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

99 results

Time (local)	Label
2023-05-10 10:45:33	ga_ls8c_ard_3-2-1_105067_2023-05-10_final
2023-05-10 10:45:57	ga_ls8c_ard_3-2-1_105068_2023-05-10_final
2023-05-10 10:46:21	ga_ls8c_ard_3-2-1_105069_2023-05-10_final
2023-05-10 10:46:45	ga_ls8c_ard_3-2-1_105070_2023-05-10_final
2023-05-10 10:47:33	ga_ls8c_ard_3-2-1_105072_2023-05-10_final
2023-05-10 10:47:56	ga_ls8c_ard_3-2-1_105073_2023-05-10_final
2023-05-10 10:49:08	ga_ls8c_ard_3-2-1_105076_2023-05-10_final
2023-05-10 10:49:32	ga_ls8c_ard_3-2-1_105077_2023-05-10_final
2023-05-10 10:49:56	ga_ls8c_ard_3-2-1_105078_2023-05-10_final
2023-05-10 10:50:44	ga_ls8c_ard_3-2-1_105080_2023-05-10_final
2023-05-10 10:51:08	ga_ls8c_ard_3-2-1_105081_2023-05-10_final
2023-05-11 09:51:54	ga_ls8c_ard_3-2-1_096072_2023-05-11_final
2023-05-11 09:52:42	ga_ls8c_ard_3-2-1_096074_2023-05-11_final
2023-05-11 09:53:06	ga_ls8c_ard_3-2-1_096075_2023-05-11_final
2023-05-11 09:53:30	ga_ls8c_ard_3-2-1_096076_2023-05-11_final
2023-05-11 09:53:54	ga_ls8c_ard_3-2-1_096077_2023-05-11_final
2023-05-11 09:54:18	ga_ls8c_ard_3-2-1_096078_2023-05-11_final
2023-05-11 09:55:29	ga_ls8c_ard_3-2-1_096081_2023-05-11_final
2023-05-11 09:55:53	ga_ls8c_ard_3-2-1_096082_2023-05-11_final
2023-05-11 09:56:17	ga_ls8c_ard_3-2-1_096083_2023-05-11_final
2023-05-11 09:56:41	ga_ls8c_ard_3-2-1_096084_2023-05-11_final
2023-05-11 09:57:05	ga_ls8c_ard_3-2-1_096085_2023-05-11_final
2023-05-11 09:57:29	ga_ls8c_ard_3-2-1_096086_2023-05-11_final
2023-05-11 11:30:47	ga_ls8c_ard_3-2-1_112072_2023-05-11_final
2023-05-11 11:31:59	ga_ls8c_ard_3-2-1_112075_2023-05-11_final
2023-05-11 11:32:47	ga_ls8c_ard_3-2-1_112077_2023-05-11_final
2023-05-11 11:33:11	ga_ls8c_ard_3-2-1_112078_2023-05-11_final
2023-05-11 11:33:34	ga_ls8c_ard_3-2-1_112079_2023-05-11_final
2023-05-11 11:34:46	ga_ls8c_ard_3-2-1_112082_2023-05-11_final
2023-05-11 11:35:10	ga_ls8c_ard_3-2-1_112083_2023-05-11_final
2023-05-11 11:35:34	ga_ls8c_ard_3-2-1_112084_2023-05-11_final
2023-05-12 10:33:57	ga_ls8c_ard_3-2-1_103069_2023-05-12_final
2023-05-12 10:34:21	ga_ls8c_ard_3-2-1_103070_2023-05-12_final
2023-05-12 10:35:09	ga_ls8c_ard_3-2-1_103072_2023-05-12_final
2023-05-12 10:35:32	ga_ls8c_ard_3-2-1_103073_2023-05-12_final
2023-05-12 10:35:56	ga_ls8c_ard_3-2-1_103074_2023-05-12_final
2023-05-12 10:36:44	ga_ls8c_ard_3-2-1_103076_2023-05-12_final
2023-05-12 10:37:32	ga_ls8c_ard_3-2-1_103078_2023-05-12_final
2023-05-12 10:38:20	ga_ls8c_ard_3-2-1_103080_2023-05-12_final
2023-05-12 10:38:44	ga_ls8c_ard_3-2-1_103081_2023-05-12_final
2023-05-12 10:39:08	ga_ls8c_ard_3-2-1_103082_2023-05-12_final
2023-05-13 09:39:07	ga_ls8c_ard_3-2-1_094071_2023-05-13_final
2023-05-13 09:39:55	ga_ls8c_ard_3-2-1_094073_2023-05-13_final
2023-05-13 09:40:19	ga_ls8c_ard_3-2-1_094074_2023-05-13_final
2023-05-13 09:41:07	ga_ls8c_ard_3-2-1_094076_2023-05-13_final
2023-05-13 09:41:31	ga_ls8c_ard_3-2-1_094077_2023-05-13_final
2023-05-13 09:42:18	ga_ls8c_ard_3-2-1_094079_2023-05-13_final
2023-05-13 09:43:30	ga_ls8c_ard_3-2-1_094082_2023-05-13_final
2023-05-13 09:43:54	ga_ls8c_ard_3-2-1_094083_2023-05-13_final
