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

71 results

Time (local)	Label
2023-12-14 11:24:16	ga_ls8c_ard_3-2-1_111069_2023-12-14_final
2023-12-14 11:27:04	ga_ls8c_ard_3-2-1_111076_2023-12-14_final
2023-12-14 11:27:52	ga_ls8c_ard_3-2-1_111078_2023-12-14_final
2023-12-14 11:28:16	ga_ls8c_ard_3-2-1_111079_2023-12-14_final
2023-12-14 11:30:15	ga_ls8c_ard_3-2-1_111084_2023-12-14_final
2023-12-16 09:34:38	ga_ls8c_ard_3-2-1_093073_2023-12-16_final
2023-12-16 09:37:02	ga_ls8c_ard_3-2-1_093079_2023-12-16_final
2023-12-16 09:38:38	ga_ls8c_ard_3-2-1_093083_2023-12-16_final
2023-12-16 11:13:07	ga_ls8c_ard_3-2-1_109072_2023-12-16_final
2023-12-16 11:15:07	ga_ls8c_ard_3-2-1_109077_2023-12-16_final
2023-12-18 09:21:54	ga_ls8c_ard_3-2-1_091072_2023-12-17_final
2023-12-18 09:27:29	ga_ls8c_ard_3-2-1_091086_2023-12-17_final
2023-12-18 11:04:22	ga_ls8c_ard_3-2-1_107081_2023-12-18_final
2023-12-19 10:03:58	ga_ls8c_ard_3-2-1_098069_2023-12-19_final
2023-12-19 10:05:57	ga_ls8c_ard_3-2-1_098074_2023-12-19_final
2023-12-19 10:07:09	ga_ls8c_ard_3-2-1_098077_2023-12-19_final
2023-12-19 10:07:33	ga_ls8c_ard_3-2-1_098078_2023-12-19_final
2023-12-19 10:09:09	ga_ls8c_ard_3-2-1_098082_2023-12-19_final
2023-12-20 09:10:44	ga_ls8c_ard_3-2-1_089075_2023-12-19_final
2023-12-20 10:48:01	ga_ls8c_ard_3-2-1_105071_2023-12-20_final
2023-12-20 10:49:37	ga_ls8c_ard_3-2-1_105075_2023-12-20_final
2023-12-21 09:52:48	ga_ls8c_ard_3-2-1_096072_2023-12-21_final
2023-12-21 09:53:12	ga_ls8c_ard_3-2-1_096073_2023-12-21_final
2023-12-21 09:54:24	ga_ls8c_ard_3-2-1_096076_2023-12-21_final
2023-12-21 11:31:41	ga_ls8c_ard_3-2-1_112072_2023-12-21_final
2023-12-23 09:45:14	ga_ls8c_ard_3-2-1_094084_2023-12-23_final
2023-12-23 11:18:56	ga_ls8c_ard_3-2-1_110071_2023-12-23_final
2023-12-23 11:20:31	ga_ls8c_ard_3-2-1_110075_2023-12-23_final
2023-12-23 11:20:55	ga_ls8c_ard_3-2-1_110076_2023-12-23_final
2023-12-24 10:24:30	ga_ls8c_ard_3-2-1_101074_2023-12-24_final
2023-12-24 10:25:18	ga_ls8c_ard_3-2-1_101076_2023-12-24_final
2023-12-24 10:26:06	ga_ls8c_ard_3-2-1_101078_2023-12-24_final
2023-12-24 10:27:41	ga_ls8c_ard_3-2-1_101082_2023-12-24_final
2023-12-25 09:28:04	ga_ls8c_ard_3-2-1_092072_2023-12-24_final
2023-12-25 09:28:28	ga_ls8c_ard_3-2-1_092073_2023-12-24_final
2023-12-25 09:29:40	ga_ls8c_ard_3-2-1_092076_2023-12-24_final
2023-12-25 09:33:40	ga_ls8c_ard_3-2-1_092086_2023-12-25_final
2023-12-25 09:34:03	ga_ls8c_ard_3-2-1_092087_2023-12-25_final
2023-12-25 09:34:51	ga_ls8c_ard_3-2-1_092089_2023-12-25_final
2023-12-25 11:06:57	ga_ls8c_ard_3-2-1_108072_2023-12-25_final
2023-12-25 11:07:45	ga_ls8c_ard_3-2-1_108074_2023-12-25_final
2023-12-25 11:08:33	ga_ls8c_ard_3-2-1_108076_2023-12-25_final
2023-12-25 11:10:09	ga_ls8c_ard_3-2-1_108080_2023-12-25_final
2023-12-25 11:10:57	ga_ls8c_ard_3-2-1_108082_2023-12-25_final
2023-12-25 11:11:45	ga_ls8c_ard_3-2-1_108084_2023-12-25_final
2023-12-26 10:09:20	ga_ls8c_ard_3-2-1_099067_2023-12-26_final
2023-12-26 10:10:32	ga_ls8c_ard_3-2-1_099070_2023-12-26_final
2023-12-26 10:12:07	ga_ls8c_ard_3-2-1_099074_2023-12-26_final
2023-12-26 10:12:31	ga_ls8c_ard_3-2-1_099075_2023-12-26_final
2023-12-26 10:13:43	ga_ls8c_ard_3-2-1_099078_2023-12-26_final
2023-12-26 10:14:31	ga_ls8c_ard_3-2-1_099080_2023-12-26_final
2023-12-26 10:16:31	ga_ls8c_ard_3-2-1_099085_2023-12-26_final
2023-12-26 11:51:48	ga_ls8c_ard_3-2-1_115076_2023-12-26_final
2023-12-26 11:52:36	ga_ls8c_ard_3-2-1_115078_2023-12-26_final
2023-12-26 11:53:00	ga_ls8c_ard_3-2-1_115079_2023-12-26_final
2023-12-26 11:53:24	ga_ls8c_ard_3-2-1_115080_2023-12-26_final
2023-12-27 09:16:30	ga_ls8c_ard_3-2-1_090074_2023-12-26_final
2023-12-27 09:18:05	ga_ls8c_ard_3-2-1_090078_2023-12-26_final
2023-12-27 09:18:53	ga_ls8c_ard_3-2-1_090080_2023-12-26_final
2023-12-27 09:21:17	ga_ls8c_ard_3-2-1_090086_2023-12-26_final
2023-12-27 09:21:41	ga_ls8c_ard_3-2-1_090087_2023-12-26_final
2023-12-27 09:22:29	ga_ls8c_ard_3-2-1_090089_2023-12-26_final
2023-12-27 09:22:53	ga_ls8c_ard_3-2-1_090090_2023-12-26_final
2023-12-27 10:52:59	ga_ls8c_ard_3-2-1_106068_2023-12-27_final
2023-12-27 10:53:23	ga_ls8c_ard_3-2-1_106069_2023-12-27_final
2023-12-27 10:54:59	ga_ls8c_ard_3-2-1_106073_2023-12-27_final
2023-12-27 10:55:23	ga_ls8c_ard_3-2-1_106074_2023-12-27_final
2023-12-27 10:55:47	ga_ls8c_ard_3-2-1_106075_2023-12-27_final
2023-12-27 10:56:58	ga_ls8c_ard_3-2-1_106078_2023-12-27_final
2023-12-27 10:57:46	ga_ls8c_ard_3-2-1_106080_2023-12-27_final
2023-12-27 10:58:34	ga_ls8c_ard_3-2-1_106082_2023-12-27_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

Land and vegetation

Inland water

Sea, ocean and coast

Hazards

Other products

All years