Search ga_ls8c_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:

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):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

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:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

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 Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

83 results

Time (local)	Label
2021-10-16 11:06:22	ga_ls8c_ard_3-2-0_108070_2021-10-16_final
2021-10-16 11:06:46	ga_ls8c_ard_3-2-0_108071_2021-10-16_final
2021-10-16 11:07:10	ga_ls8c_ard_3-2-0_108072_2021-10-16_final
2021-10-16 11:08:22	ga_ls8c_ard_3-2-0_108075_2021-10-16_final
2021-10-16 11:09:10	ga_ls8c_ard_3-2-0_108077_2021-10-16_final
2021-10-16 11:09:34	ga_ls8c_ard_3-2-0_108078_2021-10-16_final
2021-10-16 11:09:58	ga_ls8c_ard_3-2-0_108079_2021-10-16_final
2021-10-16 11:10:22	ga_ls8c_ard_3-2-0_108080_2021-10-16_final
2021-10-16 11:10:46	ga_ls8c_ard_3-2-0_108081_2021-10-16_final
2021-10-16 11:11:10	ga_ls8c_ard_3-2-0_108082_2021-10-16_final
2021-10-16 11:12:21	ga_ls8c_ard_3-2-0_108085_2021-10-16_final
2021-10-17 10:09:33	ga_ls8c_ard_3-2-0_099067_2021-10-17_final
2021-10-17 10:09:57	ga_ls8c_ard_3-2-0_099068_2021-10-17_final
2021-10-17 10:10:21	ga_ls8c_ard_3-2-0_099069_2021-10-17_final
2021-10-17 10:10:45	ga_ls8c_ard_3-2-0_099070_2021-10-17_final
2021-10-17 10:11:09	ga_ls8c_ard_3-2-0_099071_2021-10-17_final
2021-10-17 10:11:33	ga_ls8c_ard_3-2-0_099072_2021-10-17_final
2021-10-17 10:11:57	ga_ls8c_ard_3-2-0_099073_2021-10-17_final
2021-10-17 10:12:21	ga_ls8c_ard_3-2-0_099074_2021-10-17_final
2021-10-17 10:13:09	ga_ls8c_ard_3-2-0_099076_2021-10-17_final
2021-10-17 10:13:33	ga_ls8c_ard_3-2-0_099077_2021-10-17_final
2021-10-17 10:14:21	ga_ls8c_ard_3-2-0_099079_2021-10-17_final
2021-10-17 10:15:08	ga_ls8c_ard_3-2-0_099081_2021-10-17_final
2021-10-17 10:15:56	ga_ls8c_ard_3-2-0_099083_2021-10-17_final
2021-10-17 10:16:44	ga_ls8c_ard_3-2-0_099085_2021-10-17_final
2021-10-17 11:51:38	ga_ls8c_ard_3-2-0_115075_2021-10-17_final
2021-10-17 11:52:26	ga_ls8c_ard_3-2-0_115077_2021-10-17_final
2021-10-17 11:53:14	ga_ls8c_ard_3-2-0_115079_2021-10-17_final
2021-10-18 09:19:55	ga_ls8c_ard_3-2-0_090082_2021-10-17_final
2021-10-18 09:20:19	ga_ls8c_ard_3-2-0_090083_2021-10-17_final
2021-10-18 09:20:43	ga_ls8c_ard_3-2-0_090084_2021-10-17_final
2021-10-18 09:21:07	ga_ls8c_ard_3-2-0_090085_2021-10-17_final
2021-10-18 09:21:31	ga_ls8c_ard_3-2-0_090086_2021-10-17_final
2021-10-18 10:54:01	ga_ls8c_ard_3-2-0_106070_2021-10-18_final
2021-10-18 10:54:25	ga_ls8c_ard_3-2-0_106071_2021-10-18_final
2021-10-18 10:54:49	ga_ls8c_ard_3-2-0_106072_2021-10-18_final
2021-10-18 10:56:25	ga_ls8c_ard_3-2-0_106076_2021-10-18_final
2021-10-18 10:56:48	ga_ls8c_ard_3-2-0_106077_2021-10-18_final
2021-10-18 10:57:36	ga_ls8c_ard_3-2-0_106079_2021-10-18_final