2023-05-13 09:44:18	ga_ls8c_ard_3-2-1_094084_2023-05-13_final
2023-05-13 09:44:42	ga_ls8c_ard_3-2-1_094085_2023-05-13_final
2023-05-13 09:45:06	ga_ls8c_ard_3-2-1_094086_2023-05-13_final
2023-05-13 11:18:48	ga_ls8c_ard_3-2-1_110073_2023-05-13_final
2023-05-13 11:19:36	ga_ls8c_ard_3-2-1_110075_2023-05-13_final
2023-05-13 11:20:00	ga_ls8c_ard_3-2-1_110076_2023-05-13_final
2023-05-13 11:20:24	ga_ls8c_ard_3-2-1_110077_2023-05-13_final
2023-05-13 11:21:59	ga_ls8c_ard_3-2-1_110081_2023-05-13_final
2023-05-13 11:23:35	ga_ls8c_ard_3-2-1_110085_2023-05-13_final
2023-05-14 10:22:46	ga_ls8c_ard_3-2-1_101072_2023-05-14_final
2023-05-14 10:23:10	ga_ls8c_ard_3-2-1_101073_2023-05-14_final
2023-05-14 10:24:46	ga_ls8c_ard_3-2-1_101077_2023-05-14_final
2023-05-14 10:25:58	ga_ls8c_ard_3-2-1_101080_2023-05-14_final
2023-05-14 10:26:22	ga_ls8c_ard_3-2-1_101081_2023-05-14_final
2023-05-15 09:26:44	ga_ls8c_ard_3-2-1_092071_2023-05-14_final
2023-05-15 09:27:08	ga_ls8c_ard_3-2-1_092072_2023-05-14_final
2023-05-15 09:27:32	ga_ls8c_ard_3-2-1_092073_2023-05-14_final
2023-05-15 09:27:56	ga_ls8c_ard_3-2-1_092074_2023-05-14_final
2023-05-15 09:28:20	ga_ls8c_ard_3-2-1_092075_2023-05-14_final
2023-05-15 09:28:44	ga_ls8c_ard_3-2-1_092076_2023-05-14_final
2023-05-15 09:29:08	ga_ls8c_ard_3-2-1_092077_2023-05-14_final
2023-05-15 09:29:32	ga_ls8c_ard_3-2-1_092078_2023-05-14_final
2023-05-15 09:29:56	ga_ls8c_ard_3-2-1_092079_2023-05-14_final
2023-05-15 09:30:20	ga_ls8c_ard_3-2-1_092080_2023-05-15_final
2023-05-15 09:30:44	ga_ls8c_ard_3-2-1_092081_2023-05-15_final
2023-05-15 09:31:08	ga_ls8c_ard_3-2-1_092082_2023-05-15_final
2023-05-15 09:31:32	ga_ls8c_ard_3-2-1_092083_2023-05-15_final
2023-05-15 09:31:56	ga_ls8c_ard_3-2-1_092084_2023-05-15_final
2023-05-15 09:32:20	ga_ls8c_ard_3-2-1_092085_2023-05-15_final
2023-05-15 09:32:44	ga_ls8c_ard_3-2-1_092086_2023-05-15_final
2023-05-15 09:33:07	ga_ls8c_ard_3-2-1_092087_2023-05-15_final
2023-05-15 09:33:31	ga_ls8c_ard_3-2-1_092088_2023-05-15_final
2023-05-15 09:33:55	ga_ls8c_ard_3-2-1_092089_2023-05-15_final
2023-05-15 09:34:19	ga_ls8c_ard_3-2-1_092090_2023-05-15_final
2023-05-15 11:04:49	ga_ls8c_ard_3-2-1_108069_2023-05-15_final
2023-05-15 11:05:13	ga_ls8c_ard_3-2-1_108070_2023-05-15_final
2023-05-15 11:05:37	ga_ls8c_ard_3-2-1_108071_2023-05-15_final
2023-05-15 11:06:01	ga_ls8c_ard_3-2-1_108072_2023-05-15_final
2023-05-15 11:06:25	ga_ls8c_ard_3-2-1_108073_2023-05-15_final
2023-05-15 11:06:49	ga_ls8c_ard_3-2-1_108074_2023-05-15_final
2023-05-15 11:07:13	ga_ls8c_ard_3-2-1_108075_2023-05-15_final
2023-05-15 11:07:37	ga_ls8c_ard_3-2-1_108076_2023-05-15_final
2023-05-15 11:08:01	ga_ls8c_ard_3-2-1_108077_2023-05-15_final
2023-05-15 11:08:25	ga_ls8c_ard_3-2-1_108078_2023-05-15_final
2023-05-15 11:08:49	ga_ls8c_ard_3-2-1_108079_2023-05-15_final
2023-05-15 11:09:13	ga_ls8c_ard_3-2-1_108080_2023-05-15_final
2023-05-15 11:09:37	ga_ls8c_ard_3-2-1_108081_2023-05-15_final
2023-05-15 11:10:01	ga_ls8c_ard_3-2-1_108082_2023-05-15_final
2023-05-15 11:10:25	ga_ls8c_ard_3-2-1_108083_2023-05-15_final
2023-05-15 11:10:49	ga_ls8c_ard_3-2-1_108084_2023-05-15_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