Search ga_s2am_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. 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 (e.g. ‘epsg:32654’) :

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm 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 from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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) 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. For Sentinel it is MGRS code. :

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to s3cloudless to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud land pixels according to s3cloudless to (exclusive):

Unique identifier for a datastrip relative to a given Datatake. (e.g. ‘S2A_OPER_MSI_L1C_DS_SGS__20161214T040601_S20161214T005840_N02.04’) :

ESA product URI, with the '.SAFE' ending removed. (e.g. 'S2A_MSIL1C_20220303T000731_N0400_R073_T56LNM_20220303T012845') :

Granule ID according to the ESA naming convention (e.g. ‘S2A_OPER_MSI_L1C_TL_SGS__20161214T040601_A007721_T53KRB_N02.04’) :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2022-03-28 12:15:13	ga_s2am_ard_3-2-1_49JGL_2022-03-28_final
2022-03-29 10:01:35	ga_s2am_ard_3-2-1_55KEB_2022-03-29_final
2022-03-29 10:01:38	ga_s2am_ard_3-2-1_55KDB_2022-03-29_final
2022-03-29 10:02:07	ga_s2am_ard_3-2-1_55KFU_2022-03-29_final
2022-03-29 10:02:10	ga_s2am_ard_3-2-1_55KCV_2022-03-29_final
2022-03-29 10:02:17	ga_s2am_ard_3-2-1_55KBV_2022-03-29_final
2022-03-29 10:02:18	ga_s2am_ard_3-2-1_55KEU_2022-03-29_final
2022-03-29 10:02:22	ga_s2am_ard_3-2-1_55KDU_2022-03-29_final
2022-03-29 10:02:25	ga_s2am_ard_3-2-1_55KCU_2022-03-29_final
2022-03-29 10:02:28	ga_s2am_ard_3-2-1_55KBU_2022-03-29_final
2022-03-29 10:02:42	ga_s2am_ard_3-2-1_55KBT_2022-03-29_final
2022-03-29 10:02:47	ga_s2am_ard_3-2-1_55KES_2022-03-29_final
2022-03-29 10:02:51	ga_s2am_ard_3-2-1_55KDS_2022-03-29_final
2022-03-29 10:02:54	ga_s2am_ard_3-2-1_55KCS_2022-03-29_final
2022-03-29 10:03:05	ga_s2am_ard_3-2-1_55KDR_2022-03-29_final
2022-03-29 10:03:08	ga_s2am_ard_3-2-1_55KCR_2022-03-29_final
2022-03-29 10:03:12	ga_s2am_ard_3-2-1_55KBR_2022-03-29_final
2022-03-29 10:03:12	ga_s2am_ard_3-2-1_54KZA_2022-03-29_final
2022-03-29 10:03:19	ga_s2am_ard_3-2-1_55KDQ_2022-03-29_final
2022-03-29 10:03:26	ga_s2am_ard_3-2-1_54KZV_2022-03-29_final
2022-03-29 10:03:41	ga_s2am_ard_3-2-1_55KBP_2022-03-29_final
2022-03-29 10:03:45	ga_s2am_ard_3-2-1_54KYU_2022-03-29_final