2021-10-18 10:58:00	ga_ls8c_ard_3-2-0_106080_2021-10-18_final
2021-10-18 10:58:24	ga_ls8c_ard_3-2-0_106081_2021-10-18_final
2021-10-18 10:58:48	ga_ls8c_ard_3-2-0_106082_2021-10-18_final
2021-10-18 10:59:36	ga_ls8c_ard_3-2-0_106084_2021-10-18_final
2021-10-19 09:57:12	ga_ls8c_ard_3-2-0_097067_2021-10-19_final
2021-10-19 09:57:36	ga_ls8c_ard_3-2-0_097068_2021-10-19_final
2021-10-19 09:58:00	ga_ls8c_ard_3-2-0_097069_2021-10-19_final
2021-10-19 09:58:24	ga_ls8c_ard_3-2-0_097070_2021-10-19_final
2021-10-19 09:58:48	ga_ls8c_ard_3-2-0_097071_2021-10-19_final
2021-10-19 09:59:12	ga_ls8c_ard_3-2-0_097072_2021-10-19_final
2021-10-19 09:59:36	ga_ls8c_ard_3-2-0_097073_2021-10-19_final
2021-10-19 09:59:59	ga_ls8c_ard_3-2-0_097074_2021-10-19_final
2021-10-19 10:00:23	ga_ls8c_ard_3-2-0_097075_2021-10-19_final
2021-10-19 10:00:47	ga_ls8c_ard_3-2-0_097076_2021-10-19_final
2021-10-19 10:01:11	ga_ls8c_ard_3-2-0_097077_2021-10-19_final
2021-10-19 10:01:35	ga_ls8c_ard_3-2-0_097078_2021-10-19_final
2021-10-19 10:01:59	ga_ls8c_ard_3-2-0_097079_2021-10-19_final
2021-10-19 10:02:23	ga_ls8c_ard_3-2-0_097080_2021-10-19_final
2021-10-19 10:02:47	ga_ls8c_ard_3-2-0_097081_2021-10-19_final
2021-10-19 10:03:11	ga_ls8c_ard_3-2-0_097082_2021-10-19_final
2021-10-19 10:03:35	ga_ls8c_ard_3-2-0_097083_2021-10-19_final
2021-10-19 10:03:59	ga_ls8c_ard_3-2-0_097084_2021-10-19_final
2021-10-19 10:04:23	ga_ls8c_ard_3-2-0_097085_2021-10-19_final
2021-10-19 10:04:47	ga_ls8c_ard_3-2-0_097086_2021-10-19_final
2021-10-19 11:36:05	ga_ls8c_ard_3-2-0_113067_2021-10-19_final
2021-10-19 11:38:05	ga_ls8c_ard_3-2-0_113072_2021-10-19_final
2021-10-19 11:38:29	ga_ls8c_ard_3-2-0_113073_2021-10-19_final
2021-10-19 11:38:53	ga_ls8c_ard_3-2-0_113074_2021-10-19_final
2021-10-19 11:39:16	ga_ls8c_ard_3-2-0_113075_2021-10-19_final
2021-10-19 11:39:40	ga_ls8c_ard_3-2-0_113076_2021-10-19_final
2021-10-19 11:40:04	ga_ls8c_ard_3-2-0_113077_2021-10-19_final
2021-10-19 11:40:28	ga_ls8c_ard_3-2-0_113078_2021-10-19_final
2021-10-19 11:40:52	ga_ls8c_ard_3-2-0_113079_2021-10-19_final
2021-10-19 11:41:16	ga_ls8c_ard_3-2-0_113080_2021-10-19_final
2021-10-19 11:41:40	ga_ls8c_ard_3-2-0_113081_2021-10-19_final
2021-10-19 11:42:04	ga_ls8c_ard_3-2-0_113082_2021-10-19_final
2021-10-19 11:42:28	ga_ls8c_ard_3-2-0_113083_2021-10-19_final
2021-10-19 11:42:52	ga_ls8c_ard_3-2-0_113084_2021-10-19_final
2021-10-20 09:06:22	ga_ls8c_ard_3-2-0_088079_2021-10-19_final
2021-10-20 09:06:46	ga_ls8c_ard_3-2-0_088080_2021-10-19_final
2021-10-20 09:07:10	ga_ls8c_ard_3-2-0_088081_2021-10-19_final
2021-10-20 09:07:34	ga_ls8c_ard_3-2-0_088082_2021-10-19_final
2021-10-20 09:07:58	ga_ls8c_ard_3-2-0_088083_2021-10-19_final
2021-10-20 09:08:22	ga_ls8c_ard_3-2-0_088084_2021-10-19_final

Return to ga_ls8c_ard_3 whole collection overview

ga_ls8c_ard_3: Geoscience Australia Landsat 8 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years