQP_2023-04-23_final
2023-04-23 11:45:35	ga_s2am_ard_3-2-1_50JPP_2023-04-23_final
2023-04-23 11:45:45	ga_s2am_ard_3-2-1_50JQN_2023-04-23_final
2023-04-23 11:45:53	ga_s2am_ard_3-2-1_50JNN_2023-04-23_final
2023-04-23 11:46:12	ga_s2am_ard_3-2-1_50JMM_2023-04-23_final
2023-04-23 11:46:40	ga_s2am_ard_3-2-1_50HMK_2023-04-23_final
2023-04-23 11:46:42	ga_s2am_ard_3-2-1_50HQJ_2023-04-23_final
2023-04-23 11:46:55	ga_s2am_ard_3-2-1_50HMJ_2023-04-23_final
2023-04-23 11:47:01	ga_s2am_ard_3-2-1_50HPH_2023-04-23_final
2023-04-23 11:47:09	ga_s2am_ard_3-2-1_50HMH_2023-04-23_final
2023-04-23 11:47:13	ga_s2am_ard_3-2-1_50HLH_2023-04-23_final
2023-04-23 11:47:16	ga_s2am_ard_3-2-1_50HPG_2023-04-23_final
2023-04-23 11:47:20	ga_s2am_ard_3-2-1_50HNG_2023-04-23_final
2023-04-23 11:47:26	ga_s2am_ard_3-2-1_50HLG_2023-04-23_final
2023-05-03 11:41:12	ga_s2am_ard_3-2-1_51LWF_2023-05-03_nrt
2023-05-03 11:42:05	ga_s2am_ard_3-2-1_51LTC_2023-05-03_nrt
2023-05-03 11:42:49	ga_s2am_ard_3-2-1_51KTV_2023-05-03_nrt
2023-05-03 11:42:50	ga_s2am_ard_3-2-1_50KRE_2023-05-03_nrt
2023-05-03 11:47:29	ga_s2am_ard_3-2-1_50HPF_2023-05-03_nrt
2023-05-03 11:47:33	ga_s2am_ard_3-2-1_50HLF_2023-05-03_nrt
2023-05-04 11:11:09	ga_s2am_ard_3-2-1_52LDL_2023-05-04_nrt

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