2022-03-29 10:03:52	ga_s2am_ard_3-2-1_55JCN_2022-03-29_final
2022-03-29 10:03:55	ga_s2am_ard_3-2-1_54JZT_2022-03-29_final
2022-03-29 10:04:03	ga_s2am_ard_3-2-1_55JDM_2022-03-29_final
2022-03-29 10:04:16	ga_s2am_ard_3-2-1_55JDL_2022-03-29_final
2022-03-29 10:04:21	ga_s2am_ard_3-2-1_55JCL_2022-03-29_final
2022-03-29 10:04:24	ga_s2am_ard_3-2-1_55JBL_2022-03-29_final
2022-03-29 10:04:26	ga_s2am_ard_3-2-1_55JDK_2022-03-29_final
2022-03-29 10:04:28	ga_s2am_ard_3-2-1_54JYR_2022-03-29_final
2022-03-29 10:04:35	ga_s2am_ard_3-2-1_54JXR_2022-03-29_final
2022-03-29 10:04:54	ga_s2am_ard_3-2-1_55JBJ_2022-03-29_final
2022-03-29 10:05:08	ga_s2am_ard_3-2-1_55JBH_2022-03-29_final
2022-03-29 10:05:11	ga_s2am_ard_3-2-1_54JYN_2022-03-29_final
2022-03-29 10:05:23	ga_s2am_ard_3-2-1_55JBG_2022-03-29_final
2022-03-29 10:05:25	ga_s2am_ard_3-2-1_54JYM_2022-03-29_final
2022-03-29 10:06:06	ga_s2am_ard_3-2-1_55HBD_2022-03-29_final
2022-03-29 10:06:09	ga_s2am_ard_3-2-1_54HYJ_2022-03-29_final
2022-03-29 10:06:12	ga_s2am_ard_3-2-1_54HXJ_2022-03-29_final
2022-03-29 10:06:16	ga_s2am_ard_3-2-1_54HWJ_2022-03-29_final
2022-03-29 10:06:21	ga_s2am_ard_3-2-1_55HBC_2022-03-29_final
2022-03-29 10:06:23	ga_s2am_ard_3-2-1_54HYH_2022-03-29_final
2022-03-29 10:06:45	ga_s2am_ard_3-2-1_54HWG_2022-03-29_final
2022-03-29 10:06:49	ga_s2am_ard_3-2-1_54HVG_2022-03-29_final
2022-03-29 10:07:00	ga_s2am_ard_3-2-1_54HWF_2022-03-29_final
2022-03-29 10:07:03	ga_s2am_ard_3-2-1_54HVF_2022-03-29_final
2022-03-29 10:07:10	ga_s2am_ard_3-2-1_54HXE_2022-03-29_final
2022-03-29 10:07:14	ga_s2am_ard_3-2-1_54HWE_2022-03-29_final
2022-03-29 10:07:18	ga_s2am_ard_3-2-1_54HVE_2022-03-29_final
2022-03-29 11:41:17	ga_s2am_ard_3-2-1_51LVF_2022-03-29_final
2022-03-29 11:41:21	ga_s2am_ard_3-2-1_51LUF_2022-03-29_final
2022-03-29 11:41:28	ga_s2am_ard_3-2-1_51LWE_2022-03-29_final
2022-03-29 11:41:32	ga_s2am_ard_3-2-1_51LVE_2022-03-29_final
2022-03-29 11:41:35	ga_s2am_ard_3-2-1_51LUE_2022-03-29_final
2022-03-29 11:41:58	ga_s2am_ard_3-2-1_51LWC_2022-03-29_final
2022-03-29 11:42:01	ga_s2am_ard_3-2-1_51LVC_2022-03-29_final
2022-03-29 11:42:12	ga_s2am_ard_3-2-1_51KWB_2022-03-29_final
2022-03-29 11:42:16	ga_s2am_ard_3-2-1_51KVB_2022-03-29_final
2022-03-29 11:42:23	ga_s2am_ard_3-2-1_51KVB_2022-03-29_final
2022-03-29 11:42:48	ga_s2am_ard_3-2-1_51KUV_2022-03-29_final
2022-03-29 11:42:59	ga_s2am_ard_3-2-1_51KVU_2022-03-29_final
2022-03-29 11:43:03	ga_s2am_ard_3-2-1_51KUU_2022-03-29_final
2022-03-29 11:43:06	ga_s2am_ard_3-2-1_51KTU_2022-03-29_final
2022-03-29 11:43:06	ga_s2am_ard_3-2-1_50KRD_2022-03-29_final
2022-03-29 11:43:11	ga_s2am_ard_3-2-1_50KQD_2022-03-29_final.stac-item
2022-03-29 11:43:20	ga_s2am_ard_3-2-1_51KTT_2022-03-29_final
2022-03-29 11:43:24	ga_s2am_ard_3-2-1_50KQC_2022-03-29_final
2022-03-29 11:43:32	ga_s2am_ard_3-2-1_51KUS_2022-03-29_final
2022-03-29 11:43:35	ga_s2am_ard_3-2-1_50KRB_2022-03-29_final
2022-03-29 11:43:38	ga_s2am_ard_3-2-1_51KVR_2022-03-29_final
2022-03-29 11:43:46	ga_s2am_ard_3-2-1_51KUR_2022-03-29_final
2022-03-29 11:43:50	ga_s2am_ard_3-2-1_51KTR_2022-03-29_final
2022-03-29 11:43:50	ga_s2am_ard_3-2-1_50KRA_2022-03-29_final
2022-03-29 11:43:53	ga_s2am_ard_3-2-1_50KQA_2022-03-29_final
2022-03-29 11:44:04	ga_s2am_ard_3-2-1_50KRV_2022-03-29_final
2022-03-29 11:44:08	ga_s2am_ard_3-2-1_50KQV_2022-03-29_final
2022-03-29 11:44:15	ga_s2am_ard_3-2-1_51KUP_2022-03-29_final
2022-03-29 11:44:19	ga_s2am_ard_3-2-1_50KRU_2022-03-29_final
2022-03-29 11:44:22	ga_s2am_ard_3-2-1_50KQU_2022-03-29_final
2022-03-29 11:44:26	ga_s2am_ard_3-2-1_50KPU_2022-03-29_final
2022-03-29 11:44:33	ga_s2am_ard_3-2-1_50JRT_2022-03-29_final
2022-03-29 11:44:51	ga_s2am_ard_3-2-1_50JQS_2022-03-29_final
2022-03-29 11:44:54	ga_s2am_ard_3-2-1_51JUL_2022-03-29_final
2022-03-29 11:45:02	ga_s2am_ard_3-2-1_51JTL_2022-03-29_final
2022-03-29 11:45:06	ga_s2am_ard_3-2-1_50JQR_2022-03-29_final
2022-03-29 11:45:09	ga_s2am_ard_3-2-1_50JPR_2022-03-29_final
2022-03-29 11:45:14	ga_s2am_ard_3-2-1_50JNR_2022-03-29_final
2022-03-29 11:45:27	ga_s2am_ard_3-2-1_50JNQ_2022-03-29_final
2022-03-29 11:45:42	ga_s2am_ard_3-2-1_50JNP_2022-03-29_final
2022-03-29 11:45:46	ga_s2am_ard_3-2-1_51JTH_2022-03-29_final
2022-03-29 11:45:49	ga_s2am_ard_3-2-1_50JQN_2022-03-29_final
2022-03-29 11:45:56	ga_s2am_ard_3-2-1_50JNN_2022-03-29_final
2022-03-29 11:45:59	ga_s2am_ard_3-2-1_51JTG_2022-03-29_final
2022-03-29 11:46:03	ga_s2am_ard_3-2-1_50JQM_2022-03-29_final
2022-03-29 11:46:45	ga_s2am_ard_3-2-1_50HQJ_2022-03-29_final
2022-03-29 11:46:50	ga_s2am_ard_3-2-1_50HPJ_2022-03-29_final
2022-03-29 11:46:54	ga_s2am_ard_3-2-1_50HNJ_2022-03-29_final
2022-03-29 11:46:56	ga_s2am_ard_3-2-1_50HQH_2022-03-29_final
2022-03-29 11:46:58	ga_s2am_ard_3-2-1_50HMJ_2022-03-29_final
2022-03-29 11:47:23	ga_s2am_ard_3-2-1_50HNG_2022-03-29_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

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years